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Sample records for chemometric analysis discriminacao

  1. Chemometric Analysis of Nuclear Magnetic Resonance Spectroscopy Data

    Energy Technology Data Exchange (ETDEWEB)

    ALAM,TODD M.; ALAM,M. KATHLEEN

    2000-07-20

    Chemometric analysis of nuclear magnetic resonance (NMR) spectroscopy has increased dramatically in recent years. A variety of different chemometric techniques have been applied to a wide range of problems in food, agricultural, medical, process and industrial systems. This article gives a brief review of chemometric analysis of NMR spectral data, including a summary of the types of mixtures and experiments analyzed with chemometric techniques. Common experimental problems encountered during the chemometric analysis of NMR data are also discussed.

  2. Chemometrics.

    Science.gov (United States)

    Kowalski, Bruce R.

    1980-01-01

    Outlines recent advances in the development of the field of chemometrics, defined as the application of mathematical and statistical methods to chemical measurements. Emphasizes applications in the field. Cites 288 references. (CS)

  3. Functional Data Analysis Applied in Chemometrics

    DEFF Research Database (Denmark)

    Muller, Martha

    In this thesis we explore the use of functional data analysis as a method to analyse chemometric data, more specically spectral data in metabolomics. Functional data analysis is a vibrant eld in statistics. It has been rapidly expanding in both methodology and applications since it was made well...... nutritional status and metabolic phenotype. We want to understand how metabolomic spectra can be analysed using functional data analysis to detect the in uence of dierent factors on specic metabolites. These factors can include, for example, gender, diet culture or dietary intervention. In Paper I we apply...... of functional condence intervals for mean curves. We also discuss the many practical considerations in wavelet estimation and thresholding, and the important in uence the choices can have on the resulting estimates. On a conceptual level, the purpose of this thesis is to build a stronger connection between...

  4. Principal Component Analysis: Most Favourite Tool in Chemometrics

    Indian Academy of Sciences (India)

    Abstract. Principal component analysis (PCA) is the most commonlyused chemometric technique. It is an unsupervised patternrecognition technique. PCA has found applications in chemistry,biology, medicine and economics. The present work attemptsto understand how PCA work and how can we interpretits results.

  5. Chemometric analysis of metal contents in different types of chocolates

    Directory of Open Access Journals (Sweden)

    Jevrić Lidija R.

    2014-01-01

    Full Text Available The relationships between the contents of various metals (Cu, Ni, Pb and Al in 38 different milk chocolate samples were studied using a chemometric approach. The chemometric expressions were generated using a training set of 25 chocolate samples and the predictive ability of the resulting models was evaluated against a test set of 13 chocolate samples. The chemometric analysis was based on the application of multiple linear regression analysis (MLR. MLR was performed in order to select the significant models for predicting the metal contents. The MLR equations that represent the content of one metal as a function of the contents of other metals were established. High agreement between experimental and predicted values, obtained in the validation procedure, indicated the good quality of the models. It enables the researchers to establish reliable relationships between the contents of various metals which can be used for their prediction in different types of chocolate prior to their analysis. This can reduce the trial-and-error element and experimental costs in the production.[Projekat Ministarstva nauke Republike Srbije, br. 31055, br. 172012 i br. 172014

  6. Chemometrics in analytical chemistry-part I: history, experimental design and data analysis tools.

    Science.gov (United States)

    Brereton, Richard G; Jansen, Jeroen; Lopes, João; Marini, Federico; Pomerantsev, Alexey; Rodionova, Oxana; Roger, Jean Michel; Walczak, Beata; Tauler, Romà

    2017-10-01

    Chemometrics has achieved major recognition and progress in the analytical chemistry field. In the first part of this tutorial, major achievements and contributions of chemometrics to some of the more important stages of the analytical process, like experimental design, sampling, and data analysis (including data pretreatment and fusion), are summarised. The tutorial is intended to give a general updated overview of the chemometrics field to further contribute to its dissemination and promotion in analytical chemistry.

  7. Chemometric analysis of ecological toxicants in petrochemical and industrial environments.

    Science.gov (United States)

    Olawoyin, Richard; Heidrich, Brenden; Oyewole, Samuel; Okareh, Oladapo T; McGlothlin, Charles W

    2014-10-01

    The application of chemometrics in the assessment of toxicants, such as heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs) potentially derived from petrochemical activities in the microenvironment, is vital in providing safeguards for human health of children and adults residing around petrochemical industrial regions. Several multivariate statistical methods are used in geosciences and environmental protection studies to classify, identify and group prevalent pollutants with regard to exhibited trends. Chemometrics can be applied for toxicant source identification, estimation of contaminants contributions to the toxicity of sites of interest, the assessment of the integral risk index of an area and provision of mitigating measures that limit or eliminate the contaminants identified. In this study, the principal component analysis (PCA) was used for dimensionality reduction of both organic and inorganic substances data in the environment, which are potentially hazardous. The high molecular weight (HMW) PAHs correlated positively with stronger impact on the model than the lower molecular weight (LMW) PAHs, the total petroleum hydrocarbons (TPHs), PAHs and BTEX correlate positively in the F1 vs F2 plot indicating similar source contributions of these pollutants in the environmental material. Cu, Cr, Cd, Fe, Zn and Pb all show positive correlation in the same space indicating similar source of contamination. Analytical processes involving environmental assessment data obtained in the Niger Delta area of Nigeria, confirmed the usefulness of chemometrics for comprehensive ecological evaluation. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. Functional Data Analysis Applied in Chemometrics

    DEFF Research Database (Denmark)

    Muller, Martha

    studies the `unique chemical ngerprints' (Daviss, 2005) that cellular processes create in living systems. Metabolomics is used to study the in uence of nutrition on the human metabolome. Nutritional metabolomics shows great potential for the discovery of novel biomarkers of food consumption, personal...... nutritional status and metabolic phenotype. We want to understand how metabolomic spectra can be analysed using functional data analysis to detect the in uence of dierent factors on specic metabolites. These factors can include, for example, gender, diet culture or dietary intervention. In Paper I we apply...... care, including personalised nutrition for prevention and treatment....

  9. IMMAN: free software for information theory-based chemometric analysis.

    Science.gov (United States)

    Urias, Ricardo W Pino; Barigye, Stephen J; Marrero-Ponce, Yovani; García-Jacas, César R; Valdes-Martiní, José R; Perez-Gimenez, Facundo

    2015-05-01

    The features and theoretical background of a new and free computational program for chemometric analysis denominated IMMAN (acronym for Information theory-based CheMoMetrics ANalysis) are presented. This is multi-platform software developed in the Java programming language, designed with a remarkably user-friendly graphical interface for the computation of a collection of information-theoretic functions adapted for rank-based unsupervised and supervised feature selection tasks. A total of 20 feature selection parameters are presented, with the unsupervised and supervised frameworks represented by 10 approaches in each case. Several information-theoretic parameters traditionally used as molecular descriptors (MDs) are adapted for use as unsupervised rank-based feature selection methods. On the other hand, a generalization scheme for the previously defined differential Shannon's entropy is discussed, as well as the introduction of Jeffreys information measure for supervised feature selection. Moreover, well-known information-theoretic feature selection parameters, such as information gain, gain ratio, and symmetrical uncertainty are incorporated to the IMMAN software ( http://mobiosd-hub.com/imman-soft/ ), following an equal-interval discretization approach. IMMAN offers data pre-processing functionalities, such as missing values processing, dataset partitioning, and browsing. Moreover, single parameter or ensemble (multi-criteria) ranking options are provided. Consequently, this software is suitable for tasks like dimensionality reduction, feature ranking, as well as comparative diversity analysis of data matrices. Simple examples of applications performed with this program are presented. A comparative study between IMMAN and WEKA feature selection tools using the Arcene dataset was performed, demonstrating similar behavior. In addition, it is revealed that the use of IMMAN unsupervised feature selection methods improves the performance of both IMMAN and WEKA

  10. Computer Series, 43: Chemometrics in the Chemistry Curriculum.

    Science.gov (United States)

    Howery, Darryl G.; Hirsch, Roland F.

    1983-01-01

    Discusses chemometrics (analysis of data from chemical measurements), tracing developments in this area and summarizing reasons for teaching chemometrics. Includes highlights of presentations given at a symposium (Interpreting Complex Chemical Data: Teaching Chemometrics) and brief descriptions of chemometric methods. (JN)

  11. Chemometric analysis of proteolysis during ripening of Ragusano cheese.

    Science.gov (United States)

    Fallico, V; McSweeney, P L H; Siebert, K J; Horne, J; Carpino, S; Licitra, G

    2004-10-01

    Chemometric modeling of peptide and free amino acid data was used to study proteolysis in Protected Denomination of Origin Ragusano cheese. Twelve cheeses ripened 3 to 7 mo were selected from local farmers and were analyzed in 4 layers: rind, external, middle, and internal. Proteolysis was significantly affected by cheese layer and age. Significant increases in nitrogen soluble in pH 4.6 acetate buffer and 12% trichloroacetic acid were found from rind to core and throughout ripening. Patterns of proteolysis by urea-PAGE showed that rind-to-core and age-related gradients of moisture and salt contents influenced coagulant and plasmin activities, as reflected in varying rates of hydrolysis of the caseins. Analysis of significant intercorrelations among chemical parameters revealed that moisture, more than salt content, had the largest single influence on rates of proteolysis. Lower levels of 70% ethanol-insoluble peptides coupled to higher levels of 70% ethanol-soluble peptides were found by reversed phase-HPLC in the innermost cheese layers and as the cheeses aged. Non-significant increases of individual free amino acids were found with cheese age and layer. Total free amino acids ranged from 14.3 mg/g (6.2% of total protein) at 3 mo to 22.0 mg/g (8.4% of total protein) after 7 mo. Glutamic acid had the largest concentration in all samples at each time and, jointly with lysine and leucine, accounted for 48% of total free amino acids. Principal components analysis and hierarchical cluster analysis of the data from reversed phase-HPLC chromatograms and free amino acids analysis showed that the peptide profiles were more useful in differentiating Ragusano cheese by age and farm origin than the amino acid data. Combining free amino acid and peptide data resulted in the best partial least squares regression model (R(2) = 0.976; Q(2) = 0.952) predicting cheese age, even though the peptide data alone led to a similarly precise prediction (R(2) = 0.961; Q(2) = 0.923). The

  12. Chemometrics in spectroscopy

    International Nuclear Information System (INIS)

    Geladi, Paul; Sethson, Britta; Nystroem, Josefina; Lillhonga, Tom; Lestander, Torbjoern; Burger, Jim

    2004-01-01

    Some of the principles and main methods of chemometrics are illustrated by examples. The examples are from electrochemistry, process analytical chemistry and multivariate imaging. Principal component analysis, partial least squares regression and multivariate image analysis are used to illustrate the power of chemometrical thinking. The emphasis is on plotting and visualization for showing the salient features of a model or data set

  13. New insights in forensic chemistry: NIR/Chemometrics analysis of toners for questioned documents examination.

    Science.gov (United States)

    Materazzi, Stefano; Risoluti, Roberta; Pinci, Sara; Saverio Romolo, Francesco

    2017-11-01

    Near-Infrared spectroscopy (NIRs) coupled to chemometrics was investigated for the first time as a new tool for the analysis of black toners to evaluate its application in forensic cases. Ten black toners from four manufacturers were included in this study and the acquired spectra were compared in order to differentiate toners. Multivariate statistical analysis based on Principal Component Analysis (PCA) was considered to develop a model of comparison of toners in questioned documents. Results demonstrated the capabilities of the approach NIR/Chemometrics to correctly identify toners when printed on different papers and to be not affected by the printing process. This study has shown that NIRs can be considered as a useful, fast, non-destructive tool providing the characterisation of toners in forensic caseworks. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Analysis of Flavonoid in Medicinal Plant Extract Using Infrared Spectroscopy and Chemometrics

    Directory of Open Access Journals (Sweden)

    Lestyo Wulandari

    2016-01-01

    Full Text Available Infrared (IR spectroscopy combined with chemometrics has been developed for simple analysis of flavonoid in the medicinal plant extract. Flavonoid was extracted from medicinal plant leaves by ultrasonication and maceration. IR spectra of selected medicinal plant extract were correlated with flavonoid content using chemometrics. The chemometric method used for calibration analysis was Partial Last Square (PLS and the methods used for classification analysis were Linear Discriminant Analysis (LDA, Soft Independent Modelling of Class Analogies (SIMCA, and Support Vector Machines (SVM. In this study, the calibration of NIR model that showed best calibration with R2 and RMSEC value was 0.9916499 and 2.1521897, respectively, while the accuracy of all classification models (LDA, SIMCA, and SVM was 100%. R2 and RMSEC of calibration of FTIR model were 0.8653689 and 8.8958149, respectively, while the accuracy of LDA, SIMCA, and SVM was 86.0%, 91.2%, and 77.3%, respectively. PLS and LDA of NIR models were further used to predict unknown flavonoid content in commercial samples. Using these models, the significance of flavonoid content that has been measured by NIR and UV-Vis spectrophotometry was evaluated with paired samples t-test. The flavonoid content that has been measured with both methods gave no significant difference.

  15. GC/MS Analysis of Pesticides in the Ferrara Area (Italy) Surface Water: A Chemometric Study

    International Nuclear Information System (INIS)

    Pasti, L.; Dondi, F.; Nava, E.; Morelli, M.; Bignami, S.

    2007-01-01

    The development of a network to monitor surface waters is a critical element in the assessment, restoration and protection of water quality. In this study, concentrations of 42 pesticides - determined by GC-MS on samples from 11 points along the Ferrara area rivers - have been analyzed by chemometric tools. The data were collected over a three-year period (2002-2004). Principal component analysis of the detected pesticides was carried out in order to define the best spatial locations for the sampling points. The results obtained have been interpreted in view of agricultural land use. Time series data regarding pesticide contents in surface waters has been analyzed using the Autocorrelation function. This chemometric tool allows for seasonal trends and makes it possible to optimize sampling frequency in order to detect the effective maximum pesticide content

  16. Chemometrics Methods for Specificity, Authenticity and Traceability Analysis of Olive Oils: Principles, Classifications and Applications.

    Science.gov (United States)

    Messai, Habib; Farman, Muhammad; Sarraj-Laabidi, Abir; Hammami-Semmar, Asma; Semmar, Nabil

    2016-11-17

    Olive oils (OOs) show high chemical variability due to several factors of genetic, environmental and anthropic types. Genetic and environmental factors are responsible for natural compositions and polymorphic diversification resulting in different varietal patterns and phenotypes. Anthropic factors, however, are at the origin of different blends' preparation leading to normative, labelled or adulterated commercial products. Control of complex OO samples requires their (i) characterization by specific markers; (ii) authentication by fingerprint patterns; and (iii) monitoring by traceability analysis. These quality control and management aims require the use of several multivariate statistical tools: specificity highlighting requires ordination methods; authentication checking calls for classification and pattern recognition methods; traceability analysis implies the use of network-based approaches able to separate or extract mixed information and memorized signals from complex matrices. This chapter presents a review of different chemometrics methods applied for the control of OO variability from metabolic and physical-chemical measured characteristics. The different chemometrics methods are illustrated by different study cases on monovarietal and blended OO originated from different countries. Chemometrics tools offer multiple ways for quantitative evaluations and qualitative control of complex chemical variability of OO in relation to several intrinsic and extrinsic factors.

  17. Chemometrics Methods for Specificity, Authenticity and Traceability Analysis of Olive Oils: Principles, Classifications and Applications

    Directory of Open Access Journals (Sweden)

    Habib Messai

    2016-11-01

    Full Text Available Background. Olive oils (OOs show high chemical variability due to several factors of genetic, environmental and anthropic types. Genetic and environmental factors are responsible for natural compositions and polymorphic diversification resulting in different varietal patterns and phenotypes. Anthropic factors, however, are at the origin of different blends’ preparation leading to normative, labelled or adulterated commercial products. Control of complex OO samples requires their (i characterization by specific markers; (ii authentication by fingerprint patterns; and (iii monitoring by traceability analysis. Methods. These quality control and management aims require the use of several multivariate statistical tools: specificity highlighting requires ordination methods; authentication checking calls for classification and pattern recognition methods; traceability analysis implies the use of network-based approaches able to separate or extract mixed information and memorized signals from complex matrices. Results. This chapter presents a review of different chemometrics methods applied for the control of OO variability from metabolic and physical-chemical measured characteristics. The different chemometrics methods are illustrated by different study cases on monovarietal and blended OO originated from different countries. Conclusion. Chemometrics tools offer multiple ways for quantitative evaluations and qualitative control of complex chemical variability of OO in relation to several intrinsic and extrinsic factors.

  18. Analysis of the essential oils of Coriandrum sativum Using GC-MS coupled with chemometric resolution methods.

    Science.gov (United States)

    Zhou, Zhi-Feng; Chen, Ling-Yun; Shen, Mei; Ma, An-De; Yang, Xue-Mei; Zou, Fei

    2011-01-01

    The essential oils extracted from Coriandrum sativum L. were analyzed by GC-MS coupled with chemometric resolution methods. Through the chemometric resolution methods, peak clusters were uniquely resolved into the pure chromatographic profiles and mass spectra of each component. Qualitative analysis was performed by comparing the pure mass spectra with those in the NIST 05 mass spectral library. Quantitative analysis was performed using the total volume integration method. A total of 118 constituents were detected, of which 104 were identified, accounting for 97.27% of the total content. The results indicate that GC-MS combined with chemometric resolution methods can greatly enhance the capability of separation and the reliability of qualitative and quantitative results. The combined method is an economical and accurate approach for the rapid analysis of the complex essential oil samples in Coriandrum sativum L.

  19. Differentiating Milk and Non-milk Proteins by UPLC Amino Acid Fingerprints Combined with Chemometric Data Analysis Techniques.

    Science.gov (United States)

    Lu, Weiying; Lv, Xiaxia; Gao, Boyan; Shi, Haiming; Yu, Liangli Lucy

    2015-04-22

    Amino acid fingerprinting combined with chemometric data analysis was used to differentiate milk and non-milk proteins in this study. Microwave-assisted hydrolysis and ultraperformance liquid chromatography (UPLC) were used to obtain the amino acid fingerprints. Both univariate and multivariate chemometrics methods were applied for differentiation. The confidence boundary of amino acid concentration, principal component analysis (PCA), and partial least-squares-discriminant analysis (PLS-DA) of the amino acid fingerprints demonstrated that there were significant differences between milk proteins and inexpensive non-milk protein powders from other biological sources including whey, peanut, corn, soy, fish, egg yolk, beef extract, collagen, and cattle bone. The results indicate that the amino acid compositions with the chemometric techniques could be applied for the detection of potential protein adulterants in milk.

  20. Chemometric analysis for discrimination of extra virgin olive oils from whole and stoned olive pastes.

    Science.gov (United States)

    De Luca, Michele; Restuccia, Donatella; Clodoveo, Maria Lisa; Puoci, Francesco; Ragno, Gaetano

    2016-07-01

    Chemometric discrimination of extra virgin olive oils (EVOO) from whole and stoned olive pastes was carried out by using Fourier transform infrared (FTIR) data and partial least squares-discriminant analysis (PLS1-DA) approach. Four Italian commercial EVOO brands, all in both whole and stoned version, were considered in this study. The adopted chemometric methodologies were able to describe the different chemical features in phenolic and volatile compounds contained in the two types of oil by using unspecific IR spectral information. Principal component analysis (PCA) was employed in cluster analysis to capture data patterns and to highlight differences between technological processes and EVOO brands. The PLS1-DA algorithm was used as supervised discriminant analysis to identify the different oil extraction procedures. Discriminant analysis was extended to the evaluation of possible adulteration by addition of aliquots of oil from whole paste to the most valuable oil from stoned olives. The statistical parameters from external validation of all the PLS models were very satisfactory, with low root mean square error of prediction (RMSEP) and relative error (RE%). Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Activated sludge characterization through microscopy: A review on quantitative image analysis and chemometric techniques

    Energy Technology Data Exchange (ETDEWEB)

    Mesquita, Daniela P. [IBB-Institute for Biotechnology and Bioengineering, Centre of Biological Engineering, Universidade do Minho, Campus de Gualtar, 4710-057 Braga (Portugal); Amaral, A. Luís [IBB-Institute for Biotechnology and Bioengineering, Centre of Biological Engineering, Universidade do Minho, Campus de Gualtar, 4710-057 Braga (Portugal); Instituto Politécnico de Coimbra, ISEC, DEQB, Rua Pedro Nunes, Quinta da Nora, 3030-199 Coimbra (Portugal); Ferreira, Eugénio C., E-mail: ecferreira@deb.uminho.pt [IBB-Institute for Biotechnology and Bioengineering, Centre of Biological Engineering, Universidade do Minho, Campus de Gualtar, 4710-057 Braga (Portugal)

    2013-11-13

    Graphical abstract: -- Highlights: •Quantitative image analysis shows potential to monitor activated sludge systems. •Staining techniques increase the potential for detection of operational problems. •Chemometrics combined with quantitative image analysis is valuable for process monitoring. -- Abstract: In wastewater treatment processes, and particularly in activated sludge systems, efficiency is quite dependent on the operating conditions, and a number of problems may arise due to sludge structure and proliferation of specific microorganisms. In fact, bacterial communities and protozoa identification by microscopy inspection is already routinely employed in a considerable number of cases. Furthermore, quantitative image analysis techniques have been increasingly used throughout the years for the assessment of aggregates and filamentous bacteria properties. These procedures are able to provide an ever growing amount of data for wastewater treatment processes in which chemometric techniques can be a valuable tool. However, the determination of microbial communities’ properties remains a current challenge in spite of the great diversity of microscopy techniques applied. In this review, activated sludge characterization is discussed highlighting the aggregates structure and filamentous bacteria determination by image analysis on bright-field, phase-contrast, and fluorescence microscopy. An in-depth analysis is performed to summarize the many new findings that have been obtained, and future developments for these biological processes are further discussed.

  2. Chemical comparison of Tripterygium wilfordii and Tripterygium hypoglaucum based on quantitative analysis and chemometrics methods.

    Science.gov (United States)

    Guo, Long; Duan, Li; Liu, Ke; Liu, E-Hu; Li, Ping

    2014-07-01

    Tripterygium wilfordii (T. wilfordii) and Tripterygium hypoglaucum (T. hypoglaucum), two commonly used Chinese herbal medicines derived from Tripterygium genus, have been widely used for the treatment of rheumatoid arthritis and other related inflammatory diseases in clinical therapy. In the present study, a rapid resolution liquid chromatography/electrospray ionization tandem mass spectrometry (RRLC-ESI-MS(n)) method has been developed and validated for simultaneous determination of 19 bioactive compounds including four catechins, three sesquiterpene alkaloids, four diterpenoids, and eight triterpenoids in these two similar herbs. The method validation results indicated that the developed method had desirable specificity, linearity, precision and accuracy. Quantitative analysis results showed that there were significant differences in the content of different types of compounds in T. wilfordii and T. hypoglaucum. Moreover, chemometrics methods such as one-way ANOVA, principal component analysis (PCA) and hierarchical clustering analysis (HCA) were performed to compare and discriminate the two Tripterygium herbs based on the quantitative data of analytes, and it was proven straightforward and reliable to differentiate T. wilfordii and T. hypoglaucum samples from different origins. In conclusion, simultaneous quantification of multiple-active component by RRLC-ESI-MS(n) coupled with chemometrics analysis could be a well-acceptable strategy to compare and evaluate the quality of T. wilfordii and T. hypoglaucum. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. Suitable classification of mortars from ancient Roman and Renaissance frescoes using thermal analysis and chemometrics.

    Science.gov (United States)

    Tomassetti, Mauro; Marini, Federico; Campanella, Luigi; Positano, Matteo; Marinucci, Francesco

    2015-01-01

    Literature on mortars has mainly focused on the identification and characterization of their components in order to assign them to a specific historical period, after accurate classification. For this purpose, different analytical techniques have been proposed. Aim of the present study was to verify whether the combination of thermal analysis and chemometric methods could be used to obtain a fast but correct classification of ancient mortar samples of different ages (Roman era and Renaissance). Ancient Roman frescoes from Museo Nazionale Romano (Terme di Diocleziano, Rome, Italy) and Renaissance frescoes from Sistine Chapel and Old Vatican Rooms (Vatican City) were analyzed by thermogravimetry (TG) and differential thermal analysis (DTA). Principal Component analysis (PCA) on the main thermal data evidenced the presence of two clusters, ascribable to the two different ages. Inspection of the loadings allowed to interpret the observed differences in terms of the experimental variables. PCA allowed differentiating the two kinds of mortars (Roman and Renaissance frescoes), and evidenced how the ancient Roman samples are richer in binder (calcium carbonate) and contain less filler (aggregate) than the Renaissance ones. It was also demonstrated how the coupling of thermoanalytical techniques and chemometric processing proves to be particularly advantageous when a rapid and correct differentiation and classification of cultural heritage samples of various kinds or ages has to be carried out. Graphical abstractPCA analysis of TG data allows differentiating mortar samples from different ages (Roman era and Renaissance).

  4. Chemometric brand differentiation of commercial spices using direct analysis in real time mass spectrometry.

    Science.gov (United States)

    Pavlovich, Matthew J; Dunn, Emily E; Hall, Adam B

    2016-05-15

    Commercial spices represent an emerging class of fuels for improvised explosives. Being able to classify such spices not only by type but also by brand would represent an important step in developing methods to analytically investigate these explosive compositions. Therefore, a combined ambient mass spectrometric/chemometric approach was developed to quickly and accurately classify commercial spices by brand. Direct analysis in real time mass spectrometry (DART-MS) was used to generate mass spectra for samples of black pepper, cayenne pepper, and turmeric, along with four different brands of cinnamon, all dissolved in methanol. Unsupervised learning techniques showed that the cinnamon samples clustered according to brand. Then, we used supervised machine learning algorithms to build chemometric models with a known training set and classified the brands of an unknown testing set of cinnamon samples. Ten independent runs of five-fold cross-validation showed that the training set error for the best-performing models (i.e., the linear discriminant and neural network models) was lower than 2%. The false-positive percentages for these models were 3% or lower, and the false-negative percentages were lower than 10%. In particular, the linear discriminant model perfectly classified the testing set with 0% error. Repeated iterations of training and testing gave similar results, demonstrating the reproducibility of these models. Chemometric models were able to classify the DART mass spectra of commercial cinnamon samples according to brand, with high specificity and low classification error. This method could easily be generalized to other classes of spices, and it could be applied to authenticating questioned commercial samples of spices or to examining evidence from improvised explosives. Copyright © 2016 John Wiley & Sons, Ltd.

  5. Analysis of lard in meatball broth using Fourier transform infrared spectroscopy and chemometrics.

    Science.gov (United States)

    Kurniawati, Endah; Rohman, Abdul; Triyana, Kuwat

    2014-01-01

    Meatball is one of the favorite foods in Indonesia. For the economic reason (due to the price difference), the substitution of beef meat with pork can occur. In this study, FTIR spectroscopy in combination with chemometrics of partial least square (PLS) and principal component analysis (PCA) was used for analysis of pork fat (lard) in meatball broth. Lard in meatball broth was quantitatively determined at wavenumber region of 1018-1284 cm(-1). The coefficient of determination (R(2)) and root mean square error of calibration (RMSEC) values obtained were 0.9975 and 1.34% (v/v), respectively. Furthermore, the classification of lard and beef fat in meatball broth as well as in commercial samples was performed at wavenumber region of 1200-1000 cm(-1). The results showed that FTIR spectroscopy coupled with chemometrics can be used for quantitative analysis and classification of lard in meatball broth for Halal verification studies. The developed method is simple in operation, rapid and not involving extensive sample preparation. © 2013.

  6. Analysis of laser printer and photocopier toners by spectral properties and chemometrics

    Science.gov (United States)

    Verma, Neha; Kumar, Raj; Sharma, Vishal

    2018-05-01

    The use of printers to generate falsified documents has become a common practice in today's world. The examination and identification of the printed matter in the suspected documents (civil or criminal cases) may provide important information about the authenticity of the document. In the present study, a total number of 100 black toner samples both from laser printers and photocopiers were examined using diffuse reflectance UV-Vis Spectroscopy. The present research is divided into two parts; visual discrimination and discrimination by using multivariate analysis. A comparison between qualitative and quantitative analysis showed that multivariate analysis (Principal component analysis) provides 99.59%pair-wise discriminating power for laser printer toners while 99.84% pair-wise discriminating power for photocopier toners. The overall results obtained confirm the applicability of UV-Vis spectroscopy and chemometrics, in the nondestructive analysis of toner printed documents while enhancing their evidential value for forensic applications.

  7. Differentiation and classification of bacteria using vancomycin functionalized silver nanorods array based surface-enhanced raman spectroscopy an chemometric analysis

    Science.gov (United States)

    The intrinsic surface-enhanced Raman scattering (SERS) was used for differentiating and classifying bacterial species with chemometric data analysis. Such differentiation has often been conducted with an insufficient sample population and strong interference from the food matrices. To address these ...

  8. Current role and future perspectives of multivariate (chemometric) methods in NMR spectroscopic analysis of pharmaceutical products.

    Science.gov (United States)

    Monakhova, Yulia B; Holzgrabe, Ulrike; Diehl, Bernd W K

    2018-01-05

    Nuclear magnetic resonance (NMR) is a fast and accurate analytical method. Associated with chemometrics, it gradually becomes more important tool for the pharmaceutical industry. In this review studies dealing with the applications of multivariate analysis to NMR spectroscopic profiles were grouped and discussed according to the analytical problem solved. The following topics were covered: authenticity of medicines according to variety, seasonal and geographical differences of herbal plants; quantitative prediction of pharmacologically relevant parameters; production and batches approval; investigation of drug structure modifications; site-specific natural isotope fractionation (SNIF-NMR) fingerprinting for origin and manufacturer tracking and others. Special focus was put on the heparin authenticity by using 1D and 2D NMR measurements. Finally, further research directions have been outlined. Our review has shown that chemometrics plays an important role for the quality control and authenticity of pharmaceutical products and its role will definitely increase in the future. The discussed approaches are recommended to be implemented during development and production process of pharmaceuticals or in quality control laboratories. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. HPLC Fingerprint Analysis Combined with Chemometrics for Authentication of Kaempferia galanga from Related Species

    Directory of Open Access Journals (Sweden)

    Cahya Septyanti

    2016-12-01

    Full Text Available Fingerprint analysis using high performance liquid chromatography (HPLC has been developed for authentication of Kaempferia galanga from related species, such as Kaempferia pandurata and K. rotunda. By comparing the fingerprint chromatograms of K. galanga, K. pandurata and K. rotunda, we could identify K. galanga samples and detect adulteration of K. galanga from K. pandurata and K. rotunda by using their marker peaks. We also combined HPLC fingerprint with chemometrics for discrimination the three species and also for authentication of K. galanga. All the three species and K. galanga adulterated with K. pandurata and K. rotunda were discriminated successfully by using principal component analysis (PCA and discriminant analysis (DA. This result indicates that HPLC fingerprint analysis in combination with PCA (PC1 = 30.06% and PC2 = 34.74% and DA (DF1 = 94.59% and DF2 = 3.32% could be used for authentication of K. galanga samples from the related species.

  10. Chemometric analysis of ESIMS and NMR data from Piper species

    International Nuclear Information System (INIS)

    Yamaguchi, Lydia F.; Freitas, Giovana C.; Yoshida, Nidia C.; Silva, Renata A.; Gaia, Anderson M.; Silva, Adalberto M.; Kato, Massuo J.; Emerenciano, Vicente de P.; Scotti, Marcus T.; Guimaraes, Elsie F.; Floh, Eny I.S.; Colombo, Carlos A.; Siqueira, Walter J.

    2011-01-01

    The metabolomic profiling based on the application of multivariate analysis (principal component analysis, PCA) of positive mode electrospray ionization mass spectrometric (ESIMS) and 1 H nuclear magnetic resonance (NMR) data of crude extracts highlighted some species characterized by lignans (P. solmsianum, P. truncatum and P. cernuum), neolignans (P. regnellii) and chromenes (P. gaudichaudianum). A specific analysis focusing on species having pendant and globular inflorescences (P. caldense, P. carniconnectivum, P. bowiei and P. permucronatum) or amides-producing species indicated higher potential of the methodology in determining similarities and establishing priorities for further phytochemical investigation. Such intraspecific analysis applied to analyzed seedling leaves of the P. solmsianum, P. regnellii and P. gaudichaudianum species revealed the production of dillapiole and apiole instead of lignans, neolignans or prenylated benzoic acid, produced by the adult leaves, respectively. In case of amides-producing species, a similar profile was observed regardless the developmental stage. (author)

  11. Chemometric analysis of ESIMS and NMR data from Piper species

    Energy Technology Data Exchange (ETDEWEB)

    Yamaguchi, Lydia F.; Freitas, Giovana C.; Yoshida, Nidia C.; Silva, Renata A.; Gaia, Anderson M.; Silva, Adalberto M.; Kato, Massuo J.; Emerenciano, Vicente de P., E-mail: majokato@iq.usp.br [Departamento de Quimica Fundamental, Instituto de Quimica, Universidade de Sao Paulo, SP (Brazil); Scotti, Marcus T. [Centro de Ciencias Aplicadas e Educacao (Campus IV), Universidade Federal da Paraiba, Rio Tinto, PB (Brazil); Guimaraes, Elsie F. [Instituto de Pesquisas Jardim Botanico do Rio de Janeiro, RJ (Brazil); Floh, Eny I.S. [Departamento de Botanica, Instituto de Biociencias, Sao Paulo, SP (Brazil); Colombo, Carlos A.; Siqueira, Walter J. [Centro de Genetica Biologia Molecular e Fitoquimica, Instituto Agronomico de Campinas, SP (Brazil)

    2011-09-15

    The metabolomic profiling based on the application of multivariate analysis (principal component analysis, PCA) of positive mode electrospray ionization mass spectrometric (ESIMS) and {sup 1}H nuclear magnetic resonance (NMR) data of crude extracts highlighted some species characterized by lignans (P. solmsianum, P. truncatum and P. cernuum), neolignans (P. regnellii) and chromenes (P. gaudichaudianum). A specific analysis focusing on species having pendant and globular inflorescences (P. caldense, P. carniconnectivum, P. bowiei and P. permucronatum) or amides-producing species indicated higher potential of the methodology in determining similarities and establishing priorities for further phytochemical investigation. Such intraspecific analysis applied to analyzed seedling leaves of the P. solmsianum, P. regnellii and P. gaudichaudianum species revealed the production of dillapiole and apiole instead of lignans, neolignans or prenylated benzoic acid, produced by the adult leaves, respectively. In case of amides-producing species, a similar profile was observed regardless the developmental stage. (author)

  12. Discrimination of red and white rice bran from Indonesia using HPLC fingerprint analysis combined with chemometrics.

    Science.gov (United States)

    Sabir, Aryani; Rafi, Mohamad; Darusman, Latifah K

    2017-04-15

    HPLC fingerprint analysis combined with chemometrics was developed to discriminate between the red and the white rice bran grown in Indonesia. The major component in rice bran is γ-oryzanol which consisted of 4 main compounds, namely cycloartenol ferulate, cyclobranol ferulate, campesterol ferulate and β-sitosterol ferulate. Separation of these four compounds along with other compounds was performed using C18 and methanol-acetonitrile with gradient elution system. By using these intensity variations, principal component and discriminant analysis were performed to discriminate the two samples. Discriminant analysis was successfully discriminated the red from the white rice bran with predictive ability of the model showed a satisfactory classification for the test samples. The results of this study indicated that the developed method was suitable as quality control method for rice bran in terms of identification and discrimination of the red and the white rice bran. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Principal Component Analysis: Most Favourite Tool in Chemometrics

    Indian Academy of Sciences (India)

    differentiate olive oils from non-olive vegetable oils. Moreover, manual analysis of such a large volume of data is laborious and time consuming, and may not provide any meaningful interpre-. Figure 4. Amount of vari- ance captured by different principal components (PCs). The plot indicates that first two PCs are sufficient to ...

  14. Chemometric Analysis for Pollution Source Assessment of Harbour Sediments in Arctic Locations

    DEFF Research Database (Denmark)

    Pedersen, Kristine B.; Lejon, Tore; Jensen, Pernille Erland

    2015-01-01

    Pollution levels, pollutant distribution and potential source assessments based on multivariate analysis (chemometrics) were made for harbour sediments from two Arctic locations; Hammerfest in Norway and Sisimiut in Greenland. High levels of heavy metals were detected in addition to organic...... pollutants. Preliminary assessments based on principal component analysis (PCA) revealed different sources and pollutant distribution in the sediments of the two harbours. Tributyltin (TBT) was, however, found to originate from point source(s), and the highest concentrations of TBT in both harbours were...... indicated relation primarily to German, Russian and American mixtures in Hammerfest; and American, Russian and Japanese mixtures in Sisimiut. PCA was shown to be an important tool for identifying pollutant sources and differences in pollutant composition in relation to sediment characteristics....

  15. Thermogravimetric analysis coupled with chemometrics as a powerful predictive tool for ß-thalassemia screening.

    Science.gov (United States)

    Risoluti, Roberta; Materazzi, Stefano; Sorrentino, Francesco; Maffei, Laura; Caprari, Patrizia

    2016-10-01

    β-Thalassemia is a hemoglobin genetic disorder characterized by the absence or reduced β-globin chain synthesis, one of the constituents of the adult hemoglobin tetramer. In this study the possibility of using thermogravimetric analysis (TGA) followed by chemometrics as a new approach for β-thalassemia detection is proposed. Blood samples from patients with β-thalassemia were analyzed by the TG7 thermobalance and the resulting curves were compared to those typical of healthy individuals. Principal Component Analysis (PCA) was used to evaluate the correlation between the hematological parameters and the thermogravimetric results. The thermogravimetric profiles of blood samples from β-thalassemia patients were clearly distinct from those of healthy individuals as result of the different quantities of water content and corpuscular fraction. The hematological overview showed significant decreases in the values of red blood cell indices and an increase in red cell distribution width value in thalassemia subjects when compared with those of healthy subjects. The implementation of a predictive model based on Partial Least Square Discriminant Analysis (PLS-DA) for β-thalassemia diagnosis, was performed and validated. This model permitted the discrimination of anemic patients and healthy individuals and was able to detect thalassemia in clinically heterogeneous patients as in the presence of δβ-thalassemia and β-thalassemia combined with Hb Lepore. TGA and Chemometrics are capable of predicting ß-thalassemia syndromes using only a few microliters of blood without any pretreatment and with an hour of analysis time. A fast, rapid and cost-effective diagnostic tool for the β-thalassemia screening is proposed. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Chemometric analysis of minerals and trace elements in Sicilian wines from two different grape cultivars.

    Science.gov (United States)

    Potortί, Angela Giorgia; Lo Turco, Vincenzo; Saitta, Marcello; Bua, Giuseppe Daniel; Tropea, Alessia; Dugo, Giacomo; Di Bella, Giuseppa

    2017-05-01

    Chemometric analysis are used for food authenticity evaluation, correlating botanical and geographical origins with food chemical composition. This research was carried out in order to prove that it is possible linked red wines to Nero d'Avola and Syrah cultivars of Vitis vinifera according to their mineral content, while the values of the physical and chemical parameters do not affect relevantly this discrimination. The levels of mineral elements were determined by ICP-OES and ICP-MS. Samples from cv Nero d'Avola had the highest content of Zn, Cr, Ni, As and Cd, whereas the highest mineral concentration in cv Syrah samples was represented by K, Mg, Cu, and Sb. The research highlights that it is possible linked red wines to Nero d'Avola and Syrah cultivars of V. vinifera according to their mineral contents, adding knowledge to the determination studies of the wine botanical origin.

  17. [Study on rapid determination and analysis of rocket kerosene by near infrared spectrum and chemometrics].

    Science.gov (United States)

    Xia, Ben-Li; Cong, Ji-Xin; Li, Xia; Wang, Xuan-Jun

    2011-06-01

    The rocket kerosene quality properties such as density, distillation range, viscosity and iodine value were successfully measured based on their near-infrared spectrum (NIRS) and chemometrics. In the present paper, more than 70 rocket kerosene samples were determined by near infrared spectrum, the models were built using the partial least squares method within the appropriate wavelength range. The correlation coefficients (R2) of every rocket kerosene's quality properties ranged from 0.862 to 0.999. Ten unknown samples were determined with the model, and the result showed that the prediction accuracy of near infrared spectrum method accords with standard analysis requirements. The new method is well suitable for replacing the traditional standard method to rapidly determine the properties of the rocket kerosene.

  18. Chemometric methods in capillary electrophoresis

    National Research Council Canada - National Science Library

    Hanrahan, Grady; Gomez, Frank A

    2010-01-01

    ... 113 6 CHEMOMETRIC METHODS FOR THE OPTIMIZATION OF CE AND CE- MS IN PHARMACEUTICAL, ENVIRONMENTAL, AND FOOD ANALYSIS Javier Hernández-Borges, Miguel Ángel Rodríguez-Delgado, and Alejandro Cifuent...

  19. Automatic untargeted metabolic profiling analysis coupled with Chemometrics for improving metabolite identification quality to enhance geographical origin discrimination capability.

    Science.gov (United States)

    Han, Lu; Zhang, Yue-Ming; Song, Jing-Jing; Fan, Mei-Juan; Yu, Yong-Jie; Liu, Ping-Ping; Zheng, Qing-Xia; Chen, Qian-Si; Bai, Chang-Cai; Sun, Tao; She, Yuan-Bin

    2018-03-16

    Untargeted metabolic profiling analysis is employed to screen metabolites for specific purposes, such as geographical origin discrimination. However, the data analysis remains a challenging task. In this work, a new automatic untargeted metabolic profiling analysis coupled with a chemometric strategy was developed to improve the metabolite identification results and to enhance the geographical origin discrimination capability. Automatic untargeted metabolic profiling analysis with chemometrics (AuMPAC) was used to screen the total ion chromatographic (TIC) peaks that showed significant differences among the various geographical regions. Then, a chemometric peak resolution strategy is employed for the screened TIC peaks. The retrieved components were further analyzed using ANOVA, and those that showed significant differences were used to build a geographical origin discrimination model by using two-way encoding partial least squares. To demonstrate its performance, a geographical origin discrimination of flaxseed samples from six geographical regions in China was conducted, and 18 TIC peaks were screened. A total of 19 significant different metabolites were obtained after the peak resolution. The accuracy of the geographical origin discrimination was up to 98%. A comparison of the AuMPAC, AMDIS, and XCMS indicated that AuMPACobtained the best geographical origin discrimination results. In conclusion, AuMPAC provided another method for data analysis. Copyright © 2018 Elsevier B.V. All rights reserved.

  20. Comparison of Aurantii Fructus Immaturus and Aurantii Fructus based on multiple chromatographic analysis and chemometrics methods.

    Science.gov (United States)

    Li, Pei; Zeng, Su-Ling; Duan, Li; Ma, Xiao-Dong; Dou, Li-Li; Wang, Lan-Jin; Li, Ping; Bi, Zhi-Ming; Liu, E-Hu

    2016-10-21

    To get a better understanding of the bioactive constituents in Aurantii Fructus Immaturus (AFI) and Aurantii Fructus (AF), in the present study, a comprehensive strategy integrating multiple chromatographic analysis and chemometrics methods was firstly proposed. Based on segmental monitoring, a high-performance liquid chromatography (HPLC)-variable wavelength detection method was established for simultaneous quantification of ten major flavonoids, and the quantitative data were further analyzed by hierarchical cluster analysis (HCA) and principal component analysis (PCA). A strong cation exchange-high performance liquid chromatography (SCX-HPLC) method combined with t-test and one-way analysis of variance (ANOVA) was developed to determine synephrine, the major alkaloid in AFI and AF. The essential oils were analyzed by gas chromatography-mass spectrometry (GC-MS) and further processed by partial least squares discrimination analysis (PLS-DA). The results indicated that the contents of ten flavonoids and synephrine in AFI were significantly higher than those in AF, and significant difference existed in samples from different geographical origins. Also, 9 differential volatile constituents detected could be used as chemical markers for discrimination of AFI and AF. Collectively, the proposed comprehensive analysis might be a well-acceptable strategy to evaluate the quality of traditional citrus herbs. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. Fingerprint analysis of polysaccharides from different Ganoderma by HPLC combined with chemometrics methods.

    Science.gov (United States)

    Sun, Xiaomei; Wang, Haohao; Han, Xiaofeng; Chen, Shangwei; Zhu, Song; Dai, Jun

    2014-12-19

    A fingerprint analysis method has been developed for characterization and discrimination of polysaccharides from different Ganoderma by high performance liquid chromatography (HPLC) coupled with chemometrics means. The polysaccharides were extracted under ultrasonic-assisted condition, and then partly hydrolyzed with trifluoroacetic acid. Monosaccharides and oligosaccharides in the hydrolyzates were subjected to pre-column derivatization with 1-phenyl-3-methyl-5-pyrazolone and HPLC analysis, which will generate unique fingerprint information related to chemical composition and structure of polysaccharides. The peak data were imported to professional software in order to obtain standard fingerprint profiles and evaluate similarity of different samples. Meanwhile, the data were further processed by hierarchical cluster analysis and principal component analysis. Polysaccharides from different parts or species of Ganoderma or polysaccharides from the same parts of Ganoderma but from different geographical regions or different strains could be differentiated clearly. This fingerprint analysis method can be applied to identification and quality control of different Ganoderma and their products. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Analysis of laser printer and photocopier toners by spectral properties and chemometrics.

    Science.gov (United States)

    Verma, Neha; Kumar, Raj; Sharma, Vishal

    2018-05-05

    The use of printers to generate falsified documents has become a common practice in today's world. The examination and identification of the printed matter in the suspected documents (civil or criminal cases) may provide important information about the authenticity of the document. In the present study, a total number of 100 black toner samples both from laser printers and photocopiers were examined using diffuse reflectance UV-Vis Spectroscopy. The present research is divided into two parts; visual discrimination and discrimination by using multivariate analysis. A comparison between qualitative and quantitative analysis showed that multivariate analysis (Principal component analysis) provides 99.59%pair-wise discriminating power for laser printer toners while 99.84% pair-wise discriminating power for photocopier toners. The overall results obtained confirm the applicability of UV-Vis spectroscopy and chemometrics, in the nondestructive analysis of toner printed documents while enhancing their evidential value for forensic applications. Copyright © 2018 Elsevier B.V. All rights reserved.

  3. A modern approach to the authentication and quality assessment of thyme using UV spectroscopy and chemometric analysis.

    Science.gov (United States)

    Gad, Haidy A; El-Ahmady, Sherweit H; Abou-Shoer, Mohamed I; Al-Azizi, Mohamed M

    2013-01-01

    Recently, the fields of chemometrics and multivariate analysis have been widely implemented in the quality control of herbal drugs to produce precise results, which is crucial in the field of medicine. Thyme represents an essential medicinal herb that is constantly adulterated due to its resemblance to many other plants with similar organoleptic properties. To establish a simple model for the quality assessment of Thymus species using UV spectroscopy together with known chemometric techniques. The success of this model may also serve as a technique for the quality control of other herbal drugs. The model was constructed using 30 samples of authenticated Thymus vulgaris and challenged with 20 samples of different botanical origins. The methanolic extracts of all samples were assessed using UV spectroscopy together with chemometric techniques: principal component analysis (PCA), soft independent modeling of class analogy (SIMCA) and hierarchical cluster analysis (HCA). The model was able to discriminate T. vulgaris from other Thymus, Satureja, Origanum, Plectranthus and Eriocephalus species, all traded in the Egyptian market as different types of thyme. The model was also able to classify closely related species in clusters using PCA and HCA. The model was finally used to classify 12 commercial thyme varieties into clusters of species incorporated in the model as thyme or non-thyme. The model constructed is highly recommended as a simple and efficient method for distinguishing T. vulgaris from other related species as well as the classification of marketed herbs as thyme or non-thyme. Copyright © 2013 John Wiley & Sons, Ltd.

  4. Chemometric analysis of MALDI mass spectrometric images of three-dimensional cell culture systems.

    Science.gov (United States)

    Weaver, Eric M; Hummon, Amanda B; Keithley, Richard B

    2015-09-07

    As imaging mass spectrometry (IMS) has grown in popularity in recent years, the applications of this technique have become increasingly diverse. Currently there is a need for sophisticated data processing strategies that maximize the information gained from large IMS data sets. Traditional two-dimensional heat maps of single ions generated in IMS experiments lack analytical detail, yet manual analysis of multiple peaks across hundreds of pixels within an entire image is time-consuming, tedious and subjective. Here, various chemometric methods were used to analyze data sets obtained by matrix-assisted laser desorption/ionization (MALDI) IMS of multicellular spheroids. HT-29 colon carcinoma multicellular spheroids are an excellent in vitro model system that mimic the three dimensional morphology of tumors in vivo . These data are especially challenging to process because, while different microenvironments exist, the cells are clonal which can result in strong similarities in the mass spectral profiles within the image. In this proof-of-concept study, a combination of principal component analysis (PCA), clustering methods, and linear discriminant analysis was used to identify unique spectral features present in spatially heterogeneous locations within the image. Overall, the application of these exploratory data analysis tools allowed for the isolation and detection of proteomic changes within IMS data sets in an easy, rapid, and unsupervised manner. Furthermore, a simplified, non-mathematical theoretical introduction to the techniques is provided in addition to full command routines within the MATLAB programming environment, allowing others to easily utilize and adapt this approach.

  5. Metabolomic differentiation of maca (Lepidium meyenii) accessions cultivated under different conditions using NMR and chemometric analysis.

    Science.gov (United States)

    Zhao, Jianping; Avula, Bharathi; Chan, Michael; Clément, Céline; Kreuzer, Michael; Khan, Ikhlas A

    2012-01-01

    To gain insights on the effects of color type, cultivation history, and growing site on the composition alterations of maca (Lepidium meyenii Walpers) hypocotyls, NMR profiling combined with chemometric analysis was applied to investigate the metabolite variability in different maca accessions. Maca hypocotyls with different colors (yellow, pink, violet, and lead-colored) cultivated at different geographic sites and different areas were examined for differences in metabolite expression. Differentiations of the maca accessions grown under the different cultivation conditions were determined by principle component analyses (PCAs) which were performed on the datasets derived from their ¹H NMR spectra. A total of 16 metabolites were identified by NMR analysis, and the changes in metabolite levels in relation to the color types and growing conditions of maca hypocotyls were evaluated using univariate statistical analysis. In addition, the changes of the correlation pattern among the metabolites identified in the maca accessions planted at the two different sites were examined. The results from both multivariate and univariate analysis indicated that the planting site was the major determining factor with regards to metabolite variations in maca hypocotyls, while the color of maca accession seems to be of minor importance in this respect. © Georg Thieme Verlag KG Stuttgart · New York.

  6. Assessment of genetically modified soybean crops and different cultivars by Fourier transform infrared spectroscopy and chemometric analysis

    Directory of Open Access Journals (Sweden)

    Glaucia Braz Alcantara

    2010-06-01

    Full Text Available This paper describes the potentiality of Fourier transform infrared (FT-IR spectroscopy associated to chemometric analysis for assessment of conventional and genetically modified soybean crops. Recently, genetically modified organisms have been queried about their influence on the environment and their safety as food/feed. In this regard, chemical investigations are ever more required. Thus three different soybean cultivars distributed in transgenic Roundup ReadyTM soybean and theirs conventional counterparts were directly investigated by FT-IR spectroscopy and chemometric analysis. The application of PCA and KNN methods permitted the discrimination and classification of the genetically modified samples from conventional ones when they were separately analysed. The analyses showed the chemical variation according to genetic modification. Furthermore, this methodology was efficient for cultivar grouping and highlights cultivar dependence for discrimination between transgenic and non-transgenic samples. According to this study, FT-IR and chemometrics could be used as a quick, easy and low cost tool to assess the chemical composition variation in genetically modified organisms.

  7. Rapid nuclear forensics analysis via laser based microphotonic techniques coupled with chemometrics

    International Nuclear Information System (INIS)

    Bhatta, B.; Kalambuka, H.A.; Dehayem-Kamadjeu, A.

    2017-01-01

    Nuclear forensics (NF) is an important tool for analysis and attribution of nuclear and radiological materials (NRM) in support of nuclear security. The critical challenge in NF currently is the lack of suitable microanalytical methodologies for direct, rapid and minimally-invasive detection and quantification of NF signatures. Microphotonic techniques can achieve this task particularly when the materials are of limited size and under concealed condition. The purpose of this paper is to demonstrate the combined potential of chemometrics enabled LIBS and laser Raman spectromicroscopy (LRS) for rapid NF analysis and attribution. Using LIBS, uranium lines at 385.464 nm, 385.957 nm and 386.592 nm were identified as NF signatures in uranium ore surrogates. A multivariate calibration strategy using artificial neural network was developed for quantification of trace uranium. Principal component analysis (PCA) of LIBS spectra achieved source attribution of the ores. LRS studies on UCl3, UO3(NO3)2.6H2O, UO2SO4.3H2O and UO3 in pellet state identified the bands associated with different uranium molecules as varying in the range of (840 to 867) ± 15 cm-1. Using this signature, we have demonstrated spectral imaging of uranium under concealed conditions (author)

  8. Provenance Establishment of Stingless Bee Honey Using Multi-element Analysis in Combination with Chemometrics Techniques.

    Science.gov (United States)

    Shadan, Aidil Fahmi; Mahat, Naji A; Wan Ibrahim, Wan Aini; Ariffin, Zaiton; Ismail, Dzulkiflee

    2018-01-01

    As consumption of stingless bee honey has been gaining popularity in many countries including Malaysia, ability to identify accurately its geographical origin proves pertinent for investigating fraudulent activities for consumer protection. Because a chemical signature can be location-specific, multi-element distribution patterns may prove useful for provenancing such product. Using the inductively coupled-plasma optical emission spectrometer as well as principal component analysis (PCA) and linear discriminant analysis (LDA), the distributions of multi-elements in stingless bee honey collected at four different geographical locations (North, West, East, and South) in Johor, Malaysia, were investigated. While cross-validation using PCA demonstrated 87.0% correct classification rate, the same was improved (96.2%) with the use of LDA, indicating that discrimination was possible for the different geographical regions. Therefore, utilization of multi-element analysis coupled with chemometrics techniques for assigning the provenance of stingless bee honeys for forensic applications is supported. © 2017 American Academy of Forensic Sciences.

  9. UV-visible scanning spectrophotometry and chemometric analysis as tools for carotenoids analysis in cassava genotypes (Manihot esculenta Crantz).

    Science.gov (United States)

    Moresco, Rodolfo; Uarrota, Virgílio Gavicho; Pereira, Aline; Tomazzoli, Maíra Maciel; Nunes, Eduardo da C; Peruch, Luiz Augusto Martins; Gazzola, Jussara; Costa, Christopher; Rocha, Miguel; Maraschin, Marcelo

    2015-10-21

    In this study, the metabolomics characterization focusing on the carotenoid composition of ten cassava (Manihot esculenta) genotypes cultivated in southern Brazil by UV-visible scanning spectrophotometry and reverse phase-high performance liquid chromatography was performed. Cassava roots rich in β-carotene are an important staple food for populations with risk of vitamin A deficiency. Cassava genotypes with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin. The data set was used for the construction of a descriptive model by chemometric analysis. The genotypes of yellow-fleshed roots were clustered by the higher concentrations of cis-β-carotene and lutein. Inversely, cream-fleshed roots genotypes were grouped precisely due to their lower concentrations of these pigments, as samples rich in lycopene (red-fleshed) differed among the studied genotypes. The analytical approach (UV-Vis, HPLC, and chemometrics) used showed to be efficient for understanding the chemodiversity of cassava genotypes, allowing to classify them according to important features for human health and nutrition.

  10. Chemometric approach to texture profile analysis of kombucha fermented milk products.

    Science.gov (United States)

    Malbaša, Radomir; Jevrić, Lidija; Lončar, Eva; Vitas, Jasmina; Podunavac-Kuzmanović, Sanja; Milanović, Spasenija; Kovačević, Strahinja

    2015-09-01

    In the present work, relationships between the textural characteristics of fermented milk products obtained by kombucha inoculums with various teas were investigated by using chemometric analysis. The presented data which describe numerically the textural characteristics (firmness, consistency, cohesiveness and index of viscosity) were analysed. The quadratic correlation was determined between the textural characteristics of fermented milk products obtained at fermentation temperatures of 40 and 43 °C, using milk with 0.8, 1.6 and 2.8% milk fat and kombucha inoculums cultivated on the extracts of peppermint, stinging nettle, wild thyme and winter savory. Hierarchical cluster analysis (HCA) was performed to identify the similarities among the fermented products. The best mathematical models predicting the textural characteristics of investigated samples were developed. The results of this study indicate that textural characteristics of sample based on winter savory have a significant effect on textural characteristics of samples based on peppermint, stinging nettle and wild thyme, which can be very useful in the determination of products texture profile.

  11. Chemometric analysis for near-infrared spectral detection of beef in fish meal

    Science.gov (United States)

    Yang, Chun-Chieh; Garrido-Novell, Cristóbal; Pérez-Marín, Dolores; Guerrero-Ginel, José E.; Garrido-Varo, Ana; Kim, Moon S.

    2015-05-01

    This paper reports the chemometric analysis of near-infrared spectra drawn from hyperspectral images to develop, evaluate, and compare statistical models for the detection of beef in fish meal. There were 40 pure-fish meal samples, 15 pure-beef meal samples, and 127 fish/beef mixture meal samples prepared for hyperspectral line-scan imaging by a machine vision system. Spectral data for 3600 pixels per sample, in which individual spectra was obtain, were retrieved from the region of interest (ROI) in every sample image. The spectral data spanning 969 nm to 1551 nm (across 176 spectral bands) were analyzed. Statistical models were built using the principal component analysis (PCA) and the partial least squares regression (PLSR) methods. The models were created and developed using the spectral data from the purefish meal and pure-beef meal samples, and were tested and evaluated using the data from the ROI in the mixture meal samples. The results showed that, with a ROI as large as 3600 pixels to cover sufficient area of a mixture meal sample, the success detection rate of beef in fish meal could be satisfactory 99.2% by PCA and 98.4% by PLSR.

  12. The spectral analysis of fuel oils using terahertz radiation and chemometric methods

    International Nuclear Information System (INIS)

    Zhan, Honglei; Zhao, Kun; Xiao, Lizhi; Zhao, Hui; Li, Qian; Zhu, Shouming

    2016-01-01

    The combustion characteristics of fuel oils are closely related to both engine efficiency and pollutant emissions, and the analysis of oils and their additives is thus important. These oils and additives have been found to generate distinct responses to terahertz (THz) radiation as the result of various molecular vibrational modes. In the present work, THz spectroscopy was employed to identify a number of oils, including lubricants, gasoline and diesel, with different additives. The identities of dozens of these oils could be readily established using statistical models based on principal component analysis. The THz spectra of gasoline, diesel, sulfur and methyl methacrylate (MMA) were acquired and linear fittings were obtained. By using chemometric methods, including back propagation, artificial neural network and support vector machine techniques, typical concentrations of sulfur in gasoline (ppm-grade) could be detected, together with MMA in diesel below 0.5%. The absorption characteristics of the oil additives were also assessed using 2D correlation spectroscopy, and several hidden absorption peaks were discovered. The technique discussed herein should provide a useful new means of analyzing fuel oils with various additives and impurities in a non-destructive manner and therefore will be of benefit to the field of chemical detection and identification. (paper)

  13. GC-FID coupled with chemometrics for quantitative and chemical fingerprinting analysis of Alpinia oxyphylla oil.

    Science.gov (United States)

    Miao, Qing; Kong, Weijun; Zhao, Xiangsheng; Yang, Shihai; Yang, Meihua

    2015-01-01

    Analytical methods for quantitative analysis and chemical fingerprinting of volatile oils from Alpinia oxyphylla were established. The volatile oils were prepared by hydrodistillation, and the yields were between 0.82% and 1.33%. The developed gas chromatography-flame ionization detection (GC-FID) method showed good specificity, linearity, reproducibility, stability and recovery, and could be used satisfactorily for quantitative analysis. The results showed that the volatile oils contained 2.31-77.30 μL/mL p-cymene and 12.38-99.34 mg/mL nootkatone. A GC-FID fingerprinting method was established, and the profiles were analyzed using chemometrics. GC-MS was used to identify the principal compounds in the GC-FID profiles. The profiles of almost all the samples were consistent and stable. The harvesting time and source were major factors that affected the profile, while the volatile oil yield and the nootkatone content had minor secondary effects. Copyright © 2014 Elsevier B.V. All rights reserved.

  14. Estimating cocoa bean parameters by FT-NIRS and chemometrics analysis.

    Science.gov (United States)

    Teye, Ernest; Huang, Xingyi; Sam-Amoah, Livingstone K; Takrama, Jemmy; Boison, Daniel; Botchway, Francis; Kumi, Francis

    2015-06-01

    Rapid analysis of cocoa beans is an important activity for quality assurance and control investigations. In this study, Fourier transform near infrared spectroscopy (FT-NIRS) and chemometric techniques were attempted to estimate cocoa bean quality categories, pH and fermentation index (FI). The performances of the models were optimised by cross-validation and examined by identification rate (%), correlation coefficient (Rpre) and root mean square error of prediction (RMSEP) in the prediction set. The optimal identification model by back propagation artificial neural network (BPANN) was 99.73% at 5 principal components. The efficient variable selection model derived by synergy interval back propagation artificial neural network regression (Si-BPANNR) was superior for pH and FI estimation. Si-BPANNR model for pH was Rpre=0.98 and RMSEP=0.06, while for FI was Rpre=0.98 and RMSEP=0.05. The results demonstrated that FT-NIRS together with BPANN and Si-BPANNR model could successfully be used for cocoa beans examination. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. MIR-biospectroscopy coupled with chemometrics in cancer studies.

    Science.gov (United States)

    Siqueira, Laurinda F S; Lima, Kássio M G

    2016-08-02

    This review focuses on chemometric techniques applied in MIR-biospectroscopy for cancer diagnosis and analysis over the last ten years of research. Experimental applications of chemometrics coupled with biospectroscopy are discussed throughout this work. The advantages and drawbacks of this association are also highlighted. Chemometric algorithms are evidenced as a powerful tool for cancer diagnosis, classification, and in different matrices. In fact, it is shown how chemometrics can be implemented along all different types of cancer analyses.

  16. Quantitative and fingerprinting analysis of Atractylodes rhizome based on gas chromatography with flame ionization detection combined with chemometrics.

    Science.gov (United States)

    Liu, Qiutao; Kong, Dandan; Luo, Jiaoyang; Kong, Weijun; Guo, Weiying; Yang, Meihua

    2016-07-01

    This study assessed the feasibility of gas chromatography with flame ionization detection fingerprinting combined with chemometrics for quality analysis of Atractylodes rhizome. We extracted essential oils from 20 Atractylodes lancea and Atractylodes koreana samples by hydrodistillation. The variation in extraction yields (1.33-4.06%) suggested that contents of the essential oils differed between species. The volatile components (atractylon, atractydin, and atractylenolide I, II, and III) were quantified by gas chromatography with flame ionization detection and confirmed by gas chromatography with mass spectrometry, and the results demonstrated that the number and content of volatile components differed between A. lancea and A. koreana. We then calculated the relative peak areas of common components and similarities of samples by comparing the chromatograms of A. lancea and A. koreana extracts. Also, we employed several chemometric techniques, including similarity analysis, hierarchical clustering analysis, principal component analysis, and partial least-squares discriminate analysis, to analyze the samples. Results were consistent across analytical methods and showed that samples could be separated according to species. Five volatile components in the essential oils were quantified to further validate the results of the multivariate statistical analysis. The method is simple, stable, accurate, and reproducible. Our results provide a foundation for quality control analysis of A. lancea and A. koreana. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Chemometric Analysis of Multicomponent Biodegradable Plastics by Fourier Transform Infrared Spectrometry: The R-Matrix Method

    Science.gov (United States)

    A new chemometric method based on absorbance ratios from Fourier transform infrared spectra was devised to analyze multicomponent biodegradable plastics. The method uses the BeerLambert law to directly compute individual component concentrations and weight losses before and after biodegradation of c...

  18. Robust procedures in chemometrics

    DEFF Research Database (Denmark)

    Kotwa, Ewelina

    -way chemometrical methods, such as PCA and PARAFAC models for analysing spatial and depth profiles of sea water samples, defined by three data modes: depth, variables and geographical location. Emphasis was also put on predicting fluorescence values, as being a natural measure of biological activity, by applying...... if contamination in the data is present. For this becoming a standard procedure, further work is required, aiming at implementing reliable robust algorithms into standard statistical programs.......The general aim of the thesis was to contribute to the improvement of data analytical techniques within the chemometric field. Regardless the multivariate structure of the data, it is still common in some fields to perform uni-variate data analysis using only simple statistics such as sample mean...

  19. Chemometric analysis of frequency-domain photon migration data: quantitative measurements of optical properties and chromophore concentrations in multicomponent turbid media

    International Nuclear Information System (INIS)

    Berger, Andrew J.; Venugopalan, Vasan; Durkin, Anthony J.; Pham, Tuan; Tromberg, Bruce J.

    2000-01-01

    Frequency-domain photon migration (FDPM) is a widely used technique for measuring the optical properties (i.e., absorption, μ a , and reduced scattering, μ s ' , coefficients) of turbid samples. Typically, FDPM data analysis is performed with models based on a photon diffusion equation; however, analytical solutions are difficult to obtain for many realistic geometries. Here, we describe the use of models based instead on representative samples and multivariate calibration (chemometrics). FDPM data at seven wavelengths (ranging from 674 to 956 nm) and multiple modulation frequencies (ranging from 50 to 600 MHz) were gathered from turbid samples containing mixtures of three absorbing dyes. Values for μ a and μ s ' were extracted from the FDPM data in different ways, first with the diffusion theory and then with the chemometric technique of partial least squares. Dye concentrations were determined from the FDPM data by three methods, first by least-squares fits to the diffusion results and then by two chemometric approaches. The accuracy of the chemometric predictions was comparable or superior for all three dyes. Our results indicate that chemometrics can recover optical properties and dye concentrations from the frequency-dependent behavior of photon density waves, without the need for diffusion-based models. Future applications to more complicated geometries, lower-scattering samples, and simpler FDPM instrumentation are discussed. (c) 2000 Optical Society of America

  20. Rapid differentiation ofXihuangcaofrom the threeIsodonspecies by UPLC-ESI-QTOF-MS/MS and chemometrics analysis.

    Science.gov (United States)

    Wong, Lai Lai; Liang, Zhitao; Chen, Hubiao; Zhao, Zhongzhen

    2016-01-01

    Isodon lophanthoides , I. lophanthoides var. graciliflorus and I. serra are the three botanical sources of Xihuangcao , which are often used indiscriminately in herbal products. The aim of this study was to develop a rapid and accurate analytical method to identify the three different botanical sources of Xihuangcao by combining UPLC-ESI-QTOF-MS with chemometrics analysis. Fifteen batches of plants were collected as reference materials and their chemical profiles were analyzed by UPLC-ESI-QTOF-MS. These data were subsequently processed by statistical methods, including principal component analysis (PCA), hierarchical cluster analysis (HCA) and orthogonal partial least squared discriminant analysis (OPLS-DA). An automated sample class prediction model was also built using Naive Bayes as a class prediction algorithm to rapidly determine the source species of twenty-seven batches of commercial Xihuangcao samples. The base peak chromatograms of the three authenticated species showed different patterns and twenty-seven peaks were chosen, including six diterpenoids, one phenolic acid and two glycosides to distinguish among these three species. The results showed good differentiation among the three species by PCA, HCA and OPLS-DA. Isodon lophanthoides var. graciliflorus was found to be the major botanical source of the commercial samples. UPLC-ESI-QTOF-MS and subsequent chemometrics analysis were demonstrated effective to differentiate among the three different species of plants used as Xihuangcao .

  1. Multi-elemental analysis of Ziziphora clinopodioidesfrom different regions, periods and parts using atomic absorption spectrometry and chemometric approaches

    Directory of Open Access Journals (Sweden)

    Xuejia Zhang

    Full Text Available ABSTRACTIn this study, ten trace elements in Ziziphora clinopodioidesLam., Lamiaceae, from different regions, periods and parts in Xinjiang were determined by atomic absorption spectrometry following microwave-assisted acid digestion. The decreasing sequence of elements levels was K > Ca > Mg > Fe > Cu > Zn > Na > Mn > Cd > Pb. Chemometric approaches, such as correlation analysis, principal component analysis, and hierarchical cluster analysis were applied to classify Z. clinopodioides according to its elements contents. Principal component analysis revealed 83.51% of the variance with the first four principal component variables. Hierarchical cluster analysis indicated five groups from the eighteen regions, and the result of classification can correspond to the geographical distribution for the most regions. Variation in the elements exhibited a decreasing trend, but of different types in the studied periods. Elemental contents distributed in leaves were higher than those in flowers and stems. Therefore, chemometric approaches could be used to analyze data to accurately classify Z. clinopodioides according to origins. This study provided some elemental information on chemotaxonomy, diversity, changing pattern, distribution, and metabolism of Z. clinopodioides at spatial and temporal levels, and could be used as a reference of planting and quality standards.

  2. Simultaneous kinetic spectrophotometric analysis of five synthetic food colorants with the aid of chemometrics.

    Science.gov (United States)

    Ni, Yongnian; Wang, Yong; Kokot, Serge

    2009-04-30

    This paper describes a simple and sensitive kinetic spectrophotometric method for the simultaneous determination of Amaranth, Ponceau 4R, Sunset Yellow, Tartrazine and Brilliant Blue in mixtures with the aid of chemometrics. The method involved two coupled reactions, viz. the reduction of iron(III) by the analytes to iron(II) in sodium acetate/hydrochloric acid solution (pH 1.71) and the chromogenic reaction between iron(II) and hexacyanoferrate(III) ions to yield a Prussian blue peak at 760 nm. The spectral data were recorded over the 500-1000 nm wavelength range every 2s for 600 s. The kinetic data were collected at 760 nm and 600 s, and linear calibration models were satisfactorily constructed for each of the dyes with detection limits in the range of 0.04-0.50 mg L(-1). Multivariate calibration models for kinetic data were established and verified for methods such as the Iterative target transform factor analysis (ITTFA), principal component regression (PCR), partial least squares (PLS), and principal component-radial basis function-artificial neural network (PC-RBF-ANN) with and without wavelet packet transform (WPT) pre-treatment. The PC-RBF-ANN with WPT calibration performed somewhat better than others on the basis of the %RPE(T) (approximately 9) and %Recovery parameters (approximately 108), although the effect of the WPT pre-treatment was marginal (approximately 0.5% RPE(T)). The proposed method was applied for the simultaneous determination of the five colorants in foodstuff samples, and the results were comparable with those from a reference HPLC method.

  3. Characterization of Hatay honeys according to their multi-element analysis using ICP-OES combined with chemometrics.

    Science.gov (United States)

    Yücel, Yasin; Sultanoğlu, Pınar

    2013-09-01

    Chemical characterisation has been carried out on 45 honey samples collected from Hatay region of Turkey. The concentrations of 17 elements were determined by inductively coupled plasma optical emission spectrometry (ICP-OES). Ca, K, Mg and Na were the most abundant elements, with mean contents of 219.38, 446.93, 49.06 and 95.91 mg kg(-1) respectively. The trace element mean contents ranged between 0.03 and 15.07 mg kg(-1). Chemometric methods such as principal component analysis (PCA) and cluster analysis (CA) techniques were applied to classify honey according to mineral content. The first most important principal component (PC) was strongly associated with the value of Al, B, Cd and Co. CA showed eight clusters corresponding to the eight botanical origins of honey. PCA explained 75.69% of the variance with the first six PC variables. Chemometric analysis of the analytical data allowed the accurate classification of the honey samples according to origin. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. Investigation of Arctic and Antarctic spatial and depth patterns of sea water in CTD profiles using chemometric data analysis

    DEFF Research Database (Denmark)

    Kotwa, Ewelina Katarzyna; Lacorte, Silvia; Duarte, Carlos

    2014-01-01

    In this paper we examine 2- and 3-way chemometric methods for analysis of Arctic and Antarctic water samples. Standard CTD (conductivity–temperature–depth) sensor devices were used during two oceanographic expeditions (July 2007 in the Arctic; February 2009 in the Antarctic) covering a total of 1...... properties of the water samples; and 4) we confirm the ability to predict fluorescence values from physical measurements when the 3-way data structure is used in N-way PLS regression.......In this paper we examine 2- and 3-way chemometric methods for analysis of Arctic and Antarctic water samples. Standard CTD (conductivity–temperature–depth) sensor devices were used during two oceanographic expeditions (July 2007 in the Arctic; February 2009 in the Antarctic) covering a total of 174...... locations. The output from these devices can be arranged in a 3-way data structure (according to sea water depth, measured variables, and geographical location). We used and compared 2- and 3-way statistical tools including PCA, PARAFAC, PLS, and N-PLS for exploratory analysis, spatial patterns discovery...

  5. Combination of quantitative analysis and chemometric analysis for the quality evaluation of three different frankincenses by ultra high performance liquid chromatography and quadrupole time of flight mass spectrometry.

    Science.gov (United States)

    Zhang, Chao; Sun, Lei; Tian, Run-tao; Jin, Hong-yu; Ma, Shuang-Cheng; Gu, Bing-ren

    2015-10-01

    Frankincense has gained increasing attention in the pharmaceutical industry because of its pharmacologically active components such as boswellic acids. However, the identity and overall quality evaluation of three different frankincense species in different Pharmacopeias and the literature have less been reported. In this paper, quantitative analysis and chemometric evaluation were established and applied for the quality control of frankincense. Meanwhile, quantitative and chemometric analysis could be conducted under the same analytical conditions. In total 55 samples from four habitats (three species) of frankincense were collected and six boswellic acids were chosen for quantitative analysis. Chemometric analyses such as similarity analysis, hierarchical cluster analysis, and principal component analysis were used to identify frankincense of three species to reveal the correlation between its components and species. In addition, 12 chromatographic peaks have been tentatively identified explored by reference substances and quadrupole time-of-flight mass spectrometry. The results indicated that the total boswellic acid profiles of three species of frankincense are similar and their fingerprints can be used to differentiate between them. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Identification of heparin samples that contain impurities or contaminants by chemometric pattern recognition analysis of proton NMR spectral data

    International Nuclear Information System (INIS)

    Zang, Qingda; Keire, David A.; Buhse, Lucinda F.; Trehy, Michael L.; Wood, Richard D.; Mital, Dinesh P.; Haque, Syed; Srinivasan, Shankar; Moore, Christine M.V.; Nasr, Moheb; Al-Hakim, Ali; Welsh, William J.

    2011-01-01

    Chemometric analysis of a set of one-dimensional (1D) 1 H nuclear magnetic resonance (NMR) spectral data for heparin sodium active pharmaceutical ingredient (API) samples was employed to distinguish USP-grade heparin samples from those containing oversulfated chondroitin sulfate (OSCS) contaminant and/or unacceptable levels of dermatan sulfate (DS) impurity. Three chemometric pattern recognition approaches were implemented: classification and regression tree (CART), artificial neural network (ANN), and support vector machine (SVM). Heparin sodium samples from various manufacturers were analyzed in 2008 and 2009 by 1D 1 H NMR, strong anion-exchange high-performance liquid chromatography, and percent galactosamine in total hexosamine tests. Based on these data, the samples were divided into three groups: Heparin, DS ≤ 1.0% and OSCS = 0%; DS, DS > 1.0% and OSCS = 0%; and OSCS, OSCS > 0% with any content of DS. Three data sets corresponding to different chemical shift regions (1.95-2.20, 3.10-5.70, and 1.95-5.70 ppm) were evaluated. While all three chemometric approaches were able to effectively model the data in the 1.95-2.20 ppm region, SVM was found to substantially outperform CART and ANN for data in the 3.10-5.70 ppm region in terms of classification success rate. A 100% prediction rate was frequently achieved for discrimination between heparin and OSCS samples. The majority of classification errors between heparin and DS involved cases where the DS content was close to the 1.0% DS borderline between the two classes. When these borderline samples were removed, nearly perfect classification results were attained. Satisfactory results were achieved when the resulting models were challenged by test samples containing blends of heparin APIs spiked with non-, partially, or fully oversulfated chondroitin sulfate A, heparan sulfate, or DS at the 1.0%, 5.0%, and 10.0% (w/w) levels. This study demonstrated that the combination of 1D 1 H NMR spectroscopy with multivariate

  7. Identification of heparin samples that contain impurities or contaminants by chemometric pattern recognition analysis of proton NMR spectral data

    Energy Technology Data Exchange (ETDEWEB)

    Zang, Qingda [University of Medicine and Dentistry of New Jersey, Department of Pharmacology, Robert Wood Johnson Medical School, Piscataway, NJ (United States); Snowdon, Inc., Monmouth Junction, NJ (United States); University of Medicine and Dentistry of New Jersey, Department of Health Informatics, School of Health Related Professions, Newark, NJ (United States); Keire, David A.; Buhse, Lucinda F.; Trehy, Michael L. [Food and Drug Administration, CDER, Division of Pharmaceutical Analysis, St. Louis, MO (United States); Wood, Richard D. [Snowdon, Inc., Monmouth Junction, NJ (United States); Mital, Dinesh P.; Haque, Syed; Srinivasan, Shankar [University of Medicine and Dentistry of New Jersey, Department of Health Informatics, School of Health Related Professions, Newark, NJ (United States); Moore, Christine M.V.; Nasr, Moheb; Al-Hakim, Ali [Food and Drug Administration, CDER, Office of New Drug Quality Assessment, Silver Spring, MD (United States); Welsh, William J. [University of Medicine and Dentistry of New Jersey, Department of Pharmacology, Robert Wood Johnson Medical School, Piscataway, NJ (United States)

    2011-08-15

    Chemometric analysis of a set of one-dimensional (1D) {sup 1}H nuclear magnetic resonance (NMR) spectral data for heparin sodium active pharmaceutical ingredient (API) samples was employed to distinguish USP-grade heparin samples from those containing oversulfated chondroitin sulfate (OSCS) contaminant and/or unacceptable levels of dermatan sulfate (DS) impurity. Three chemometric pattern recognition approaches were implemented: classification and regression tree (CART), artificial neural network (ANN), and support vector machine (SVM). Heparin sodium samples from various manufacturers were analyzed in 2008 and 2009 by 1D {sup 1}H NMR, strong anion-exchange high-performance liquid chromatography, and percent galactosamine in total hexosamine tests. Based on these data, the samples were divided into three groups: Heparin, DS {<=} 1.0% and OSCS = 0%; DS, DS > 1.0% and OSCS = 0%; and OSCS, OSCS > 0% with any content of DS. Three data sets corresponding to different chemical shift regions (1.95-2.20, 3.10-5.70, and 1.95-5.70 ppm) were evaluated. While all three chemometric approaches were able to effectively model the data in the 1.95-2.20 ppm region, SVM was found to substantially outperform CART and ANN for data in the 3.10-5.70 ppm region in terms of classification success rate. A 100% prediction rate was frequently achieved for discrimination between heparin and OSCS samples. The majority of classification errors between heparin and DS involved cases where the DS content was close to the 1.0% DS borderline between the two classes. When these borderline samples were removed, nearly perfect classification results were attained. Satisfactory results were achieved when the resulting models were challenged by test samples containing blends of heparin APIs spiked with non-, partially, or fully oversulfated chondroitin sulfate A, heparan sulfate, or DS at the 1.0%, 5.0%, and 10.0% (w/w) levels. This study demonstrated that the combination of 1D {sup 1}H NMR spectroscopy

  8. Infrared imaging spectroscopy and chemometric tools for in situ analysis of an imiquimod pharmaceutical preparation presented as cream

    Science.gov (United States)

    Carneiro, Renato Lajarim; Poppi, Ronei Jesus

    2014-01-01

    In the present work the homogeneity of a pharmaceutical formulation presented as a cream was studied using infrared imaging spectroscopy and chemometric methodologies such as principal component analysis (PCA) and multivariate curve resolution with alternating least squares (MCR-ALS). A cream formulation, presented as an emulsion, was prepared using imiquimod as the active pharmaceutical ingredient (API) and the excipients: water, vaseline, an emulsifier and a carboxylic acid in order to dissolve the API. After exposure at 45 °C during 3 months to perform accelerated stability test, the presence of some crystals was observed, indicating homogeneity problems in the formulation. PCA exploratory analysis showed that the crystal composition was different from the composition of the emulsion, since the score maps presented crystal structures in the emulsion. MCR-ALS estimated the spectra of the crystals and the emulsion. The crystals presented amine and C-H bands, suggesting that the precipitate was a salt formed by carboxylic acid and imiquimod. These results indicate the potential of infrared imaging spectroscopy in conjunction with chemometric methodologies as an analytical tool to ensure the quality of cream formulations in the pharmaceutical industry.

  9. A novel strategy for quantitative analysis of the formulated complex system using chromatographic fingerprints combined with some chemometric techniques.

    Science.gov (United States)

    Zhong, Xuan; Yan, Jun; Li, Yan-Chun; Kong, Bo; Lu, Hong-Bing; Liang, Yi-Zeng

    2014-11-28

    In this work, a novel strategy based on chromatographic fingerprints and some chemometric techniques is proposed for quantitative analysis of the formulated complex system. Here, the formulated complex system means a formulated type of complicated analytical system containing more than one kind of raw material under some concentration composition according to a certain formula. The strategy is elaborated by an example of quantitative determination of mixtures consist of three essential oils. Three key steps of the strategy are as follows: (1) remove baselines of the chromatograms; (2) align retention time; (3) conduct quantitative analysis using multivariate regression with entire chromatographic profiles. Through the determination of concentration compositions of nine mixtures arranged by uniform design, the feasibility of the proposed strategy is validated and the factors that influence the quantitative result are also discussed. This strategy is proved to be viable and the validation indicates that quantitative result obtained using this strategy mainly depends on the efficiency of the alignment method as well as chromatographic peak shape of the chromatograms. Previously, chromatographic fingerprints were only used for identification and/or recognition of some products. This work demonstrates that with the assistance of some effective chemometric techniques, chromatographic fingerprints are also potential and promising in solving quantitative problems of complex analytical systems. Copyright © 2014 Elsevier B.V. All rights reserved.

  10. Determination of the predominant minerals in sedimentary rocks by chemometric analysis of infrared spectra

    Czech Academy of Sciences Publication Activity Database

    Ritz, M.; Vaculíková, Lenka; Plevová, Eva; Matýsek, D.; Mališ, J.

    2012-01-01

    Roč. 60, č. 6 (2012), s. 655-665 ISSN 0009-8604 R&D Projects: GA MŠk ED2.1.00/03.0082 Grant - others:GA MŠk(CZ) ED0040/01/01 Institutional support: RVO:68145535 Keywords : infrared spectroscopy * chemometrics * minerals Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 1.114, year: 2012 http://ccm.geoscienceworld.org/content/60/6/655.full.pdf+html

  11. Unintended compositional changes in transgenic rice seeds ( Oryza sativa L.) studied by spectral and chromatographic analysis coupled with chemometrics methods.

    Science.gov (United States)

    Jiao, Zhe; Si, Xiao-xi; Li, Gong-ke; Zhang, Zhuo-min; Xu, Xin-ping

    2010-02-10

    Unintended compositional changes in transgenic rice seeds were studied by near-infrared reflectance, GC-MS, HPLC, and ICP-AES coupled with chemometrics strategies. Three kinds of transgenic rice with resistance to fungal diseases or insect pests were comparatively studied with the nontransgenic counterparts in terms of key nutrients such as protein, amino acids, fatty acids, vitamins, elements, and antinutrient phytic acid recommended by the Organization for Economic Co-operation and Development (OECD). The compositional profiles were discriminated by chemometrics methods, and the discriminatory compounds were protein, three amino acids, two fatty acids, two vitamins, and several elements. Significance of differences for these compounds was proved by analysis of variance, and the variation extent ranged from 20 to 74% for amino acids, from 19 to 38% for fatty acids, from 25 to 57% for vitamins, from 20 to 50% for elements, and 25% for protein, whereas phytic acid content did not change significantly. The unintended compositional alterations as well as unintended change of physical characteristic in transgenic rice compared with nontransgenic rice might be related to the genetic transformation, the effect of which needs to be elucidated by additional studies.

  12. Validation of botanical origins and geographical sources of some Saudi honeys using ultraviolet spectroscopy and chemometric analysis.

    Science.gov (United States)

    Ansari, Mohammad Javed; Al-Ghamdi, Ahmad; Khan, Khalid Ali; Adgaba, Nuru; El-Ahmady, Sherweit H; Gad, Haidy A; Roshan, Abdulrahman; Meo, Sultan Ayoub; Kolyali, Sevgi

    2018-02-01

    This study aims at distinguishing honey based on botanical and geographical sources. Different floral honey samples were collected from diverse geographical locations of Saudi Arabia. UV spectroscopy in combination with chemometric analysis including Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), and Soft Independent Modeling of Class Analogy (SIMCA) were used to classify honey samples. HCA and PCA presented the initial clustering pattern to differentiate between botanical as well as geographical sources. The SIMCA model clearly separated the Ziziphus sp. and other monofloral honey samples based on different locations and botanical sources. The results successfully discriminated the honey samples of different botanical and geographical sources validating the segregation observed using few physicochemical parameters that are regularly used for discrimination.

  13. Chemotaxonomy of the Amazonian Unonopsis Species Based on GC-MS and Chemometric Analysis of the Leaf Essential Oils

    Directory of Open Access Journals (Sweden)

    Felipe M. A. da Silva

    2015-06-01

    Full Text Available Twelve Unonopsis specimens, comprising five species commonly found at Amazonas state (Brazil were collected in three different sites. The leaves of the specimens were extracted by hydrodistillation and analyzed by gas chromatography coupled to mass spectrometry (GC-MS. The data treated by chemometric analysis with the objective of verify the potential of their chemical profiles for chemotaxonomic approaches. Despite the essential oils presented spathulenol and caryophyllene oxide as a main constituent in most samples, the multivariate analysis showed significant differences between the species and their collection sites. The obtained results suggest high chemical similarity between U. floribunda and U. rufescens species and proved that U. guatterioides has a distinct chemistry when compared to the analyzed species. The chemical identification points to α-guaiene, α-calacorene and widdrol as possible chemical markers for U. floribunda and U. rufescens species.

  14. Structural Analysis of Multi-component Amyloid Systems by Chemometric SAXS Data Decomposition

    DEFF Research Database (Denmark)

    Trillo, Isabel Fatima Herranz; Jensen, Minna Grønning; van Maarschalkerweerd, Andreas

    2017-01-01

    Formation of amyloids is the hallmark of several neurodegenerative pathologies. Structural investigation of these complex transformation processes poses significant experimental challenges due to the co-existence of multiple species. The additive nature of small-angle X-ray scattering (SAXS) data...... least squares (MCR-ALS) chemometric method. The approach enables rigorous and robust decomposition of synchrotron SAXS data by simultaneously introducing these data in different representations that emphasize molecular changes at different time and structural resolution ranges. The approach has allowed...

  15. The application of chemometrics on Infrared and Raman spectra as a tool for the forensic analysis of paints.

    Science.gov (United States)

    Muehlethaler, Cyril; Massonnet, Genevieve; Esseiva, Pierre

    2011-06-15

    The aim of this work is to evaluate the capabilities and limitations of chemometric methods and other mathematical treatments applied on spectroscopic data and more specifically on paint samples. The uniqueness of the spectroscopic data comes from the fact that they are multivariate - a few thousands variables - and highly correlated. Statistical methods are used to study and discriminate samples. A collection of 34 red paint samples was measured by Infrared and Raman spectroscopy. Data pretreatment and variable selection demonstrated that the use of Standard Normal Variate (SNV), together with removal of the noisy variables by a selection of the wavelengths from 650 to 1830 cm(-1) and 2730-3600 cm(-1), provided the optimal results for infrared analysis. Principal component analysis (PCA) and hierarchical clusters analysis (HCA) were then used as exploratory techniques to provide evidence of structure in the data, cluster, or detect outliers. With the FTIR spectra, the Principal Components (PCs) correspond to binder types and the presence/absence of calcium carbonate. 83% of the total variance is explained by the four first PCs. As for the Raman spectra, we observe six different clusters corresponding to the different pigment compositions when plotting the first two PCs, which account for 37% and 20% respectively of the total variance. In conclusion, the use of chemometrics for the forensic analysis of paints provides a valuable tool for objective decision-making, a reduction of the possible classification errors, and a better efficiency, having robust results with time saving data treatments. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  16. Chemometric, physicomechanical and rheological analysis of the sol-gel dynamics and degree of crosslinking of glycosidic polymers

    International Nuclear Information System (INIS)

    Choonara, Y E; Pillay, V; Singh, N; Ndesendo, V M K; Khan, R A

    2008-01-01

    The influence of calcium (Ca 2+ ), zinc (Zn 2+ ) and barium (Ba 2+ ) ions on the sol-gel interconversion dynamics, degree of crosslinking and the matrix resilience of crosslinked alginate gelispheres was determined. The dependent compositional and operational variables of crosslinking make it a challenging task to optimize the degree of crosslinking and the physicomechanical properties of alginate gelispheres. The combinatory approach of textural profiling, assessing pertinent rheological descriptors and chemometric model analysis of the sol-gel interconversion mechanisms and energy paradigms involved during crosslinking, hydration and erosion of gelispheres was explored. Molecular structural modelling of the gelispheres provided a mechanistic understanding of the sol-gel interconversion phenomena and their influence on the degree of crosslinking, the hydrational dynamics and gelisphere formation. Rheological analysis revealed offset yield point values of 6.1 mg ml -1 and 8.0 mg ml -1 were computed from fitted regression curves for determining the crosslinker concentration required for combinatory crosslinkers such as Ca/Zn/Ba ions and Ba/Zn, respectively. The influence of hydration on the erosion was a direct function of the gelispheres physicomechanical strength. Textural profiling characterized the gelisphere matrices for their resilience. The various crosslinkers interacted with monomeric units at varying intensities. Ba-crosslinked gelispheres were brittle with dense polymeric networks. Zn-crosslinked gelispheres produced permeable resilient matrices when hydrated and Ca-crosslinked gelispheres demonstrated intermediate resilience with greater G/M ratio alginate grades. Chemometrical analysis explicated a potential link between several phenomena such as the type of crosslinkers employed, the static shear-rate viscosity attained, the matrix resilience and the associated sol-gel mechanisms and energy paradigms of crosslinked gelispheres

  17. Optimization of wavelength range and data interval in chemometric analysis of complex pharmaceutical mixtures

    Directory of Open Access Journals (Sweden)

    Michele De Luca

    2016-02-01

    Full Text Available The performance of different chemometric approaches was evaluated in the spectrophotometric determination of pharmaceutical mixtures characterized by having the amount of components with a very high ratio. Principal component regression (PCR, partial least squares with one dependent variable (PLS1 or multi-dependent variables (PLS2, and multivariate curve resolution (MCR were applied to the spectral data of a ternary mixture containing paracetamol, sodium ascorbate and chlorpheniramine (150:140:1, m/m/m, and a quaternary mixture containing paracetamol, caffeine, phenylephrine and chlorpheniramine (125:6. 25:1.25:1, m/m/m/m. The UV spectra of the calibration samples in the range of 200–320 nm were pre-treated by removing noise and useless data, and the wavelength regions having the most useful analytical information were selected using the regression coefficients calculated in the multivariate modeling. All the defined chemometric models were validated on external sample sets and then applied to commercial pharmaceutical formulations. Different data intervals, fixed at 0.5, 1.0, and 2.0 point/nm, were tested to optimize the prediction ability of the models. The best results were obtained using the PLS1calibration models and the quantification of the species of a lower amount was significantly improved by adopting 0.5 data interval, which showed accuracy between 94.24% and 107.76%.

  18. Spectroscopic analysis of pharmaceutical formulations through the use of chemometric tools

    Science.gov (United States)

    Ornelas-Soto, N.; Barbosa-García, O.; Meneses-Nava, M.; Ramos-Ortíz, G.; Pichardo-Molina, J.; Maldonado, J. L.; Contreras, U.; López-Martínez, L.; López-de-Alba, P.; López-Barajas, F.

    2009-09-01

    In this work, fast and reliable spectroscopic methods in combination with chemometric tools were developed for simultaneous determination of Acetylsalicylic Acid, Acetaminophen and Caffeine in commercial formulations. For the first-order multivariate calibration method (PLS-1), calibration and validation sets were constructed with 23 and 10 samples respectively according to a central composite design. The Micro-Raman, FTIR-HATR and UV absorption spectra in the region of 100-2000 cm-1, 400-4400 cm-1 and 200-350 nm, respectively, were recorded. The % REP's (Percentage of relative error of prediction) was less than 18 for all used spectroscopic techniques. Subsequently, commercial pharmaceutical samples were analyzed with percentage of recovery between 90 and 117% for the three compounds.

  19. [The analysis of multivariate image and chemometrics in TLC fingerprinting of artificial cow-bezoar].

    Science.gov (United States)

    Yao, Ling-Wen; Shi, Yan; Sun, Dong-Mei; Cheng, Xian-Long; Wei, Feng; Ma, Shuang-Cheng

    2017-06-01

    A method of thin-layer fingerprinting chromatogram of artificial cow-bezoar was established with the developing solvent consisting of cyclohexane, ethyl acetate, acetic acid and methanol (2∶7∶1∶2), and 10% sulfuric acid ethanol solution sprayed as colour-developing agent. After heated at 105 ℃, TLC was recorded as an image in ultraviolet light at 366 nm which was converted into grayscale. By the gray value extracted from the grayscale, the multivariate data obtained from TLC of samples could be analyzed by chemometric method. The results indicated that samples from different manufacturers could be distinguished by this method and some specific bands were found out. All in one, this simple and practical method was suitable for the evaluation of quality difference. Copyright© by the Chinese Pharmaceutical Association.

  20. Chemometric analysis applied in 1H HR-MAS NMR and FT-IR data for chemotaxonomic distinction of intact lichen samples

    International Nuclear Information System (INIS)

    Alcantara, Glaucia Braz; Honda, Neli Kika; Castro Ferreira, Marcia Miguel; Ferreira, Antonio Gilberto

    2007-01-01

    This paper describes the potentiality of chemometric analysis applied in 1 H HR-MAS NMR and FT-IR data for lichen chemotaxonomic investigations. Lichens present a difficult morphologic differentiation and the chemical analyses are frequently employed for their taxonomic classification, mainly due to the secondary metabolites to be relatively constant for these organisms. The lichen chemotaxonomic classification is usually carried out by color reactions, chromatography, fluorescence and mass spectrometry analysis, where the identification is obtained by one or more techniques. There are some papers which use the carbohydrate content in chemotaxonomy investigation. However, the majority of these techniques involve laborious and time consuming sample pre-treatment. This work focuses on application of 1 H high resolution magic angle spinning - nuclear magnetic resonance (HR-MAS NMR) and Fourier transform infrared (FT-IR) associated with chemometric analysis to intact samples. In comparison to other traditional techniques, 1 H HR-MAS NMR and FT-IR allied with chemometrics provided a fast and economic method for lichen chemotaxonomy. Both methods were useful for lichen analysis and permitted the satisfactory distinction among families, genera and species, although better results were achieved for FT-IR data

  1. Chemometric analysis applied in {sup 1}H HR-MAS NMR and FT-IR data for chemotaxonomic distinction of intact lichen samples

    Energy Technology Data Exchange (ETDEWEB)

    Alcantara, Glaucia Braz [Departamento de Quimica, Universidade Federal de Sao Carlos, P.O. Box 676, CEP 13565-905, Sao Carlos/SP (Brazil)]. E-mail: glabraz@yahoo.com.br; Honda, Neli Kika [Departamento de Quimica, Universidade Federal de Mato Grosso do Sul, P.O. Box 549, CEP 79070-900, Campo Grande/MS (Brazil); Castro Ferreira, Marcia Miguel [Instituto de Quimica, Universidade Estadual de Campinas, P.O. Box 6154, CEP 13084-971, Campinas/SP (Brazil); Ferreira, Antonio Gilberto [Departamento de Quimica, Universidade Federal de Sao Carlos, P.O. Box 676, CEP 13565-905, Sao Carlos/SP (Brazil)

    2007-07-09

    This paper describes the potentiality of chemometric analysis applied in {sup 1}H HR-MAS NMR and FT-IR data for lichen chemotaxonomic investigations. Lichens present a difficult morphologic differentiation and the chemical analyses are frequently employed for their taxonomic classification, mainly due to the secondary metabolites to be relatively constant for these organisms. The lichen chemotaxonomic classification is usually carried out by color reactions, chromatography, fluorescence and mass spectrometry analysis, where the identification is obtained by one or more techniques. There are some papers which use the carbohydrate content in chemotaxonomy investigation. However, the majority of these techniques involve laborious and time consuming sample pre-treatment. This work focuses on application of {sup 1}H high resolution magic angle spinning - nuclear magnetic resonance (HR-MAS NMR) and Fourier transform infrared (FT-IR) associated with chemometric analysis to intact samples. In comparison to other traditional techniques, {sup 1}H HR-MAS NMR and FT-IR allied with chemometrics provided a fast and economic method for lichen chemotaxonomy. Both methods were useful for lichen analysis and permitted the satisfactory distinction among families, genera and species, although better results were achieved for FT-IR data.

  2. On-line Speciation of Cr(III) and Cr(VI) by Flow Injection Analysis With Spectrophotometric Detection and Chemometrics

    DEFF Research Database (Denmark)

    Diacu, Elena; Andersen, Jens Enevold Thaulov

    2003-01-01

    A flow injection system has been developed, for on-line speciation. of Cr(III) and Cr(VI) by the Diphenylcarbazide (DPC) method with H2O2 oxidation followed by spectrophotometric detection at the 550 nm wavelength. The data thus obtained were subjected to a chemometric analysis (PLS), which showe....../L and a maximum sampling frequency of 120 injections per hour were obtained, excluding calculations and sample pre-treatments....

  3. Quantitative Analysis in Combination with Fingerprint Technology and Chemometric Analysis Applied for Evaluating Six Species of Wild Paris Using UHPLC-UV-MS

    Directory of Open Access Journals (Sweden)

    Yuangui Yang

    2016-01-01

    Full Text Available A fast method was developed by ultra high performance liquid chromatography (UHPLC for simultaneous determination of polyphyllin I and polyphyllin II. Chemometric analyses including principal component analysis (PCA and partial least squares discriminant analysis (PLS-DA based on UHPLC chromatography were used to evaluate 38 batches from six species of Paris. Variable importance of projection was applied to select important peaks. Meanwhile, similarity analysis of UHPLC fingerprint was used to evaluate the sample of Paris polyphylla yunnanensis (PPY and P. axialis (PA. The results indicated that the total content of saponins in PPY and PA collected from Baoshan City of Yunnan Province above 8.07 mg/g was stronger than that from other areas of the rest of species. PLS-DA showed better performance than PCA with regard to classifying the samples. Retention time during 20–27 minutes of UHPLC was screened as significant peak for distinguishing Paris of different species and original geography. All of PPY and PA with similarity value were more than 0.80. It indicated that quantitative analysis combined with chemometric and similarity analyses could evaluate the different species of Paris effectively and comprehensively.

  4. [Detection of Syrup Adulterants in Prepackaged Pure Pineapple Juice by Fourier-Transform Infrared Spectroscopy and Chemometric Analysis].

    Science.gov (United States)

    Zhou, Mi; Ke, Jian; Li, Bao-li; Tang, Cui-e; Tan, Jun; Liu, Rui; Wang, Hong; Li, Tao; Zhou, Sheng-yin

    2015-10-01

    This study was performed to establish a method that can quickly and accurately identify adulterated syrup in the pure pineapple juice. A attenuated total internal refraction-fourier transform infrared spectroscopy was used to collect the range of 900 -1 500 cm(-1) infrared spectra of 234 samples pure pineapple juice and adulterated syrup by beet syrup, rice syrup and cassava syrup. By using linear discriminant analysis and support vector machine for the identification model, comparing the full spectral and selected wavelengths based on principal component analysis loading plots of the two models to identify adulteration. Studies showed that the correct rate of validation set by linear discriminant analysis and support vector machine model on full spectral were both higher than 88%, variables were significantly reduced from 312 to 8 after selecting the eight characteristic wavelengths, the correct rate of validation set by linear discriminant analysis model was up to 96.15% and support vector machine was increase to 94.87%. The results demonstrated that the model built using a attenuated total internal refraction-fourier transform infrared spectroscopy in combination with chemometric methods after selected characteristic wavelengths could be used for the identification of the adulterated syrup in the pure pineapple juice.

  5. Fingerprint Analysis of Desmodium Triquetrum L. Based on Ultra Performance Liquid Chromatography with Photodiode Array Detector Combined with Chemometrics Methods

    Science.gov (United States)

    Zhang, Meiling; Zhao, Cui; Liang, Xianrui; Ying, Yin; Han, Bing; Yang, Bo; Jiang, Cheng

    2016-01-01

    A fingerprinting approach was developed by means of ultra high-performance liquid chromatography with photodiode array detector for the quality control of Desmodium triquetrum L., an herbal medicine widely used for clinical purposes. Ten batches of raw material samples of D. triquetrum were collected from different regions of China. All UPLC analyses were carried out on a Waters ACQUITY UPLC BEH shield RP18 column (2.1 × 50 mm, 1.7 µm particle size) at 60°C, with a gradient mobile phase composed of 0.1% aqueous formic acid and acetonitrile at a flow rate of 0.45 mL/min. The method validation results demonstrated the developed method possessing desirable reproducibility, efficiency, and allowing fingerprint analysis in one chromatographic run within 13 min. The quality assessment was achieved by using chemometrics methods including similarity analysis, hierarchical clustering analysis and principal component analysis. The developed method can be used for further quality control of D. triquetrum. PMID:26791345

  6. Micro-Raman spectroscopy and chemometrical analysis for the distinction of copper phthalocyanine polymorphs in paint layers.

    Science.gov (United States)

    Defeyt, C; Van Pevenage, J; Moens, L; Strivay, D; Vandenabeele, P

    2013-11-01

    In art analysis, copper phthalocyanine (CuPc) is often identified as an important pigment (PB15) in 20th century artworks. Raman spectroscopy is a very valuable technique for the detection of this pigment in paint systems. However, PB15 is used in different polymorphic forms and identification of the polymorph could retrieve information on the production process of the pigment at the moment. Raman spectroscopy, being a molecular spectroscopic method of analysis, is able to discriminate between polymorphs of crystals. However, in the case of PB15, spectral interpretation is not straightforward, and Raman data treatment requires some improvements concerning the PB15 polymorphic discrimination in paints. Here, Raman spectroscopy is combined with chemometrical analysis in order to develop a procedure allowing us to identify the PB15 crystalline structure in painted layers and in artworks. The results obtained by Linear Discriminant Analysis (LDA), using intensity ratios as variables, demonstrate the ability of this procedure to predict the crystalline structure of a PB15 pigment in unknown paint samples. Copyright © 2013 Elsevier B.V. All rights reserved.

  7. Chemical characterization of two morphologically related Espeletia (Asteraceae species and chemometric analysis based on essential oil components

    Directory of Open Access Journals (Sweden)

    Guillermo F. Padilla-González

    Full Text Available ABSTRACT In this study, a comprehensive phytochemical characterization of two morphologically related species from the genus Espeletia Mutis ex Bonpl., namely, Espeletia grandiflora Humb. & Bonpl. and Espeletia killipii Cuatrec., Asteraceae, has been performed by gas chromatography coupled to flame ionization detection, gas chromatography coupled to mass spectrometry and ultra-high performance liquid chromatography coupled to ultraviolet and high-resolution mass spectrometry. Analysis of ethanol extracts (70%, v/v from leaves and concomitant compound dereplication allowed the identification of major peaks, most of them new reports for the genus Espeletia or the subtribe Espeletiinae. Chemical characterization of resins essential oils indicated several similarities and differences between both species and from other members of the subtribe. Chemometric analysis (hierarchical clustering analysis and orthogonal partial least-squares discriminant analysis applied to the essential oil composition of 31 species from Espeletiinae furthermore allowed the identification of three primary clusters correlated with the taxonomy. Hence, this study underscored qualitative and semiquantitative differences between the chemical composition of leaves and resins of E. grandiflora and E. killipii, provided information on chemotaxonomy and described the presence of different trends in the essential oil composition from species of Espeletiinae.

  8. Phytochemical diversity of cranberry (Vaccinium macrocarpon Aiton) cultivars by anthocyanin determination and metabolomic profiling with chemometric analysis.

    Science.gov (United States)

    Brown, Paula N; Murch, Susan J; Shipley, Paul

    2012-01-11

    Originally native to the eastern United States, American cranberry ( Vaccinium macrocarpon Aiton, family Ericaceae) cultivation of native and hybrid varieties has spread across North America. Herein is reported the phytochemical diversity of five cranberry cultivars (Stevens, Ben Lear, Bergman, Pilgrim, and GH1) collected in the Greater Vancouver Regional District, by anthocyanin content and UPLC-TOF-MS metabolomic profiling. The anthocyanin content for biological replicates (n = 5) was determined as 7.98 ± 5.83, Ben Lear; 7.02 ± 1.75, Bergman; 6.05 ± 2.51, GH1; 3.28 ± 1.88, Pilgrim; and 2.81 ± 0.81, Stevens. Using subtractive metabonomic algorithms 6481 compounds were found conserved across all varietals, with 136 (Ben Lear), 84 (Bergman), 91 (GH1), 128 (Pilgrim), and 165 (Stevens) unique compounds observed. Principal component analysis (PCA) did not differentiate varieties, whereas partial least-squares discriminate analysis (PLS-DA) exhibited clustering patterns. Univariate statistical approaches were applied to the data set, establishing significance of values and assessing quality of the models. Metabolomic profiling with chemometric analysis proved to be useful for characterizing metabonomic changes across cranberry varieties.

  9. Intra-regional classification of grape seeds produced in Mendoza province (Argentina) by multi-elemental analysis and chemometrics tools.

    Science.gov (United States)

    Canizo, Brenda V; Escudero, Leticia B; Pérez, María B; Pellerano, Roberto G; Wuilloud, Rodolfo G

    2018-03-01

    The feasibility of the application of chemometric techniques associated with multi-element analysis for the classification of grape seeds according to their provenance vineyard soil was investigated. Grape seed samples from different localities of Mendoza province (Argentina) were evaluated. Inductively coupled plasma mass spectrometry (ICP-MS) was used for the determination of twenty-nine elements (Ag, As, Ce, Co, Cs, Cu, Eu, Fe, Ga, Gd, La, Lu, Mn, Mo, Nb, Nd, Ni, Pr, Rb, Sm, Te, Ti, Tl, Tm, U, V, Y, Zn and Zr). Once the analytical data were collected, supervised pattern recognition techniques such as linear discriminant analysis (LDA), partial least square discriminant analysis (PLS-DA), k-nearest neighbors (k-NN), support vector machine (SVM) and Random Forest (RF) were applied to construct classification/discrimination rules. The results indicated that nonlinear methods, RF and SVM, perform best with up to 98% and 93% accuracy rate, respectively, and therefore are excellent tools for classification of grapes. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Chemometric analysis reveals links in the formation of fragrant bio-molecules during agarwood (Aquilaria malaccensis) and fungal interactions.

    Science.gov (United States)

    Sen, Supriyo; Dehingia, Madhusmita; Talukdar, Narayan Chandra; Khan, Mojibur

    2017-03-14

    Fragrant agarwood, arguably the costliest wood in the world, is formed by plant-fungal interactions in Aquilaria spp. However, very little is known about this fragrant outcome of interaction. Therefore, mimicking the ancient traditions of agarwood production in Assam (Northeast India), a chemometric assessment of the agarwood-fungus interaction was made by chemical profiling (GC-MS) coupled with statistical analysis (principal component, correlation network analysis) across three platforms, viz. callus, juvenile plants and resinous wood-chips with an associated Fusarium. In the study of callus-fungus interaction, increased accumulation of key aroma compounds such as pentatriacontane {fold change (log2FC) = 3.47)}, 17-pentatriacontene (log2FC = 2.95), tetradecane, 2-methyl- (log2FC = 1.10) over callus and activation of pathways related to defense and secondary metabolism indicated links to aroma production. Study on fungal interactions in juvenile plants and resinous wood-chips indicated formation of terpenoid precursors (e.g. farnesol, geranylgeraniol acetate) and agarwood sesquiterpenes (e.g. agarospirol, γ-eudesmol). Correlation network analysis revealed the possible regulation of sesquiterpene biosynthesis involving squalene. Also a direct role of fungus in aroma (e.g. dodecane, 4-methyl-, tetracosane) was highlighted. Appearance of fragrant molecules unknown to agarwood during interaction featured as a new possibility for future research.

  11. Quality evaluation of Polygonum multiflorum in China based on HPLC analysis of hydrophilic bioactive compounds and chemometrics.

    Science.gov (United States)

    Han, D Q; Zhao, J; Xu, J; Peng, H S; Chen, X J; Li, S P

    2013-01-01

    Polygonum multiflorum is one of the most commonly used Chinese medicines. In this study, an effective pressurized water extraction and HPLC method was developed for first simultaneous determination of 8 hydrophilic compounds, including gallic acid, Hypaphorine, Catechin, Proanthocyanidin B1, Epicatechin, Proanthocyanidin B2, Emodin-8-O-β-d-glucopyranoside, stilbene glycosides, in P. multiflorum. The analysis was performed on a Zorbax SB-AQ column with gradient elution of 0.05% phosphoric acid aqueous solution and acetonitrile in 45 min. All calibration curves showed good linearity (R(2)>0.9994) within test ranges. The LOD and LOQ were lower than 0.2 and 1.0 μg/mL on column, respectively. RSD for intra- and inter-day of 8 analytes were less than 4.1% and 4.0%, respectively, and the overall recovery was 96.0-100.7%. The validated method was successfully applied to quantification of 8 hydrophilic compounds in samples of P. multiflorum from different locations of China. Chemometrics such as principal component analysis (PCA) and hierarchical clustering analysis (HCA) were used to evaluate homogeneity of P. multiflorum in China, which suggested that their quality homogeneity was good. Copyright © 2012 Elsevier B.V. All rights reserved.

  12. APPLICATION OF CHEMOMETRICS FOR ANALYSIS OF BIOAEROSOLS BY FLOW-OPTICAL METHOD

    Directory of Open Access Journals (Sweden)

    E. S. Khudyakov

    2016-01-01

    Full Text Available Subject of Research. The informativity of detection channels for bioaerosol analyzer is investigated. Analyzer operation is based on flow-optical method. Method. Measurements of fluorescence and the light scattering of separate bioaerosol particles were performed in five and two spectral ranges, correspondingly. The signals of soil dust particles were registered and used as an imitation of background atmospheric particles. For fluorescenceinduction of bioaerosol particles we used light sources: a laser one with a wavelength equal to 266 nm and 365 nm LED source.Main Results. Using chemometric data processing the classification of informative parameters has been performed and three most significant parameters have been chosen which account for 72% of total data variance. Testing has been done using SIMCA and k-NN methods. It has been proved that the use of the original and the reduced sets of three parameters produces comparable accuracy for classification of bioaerosols. Practical Relevance. The possibility of rapid detection and identification of bioaerosol particles of 1-10 microns respirable fraction (hindering in the human respiratory system by flow-optical method on a background of non-biological particles is demonstrated. The most informative optical spectral ranges for development of compact and inexpensive analyzer are chosen.

  13. Chemometric models for the quantitative descriptive sensory analysis of Arabica coffee beverages using near infrared spectroscopy.

    Science.gov (United States)

    Ribeiro, J S; Ferreira, M M C; Salva, T J G

    2011-02-15

    Mathematical models based on chemometric analyses of the coffee beverage sensory data and NIR spectra of 51 Arabica roasted coffee samples were generated aiming to predict the scores of acidity, bitterness, flavour, cleanliness, body and overall quality of coffee beverage. Partial least squares (PLS) were used to construct the models. The ordered predictor selection (OPS) algorithm was applied to select the wavelengths for the regression model of each sensory attribute in order to take only significant regions into account. The regions of the spectrum defined as important for sensory quality were closely related to the NIR spectra of pure caffeine, trigonelline, 5-caffeoylquinic acid, cellulose, coffee lipids, sucrose and casein. The NIR analyses sustained that the relationship between the sensory characteristics of the beverage and the chemical composition of the roasted grain were as listed below: 1 - the lipids and proteins were closely related to the attribute body; 2 - the caffeine and chlorogenic acids were related to bitterness; 3 - the chlorogenic acids were related to acidity and flavour; 4 - the cleanliness and overall quality were related to caffeine, trigonelline, chlorogenic acid, polysaccharides, sucrose and protein. Copyright © 2010 Elsevier B.V. All rights reserved.

  14. Analysis of car shredder polymer waste with Raman mapping and chemometrics

    Directory of Open Access Journals (Sweden)

    B. Vajna

    2012-02-01

    Full Text Available A novel evaluation method was developed for Raman microscopic quantitative characterization of polymer waste. Car shredder polymer waste was divided into different density fractions by magnetic density separation (MDS technique, and each fraction was investigated by Raman mapping, which is capable of detecting the components being present even in low concentration. The only method available for evaluation of the mapping results was earlier to assign each pixel to a component visually and to count the number of different polymers on the Raman map. An automated method is proposed here for pixel classification, which helps to detect the different polymers present and enables rapid assignment of each pixel to the appropriate polymer. Six chemometric methods were tested to provide a basis for the pixel classification, among which multivariate curve resolution-alternating least squares (MCR-ALS provided the best results. The MCR-ALS based pixel identification method was then used for the quantitative characterization of each waste density fraction, where it was found that the automated method yields accurate results in a very short time, as opposed to manual pixel counting method which may take hours of human work per dataset.

  15. Multi-component analysis in sun-dried and sulfur-fumigated Angelicae Sinensis Radix by single marker quantitation and chemometric discrimination.

    Science.gov (United States)

    Lou, Yajing; Cai, Hao; Liu, Xiao; Cao, Gang; Tu, Sicong; Li, Songlin; Ma, Xiaoqing; Qin, Kunming; Cai, Baochang

    2014-01-01

    A new method has been developed for the simultaneous determination of ferulic acid, senkyunolide A, and Z-ligustilide in Angelicae Sinensis Radix before and after sulfur-fumigation using quantitative analysis of multi-components by a single marker (QAMS). The feasibility and accuracy of QAMS were checked by the external standard method, and various high-performance liquid chromatographic instruments and chromatographic conditions were investigated to verify its applicability. Using ferulic acid as the internal reference substance, and the contents of senkyunolide A and Z-ligustilide were calculated according to relative correction factors by high-performance liquid chromatography. Meanwhile, the influence of sulfur-fumigation on these chemical components in Angelicae Sinensis Radix were evaluated and discriminated by chromatographic fingerprint and chemometrics. There was no significant difference observed between the QAMS method and the external standard method. Furthermore, sulfur-fumigation reduced the contents of ferulic acid, senkyunolide A, and Z-ligustilide in Angelicae Sinensis Radix by some degree, and the sun-drying and sulfur-fumigation processing could be easily discriminated by chromatographic fingerprint and chemometrics. QAMS is a convenient and accurate approach to analyzing multi-component when reference substances are unavailable, simultaneously, chemometrics is an effective way to discriminate sun-dried and sulfur-fumigated Angelicae Sinensis Radix.

  16. ¹H-NMR Profiling and Chemometric Analysis of Selected Honeys from South Africa, Zambia, and Slovakia.

    Science.gov (United States)

    Olawode, Emmanuel O; Tandlich, Roman; Cambray, Garth

    2018-03-05

    Honey is the natural sweet substance produced by honeybee from nectar or honeydew, exhibiting several nutritional and health benefits. It contains a complex mixture of compounds in different proportions, with sugars being the main component. The physicochemical characteristics of ten honeys were evaluated; represented by five, three, and two from South Africa, Slovakia, and Zambia, respectively. The range of values for the pH (3.75-4.38), electrical conductivity (99-659 µS/cm), and moisture content (14.2-17.7%) are within the recommended limits for quality honeys. ¹H-NMR (Nuclear Magnetic Resonance) profiling of the honeys in D₂O was determined, and the data were analysed by chemometrics. This method is fast, reproducible, and sample pre-treatment is not necessary. The ¹H-NMR fingerprints of various chemical shift regions showed similarity or dissimilarity across geographical origins that are useful for identification, detection of adulteration, and quality control. The principal component analysis PCA and partial linear square discriminant analysis PLS-DA of the ¹H-NMR profiles successively categorises the honeys into two chemically related groups. The R² values are higher than the corresponding Q² values for all samples, confirming the reliability of the model. Honeys in the same cluster contain similar metabolites and belong to the same botanic or floral origin.

  17. Use of chemometric and quantum-mechanical methods in the analysis of bioactive terpenoids and phenylpropanoids against the Aedes aegypti

    Directory of Open Access Journals (Sweden)

    Reginaldo Bezerra dos Santos

    2010-01-01

    Full Text Available Dengue fever is one of the main public health problems in the world. Many mosquitoes have developed resistance to the conventional insecticides used. Thus, the search for vegetable extracts and natural substances as alternative insecticides has increased. In this study, chemometric methods were employed to classify a group of terpenoid and phenylpropanoid compounds with biological activity against the larval of the A. aegypti mosquitoes. The AM1 (Austin Model 1 method was used to calculate a set of molecular descriptors (properties for the studied compounds. Then, the descriptors were analyzed using the following methods of pattern recognition: Principal Component Analysis (PCA and Hierarchical Clustering Analysis (HCA. The PCA and HCA methods have shown to be very effective for the classification of the study compounds in two groups (active and inactive. The electronic variables EHOMO-1, EHOMO-2, ELUMO, ELUMO+2, and the structural LogP were used to classify as active and inactive compounds. In most studied compounds, the variables responsible for separating active from inactive compounds were electronic descriptors. Thus, it can be concluded that electronic effects play a fundamental role in the interaction between biological receptor and terpenoid and phenylpropanoid compounds with activity against larval A. aegypti mosquitoes.

  18. Exploring 5-nitrofuran derivatives against nosocomial pathogens: synthesis, antimicrobial activity and chemometric analysis.

    Science.gov (United States)

    Zorzi, Rodrigo Rocha; Jorge, Salomão Dória; Palace-Berl, Fanny; Pasqualoto, Kerly Fernanda Mesquita; Bortolozzo, Leandro de Sá; de Castro Siqueira, André Murillo; Tavares, Leoberto Costa

    2014-05-15

    The burden of nosocomial or health care-associated infection (HCAI) is increasing worldwide. According to the World Health Organization (WHO), it is several fold higher in low- and middle-income countries. Considering the multidrug-resistant infections, the development of new and more effective drugs is crucial. Herein, two series (I and II) of 5-nitrofuran derivatives were designed, synthesized and assayed against microorganisms, including Gram-positive and -negative bacteria, and fungi. The pathogens screened was directly related to either the most currently relevant HCAI, or to multidrug-resistant infection caused by MRSA/VRSA strains, for instance. The sets I and II were composed by substituted-[N'-(5-nitrofuran-2-yl)methylene]benzhydrazide and 3-acetyl-5-(substituted-phenyl)-2-(5-nitro-furan-2-yl)-2,3-dihydro-1,3,4-oxadiazole compounds, respectively. The selection of the substituent groups was based upon physicochemical properties, such as hydrophobicity and electronic effect. The compounds have showed better activity against Staphylococcus aureus, Escherichia coli, and Enterococcus faecalis. The findings from S. aureus strain, which was more susceptible, were used to investigate the intersamples and intervariables relationships by applying chemometric methods. It is noteworthy that the compound 4-butyl-[N'-(5-nitrofuran-2-yl)methylene]benzhydrazide has showed similar MIC value to vancomycin, which is the reference drug for multidrug-resistant S. aureus infections. Taken the findings together, the 5-nitrofuran derivatives might be indeed considered as promising hits to develop novel antimicrobial drugs to fight against nosocomial infection. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. Analysis of chicken fat as adulterant in butter using fourier transform infrared spectroscopy and chemometrics

    Directory of Open Access Journals (Sweden)

    Nurrulhidayah, A. F.

    2013-09-01

    Full Text Available Butter may be adulterated with cheaper animal fats, such as chicken fat (CF. Thus, the detection and quantification of butter adulteration with CF was monitored using Fourier transform infrared (FTIR spectroscopy, combined with chemometric of partial least square (PLS at the frequency regions of 1200-1000cm–1. FTIR measurements were made on pure butter and that adulterated with varying concentrations of CF (0-100% w/w in butter. PLS calibration exhibits a good relationship between actual and FTIR predicted values of CF with a coefficient of determination (R2 of 0.981. The root means standard error of calibration (RMSEC and during cross validation (RMSECV obtained using six principal components (PCs are 2.08 and 4.33% v/v, respectively.La mantequilla puede ser adulterada con grasas animales más baratas, como la grasa de pollo (GP. Así, la detección y cuantificación de la adulteración de mantequilla con GP se controló usando transformada de Fourier infrarroja (FTIR, combinada con técnicas quimiométricas de mínimos cuadrados parciales (PLS en las regiones de frecuencia de 1200-1000cm–1. Las medidas FTIR se realizaron sobre la mantequilla pura y adulterada con diferentes concentraciones de GP (0-100% w/w en la mantequilla. La calibración de PLS presenta una buena relación entre los valores reales y los valores pronosticados de FTIR de la GP con un coeficiente de determinación (R2 de 0.981. La raíz del error estándar de calibración (RMSEC durante la validación cruzada (RMSECV obtenido utilizando seis componentes principales (PC fueron 2,08 y 4,33% v/v, respectivamente.

  20. Chemometric analysis for identification of botanical raw materials for pharmaceutical use: a case study using Panax notoginseng.

    Science.gov (United States)

    Zhu, Jieqiang; Fan, Xiaohui; Cheng, Yiyu; Agarwal, Rajiv; Moore, Christine M V; Chen, Shaw T; Tong, Weida

    2014-01-01

    The overall control of the quality of botanical drugs starts from the botanical raw material, continues through preparation of the botanical drug substance and culminates with the botanical drug product. Chromatographic and spectroscopic fingerprinting has been widely used as a tool for the quality control of herbal/botanical medicines. However, discussions are still on-going on whether a single technique provides adequate information to control the quality of botanical drugs. In this study, high performance liquid chromatography (HPLC), ultra performance liquid chromatography (UPLC), capillary electrophoresis (CE) and near infrared spectroscopy (NIR) were used to generate fingerprints of different plant parts of Panax notoginseng. The power of these chromatographic and spectroscopic techniques to evaluate the identity of botanical raw materials were further compared and investigated in light of the capability to distinguishing different parts of Panax notoginseng. Principal component analysis (PCA) and clustering results showed that samples were classified better when UPLC- and HPLC-based fingerprints were employed, which suggested that UPLC- and HPLC-based fingerprinting are superior to CE- and NIR-based fingerprinting. The UPLC- and HPLC- based fingerprinting with PCA were able to correctly distinguish between samples sourced from rhizomes and main root. Using chemometrics and its ability to distinguish between different plant parts could be a powerful tool to help assure the identity and quality of the botanical raw materials and to support the safety and efficacy of the botanical drug products.

  1. Chemometric analysis for identification of botanical raw materials for pharmaceutical use: a case study using Panax notoginseng.

    Directory of Open Access Journals (Sweden)

    Jieqiang Zhu

    Full Text Available The overall control of the quality of botanical drugs starts from the botanical raw material, continues through preparation of the botanical drug substance and culminates with the botanical drug product. Chromatographic and spectroscopic fingerprinting has been widely used as a tool for the quality control of herbal/botanical medicines. However, discussions are still on-going on whether a single technique provides adequate information to control the quality of botanical drugs. In this study, high performance liquid chromatography (HPLC, ultra performance liquid chromatography (UPLC, capillary electrophoresis (CE and near infrared spectroscopy (NIR were used to generate fingerprints of different plant parts of Panax notoginseng. The power of these chromatographic and spectroscopic techniques to evaluate the identity of botanical raw materials were further compared and investigated in light of the capability to distinguishing different parts of Panax notoginseng. Principal component analysis (PCA and clustering results showed that samples were classified better when UPLC- and HPLC-based fingerprints were employed, which suggested that UPLC- and HPLC-based fingerprinting are superior to CE- and NIR-based fingerprinting. The UPLC- and HPLC- based fingerprinting with PCA were able to correctly distinguish between samples sourced from rhizomes and main root. Using chemometrics and its ability to distinguish between different plant parts could be a powerful tool to help assure the identity and quality of the botanical raw materials and to support the safety and efficacy of the botanical drug products.

  2. A Combination of Chemometrics and Quantum Mechanics Methods Applied to Analysis of Femtosecond Transient Absorption Spectrum of Ortho-Nitroaniline

    Science.gov (United States)

    Yi, Jing; Xiong, Ying; Cheng, Kemei; Li, Menglong; Chu, Genbai; Pu, Xuemei; Xu, Tao

    2016-01-01

    A combination of the advanced chemometrics method with quantum mechanics calculation was for the first time applied to explore a facile yet efficient analysis strategy to thoroughly resolve femtosecond transient absorption spectroscopy of ortho-nitroaniline (ONA), served as a model compound of important nitroaromatics and explosives. The result revealed that the ONA molecule is primarily excited to S3 excited state from the ground state and then ultrafast relaxes to S2 state. The internal conversion from S2 to S1 occurs within 0.9 ps. One intermediate state S* was identified in the intersystem crossing (ISC) process, which is different from the specific upper triplet receiver state proposed in some other nitroaromatics systems. The S1 state decays to the S* one within 6.4 ps and then intersystem crossing to the lowest triplet state within 19.6 ps. T1 was estimated to have a lifetime up to 2 ns. The relatively long S* state and very long-lived T1 one should play a vital role as precursors to various nitroaromatic and explosive photoproducts.

  3. A Combination of Chemometrics and Quantum Mechanics Methods Applied to Analysis of Femtosecond Transient Absorption Spectrum of Ortho-Nitroaniline

    Science.gov (United States)

    Yi, Jing; Xiong, Ying; Cheng, Kemei; Li, Menglong; Chu, Genbai; Pu, Xuemei; Xu, Tao

    2016-01-01

    A combination of the advanced chemometrics method with quantum mechanics calculation was for the first time applied to explore a facile yet efficient analysis strategy to thoroughly resolve femtosecond transient absorption spectroscopy of ortho-nitroaniline (ONA), served as a model compound of important nitroaromatics and explosives. The result revealed that the ONA molecule is primarily excited to S3 excited state from the ground state and then ultrafast relaxes to S2 state. The internal conversion from S2 to S1 occurs within 0.9 ps. One intermediate state S* was identified in the intersystem crossing (ISC) process, which is different from the specific upper triplet receiver state proposed in some other nitroaromatics systems. The S1 state decays to the S* one within 6.4 ps and then intersystem crossing to the lowest triplet state within 19.6 ps. T1 was estimated to have a lifetime up to 2 ns. The relatively long S* state and very long-lived T1 one should play a vital role as precursors to various nitroaromatic and explosive photoproducts. PMID:26781083

  4. Black Heart Detection in White Radish by Hyperspectral Transmittance Imaging Combined with Chemometric Analysis and a Successive Projections Algorithm

    Directory of Open Access Journals (Sweden)

    Dajie Song

    2016-09-01

    Full Text Available Radishes with black hearts will lose edible value and cause food safety problems, so it is important to detect and remove the defective ones before processing and consumption. A hyperspectral transmittance imaging system with 420 wavelengths was developed to capture images from white radishes. A successive-projections algorithm (SPA was applied with 10 wavelengths selected to distinguish defective radishes with black hearts from normal samples. Pearson linear correlation coefficients were calculated to further refine the set of wavelengths with 4 wavelengths determined. Four chemometric classifiers were developed for classification of normal and defective radishes, using 420, 10 and 4 wavelengths as input variables. The overall classifying accuracy based on the four classifiers were 95.6%–100%. The highest classification with 100% was obtained with a back propagation artificial neural network (BPANN for both calibration and prediction using 420 and 10 wavelengths. Overall accuracies of 98.4% and 97.8% were obtained for calibration and prediction, respectively, with Fisher's linear discriminant analysis (FLDA based on 4 wavelengths, and was better than the other three classifiers. This indicated that the developed hyperspectral transmittance imaging was suitable for black heart detection in white radishes with the optimal wavelengths, which has potential for fast on-line discrimination before food processing or reaching storage shelves.

  5. Discriminatory components retracing strategy for monitoring the preparation procedure of Chinese patent medicines by fingerprint and chemometric analysis.

    Directory of Open Access Journals (Sweden)

    Shuai Yao

    Full Text Available Chinese patent medicines (CPM, generally prepared from several traditional Chinese medicines (TCMs in accordance with specific process, are the typical delivery form of TCMs in Asia. To date, quality control of CPMs has typically focused on the evaluation of the final products using fingerprint technique and multi-components quantification, but rarely on monitoring the whole preparation process, which was considered to be more important to ensure the quality of CPMs. In this study, a novel and effective strategy labeling "retracing" way based on HPLC fingerprint and chemometric analysis was proposed with Shenkang injection (SKI serving as an example to achieve the quality control of the whole preparation process. The chemical fingerprints were established initially and then analyzed by similarity, principal component analysis (PCA and partial least squares-discriminant analysis (PLS-DA to evaluate the quality and to explore discriminatory components. As a result, the holistic inconsistencies of ninety-three batches of SKIs were identified and five discriminatory components including emodic acid, gallic acid, caffeic acid, chrysophanol-O-glucoside, and p-coumaroyl-O-galloyl-glucose were labeled as the representative targets to explain the retracing strategy. Through analysis of the targets variation in the corresponding semi-products (ninety-three batches, intermediates (thirty-three batches, and the raw materials, successively, the origins of the discriminatory components were determined and some crucial influencing factors were proposed including the raw materials, the coextraction temperature, the sterilizing conditions, and so on. Meanwhile, a reference fingerprint was established and subsequently applied to the guidance of manufacturing. It was suggested that the production process should be standardized by taking the concentration of the discriminatory components as the diagnostic marker to ensure the stable and consistent quality for multi

  6. Effect of genetic algorithm as a variable selection method on different chemometric models applied for the analysis of binary mixture of amoxicillin and flucloxacillin: A comparative study

    Science.gov (United States)

    Attia, Khalid A. M.; Nassar, Mohammed W. I.; El-Zeiny, Mohamed B.; Serag, Ahmed

    2016-03-01

    Different chemometric models were applied for the quantitative analysis of amoxicillin (AMX), and flucloxacillin (FLX) in their binary mixtures, namely, partial least squares (PLS), spectral residual augmented classical least squares (SRACLS), concentration residual augmented classical least squares (CRACLS) and artificial neural networks (ANNs). All methods were applied with and without variable selection procedure (genetic algorithm GA). The methods were used for the quantitative analysis of the drugs in laboratory prepared mixtures and real market sample via handling the UV spectral data. Robust and simpler models were obtained by applying GA. The proposed methods were found to be rapid, simple and required no preliminary separation steps.

  7. Chemometric Analysis of High Molecular Mass Glutenin Subunits and Image Data of Bread Crumb Structure from Croatian Wheat Cultivars

    Directory of Open Access Journals (Sweden)

    Zorica Jurković

    2002-01-01

    Full Text Available The aim of this work is to investigate functional relationships among wheat properties, high molecular mass (weight (HMW glutenin subunits and bread quality produced from eleven Croatian wheat cultivars by chemometric analysis. HMW glutenin subunits were fractionated by sodium dodecylsulfate polyacrylamid gel electrophoresis (SDS-PAGE and subsequently analysed by scanning densitometry in order to quantify HMW glutenin fractions. Wheat properties are characterised by four variables: protein content, sedimentation value, wet gluten and gluten index. Bread quality is assessed by the standard measurement of loaf volume, and visual quality of bread slice is quantified by 8 parameters by the use of computer image analysis. The data matrix with 21 columns (measured variables and 11 rows (cultivars is analysed for determination of number of latent variables. It was found that the first two latent variables account for 92, 85 and 87 % of variance of wheat quality properties, HMW glutenin fractions, and the bread quality parameters, respectively. Classification and functional relationships are discussed from the case data (cultivars and variable projections to the planes of the first two latent variables. Between Glu-D1y proportion and the bread quality parameters (standard parameter loaf volume and bread crumb cell area fraction determined by image analysis the strongest positive correlations are found r = 0.651 and r = 0.885, respectively. Between Glu-B1x proportion and the bread quality parameters the strongest negative correlations are found r =-0.535 and r = –0.841, respectively. The results are discussed in view of possible development of new and improvement of existing wheat cultivars and optimisation of bread production.

  8. A novel exploratory chemometric approach to environmental monitorring by combining block clustering with Partial Least Square (PLS) analysis.

    Science.gov (United States)

    Nica, Dragos V; Bordean, Despina Maria; Pet, Ioan; Pet, Elena; Alda, Simion; Gergen, Iosif

    2013-08-30

    Given the serious threats posed to terrestrial ecosystems by industrial contamination, environmental monitoring is a standard procedure used for assessing the current status of an environment or trends in environmental parameters. Measurement of metal concentrations at different trophic levels followed by their statistical analysis using exploratory multivariate methods can provide meaningful information on the status of environmental quality. In this context, the present paper proposes a novel chemometric approach to standard statistical methods by combining the Block clustering with Partial least square (PLS) analysis to investigate the accumulation patterns of metals in anthropized terrestrial ecosystems. The present study focused on copper, zinc, manganese, iron, cobalt, cadmium, nickel, and lead transfer along a soil-plant-snai food chain, and the hepatopancreas of the Roman snail (Helix pomatia) was used as a biological end-point of metal accumulation. Block clustering deliniates between the areas exposed to industrial and vehicular contamination. The toxic metals have similar distributions in the nettle leaves and snail hepatopancreas. PLS analysis showed that (1) zinc and copper concentrations at the lower trophic levels are the most important latent factors that contribute to metal accumulation in land snails; (2) cadmium and lead are the main determinants of pollution pattern in areas exposed to industrial contamination; (3) at the sites located near roads lead is the most threatfull metal for terrestrial ecosystems. There were three major benefits by applying block clustering with PLS for processing the obtained data: firstly, it helped in grouping sites depending on the type of contamination. Secondly, it was valuable for identifying the latent factors that contribute the most to metal accumulation in land snails. Finally, it optimized the number and type of data that are best for monitoring the status of metallic contamination in terrestrial ecosystems

  9. Chemometric analysis of fatty acids profile of bream (Abramis brama, ruffe (Gymnocephalus cernua and perch (Perca fluviatilis meat from Lake Gopło and Włocławski Dam Reservoir

    Directory of Open Access Journals (Sweden)

    Bogumila Kupcewicz

    2012-01-01

    Full Text Available The 18 fatty acid profiles have been determined in 63 samples of muscles from three freshwater fish species: bream, ruffe and perch by gas chromatography method. The fish were collected in natural condition from two reservoirs located in central Poland: Lake Gopło and Włocławski Reservoir. A chemometric study with the use of hierarchical cluster analysis (HCA, principal component (PCA and stepwise linear discrimination analysis (LDA was applied to characterize, classify and differentiate collected samples. The chemometric techniques by using fatty acids content as descriptors allow clearly distinguish 6 groups according to fish species and their geographical origin.

  10. A nested multivariate chemometrics based calibration strategy for direct trace biometal analysis in soft tissue utilizing Energy Dispersive X-Ray Fluorescence (EDXRF) and scattering spectrometry.

    Science.gov (United States)

    Okonda, J J; Angeyo, K H; Mangala, J M; Kisia, S M

    2017-11-01

    Compton scatter-modulated fluorescence and multivariate chemometric (artificial neural network (ANN) and principal component regression (PCR)) calibration strategy was explored for direct rapid trace biometals (Mn, Fe, Cu, Zn, Se) analysis in "complex" matrices (model soft tissues). This involved spectral feature selection (multiple fluorescence signatures) normalized to or in conjunction with Compton scatter. ANN model resulted in more accurate trace biometal determination (R 2 >0.9) compared to PCR. Hybrid nested (ANN and PCR) approach led to optimized accurate biometals' concentrations in Oyster tissue (≤ ± 10%). Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Simultaneous determination of trace-levels of alloying zinc and copper by semi-mercury-free potentiometric stripping analysis with chemometric data treatment

    DEFF Research Database (Denmark)

    Andersen, Jens Enevold Thaulov; Hansen, Elo Harald

    1998-01-01

    Assays of copper and zinc in brass samples were performed by Semi-Mercury Free Potentiometric Stripping Analysis (S-MF PSA) using a thin-film mercury covered glassy-carbon working electrode and dissolved oxygen as oxidizing agent during the stripping step. The stripping peak transients were resol...... by factors in the range 2.104 - 5.105 which resulted in quantification of the copper and of zinc contents comparable to the specified values within 10%. On the basis of the chemometric treatment, an empirical expression is deduced relating the stripping time to the recorded potential....

  12. Chemometric and multivariate statistical analysis of time-of-flight secondary ion mass spectrometry spectra from complex Cu-Fe sulfides.

    Science.gov (United States)

    Kalegowda, Yogesh; Harmer, Sarah L

    2012-03-20

    Time-of-flight secondary ion mass spectrometry (TOF-SIMS) spectra of mineral samples are complex, comprised of large mass ranges and many peaks. Consequently, characterization and classification analysis of these systems is challenging. In this study, different chemometric and statistical data evaluation methods, based on monolayer sensitive TOF-SIMS data, have been tested for the characterization and classification of copper-iron sulfide minerals (chalcopyrite, chalcocite, bornite, and pyrite) at different flotation pulp conditions (feed, conditioned feed, and Eh modified). The complex mass spectral data sets were analyzed using the following chemometric and statistical techniques: principal component analysis (PCA); principal component-discriminant functional analysis (PC-DFA); soft independent modeling of class analogy (SIMCA); and k-Nearest Neighbor (k-NN) classification. PCA was found to be an important first step in multivariate analysis, providing insight into both the relative grouping of samples and the elemental/molecular basis for those groupings. For samples exposed to oxidative conditions (at Eh ~430 mV), each technique (PCA, PC-DFA, SIMCA, and k-NN) was found to produce excellent classification. For samples at reductive conditions (at Eh ~ -200 mV SHE), k-NN and SIMCA produced the most accurate classification. Phase identification of particles that contain the same elements but a different crystal structure in a mixed multimetal mineral system has been achieved.

  13. Chemometrics-enhanced one-dimensional/comprehensive two-dimensional gas chromatographic analysis for bioactive terpenoids and phthalides in Chaihu Shugan San essential oils.

    Science.gov (United States)

    He, Min; Yang, Zhi-Yu; Yang, Tian-Biao; Ye, Ying; Nie, Juan; Hu, Yong; Yan, Pan

    2017-05-01

    Chemometrics-enhanced one-dimensional/comprehensive two-dimensional gas chromatographic (GC/GC×GC) technologies, were used to explore the compositions of Chaihu Shugan San essential oils, that were extracted from the herbal formulae by different schemes. We have shown that chemometric resolution using gas chromatographic- mass spectrometry (GC-MS) could be used for the qualitative and quantitative analysis of the majority of Terpenoids or Phthalides from herb formulae and single herbs. A GC×GC system was further optimized to achieve the increased peak capacity and the enhanced signal of the hydro-distillation sample (CSSh). When hardware bottleneck resulted from very complex sample, chemometric tools were once again applied to recover the stained information in the second dimension ( 2 D) matrix data. Heuristic evolving latent projections (HELP) could be used for two dimensional (2D) sub-matrixes Xi at n spectral detection channels, after three dimensional (3D) data splitting. For a real 3D data matrix, alternating trilinear decomposition (ATLD) algorithm could conduct regularization for an iterative trilinear decomposition procedure, by Moore-Penrose pseudoinverse computations based on singular value decomposition. After retention indices (RI) confirmation, 216 target analytes (terpenoids or phthalides) could be elucidated both in CSSh and in supercritical fluid extract (CSSs). Based on the obtained data, some potential quality markers (Q-markers) were identified which may affect the quality of the products. Finally, a "connectivity map" was plotted to describe the unique mechanisms of tradition Chinese medicine (TCM). Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Evaluation and quantitative analysis of 11 compounds in Morinda officinalis using ultra-high performance liquid chromatography and photodiode array detection coupled with chemometrics.

    Science.gov (United States)

    Zhao, Xiangsheng; Kong, Weijun; Zhou, Yakui; Wei, Jianhe; Yang, Meihua

    2017-10-01

    Morinda officinalis (Rubiaceae) is a traditional Chinese medicine widely used for the treatment of impotence and osteoporosis in clinical therapy. In the present study, a rapid and simple ultra-high performance liquid chromatography with photodiode array detection method was developed and validated for the simultaneous determination of 11 bioactive compounds in M. officinalis. This assay method was validated with respect to linearity (R 2   > 0.9991), precision, repeatability, limit of detection, limit of quantification, and accuracy (with observed recovery rates between 94.21 and 100.38%). The quantitative results revealed significant differences in the concentrations of the selected compounds. Additionally, chemometric methods, including hierarchical clustering analysis, principal component analysis, and partial least-squares discriminate analysis, were applied to compare and sort the 25 batches of M. officinalis samples based on the quantitative data of the analytes. All of the samples were clearly divided into two groups: the Hainan samples were successfully discriminated from the samples from other origins. Simultaneous determination of multiple compounds using the proposed method combined with chemometrics could be a viable strategy to compare and evaluate the quality of M. officinalis. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Analytical fingerprint and chemometrics as phytochemical composition control tools in food supplement analysis: characterization of raspberry bud preparations of different cultivars.

    Science.gov (United States)

    Donno, Dario; Beccaro, Gabriele L; Carlen, Christoph; Ançay, André; Cerutti, Alessandro K; Mellano, Maria Gabriella; Bounous, Giancarlo

    2016-07-01

    The raspberry, Rubus idaeus L., provides several plant parts (as buds) used for food supplements. The aim of this research was to establish a technique for chemical composition control of R. idaeus herbal preparations, using chromatographic methods. These methods allowed us to identify and quantify the main phytochemicals, obtaining a specific phytochemical fingerprint (phytocomplex). Combined with two different chemometric methods - clustering analysis and principal component analysis - the raspberry bud extracts of the different cultivars were efficiently characterized. Rubus idaeus buds were identified as a rich source of anti-inflammatory and antioxidant compounds: organic acids, vitamins and catechins were found to be the most discriminating variables by chemometric techniques to differentiate raspberry cultivars. In particular, catechins (13.25%) and flavonols (8.71%) were the most important polyphenolic classes, followed by cinnamic and benzoic acids. This study developed a useful tool for R. idaeus extract phytochemical characterization that could be applied also for differentiation and composition control of other herbal preparations. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

  16. Direct rapid analysis of trace bioavailable soil macronutrients by chemometrics-assisted energy dispersive X-ray fluorescence and scattering spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Kaniu, M.I., E-mail: ikaniu@uonbi.ac.ke [Institute of Nuclear Science and Technology, University of Nairobi, P.O. Box 30197-00100 Nairobi (Kenya); Angeyo, K.H. [Department of Physics, University of Nairobi, P.O. Box 30197-00100 Nairobi (Kenya); Mwala, A.K. [Department of Land Resource Management and Agricultural Technology, University of Nairobi, P.O. Box 30197-00100 Nairobi (Kenya); Mangala, M.J. [Institute of Nuclear Science and Technology, University of Nairobi, P.O. Box 30197-00100 Nairobi (Kenya)

    2012-06-04

    Highlights: Black-Right-Pointing-Pointer Chemometrics-assisted EDXRFS spectroscopy realizes direct, rapid and accurate analysis of trace bioavailable macronutrients in soils. Black-Right-Pointing-Pointer The method is minimally invasive, involves little sample preparation, short analysis times and is relatively insensitive to matrix effects. Black-Right-Pointing-Pointer This opens up the ability to rapidly characterize large number of samples/matrices with this method. - Abstract: Precision agriculture depends on the knowledge and management of soil quality (SQ), which calls for affordable, simple and rapid but accurate analysis of bioavailable soil nutrients. Conventional SQ analysis methods are tedious and expensive. We demonstrate the utility of a new chemometrics-assisted energy dispersive X-ray fluorescence and scattering (EDXRFS) spectroscopy method we have developed for direct rapid analysis of trace 'bioavailable' macronutrients (i.e. C, N, Na, Mg, P) in soils. The method exploits, in addition to X-ray fluorescence, the scatter peaks detected from soil pellets to develop a model for SQ analysis. Spectra were acquired from soil samples held in a Teflon holder analyzed using {sup 109}Cd isotope source EDXRF spectrometer for 200 s. Chemometric techniques namely principal component analysis (PCA), partial least squares (PLS) and artificial neural networks (ANNs) were utilized for pattern recognition based on fluorescence and Compton scatter peaks regions, and to develop multivariate quantitative calibration models based on Compton scatter peak respectively. SQ analyses were realized with high CMD (R{sup 2} > 0.9) and low SEP (0.01% for N and Na, 0.05% for C, 0.08% for Mg and 1.98 {mu}g g{sup -1} for P). Comparison of predicted macronutrients with reference standards using a one-way ANOVA test showed no statistical difference at 95% confidence level. To the best of the authors' knowledge, this is the first time that an XRF method has demonstrated

  17. Chemometrics-assisted high performance liquid chromatography-diode array detection strategy to solve varying interfering patterns from different chromatographic columns and sample matrices for beverage analysis.

    Science.gov (United States)

    Yin, Xiao-Li; Wu, Hai-Long; Gu, Hui-Wen; Hu, Yong; Wang, Li; Xia, Hui; Xiang, Shou-Xia; Yu, Ru-Qin

    2016-02-26

    This work reports a chemometrics-assisted high performance liquid chromatography-diode array detection (HPLC-DAD) strategy to solve varying interfering patterns from different chromatographic columns and sample matrices for the rapid simultaneous determination of six synthetic colorants in five kinds of beverages with little sample pretreatment. The investigation was performed using two types of LC columns under the same elution conditions. Although analytes using different columns have different co-elution patterns that appear more seriously in complex backgrounds, all colorants were properly resolved by alternating trilinear decomposition (ATLD) method and accurate chromatographic elution profiles, spectral profiles as well as relative concentrations were obtained. The results were confirmed by those obtained from traditional HPLC-UV method at a particular wavelength and the results of both methods were consistent with each other. All results demonstrated that the proposed chemometrics-assisted HPLC-DAD method is accurate, economical and universal, and can be promisingly applied to solve varying interfering patterns from different chromatographic columns and sample matrices for the analysis of complex food samples. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. Chemometrics: A new scenario in herbal drug standardization

    Directory of Open Access Journals (Sweden)

    Ankit Bansal

    2014-08-01

    Full Text Available Chromatography and spectroscopy techniques are the most commonly used methods in standardization of herbal medicines but the herbal system is not easy to analyze because of their complexity of chemical composition. Many cutting-edge analytical technologies have been introduced to evaluate the quality of medicinal plants and significant amount of measurement data has been produced. Chemometric techniques provide a good opportunity for mining more useful chemical information from the original data. Then, the application of chemometrics in the field of medicinal plants is spontaneous and necessary. Comprehensive methods and hyphenated techniques associated with chemometrics used for extracting useful information and supplying various methods of data processing are now more and more widely used in medicinal plants, among which chemometrics resolution methods and principal component analysis (PCA are most commonly used techniques. This review focuses on the recent various important analytical techniques, important chemometrics tools and interpretation of results by PCA, and applications of chemometrics in quality evaluation of medicinal plants in the authenticity, efficacy and consistency. Key words: Chemometrics, HELP, Herbal drugs, PCA, OPA

  19. Near infrared spectroscopy and chemometrics analysis of complex traits in animal physiology

    Science.gov (United States)

    Near infrared reflectance (NIR) applications have been expanding from the traditional framework of small molecule chemical purity and composition (as defined by spectral libraries) to complex system analysis and holistic exploratory approaches to questions in biochemistry, biophysics and environment...

  20. Pulmonary vasculature in dogs assessed by three-dimensional fractal analysis and chemometrics

    DEFF Research Database (Denmark)

    Müller, Anna V; Marschner, Clara B; Kristensen, Annemarie T

    2017-01-01

    Fractal analysis of canine pulmonary vessels could allow quantification of their space-filling properties. Aims of this prospective, analytical, cross-sectional study were to describe methods for reconstructing three dimensional pulmonary arterial vascular trees from computed tomographic pulmonary...... angiogram, applying fractal analyses of these vascular trees in dogs with and without diseases that are known to predispose to thromboembolism, and testing the hypothesis that diseased dogs would have a different fractal dimension than healthy dogs. A total of 34 dogs were sampled. Based on computed...... for each dog using a semiautomated segmentation technique. Vascular three-dimensional reconstructions were then evaluated using fractal analysis. Fractal dimensions were analyzed, by group, using analysis of variance and principal component analysis. Fractal dimensions were significantly different among...

  1. Determining the geographical origin of Sechium edule fruits by multielement analysis and advanced chemometric techniques.

    Science.gov (United States)

    Hidalgo, Melisa J; Fechner, Diana C; Marchevsky, Eduardo J; Pellerano, Roberto G

    2016-11-01

    This paper describes the determination and evaluation of the major and trace element composition (Al, As, Ba, Ca, Cd, Co, Cu, Fe, K, Mg, Mn, Na, Pb, Sr and Zn) of Sechium edule (Jacq) Swartz fruits collected from four different places of production in Corrientes province, Argentina. Element concentrations were determined by using inductively coupled plasma optical emission spectrometry (ICP OES) after microwave digestion. The accuracy was confirmed with standard reference material of spinach leaves (NIST, 1570a) and spiking tests. Principal component analysis (PCA), linear discriminant analysis (LDA), k-nearest neighbors (kNN), partial least square-discriminant analysis (PLS-DA) and support vector machine (SVM) were applied to the results for discriminating the geographical origin of S. edule fruits. Finally, the LDA method was found to perform best with up to 90% accuracy rate based on the following elements: Ca, Ba, Cu, Mn, Na, Sr, and Zn. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Pulmonary vasculature in dogs assessed by three-dimensional fractal analysis and chemometrics.

    Science.gov (United States)

    Müller, Anna V; Marschner, Clara B; Kristensen, Annemarie T; Wiinberg, Bo; Sato, Amy F; Rubio, Jose M A; McEvoy, Fintan J

    2017-11-01

    Fractal analysis of canine pulmonary vessels could allow quantification of their space-filling properties. Aims of this prospective, analytical, cross-sectional study were to describe methods for reconstructing three dimensional pulmonary arterial vascular trees from computed tomographic pulmonary angiogram, applying fractal analyses of these vascular trees in dogs with and without diseases that are known to predispose to thromboembolism, and testing the hypothesis that diseased dogs would have a different fractal dimension than healthy dogs. A total of 34 dogs were sampled. Based on computed tomographic pulmonary angiograms findings, dogs were divided in three groups: diseased with pulmonary thromboembolism (n = 7), diseased but without pulmonary thromboembolism (n = 21), and healthy (n = 6). An observer who was aware of group status created three-dimensional pulmonary artery vascular trees for each dog using a semiautomated segmentation technique. Vascular three-dimensional reconstructions were then evaluated using fractal analysis. Fractal dimensions were analyzed, by group, using analysis of variance and principal component analysis. Fractal dimensions were significantly different among the three groups taken together (P = 0.001), but not between the diseased dogs alone (P = 0.203). The principal component analysis showed a tendency of separation between healthy control and diseased groups, but not between groups of dogs with and without pulmonary thromboembolism. Findings indicated that computed tomographic pulmonary angiogram images can be used to reconstruct three-dimensional pulmonary arterial vascular trees in dogs and that fractal analysis of these three-dimensional vascular trees is a feasible method for quantifying the spatial relationships of pulmonary arteries. These methods could be applied in further research studies on pulmonary and vascular diseases in dogs. © 2017 American College of Veterinary Radiology.

  3. Headspace Analysis of Volatile Compounds Coupled to Chemometrics in Leaves from the Magnoliaceae Family

    Directory of Open Access Journals (Sweden)

    Mohamed A. Farag

    2015-01-01

    Full Text Available Headspace volatile analysis has been used for volatiles profiling in leaves of 4 Magnolia species with a total of 75 compounds were identified. Monterpene hydrocarbons dominated the volatile blend of M. calophylla (86%, M. acuminata (78%, M. virginiana (70% and M. grandiflora (47% with b -pinene and b -ocimene occurring in the largest amounts, whereas sesquiterpenes were the most abundant compounds in M. grandiflora (39%. High levels of oxygenated compounds were only found in M. virginiana volatile blend (11.4% with 2-phenylethyl alcohol as major component. Hierarchical cluster analysis performed on volatiles content revealed the close relationship between M. acuminata and M. calophylla.

  4. Spatial aspects of surface water quality in the Jakara Basin, Nigeria using chemometric analysis.

    Science.gov (United States)

    Mustapha, Adamu; Aris, Ahmad Zaharin

    2012-01-01

    Multivariate statistical techniques such as hierarchical Agglomerated cluster analysis (HACA), discriminant analysis (DA), principal component analysis (PCA), and factor analysis (FA) were applied to identify the spatial variation and pollution sources of Jakara River, Kano, Nigeria. Thirty surface water samples were collected: 23 along Getsi River and 7 along the main channel of River Jakara. Twenty-three water quality parameters, namely pH, temperature, turbidity, electrical conductivity (EC), dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD(5)), Faecal coliform, total solids (TS), nitrates (NO(3)(-)), phosphates (PO(4)(3-)), cobalt (Co), iron (Fe), nickel (Ni), manganese (Mn), copper (Cu), sodium (Na), potassium (K), mercury (Hg), chromium (Cr), cadmium (Cd), lead (Pb), magnesium (Mg), and calcium(Ca) were analysed. HACA grouped the sampling points into three clusters based on the similarities of river water quality characteristics: industrial, domestic, and agricultural water pollution sources. Forward and backward DA effectively discriminated 5 and 15 water quality variables, respectively, each assigned with 100% correctness from the original 23 variables. PCA and FA were used to investigate the origin of each water quality parameter due to various land use activities, 7 principal components were obtained with 77.5% total variance, and in addition PCA identified 3 latent pollution sources to support HACA. From this study, one can conclude that the application of multivariate techniques derives meaningful information from water quality data.

  5. Fluorescence spectral analysis for the discrimination of complex, similar mixtures with the aid of chemometrics.

    Science.gov (United States)

    Ni, Yongnian; Lai, Yanhua; Kokot, Serge

    2012-07-01

    An analytical method for the classification of complex real-world samples was researched and developed with the use of excitation-emission fluorescence matrix (EEFM) spectroscopy, using the medicinal herbs, Rhizoma corydalis decumbentis (RCD) and Rhizoma corydalis (RC) as example samples. The data set was obtained from various authentic RCD-A and RC-A, adulterated AD, and commercial RCD-C and RC-C samples. The spectra (range: λ(ex) = 215∼395 nm and λ(em) = 290∼560 nm), arranged in two- and three-way data matrix formats, were processed using principal component analysis (PCA) and parallel factor analysis (PARAFAC) to produce two-dimensional component-by-component plots for qualitative data classification. The RCD-A and RC-A object groups were clearly discriminated, but the AD and the RCD-C as well as RC-C samples were less well separated. PARAFAC analysis produced somewhat better discrimination, and loadings plots revealed the presence of the marker compound Protopine-a strongly fluorescing substance-as well as at least two other unidentified fluorescent components. Classification performance of the common K-nearest neighbors (KNN) and linear discrimination analysis (LDA) methods was relatively poor when compared with that of the back propagation- and radial basis function-artificial neural networks (BP-ANN and RBF-ANN) models on the basis of two- and three-way formatted data. The best results were obtained with the three-way fingerprints and the RBF-ANN model. Subsequently, the quality of the commercial samples (RCD-C and RC-C) was classified on the best optimized RBF-ANN model. Thus, EEFM spectroscopy, which provides three-way measured data, is potentially a powerful analytical technique for the analysis of complex real-world substances provided the classification is performed by the RBF-ANN or similar ANN methods.

  6. Characterization of Leaf Extracts of Schinus terebinthifolius Raddi by GC-MS and Chemometric Analysis

    Science.gov (United States)

    Carneiro, Fabíola B.; Lopes, Pablo Q.; Ramalho, Ricardo C.; Scotti, Marcus T.; Santos, Sócrates G.; Soares, Luiz A. L.

    2017-01-01

    Background: Schinus terebinthifolius Raddi belongs to Anacardiacea family and is widely known as “aroeira.” This species originates from South America, and its extracts are used in folk medicine due to its therapeutic properties, which include antimicrobial, anti-inflammatory, and antipyretic effects. The complexity and variability of the chemical constitution of the herbal raw material establishes the quality of the respective herbal medicine products. Objective: Thus, the purpose of this study was to investigate the variability of the volatile compounds from leaves of S. terebinthifolius. Materials and Methods: The samples were collected from different states of the Northeast region of Brazil and analyzed with a gas chromatograph coupled to a mass spectrometer (GC-MS). The collected data were analyzed using multivariate data analysis. Results: The samples’ chromatograms, obtained by GC-MS, showed similar chemical profiles in a number of peaks, but some differences were observed in the intensity of these analytical markers. The chromatographic fingerprints obtained by GC-MS were suitable for discrimination of the samples; these results along with a statistical treatment (principal component analysis [PCA]) were used as a tool for comparative analysis between the different samples of S. terebinthifolius. Conclusion: The experimental data show that the PCA used in this study clustered the samples into groups with similar chemical profiles, which builds an appropriate approach to evaluate the similarity in the phytochemical pattern found in the different leaf samples. SUMMARY The leave extracts of Schinus terebinthifolius were obtained by turbo-extractionThe extracts were partitioned with hexane and analyzed by GC-MSThe chromatographic data were analyzed using the principal component analysis (PCA)The PCA plots showed the main compounds (phellandrene, limonene, and carene), which were used to group the samples from a different geographical location in

  7. Metabolic fingerprinting of Angelica sinensis during growth using UPLC-TOFMS and chemometrics data analysis

    Science.gov (United States)

    2013-01-01

    Background The radix of Angelica sinensis is widely used as a medicinal herbal and metabolomics research of this plant during growth is necessary. Results Principal component analysis of the UPLC-QTOFMS data showed that these 27 samples could be separated into 4 different groups. The chemical markers accounting for these separations were identified from the PCA loadings plot. These markers were further verified by accurate mass tandem mass and retention times of available reference standards. The study has shown that accumulation of secondary metabolites of Angelica sinensis is closely related to the growth periods. Conclusions The UPLC-QTOFMS based metabolomics approach has great potential for analysis of the alterations of secondary metabolites of Angelica sinensis during growth. PMID:23453085

  8. In situ Analysis of Fireworks Using Laser-Induced Breakdown Spectroscopy and Chemometrics

    Science.gov (United States)

    Awasthi, S.; Kumar, R.; Rai, A. K.

    2017-11-01

    Different types of fireworks are analyzed using the laser-induced breakdown spectroscopy (LIBS) technique. The system employed for spectral acquisition consists of a Nd:YAG laser (532 nm, FWHM = 4 ns) and an Andor Mechelle ME 5000 echelle spectrometer. The presence of Ba, Ca, Mg, Fe, Na, Sr, Si, and Al is identified in the LIBS spectra of different fireworks. These elements can mix easily into the surroundings and thus pollute the environment. In combination with LIBS, multivariate statistical methods, such as principal component analysis and partial least square discriminant analysis, are employed for qualitative classification, regression, and prediction purposes. These methods show good applicability for the classification and prediction of a large data set.

  9. High-throughput identification of monoclonal antibodies after compounding by UV spectroscopy coupled to chemometrics analysis.

    Science.gov (United States)

    Jaccoulet, Emmanuel; Boccard, Julien; Taverna, Myriam; Azevedos, Andrea Santos; Rudaz, Serge; Smadja, Claire

    2016-08-01

    Monoclonal antibodies (mAbs) compounded into the hospital pharmacy are widely used nowadays. Their fast identification after compounding and just before administration to the patient is of paramount importance for quality control at the hospital. This remains challenging due to the high similarity of the structure between mAbs. Analysis of the ultraviolet spectral data of four monoclonal antibodies (cetuximab, rituximab, bevacizumab, and trastuzumab) using unsupervised principal component analysis led us to focus exclusively on the second-derivative spectra. Partial least squares-discriminant analysis (PLS-DA) applied to these data allowed us to build models for predicting which monoclonal antibody was present in a given infusion bag. The calibration of the models was obtained from a k-fold validation. A prediction set from another batch was used to demonstrate the ability of the models to predict well. PLS-DA models performed on the spectra of the region of aromatic amino acid residues presented high ability to predict mAb identity. The region corresponding to the tyrosine residue reached the highest score of good classification with 89 %. To improve the score, standard normal variate (SNV) preprocessing was applied to the spectral data. The quality of the optimized PLS-DA models was enhanced and the region from the tyrosine/tryptophan residues allowed us excellent classification (100 %) of the four mAbs according to the matrix of confusion. The sensitivity and specificity performance parameters assessed this excellent classification. The usefulness of the combination of UV second-derivative spectroscopy to multivariate analysis with SNV preprocessing demonstrated the unambiguous identification of commercially available monoclonal antibodies. Graphical abstract PLS-DA models on the spectra of the region of aromatic amino acid residues allows mAb identification with high prediction.

  10. Routine analysis of mercury species using commercially available instrumentation: chemometric optimisation of the instrumental variables

    Energy Technology Data Exchange (ETDEWEB)

    Sanz, J.; Diego, A. de; Raposo, J.C.; Madariaga, J.M

    2003-06-17

    Mercury speciation analysis (inorganic mercury, Hg{sup 2+}, methylmercury, CH{sub 3}Hg{sup +} and dimethylmercury, (CH{sub 3}){sub 2}Hg) by gas chromatography (GC) coupled to atomic emission spectroscopy with microwave induced plasma as excitation source (MIP-AES), after ethylation of the sample and extraction of the derivatised species into an organic phase, has been optimised using factorial design, analysis of variance and MultiSimplex techniques. Standard conditions were used in the derivatisation step with sodium tetraethylborate (NaB(C{sub 2}H{sub 5}){sub 4}) and in the extraction step into hexane. Good separation of the species investigated and maximum sensitivity was achieved using an OV-1701 capillary column. The sensitivity was found to be maximum with an helium flow rate (make-up flow) of 100 ml min{sup -1}. Procedures for a correct cleaning of glass and plastic ware, as well as for the purification of reagents used throughout the analytical process, are also suggested in order to avoid unacceptably high blank signals. The effect that ageing of stock solutions used in calibrations has on the artefact formation of CH{sub 3}Hg{sup +} has been also investigated. Using the optimum conditions found, good quality calibration curves (R{sup 2}>0.995) for the three mercury species were obtained. Absolute detection limits of 0.5, 3 and 15 pg of (CH{sub 3}){sub 2}Hg, CH{sub 3}Hg{sup +} and Hg{sup 2+}, respectively, were estimated. The repeatability of the analysis was found to be better than 5% (n=5) in relative standard deviation (R.S.D.) units. The optimised procedure for the speciation of mercury in standard samples is the first step in the development of a method for routine analysis of mercury species in aquatic environmental samples.

  11. Extraction optimization and pixel-based chemometric analysis of semi-volatile organic compounds in groundwater

    DEFF Research Database (Denmark)

    Christensen, Peter; Tomasi, Giorgio; Kristensen, Mette

    2017-01-01

    Semi-volatile organic compounds (semi-VOCs) are found in complex mixtures, and at low concentrations in groundwater. Chemical fingerprint analysis of groundwater is therefore challenging, as it is necessary to obtain high enrichment factors for compounds with a wide range of properties. In this s......Semi-volatile organic compounds (semi-VOCs) are found in complex mixtures, and at low concentrations in groundwater. Chemical fingerprint analysis of groundwater is therefore challenging, as it is necessary to obtain high enrichment factors for compounds with a wide range of properties....... In this study, we tested the combination of solid phase extraction (SPE) with dispersive liquid-liquid micro extraction (DLLME), or with stir bar sorptive extraction (SBSE), as an extraction method for semi-VOCs in groundwater. Combining SPE with DLLME or SBSE resulted in better separation of peaks...... in an unresolved complex mixture. SPE-DLLME was chosen as the preferred extraction method. SPE-DLLME covered a larger polarity range (logKo/w 2.0-11.2), had higher extraction efficiency at logKo/w 2.0-3.8 and 5.8-11.2, and was faster compared to SPE-SBSE. SPE-DLLME extraction combined with chemical analysis by gas...

  12. Simultaneous quantitative analysis of olmesartan, amlodipine and hydrochlorothiazide in their combined dosage form utilizing classical and alternating least squares based chemometric methods

    Directory of Open Access Journals (Sweden)

    Darwish Hany W.

    2016-03-01

    Full Text Available Simultaneous spectrophotometric analysis of a multi-component dosage form of olmesartan, amlodipine and hydrochlorothiazide used for the treatment of hypertension has been carried out using various chemometric methods. Multivariate calibration methods include classical least squares (CLS executed by net analyte processing (NAP-CLS, orthogonal signal correction (OSC-CLS and direct orthogonal signal correction (DOSC-CLS in addition to multivariate curve resolution-alternating least squares (MCR-ALS. Results demonstrated the efficiency of the proposed methods as quantitative tools of analysis as well as their qualitative capability. The three analytes were determined precisely using the aforementioned methods in an external data set and in a dosage form after optimization of experimental conditions. Finally, the efficiency of the models was validated via comparison with the partial least squares (PLS method in terms of accuracy and precision.

  13. Vibrational spectroscopy and chemometrics for rapid, quantitative analysis of bitter acids in hops (Humulus lupulus).

    Science.gov (United States)

    Killeen, Daniel P; Andersen, David H; Beatson, Ron A; Gordon, Keith C; Perry, Nigel B

    2014-12-31

    Hops, Humulus lupulus, are grown worldwide for use in the brewing industry to impart characteristic flavor and aroma to finished beer. Breeders produce many varietal crosses with the aim of improving and diversifying commercial hops varieties. The large number of crosses critical to a successful breeding program imposes high demands on the supporting chemical analytical laboratories. With the aim of reducing the analysis time associated with hops breeding, quantitative partial least-squares regression (PLS-R) models have been produced, relating reference data acquired by the industrial standard HPLC and UV methods, to vibrational spectra of the same, chemically diverse hops sample set. These models, produced from rapidly acquired infrared (IR), near-infrared (NIR), and Raman spectra, were appraised using standard statistical metrics. Results demonstrated that all three spectroscopic methods could be used for screening hops for α-acid, total bitter acids, and cohumulone concentrations in powdered hops. Models generated from Raman and IR spectra also showed potential for use in screening hops varieties for xanthohumol concentrations. NIR analysis was performed using both a standard benchtop spectrometer and a portable NIR spectrometer, with comparable results obtained by both instruments. Finally, some important vibrational features of cohumulone, colupulone, and xanthohumol were assigned using DFT calculations, which allow more insightful interpretation of PLS-R latent variable plots.

  14. Determination of residual oil in diesel oil by spectrofluorimetric and chemometric analysis.

    Science.gov (United States)

    Corgozinho, Camila N C; Pasa, Vânya M D; Barbeira, Paulo J S

    2008-07-15

    Multivariate calibration (PLS), principal components analysis (PCA) and linear discriminant analysis (LDA), associated to synchronous spectrofluorimetry, were used to identify and quantify non-transesterified residual vegetable oil in diesel oil with the addition of 2% of biodiesel (B2). The addition of residual oil, one of the easiest ways of adultering fuel, damages engines and leads to tax evasion. Using this method, the samples of diesel oil, B2, and B2 contaminated with residual oil were classified correctly and separated into three well-defined groups. The quantification of residual oil in B2 was carried out in the 0-25% (w/w) band, RMSEC and RMSEP values ranging from 0.26 to 0.48% (w/w) and 1.6-2.6% (w/w), respectively. The method is highly sensitive and efficient to identify and quantify this type of adulterant in which 100% of the samples were correctly classified and the average relative error was approximately 4% in the range 0.5-25% (w/w).

  15. Source Attribution of Cyanides using Anionic Impurity Profiling, Stable Isotope Ratios, Trace Elemental Analysis and Chemometrics

    Energy Technology Data Exchange (ETDEWEB)

    Mirjankar, Nikhil S.; Fraga, Carlos G.; Carman, April J.; Moran, James J.

    2016-01-08

    Chemical attribution signatures (CAS) for chemical threat agents (CTAs) are being investigated to provide an evidentiary link between CTAs and specific sources to support criminal investigations and prosecutions. In a previous study, anionic impurity profiles developed using high performance ion chromatography (HPIC) were demonstrated as CAS for matching samples from eight potassium cyanide (KCN) stocks to their reported countries of origin. Herein, a larger number of solid KCN stocks (n = 13) and, for the first time, solid sodium cyanide (NaCN) stocks (n = 15) were examined to determine what additional sourcing information can be obtained through anion, carbon stable isotope, and elemental analyses of cyanide stocks by HPIC, isotope ratio mass spectrometry (IRMS), and inductively coupled plasma optical emission spectroscopy (ICP-OES), respectively. The HPIC anion data was evaluated using the variable selection methods of Fisher-ratio (F-ratio), interval partial least squares (iPLS), and genetic algorithm-based partial least squares (GAPLS) and the classification methods of partial least squares discriminate analysis (PLSDA), K nearest neighbors (KNN), and support vector machines discriminate analysis (SVMDA). In summary, hierarchical cluster analysis (HCA) of anion impurity profiles from multiple cyanide stocks from six reported country of origins resulted in cyanide samples clustering into three groups: Czech Republic, Germany, and United States, independent of the associated alkali metal (K or Na). The three country groups were independently corroborated by HCA of cyanide elemental profiles and corresponded to countries with known solid cyanide factories. Both the anion and elemental CAS are believed to originate from the aqueous alkali hydroxides used in cyanide manufacture. Carbon stable isotope measurements resulted in two clusters: Germany and United States (the single Czech stock grouped with United States stocks). The carbon isotope CAS is believed to

  16. Rapid discrimination and determination of antibiotics drugs in plastic syringes using near infrared spectroscopy with chemometric analysis: Application to amoxicillin and penicillin.

    Science.gov (United States)

    Lê, Laetitia Minh Mai; Eveleigh, Luc; Hasnaoui, Ikram; Prognon, Patrice; Baillet-Guffroy, Arlette; Caudron, Eric

    2017-05-10

    The aim of this study was to investigate near infrared spectroscopy (NIRS) combined to chemometric analysis to discriminate and quantify three antibiotics by direct measurement in plastic syringes.Solutions of benzylpenicillin (PENI), amoxicillin (AMOX) and amoxicillin/clavulanic acid (AMOX/CLAV) were analyzed at therapeutic concentrations in glass vials and plastic syringes with NIR spectrometer by direct measurement. Chemometric analysis using partial least squares regression and discriminative analysis was conducted to develop qualitative and quantitative calibration models. Discrimination of the three antibiotics was optimal for concentrated solutions with 100% of accuracy. For quantitative analysis, the three antibiotics furnished a linear response (R²>0.9994) for concentrations ranging from 0.05 to 0.2 g/mL for AMOX, 0.1 to 1.0 MUI/mL for PENI and 0.005 to 0.05 g/mL for AMOX/CLAV with excellent repeatability (maximum 1.3%) and intermediate precision (maximum of 3.2%). Based on proposed models, 94.4% of analyzed AMOX syringes, 80.0% of AMOX/CLAV syringes and 85.7% of PENI syringes were compliant with a relative error including the limit of ± 15%.NIRS as rapid, non-invasive and non-destructive analytical method represents a potentially powerful tool to further develop for securing the drug administration circuit of healthcare institutions to ensure that patients receive the correct product at the right dose. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Diagnostic prediction of renal failure from blood serum analysis by FTIR spectrometry and chemometrics

    Science.gov (United States)

    Khanmohammadi, Mohammdreza; Ghasemi, Keyvan; Garmarudi, Amir Bagheri; Ramin, Mehdi

    2015-02-01

    A new diagnostic approach based on Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectrometry and classification algorithm has been introduced which provides a rapid, reliable, and easy way to perform blood test for the diagnosis of renal failure. Blood serum samples from 35 renal failure patients and 40 healthy persons were analyzed by ATR-FTIR spectrometry. The resulting data was processed by Quadratic Discriminant Analysis (QDA) and QDA combined with simple filtered method. Spectroscopic studies were performed in 900-2000 cm-1 spectral region with 3.85 cm-1 data space. Results showed 93.33% and 100% of accuracy for QDA and filter-QDA models, respectively. In the first step, 30 samples were applied to construct the model. In order to modify the capability of QDA in prediction of test samples, filter-based feature selection methods were applied. It was found that the filtered spectra coupled with QDA could correctly predict the test samples in most of the cases.

  18. Synergistic effect of the simultaneous chemometric analysis of 1H NMR spectroscopic and stable isotope (SNIF-NMR, 18O, 13C) data: Application to wine analysis

    International Nuclear Information System (INIS)

    Monakhova, Yulia B.; Godelmann, Rolf; Hermann, Armin; Kuballa, Thomas; Cannet, Claire; Schäfer, Hartmut; Spraul, Manfred; Rutledge, Douglas N.

    2014-01-01

    Highlights: • 1 H NMR profilings of 718 wines were fused with stable isotope analysis data (SNIF-NMR, 18 O, 13 C). • The best improvement was obtained for prediction of the geographical origin of wine. • Certain enhancement was also obtained for the year of vintage (from 88 to 97% for 1 H NMR to 99% for the fused data). • Independent component analysis was used as an alternative chemometric tool for classification. - Abstract: It is known that 1 H NMR spectroscopy represents a good tool for predicting the grape variety, the geographical origin, and the year of vintage of wine. In the present study we have shown that classification models can be improved when 1 H NMR profiles are fused with stable isotope (SNIF-NMR, 18 O, 13 C) data. Variable selection based on clustering of latent variables was performed on 1 H NMR data. Afterwards, the combined data of 718 wine samples from Germany were analyzed using linear discriminant analysis (LDA), partial least squares-discriminant analysis (PLS-DA), factorial discriminant analysis (FDA) and independent components analysis (ICA). Moreover, several specialized multiblock methods (common components and specific weights analysis (ComDim), consensus PCA and consensus PLS-DA) were applied to the data. The best improvement in comparison with 1 H NMR data was obtained for prediction of the geographical origin (up to 100% for the fused data, whereas stable isotope data resulted only in 60–70% correct prediction and 1 H NMR data alone in 82–89% respectively). Certain enhancement was obtained also for the year of vintage (from 88 to 97% for 1 H NMR to 99% for the fused data), whereas in case of grape varieties improved models were not obtained. The combination of 1 H NMR data with stable isotope data improves efficiency of classification models for geographical origin and vintage of wine and can be potentially used for other food products as well

  19. Comprehensive analysis of Polygoni Multiflori Radix of different geographical origins using ultra-high-performance liquid chromatography fingerprints and multivariate chemometric methods

    Directory of Open Access Journals (Sweden)

    Li-Li Sun

    2018-01-01

    Full Text Available Polygoni Multiflori Radix (PMR is increasingly being used not just as a traditional herbal medicine but also as a popular functional food. In this study, multivariate chemometric methods and mass spectrometry were combined to analyze the ultra-high-performance liquid chromatograph (UPLC fingerprints of PMR from six different geographical origins. A chemometric strategy based on multivariate curve resolution–alternating least squares (MCR–ALS and three classification methods is proposed to analyze the UPLC fingerprints obtained. Common chromatographic problems, including the background contribution, baseline contribution, and peak overlap, were handled by the established MCR–ALS model. A total of 22 components were resolved. Moreover, relative species concentrations were obtained from the MCR–ALS model, which was used for multivariate classification analysis. Principal component analysis (PCA and Ward's method have been applied to classify 72 PMR samples from six different geographical regions. The PCA score plot showed that the PMR samples fell into four clusters, which related to the geographical location and climate of the source areas. The results were then corroborated by Ward's method. In addition, according to the variance-weighted distance between cluster centers obtained from Ward's method, five components were identified as the most significant variables (chemical markers for cluster discrimination. A counter-propagation artificial neural network has been applied to confirm and predict the effects of chemical markers on different samples. Finally, the five chemical markers were identified by UPLC–quadrupole time-of-flight mass spectrometer. Components 3, 12, 16, 18, and 19 were identified as 2,3,5,4′-tetrahydroxy-stilbene-2-O-β-d-glucoside, emodin-8-O-β-d-glucopyranoside, emodin-8-O-(6′-O-acetyl-β-d-glucopyranoside, emodin, and physcion, respectively. In conclusion, the proposed method can be applied for the

  20. The relationship between mineral contents, particle matter and bottom ash distribution during pellet combustion: molar balance and chemometric analysis.

    Science.gov (United States)

    Jeguirim, Mejdi; Kraiem, Nesrine; Lajili, Marzouk; Guizani, Chamseddine; Zorpas, Antonis; Leva, Yann; Michelin, Laure; Josien, Ludovic; Limousy, Lionel

    2017-04-01

    This paper aims to identify the correlation between the mineral contents in agropellets and particle matter and bottom ash characteristics during combustion in domestic boilers. Four agrifood residues with higher mineral contents, namely grape marc (GM), tomato waste (TW), exhausted olive mill solid waste (EOMSW) and olive mill wastewater (OMWW), were selected. Then, seven different pellets were produced from pure residues or their mixture and blending with sawdust. The physico-chemical properties of the produced pellets were analysed using different analytical techniques, and a particular attention was paid to their mineral contents. Combustion tests were performed in 12-kW domestic boiler. The particle matter (PM) emission was characterised through the particle number and mass quantification for different particle size. The bottom ash composition and size distribution were also characterised. Molar balance and chemometric analyses were performed to identify the correlation between the mineral contents and PM and bottom ash characteristics. The performed analyses indicate that K, Na, S and Cl are released partially or completely during combustion tests. In contrast, Ca, Mg, Si, P, Al, Fe and Mn are retained in the bottom ash. The chemometric analyses indicate that, in addition to the operating conditions and the pellet ash contents, K and Si concentrations have a significant effect on the PM emissions as well as on the agglomeration of bottom ash.

  1. Current application of chemometrics in traditional Chinese herbal medicine research.

    Science.gov (United States)

    Huang, Yipeng; Wu, Zhenwei; Su, Rihui; Ruan, Guihua; Du, Fuyou; Li, Gongke

    2016-07-15

    Traditional Chinese herbal medicines (TCHMs) are promising approach for the treatment of various diseases which have attracted increasing attention all over the world. Chemometrics in quality control of TCHMs are great useful tools that harnessing mathematics, statistics and other methods to acquire information maximally from the data obtained from various analytical approaches. This feature article focuses on the recent studies which evaluating the pharmacological efficacy and quality of TCHMs by determining, identifying and discriminating the bioactive or marker components in different samples with the help of chemometric techniques. In this work, the application of chemometric techniques in the classification of TCHMs based on their efficacy and usage was introduced. The recent advances of chemometrics applied in the chemical analysis of TCHMs were reviewed in detail. Copyright © 2015 Elsevier B.V. All rights reserved.

  2. Classification of cultivated mussels from Galicia (Northwest Spain) with European Protected Designation of Origin using trace element fingerprint and chemometric analysis

    International Nuclear Information System (INIS)

    Costas-Rodriguez, M.; Lavilla, I.; Bendicho, C.

    2010-01-01

    Inductively coupled plasma-mass spectrometry (ICP-MS) in combination with different supervised chemometric approaches has been used to classify cultivated mussels in Galicia (Northwest of Spain) under the European Protected Designation of Origin (PDO). 158 mussel samples, collected in the five rias on the basis of the production, along with minor and trace elements, including high field strength elements (HFSEs) and rare earth elements (REEs), were used with this aim. The classification of samples was achieved according to their origin: Galician vs. other regions (from Tarragona, Spain, and Ethang de Thau, France) and between the Galician Rias. The ability of linear discriminant analysis (LDA), soft independent modelling of class analogy (SIMCA) and artificial neural network (ANN) to classify the samples was investigated. Correct assignations for Galician and non-Galician samples were obtained when LDA and SIMCA were used. ANNs were more effective when a classification according to the ria of origin was to be applied.

  3. Classification of cultivated mussels from Galicia (Northwest Spain) with European Protected Designation of Origin using trace element fingerprint and chemometric analysis

    Energy Technology Data Exchange (ETDEWEB)

    Costas-Rodriguez, M.; Lavilla, I. [Departamento de Quimica Analitica y Alimentaria, Area de Quimica Analitica, Facultad de Quimica, Universidad de Vigo, As Lagoas-Marcosende s/n, 36310 Vigo (Spain); Bendicho, C., E-mail: bendicho@uvigo.es [Departamento de Quimica Analitica y Alimentaria, Area de Quimica Analitica, Facultad de Quimica, Universidad de Vigo, As Lagoas-Marcosende s/n, 36310 Vigo (Spain)

    2010-04-07

    Inductively coupled plasma-mass spectrometry (ICP-MS) in combination with different supervised chemometric approaches has been used to classify cultivated mussels in Galicia (Northwest of Spain) under the European Protected Designation of Origin (PDO). 158 mussel samples, collected in the five rias on the basis of the production, along with minor and trace elements, including high field strength elements (HFSEs) and rare earth elements (REEs), were used with this aim. The classification of samples was achieved according to their origin: Galician vs. other regions (from Tarragona, Spain, and Ethang de Thau, France) and between the Galician Rias. The ability of linear discriminant analysis (LDA), soft independent modelling of class analogy (SIMCA) and artificial neural network (ANN) to classify the samples was investigated. Correct assignations for Galician and non-Galician samples were obtained when LDA and SIMCA were used. ANNs were more effective when a classification according to the ria of origin was to be applied.

  4. Chemometrics Methods and Strategies in Metabolomics.

    Science.gov (United States)

    Pinto, Rui Climaco

    2017-01-01

    Chemometrics has been a fundamental discipline for the development of metabolomics, while symbiotically growing with it. From design of experiments, through data processing, to data analysis, chemometrics tools are used to design, process, visualize, explore and analyse metabolomics data.In this chapter, the most commonly used chemometrics methods for data analysis and interpretation of metabolomics experiments will be presented, with focus on multivariate analysis. These are projection-based linear methods, like principal component analysis (PCA) and orthogonal projection to latent structures (OPLS), which facilitate interpretation of the causes behind the observed sample trends, correlation with outcomes or group discrimination analysis. Validation procedures for multivariate methods will be presented and discussed.Univariate analysis is briefly discussed in the context of correlation-based linear regression methods to find associations to outcomes or in analysis of variance-based and logistic regression methods for class discrimination. These methods rely on frequentist statistics, with the determination of p-values and corresponding multiple correction procedures.Several strategies of design-analysis of metabolomics experiments will be discussed, in order to guide the reader through different setups, adopted to better address some experimental issues and to better test the scientific hypotheses.

  5. Chemometrics: A new scenario in herbal drug standardization.

    Science.gov (United States)

    Bansal, Ankit; Chhabra, Vikas; Rawal, Ravindra K; Sharma, Simant

    2014-08-01

    Chromatography and spectroscopy techniques are the most commonly used methods in standardization of herbal medicines but the herbal system is not easy to analyze because of their complexity of chemical composition. Many cutting-edge analytical technologies have been introduced to evaluate the quality of medicinal plants and significant amount of measurement data has been produced. Chemometric techniques provide a good opportunity for mining more useful chemical information from the original data. Then, the application of chemometrics in the field of medicinal plants is spontaneous and necessary. Comprehensive methods and hyphenated techniques associated with chemometrics used for extracting useful information and supplying various methods of data processing are now more and more widely used in medicinal plants, among which chemometrics resolution methods and principal component analysis (PCA) are most commonly used techniques. This review focuses on the recent various important analytical techniques, important chemometrics tools and interpretation of results by PCA, and applications of chemometrics in quality evaluation of medicinal plants in the authenticity, efficacy and consistency.

  6. Chemometrics for drug impurity profiling : optimisation of capillary electrophoresis and deconvolution of overlapping peaks

    NARCIS (Netherlands)

    Zomeren, Paul Vincent van

    2008-01-01

    The potential of chemometrics for drug impurity profiling has been examined in this thesis. Generally, various hyphenated methods are used for the analysis of drug sub¬stance and product in order to enable the identification and quantification of impuri¬ties. chemometrics can be used to enhance the

  7. Chemometric classification of gunshot residues based on energy dispersive X-ray microanalysis and inductively coupled plasma analysis with mass-spectrometric detection

    Science.gov (United States)

    Steffen, S.; Otto, M.; Niewoehner, L.; Barth, M.; Bro¿żek-Mucha, Z.; Biegstraaten, J.; Horváth, R.

    2007-09-01

    A gunshot residue sample that was collected from an object or a suspected person is automatically searched for gunshot residue relevant particles. Particle data (such as size, morphology, position on the sample for manual relocation, etc.) as well as the corresponding X-ray spectra and images are stored. According to these data, particles are classified by the analysis-software into different groups: 'gunshot residue characteristic', 'consistent with gunshot residue' and environmental particles, respectively. Potential gunshot residue particles are manually checked and - if necessary - confirmed by the operating forensic scientist. As there are continuing developments on the ammunition market worldwide, it becomes more and more difficult to assign a detected particle to a particular ammunition brand. As well, the differentiation towards environmental particles similar to gunshot residue is getting more complex. To keep external conditions unchanged, gunshot residue particles were collected using a specially designed shooting device for the test shots revealing defined shooting distances between the weapon's muzzle and the target. The data obtained as X-ray spectra of a number of particles (3000 per ammunition brand) were reduced by Fast Fourier Transformation and subjected to a chemometric evaluation by means of regularized discriminant analysis. In addition to the scanning electron microscopy in combination with energy dispersive X-ray microanalysis results, isotope ratio measurements based on inductively coupled plasma analysis with mass-spectrometric detection were carried out to provide a supplementary feature for an even lower risk of misclassification.

  8. On-line Speciation of Cr(III) and Cr(VI) by Flow Injection Analysis With Spectrophotometric Detection and Chemometrics

    DEFF Research Database (Denmark)

    Diacu, Elena; Andersen, Jens Enevold Thaulov

    2003-01-01

    A flow injection system has been developed, for on-line speciation. of Cr(III) and Cr(VI) by the Diphenylcarbazide (DPC) method with H2O2 oxidation followed by spectrophotometric detection at the 550 nm wavelength. The data thus obtained were subjected to a chemometric analysis (PLS), which showed...... that it was possible to obtain reliable predictions of Cr(III) and Cr(VI) species. The method was validated on samples of stainless steel. In order to facilitate analysis of stainless-steel samples it was essential to perform a step of evaporation to dryness followed by re-dissolution. The analysis showed that species...... of Cr(III) and Cr(VI) coexisted in the samples digested by this method, By spiking the samples with iron and nickel species, it was found that, although the total amount of chromium remained constant, the equilibrium of the two chromium species was displaced towards Cr(III). A detection limit of 10 mug...

  9. Chemometric classification of gunshot residues based on energy dispersive X-ray microanalysis and inductively coupled plasma analysis with mass-spectrometric detection

    International Nuclear Information System (INIS)

    Steffen, S.; Otto, M.; Niewoehner, L.; Barth, M.; Brozek-Mucha, Z.; Biegstraaten, J.; Horvath, R.

    2007-01-01

    A gunshot residue sample that was collected from an object or a suspected person is automatically searched for gunshot residue relevant particles. Particle data (such as size, morphology, position on the sample for manual relocation, etc.) as well as the corresponding X-ray spectra and images are stored. According to these data, particles are classified by the analysis-software into different groups: 'gunshot residue characteristic', 'consistent with gunshot residue' and environmental particles, respectively. Potential gunshot residue particles are manually checked and - if necessary - confirmed by the operating forensic scientist. As there are continuing developments on the ammunition market worldwide, it becomes more and more difficult to assign a detected particle to a particular ammunition brand. As well, the differentiation towards environmental particles similar to gunshot residue is getting more complex. To keep external conditions unchanged, gunshot residue particles were collected using a specially designed shooting device for the test shots revealing defined shooting distances between the weapon's muzzle and the target. The data obtained as X-ray spectra of a number of particles (3000 per ammunition brand) were reduced by Fast Fourier Transformation and subjected to a chemometric evaluation by means of regularized discriminant analysis. In addition to the scanning electron microscopy in combination with energy dispersive X-ray microanalysis results, isotope ratio measurements based on inductively coupled plasma analysis with mass-spectrometric detection were carried out to provide a supplementary feature for an even lower risk of misclassification

  10. Discovery of discriminatory quality control markers for Chinese herbal medicines and related processed products by combination of chromatographic analysis and chemometrics methods: Radix Scutellariae as a case study.

    Science.gov (United States)

    Wang, Fei; Wang, Bo; Wang, Long; Xiong, Zi-Yue; Gao, Wen; Li, Ping; Li, Hui-Jun

    2017-05-10

    The processing procedure of traditional Chinese herbal medicines (CHMs) plays an essential role in clinical applications. However, little progress has been made on the quality control of crude and processed products. The present work, taking Radix Scutellariae (RS), wine-processed RS and carbonized RS as a typical case, developed a comprehensive strategy integrating chromatographic analysis and chemometric methods for quality evaluation and discrimination of crude RS and its processed products. Chemical fingerprints were established by high-performance liquid chromatography coupled with photodiode array detector and quadrupole time-of-flight mass spectrometry, and similarity analyses were calculated based on eleven common characteristic peaks. Subsequently, four chemical markers were discovered by back propagation-artificial neural network (BP-ANN) modeling. The selected markers were quantified by the 'single standard to determine multi-components' (SSDMC) method, and then the quantitative data were subjected to principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA). Furthermore, support vector machine (SVM) was employed to predict the different processed products of RS. Finally, a hotmap visualization was conducted for clarifying the distribution of major flavonoids among different drugs. Collectively, the proposed strategy might be well-acceptable for quality control of CHMs and their related processed products from the processing mechanism-based perspective. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Screening and Analysis of the Potential Bioactive Components of Poria cocos (Schw. Wolf by HPLC and HPLC-MSn with the Aid of Chemometrics

    Directory of Open Access Journals (Sweden)

    Ling-Fang Wu

    2016-02-01

    Full Text Available The aim of the present study was to establish a new method based on Similarity Analysis (SA, Cluster Analysis (CA and Principal Component Analysis (PCA to determine the quality of different samples of Poria cocos (Schw. Wolf obtained from Yunnan, Hubei, Guizhou, Fujian, Henan, Guangxi, Anhui and Sichuan in China. For this purpose 15 samples from the different habitats were analyzed by HPLC-PAD and HPLC-MSn. Twenty-three compounds were detected by HPLC-MSn, of which twenty compounds were tentatively identified by comparing their retention times and mass spectrometry data with that of reference compounds and reviewing the literature. The characteristic fragmentations were summarized. 3-epi-Dehydrotumulosic acid (F13, 3-oxo-16α,25-dihydroxylanosta-7,9(11,24(31-trien-21-oic acid (F4, 3-oxo-6,16α-dihydroxylanosta-7,9(11,24(31-trien-21-oic acid (F7 and dehydropachymic acid (F15 were deemed to be suitable marker compounds to distinguish between samples of different quality according to CA and PCA. This study provides helpful chemical information for further anti-tumor activity and active mechanism research on P. cocos. The results proved that fingerprint combined with a chemometric approach is a simple, rapid and effective method for the quality discrimination of P. cocos.

  12. Chemometric classification of gunshot residues based on energy dispersive X-ray microanalysis and inductively coupled plasma analysis with mass-spectrometric detection

    Energy Technology Data Exchange (ETDEWEB)

    Steffen, S. [Bundeskriminalamt (BKA), Forensic Science Institute KT23, Thaerstr. 11, D - 65193 Wiesbaden (Germany); Otto, M. [TU Bergakademie Freiberg (TU BAF), Institute for Analytical Chemistry, Leipziger Str. 29, D - 09599 Freiberg (Germany)], E-mail: matthias.otto@chemie.tu-freiberg.de; Niewoehner, L.; Barth, M. [Bundeskriminalamt (BKA), Forensic Science Institute KT23, Thaerstr. 11, D - 65193 Wiesbaden (Germany); Brozek-Mucha, Z. [Instytut Ekspertyz Sadowych (IES), Westerplatte St. 9, PL - 31-033 Krakow (Poland); Biegstraaten, J. [Nederlands Forensisch Instituut (NFI), Fysische Technologie, Laan van Ypenburg 6, NL-2497 GB Den Haag (Netherlands); Horvath, R. [Kriminalisticky a Expertizny Ustav (KEU PZ), Institute of Forensic Science, Sklabinska 1, SK - 812 72 Bratislava (Slovakia)

    2007-09-15

    A gunshot residue sample that was collected from an object or a suspected person is automatically searched for gunshot residue relevant particles. Particle data (such as size, morphology, position on the sample for manual relocation, etc.) as well as the corresponding X-ray spectra and images are stored. According to these data, particles are classified by the analysis-software into different groups: 'gunshot residue characteristic', 'consistent with gunshot residue' and environmental particles, respectively. Potential gunshot residue particles are manually checked and - if necessary - confirmed by the operating forensic scientist. As there are continuing developments on the ammunition market worldwide, it becomes more and more difficult to assign a detected particle to a particular ammunition brand. As well, the differentiation towards environmental particles similar to gunshot residue is getting more complex. To keep external conditions unchanged, gunshot residue particles were collected using a specially designed shooting device for the test shots revealing defined shooting distances between the weapon's muzzle and the target. The data obtained as X-ray spectra of a number of particles (3000 per ammunition brand) were reduced by Fast Fourier Transformation and subjected to a chemometric evaluation by means of regularized discriminant analysis. In addition to the scanning electron microscopy in combination with energy dispersive X-ray microanalysis results, isotope ratio measurements based on inductively coupled plasma analysis with mass-spectrometric detection were carried out to provide a supplementary feature for an even lower risk of misclassification.

  13. Screening and Analysis of the Marker Components in Ganoderma lucidum by HPLC and HPLC-MSn with the Aid of Chemometrics.

    Science.gov (United States)

    Wu, Lingfang; Liang, Wenyi; Chen, Wenjing; Li, Shi; Cui, Yaping; Qi, Qi; Zhang, Lanzhen

    2017-04-06

    Ganoderma triterpenes (GTs) are the major secondary metabolites of Ganoderma lucidum , which is a popularly used traditional Chinese medicine for complementary cancer therapy. The present study was to establish a fingerprint evaluation system based on Similarity Analysis (SA), Cluster Analysis (CA) and Principal Component Analysis (PCA) for the identification and quality control of G. lucidum . Fifteen samples from the Chinese provinces of Hainan, Neimeng, Shangdong, Jilin, Anhui, Henan, Yunnan, Guangxi and Fujian were analyzed by HPLC-PAD and HPLC-MS n . Forty-seven compounds were detected by HPLC, of which forty-two compounds were tentatively identified by comparing their retention times and mass spectrometry data with that of reference compounds and reviewing the literature. Ganoderic acid B, 3,7,15-trihydroxy-11,23-dioxolanost-8,16-dien-26-oic acid, lucidenic acid A, ganoderic acid G, and 3,7-oxo-12-acetylganoderic acid DM were deemed to be the marker compounds to distinguish the samples with different quality according to both CA and PCA. This study provides helpful chemical information for further research on the anti-tumor activity and mechanism of action of G. lucidum . The results proved that fingerprints combined with chemometrics are a simple, rapid and effective method for the quality control of G. lucidum .

  14. Chemometrics review for chemical sensor development, task 7 report

    International Nuclear Information System (INIS)

    1994-05-01

    This report, the seventh in a series on the evaluation of several chemical sensors for use in the U.S. Department of Energy's (DOE's) site characterization and monitoring programs, concentrates on the potential use of chemometrics techniques in analysis of sensor data. Chemometrics is the chemical discipline that uses mathematical, statistical, and other methods that employ formal logic to: design or select optimal measurement procedures and experiments and provide maximum relevant chemical information by analyzing chemical data. The report emphasizes the latter aspect. In a formal sense, two distinct phases are in chemometrics applications to analytical chemistry problems: (1) the exploratory data analysis phase and (2) the calibration and prediction phase. For use in real-world problems, it is wise to add a third aspect - the independent validation and verification phase. In practical applications, such as the ERWM work, and in order of decreasing difficulties, the most difficult tasks in chemometrics are: establishing the necessary infrastructure (to manage sampling records, data handling, and data storage and related aspects), exploring data analysis, and solving calibration problems, especially for nonlinear models. Chemometrics techniques are different for what are called zeroth-, first-, and second-order systems, and the details depend on the form of the assumed functional relationship between the measured response and the concentrations of components in mixtures. In general, linear relationships can be handled relatively easily, but nonlinear relationships can be difficult

  15. Chemometrics review for chemical sensor development, task 7 report

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1994-05-01

    This report, the seventh in a series on the evaluation of several chemical sensors for use in the U.S. Department of Energy`s (DOE`s) site characterization and monitoring programs, concentrates on the potential use of chemometrics techniques in analysis of sensor data. Chemometrics is the chemical discipline that uses mathematical, statistical, and other methods that employ formal logic to: design or select optimal measurement procedures and experiments and provide maximum relevant chemical information by analyzing chemical data. The report emphasizes the latter aspect. In a formal sense, two distinct phases are in chemometrics applications to analytical chemistry problems: (1) the exploratory data analysis phase and (2) the calibration and prediction phase. For use in real-world problems, it is wise to add a third aspect - the independent validation and verification phase. In practical applications, such as the ERWM work, and in order of decreasing difficulties, the most difficult tasks in chemometrics are: establishing the necessary infrastructure (to manage sampling records, data handling, and data storage and related aspects), exploring data analysis, and solving calibration problems, especially for nonlinear models. Chemometrics techniques are different for what are called zeroth-, first-, and second-order systems, and the details depend on the form of the assumed functional relationship between the measured response and the concentrations of components in mixtures. In general, linear relationships can be handled relatively easily, but nonlinear relationships can be difficult.

  16. Ultra-HPLC-MS(n) (Poly)phenolic profiling and chemometric analysis of juices from ancient Punica granatum L. Cultivars: a nontargeted approach.

    Science.gov (United States)

    Calani, Luca; Beghè, Deborah; Mena, Pedro; Del Rio, Daniele; Bruni, Renato; Fabbri, Andrea; Dall'asta, Chiara; Galaverna, Gianni

    2013-06-12

    This study deals with the qualitative characterization of the phenolic profile of pomegranate juices obtained from ancient accessions. Composition data, together with genetic, morphological, and agronomical parameters, may lead to a full characterization of such germplasm, with the aim of its retrieval and biodiversity valorization. Environmental adaptation, indeed, may contribute to an enrichment of the phenolic content in pomegranate, with important effects on its nutritional properties. More than 65 punicalagins, ellagic acid derivatives, flavonoids, anthocyanins, and phenylpropanoids were simultaneously detected from four centuries old Punica granatum L. ecotypes from northern Italy and compared with those of P. granatum cv. Dente di Cavallo, a widely cultivated Italian cultivar, using a simple ultra-HPLC (uHPLC) separation and MS(n) linear ion trap mass spectrometric characterization. Fingerprinting phytochemical discrimination of the accessions was obtained by chemometric analysis despite their limited geographical distribution, confirming the great intraspecific variability in pomegranate secondary metabolism. The combined recourse to uHPLC-MS(n) qualitative fingerprinting and multivariate analysis may represent a useful tool for the discrimination and selection of pomegranate germplasm with specific properties related to polyphenolic content.

  17. Chemometric analysis of correlations between electronic absorption characteristics and structural and/or physicochemical parameters for ampholytic substances of biological and pharmaceutical relevance

    Science.gov (United States)

    Judycka-Proma, U.; Bober, L.; Gajewicz, A.; Puzyn, T.; Błażejowski, J.

    2015-03-01

    Forty ampholytic compounds of biological and pharmaceutical relevance were subjected to chemometric analysis based on unsupervised and supervised learning algorithms. This enabled relations to be found between empirical spectral characteristics derived from electronic absorption data and structural and physicochemical parameters predicted by quantum chemistry methods or phenomenological relationships based on additivity rules. It was found that the energies of long wavelength absorption bands are correlated through multiparametric linear relationships with parameters reflecting the bulkiness features of the absorbing molecules as well as their nucleophilicity and electrophilicity. These dependences enable the quantitative analysis of spectral features of the compounds, as well as a comparison of their similarities and certain pharmaceutical and biological features. Three QSPR models to predict the energies of long-wavelength absorption in buffers with pH = 2.5 and pH = 7.0, as well as in methanol, were developed and validated in this study. These models can be further used to predict the long-wavelength absorption energies of untested substances (if they are structurally similar to the training compounds).

  18. UHPLC-MS/MS quantification combined with chemometrics for the comparative analysis of different batches of raw and wine-processed Dipsacus asper.

    Science.gov (United States)

    Tao, Yi; Du, Yingshan; Su, Dandan; Li, Weidong; Cai, Baochang

    2017-04-01

    A rapid and sensitive ultra-high performance liquid chromatography with tandem mass spectrometry approach was established for the simultaneous determination of 4-caffeoylquinic acid, loganic acid, chlorogenic acid, loganin, 3,5-dicaffeoylquinic acid, dipsacoside B, asperosaponin VI, and sweroside in raw and wine-processed Dipsacus asper. Chloramphenicol and glycyrrhetinic acid were employed as internal standards. The proposed approach was fully validated in terms of linearity, sensitivity, precision, repeatability as well as recovery. Intra- and interassay variability for all analytes were 2.8-4.9 and 1.7-4.8%, respectively. The standard addition method determined recovery rates for each analytes (96.8-104.6%). In addition, the developed approach was applied to 20 batches of raw and wine-processed samples of Dipsacus asper. Principle component analysis and partial least squares-discriminate analysis revealed a clear separation between the raw group and wine-processed group. After wine-processing, the contents of loganic acid, chlorogenic acid, dipsacoside B, and asperosaponin VI were upregulated, while the contents of 3,5-dicaffeoylquinic acid, 4-caffeoylquinic acid, loganin, and sweroside were downregulated. Our results demonstrated that ultra-high performance liquid chromatography with tandem mass spectrometry quantification combined with chemometrics is a viable method for quality evaluation of the raw Dipsacus asper and its wine-processed products. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Chemometric analysis for the detection of biogenic amines in Chilean Cabernet Sauvignon wines: a comparative study between organic and nonorganic production.

    Science.gov (United States)

    Yañez, L; Saavedra, J; Martínez, C; Córdova, A; Ganga, M A

    2012-08-01

    In this work, the presence of biogenic amines (BAs) was correlated with the type of wine grape culture (traditional or organic) and their concentration in the different stages of winemaking (must, alcoholic fermentation [AF] and malolactic fermentation [MLF]). The formation of BA occurred mainly during MLF in which the percentages for putrescine, cadaverine, phenylethylamine, histamine, and tyramine were 100%, 70%, 13%, 61%, and 44% for the wines produced with traditional grapes and 100%, 94%, 25%, 88%, and 13% for the wines produced with organic grapes, respectively. In general, these latter wines exhibited a lower concentration of total amines. The principal component analysis and partial least-square discriminate analysis indicated that the generation of BA has a certain behavioral pattern in the wines analyzed, which is associated with the different stages of wine production and with the type of culture (traditional or organic) used in the wine grapes. Chemometrics tools can be useful as a method of characterization and classification in a global overview of the process variables involved in the development of toxic chemicals in foods, such as the production of BA in wine. © 2012 Institute of Food Technologists®

  20. Thermodynamic Study of the Ion-Pair Complexation Equilibria of Dye and Surfactant by Spectral Titration and Chemometric Analysis

    Directory of Open Access Journals (Sweden)

    Hakimeh Abbasi Awal

    2017-12-01

    Full Text Available Surfactant-dye interactions are very important in chemical and dyeing processes. The dyes interact strongly with surfactant and show new spectrophotometric properties, so the UV-vis absorption spectrophotometric method has been used to study this process and extract some thermodynamic parameters. In this work, the association equilibrium between ionic dyes and ionic surfactant were studied by analyzing spectrophotometric data using chemometric methods. Methyl orange and crystal violet were selected as a model of cationic and anionic dyes respectively. Also sodium dodecyl sulphate and cetyltrimethylammonium bromide were selected as anionic and cationic surfactant, respectively. Hard model methods such as target transform fitting (TTF classical multi-wavelength fitting and soft model method such as multivariate curve resolution (MCR were used to analyze data that were recorded as a function of surfactant concentration in premicellar and postmicellar regions. Hard model methods were used to resolve data using ion-pair model in premicellar region in order to extract the concentration and spectral profiles of individual components and also related thermodynamic parameters. The equilibrium constants and other thermodynamic parameters of interaction of dyes with surfactants were determined by studying the dependence of their absorption spectra on the temperature in the range 293–308 K at concentrations of 5 × 10−6 M and 8 × 10−6 M for dye crystal violet and methyl orange, respectively. In postmicellar region, the MCR-ALS method was applied for resolving data and getting the spectra and concentration profiles in complex mixtures of dyes and surfactants.

  1. Chemometrics-assisted effect-directed analysis of crude and refined oil using comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry.

    Science.gov (United States)

    Radović, Jagoš R; Thomas, Kevin V; Parastar, Hadi; Díez, Sergi; Tauler, Romà; Bayona, Josep M

    2014-01-01

    An effect-directed analysis (EDA) of fresh and artificially weathered (evaporated, photooxidized) samples of North Sea crude oil and residual heavy fuel oil is presented. Aliphatic, aromatic, and polar oil fractions were tested for the presence of aryl hydrocarbon receptor (AhR) agonist and androgen receptor (AR) antagonist, demonstrating for the first time the AR antagonist effects in the aromatic and, to a lesser extent, polar fractions. An extension of the typical EDA strategy to include an N-way partial least-squares (N-PLS) model capable of relating the comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOFMS) data set to the bioassay data obtained from normal-phase LC fractions is proposed. The predicted AhR binding effects in the fresh and artificially weathered aromatic oil fractions facilitated the identification of alkyl-substituted three- and four-ring aromatic systems in the active fractions through the weighting of their contributions to the observed effects. A N-PLS chemometric model is demonstrated as a potentially useful strategy for future EDA studies that can streamline the compound identification process and provide additional reduction of samples' complexity. The AhR binding effects of the suspected compounds predicted by N-PLS and identified by GC × GC-TOFMS were confirmed using quantitative structure-activity relationship (QSAR) estimates.

  2. Chromatographic fingerprint analysis of secondary metabolites in citrus fruits peels using gas chromatography-mass spectrometry combined with advanced chemometric methods.

    Science.gov (United States)

    Parastar, Hadi; Jalali-Heravi, Mehdi; Sereshti, Hassan; Mani-Varnosfaderani, Ahmad

    2012-08-17

    Multivariate curve resolution (MCR) and multivariate clustering methods along with other chemometric methods are proposed to improve the analysis of gas chromatography-mass spectrometry (GC-MS) fingerprints of secondary metabolites in citrus fruits peels. In this way, chromatographic problems such as baseline/background contribution, low S/N peaks, asymmetric peaks, retention time shifts, and co-elution (overlapped and embedded peaks) occurred during GC-MS analysis of chromatographic fingerprints are solved using the proposed strategy. In this study, first, informative GC-MS fingerprints of citrus secondary metabolites are generated and then, whole data sets are segmented to some chromatographic regions. Each chromatographic segment for eighteen samples is column-wise augmented with m/z values as common mode to preserve bilinear model assumption needed for MCR analysis. Extended multivariate curve resolution alternating least squares (MCR-ALS) is used to obtain pure elution and mass spectral profiles for the components present in each chromatographic segment as well as their relative concentrations. After finding the best MCR-ALS model, the relative concentrations for resolved components are examined using principal component analysis (PCA) and k-nearest neighbor (KNN) clustering methods to explore similarities and dissimilarities among different citrus samples according to their secondary metabolites. In general, four clear-cut clusters are determined and the chemical markers (chemotypes) responsible to this differentiation are characterized by subsequent discriminate analysis using counter-propagation artificial neural network (CPANN) method. It is concluded that the use of proposed strategy is a more reliable and faster way for the analysis of large data sets like chromatographic fingerprints of natural products compared to conventional methods. Copyright © 2012 Elsevier B.V. All rights reserved.

  3. Qualitative and quantitative analysis on aroma characteristics of ginseng at different ages using E-nose and GC-MS combined with chemometrics.

    Science.gov (United States)

    Cui, Shaoqing; Wang, Jun; Yang, Liangcheng; Wu, Jianfeng; Wang, Xinlei

    2015-01-01

    Aroma profiles of ginseng samples at different ages were investigated using electronic nose (E-nose) and GC-MS techniques combined with chemometrics analysis. The bioactive ginsenoside and volatile oil content increased with age. E-nose performed well in the qualitative analyses. Both Principal Component Analysis (PCA) and Discriminant Functions Analysis (DFA) performed well when used to analyze ginseng samples, with the first two principal components (PCs) explaining 85.51% and the first two factors explaining 95.51% of the variations. Hierarchical Cluster Analysis (HCA) successfully clustered the different types of ginsengs into four groups. A total of 91 volatile constituents were identified. 50 of them were calculated and compared using GC-MS. The main fragrance ingredients were terpenes and alcohols, followed by aromatics and ester. The changes in terpenes, alcohols, aromatics, esters, and acids during the growth year once again confirmed the dominant role of terpenes. The Partial Least Squares (PLS) loading plot of gas sensors and aroma ingredients indicated that particular sensors were closely related to terpenes. The scores plot indicated that terpenes and its corresponding sensors contributed the most in grouping. As regards to quantitative analyze, 7 constituent of terpenes could be accurately explained and predicted by using gas sensors in PLS models. In predicting ginseng age using Back Propagation-Artificial Neural Networks (BP-ANN), E-nose data was found to predict more accurately than GC-MS data. E-nose measurement may be a potential method for determining ginseng age. The combination of GC-MS can help explain the hidden correlation between sensors and fragrance ingredients from two different viewpoints. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. Determination of cannabinoids in hemp nut products in Taiwan by HPLC-MS/MS coupled with chemometric analysis: quality evaluation and a pilot human study.

    Science.gov (United States)

    Chang, Chih-Wei; Tung, Chun-Wei; Tsai, Chin-Chuan; Wu, Yu-Tse; Hsu, Mei-Chich

    2017-06-01

    Hemp nuts are mature cannabis seeds obtained after shelling and that are commonly used in traditional Chinese medicine for treating functional constipation. In this work, we screened hemp nut products, classified them, and verified the legality of consuming them. A total of 18 products were purchased from Taiwan, China, and Canada. Validated high-performance liquid chromatography with tandem mass spectrometry methods were developed for analyzing the cannabinoid (i.e., Δ 9 -tetrahydrocannabinol (THC), cannabidiol (CBD), and cannabinol) content of the products and the concentration of urinary 11-nor-9-carboxy-THC. Chemometric techniques, namely hierarchical clustering analysis (HCA) and principal component analysis (PCA), were applied for rapidly classifying 11 concentrated powder products in Taiwan. A pilot human study comprising single and multiple administrations of a product with 1.5 µg/g of THC was conducted to examine the urinary 11-nor-9-carboxy-THC concentration. Through optimization of 3 2 full factorial design, using 60% isopropanol as the extraction solvent exhibited the highest yield of cannabinoids and was applied as the optimal condition in further analysis. The results of HCA and PCA on quality evaluation were in good agreement; however, the tested products possessed distinct CBD-to-THC ratios which ranged widely from 0.1:1 to 46.8:1. Particularly, the products with CBD-to-THC ratios higher than 1:1 were the majority in Taiwan. Our data suggested that all the tested hemp nut products met the Taiwan restriction criterion of 10 µg/g of THC. We propose a usual consumption amount of hemp nut products in Taiwan would unlikely to violate the cut-off point of 15 ng/mL of urinary 11-nor-9-carboxy-THC. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  5. A solid-phase extraction procedure coupled to 1H NMR, with chemometric analysis, to seek reliable markers of the botanical origin of honey.

    Science.gov (United States)

    Beretta, Giangiacomo; Caneva, Enrico; Regazzoni, Luca; Bakhtyari, Nazanin Golbamaki; Maffei Facino, Roberto

    2008-07-14

    The aim of this work was to establish an analytical method for identifying the botanical origin of honey, as an alternative to conventional melissopalynological, organoleptic and instrumental methods (gas-chromatography coupled to mass spectrometry (GC-MS), high-performance liquid chromatography HPLC). The procedure is based on the (1)H nuclear magnetic resonance (NMR) profile coupled, when necessary, with electrospray ionisation-mass spectrometry (ESI-MS) and two-dimensional NMR analyses of solid-phase extraction (SPE)-purified honey samples, followed by chemometric analyses. Extracts of 44 commercial Italian honeys from 20 different botanical sources were analyzed. Honeydew, chestnut and linden honeys showed constant, specific, well-resolved resonances, suitable for use as markers of origin. Honeydew honey contained the typical resonances of an aliphatic component, very likely deriving from the plant phloem sap or excreted into it by sap-sucking aphids. Chestnut honey contained the typical signals of kynurenic acid and some structurally related metabolite. In linden honey the (1)H NMR profile gave strong signals attributable to the mono-terpene derivative cyclohexa-1,3-diene-1-carboxylic acid (CDCA) and to its 1-O-beta-gentiobiosyl ester (CDCA-GBE). These markers were not detectable in the other honeys, except for the less common nectar honey from rosa mosqueta. We compared and analyzed the data by multivariate techniques. Principal component analysis found different clusters of honeys based on the presence of these specific markers. The results, although obviously only preliminary, suggest that the (1)H NMR profile (with HPLC-MS analysis when necessary) can be used as a reference framework for identifying the botanical origin of honey.

  6. A solid-phase extraction procedure coupled to {sup 1}H NMR, with chemometric analysis, to seek reliable markers of the botanical origin of honey

    Energy Technology Data Exchange (ETDEWEB)

    Beretta, Giangiacomo [Istituto di Chimica Farmaceutica e Tossicologica ' Pietro Pratesi' , Faculty of Pharmacy, University of Milan, via Mangiagalli 25, 20133 Milan (Italy)], E-mail: giangiacomo.beretta@unimi.it; Caneva, Enrico [Ciga - Centro Interdipartimentale Grandi Apparecchiature, University of Milan, via Golgi 19, 20133 Milan (Italy); Regazzoni, Luca; Bakhtyari, Nazanin Golbamaki; Maffei Facino, Roberto [Istituto di Chimica Farmaceutica e Tossicologica ' Pietro Pratesi' , Faculty of Pharmacy, University of Milan, via Mangiagalli 25, 20133 Milan (Italy)

    2008-07-14

    The aim of this work was to establish an analytical method for identifying the botanical origin of honey, as an alternative to conventional melissopalynological, organoleptic and instrumental methods (gas-chromatography coupled to mass spectrometry (GC-MS), high-performance liquid chromatography HPLC). The procedure is based on the {sup 1}H nuclear magnetic resonance (NMR) profile coupled, when necessary, with electrospray ionisation-mass spectrometry (ESI-MS) and two-dimensional NMR analyses of solid-phase extraction (SPE)-purified honey samples, followed by chemometric analyses. Extracts of 44 commercial Italian honeys from 20 different botanical sources were analyzed. Honeydew, chestnut and linden honeys showed constant, specific, well-resolved resonances, suitable for use as markers of origin. Honeydew honey contained the typical resonances of an aliphatic component, very likely deriving from the plant phloem sap or excreted into it by sap-sucking aphids. Chestnut honey contained the typical signals of kynurenic acid and some structurally related metabolite. In linden honey the {sup 1}H NMR profile gave strong signals attributable to the mono-terpene derivative cyclohexa-1,3-diene-1-carboxylic acid (CDCA) and to its 1-O-{beta}-gentiobiosyl ester (CDCA-GBE). These markers were not detectable in the other honeys, except for the less common nectar honey from rosa mosqueta. We compared and analyzed the data by multivariate techniques. Principal component analysis found different clusters of honeys based on the presence of these specific markers. The results, although obviously only preliminary, suggest that the {sup 1}H NMR profile (with HPLC-MS analysis when necessary) can be used as a reference framework for identifying the botanical origin of honey.

  7. Structural characterization and discrimination of Chinese medicinal materials with multiple botanical origins based on metabolite profiling and chemometrics analysis: Clematidis Radix et Rhizoma as a case study.

    Science.gov (United States)

    Guo, Lin-Xiu; Li, Rui; Liu, Ke; Yang, Jie; Li, Hui-Jun; Li, Song-Lin; Liu, Jian-Qun; Liu, Li-Fang; Xin, Gui-Zhong

    2015-12-18

    Traditional Chinese medicines (TCMs)-based products are becoming more and more popular over the world. To ensure the safety and efficacy, authentication of Chinese medicinal materials has been an important issue, especially for that with multiple botanical origins (one-to-multiple). Taking Clematidis Radix et Rhizoma (CRR) as a case study, we herein developed an integrated platform based on metabolite profiling and chemometrics analysis to characterize, classify, and predict the "one-to-multiple" herbs. Firstly, the predominant constituents, triterpenoid saponins, in three Clematis CRR were rapid characterized by a novel UPLC-QTOF/MS-based strategy, and a total of 49 triterpenoid saponins were identified. Secondly, metabolite profiling was performed by UPLC-QTOF/MS, and 4623 variables were extracted and aligned as dataset. Thirdly, by using pattern recognition analysis, a clear separation of the three Clematis CRR was achieved as well as a total number of 28 variables were screened as the valuable variables for discrimination. By matching with identified saponins, these 28 variables were corresponding to 10 saponins which were identified as marker compounds. Fourthly, based on the relative intensity of the marker compounds-related variables, genetic algorithm optimized support vector machines (GA-SVM) was employed to predict the species of CRR samples. The obtained model showed excellent prediction performance with a prediction accuracy of 100%. Finally, a heatmap visualization was employed for clarifying the distribution of identified saponins, which could be useful for phytochemotaxonomy study of Clematis herbs. These results indicated that our proposed platform was a powerful tool for chemical profiling and discrimination of herbs with multiple botanical origins, providing promising perspectives in tracking the formulation processes of TCMs products. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. A solid-phase extraction procedure coupled to 1H NMR, with chemometric analysis, to seek reliable markers of the botanical origin of honey

    International Nuclear Information System (INIS)

    Beretta, Giangiacomo; Caneva, Enrico; Regazzoni, Luca; Bakhtyari, Nazanin Golbamaki; Maffei Facino, Roberto

    2008-01-01

    The aim of this work was to establish an analytical method for identifying the botanical origin of honey, as an alternative to conventional melissopalynological, organoleptic and instrumental methods (gas-chromatography coupled to mass spectrometry (GC-MS), high-performance liquid chromatography HPLC). The procedure is based on the 1 H nuclear magnetic resonance (NMR) profile coupled, when necessary, with electrospray ionisation-mass spectrometry (ESI-MS) and two-dimensional NMR analyses of solid-phase extraction (SPE)-purified honey samples, followed by chemometric analyses. Extracts of 44 commercial Italian honeys from 20 different botanical sources were analyzed. Honeydew, chestnut and linden honeys showed constant, specific, well-resolved resonances, suitable for use as markers of origin. Honeydew honey contained the typical resonances of an aliphatic component, very likely deriving from the plant phloem sap or excreted into it by sap-sucking aphids. Chestnut honey contained the typical signals of kynurenic acid and some structurally related metabolite. In linden honey the 1 H NMR profile gave strong signals attributable to the mono-terpene derivative cyclohexa-1,3-diene-1-carboxylic acid (CDCA) and to its 1-O-β-gentiobiosyl ester (CDCA-GBE). These markers were not detectable in the other honeys, except for the less common nectar honey from rosa mosqueta. We compared and analyzed the data by multivariate techniques. Principal component analysis found different clusters of honeys based on the presence of these specific markers. The results, although obviously only preliminary, suggest that the 1 H NMR profile (with HPLC-MS analysis when necessary) can be used as a reference framework for identifying the botanical origin of honey

  9. Chemometric analysis of the secondary metabolite profile of Yarrow (Achillea collina Becker ex Rchb. affected by phloem feeding Myzus persicae Sulzer aphids

    Directory of Open Access Journals (Sweden)

    Annamaria Giorgi

    2010-07-01

    Full Text Available Yarrow (Achillea collina Becker ex Rchb. has a high content of secondary metabolites including phenolic acids. Among them, hydroxycinnamic acid such as chlorogenic acid and its derivatives were found to be the most abundant ones. The phloem feeding Myzus persicae Sulzer was hypothesized to affect the contents of secondary metabolites and change the metabolite profile. A high-performance liquid chromatography technique (HPLC was used to evaluate whether there is a difference in the phenolic profile between aphid infested and non-infested yarrow leaves. M. persicae colonies composed of between 20 and 30 individuals were allowed to feed for 10 and 20 days. Preprocessing was carried out to standardize the procedures in order to obtain optimal separation of analytes, good chromatographic peak shape and robustness of the results. The methanol extracts of leaves were analyzed by means of HPLC, and the time series of peak areas obtained from each extract were evaluated through chemometric analyses. Results of the phenolic fingerprints showed a specific chromatographic profile with 58 peaks. An autoregression analysis demonstrated the absence of correlation. The discriminant analysis carried out with the data satisfying the assumption of the absence of collinearity showed a significant effect of phloem feeding on soluble phenolic compounds and identified two peaks that separate aphid infested from non-infested plants. The hydroxycinnamic acids widely found in A. collina leaves were not affected by M. persicae feeding. The results are the basis for the current studies aiming at the identification of chemical compounds that correspond to the peaks.

  10. Assessment of the surface chemistry of carbon blacks by TGA-MS, XPS and inverse gas chromatography using statistical chemometric analysis

    International Nuclear Information System (INIS)

    Strzemiecka, Beata; Voelkel, Adam; Donate-Robles, Jessica; Martín-Martínez, José Miguel

    2014-01-01

    Highlights: • Carbon blacks with lower specific surface area had basic character (electron donor) due to C=O and C-O groups. • Carbon blacks with higher specific surface area had acidic character (acceptor electron) due to OH groups. • Total surface energy and its dispersive component of carbon blacks increased by increasing their specific surface area. (table) - Abstract: Four carbon blacks with different specific surface areas and surface chemistries (C32, C71, C159 and C178) were analyzed by transmission electron microscopy (TEM) and nitrogen adsorption isotherms at 77 K. Their surface chemistries were analyzed by X-ray photoelectron spectroscopy (XPS), thermal gravimetric analysis coupled with mass spectrometry (TGA-MS) and inverse gas chromatography (IGC). The carbon blacks contained 2.7–5.8 wt% volatiles corresponding to -OH, C-O, C=O and COO groups. The surface chemistry parameters obtained with the different experimental techniques were inter-related by using chemometric statistical analysis tools. The application of this methodology showed that the carbon blacks with lower specific surface area (C32 and C71) had basic character (electron donor) mainly due to C=O and C-O groups, whereas the carbon black with the highest specific surface area (C178) showed acidic character (acceptor electron) due to its high content of OH groups. Moreover, the total surface energy and the dispersive component of the surface energy of the carbon blacks increased with the increase of their specific surface area. In general the specific interactions of the carbon blacks also increased with the increase of their specific surface area although C71 is exceptional due to higher oxygen content corresponding to C-O groups

  11. Economical, Plain, and Rapid Authentication of Actaea racemosa L. (syn. Cimicifuga racemosa, Black Cohosh) Herbal Raw Material by Resilient RP-PDA-HPLC and Chemometric Analysis.

    Science.gov (United States)

    Bittner, Marian; Schenk, Regina; Springer, Andreas; Melzig, Matthias F

    2016-11-01

    The medicinal plant Actaea racemosa L. (Ranunculaceae, aka black cohosh) is widely used to treat climacteric complaints as an alternative to hormone substitution. Recent trials prove efficacy and safety of the approved herbal medicinal products from extracts of pharmaceutical quality. This led to worldwide increasing sales. A higher demand for the plant material results in problems with economically motivated adulteration. Thus, reliable tools for herbal drug authentication are necessary. To develop an economical, plain, and rapid method to distinguish between closely related American and Asian Actaea species, using securely established and resilient analytical methods coupled to a chemometric evaluation of the resulting data. We developed and validated a RP-PDA-HPLC method including an extraction by ultra-sonication to determine the genuine contents of partly hydrolysis-sensitive polyphenols in Actaea racemosa roots and rhizomes, and applied it to a large number of 203 Actaea samples consisting of seven species. We were able to generate reliable data with regards to the polyphenolic esters in the samples. The evaluation of this data by principle component analysis (PCA) made a discrimination between Asian Actaea species (sheng ma), one American Actaea species (Appalachian bugbane), and A. racemosa possible. The developed RP-PDA-HPLC method coupled to PCA is an excellent tool for authentication of the Actaea racemosa herbal drug, and can be a powerful addition to the TLC methods used in the dedicated pharmacopoeias, and is a promising alternative to expensive and lots of expertise requiring methods. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  12. Focus: Bridging the Chemistry-Statistics Gap: Chemometrics Research Conference.

    Science.gov (United States)

    Analytical Chemistry, 1985

    1985-01-01

    Presents highlights of a conference that provided an open forum for experts in statistics and in chemistry to exchange views on how research in statistical modeling and analysis can affect research in chemistry. A list of activities to reach new "customers" (including teaching chemometrics in high school) is included. (JN)

  13. Avaliação do uso de métodos quimiométricos em análise de solos Evaluation of the use of chemometric methods in soil analysis

    Directory of Open Access Journals (Sweden)

    Marcelo M. de Sena

    2000-08-01

    Full Text Available One of the major interests in soil analysis is the evaluation of its chemical, physical and biological parameters, which are indicators of soil quality (the most important is the organic matter. Besides there is a great interest in the study of humic substances and on the assessment of pollutants, such as pesticides and heavy metals, in soils. Chemometrics is a powerful tool to deal with these problems and can help soil researchers to extract much more information from their data. In spite of this, the presence of these kinds of strategies in the literature has obtained projection only recently. The utilization of chemometric methods in soil analysis is evaluated in this article. The applications will be divided in four parts (with emphasis in the first two: (i descriptive and exploratory methods based on Principal Component Analysis (PCA; (ii multivariate calibration methods (MLR, PCR and PLS; (iii methods such as Evolving Factor Analysis and SIMPLISMA; and (iv artificial intelligence methods, such as Artificial Neural Networks.

  14. Multi-responses extraction optimization combined with high-performance liquid chromatography-diode array detection-electrospray ionization-tandem mass spectrometry and chemometrics techniques for the fingerprint analysis of Aloe barbadensis Miller.

    Science.gov (United States)

    Zhong, Jia-Sheng; Wan, Jin-Zhi; Ding, Wen-Jing; Wu, Xiao-Fang; Xie, Zhi-Yong

    2015-03-25

    A quality control strategy using high-performance liquid chromatography-diode array detector-electrospray ionization-tandem mass spectrometry (HPLC-DAD-ESI-MS/MS) coupled with chemometrics analysis was proposed for Aloe barbadensis Miller. Firstly, the extraction conditions including methanol concentration, extraction time and solvent-to-material ratio were optimized by multi-responses optimization based on response surface methodology (RSM). The optimum conditions were achieved by Derringer's desirability function and experimental validation implied that the established model exhibited favorable prediction ability. Then, HPLC fingerprint consisting of 27 common peaks was developed among 15 batches of A. barbadensis samples. 25 common peaks were identified using HPLC-DAD-ESI-MS/MS method by their spectral characteristics or comparison with the authentic standards. Chemometrics techniques including similarity analysis (SA), principal components analysis (PCA) and hierarchical clustering analysis (HCA) were implemented to classify A. barbadensis samples. The results demonstrated that all A. barbadensis samples shared similar chromatographic patterns as well as differences. These achievements provided an effective, reliable and comprehensive quality control method for A. barbadensis. Copyright © 2015 Elsevier B.V. All rights reserved.

  15. Qualitative and quantitative analysis of multiple components for quality control of Deng-Zhan-Sheng-Mai capsules by ultra high performance liquid chromatography tandem mass spectrometry method coupled with chemometrics.

    Science.gov (United States)

    Jiang, Pin; Lu, Yan; Chen, Daofeng

    2017-02-01

    Deng-Zhan-Sheng-Mai capsules are a well-known traditional Chinese patent medicine that was developed in China for the treatment of ischemic stroke. Its quality control focuses on Erigerontis Herba but ignores the contributions of Ginseng Radix et Rhizoma, Schisandrae Chinensis Fructus, and Ophiopogonis Radix. To improve the quality standards for this medicine, this work reports the application of a systematic ultra high performance liquid chromatography tandem mass spectrometric method coupled with chemometrics. Three qualitative and quantitative parameters are established for the evaluation of quality: chemical profiling, the relationship between the contents of 18 compounds and the antioxidant activity, and chemometric analysis. A total of 55 compounds, including 20 phenolic acids, 10 flavonoids, 15 saponins, and 10 lignans, were identified. The method for the quantitative determination of the aforementioned 18 compounds was validated. The limit of quantification ranged from 0.13 to 9.60 ng/mL. The overall recoveries ranged from 95.31 to 103.54%. Hierarchical cluster analysis and principal component analysis were applied to the data of 18 components in ten batches of samples. Nine compounds, including scutellarin, 3,5-O-dicaffeoylquinic acid, 4,5-O-dicaffeoylquinic acid, ginsenoside Rb1, ginsenoside Re, ginsenoside Rg1, ophiopogonin D, schisandrin, and schisandrol B, are suggested as chemical markers for evaluating the quality. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Chemometrics applied to quality control and metabolomics for traditional Chinese medicines.

    Science.gov (United States)

    Liu, Shao; Liang, Yi-Zeng; Liu, Hai-Tao

    2016-03-15

    Traditional Chinese medicines (TCMs) bring a great challenge in quality control and evaluating the efficacy because of their complexity of chemical composition. Chemometric techniques provide a good opportunity for mining more useful chemical information from TCMs. Then, the application of chemometrics in the field of TCMs is spontaneous and necessary. This review focuses on the recent various important chemometrics tools for chromatographic fingerprinting, including peak alignment information features, baseline correction and applications of chemometrics in metabolomics and modernization of TCMs, including authentication and evaluation of the quality of TCMs, evaluating the efficacy of TCMs and essence of TCM syndrome. In the conclusions, the general trends and some recommendations for improving chromatographic metabolomics data analysis are provided. Copyright © 2016 Elsevier B.V. All rights reserved.

  17. Basic Study of Defective Ammunition Detection by the Combination of PGNAA (Prompt Gamma-ray Neutron Activation Analysis) and Chemometrics

    International Nuclear Information System (INIS)

    Im, Hee Jung; Song, Byoung Chul; Shin, Jae Kon; Park, Yong Joon; Song, Kyu Seok

    2010-01-01

    We are interested in evaluating detection capability of defective ammunition in store for years even decades by using prompt gamma-ray neutron activation analysis (PGNAA) method. The PGNAA method can be used for multielemental analysis of ammunition to check the inner elemental composition changes. At first, in this study, instead of the real experimental gamma spectrum data from PGNAA, the gamma spectrum data from MCNP transport code simulation were obtained to observe discriminant classes for defective ammunition by adding 10% moisture. For this, the collected MCNP data were applied to principal component analysis (PCA) for the effective pattern recognition

  18. Investigating the provenance of un-dyed spun cotton fibre using multi-isotope profiles and chemometric analysis.

    Science.gov (United States)

    Daéid, Niamh Nic; Meier-Augenstein, Wolfram; Kemp, Helen F

    2011-07-15

    The analysis of un-dyed spun cotton fibres can be challenging within a forensic science context where discrimination of one fibre from another is of importance. Conventional microscopic and chemical analysis of these fibres is generally unsuccessful because of their similar morphology. In this work we have explored the potential of isotope ratio mass spectrometry (IRMS) as a tool for spun cotton fibre analysis in an attempt to reveal any discriminatory information available. Seven different batches of un-dyed spun cotton fibre from four different countries were analysed. A combination of the hydrogen and oxygen isotopic data facilitated the correct association of the samples, demonstrating, for the first time, the applicability of IRMS to fibre analysis in this way. Copyright © 2011 John Wiley & Sons, Ltd.

  19. The comparative study of four Portuguese sixteenth-century illuminated Manueline Charters based on spectroscopy and chemometrics analysis

    Science.gov (United States)

    Miguel, Catarina; Barrocas-Dias, Cristina; Ferreira, Teresa; Candeias, António

    2017-01-01

    The comparative study based on spectroscopic analysis of the materials used to produce four sixteenth-century Manueline Charters (the Charters of Alcochete, Terena, Alandroal and Évora) was performed following a systematic analytical approach. SEM-EDS, μ-Raman and μ-FTIR analysis highlighted interesting features between them, namely the use of different pigments and colourants (such as different green and yellow pigments), the presence of pigments alterations and the use of a non-expected extemporaneous material (with the presence of titanium white in the Charter of Alcochete). Principal component analysis restricted to the C-H absorption region (3000-2840 cm-1) was applied to 36 infrared spectra of blue historical samples from the Charters of Alcochete, Terena, Alandroal and Évora, suggesting the use of a mixture of a triglyceride and polysaccharide as binder.

  20. Characterization of Leaf Extracts ofSchinus terebinthifoliusRaddi by GC-MS and Chemometric Analysis.

    Science.gov (United States)

    Carneiro, Fabíola B; Lopes, Pablo Q; Ramalho, Ricardo C; Scotti, Marcus T; Santos, Sócrates G; Soares, Luiz A L

    2017-10-01

    Schinus terebinthifolius Raddi belongs to Anacardiacea family and is widely known as "aroeira." This species originates from South America, and its extracts are used in folk medicine due to its therapeutic properties, which include antimicrobial, anti-inflammatory, and antipyretic effects. The complexity and variability of the chemical constitution of the herbal raw material establishes the quality of the respective herbal medicine products. Thus, the purpose of this study was to investigate the variability of the volatile compounds from leaves of S. terebinthifolius . The samples were collected from different states of the Northeast region of Brazil and analyzed with a gas chromatograph coupled to a mass spectrometer (GC-MS). The collected data were analyzed using multivariate data analysis. The samples' chromatograms, obtained by GC-MS, showed similar chemical profiles in a number of peaks, but some differences were observed in the intensity of these analytical markers. The chromatographic fingerprints obtained by GC-MS were suitable for discrimination of the samples; these results along with a statistical treatment (principal component analysis [PCA]) were used as a tool for comparative analysis between the different samples of S. terebinthifolius . The experimental data show that the PCA used in this study clustered the samples into groups with similar chemical profiles, which builds an appropriate approach to evaluate the similarity in the phytochemical pattern found in the different leaf samples. The leave extracts of Schinus terebinthifolius were obtained by turbo-extractionThe extracts were partitioned with hexane and analyzed by GC-MSThe chromatographic data were analyzed using the principal component analysis (PCA)The PCA plots showed the main compounds (phellandrene, limonene, and carene), which were used to group the samples from a different geographical location in accordance to their chemical similarity. Abbreviations used: AL: Alagoas, BA: Bahia, CE

  1. Quality assessment of raw and processed Arctium lappa L. through multicomponent quantification, chromatographic fingerprint, and related chemometric analysis.

    Science.gov (United States)

    Qin, Kunming; Wang, Bin; Li, Weidong; Cai, Hao; Chen, Danni; Liu, Xiao; Yin, Fangzhou; Cai, Baochang

    2015-05-01

    In traditional Chinese medicine, raw and processed herbs are used to treat different diseases. Suitable quality assessment methods are crucial for the discrimination between raw and processed herbs. The dried fruit of Arctium lappa L. and their processed products are widely used in traditional Chinese medicine, yet their therapeutic effects are different. In this study, a novel strategy using high-performance liquid chromatography and diode array detection coupled with multivariate statistical analysis to rapidly explore raw and processed Arctium lappa L. was proposed and validated. Four main components in a total of 30 batches of raw and processed Fructus Arctii samples were analyzed, and ten characteristic peaks were identified in the fingerprint common pattern. Furthermore, similarity evaluation, principal component analysis, and hierachical cluster analysis were applied to demonstrate the distinction. The results suggested that the relative amounts of the chemical components of raw and processed Fructus Arctii samples are different. This new method has been successfully applied to detect the raw and processed Fructus Arctii in marketed herbal medicinal products. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Contribution of Bacillus Isolates to the Flavor Profiles of Vanilla Beans Assessed through Aroma Analysis and Chemometrics

    Directory of Open Access Journals (Sweden)

    Fenglin Gu

    2015-10-01

    Full Text Available Colonizing Bacillus in vanilla (Vanilla planifolia Andrews beans is involved in glucovanillin hydrolysis and vanillin formation during conventional curing. The flavor profiles of vanilla beans under Bacillus-assisted curing were analyzed through gas chromatography-mass spectrometry, electronic nose, and quantitative sensory analysis. The flavor profiles were analytically compared among the vanilla beans under Bacillus-assisted curing, conventional curing, and non-microorganism-assisted curing. Vanilla beans added with Bacillus vanillea XY18 and Bacillus subtilis XY20 contained higher vanillin (3.58% ± 0.05% and 3.48% ± 0.10%, respectively than vanilla beans that underwent non-microorganism-assisted curing and conventional curing (3.09% ± 0.14% and 3.21% ± 0.15%, respectively. Forty-two volatiles were identified from endogenous vanilla metabolism. Five other compounds were identified from exogenous Bacillus metabolism. Electronic nose data confirmed that vanilla flavors produced through the different curing processes were easily distinguished. Quantitative sensory analysis confirmed that Bacillus-assisted curing increased vanillin production without generating any unpleasant sensory attribute. Partial least squares regression further provided a correlation model of different measurements. Overall, we comparatively analyzed the flavor profiles of vanilla beans under Bacillus-assisted curing, indirectly demonstrated the mechanism of vanilla flavor formation by microbes.

  3. Chemometric Analysis of the Volatile Compounds Generated by Aspergillus carbonarius Strains Isolated from Grapes and Dried Vine Fruits

    Directory of Open Access Journals (Sweden)

    Zhan Cheng

    2018-02-01

    Full Text Available Ochratoxin A (OTA contamination in grape production is an important problem worldwide. Microbial volatile organic compounds (MVOCs have been demonstrated as useful tools to identify different toxigenic strains. In this study, Aspergillus carbonarius strains were classified into two groups, moderate toxigenic strains (MT and high toxigenic strains (HT, according to OTA-forming ability. The MVOCs were analyzed by GC-MS and the data processing was based on untargeted profiling using XCMS Online software. Orthogonal projection to latent structures discriminant analysis (OPLS-DA was performed using extract ion chromatogram GC-MS datasets. For contrast, quantitative analysis was also performed. Results demonstrated that the performance of the OPLS-DA model of untargeted profiling was better than the quantitative method. Potential markers were successfully discovered by variable importance on projection (VIP and t-test. (E-2-octen-1-ol, octanal, 1-octen-3-one, styrene, limonene, methyl-2-phenylacetate and 3 unknown compounds were selected as potential markers for the MT group. Cuparene, (Z-thujopsene, methyl octanoate and 1 unknown compound were identified as potential markers for the HT groups. Finally, the selected markers were used to construct a supported vector machine classification (SVM-C model to check classification ability. The models showed good performance with the accuracy of cross-validation and test prediction of 87.93% and 92.00%, respectively.

  4. Contribution of Bacillus Isolates to the Flavor Profiles of Vanilla Beans Assessed through Aroma Analysis and Chemometrics.

    Science.gov (United States)

    Gu, Fenglin; Chen, Yonggan; Fang, Yiming; Wu, Guiping; Tan, Lehe

    2015-10-09

    Colonizing Bacillus in vanilla (Vanilla planifolia Andrews) beans is involved in glucovanillin hydrolysis and vanillin formation during conventional curing. The flavor profiles of vanilla beans under Bacillus-assisted curing were analyzed through gas chromatography-mass spectrometry, electronic nose, and quantitative sensory analysis. The flavor profiles were analytically compared among the vanilla beans under Bacillus-assisted curing, conventional curing, and non-microorganism-assisted curing. Vanilla beans added with Bacillus vanillea XY18 and Bacillus subtilis XY20 contained higher vanillin (3.58%±0.05% and 3.48%±0.10%, respectively) than vanilla beans that underwent non-microorganism-assisted curing and conventional curing (3.09%±0.14% and 3.21%±0.15%, respectively). Forty-two volatiles were identified from endogenous vanilla metabolism. Five other compounds were identified from exogenous Bacillus metabolism. Electronic nose data confirmed that vanilla flavors produced through the different curing processes were easily distinguished. Quantitative sensory analysis confirmed that Bacillus-assisted curing increased vanillin production without generating any unpleasant sensory attribute. Partial least squares regression further provided a correlation model of different measurements. Overall, we comparatively analyzed the flavor profiles of vanilla beans under Bacillus-assisted curing, indirectly demonstrated the mechanism of vanilla flavor formation by microbes.

  5. Chemometric analysis of alternations in coal ash quality induced by application of different mechano-chemical processing parameters

    Directory of Open Access Journals (Sweden)

    Terzić Anja

    2017-01-01

    Full Text Available The coal fly ash mechano-chemical activation conducted via high energy ultra-centrifugal mill was optimized using mathematical and statistical tools. The aim of the investigation was to accent the merits of alternations in ash processing schemes with a referral regarding the enhancement of the ash reactivity that will lead to its higher volume utilization as a cement replacement in concrete design. The impact of the processing parameters sets (number of rotor revolutions, current intensity, activation period, circumferential rotor speed, mill capacity on the on the product’s quality factors (grain size distribution, average grain size, micronization level, agglomeration tendency, specific surface area was assessed via Response surface method, Standard score analysis and Principal component analysis in order to obtain the most favorable output. Developed models were able to meticulously predict quality parameters in an extensive range of processing parameters. The calculated r2 values were in the range of 0.846-0.999. The optimal ash sample, that reached the Standard Score as high as 0.93, was produced using a set of processing parameters appropriate to experimental sequence with applied 120 μm sieve mesh. The microstructural characteristics were assessed using image-processing values and histogram plots of the activated fly ash SEM images. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. ON 172057, Grant no. III 45008, Grant no. TR 31055 and Grant no. TR 34006

  6. Differentiation of frog fats from vegetable and marine oils by Fourier Transform Infrared Spectroscopy and chemometric analysis

    Directory of Open Access Journals (Sweden)

    A. N. Nina Naquiah

    2015-01-01

    Full Text Available The agro-based production and consumption of frogs coupled with world-wide trading have been increased in the recent years giving rise to the risk of frog fat adulteration in expensive vegetable and marine oils. For the first time, we profiled here frog fats using Fourier Transform Infrared (FTIR Spectroscopy coupled with multivariate principal component analysis (PCA. The comparison of the FTIR spectral absorbance intensities demonstrated linkage of frog fats to other edible fats and oils. Three commercially available marine oils and three vegetables oils were studied with frog fats and clear pattern of clusters with distinctive identifiable features were obtained through PCA modeling. PCA analysis identified 2922.21 cm-1, 2852.88 cm-1, 1745.45 cm-1, 1158.29 cm-1 and 721.51 cm-1 FTIR-frequencies as the most discriminating variables influencing the group separation into different clusters. This fundamental study has clear implications in the identification of frog fat from its marine and vegetable counterparts for the potential detection of frog fat adulteration in various fat and oils.

  7. Multiplexed analysis combining distinctly-sized CdTe-MPA quantum dots and chemometrics for multiple mutually interfering analyte determination.

    Science.gov (United States)

    Bittar, Dayana B; Ribeiro, David S M; Páscoa, Ricardo N M J; Soares, José X; Rodrigues, S Sofia M; Castro, Rafael C; Pezza, Leonardo; Pezza, Helena R; Santos, João L M

    2017-11-01

    Semiconductor quantum dots (QDs) have demonstrated a great potential as fluorescent probes for heavy metals monitoring. However, their great reactivity, whose tunability could be difficult to attain, could impair selectivity yielding analytical results with poor accuracy. In this work, the combination in the same analysis of multiple QDs, each with a particular ability to interact with the analyte, assured a multi-point detection that was not only exploited for a more precise analyte discrimination but also for the simultaneous discrimination of multiple mutually interfering species, in the same sample. Three different MPA-CdTe QDs (2.5, 3.0 and 3.8nm) with a good size distribution, confirmed by the FWHM values of 48.6, 55.4 and 80.8nm, respectively, were used. Principal component analysis (PCA) and partial least squares regression (PLS) were used for fluorescence data analysis. Mixtures of two MPA-CdTe QDs, emitting at different wavelength namely 549/566, 549/634 and 566/634nm were assayed. The 549/634nm emitting QDs mixture provided the best results for the discrimination of distinct ions on binary and ternary mixtures. The obtained RMSECV and R 2 CV values for the binary mixture were good, namely, from 0.01 to 0.08mgL -1 and from 0.74 to 0.89, respectively. Regarding the ternary mixture the RMSECV and R 2 CV values were good for Hg(II) (0.06 and 0.73mgL -1 , respectively) and Pb(II) (0.08 and 0.87mg L -1 , respectively) and acceptable for Cu(II) (0.02 and 0.51mgL -1 , respectively). In conclusion, the obtained results showed that the developed approach is capable of resolve binary and ternary mixtures of Pb (II), Hg (II) and Cu (II), providing accurate information about lead (II) and mercury (II) concentration and signaling the occurrence of Cu (II). Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Unsupervised classification of petroleum Certified Reference Materials and other fuels by chemometric analysis of gas chromatography-mass spectrometry data.

    Science.gov (United States)

    de Carvalho Rocha, Werickson Fortunato; Schantz, Michele M; Sheen, David A; Chu, Pamela M; Lippa, Katrice A

    2017-06-01

    As feedstocks transition from conventional oil to unconventional petroleum sources and biomass, it will be necessary to determine whether a particular fuel or fuel blend is suitable for use in engines. Certifying a fuel as safe for use is time-consuming and expensive and must be performed for each new fuel. In principle, suitability of a fuel should be completely determined by its chemical composition. This composition can be probed through use of detailed analytical techniques such as gas chromatography-mass spectroscopy (GC-MS). In traditional analysis, chromatograms would be used to determine the details of the composition. In the approach taken in this paper, the chromatogram is assumed to be entirely representative of the composition of a fuel, and is used directly as the input to an algorithm in order to develop a model that is predictive of a fuel's suitability. When a new fuel is proposed for service, its suitability for any application could then be ascertained by using this model to compare its chromatogram with those of the fuels already known to be suitable for that application. In this paper, we lay the mathematical and informatics groundwork for a predictive model of hydrocarbon properties. The objective of this work was to develop a reliable model for unsupervised classification of the hydrocarbons as a prelude to developing a predictive model of their engine-relevant physical and chemical properties. A set of hydrocarbons including biodiesel fuels, gasoline, highway and marine diesel fuels, and crude oils was collected and GC-MS profiles obtained. These profiles were then analyzed using multi-way principal components analysis (MPCA), principal factors analysis (PARAFAC), and a self-organizing map (SOM), which is a kind of artificial neural network. It was found that, while MPCA and PARAFAC were able to recover descriptive models of the fuels, their linear nature obscured some of the finer physical details due to the widely varying composition of the

  9. Multielemental Composition of Suet Oil Based on Quantification by Ultrawave/ICP-MS Coupled with Chemometric Analysis

    Directory of Open Access Journals (Sweden)

    Jun Jiang

    2014-04-01

    Full Text Available Suet oil (SO has been used commonly for food and medicine preparation. The determination of its elemental composition has became an important challenge for human safety and health owing to its possible contents of heavy metals or other elements. In this study, ultrawave single reaction chamber microwave digestion (Ultrawave and inductively coupled plasma-mass spectrometry (ICP-MS analysis was performed to determine 14 elements (Pb, As, Hg, Cd, Fe, Cu, Mn, Ti, Ni, V, Sr, Na, Ka and Ca in SO samples. Furthermore, the multielemental content of 18 SO samples, which represented three different sources in China: Qinghai, Anhui and Jiangsu, were evaluated and compared. The optimal ultrawave digestion conditions, namely, the optimal time (35 min, temperature (210 °C and pressure (90 bar, were screened by Box-Behnken design (BBD. Eighteen samples were successfully classified into three groups by principal component analysis (PCA according to the contents of 14 elements. The results showed that all SO samples were rich in elements, but with significant differences corresponding to different origins. The outliers and majority of SO could be discriminated by PCA according to the multielemental content profile. The results highlighted that the element distribution was associated with the origins of SO samples. The proposed ultrawave digestion system was quite efficient and convenient, which could be mainly attributed to its high pressure and special high-throughput for the sample digestion procedure. Our established method could be useful for the quality control and standardization of elements in SO samples and products.

  10. Potential of spectroscopic techniques and chemometric analysis for rapid measurement of docosahexaenoic acid and eicosapentaenoic acid in algal oil.

    Science.gov (United States)

    Wu, Di; He, Yong

    2014-09-01

    Developing rapid methods for measuring long-chain ω-3 (n-3) poly-unsaturated fatty acid (LCPUFA) contents has been a crucial request from the algal oil industry. In this study, four spectroscopy techniques, namely visible and short-wave near infra-red (Vis-SNIR), long-wave near infra-red (LNIR), mid-infra-red (MIR) and nuclear magnetic resonance (NMR) spectroscopy, were exploited for determining the docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) contents in algal oil. The best prediction for both DHA and EPA were achieved by NMR spectroscopy, in which the determination coefficients of cross-validation (rCV(2)) values were 0.963 and 0.967 for two LCPUFAs. The performances of Vis-SNIR and LNIR spectroscopy were also accepted. The variable selection was proved as an efficient and necessary step for the spectral analysis in this study. The results were promising and implied that spectroscopy techniques have a great potential for assessment of DHA and EPA in algal oil. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Laser-Induced Breakdown Spectroscopy coupled with chemometrics for the analysis of steel: The issue of spectral outliers filtering

    Science.gov (United States)

    Pořízka, Pavel; Klus, Jakub; Prochazka, David; Képeš, Erik; Hrdlička, Aleš; Novotný, Jan; Novotný, Karel; Kaiser, Jozef

    2016-09-01

    In this manuscript we highlight the necessity of outlier filtering prior the multivariate classification in Laser-Induced Breakdown Spectroscopy (LIBS) analyses. For the purpose of classification we chose to analyse BAM steel standards that possess similar composition of major and trace elements. To assess the improvement in figures of merit we compared the performance of three outlier filtering approaches (based on Principal Component Analysis, linear correlation and total spectral intensity) already separately discussed in the LIBS literature. The truncated data set was classified using Soft Independent Modelling of Class Analogies (SIMCA). Yielded results showed significant improvement in the performance of multivariate classification coupled to filtered data. The best performance was observed for the total spectral intensity filtering approach gaining the analytical figures of merit (overall accuracy, sensitivity, and specificity) over 98%. It is noteworthy that the results showed relatively low sensitivity and high specificity of the SIMCA algorithm regardless of the presence of outliers in the data sets. Moreover, it was shown that the variance in the data topology of training and testing data sets has a great impact on the consequent data classification.

  12. Profiling of Fatty Acids Composition in Suet Oil Based on GC–EI-qMS and Chemometrics Analysis

    Directory of Open Access Journals (Sweden)

    Jun Jiang

    2015-01-01

    Full Text Available Fatty acid (FA composition of suet oil (SO was measured by precolumn methylesterification (PME optimized using a Box–Behnken design (BBD and gas chromatography/electron ionization-quadrupole mass spectrometry (GC–EI-qMS. A spectral library (NIST 08 and standard compounds were used to identify FAs in SO representing 90.89% of the total peak area. The ten most abundant FAs were derivatized into FA methyl esters (FAMEs and quantified by GC–EI-qMS; the correlation coefficient of each FAME was 0.999 and the lowest concentration quantified was 0.01 μg/mL. The range of recovery of the FAMEs was 82.1%–98.7% (relative standard deviation 2.2%–6.8%. The limits of quantification (LOQ were 1.25–5.95 μg/L. The number of carbon atoms in the FAs identified ranged from 12 to 20; hexadecanoic and octadecanoic acids were the most abundant. Eighteen samples of SO purchased from Qinghai, Anhui and Jiangsu provinces of China were categorized into three groups by principal component analysis (PCA according to the contents of the most abundant FAs. The results showed SOs samples were rich in FAs with significantly different profiles from different origins. The method described here can be used for quality control and SO differentiation on the basis of the FA profile.

  13. Profiling of Fatty Acids Composition in Suet Oil Based on GC–EI-qMS and Chemometrics Analysis

    Science.gov (United States)

    Jiang, Jun; Jia, Xiaobin

    2015-01-01

    Fatty acid (FA) composition of suet oil (SO) was measured by precolumn methylesterification (PME) optimized using a Box–Behnken design (BBD) and gas chromatography/electron ionization-quadrupole mass spectrometry (GC–EI-qMS). A spectral library (NIST 08) and standard compounds were used to identify FAs in SO representing 90.89% of the total peak area. The ten most abundant FAs were derivatized into FA methyl esters (FAMEs) and quantified by GC–EI-qMS; the correlation coefficient of each FAME was 0.999 and the lowest concentration quantified was 0.01 μg/mL. The range of recovery of the FAMEs was 82.1%–98.7% (relative standard deviation 2.2%–6.8%). The limits of quantification (LOQ) were 1.25–5.95 μg/L. The number of carbon atoms in the FAs identified ranged from 12 to 20; hexadecanoic and octadecanoic acids were the most abundant. Eighteen samples of SO purchased from Qinghai, Anhui and Jiangsu provinces of China were categorized into three groups by principal component analysis (PCA) according to the contents of the most abundant FAs. The results showed SOs samples were rich in FAs with significantly different profiles from different origins. The method described here can be used for quality control and SO differentiation on the basis of the FA profile. PMID:25636032

  14. Chemometric analysis of groundwater quality data around municipal landfill and paper factory and their potential influence on population's health.

    Science.gov (United States)

    Gvozdić, Vlatka; Cačić, Ljiljana; Brana, Josip; Puntarić, Dinko; Vidosavljević, Domagoj

    2012-02-01

    To assess the level of 15 groundwater quality parameters in groundwater samples collected around municipal landfill and paper factory in order to evaluate usefulness of the groundwater and its possible implication on the human health. Obtained data have been analyzed by principal component analysis (PCA) technique, in order to differentiate the groundwater samples on the basis of their compositional differences and origin. Wastes and effluents from municipal landfill did not contribute significantly to the pollution of the aquatic medium. Groundwater degradation caused by high contents of nitrate, mineral oils, organic and inorganic matters was particularly expressed in the narrow area of the city centre, near the paper factory and most likely it has occurred over a long period of time. The results have shown that the concentrations of the most measured parameters (NO3-N, NH4-N, oils, organic matter, Fe, Pb, Ni and Cr) were above allowed limits for drinking and domestic purposes. This study has provided important information on ecological status of the groundwater systems and for identification of groundwater quality parameters with concentrations above allowable limits for human consumption. The results generally revealed that groundwater assessed in this study mainly does not satisfy safe limits for drinking water and domestic use. As a consequence, contaminated groundwater becomes a large hygienic and toxicological problem, since it considerably impedes groundwater utilization. Even though, all of these contaminants have not yet reached toxic levels, they still represent long term risk for health of the population.

  15. Seized cannabis seeds cultivated in greenhouse: A chemical study by gas chromatography-mass spectrometry and chemometric analysis.

    Science.gov (United States)

    Mariotti, Kristiane de Cássia; Marcelo, Marcelo Caetano Alexandre; Ortiz, Rafael S; Borille, Bruna Tassi; Dos Reis, Monique; Fett, Mauro Sander; Ferrão, Marco Flôres; Limberger, Renata Pereira

    2016-01-01

    Cannabis sativa L. is cultivated in most regions of the world. In 2013, the Brazilian Federal Police (BFP) reported 220 tons of marijuana seized and about 800,000 cannabis plants eradicated. Efforts to eradicate cannabis production may have contributed to the development of a new form of international drug trafficking in Brazil: the sending of cannabis seeds in small amounts to urban centers by logistics postal. This new and increasing panorama of cannabis trafficking in Brazil, encouraged the chemical study of cannabis seeds cultivated in greenhouses by gas-chromatography coupled with mass spectrometry (GC-MS) associated with exploratory and discriminant analysis. Fifty cannabis seeds of different varieties and brands, seized by the BFP were cultivated under predefined conditions for a period of 4.5 weeks, 5.5 weeks, 7.5 weeks, 10 weeks and 12 weeks. Aerial parts were analyzed and cannabigerol, cannabinol, cannabidiol, cannabichromene Δ9-tetrahydrocannabinol (THC) and other terpenoids were detected. The chromatographic chemical profiles of the samples were significantly different, probably due to different variety, light exposition and age. THC content increased with the age of the plant, however, for other cannabinoids, this correlation was not observed. The chromatograms were plotted in a matrix with 50 rows (samples) and 3886 columns (abundance in a retention time) and submitted to PCA, HCA and PLS-DA after pretreatment (normalization, first derivative and autoscale). The PCA and HCA showed age separation between samples however it was not possible to verify the separation by varieties and brands. The PLS-DA classification provides a satisfactory prediction of plant age. Copyright © 2015 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

  16. Effect of the acid treatment conditions of kaolinite on etheramine adsorption: A comparative analysis using chemometric tools.

    Science.gov (United States)

    Leal, Paulo Vitor Brandão; Magriotis, Zuy Maria; Sales, Priscila Ferreira de; Papini, Rísia Magriotis; Viana, Paulo Roberto de Magalhães

    2017-07-15

    The present work evaluated the effect of the acid treatment conditions of natural kaolinite (NK) regarding its efficiency in removing etheramine. The treatment was conducted using sulfuric acid at the concentrations of 1 mol L -1 (KA-01), 2 mol L -1 (KA-02) and 5 mol L -1 (KA-05) at 85 °C. The obtained adsorbents were characterized by X-ray fluorescence, X-ray diffraction, N 2 adsorption/desorption isotherms, zeta potential analysis and infrared spectroscopy. The Response Surface Method was used to optimize adsorption parameters (initial concentration of etheramine, adsorbent mass and pH of the solution). The results, described by means of a central composite design, were adjusted to the quadratic model. Results revealed that the adsorption was more efficient at the etheramine concentration of 400 mg L -1 , pH 10 and adsorbent mass of 0.1 g for NK and 0.2 g for KA-01, KA-02 and KA-05. The sample KA-02 presented a significant increase of etheramine removal compared to the NK sample. The adsorption kinetics conducted under optimized conditions showed that the system reached the equilibrium in approximately 30 min. The kinetic data were better adjusted to the pseudo-second order model. The isotherm data revealed that the Sips model was the most adequate one. The calculation of E ads allowed to infer that the mechanism for etheramine removal in all the evaluated samples was chemisorption. The reuse tests showed that, after four uses, the efficiency of adsorbents in removing etheramine did not suffer significant modifications, which makes the use of kaolinite to treat effluents from the reverse flotation of iron ore feasible. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Rapid and sensitive analysis of 27 underivatized free amino acids, dipeptides, and tripeptides in fruits of Siraitia grosvenorii Swingle using HILIC-UHPLC-QTRAP(®)/MS (2) combined with chemometrics methods.

    Science.gov (United States)

    Zhou, Guisheng; Wang, Mengyue; Li, Yang; Peng, Ying; Li, Xiaobo

    2015-08-01

    In the present study, a new strategy based on chemical analysis and chemometrics methods was proposed for the comprehensive analysis and profiling of underivatized free amino acids (FAAs) and small peptides among various Luo-Han-Guo (LHG) samples. Firstly, the ultrasound-assisted extraction (UAE) parameters were optimized using Plackett-Burman (PB) screening and Box-Behnken designs (BBD), and the following optimal UAE conditions were obtained: ultrasound power of 280 W, extraction time of 43 min, and the solid-liquid ratio of 302 mL/g. Secondly, a rapid and sensitive analytical method was developed for simultaneous quantification of 24 FAAs and 3 active small peptides in LHG at trace levels using hydrophilic interaction ultra-performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry (HILIC-UHPLC-QTRAP(®)/MS(2)). The analytical method was validated by matrix effects, linearity, LODs, LOQs, precision, repeatability, stability, and recovery. Thirdly, the proposed optimal UAE conditions and analytical methods were applied to measurement of LHG samples. It was shown that LHG was rich in essential amino acids, which were beneficial nutrient substances for human health. Finally, based on the contents of the 27 analytes, the chemometrics methods of unsupervised principal component analysis (PCA) and supervised counter propagation artificial neural network (CP-ANN) were applied to differentiate and classify the 40 batches of LHG samples from different cultivated forms, regions, and varieties. As a result, these samples were mainly clustered into three clusters, which illustrated the cultivating disparity among the samples. In summary, the presented strategy had potential for the investigation of edible plants and agricultural products containing FAAs and small peptides.

  18. Implementation of chemometrics in quality evaluation of food and beverages.

    Science.gov (United States)

    Efenberger-Szmechtyk, Magdalena; Nowak, Agnieszka; Kregiel, Dorota

    2017-01-27

    Conventional methods for food quality evaluation based on chemical or microbiological analysis followed by traditional univariate statistics such as ANOVA are considered insufficient for some purposes. More sophisticated instrumental methods including spectroscopy and chromatography, in combination with multivariate analysis-chemometrics, can be used to determine food authenticity, identify adulterations or mislabeling and determine food safety. The purpose of this review is to present the current state of knowledge on the use of chemometric tools for evaluating quality of food products of animal and plant origin and beverages. The article describes applications of several multivariate techniques in food and beverages research, showing their role in adulteration detection, authentication, quality control, differentiation of samples and comparing their classification and prediction ability.

  19. Best conditions for biodegradation of diesel oil by chemometric tools

    OpenAIRE

    Kaczorek, Ewa; Bielicka-Daszkiewicz, Katarzyna; Héberger, Károly; Kemény, Sándor; Olszanowski, Andrzej; Voelkel, Adam

    2014-01-01

    Diesel oil biodegradation by different bacteria-yeast-rhamnolipids consortia was tested. Chromatographic analysis of post-biodegradation residue was completed with chemometric tools (ANOVA, and a novel ranking procedure based on the sum of ranking differences). These tools were used in the selection of the most effective systems. The best results of aliphatic fractions of diesel oil biodegradation were observed for a yeast consortia with Aeromonas hydrophila KR4. For these systems the positiv...

  20. [Identification of two varieties of Citri Fructus by fingerprint and chemometrics].

    Science.gov (United States)

    Su, Jing-hua; Zhang, Chao; Sun, Lei; Gu, Bing-ren; Ma, Shuang-cheng

    2015-06-01

    Citri Fructus identification by fingerprint and chemometrics was investigated in this paper. Twenty-three Citri Fructus samples were collected which referred to two varieties as Cirtus wilsonii and C. medica recorded in Chinese Pharmacopoeia. HPLC chromatograms were obtained. The components were partly identified by reference substances, and then common pattern was established for chemometrics analysis. Similarity analysis, principal component analysis (PCA) , partial least squares-discriminant analysis (PLS-DA) and hierarchical cluster analysis heatmap were applied. The results indicated that C. wilsonii and C. medica could be ideally classified with common pattern contained twenty-five characteristic peaks. Besides, preliminary pattern recognition had verified the chemometrics analytical results. Absolute peak area (APA) was used for relevant quantitative analysis, results showed the differences between two varieties and it was valuable for further quality control as selection of characteristic components.

  1. Authentication of Tunisian virgin olive oils by chemometric analysis of fatty acid compositions and NIR spectra. Comparison with Maghrebian and French virgin olive oils.

    Science.gov (United States)

    Laroussi-Mezghani, S; Vanloot, P; Molinet, J; Dupuy, N; Hammami, M; Grati-Kamoun, N; Artaud, J

    2015-04-15

    Six Tunisian virgin olive oil (VOO) varieties, Chemlali Sfax, Chetoui, Chemchali, Oueslati, Zarrazi and Zalmati, were characterised by two analytical methods. The gas chromatography allowed the determination of 14 fatty acids and squalene amounts. With fatty acids of each variety, a characteristic "morphotypes" for each oil variety was established. Chemlali Sfax and Zalmati showed strong similarities. Gas chromatography of fatty acid methyl esters (FAME) and near infrared (NIR) spectra of oils, associated to chemometric treatment, allowed the study of the inter-varietal variability and the verification of the variety origins of some Tunisian commercial VOOs. The specificity of Tunisian VOOs was evaluated by comparing the samples to Algerian, Moroccan and French Protected Designation of Origin VOOs. Classification in varietal origins by SIMCA used the FAME compositions and NIR spectra of the most represented varieties (Chemlali Sfax, Chetoui and Oueslati) showed a high potential to authenticate the varietal origin of Tunisian VOOs. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Discrimination of sugarcane according to cultivar by 1H NMR and chemometric analyses

    Energy Technology Data Exchange (ETDEWEB)

    Alves Filho, Elenilson G.; Silva, Lorena M.A.; Choze, Rafael; Liao, Luciano M. [Laboratorio de Ressonancia Magnetica Nuclear, Instituto de Quimica, Universidade Federal de Goias (UFG), Goiania, GO (Brazil); Honda, Neli K.; Alcantara, Glaucia B. [Departamento de Quimica, Universidade Federal de Mato Grosso do Sul (UFMS), Campo Grande, MS (Brazil)

    2012-07-01

    Several technologies for the development of new sugarcane cultivars have mainly focused on the increase in productivity and greater disease resistance. Sugarcane cultivars are usually identified by the organography of the leaves and stems, the analysis of peroxidase and esterase isoenzyme activities and the total soluble protein as well as soluble solid content. Nuclear magnetic resonance (NMR) associated with chemometric analysis has proven to be a valuable tool for cultivar assessment. Thus, this article describes the potential of chemometric analysis applied to 1H high resolution magic angle spinning (HRMAS) and NMR in solution for the investigation of sugarcane cultivars. For this purpose, leaves from eight different cultivars of sugarcane were investigated by {sup 1}H NMR spectroscopy in combination with chemometric analysis. The approach shows to be a useful tool for the distinction and classification of different sugarcane cultivars as well as to access the differences on its chemical composition. (author)

  3. "Click and Screen" Technology for the Detection of Explosives on Human Hands by a Portable MicroNIR-Chemometrics Platform.

    Science.gov (United States)

    Risoluti, Roberta; Gregori, Adolfo; Schiavone, Sergio; Materazzi, Stefano

    2018-03-13

    Portable near-infrared spectroscopy (MicroNIR) coupled with chemometrics was investigated for the first time as a new tool for the on-site analysis of explosives on human hands. A novel, entirely on-site approach based on the use of a particular miniaturized NIR spectrometer was developed and validated in cooperation with the Scientific Investigation Department (Carabinieri RIS) of Rome. Spectra from 25 volunteers were acquired in the NIR region in reflectance mode, and a prediction model was optimized on the basis of chemometric tools. The results demonstrated the capability of the MicroNIR-Chemometrics approach to correctly identify explosives from hands and not be affected by the complexity and variability of the matrix. This study has shown that the MicroNIR-Chemometrics approach can be considered a useful, fast, nondestructive tool identifying the manipulation of explosives in real forensic cases.

  4. Rapid detection of milk adulteration using intact protein flow injection mass spectrometric fingerprints combined with chemometrics.

    Science.gov (United States)

    Du, Lijuan; Lu, Weiying; Cai, Zhenzhen Julia; Bao, Lei; Hartmann, Christoph; Gao, Boyan; Yu, Liangli Lucy

    2018-02-01

    Flow injection mass spectrometry (FIMS) combined with chemometrics was evaluated for rapidly detecting economically motivated adulteration (EMA) of milk. Twenty-two pure milk and thirty-five counterparts adulterated with soybean, pea, and whey protein isolates at 0.5, 1, 3, 5, and 10% (w/w) levels were analyzed. The principal component analysis (PCA), partial least-squares-discriminant analysis (PLS-DA), and support vector machine (SVM) classification models indicated that the adulterated milks could successfully be classified from the pure milks. FIMS combined with chemometrics might be an effective method to detect possible EMA in milk. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Synergistic effect of the simultaneous chemometric analysis of {sup 1}H NMR spectroscopic and stable isotope (SNIF-NMR, {sup 18}O, {sup 13}C) data: Application to wine analysis

    Energy Technology Data Exchange (ETDEWEB)

    Monakhova, Yulia B., E-mail: yul-monakhova@mail.ru [Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Strasse 3, Karlsruhe 76187 (Germany); Bruker Biospin GmbH, Silberstreifen, Rheinstetten 76287 (Germany); Department of Chemistry, Saratov State University, Astrakhanskaya Street 83, Saratov 410012 (Russian Federation); Godelmann, Rolf [Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Strasse 3, Karlsruhe 76187 (Germany); Hermann, Armin [Landesuntersuchungsamt -Institut für Lebensmittelchemie und Arzneimittelprüfung, Emy-Roeder-Straße 1, Mainz 55129 (Germany); Kuballa, Thomas [Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Strasse 3, Karlsruhe 76187 (Germany); Cannet, Claire; Schäfer, Hartmut; Spraul, Manfred [Bruker Biospin GmbH, Silberstreifen, Rheinstetten 76287 (Germany); Rutledge, Douglas N. [AgroParisTech, UMR 1145, Ingénierie Procédés Aliments, 16 rue Claude Bernard, Paris F-75005 (France)

    2014-06-23

    Highlights: • {sup 1}H NMR profilings of 718 wines were fused with stable isotope analysis data (SNIF-NMR, {sup 18}O, {sup 13}C). • The best improvement was obtained for prediction of the geographical origin of wine. • Certain enhancement was also obtained for the year of vintage (from 88 to 97% for {sup 1}H NMR to 99% for the fused data). • Independent component analysis was used as an alternative chemometric tool for classification. - Abstract: It is known that {sup 1}H NMR spectroscopy represents a good tool for predicting the grape variety, the geographical origin, and the year of vintage of wine. In the present study we have shown that classification models can be improved when {sup 1}H NMR profiles are fused with stable isotope (SNIF-NMR, {sup 18}O, {sup 13}C) data. Variable selection based on clustering of latent variables was performed on {sup 1}H NMR data. Afterwards, the combined data of 718 wine samples from Germany were analyzed using linear discriminant analysis (LDA), partial least squares-discriminant analysis (PLS-DA), factorial discriminant analysis (FDA) and independent components analysis (ICA). Moreover, several specialized multiblock methods (common components and specific weights analysis (ComDim), consensus PCA and consensus PLS-DA) were applied to the data. The best improvement in comparison with {sup 1}H NMR data was obtained for prediction of the geographical origin (up to 100% for the fused data, whereas stable isotope data resulted only in 60–70% correct prediction and {sup 1}H NMR data alone in 82–89% respectively). Certain enhancement was obtained also for the year of vintage (from 88 to 97% for {sup 1}H NMR to 99% for the fused data), whereas in case of grape varieties improved models were not obtained. The combination of {sup 1}H NMR data with stable isotope data improves efficiency of classification models for geographical origin and vintage of wine and can be potentially used for other food products as well.

  6. Chemometrics for comprehensive analysis of nucleobases, nucleosides, and nucleotides in Siraitiae Fructus by hydrophilic interaction ultra high performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry.

    Science.gov (United States)

    Zhou, Guisheng; Wang, Mengyue; Xu, Renjie; Li, Xiao-Bo

    2015-10-01

    A rapid and sensitive hydrophilic interaction ultra high performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry method was validated for the simultaneous determination of 20 nucleobases, nucleosides, and nucleotides (within 3.5 min), and then was employed to test the functional food of Luo-Han-Guo samples. The analysis showed that the Luo-Han-Guo was rich in guanosine and uridine, but contained trace levels of the other target compounds. Chemometrics methods were employed to identify 40 batches of Luo-Han-Guo samples from different cultivated forms, regions and varieties. Unsupervised hierarchical cluster analysis and principal component analysis were used to classify Luo-Han-Guo samples based on the level of the 20 target compounds, and the supervised learning method of counter propagation artificial neural network was utilized to further separate clusters and validate the established model. As a result, the samples could be clustered into three primary groups, in which correlation with cultivated varieties was observed. The present strategy could be applied to the investigation of other edible plants containing nucleobases, nucleosides, or nucleotides. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Fingerprint analysis and quality consistency evaluation of flavonoid compounds for fermented Guava leaf by combining high-performance liquid chromatography time-of-flight electrospray ionization mass spectrometry and chemometric methods.

    Science.gov (United States)

    Wang, Lu; Tian, Xiaofei; Wei, Wenhao; Chen, Gong; Wu, Zhenqiang

    2016-10-01

    Guava leaves are used in traditional herbal teas as antidiabetic therapies. Flavonoids are the main active of Guava leaves and have many physiological functions. However, the flavonoid compositions and activities of Guava leaves could change due to microbial fermentation. A high-performance liquid chromatography time-of-flight electrospray ionization mass spectrometry method was applied to identify the varieties of the flavonoids in Guava leaves before and after fermentation. High-performance liquid chromatography, hierarchical cluster analysis and principal component analysis were used to quantitatively determine the changes in flavonoid compositions and evaluate the consistency and quality of Guava leaves. Monascus anka Saccharomyces cerevisiae fermented Guava leaves contained 2.32- and 4.06-fold more total flavonoids and quercetin, respectively, than natural Guava leaves. The flavonoid compounds of the natural Guava leaves had similarities ranging from 0.837 to 0.927. The flavonoid compounds from the Monascus anka S. cerevisiae fermented Guava leaves had similarities higher than 0.993. This indicated that the quality consistency of the fermented Guava leaves was better than that of the natural Guava leaves. High-performance liquid chromatography fingerprinting and chemometric analysis are promising methods for evaluating the degree of fermentation of Guava leaves based on quality consistency, which could be used in assessing flavonoid compounds for the production of fermented Guava leaves. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. Evaluation and quantitative analysis of different growth periods of herb-arbor intercropping systems using HPLC and UV-vis methods coupled with chemometrics.

    Science.gov (United States)

    Chu, Bo-Wen; Zhang, Ji; Li, Zhi-Min; Zhao, Yan-Li; Zuo, Zhi-Tian; Wang, Yuan-Zhong; Li, Wan-Yi

    2016-10-01

    As a result of the pressure from population explosion, agricultural land resources require further protecting and rationally utilizing. Intercropping technique has been widely applied for agricultural production to save cultivated area, improve crop quality, and promote agriculture economy. In this study, we employed high-performance liquid chromatography (HPLC) and ultraviolet-visible spectroscopy (UV-vis) combined with chemometrics for determination and qualitative evaluation of several kinds of intercropping system with Gentiana rigescens Franch. ex Hemsl. (GR), which is used as an hepatic protector in local communities in China. Results revealed that GR in a Camellia sinensis intercropping system contained most gentiopicroside, sweroside, and total active constituents (six chemical indicators), whose content reached 91.09 ± 3.54, 1.03 ± 0.06, and 104.05 ± 6.48 mg g(-1), respectively. The two applied quantitative and qualitative methods reciprocally verified that GR with 2 years of growth period performed better in terms of quality than 1 year, collectively.

  9. Development, characterization and chemometric analysis of gluten-free granolas containing whole flour of pseudo-cereals new cultivars - doi: 10.4025/actascitechnol.v36i1.19195

    Directory of Open Access Journals (Sweden)

    Aloisio Henrique Pereira Souza

    2014-01-01

    Full Text Available The goal of this study was the development, quimiometric analysis, physical-chemical, microbiological, nutritional, and sensory evaluation of gluten-free granolas containing quinoa, amaranth and linseed. Gluten fractions were not detected in the granola formulations prepared. The crude protein and total lipids contents ranged from 86.72 to 97.49 and 97.84 to 134.03 g kg-1 of food, respectively. The polyunsaturated/saturated and n-6: n-3 fatty acid ratios were 3:1. Calcium was the major mineral and the contents of trace minerals copper, iron, magnesium, manganese and zinc were over 10% of the dietary reference intake values. The granola color tended to light brown. The absence of Bacillus cereus, thermotolerant coliforms, coagulase positive staphylococcus, and Salmonella sp. ensured the product safety. All the granola formulations had good sensory acceptance and high purchase intent. The gluten-free granola formulations had good physical-chemical, sensory and nutritional quality. The use of chemometric analysis enabled to distinguish the samples with respect to their fatty acid composition, minerals content and sensory aspects.

  10. A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies.

    Science.gov (United States)

    Roggo, Yves; Chalus, Pascal; Maurer, Lene; Lema-Martinez, Carmen; Edmond, Aurélie; Jent, Nadine

    2007-07-27

    Near-infrared spectroscopy (NIRS) is a fast and non-destructive analytical method. Associated with chemometrics, it becomes a powerful tool for the pharmaceutical industry. Indeed, NIRS is suitable for analysis of solid, liquid and biotechnological pharmaceutical forms. Moreover, NIRS can be implemented during pharmaceutical development, in production for process monitoring or in quality control laboratories. This review focuses on chemometric techniques and pharmaceutical NIRS applications. The following topics are covered: qualitative analyses, quantitative methods and on-line applications. Theoretical and practical aspects are described with pharmaceutical examples of NIRS applications.

  11. Grape juice quality control by means of ¹H nmr spectroscopy and chemometric analyses

    Directory of Open Access Journals (Sweden)

    Caroline Werner Pereira da Silva Grandizoli

    2014-01-01

    Full Text Available This work shows the application of ¹H NMR spectroscopy and chemometrics for quality control of grape juice. A wide range of quality assurance parameters were assessed by single ¹H NMR experiments acquired directly from juice. The investigation revealed that conditions and time of storage should be revised and indicated on all labels. The sterilization process of homemade grape juices was efficient, making it possible to store them for long periods without additives. Furthermore, chemometric analysis classified the best commercial grape juices to be similar to homemade grape juices, indicating that this approach can be used to determine the authenticity after adulteration.

  12. Grape juice quality control by means of {sup 1}H NMR spectroscopy and chemometric analyses

    Energy Technology Data Exchange (ETDEWEB)

    Grandizoli, Caroline Werner Pereira da Silva; Campos, Francinete Ramos; Simonelli, Fabio; Barison, Andersson, E-mail: andernmr@ufpr.br [Universidade Federal do Paraná (UFPR), Curitiba (Brazil). Departamento de Química

    2014-07-01

    This work shows the application of {sup 1}H NMR spectroscopy and chemometrics for quality control of grape juice. A wide range of quality assurance parameters were assessed by single {sup 1}H NMR experiments acquired directly from juice. The investigation revealed that conditions and time of storage should be revised and indicated on all labels. The sterilization process of homemade grape juices was efficient, making it possible to store them for long periods without additives. Furthermore, chemometric analysis classified the best commercial grape juices to be similar to homemade grape juices, indicating that this approach can be used to determine the authenticity after adulteration. (author)

  13. Authenticity study of Phyllanthus species by NMR and FT-IR Techniques coupled with chemometric methods

    Directory of Open Access Journals (Sweden)

    Maiara S. Santos

    2012-01-01

    Full Text Available The importance of medicinal plants and their use in industrial applications is increasing worldwide, especially in Brazil. Phyllanthus species, popularly known as "quebra-pedras" in Brazil, are used in folk medicine for treating urinary infections and renal calculus. This paper reports an authenticity study, based on herbal drugs from Phyllanthus species, involving commercial and authentic samples using spectroscopic techniques: FT-IR, ¹H HR-MAS NMR and ¹H NMR in solution, combined with chemometric analysis. The spectroscopic techniques evaluated, coupled with chemometric methods, have great potential in the investigation of complex matrices. Furthermore, several metabolites were identified by the NMR techniques.

  14. Authenticity study of Phyllanthus species by NMR and FT-IR techniques coupled with chemometric methods

    Energy Technology Data Exchange (ETDEWEB)

    Santos, Maiara S.; Pereira-Filho, Edenir R.; Ferreira, Antonio G. [Universidade Federal de Sao Carlos (UFSCAR), SP (Brazil). Dept. de Quimica; Boffo, Elisangela F. [Universidade Federal da Bahia (UFBA), Salvador, BA (Brazil). Inst. de Quimica; Figueira, Glyn M., E-mail: maiarassantos@yahoo.com.br [Universidade Estadual de Campinas (UNICAMP), Campinas, SP (Brazil). Centro Pluridisciplinar de Pesquisas Quimicas, Biologicas e Agricolas

    2012-07-01

    The importance of medicinal plants and their use in industrial applications is increasing worldwide, especially in Brazil. Phyllanthus species, popularly known as 'quebra-pedras' in Brazil, are used in folk medicine for treating urinary infections and renal calculus. This paper reports an authenticity study, based on herbal drugs from Phyllanthus species, involving commercial and authentic samples using spectroscopic techniques: FT-IR, {sup 1}H HR-MAS NMR and {sup 1}H NMR in solution, combined with chemometric analysis. The spectroscopic techniques evaluated, coupled with chemometric methods, have great potential in the investigation of complex matrices. Furthermore, several metabolites were identified by the NMR techniques. (author)

  15. [Application of chemometrics in composition-activity relationship research of traditional Chinese medicine].

    Science.gov (United States)

    Han, Sheng-Nan

    2014-07-01

    Chemometrics is a new branch of chemistry which is widely applied to various fields of analytical chemistry. Chemometrics can use theories and methods of mathematics, statistics, computer science and other related disciplines to optimize the chemical measurement process and maximize access to acquire chemical information and other information on material systems by analyzing chemical measurement data. In recent years, traditional Chinese medicine has attracted widespread attention. In the research of traditional Chinese medicine, it has been a key problem that how to interpret the relationship between various chemical components and its efficacy, which seriously restricts the modernization of Chinese medicine. As chemometrics brings the multivariate analysis methods into the chemical research, it has been applied as an effective research tool in the composition-activity relationship research of Chinese medicine. This article reviews the applications of chemometrics methods in the composition-activity relationship research in recent years. The applications of multivariate statistical analysis methods (such as regression analysis, correlation analysis, principal component analysis, etc. ) and artificial neural network (such as back propagation artificial neural network, radical basis function neural network, support vector machine, etc. ) are summarized, including the brief fundamental principles, the research contents and the advantages and disadvantages. Finally, the existing main problems and prospects of its future researches are proposed.

  16. An Advanced Undergraduate Chemistry Laboratory Experiment Exploring NIR Spectroscopy and Chemometrics

    Science.gov (United States)

    Wanke, Randall; Stauffer, Jennifer

    2007-01-01

    An advanced undergraduate chemistry laboratory experiment to study the advantages and hazards of the coupling of NIR spectroscopy and chemometrics is described. The combination is commonly used for analysis and process control of various ingredients used in agriculture, petroleum and food products.

  17. An explorative chemometric approach applied to hyperspectral images for the study of illuminated manuscripts

    Science.gov (United States)

    Catelli, Emilio; Randeberg, Lise Lyngsnes; Alsberg, Bjørn Kåre; Gebremariam, Kidane Fanta; Bracci, Silvano

    2017-04-01

    Hyperspectral imaging (HSI) is a fast non-invasive imaging technology recently applied in the field of art conservation. With the help of chemometrics, important information about the spectral properties and spatial distribution of pigments can be extracted from HSI data. With the intent of expanding the applications of chemometrics to the interpretation of hyperspectral images of historical documents, and, at the same time, to study the colorants and their spatial distribution on ancient illuminated manuscripts, an explorative chemometric approach is here presented. The method makes use of chemometric tools for spectral de-noising (minimum noise fraction (MNF)) and image analysis (multivariate image analysis (MIA) and iterative key set factor analysis (IKSFA)/spectral angle mapper (SAM)) which have given an efficient separation, classification and mapping of colorants from visible-near-infrared (VNIR) hyperspectral images of an ancient illuminated fragment. The identification of colorants was achieved by extracting and interpreting the VNIR spectra as well as by using a portable X-ray fluorescence (XRF) spectrometer.

  18. Big (Bio)Chemical Data Mining Using Chemometric Methods: A Need for Chemists.

    Science.gov (United States)

    Tauler, Roma; Parastar, Hadi

    2018-03-23

    This review aims to demonstrate abilities to analyze Big (Bio)Chemical Data (BBCD) with multivariate chemometric methods and to show some of the more important challenges of modern analytical researches. In this review, the capabilities and versatility of chemometric methods will be discussed in light of the BBCD challenges that are being encountered in chromatographic, spectroscopic and hyperspectral imaging measurements, with an emphasis on their application to omics sciences. In addition, insights and perspectives on how to address the analysis of BBCD are provided along with a discussion of the procedures necessary to obtain more reliable qualitative and quantitative results. In this review, the importance of Big Data and of their relevance to (bio)chemistry are first discussed. Then, analytical tools which can produce BBCD are presented as well as some basics needed to understand prospects and limitations of chemometric techniques when they are applied to BBCD are given. Finally, the significance of the combination of chemometric approaches with BBCD analysis in different chemical disciplines is highlighted with some examples. In this paper, we have tried to cover some of the applications of big data analysis in the (bio)chemistry field. However, this coverage is not extensive covering everything done in the field. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Thin-layer chromatographic identification of Chinese propolis using chemometric fingerprinting.

    Science.gov (United States)

    Tang, Tie-xin; Guo, Wei-yan; Xu, Ye; Zhang, Si-ming; Xu, Xin-jun; Wang, Dong-mei; Zhao, Zhi-min; Zhu, Long-ping; Yang, De-po

    2014-01-01

    Poplar tree gum has a similar chemical composition and appearance to Chinese propolis (bee glue) and has been widely used as a counterfeit propolis because Chinese propolis is typically the poplar-type propolis, the chemical composition of which is determined mainly by the resin of poplar trees. The discrimination of Chinese propolis from poplar tree gum is a challenging task. To develop a rapid thin-layer chromatographic (TLC) identification method using chemometric fingerprinting to discriminate Chinese propolis from poplar tree gum. A new TLC method using a combination of ammonia and hydrogen peroxide vapours as the visualisation reagent was developed to characterise the chemical profile of Chinese propolis. Three separate people performed TLC on eight Chinese propolis samples and three poplar tree gum samples of varying origins. Five chemometric methods, including similarity analysis, hierarchical clustering, k-means clustering, neural network and support vector machine, were compared for use in classifying the samples based on their densitograms obtained from the TLC chromatograms via image analysis. Hierarchical clustering, neural network and support vector machine analyses achieved a correct classification rate of 100% in classifying the samples. A strategy for TLC identification of Chinese propolis using chemometric fingerprinting was proposed and it provided accurate sample classification. The study has shown that the TLC identification method using chemometric fingerprinting is a rapid, low-cost method for the discrimination of Chinese propolis from poplar tree gum and may be used for the quality control of Chinese propolis. Copyright © 2014 John Wiley & Sons, Ltd.

  20. Simultaneous spectrophotometric determination of paracetamol, ibuprofen and caffeine in pharmaceuticals by chemometric methods

    Science.gov (United States)

    Khoshayand, M. R.; Abdollahi, H.; Shariatpanahi, M.; Saadatfard, A.; Mohammadi, A.

    2008-08-01

    In this study, the simultaneous determination of paracetamol, ibuprofen and caffeine in pharmaceuticals by chemometric approaches using UV spectrophotometry has been reported as a simple alternative to using separate models for each component. Spectra of paracetamol, ibuprofen and caffeine were recorded at several concentrations within their linear ranges and were used to compute the calibration mixture between wavelengths 200 and 400 nm at an interval of 1 nm in methanol:0.1 HCl (3:1). Partial least squares regression (PLS), genetic algorithm coupled with PLS (GA-PLS), and principal component-artificial neural network (PC-ANN) were used for chemometric analysis of data and the parameters of the chemometric procedures were optimized. The analytical performances of these chemometric methods were characterized by relative prediction errors and recoveries (%) and were compared with each other. The GA-PLS shows superiority over other applied multivariate methods due to the wavelength selection in PLS calibration using a genetic algorithm without loss of prediction capacity. Although the components show an important degree of spectral overlap, they have been determined simultaneously and rapidly requiring no separation step. These three methods were successfully applied to pharmaceutical formulation, capsule, with no interference from excipients as indicated by the recovery study results. The proposed methods are simple and rapid and can be easily used in the quality control of drugs as alternative analysis tools.

  1. Using of laser spectroscopy and chemometrics methods for identification of patients with lung cancer, patients with COPD and healthy people from absorption spectra of exhaled air

    Science.gov (United States)

    Bukreeva, Ekaterina B.; Bulanova, Anna A.; Kistenev, Yury V.; Kuzmin, Dmitry A.; Nikiforova, Olga Yu.; Ponomarev, Yurii N.; Tuzikov, Sergei A.; Yumov, Evgeny L.

    2014-11-01

    The results of application of the joint use of laser photoacoustic spectroscopy and chemometrics methods in gas analysis of exhaled air of patients with chronic respiratory diseases (chronic obstructive pulmonary disease and lung cancer) are presented. The absorption spectra of exhaled breath of representatives of the target groups and healthy volunteers were measured; the selection by chemometrics methods of the most informative absorption coefficients in scan spectra in terms of the separation investigated nosology was implemented.

  2. A brief understanding of process optimisation in microwave-assisted extraction of botanical materials: options and opportunities with chemometric tools.

    Science.gov (United States)

    Das, Anup Kumar; Mandal, Vivekananda; Mandal, Subhash C

    2014-01-01

    Extraction forms the very basic step in research on natural products for drug discovery. A poorly optimised and planned extraction methodology can jeopardise the entire mission. To provide a vivid picture of different chemometric tools and planning for process optimisation and method development in extraction of botanical material, with emphasis on microwave-assisted extraction (MAE) of botanical material. A review of studies involving the application of chemometric tools in combination with MAE of botanical materials was undertaken in order to discover what the significant extraction factors were. Optimising a response by fine-tuning those factors, experimental design or statistical design of experiment (DoE), which is a core area of study in chemometrics, was then used for statistical analysis and interpretations. In this review a brief explanation of the different aspects and methodologies related to MAE of botanical materials that were subjected to experimental design, along with some general chemometric tools and the steps involved in the practice of MAE, are presented. A detailed study on various factors and responses involved in the optimisation is also presented. This article will assist in obtaining a better insight into the chemometric strategies of process optimisation and method development, which will in turn improve the decision-making process in selecting influential extraction parameters. Copyright © 2013 John Wiley & Sons, Ltd.

  3. Symbiosis of chemometrics and metabolomics: past, present, and future

    NARCIS (Netherlands)

    van der Greef, J.; Smilde, A. K.

    2005-01-01

    Metabolomics is a growing area in the field of systems biology. Metabolomics has already a long history and also the connection of metabolomics with chemometrics goes back some time. This review discusses the symbiosis of metabolomics and chemometrics with emphasis on the medical domain, puts the

  4. (1)H NMR spectroscopy and chemometrics evaluation of non-thermal processing of orange juice.

    Science.gov (United States)

    Alves Filho, Elenilson G; Almeida, Francisca D L; Cavalcante, Rosane S; de Brito, Edy S; Cullen, Patrick J; Frias, Jesus M; Bourke, Paula; Fernandes, Fabiano A N; Rodrigues, Sueli

    2016-08-01

    This study evaluated the effect of atmospheric cold plasma and ozone treatments on the key compounds (sugars, amino acids and short chain organic acids) in orange juice by NMR and chemometric analysis. The juice was directly and indirectly exposed to atmospheric cold plasma field at 70kV for different treatment time (15, 30, 45 and 60sec). For ozone processing different loads were evaluated. The Principal Component Analysis shown that the groups of compounds are affected differently depending on the processing. The ozone was the processing that more affected the aromatic compounds and atmospheric cold plasma processing affected more the aliphatic compounds. However, these variations did not result in significant changes in orange juice composition as a whole. Thus, NMR data and chemometrics were suitable to follow quality changes in orange juice processing by atmospheric cold plasma and ozone. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Association and discrimination of diesel fuels using chemometric procedures

    Energy Technology Data Exchange (ETDEWEB)

    Marshall, Lucas J. [Michigan State University, Forensic Science Program, School of Criminal Justice, East Lansing, MI (United States); McIlroy, John W.; Waddell Smith, Ruth [Michigan State University, Forensic Science Program, School of Criminal Justice, East Lansing, MI (United States); Michigan State University, Department of Chemistry, East Lansing, MI (United States); McGuffin, Victoria L. [Michigan State University, Department of Chemistry, East Lansing, MI (United States)

    2009-08-15

    Five neat diesel samples were analyzed by gas chromatography-mass spectrometry and total ion chromatograms as well as extracted ion profiles of the alkane and aromatic compound classes were generated. A retention time alignment algorithm was employed to align chromatograms prior to peak area normalization. Pearson product moment correlation coefficients and principal components analysis were then employed to investigate association and discrimination among the diesel samples. The same procedures were also used to investigate the association of a diesel residue to its neat counterpart. Current limitations in the retention time alignment algorithm and the subsequent effect on the association and discrimination of the diesel samples are discussed. An understanding of these issues is crucial to ensure the accuracy of data interpretation based on such chemometric procedures. (orig.)

  6. Best conditions for biodegradation of diesel oil by chemometric tools

    Directory of Open Access Journals (Sweden)

    Ewa Kaczorek

    2014-01-01

    Full Text Available Diesel oil biodegradation by different bacteria-yeast-rhamnolipids consortia was tested. Chromatographic analysis of post-biodegradation residue was completed with chemometric tools (ANOVA, and a novel ranking procedure based on the sum of ranking differences. These tools were used in the selection of the most effective systems. The best results of aliphatic fractions of diesel oil biodegradation were observed for a yeast consortia with Aeromonas hydrophila KR4. For these systems the positive effect of rhamnolipids on hydrocarbon biodegradation was observed. However, rhamnolipids addition did not always have a positive influence on the biodegradation process (e.g. in case of yeast consortia with Stenotrophomonas maltophila KR7. Moreover, particular differences in the degradation pattern were observed for lower and higher alkanes than in the case with C22. Normally, the best conditions for "lower" alkanes are Aeromonas hydrophila KR4 + emulsifier independently from yeasts and e.g. Pseudomonas stutzeri KR7 for C24 alkane.

  7. Best conditions for biodegradation of diesel oil by chemometric tools

    Science.gov (United States)

    Kaczorek, Ewa; Bielicka-Daszkiewicz, Katarzyna; Héberger, Károly; Kemény, Sándor; Olszanowski, Andrzej; Voelkel, Adam

    2014-01-01

    Diesel oil biodegradation by different bacteria-yeast-rhamnolipids consortia was tested. Chromatographic analysis of post-biodegradation residue was completed with chemometric tools (ANOVA, and a novel ranking procedure based on the sum of ranking differences). These tools were used in the selection of the most effective systems. The best results of aliphatic fractions of diesel oil biodegradation were observed for a yeast consortia with Aeromonas hydrophila KR4. For these systems the positive effect of rhamnolipids on hydrocarbon biodegradation was observed. However, rhamnolipids addition did not always have a positive influence on the biodegradation process (e.g. in case of yeast consortia with Stenotrophomonas maltophila KR7). Moreover, particular differences in the degradation pattern were observed for lower and higher alkanes than in the case with C22. Normally, the best conditions for “lower” alkanes are Aeromonas hydrophila KR4 + emulsifier independently from yeasts and e.g. Pseudomonas stutzeri KR7 for C24 alkane. PMID:24948922

  8. Chemometrics approach to substrate development, case: semisyntetic cheese

    DEFF Research Database (Denmark)

    Nielsen, Per Væggemose; Hansen, Birgitte Vedel

    1998-01-01

    from food production facilities.The Chemometrics approach to substrate development is illustrated by the development of a semisyntetic cheese substrate. Growth, colour formation and mycotoxin production of 6 cheese related fungi were studied on 9 types of natural cheeses and 24 synthetic cheese...... substrates and compared using principal component analysis (PCA). The synthetic cheese substrates contained various amounts of Ca, K, Mg, Na, P, Fe, Cu, Zn, lactate, lactose and casein. In this manner a robust, well-defined and easy prepared laboratory cheese substrate was developed for Penicillium commune......, the most frequently occurring contaminant on semi-hard cheese. Growth experiments on the substrate were repeatable and reproducible. The substrate was also suitable for the starter P. camemberti. Mineral elements in cheese were shown to have strong effect on growth, mycotoxin production and colour...

  9. A quantitative validated method using liquid chromatography and chemometric analysis for evaluation of raw material oF Maytenus ilicifolia (Schrad. Planch., Celastraceae

    Directory of Open Access Journals (Sweden)

    Flávio Luís Beltrame

    2012-01-01

    Full Text Available The hydroalcoholic extracts prepared from standard leaves of Maytenus ilicifolia and commercial samples of espinheira-santa were evaluated qualitatively (fingerprinting and quantitatively. In this paper, fingerprinting chromatogram coupled with Principal Component Analysis (PCA is described for the metabolomic analysis of standard and commercial espinheira-santa samples. The epicatechin standard was used as an external standard for the development and validation of a quantitative method for the analysis in herbal medicines using a photo diode array detector. This method has been applied for quantification of epicatechin in commercialized herbal medicines sold as espinheira-santa in Brazil and in the standard sample of M. ilicifolia.

  10. Characterization and authentication of Spanish PDO wine vinegars using multidimensional fluorescence and chemometrics

    DEFF Research Database (Denmark)

    Ríos-Reina, Rocío; Elcoroaristizabal, Saioa; Ocaña-Gonzalez, Juan A.

    2017-01-01

    This work assesses the potential of multidimensional fluorescence spectroscopy combined with chemometrics for characterization and authentication of Spanish Protected Designation of Origin (PDO) wine vinegars. Seventy-nine vinegars of different categories (aged and sweet) belonging to the Spanish...... obtained better results (>92% of classification). In each category, SVM also allows the differentiation between PDOs. The proposed methodology could be used as an analysis method for the authentication of Spanish PDO wine vinegars....

  11. Analysis of the Correlation between Commodity Grade and Quality of Angelica sinensis by Determination of Active Compounds Using Ultraperformance Liquid Chromatography Coupled with Chemometrics.

    Science.gov (United States)

    Wang, Zenghui; Wang, Dongmei; Huang, Linfang

    2014-01-01

    The contents of ferulic acid, senkyunolide A, butylidenephthalide, ligustilide, and n-butylphthalide were determined by UPLC analytical method; the correlation among the grade, average weight, and content was explored by correlation analysis and analysis of variance (ANOVA); the different commercial grades with average weight and content were revealed by principal component analysis (PCA) and then rationality analysis grade classification of A. sinensis. The results showed that various commercial grades can be distinguished by PCA analysis. And there was significant negative correlation between the commodity grades and average weight, commodity, and the content of bioactive compounds, while the content of senkyunolide A had significant negative correlation with commodity grades (P < 0.01). Average weight had no correlation with chemicals compounds. Additionally, there was significant positive correlation among the bioactive compounds (content of ferulic acid and phthalides) of different grades of A. sinensis. The content of senkyunolide A, butylidenephthalide, and ligustilide had significant positive correlation with the content of ferulic acid. The content of ligustilide and butylidenephthalide had significant positive correlation with the content of senkyunolide A. The content of ligustilide had significant positive correlation with the content of butylidenephthalide. The basis of grades classification is related with the difference levels of the bioactive compounds.

  12. Differentiation of whole grain and refined wheat (T. aestivum) flour using a fuzzy mass spectrometric fingerprinting and chemometric approaches

    Science.gov (United States)

    A fuzzy mass spectrometric (MS) fingerprinting method combined with chemometric analysis was established to provide rapid discrimination between whole grain and refined wheat flour. Twenty one samples, including thirteen samples from three cultivars and eight from local grocery store, were studied....

  13. An Advanced Analytical Chemistry Experiment Using Gas Chromatography-Mass Spectrometry, MATLAB, and Chemometrics to Predict Biodiesel Blend Percent Composition

    Science.gov (United States)

    Pierce, Karisa M.; Schale, Stephen P.; Le, Trang M.; Larson, Joel C.

    2011-01-01

    We present a laboratory experiment for an advanced analytical chemistry course where we first focus on the chemometric technique partial least-squares (PLS) analysis applied to one-dimensional (1D) total-ion-current gas chromatography-mass spectrometry (GC-TIC) separations of biodiesel blends. Then, we focus on n-way PLS (n-PLS) applied to…

  14. Bivariate Correlation Analysis of the Chemometric Profiles of Chinese Wild Salvia miltiorrhiza Based on UPLC-Qqq-MS and Antioxidant Activities

    Directory of Open Access Journals (Sweden)

    Xiaodan Zhang

    2018-02-01

    Full Text Available To better understand the mechanisms underlying the pharmacological actions of Salvia miltiorrhiza, correlation between the chemical profiles and in vitro antioxidant activities in 50 batches of wild S. miltiorrhiza samples was analyzed. Our ultra-performance liquid chromatography–tandem mass spectrometry analysis detected twelve phenolic acids and five tanshinones and obtained various chemical profiles from different origins. In a principal component analysis (PCA and cluster analysis, the tanshinones cryptotanshinone, tanshinone IIA and dihydrotanshinone I exhibited higher weights in PC1, whereas the phenolic acids danshensu, salvianolic acids A and B and lithospermic acid were highly loaded in PC2. All components could be optimized as markers of different locations and might be suitable for S. miltiorrhiza quality analyses. Additionally, the DPPH and ABTS assays used to comprehensively evaluate antioxidant activities indicated large variations, with mean DPPH and ABTS scavenging potencies of 32.24 and 23.39 μg/mL, respectively, among S. miltiorrhiza extract solutions. Notably, samples that exceeded the mean IC50 values had higher phenolic acid contents. A correlation analysis indicated a strong correlation between the antioxidant activities and phenolic acid contents. Caffeic acid, danshensu, rosmarinic acid, lithospermic acid and salvianolic acid B were major contributors to antioxidant activity. In conclusion, phenolic compounds were the predominant antioxidant components in the investigated plant species. These plants may be sources of potent natural antioxidants and beneficial chemopreventive agents.

  15. Differentiation of the two major species of Echinacea (E. augustifolia and E. purpurea) using a flow injection mass spectrometric (FIMS) fingerprinting method and chemometric analysis

    Science.gov (United States)

    A rapid, simple, and reliable flow-injection mass spectrometric (FIMS) method was developed to discriminate two major Echinacea species (E. purpurea and E. angustifolia) samples. Fifty-eight Echinacea samples collected from United States were analyzed using FIMS. Principle component analysis (PCA) a...

  16. Fingerprint analysis, multi-component quantitation, and antioxidant activity for the quality evaluation of Salvia miltiorrhiza var. alba by high-performance liquid chromatography and chemometrics.

    Science.gov (United States)

    Zhang, Danlu; Duan, Xiaoju; Deng, Shuhong; Nie, Lei; Zang, Hengchang

    2015-10-01

    Salvia miltiorrhiza Bge. var. alba C.Y. Wu and H.W. Li has wide prospects in clinical practice. A useful comprehensive method was developed for the quality evaluation of S. miltiorrhiza var. alba by three quantitative parameters: high-performance liquid chromatography fingerprint, ten-component contents, and antioxidant activity. The established method was validated for linearity, precision, repeatability, stability, and recovery. Principal components analysis and hierarchical clustering analysis were both used to evaluate the quality of the samples from different origins. The results showed that there were category discrepancies in quality of S. miltiorrhiza var. alba samples according to the three quantitative parameters. Multivariate linear regression was adopted to explore the relationship between components and antioxidant activity. Three constituents, namely, danshensu, rosmarinic acid, and salvianolic acid B, significantly correlated with antioxidant activity, and were successfully elucidated by the optimized multivariate linear regression model. The combined use of high-performance liquid chromatography fingerprint analysis, simultaneous multicomponent quantitative analysis, and antioxidant activity for the quality evaluation of S. miltiorrhiza var. alba is a reliable, comprehensive, and promising approach, which might provide a valuable reference for other herbal products in general to improve their quality control. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Comparison of three officinal species of Callicarpa based on a biochemome profiling strategy with UHPLC-IT-MS and chemometrics analysis.

    Science.gov (United States)

    Chen, Meng-Lu; Chang, Wen-Qi; Zhou, Jian-Liang; Yin, Ying-Hao; Xia, Wen-Rui; Liu, Jian-Qun; Liu, Li-Fang; Xin, Gui-Zhong

    2017-10-25

    Traditional Chinese medicine (TCM) materials with closely related species are frequently fungible in clinical use. Therefore, holistic comparison of the composition in bioactive compounds is essential to evaluate whether they are equivalent in efficacy. Taking three officinal species of Callicarpa as a case, we proposed and validated a standardized strategy for the discrimination of closely related TCM materials, which focused on the extraction, profiling and multivariate statistical analysis of their biochemome. Firstly, serial liquid-liquid extractions were utilized to prepare different batches of Callicarpa biochemome, and the preparation yields were utilized for the normalization of sampling quantity prior to UHPLC-IT-MS analysis. Secondly, 34 compounds, including 19 phenylethanoid glycosides, 10 flavonoids and 5 terpenoids, were identified based on an untargeted UHPLC-IT-MS method. Thirdly, method validation of linearity, precision and stability showed that the UHPLC-IT-MS system was qualified (R 2 >0.995, RSD<15%) for subsequent biochemome profiling. After PCA and PLS-DA analysis, 30 marker compounds were screened and demonstrated to be of good predictability using genetic algorithm optimized support vector machines. Finally, a heatmap visualization was employed for clarifying the distribution of marker compounds, which could be helpful to determine whether the three Callicarpa species are, in fact, equivalent substitutes. This study provides a standardized biochemome profiling strategy for systemic comparison analysis of closely related TCM materials, which shows promising perspectives in tracking the supply chain of pharmaceutical suppliers. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Classification of java tea (Orthosiphon aristatus) quality using FTIR spectroscopy and chemometrics

    Science.gov (United States)

    Heryanto, R.; Pradono, D. I.; Marlina, E.; Darusman, L. K.

    2017-05-01

    Java tea (Orthosiphon aristatus) is a plant that widely used as a medicinal herb in Indonesia. Its quality is varying depends on various factors, such as cultivating area, climate and harvesting time. This study aimed to investigate the effectiveness of FTIR spectroscopy coupled with chemometrics for discriminating the quality of java tea from different cultivating area. FTIR spectra of ethanolic extracts were collected from five different regions of origin of java tea. Prior to chemometrics evaluation, spectra were pre-processed by using baselining, normalization and derivatization. Principal Components Analysis (PCA) was used to reduce the spectra to two PCs, which explained 73% of the total variance. Score plot of two PCs showed groupings of the samples according to their regions of origin. Furthermore, Partial Least Squares-Discriminant Analysis (PLSDA) was applied to the pre-processed data. The approach produced an external validation success rate of 100%. This study shows that FTIR analysis and chemometrics has discriminatory power to classify java tea based on its quality related to the region of origin.

  19. Classification of java tea ( Orthosiphon aristatus ) quality using FTIR spectroscopy and chemometrics

    International Nuclear Information System (INIS)

    Heryanto, R; Pradono, D I; Darusman, L K; Marlina, E

    2017-01-01

    Java tea ( Orthosiphon aristatus ) is a plant that widely used as a medicinal herb in Indonesia. Its quality is varying depends on various factors, such as cultivating area, climate and harvesting time. This study aimed to investigate the effectiveness of FTIR spectroscopy coupled with chemometrics for discriminating the quality of java tea from different cultivating area. FTIR spectra of ethanolic extracts were collected from five different regions of origin of java tea. Prior to chemometrics evaluation, spectra were pre-processed by using baselining, normalization and derivatization. Principal Components Analysis (PCA) was used to reduce the spectra to two PCs, which explained 73% of the total variance. Score plot of two PCs showed groupings of the samples according to their regions of origin. Furthermore, Partial Least Squares-Discriminant Analysis (PLSDA) was applied to the pre-processed data. The approach produced an external validation success rate of 100%. This study shows that FTIR analysis and chemometrics has discriminatory power to classify java tea based on its quality related to the region of origin. (paper)

  20. Hypericin cytotoxicity in tumor and non-tumor cell lines: A chemometric study.

    Science.gov (United States)

    Gonçalves, Joyce Laura da Silva; Bernal, Claudia; Imasato, Hidetake; Perussi, Janice Rodrigues

    2017-12-01

    Hypericin (HY) is an excellent photoactive compound that has been investigated for the photodynamic treatment of cancer as well as for microorganism inactivation. In this study, chemometric analysis was applied for the first time on photodynamic assays to investigate the cytotoxicity of HY in tumor (HEp-2) and non-tumor (Vero and HUVEC) cell lines. The experimental planning was based on eight assays using the 2 3 full factorial design combining three important variables for PDT: photosensitizer concentrations, incubation time of cells in HY solutions and employed light dose (λ=590±10nm). The statistical data analysis evidenced the relative significance of such variables and the correlations among them on the cell death. The chemometric results suggested that long incubation time and a low HY concentration and/or light dose allow killing selectively tumor cells. The chemometric analysis could be a new useful empiric method to a previous prediction of the IC 50 . In this study, the estimated values were in agreement with the experimental IC 50 values. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Effect of addition of olive leaves before fruits extraction process to some monovarietal Tunisian extra-virgin olive oils using chemometric analysis.

    Science.gov (United States)

    Sonda, Ammar; Akram, Zribi; Boutheina, Gargouri; Guido, Flamini; Mohamed, Bouaziz

    2014-01-08

    The analysis of the effect of cultivar and olive leaves addition before the extraction on the different analytical values revealed significant differences (p olive leaves. Twenty-three compounds were characterized, representing 86.1-99.2% of the total volatiles. Chétoui cultivar has the highest amount of (E)-2-hexenal, followed by Chemlali cultivar, whereas (E)-2-hexen-1-ol was the major constituent of Zalmati and crossbreeding Chemlali by Zalmati cultivars. Sensory analysis showed that Chemlali and Chétoui Zarzis possessed a high fruity, bitter, and pungent taste, whereas the Zalmati and crossbreeding Chemlali by Zalmati had a 'green' taste among its attributes. Indeed, the taste panel found an improvement of the oil quality when an amount of olive leaves (3%) added to the olives fruits.

  2. HMF and diastase activity in honeys: A fully validated approach and a chemometric analysis for identification of honey freshness and adulteration.

    Science.gov (United States)

    Pasias, Ioannis N; Kiriakou, Ioannis K; Proestos, Charalampos

    2017-08-15

    A fully validated approach for the determination of diastase activity and hydroxymethylfurfural content in honeys were presented in accordance with the official methods. Methods were performed in real honey sample analysis and due to the vast number of collected data sets reliable conclusions about the correlation between the composition and the quality criteria were exported. The limits of detection and quantification were calculated. Accuracy, precision and uncertainty were estimated for the first time in the kinetic and spectrometric techniques using the certified reference material and the determined values were in good accordance with the certified values. PCA and cluster analysis were performed in order to examine the correlation among the artificial feeding of honeybees with carbohydrate supplements and the chemical composition and properties of the honey. Diastase activity, sucrose content and hydroxymethylfurfural content were easily differentiated and these parameters were used for indication of the adulteration of the honey. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Chemometric representation of molecular marker data of some Niger Delta crude oils

    Directory of Open Access Journals (Sweden)

    Mudiaga Chukunedum Onojake

    2015-06-01

    Full Text Available Chemometric representation of data is the most preferred and adopted method of research reporting in contemporary times. Data are easily discerned and interpreted. Molecular maker parameters of some crude oils from the Nigerian’s Delta region are chemometrically expressed after data treatment using multivariate statistical analyses, other graphical representations were the star diagram and triangular (ternary plot. The results indicated discrimination of samples into two genetic families corresponding to their primary oil fields. These groupings were more obvious for results obtained via principal component analysis. Genetic groupings are principally due to compositional differences which are commonly attributed to unique source rock depositional environments and/or sourcing organic matter. The two families of oils identified have both terrestrial inputs, but differ comparatively by relative marine inputs.

  4. Circum-Arctic petroleum systems identified using decision-tree chemometrics

    Science.gov (United States)

    Peters, K.E.; Ramos, L.S.; Zumberge, J.E.; Valin, Z.C.; Scotese, C.R.; Gautier, D.L.

    2007-01-01

    Source- and age-related biomarker and isotopic data were measured for more than 1000 crude oil samples from wells and seeps collected above approximately 55??N latitude. A unique, multitiered chemometric (multivariate statistical) decision tree was created that allowed automated classification of 31 genetically distinct circumArctic oil families based on a training set of 622 oil samples. The method, which we call decision-tree chemometrics, uses principal components analysis and multiple tiers of K-nearest neighbor and SIMCA (soft independent modeling of class analogy) models to classify and assign confidence limits for newly acquired oil samples and source rock extracts. Geochemical data for each oil sample were also used to infer the age, lithology, organic matter input, depositional environment, and identity of its source rock. These results demonstrate the value of large petroleum databases where all samples were analyzed using the same procedures and instrumentation. Copyright ?? 2007. The American Association of Petroleum Geologists. All rights reserved.

  5. Discrimination of geographical origin of extra virgin olive oils using terahertz spectroscopy combined with chemometrics.

    Science.gov (United States)

    Liu, Wei; Liu, Changhong; Yu, Junjie; Zhang, Yan; Li, Jian; Chen, Ying; Zheng, Lei

    2018-06-15

    Discrimination of geographical origin of extra-virgin olive oils (EVOOs) is of great importance for legislation and consumers worldwide. The feasibility of a rapid discrimination of four different geographical origins of EVOOs with terahertz spectroscopy system was examined. Different chemometrics including least squares-support vector machines (LS-SVM), back propagation neural network (BPNN) and random forest (RF) combined with principal component analysis (PCA), genetic algorithm (GA) were compared to obtain the best discrimination model. The results demonstrated that there were apparent differences among the four different geographical origins of EVOOs in fatty acid compositions and the absorbance spectra, and an excellent classification (accuracy was 96.25% in prediction set) could be achieved using the LS-SVM method combine with GA. It can be concluded that THz spectroscopy together with chemometrics would be a promising technique to rapid discriminate the geographical origin of EVOOs with high efficiency. Copyright © 2018 Elsevier Ltd. All rights reserved.

  6. Multivariate analysis of Scotch whisky by total reflection x-ray fluorescence and chemometric methods: A potential tool in the identification of counterfeits.

    Science.gov (United States)

    Shand, Charles A; Wendler, Renate; Dawson, Lorna; Yates, Kyari; Stephenson, Hayleigh

    2017-07-11

    Most methods used in the identification of counterfeit whisky have focused on the profiling of volatile organic congeners determined by gas chromatography. We tested the use of total reflection x-ray fluorescence (TXRF) for trace element analysis of whisky and application of the data as a potential tool in the identification of counterfeit samples. Twenty five whiskies that were produced in different regions of Scotland or were blends, 5 counterfeit whiskies, 1 unmatured grain whisky, and 1 matured grain whisky were analysed for 11 elements (P, S, Cl, K, Ca, Mn, Fe, Cu, Zn, Br and Rb). The effect of cold plasma ashing with oxygen on whisky residues evaporated on the TXRF reflector on the instrument performance was investigated. Cold plasma ashing with oxygen reduced beam scatter and improved the limits of detection but was ultimately deemed unnecessary. The element concentration data for whisky obtained by TXRF (after log transformation) was compared with the values obtained by inductively coupled plasma spectroscopy and showed correlation values (R 2 ) ≥ 0.942 for K, Mn and Cu: ≥ 0.800 for Ca, Fe and Rb; and ≥0.535 for P, S and Zn. The range of concentration values for individual elements was variable and principal components analysis of the elemental concentrations partially differentiated the whiskies by region or type but showed clear separation of the counterfeit samples from the other samples. Using the principal component scores of the elemental concentration data, linear discriminant analysis also distinguished the counterfeits from the other samples. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. The Verification of the Usefulness of Electronic Nose Based on Ultra-Fast Gas Chromatography and Four Different Chemometric Methods for Rapid Analysis of Spirit Beverages

    Directory of Open Access Journals (Sweden)

    Paulina Wiśniewska

    2016-01-01

    Full Text Available Spirit beverages are a diverse group of foodstuffs. They are very often counterfeited which cause the appearance of low quality products or wrongly labelled products on the market. It is important to find a proper quality control and botanical origin method enabling the same time preliminary check of the composition of investigated samples, which was the main goal of this work. For this purpose, the usefulness of electronic nose based on ultra-fast gas chromatography (fast GC e-nose was verified. A set of 24 samples of raw spirits, 33 samples of vodkas, and 8 samples of whisky were analysed by fast GC e-nose. Four data analysis methods were used. The PCA was applied for the visualization of dataset, observation of the variation inside groups of samples, and selection of variables for the other three statistical methods. The SQC method was utilized to compare the quality of the samples. Both the DFA and SIMCA data analysis methods were used for discrimination of vodka, whisky, and spirits samples. The fast GC e-nose combined with four statistical methods can be used for rapid discrimination of raw spirits, vodkas, and whisky and in the same for preliminary determination of the composition of investigated samples.

  8. A chemometric analysis of ligand-induced changes in intrinsic fluorescence of folate binding protein indicates a link between altered conformational structure and physico-chemical characteristics

    DEFF Research Database (Denmark)

    Bruun, Susanne W; Holm, Jan; Hansen, Steen Ingemann

    2009-01-01

    Ligand binding alters the conformational structure and physico-chemical characteristics of bovine folate binding protein (FBP). For the purpose of achieving further information we analyzed ligand (folate and methotrexate)-induced changes in the fluorescence landscape of FBP. Fluorescence excitation...... of folate accords fairly well with the disappearance of strongly hydrophobic tryptophan residues from the solvent-exposed surface of FBP. The PARAFAC has thus proven useful to establish a hitherto unexplained link between parallel changes in conformational structure and physico-chemical characteristics...... of FBP induced by folate binding. Parameters for ligand binding derived from PARAFAC analysis of the fluorescence data were qualitatively and quantitatively similar to those obtained from binding of radiofolate to FBP. Herein, methotrexate exhibited a higher affinity for FBP than in competition...

  9. Analysis of Porous Structure Parameters of Biomass Chars Versus Bituminous Coal and Lignite Carbonized at High Pressure and Temperature—A Chemometric Study

    Directory of Open Access Journals (Sweden)

    Adam Smoliński

    2017-09-01

    Full Text Available The characteristics of the porous structure of carbonized materials affect their physical properties, such as density or strength, their sorption capacity, and their reactivity in thermochemical processing, determining both their applicability as fuels or sorbents and their efficiency in various processes. The porous structure of chars is shaped by the combined effects of physical and chemical properties of a carbonaceous material and the operating parameters applied in the carbonization process. In the study presented, the experimental dataset covering parameters of various fuels, ranging from biomass through lignite to bituminous coal, and chars produced at 1273 K and under the pressure of 1, 2, 3, and 4 MPa was analyzed with the application of the advanced method of data exploration. The principal component analysis showed that the sample of the highest coal rank was characterized by lower values of parameters reflecting the development of the porous structure of chars. A negative correlation was also observed between the carbon content in a fuel and the evolution of the porous structure of chars at high pressure. The highest total pore volume of chars produced under 1 and 3 MPa and the highest micropore surface area under 3 MPa were reported for a carbonized fuel sample of the highest moisture content.

  10. Metabolomics driven analysis of six Nigella species seeds via UPLC-qTOF-MS and GC-MS coupled to chemometrics.

    Science.gov (United States)

    Farag, Mohamed A; Gad, Haidy A; Heiss, Andreas G; Wessjohann, Ludger A

    2014-05-15

    Nigella sativa, commonly known as black cumin seed, is a popular herbal supplement that contains numerous phytochemicals including terpenoids, saponins, flavonoids, alkaloids. Only a few of the ca. 15 species in the genus Nigella have been characterized in terms of phytochemical or pharmacological properties. Here, large scale metabolic profiling including UPLC-PDA-MS and GC-MS with further multivariate analysis was utilized to classify 6 Nigella species. Under optimized conditions, we were able to annotate 52 metabolites including 8 saponins, 10 flavonoids, 6 phenolics, 10 alkaloids, and 18 fatty acids. Major peaks in UPLC-MS spectra contributing to the discrimination among species were assigned as kaempferol glycosidic conjugates, with kaempferol-3-O-[glucopyranosyl-(1→2)-galactopyranosyl-(1→2)-glucopyranoside, identified as potential taxonomic marker for N. sativa. Compared with GC-MS, UPLC-MS was found much more efficient in Nigella sample classification based on genetic and geographical origin. Nevertheless, both GC-MS and UPLC-MS support the remote position of Nigella nigellastrum in relation to the other taxa. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. Chemometric analysis of groundwater quality data around municipal landfill and paper factory and their potential influence on population’s health

    Directory of Open Access Journals (Sweden)

    Ljiljana Čačić

    2012-02-01

    Full Text Available Aim To assess the level of 15 groundwater quality parameters in groundwater samples collected around municipal landfill and paper factory in order to evaluate usefulness of the groundwater and its possible implication on the human health. Methods Obtained data have been analyzed by principal component analysis (PCA technique, in order to differentiate the groundwater samples on the basis of their compositional differences and origin. Results Wastes and effluents from municipal landfill did not contribute significantly to the pollution of the aquatic medium. Groundwater degradation caused by high contents of nitrate, mineral oils, organic and inorganic matters was particularly expressed in the narrow area of the city centre, near the paper factory and most likely it has occurred over a long period of time. The results have shown that the concentrations of the most measured parameters(NO3-N, NH4-N, oils, organic matter, Fe, Pb, Ni and Cr were above llowed limits for drinking and domestic purposes. onclusion This study has provided important information on cological status of the groundwater systems and for identification f groundwater quality parameters with concentrations above llowable limits for human consumption. The results generally evealed that groundwater assessed in this study mainly does not atisfy safe limits for drinking water and domestic use. As a consequence, ontaminated groundwater becomes a large hygienic nd toxicological problem, since it considerably impedes groundwater tilization. Even though, all of these contaminants havenot yet reached toxic levels, they still represent long term risk for ealth of the population.

  12. Development, characterization and chemometric analysis of a gluten-free food bar containing whole flour from a new cultivar of amaranth

    Directory of Open Access Journals (Sweden)

    Lilian Maria Pagamunici

    2014-06-01

    Full Text Available Food bars are consumed heavily, especially because of their practicality; however they cannot be ingested by celiac patients and present low contents of essential nutrients. The goal of this study was the development and physical-chemical, nutritional and sensory evaluation of a gluten-free food bar containing amaranth and linseed. Gluten fractions were not detected in the food bar formulations. Crude protein and total lipid contents ranged from 68.32 to 76.60 and 74.56 to 82.06 g kg-1 of food, respectively. The polyunsaturated/saturated and n-6:n-3 fatty acid ratios ranged from 0.45:1 to 0.55:1 and 1.44:1 to 2.50:1, respectively. Calcium, magnesium, copper, iron, manganese and zinc were the principal minerals. Application of multivariate analysis enabled sample B to be distinguished according to its mineral and alfa-linolenic acid content. All food bar formulations had good sensory acceptance and high purchase intent.

  13. Thermal oxidation process accelerates degradation of the olive oil mixed with sunflower oil and enables its discrimination using synchronous fluorescence spectroscopy and chemometric analysis

    Science.gov (United States)

    Mabood, Fazal; Boqué, Ricard; Folcarelli, Rita; Busto, Olga; Al-Harrasi, Ahmed; Hussain, Javid

    2015-05-01

    We have investigated the effect of thermal treatment on the discrimination of pure extra virgin olive oil (EVOO) samples from EVOO samples adulterated with sunflower oil. Two groups of samples were used. One group was analyzed at room temperature (25 °C) and the other group was thermally treated in a thermostatic water bath at 75 °C for 8 h, in contact with air and with light exposure, to favor oxidation. All samples were then measured with synchronous fluorescence spectroscopy. Fluorescence spectra were acquired by varying the excitation wavelength in the region from 250 to 720 nm. In order to optimize the differences between excitation and emission wavelengths, four constant differential wavelengths, i.e., 20 nm, 40 nm, 60 nm and 80 nm, were tried. Partial least-squares discriminant analysis (PLS-DA) was used to discriminate between pure and adulterated oils. It was found that the 20 nm difference was the optimal, at which the discrimination models showed the best results. The best PLS-DA models were those built with the difference spectra (75-25 °C), which were able to discriminate pure from adulterated oils at a 2% level of adulteration. Furthermore, PLS regression models were built to quantify the level of adulteration. Again, the best model was the one built with the difference spectra, with a prediction error of 1.75% of adulteration.

  14. The effect of thermal treatment on the enhancement of detection of adulteration in extra virgin olive oils by synchronous fluorescence spectroscopy and chemometric analysis

    Science.gov (United States)

    Mabood, F.; Boqué, R.; Folcarelli, R.; Busto, O.; Jabeen, F.; Al-Harrasi, Ahmed; Hussain, J.

    2016-05-01

    In this study the effect of thermal treatment on the enhancement of synchronous fluorescence spectroscopic method for discrimination and quantification of pure extra virgin olive oil (EVOO) samples from EVOO samples adulterated with refined oil was investigated. Two groups of samples were used. One group was analyzed at room temperature (25 °C) and the other group was thermally treated in a thermostatic water bath at 75 °C for 8 h, in contact with air and with light exposure, to favor oxidation. All the samples were then measured with synchronous fluorescence spectroscopy. Synchronous fluorescence spectra were acquired by varying the wavelength in the region from 250 to 720 nm at 20 nm wavelength differential interval of excitation and emission. Pure and adulterated olive oils were discriminated by using partial least-squares discriminant analysis (PLS-DA). It was found that the best PLS-DA models were those built with the difference spectra (75 °C-25 °C), which were able to discriminate pure from adulterated oils at a 2% level of adulteration of refined olive oils. Furthermore, PLS regression models were also built to quantify the level of adulteration. Again, the best model was the one built with the difference spectra, with a prediction error of 3.18% of adulteration.

  15. Spatial assessment of Langat River water quality using chemometrics.

    Science.gov (United States)

    Juahir, Hafizan; Zain, Sharifuddin Md; Aris, Ahmad Zaharin; Yusoff, Mohd Kamil; Mokhtar, Mazlin Bin

    2010-01-01

    The present study deals with the assessment of Langat River water quality with some chemometrics approaches such as cluster and discriminant analysis coupled with an artificial neural network (ANN). The data used in this study were collected from seven monitoring stations under the river water quality monitoring program by the Department of Environment (DOE) from 1995 to 2002. Twenty three physico-chemical parameters were involved in this analysis. Cluster analysis successfully clustered the Langat River into three major clusters, namely high, moderate and less pollution regions. Discriminant analysis identified seven of the most significant parameters which contribute to the high variation of Langat River water quality, namely dissolved oxygen, biological oxygen demand, pH, ammoniacal nitrogen, chlorine, E. coli, and coliform. Discriminant analysis also plays an important role as an input selection parameter for an ANN of spatial prediction (pollution regions). The ANN showed better prediction performance in discriminating the regional area with an excellent percentage of correct classification compared to discriminant analysis. Multivariate analysis, coupled with ANN, is proposed, which could help in decision making and problem solving in the local environment.

  16. Discrimination of Corsican honey by FT-Raman spectroscopy and chemometrics

    Directory of Open Access Journals (Sweden)

    Fernández Pierna, JA.

    2011-01-01

    Full Text Available Honey is a complex and challenging product to analyze due mainly to its composition consisting on various botanical sources. The discrimination of the origin of honey is of prime importance in order to reinforce the consumer trust in this typical food product. But this is not an easy task as usually no single chemical or physical parameter is sufficient. The aim of our paper is to investigate whether FT-Raman spectroscopy as spectroscopic fingerprint technique combined with some chemometric tools can be used as a rapid and reliable method for the discrimination of honey according to their source. In addition to that, different chemometric models are constructed in order to discriminate between Corsican honeys and honey coming from other regions in France, Italy, Austria, Germany and Ireland based on their FT-Raman spectra. These regions show a large variation in their plants. The developed models include the use of exploratory techniques as the Fisher criterion for wavenumber selection and supervised methods as Partial Least Squares-Discriminant Analysis (PLS-DA or Support Vector Machines (SVM. All these models showed a correct classification ratio between 85% and 90% of average showing that Raman spectroscopy combined to chemometric treatments is a promising way for rapid and non-expensive discrimination of honey according to their origin.

  17. Chemometrics tools used in analytical chemistry: an overview.

    Science.gov (United States)

    Kumar, Naveen; Bansal, Ankit; Sarma, G S; Rawal, Ravindra K

    2014-06-01

    This article presents various important tools of chemometrics utilized as data evaluation tools generated by various hyphenated analytical techniques including their application since its advent to today. The work has been divided into various sections, which include various multivariate regression methods and multivariate resolution methods. Finally the last section deals with the applicability of chemometric tools in analytical chemistry. The main objective of this article is to review the chemometric methods used in analytical chemistry (qualitative/quantitative), to determine the elution sequence, classify various data sets, assess peak purity and estimate the number of chemical components. These reviewed methods further can be used for treating n-way data obtained by hyphenation of LC with multi-channel detectors. We prefer to provide a detailed view of various important methods developed with their algorithm in favor of employing and understanding them by researchers not very familiar with chemometrics. Copyright © 2014 Elsevier B.V. All rights reserved.

  18. Chemometric evaluation of trace elements in Brazilian medicinal plants

    International Nuclear Information System (INIS)

    Silva, Paulo S.C. da; Francisconi, Lucilaine S.; Goncalves, Rodolfo D.M.R.

    2013-01-01

    The growing interest in herbal medicines has required standardization in order to ensure their safe use, therapeutic efficacy and quality of the products. Despite the vast flora and the extensive use of medicinal plants by the Brazilian population, scientific studies on the subject are still insufficiency In this study, 59 medicinal plans were analyzed for the determination of As, Ba, Br, Ca, Cl, Cs, Co, Cr, Fe, Hf, K, Mg, Mn, Na, Rb, Sb, Sc, Se, Ta, Th, U, Zn and Zr by neutron activation analysis and Cu, Ni, Pb, Cd and Hg by atomic absorption. The results were analyzed by chemometric methods: correlation analysis, principal component analysis and cluster analysis, in order to verify whether or not there is similarity with respect to their mineral and trace metal contents. Results obtained permitted to classify distinct groups among the analyzed plants and extracts so that these data can be useful in future studies, concerning the therapeutic action the elements here determined may exert. (author)

  19. Spectroscopic and chemometric exploration of food quality

    DEFF Research Database (Denmark)

    Pedersen, Dorthe Kjær

    2002-01-01

    The desire to develop non-invasive rapid measurements of essential quality parameters in foods is the motivation of this thesis. Due to the speed and noninvasive properties of spectroscopic techniques, they have potential as on-line or atline methods and can be employed in the food industry...... in order to control the quality of the end product and to continuously monitor the production. In this thesis, the possibilities and limitations of the application of spectroscopy and chemometrics in rapid control of food quality are discussed and demonstrated by the examples in the eight included...... publications. Different aspects of food quality are covered, but the focus is mainly on the development of multivariate calibrations for predictions of rather complex attributes such as the water-holding capacity of meat, ethical quality of the slaughtering procedure, protein content of single wheat kernels...

  20. Chromatography methods and chemometrics for determination of milk fat adulterants

    Science.gov (United States)

    Trbović, D.; Petronijević, R.; Đorđević, V.

    2017-09-01

    Milk and milk-based products are among the leading food categories according to reported cases of food adulteration. Although many authentication problems exist in all areas of the food industry, adequate control methods are required to evaluate the authenticity of milk and milk products in the dairy industry. Moreover, gas chromatography (GC) analysis of triacylglycerols (TAGs) or fatty acid (FA) profiles of milk fat (MF) in combination with multivariate statistical data processing have been used to detect adulterations of milk and dairy products with foreign fats. The adulteration of milk and butter is a major issue for the dairy industry. The major adulterants of MF are vegetable oils (soybean, sunflower, groundnut, coconut, palm and peanut oil) and animal fat (cow tallow and pork lard). Multivariate analysis enables adulterated MF to be distinguished from authentic MF, while taking into account many analytical factors. Various multivariate analysis methods have been proposed to quantitatively detect levels of adulterant non-MFs, with multiple linear regression (MLR) seemingly the most suitable. There is a need for increased use of chemometric data analyses to detect adulterated MF in foods and for their expanded use in routine quality assurance testing.

  1. Combination with Chemometrics and Quantification for Quality Evaluation and Variety Identification of Flos Chimonanthi Praecocis by HPLC.

    Science.gov (United States)

    Zhang, Chao; Su, Jing-Hua; Sun, Lei; Gu, Bing-Ren; Xing, Yi-Wen

    2016-08-01

    Flos Chimonanthi Praecocis (FCP) is one of the popular traditional Chinese medicines, which have been widely used in China. Inconspicuous appearance differences are disadvantageous for identification, and it is difficult to evaluate the quality of FCP using the current methods. In this article, a simple method that combined chemometrics and quantitative analysis was established. The samples were obtained from three typical varieties for fingerprint analysis by high-performance liquid chromatography. Contents of rutin and quercetin were determined, and then a common pattern with 16 characteristic peaks was applied for principal component analysis, similarity analysis, and the hierarchical cluster analysis heatmap (HCA heatmap) to characterize the similarity and differences among samples for identification. Furthermore, seven characteristics peaks with higher loading values were selected for chemometrics analysis after dimensionality reduction to reduce analytical difficulty, and the new common pattern showed the similar identification effects. Overall, combination with chemometrics and quantitative analysis would provide a useful and simple method for quality control of FCP in the future. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  2. Use of Raman spectroscopy and chemometrics to distinguish blue ballpoint pen inks.

    Science.gov (United States)

    de Souza Lins Borba, Flávia; Honorato, Ricardo Saldanha; de Juan, Anna

    2015-04-01

    The objective of this work is assessing whether the combination of Raman spectroscopy and chemometric tools is appropriate to differentiate blue ballpoint pen inks. Fourteen commercial blue ballpoint pen inks from different brands and models were studied and Raman spectra were obtained on ink lines written on A4 sulfite paper. First, a study of the best Raman configurations, in terms of laser intensity used and acquisition mode, was carried out to ensure sufficient spectroscopic quality without damaging the sample. Chemometric methods were applied first to improve the definition of spectral bands and to suppress fluorescence contributions from the signal. Once the spectra were suitably preprocessed, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were applied to explore whether the different inks could be distinguished from their Raman spectra. Almost all inks could be gradually differentiated, through successive PCA analyses or looking at the different levels of the dendrogram structure provided by HCA. From these exploratory results, a tree structure was constructed based on PCA and HCA results in order to reflect the degree of similarity among ink classes. This tree structure was used as the basis to develop hierarchical classification models based on partial least squares-discriminant analysis (PLS-DA). Correct classification of inks was achieved by these PLS-DA models built and the most important regions to identify the ink classes were detected using the variable importance in projection plots (VIPs). The combination of Raman spectroscopy and chemometrics has been proven to be a promising fast non-destructive tool to differentiate among very similar ink types in documents. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  3. ATR-FTIR spectroscopy and chemometrics: An interesting tool to discriminate and characterize counterfeit medicines.

    Science.gov (United States)

    Custers, D; Cauwenbergh, T; Bothy, J L; Courselle, P; De Beer, J O; Apers, S; Deconinck, E

    2015-08-10

    Counterfeit medicines pose a huge threat to public health worldwide. High amounts of counterfeit pharmaceuticals enter the European market and therefore detection of these products is essential. Attenuated Total Reflection Fourier-Transform infrared spectroscopy (ATR-FTIR) might be useful for the screening of counterfeit medicines since it is easy to use and little sample preparation is required. Furthermore, this approach might be helpful to customs to obtain a first evaluation of suspected samples. This study proposes a combination of ATR-FTIR and chemometrics to discriminate and classify counterfeit medicines. A sample set, containing 209 samples in total, was analyzed using ATR-FTIR and the obtained spectra were used as fingerprints in the chemometric data-analysis which included Principal Component Analysis (PCA), k-Nearest Neighbours (k-NN), Classification and Regression Trees (CART) and Soft Independent Modelling of Class Analogy (SIMCA). First it was verified whether the mentioned techniques are capable to distinguish samples containing different active pharmaceutical ingredients (APIs). PCA showed a clear tendency of discrimination based on the API present; k-NN, CART and SIMCA were capable to create suitable prediction models based on the presence of different APIs. However k-NN performs the least while SIMCA performs the best. Secondly, it was tested whether these three models could be expanded to discriminate between genuine and counterfeit samples as well. k-NN was not able to make the desired discrimination and therefore it was not useful. CART performed better but also this model was less suited. SIMCA, on the other hand, resulted in a model with a 100% correct discrimination between genuine and counterfeit drugs. This study shows that chemometric analysis of ATR-FTIR fingerprints is a valuable tool to discriminate genuine from counterfeit samples and to classify counterfeit medicines. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. A chemometric study of ageing in lead-based paints.

    Science.gov (United States)

    Pallipurath, Anuradha; Skelton, Jonathan; Bucklow, Spike; Elliott, Stephen

    2015-11-01

    The development of non-invasive analytical methods is of widespread interest to the field of conservation science, providing chemical insight into the materials used to create painted works of art, which can, for example, inform decisions about their restoration and preservation, or help discern original works from forgeries. A key undertaking in this area is to develop practical methods for identifying and understanding the chemical processes that occur in paint films under ageing. Furthermore, whereas a number of scientific studies have focussed on model systems in which natural ageing processes are simulated in a short time by irradiation under ultraviolet (UV) light, it remains to be established to what extent natural and accelerated ageing induce similar chemical changes. In this work, we employ FT-Raman spectroscopy, together with a simple spectral-deconvolution algorithm, to study in detail the spectral changes accompanying the natural and UV-accelerated ageing of lead-based paint films. We find that the two processes differ significantly, and that spectroscopic signatures, principally in the fluorescence background, can thus be used to differentiate the two modes of ageing and hence possibly to identify attempted forgeries. Our studies also suggest that paints based on proteinaceous binders are more stable to ageing than lipid-bound ones. Finally, we investigate the possibility of using our chemometric deconvolution technique, in conjunction with multivariate analysis, for the semi-automated characterisation of the degree or extent of ageing in unknown samples. Copyright © 2015 Elsevier B.V. All rights reserved.

  5. Thermal degradation assessment of canola and olive oil using ultra-fast gas chromatography coupled with chemometrics.

    Science.gov (United States)

    Majchrzak, Tomasz; Lubinska, Martyna; Różańska, Anna; Dymerski, Tomasz; Gębicki, Jacek; Namieśnik, Jacek

    2017-01-01

    Oil blending is often used to enhance the properties of vegetable oils. The admixture of a more thermally stable oil makes the resulting blend more suitable for use in frying. A new method of quality assessment of vegetable oils used in frying is presented in this paper. In this method, ultra-fast gas chromatography coupled with flame ionization detector and chemometrics is employed. Principal component analysis was used for data processing. The results obtained with this method were compared with the results of the Rancimat test and sensory evaluation. It is demonstrated that the addition of olive oil improves the stability of rapeseed oil, and also changes its flavour and aroma profile. In addition, it was found that ultra-fast GC coupled with chemometrics is an effective tool for the assessment of the quality of edible oils. The proposed method does not require sample preparation, and the total time of analysis is less than 2 min.

  6. Characterization of Dissolved Organic Matter from Sewage Sludge using 3D-Fluorescence Spectroscopy and Chemometric Tools

    OpenAIRE

    Martín-Mata, Julio; Marhuenda Egea, Frutos Carlos; Moral, Raúl; Torres-Climent, Ángel; Martínez Sabater, Encarnación; Paredes, Concepción; Barber, J. Xavier; Morales, Javier

    2015-01-01

    The aim of the present article is to show the possibilities of chemometric tools and the parallel factor analysis (PARAFAC) model, as well as to understand the complexities of the fluorescence emission-excitation matrix (EEM) of water-soluble organic matter (WSOM) extracted from sewage sludge samples obtained with different origins and stabilization procedures. The variation in the composition of WSOM in the different sewage sludge samples could be correlated with the conditions of stabilizat...

  7. FT-NIR characterization with chemometric analyses to differentiate goldenseal from common adulterants.

    Science.gov (United States)

    Liu, Ying; Finley, Jamie; Betz, Joseph M; Brown, Paula N

    2018-02-05

    Goldenseal (Hydrastis canadensis L.) has been a popular herb since the 1970s, with a US market share of over $32 million in 2014. Wild goldenseal has been listed in the Convention on International Trade in Endangered Species for decades. Limits in supply and greed for profit have led to adulteration with similar but more accessible and inexpensive plant materials. Fourier transform near-infrared spectroscopy (FT-NIR) coupled with three different chemometric models, partial least squares (PLS) regression, soft independent modeling of class analogy (SIMCA), and moving window principal component analysis (MW-PCA) provide fast, simple, nondestructive approaches to differentiating pure goldenseal from 4 common pure adulterants (yellow dock, yellow root, coptis, Oregon grape). All three models successfully differentiated authentic goldenseal from adulterants. The models were t-tested for detection of goldenseal intentionally mixed with individual adulterants at 2% to 95% theoretical levels made computationally. The PLS model was unable to detect adulterants mixed with goldenseal at any level. The SIMCA model was the best for detection of yellow root and Oregon grape adulteration in goldenseal, as low as 10%. The MW-PCA model proved best for detection of yellow dock at ≥ 15% and coptis adulteration ≥5% in goldenseal. This study demonstrates that NIR spectroscopy coupled with chemometric analyses is a good tool for industry and investigators to implement for rapid detection of goldenseal adulteration in the marketplace, but also indicates that the specific approach to chemometric analysis must be evaluated and selected on a case-by-case basis in order to achieve useful sensitivity and specificity. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

  8. Differentiation of Bread Made with Whole Grain and Refined Wheat (T. aestivum) Flour Using LC/MS-based chromatographic Fingerprinting and Chemometric Approaches

    Science.gov (United States)

    A fuzzy chromatography mass spectrometric (FCMS) fingerprinting method combined with chemometric analysis was established to diffrentiate between whole wheat (WW) flours and refined wheat (RW) flour, and the breads made from them. The chemical compositions of the bread samples were profiled using h...

  9. Nuclear magnetic resonance (1.40 T) and mid infrared (FTIR-ATR) associated with chemometrics as analytical methods for the analysis of methyl ester yield obtained by esterification reaction

    Energy Technology Data Exchange (ETDEWEB)

    Kollar, Sara R.M.; Suarez, Paulo A.Z., E-mail: psuarez@unb.br [Universidade de Brasilia (UnB), Brasília, DF (Brazil). Instituto de Química; Novotny, Etelvino H. [Embrapa Solos, Rio de Janeiro, RJ (Brazil); Nascimento, Claudia J. do [Universidade Federal do Estado do Rio de Janeiro (UNIRIO), Rio de Janeiro, RJ, (Brazil). Instituto de Biociências

    2017-07-01

    In this work, we compared 1.40 T nuclear magnetic resonance (NMR) to 7.05 T (60 and 300 MHz for proton, respectively), and mid-infrared with attenuated total reflectance (FTIR-ATR), associated with chemometrics methods, for the quantification of the reaction yield during esterification of fatty acids with methanol. The results showed that the integrated intensities of the ester C=O stretching region, relative to the total C=O stretching region, is useful to quantify the fatty acid methyl ester (FAME) concentration. Comparing the results obtained by the different final models: NMR (1.40 T and 7.05 T), FTIR-ATR using multivariate partial last squares regression (PLS) with orthogonal signal correction (OSC), and univariate ordinary least squares (OLS), the NMR of 1.40 T (60 MHz for proton) showed more advantages when compared to a high field spectrometer, due to the non-use of cryogenic and solvents and less laborious work for obtaining results. (author)

  10. Classification of Aroma Styles and Geographic Origins of Chinese Liquors Using Chemometrics Based on Fluorescence Spectroscopy

    Science.gov (United States)

    Ma, Y.; Huo, D.-Q.; Qin, H.; Shen, C.-H.; Yang, P.; Hou, C.-J.

    2017-05-01

    The purpose of this paper is to study the feasibility of fluorescence spectroscopy as a reliable method for discrimination of Chinese liquor according to different aroma styles and geographic origins. The 84 Chinese liquors were analyzed by fluorescence spectroscopy and chemometrics. The results showed that Chinese liquors exhibit characteristic fluorescence spectra recorded at special excitation wavelengths that may be considered as fingerprints. Both principal component analysis (PCA) and stepwise linear discriminant analysis (SLDA) were carried out on the emission spectra (330-435 nm) recorded at excitation wavelength 300 nm to classify different aroma styles of Chinese liquors. The first two principal components explained 98.87% of the total variance, and the SLDA classified correctly 100%. Both hierarchical cluster analysis (HCA) and principal component analysis (PCA) were carried out on the emission spectra (325-420 nm) recorded at excitation wavelength 300 nm to identify different geographic origins of Chinese liquors. HCA accurately identified all the samples and the first three PCA explained 98.25% of the total variance. This study indicates that fluorescence spectroscopy coupled with chemometrics offers a promising approach for identifying Chinese liquors according to different flavor types and geographic origins.

  11. Antibacterial evaluation of Salvia miltiorrhizae on Escherichia coli by microcalorimetry coupled with chemometrics.

    Science.gov (United States)

    Ying, Guangyao; Zhang, Shanshan; Hu, Yuli; Yang, Meihua; Chen, Ping; Wu, Xiaoru; Guo, Weiying; Kong, Weijun

    2017-12-01

    For seeking novel antibacterial agents with high efficacy and low toxicity to deal with drug resistance, the effects of Salvia miltiorrhizae from various sources on Escherichia coli were evaluated by microcalorimetry coupled with chemometrics. Firstly, the heat-flow power-time curves of E. coli growth affected by different S. miltiorrhizae samples were recorded. Then, some crucial quantitative thermo-kinetic parameters including growth rate constant, heat-flow power and heat output, etc. were obtained from theses curves and were further investigated by some powerful chemometric techniques including similarity analysis, multivariate analysis of variance, hierarchical clustering analysis and principle component analysis. By analyzing the principle parameters, growth rate constant of the second exponential phase (k 2 ) and the heat-flow output powers of the second highest peak (P 2 ), together with the derived parameter inhibitory ratio (I,  %), it could be quickly concluded that the tested S. miltiorrhizae samples from different sources in China exhibited strong antibacterial effects on E. coli and the samples from Beijing city exhibited the strongest anti-E. coli effects, which might be used as novel and underlying antibacterial candidates for the resistance of E. coli to the existing drugs in practice. This study provides a useful tool and helpful idea to accurately and rapidly evaluate the antibacterial effects of some complex matrices, offering some references for exploring new antibacterial agents.

  12. Application of Chemometric Techniques to Colorimetric Data in Classifying Automobile Paint

    International Nuclear Information System (INIS)

    Nur Awatif Rosli; Rozita Osman; Norashikin Saim; Mohd Zuli Jaafar

    2015-01-01

    The analysis of paint chips is of great interest to forensic investigators, particularly in the examination of hit-and run cases. This study proposes a direct and rapid method in classifying automobile paint samples based on colorimetric data sets; absorption value, reflectance value, luminosity value (L), degree of redness (a) and degree of yellowness (b) obtained from video spectral comparator (VSC) technique. A total of 42 automobile paint samples from 7 manufacturers were analysed. The colorimetric datasets obtained from VSC analysis were subjected to chemometric technique namely cluster analysis (CA) and principal component analysis (PCA). Based on CA, 5 clusters were generated; Cluster 1 consisted of silver color, cluster 2 consisted of white color, cluster 3 consisted of blue and black colors, cluster 4 consisted of red color and cluster 5 consisted of light blue color. PCA resulted in two latent factors explaining 95.58 % of the total variance, enabled to group the 42 automobile paints into five groups. Chemometric application on colorimetric datasets provide meaningful classification of automobile paints based on their tone colour (L, a, b) and light intensity These approaches have the potential to ease the interpretation of complex spectral data involving a large number of comparisons. (author)

  13. Authenticity of Cypriot sweet wine Commandaria using FT-IR and chemometrics.

    Science.gov (United States)

    Ioannou-Papayianni, Elena; Kokkinofta, Rebecca I; Theocharis, Charis R

    2011-04-01

    FT-IR spectra of 65 sweet wines produced in Cyprus and other countries were determined, in order to study the authenticity and uniqueness of the Cypriot traditional wine "Commandaria" that is produced from sun-dried grapes. Different sample preparation methods such as freeze-drying and nitrogen-flow concentration and direct analysis were used. The spectra were obtained in transmittance mode from KBr pellets and by using the attenuated total reflectance technique, and analyzed statistically using multivariate chemometric techniques, involving principal component analysis, cluster analysis, linear and regularized discriminant analysis, and classification and regression trees. A nearly correct classification for Commandaria was achieved. Fourier Transform Infrared spectroscopy and chemometrics were able to differentiate all the types of Commandaria (nonfortified, fortified, and commercial) from various sweet wines from other countries. Commandaria is a traditional Cyprus product that was proven to be very popular and economically very important. There is therefore a need to determine its chemical characteristics in order to differentiate it from its competitors and thus enable Cyprus to seek the protection of the name as a regional product. A means of easily distinguishing the genuine product from others mimicking it is also of significant economic interest.

  14. Determination of hydroxy acids in cosmetics by chemometric experimental design and cyclodextrin-modified capillary electrophoresis.

    Science.gov (United States)

    Liu, Pei-Yu; Lin, Yi-Hui; Feng, Chia Hsien; Chen, Yen-Ling

    2012-10-01

    A CD-modified CE method was established for quantitative determination of seven hydroxy acids in cosmetic products. This method involved chemometric experimental design aspects, including fractional factorial design and central composite design. Chemometric experimental design was used to enhance the method's separation capability and to explore the interactions between parameters. Compared to the traditional investigation that uses multiple parameters, the method that used chemometric experimental design was less time-consuming and lower in cost. In this study, the influences of three experimental variables (phosphate concentration, surfactant concentration, and methanol percentage) on the experimental response were investigated by applying a chromatographic resolution statistic function. The optimized conditions were as follows: a running buffer of 150 mM phosphate solution (pH 7) containing 0.5 mM CTAB, 3 mM γ-CD, and 25% methanol; 20 s sample injection at 0.5 psi; a separation voltage of -15 kV; temperature was set at 25°C; and UV detection at 200 nm. The seven hydroxy acids were well separated in less than 10 min. The LOD (S/N = 3) was 625 nM for both salicylic acid and mandelic acid. The correlation coefficient of the regression curve was greater than 0.998. The RSD and relative error values were all less than 9.21%. After optimization and validation, this simple and rapid analysis method was considered to be established and was successfully applied to several commercial cosmetic products. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Dose detection of radiated rice by infrared spectroscopy and chemometrics.

    Science.gov (United States)

    Shao, Yongni; He, Yong; Wu, Changqing

    2008-06-11

    Infrared spectroscopy based on sensitive wavelengths (SWs) and chemometrics was proposed to discriminate the nine different radiation doses (0, 250, 500, 750, 1000, 1500, 2000, 2500, and 3000 Gy) of rice. Samples ( n = 16 each dose) were selected randomly for the calibration set, and the remaining 36 samples ( n = 4 each dose) were selected for the prediction set. Partial least-squares (PLS) analysis and least-squares-support vector machine (LS-SVM) were implemented for calibration models. PLS analysis was implemented for calibration models with different wavelength bands including near-infrared (NIR) regions and mid-infrared (MIR) regions. The best PLS models were achieved in the MIR (400-4000 cm (-1)) region. Furthermore, different latent variables (5-9 LVs) were used as inputs of LS-SVM to develop the LV-LS-SVM models with a grid search technique and radial basis function (RBF) kernel. The optimal models were achieved with six LVs, and they outperformed PLS models. Moreover, independent component analysis (ICA) was executed to select several SWs based on loading weights. The optimal LS-SVM model was achieved with SWs (756, 895, 1140, and 2980 cm (-1)) selected by ICA and had better performance than PLS and LV-LS-SVM with the parameters of correlation coefficient ( r), root-mean-square error of prediction, and bias of 0.996, 80.260, and 5.172 x 10 (-4), respectively. The overall results indicted that the ICA was an effective way for the selection of SWs, and infrared spectroscopy combined with LS-SVM models had the capability to predict the different radiation doses of rice.

  16. Discrimination of Radix Polygoni Multiflori from different geographical areas by UPLC-QTOF/MS combined with chemometrics.

    Science.gov (United States)

    Tang, Jin-Fa; Li, Wei-Xia; Zhang, Fan; Li, Yu-Hui; Cao, Ying-Jie; Zhao, Ya; Li, Xue-Lin; Ma, Zhi-Jie

    2017-01-01

    Nowadays, Radix Polygoni Multiflori (RPM, Heshouwu in Chinese) from different geographical origins were used in clinic. In order to characterize the chemical profiles of different geographical origins of RPM samples, ultra-high performance liquid chromatography quadrupole time of flight mass spectrometry (UPLC-QTOF/MS) combined with chemometrics (partial least squared discriminant analysis, PLS‑DA) method was applied in the present study. The chromatography, chemical composition and MS information of RPM samples from 18 geographical origins were acquired and profiled by UPLC-QTOF/MS. The chemical markers contributing the differentiation of RPM samples were observed and characterized by supervised PLS‑DA method of chemometrics. The chemical composition differences of RPM samples derived from 18 different geographical origins were observed. Nine chemical markers were tentatively identified which could be used as specific chemical markers for the differentiation of geographical RPM samples. UPLC-QTOF/MS method coupled with chemometrics analysis has potential to be used for discriminating different geographical TCMs. Results will help to develop strategies for conservation and utilization of RPM samples.

  17. Classification of different tomato seed cultivars by multispectral visible-near infrared spectroscopy and chemometrics

    Directory of Open Access Journals (Sweden)

    Santosh Shrestha

    2016-04-01

    Full Text Available The feasibility of rapid and non-destructive classification of five different tomato seed cultivars was investigated by using visible and short-wave near infrared (Vis-NIR spectra combined with chemometric approaches. Vis-NIR spectra containing 19 different wavelengths ranging from 375 nm to 970 nm were extracted from multispectral images of tomato seeds. Principal component analysis (PCA was used for data exploration, while partial least squares discriminant analysis (PLS-DA and support vector machine discriminant analysis (SVM-DA were used to classify the five different tomato cultivars. The results showed very good classification accuracy for two independent test sets ranging from 94% to 100% for all tomato cultivars irrespective of chemometric methods. The overall classification error rates were 3.2% and 0.4% for the PLS-DA and SVM-DA calibration models, respectively. The results indicate that Vis-NIR spectra have the potential to be used for non-destructive discrimination of tomato seed cultivars with an opportunity to integrate them into plant genetic resource management, plant variety protection or registration programmes.

  18. Classification of traditional Chinese pork bacon based on physicochemical properties and chemometric techniques.

    Science.gov (United States)

    Guo, Xin; Huang, Feng; Zhang, Hong; Zhang, Chunjiang; Hu, Honghai; Chen, Wenbo

    2016-07-01

    Sixty-seven pork bacon samples from Hunan, Sichuan Guangdong, Jiangxi, and Yunnan Provinces in China were analyzed to understand their geographical properties. Classification was performed by determining their physicochemical properties through chemometric techniques, including variance analysis, principal component analysis (PCA), and discriminant analysis (DA). Results showed that certain differences existed in terms of nine physicochemical determinations in traditional Chinese pork bacon. PCA revealed the distinction among Hunan, Sichuan, and Guangdong style bacon. Meanwhile, seven key physicochemical determination criteria were identified in line with DA and could be reasonably applied to the classification of traditional Chinese pork bacon. Furthermore, the ratio of overall correct classification was 97.76% and that of cross-validation was 91.76%. These findings indicated that chemometric techniques, together with several physicochemical determination, were effective for the classification of traditional Chinese pork bacon with geographical features. Our study provided a theoretical reference for the classification of traditional Chinese pork bacon. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Characterization of pharmaceutically relevant materials at the solid state employing chemometrics methods.

    Science.gov (United States)

    Calvo, Natalia L; Maggio, Rubén M; Kaufman, Teodoro S

    2018-01-05

    The understanding of materials and processes is a requirement when it comes to build quality into pharmaceutical products. This can be achieved through the development of rapid, efficient and versatile analytical methods able to perform qualification or quantification tasks along the manufacturing and control process. Process monitoring, capable of providing reliable real-time insights into the processes performance during the manufacturing of solid dosage forms, are the key to improve such understanding. In response to these demands, in recent times multivariate chemometrics algorithms have been increasingly associated to different analytical techniques, mainly vibrational spectroscopies [Raman, mid-infrared (MIR), near-infrared (NIR)], but also ultraviolet-visible (UV-vis) spectroscopy, X-ray powder diffraction and other methodologies. The resulting associations have been applied to the characterization and evaluation of different aspects of pharmaceutical materials at the solid state. This review examines the different scenarios where these methodological marriages have been successful. The list of analytical problems and regulatory demands solved by chemometrics analysis of solid-state multivariate data covers the whole manufacturing and control processes of both, active pharmaceutical ingredients in bulk and in their drug products. Hence, these combinations have found use in monitoring the crystallization processes of drugs and supramolecular drug associations (co-crystals, co-amorphous and salts), to access the correct crystal morphology, particle size, solubility and dissolution properties. In addition, they have been applied to identify and quantitate specific compounds, mainly active pharmaceutical ingredients in complex solid state mixtures. This included drug stability against different stimuli, solid-state transformations, or detection of adulterated or fraudulent medicines. The use of chemometrics-assisted analytical methods as part of the modern

  20. Chemometrics in multispectral imaging for quality inspection of postharvest products

    NARCIS (Netherlands)

    Noordam, Jan Corstiaan

    2005-01-01

    This thesis describes different novel chemometric techniques applied to multispectral images for quality inspection on agricultural food products. These images do not only have a huge number of spectral bands which makes training set selection a challenging task, they also contain classes with small

  1. application of chemometric methods to resolve intermediates formed ...

    African Journals Online (AJOL)

    APPLICATION OF CHEMOMETRIC METHODS TO RESOLVE INTERMEDIATES. FORMED DURING ... Chromatography coupled with mass spectrometry has been proved to be a powerful technique to ..... HPLC/UV-VIS diode array and atmospheric pressure ionization quadrupole ion trap massspectrometry. Int. J. Mass ...

  2. Assessment on pattern of urban air quality by using chemometric ...

    African Journals Online (AJOL)

    The study evaluate the relationship between the main daily concentrations of criteria air pollutants in urban areas and their associations by using chemometric technique. Data were gathered from the Department of Environmental for three years observations (2011-2013) consisting of 5 major pollutants such as SO2, NO2, ...

  3. Identification of Coffee Varieties Using Laser-Induced Breakdown Spectroscopy and Chemometrics

    Science.gov (United States)

    Zhang, Chu; Shen, Tingting

    2017-01-01

    We linked coffee quality to its different varieties. This is of interest because the identification of coffee varieties should help coffee trading and consumption. Laser-induced breakdown spectroscopy (LIBS) combined with chemometric methods was used to identify coffee varieties. Wavelet transform (WT) was used to reduce LIBS spectra noise. Partial least squares-discriminant analysis (PLS-DA), radial basis function neural network (RBFNN), and support vector machine (SVM) were used to build classification models. Loadings of principal component analysis (PCA) were used to select the spectral variables contributing most to the identification of coffee varieties. Twenty wavelength variables corresponding to C I, Mg I, Mg II, Al II, CN, H, Ca II, Fe I, K I, Na I, N I, and O I were selected. PLS-DA, RBFNN, and SVM models on selected wavelength variables showed acceptable results. SVM and RBFNN models performed better with a classification accuracy of over 80% in the prediction set, for both full spectra and the selected variables. The overall results indicated that it was feasible to use LIBS and chemometric methods to identify coffee varieties. For further studies, more samples are needed to produce robust classification models, research should be conducted on which methods to use to select spectral peaks that correspond to the elements contributing most to identification, and the methods for acquiring stable spectra should also be studied. PMID:29301228

  4. Laser-Induced Breakdown Spectroscopy Coupled with Multivariate Chemometrics for Variety Discrimination of Soil

    Science.gov (United States)

    Yu, Ke-Qiang; Zhao, Yan-Ru; Liu, Fei; He, Yong

    2016-06-01

    The aim of this work was to analyze the variety of soil by laser-induced breakdown spectroscopy (LIBS) coupled with chemometrics methods. 6 certified reference materials (CRMs) of soil samples were selected and their LIBS spectra were captured. Characteristic emission lines of main elements were identified based on the LIBS curves and corresponding contents. From the identified emission lines, LIBS spectra in 7 lines with high signal-to-noise ratio (SNR) were chosen for further analysis. Principal component analysis (PCA) was carried out using the LIBS spectra at 7 selected lines and an obvious cluster of 6 soils was observed. Soft independent modeling of class analogy (SIMCA) and least-squares support vector machine (LS-SVM) were introduced to establish discriminant models for classifying the 6 types of soils, and they offered the correct discrimination rates of 90% and 100%, respectively. Receiver operating characteristic (ROC) curve was used to evaluate the performance of models and the results demonstrated that the LS-SVM model was promising. Lastly, 8 types of soils from different places were gathered to conduct the same experiments for verifying the selected 7 emission lines and LS-SVM model. The research revealed that LIBS technology coupled with chemometrics could conduct the variety discrimination of soil.

  5. Laser-Induced Breakdown Spectroscopy Coupled with Multivariate Chemometrics for Variety Discrimination of Soil

    Science.gov (United States)

    Yu, Ke-Qiang; Zhao, Yan-Ru; Liu, Fei; He, Yong

    2016-01-01

    The aim of this work was to analyze the variety of soil by laser-induced breakdown spectroscopy (LIBS) coupled with chemometrics methods. 6 certified reference materials (CRMs) of soil samples were selected and their LIBS spectra were captured. Characteristic emission lines of main elements were identified based on the LIBS curves and corresponding contents. From the identified emission lines, LIBS spectra in 7 lines with high signal-to-noise ratio (SNR) were chosen for further analysis. Principal component analysis (PCA) was carried out using the LIBS spectra at 7 selected lines and an obvious cluster of 6 soils was observed. Soft independent modeling of class analogy (SIMCA) and least-squares support vector machine (LS-SVM) were introduced to establish discriminant models for classifying the 6 types of soils, and they offered the correct discrimination rates of 90% and 100%, respectively. Receiver operating characteristic (ROC) curve was used to evaluate the performance of models and the results demonstrated that the LS-SVM model was promising. Lastly, 8 types of soils from different places were gathered to conduct the same experiments for verifying the selected 7 emission lines and LS-SVM model. The research revealed that LIBS technology coupled with chemometrics could conduct the variety discrimination of soil. PMID:27279284

  6. Identification of Coffee Varieties Using Laser-Induced Breakdown Spectroscopy and Chemometrics.

    Science.gov (United States)

    Zhang, Chu; Shen, Tingting; Liu, Fei; He, Yong

    2017-12-31

    We linked coffee quality to its different varieties. This is of interest because the identification of coffee varieties should help coffee trading and consumption. Laser-induced breakdown spectroscopy (LIBS) combined with chemometric methods was used to identify coffee varieties. Wavelet transform (WT) was used to reduce LIBS spectra noise. Partial least squares-discriminant analysis (PLS-DA), radial basis function neural network (RBFNN), and support vector machine (SVM) were used to build classification models. Loadings of principal component analysis (PCA) were used to select the spectral variables contributing most to the identification of coffee varieties. Twenty wavelength variables corresponding to C I, Mg I, Mg II, Al II, CN, H, Ca II, Fe I, K I, Na I, N I, and O I were selected. PLS-DA, RBFNN, and SVM models on selected wavelength variables showed acceptable results. SVM and RBFNN models performed better with a classification accuracy of over 80% in the prediction set, for both full spectra and the selected variables. The overall results indicated that it was feasible to use LIBS and chemometric methods to identify coffee varieties. For further studies, more samples are needed to produce robust classification models, research should be conducted on which methods to use to select spectral peaks that correspond to the elements contributing most to identification, and the methods for acquiring stable spectra should also be studied.

  7. Discrimination of Transgenic Rice containing the Cry1Ab Protein using Terahertz Spectroscopy and Chemometrics

    Science.gov (United States)

    Xu, Wendao; Xie, Lijuan; Ye, Zunzhong; Gao, Weilu; Yao, Yang; Chen, Min; Qin, Jianyuan; Ying, Yibin

    2015-01-01

    Spectroscopic techniques combined with chemometrics methods have proven to be effective tools for the discrimination of objects with similar properties. In this work, terahertz time-domain spectroscopy (THz-TDS) combined with discriminate analysis (DA) and principal component analysis (PCA) with derivative pretreatments was performed to differentiate transgenic rice (Hua Hui 1, containing the Cry1Ab protein) from its parent (Ming Hui 63). Both rice samples and the Cry1Ab protein were ground and pressed into pellets for terahertz (THz) measurements. The resulting time-domain spectra were transformed into frequency-domain spectra, and then, the transmittances of the rice and Cry1Ab protein were calculated. By applying the first derivative of the THz spectra in conjunction with the DA model, the discrimination of transgenic from non-transgenic rice was possible with accuracies up to 89.4% and 85.0% for the calibration set and validation set, respectively. The results indicated that THz spectroscopic techniques and chemometrics methods could be new feasible ways to differentiate transgenic rice. PMID:26154950

  8. Combining spectroscopic techniques and chemometrics for the interpretation of lichen biomonitoring of air pollution.

    Science.gov (United States)

    Malaspina, P; Casale, M; Malegori, C; Hooshyari, M; Di Carro, M; Magi, E; Giordani, P

    2018-05-01

    A screening evaluation of lichen thalli, based on spectroscopic techniques coupled with chemometrics, is proposed as fast, simple and "green" method for the biomonitoring of air pollution. For two consecutive years, lichen thalli of Pseudevernia furfuracea were exposed for three months in selected sites of Liguria (NW-Italy) according to different levels and types of air pollution. At the end of the exposure period, transplanted thalli were analyzed by a set of monitoring techniques, including Front-Face Fluorescence Spectroscopy (FFFS), Near Infrared Spectroscopy (NIRS) and Plant Efficiency Analyser (PEA). Data were compared with values of air pollutants recorded during the exposure period by the Regional Agency for Environmental Protection, in order to relate lichen physiological indicators with the effects of atmospheric concentrations. A chemometric evaluation of the analytical signals, including principal component analysis (PCA) and quadratic discriminant analysis (QDA), was performed; the mean prediction rate of the discriminant models calculated on the FFFS emission spectra ranged from 70 to 75% on the external test sets. Front-face fluorescence spectroscopy proved to be a promising technique for the determination of level and type of pollutants in lichen thalli. Copyright © 2018 Elsevier Ltd. All rights reserved.

  9. Spectrophotometric and thermodynamic study on the dimerization equilibrium of ionic dyes in water by chemometrics method

    Science.gov (United States)

    Niazi, Ali; Yazdanipour, Ateesa; Ghasemi, Jahanbakhsh; Kubista, Mikael

    2006-09-01

    The monomer-dimer equilibrium and thermodynamic of several ionic dyes (Neutral Red, Nile Blue A, Safranine T and Thionine) has been investigated by means of spectrophotometric and chemometrics methods. The dimerization constants of these ionic dyes have been determined by studying the dependence of their absorption spectra on the temperature in the range 20-75 °C at concentrations of Neutral Red (1.73 × 10 -5 M), Nile Blue A (3.94 × 10 -5 M), Safranine (6.59 × 10 -5 M) and Thionine (6.60 × 10 -5 M). The monomer-dimer equilibrium of these dyes has been determined by chemometrics refinement of the absorption spectra obtained by thermometric titrations performed. The processing of the data carried out for quantitative analysis of undefined mixtures, based on simultaneous resolution of the overlapping bands in the whole set of absorption spectra. The enthalpy and entropy of the dimerization reactions were determined from the dependence of the equilibrium constants to the temperature (van't Hoff equation).

  10. Non-targeted detection of milk powder adulteration using Raman spectroscopy and chemometrics: melamine case study.

    Science.gov (United States)

    Karunathilaka, Sanjeewa R; Farris, Samantha; Mossoba, Magdi M; Moore, Jeffrey C; Yakes, Betsy Jean

    2017-02-01

    Raman spectroscopy in combination with chemometrics was explored as a rapid, non-targeted screening method for the detection of milk powder (MP) adulteration using melamine as an example contaminant. Raman spectroscopy and an unsupervised pattern-recognition method, principal component analysis (PCA), allowed for the differentiation of authentic MPs from adulterated ones at concentrations > 1.0% for dry-blended (DB) samples and > 0.30% for wet-blended (WB) ones. Soft independent modelling of class analogy (SIMCA), a supervised pattern-recognition method, was also used to classify test samples as adulterated or authentic. Combined statistics at a 97% confidence level from the SIMCA models correctly classified adulteration of MP with melamine at concentrations ≥ 0.5% for DB samples and ≥ 0.30% for WB ones, while no false-positives from authentic MPs were found when the spectra in the 600-700 cm - 1 range were pre-processed using standard normal variate (SNV) followed by a gap-segment derivatisation. The combined technique of Raman spectroscopy and chemometrics proved to be a useful tool for the rapid and cost-efficient non-targeted detection of adulteration in MP at per cent spiking levels.

  11. Determination of geographical origin and icariin content of Herba Epimedii using near infrared spectroscopy and chemometrics.

    Science.gov (United States)

    Yang, Yue; Wu, Yongjiang; Li, Weili; Liu, Xuesong; Zheng, Jiyu; Zhang, Wentao; Chen, Yong

    2018-02-15

    Near infrared (NIR) spectroscopy coupled with chemometrics was used to discriminate the geographical origin of Herba Epimedii in this work. Four different classification models, namely discriminant analysis (DA), back propagation neural network (BPNN), K-nearest neighbor (KNN), and support vector machine (SVM), were constructed, and their performances in terms of recognition accuracy were compared. The results indicated that the SVM model was superior over the other models in the geographical origin identification of Herba Epimedii. The recognition rates of the optimum SVM model were up to 100% for the calibration set and 94.44% for the prediction set, respectively. In addition, the feasibility of NIR spectroscopy with the CARS-PLSR calibration model in prediction of icariin content of Herba Epimedii was also investigated. The determination coefficient (R P 2 ) and root-mean-square error (RMSEP) for prediction set were 0.9269 and 0.0480, respectively. It can be concluded that the NIR spectroscopy technique in combination with chemometrics has great potential in determination of geographical origin and icariin content of Herba Epimedii. This study can provide a valuable reference for rapid quality control of food products. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Estimation of the late postmortem interval using FTIR spectroscopy and chemometrics in human skeletal remains.

    Science.gov (United States)

    Wang, Qi; Zhang, Yinming; Lin, Hancheng; Zha, Shuai; Fang, Ruoxi; Wei, Xin; Fan, Shuanliang; Wang, Zhenyuan

    2017-12-01

    Due to a lack of reliable and accurate methods, determining the postmortem interval (PMI) of human skeletal remains is one of the most important and challenging tasks in forensic medicine. In this paper, we studied the changes to bone chemistry with increasing PMI in two different experimental conditions using Fourier transform infrared (FTIR) spectroscopy in conjunction with chemometrics methods Paired bone samples collected from 56 human corpses were buried (placed in soil) and unburied (exposed to the air) for intervals between 76 and 552 days. The results of principle component analysis (PCA) showed the chemical differences of these two cases had a significant influence on the rate of decomposition of the remains. Meanwhile, satisfactory predictions were performed by the genetic algorithm combined with partial least-squares (GA-PLS) with the root mean square errors of prediction (RMSEP) of 50.93days for buried bones and 71.03days for unburied bones. Moreover, the amide I region of proteins and the area around 1390cm -1 , which is associated with fatty acids, were identified with regular changes by GA-PLS and played an important role in estimating PMI. This study illustrates the feasibility of utilizing FTIR spectroscopy and chemometrics as an attractive alternative for estimating PMI of human remains and the great potential of these techniques in real forensic cases with natural conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Fingerprinting profile of polysaccharides from Lycium barbarum using multiplex approaches and chemometrics.

    Science.gov (United States)

    Liu, Wei; Xu, Jinnan; Zhu, Rui; Zhu, Yiqing; Zhao, Yang; Chen, Pei; Pan, Chun; Yao, Wenbing; Gao, Xiangdong

    2015-07-01

    Techniques including ultraviolet-visible spectra (UV), high performance size-exclusion chromatography (HPSEC), Fourier-transform infrared spectroscopy (FT-IR) and pre-column derivatization high-performance liquid chromatography (PCD-HPLC) were used in the fingerprinting analysis of Lycium barbarum polysaccharides (LBPs) from different locations and varieties. Multiple fingerprinting profiles were used to evaluate the similarity and classification of different LBPs with the help of chemometrics. The results indicated that sixteen batches of LBPs had good consistency, and fingerprinting techniques were simple and robust for quality control of LBPs as well as related products. In addition, fingerprinting techniques combined with chemometrics could also be used to identify different cultivation locations of LBPs samples. Finally, four monosaccharides (galacturonic acid, glucose, galactose and arabinose) and the absorptions of stretching vibration of ester carbonyl groups as well as NH variable angle vibration of -CONH- could be selected as herbal markers to distinguish different samples. Copyright © 2015 Elsevier B.V. All rights reserved.

  14. Determination of geographical origin and icariin content of Herba Epimedii using near infrared spectroscopy and chemometrics

    Science.gov (United States)

    Yang, Yue; Wu, Yongjiang; Li, Weili; Liu, Xuesong; Zheng, Jiyu; Zhang, Wentao; Chen, Yong

    2018-02-01

    Near infrared (NIR) spectroscopy coupled with chemometrics was used to discriminate the geographical origin of Herba Epimedii in this work. Four different classification models, namely discriminant analysis (DA), back propagation neural network (BPNN), K-nearest neighbor (KNN), and support vector machine (SVM), were constructed, and their performances in terms of recognition accuracy were compared. The results indicated that the SVM model was superior over the other models in the geographical origin identification of Herba Epimedii. The recognition rates of the optimum SVM model were up to 100% for the calibration set and 94.44% for the prediction set, respectively. In addition, the feasibility of NIR spectroscopy with the CARS-PLSR calibration model in prediction of icariin content of Herba Epimedii was also investigated. The determination coefficient (RP2) and root-mean-square error (RMSEP) for prediction set were 0.9269 and 0.0480, respectively. It can be concluded that the NIR spectroscopy technique in combination with chemometrics has great potential in determination of geographical origin and icariin content of Herba Epimedii. This study can provide a valuable reference for rapid quality control of food products.

  15. Application of terahertz spectroscopy imaging for discrimination of transgenic rice seeds with chemometrics.

    Science.gov (United States)

    Liu, Wei; Liu, Changhong; Hu, Xiaohua; Yang, Jianbo; Zheng, Lei

    2016-11-01

    Discrimination of genetically modified organisms is increasingly demanded by legislation and consumers worldwide. The feasibility of a non-destructive discrimination of transgenic rice seeds from its non-transgenic counterparts was examined by terahertz spectroscopy imaging system combined with chemometrics. Principal component analysis (PCA), least squares support vector machines (LS-SVM), PCA-back propagation neural network (PCA-BPNN), and random forest (RF) models with the first and second derivative and standard normal variate transformation (SNV) pre-treatments were applied to classify rice seeds based on genotype. The results demonstrated that differences between non-transgenic and transgenic rice seeds did exist, and an excellent classification (accuracy was 96.67% in the prediction set) could be achieved using the RF model combined with the first derivative pre-treatment. The results indicated that THz spectroscopy imaging together with chemometrics would be a promising technique to identify transgenic rice seeds with high efficiency and without any sample preparation. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Simultaneous quantitative determination of paracetamol and tramadol in tablet formulation using UV spectrophotometry and chemometric methods

    Science.gov (United States)

    Glavanović, Siniša; Glavanović, Marija; Tomišić, Vladislav

    2016-03-01

    The UV spectrophotometric methods for simultaneous quantitative determination of paracetamol and tramadol in paracetamol-tramadol tablets were developed. The spectrophotometric data obtained were processed by means of partial least squares (PLS) and genetic algorithm coupled with PLS (GA-PLS) methods in order to determine the content of active substances in the tablets. The results gained by chemometric processing of the spectroscopic data were statistically compared with those obtained by means of validated ultra-high performance liquid chromatographic (UHPLC) method. The accuracy and precision of data obtained by the developed chemometric models were verified by analysing the synthetic mixture of drugs, and by calculating recovery as well as relative standard error (RSE). A statistically good agreement was found between the amounts of paracetamol determined using PLS and GA-PLS algorithms, and that obtained by UHPLC analysis, whereas for tramadol GA-PLS results were proven to be more reliable compared to those of PLS. The simplest and the most accurate and precise models were constructed by using the PLS method for paracetamol (mean recovery 99.5%, RSE 0.89%) and the GA-PLS method for tramadol (mean recovery 99.4%, RSE 1.69%).

  17. Chemometric and Statistical Analyses of ToF-SIMS Spectra of Increasingly Complex Biological Samples

    Energy Technology Data Exchange (ETDEWEB)

    Berman, E S; Wu, L; Fortson, S L; Nelson, D O; Kulp, K S; Wu, K J

    2007-10-24

    Characterizing and classifying molecular variation within biological samples is critical for determining fundamental mechanisms of biological processes that will lead to new insights including improved disease understanding. Towards these ends, time-of-flight secondary ion mass spectrometry (ToF-SIMS) was used to examine increasingly complex samples of biological relevance, including monosaccharide isomers, pure proteins, complex protein mixtures, and mouse embryo tissues. The complex mass spectral data sets produced were analyzed using five common statistical and chemometric multivariate analysis techniques: principal component analysis (PCA), linear discriminant analysis (LDA), partial least squares discriminant analysis (PLSDA), soft independent modeling of class analogy (SIMCA), and decision tree analysis by recursive partitioning. PCA was found to be a valuable first step in multivariate analysis, providing insight both into the relative groupings of samples and into the molecular basis for those groupings. For the monosaccharides, pure proteins and protein mixture samples, all of LDA, PLSDA, and SIMCA were found to produce excellent classification given a sufficient number of compound variables calculated. For the mouse embryo tissues, however, SIMCA did not produce as accurate a classification. The decision tree analysis was found to be the least successful for all the data sets, providing neither as accurate a classification nor chemical insight for any of the tested samples. Based on these results we conclude that as the complexity of the sample increases, so must the sophistication of the multivariate technique used to classify the samples. PCA is a preferred first step for understanding ToF-SIMS data that can be followed by either LDA or PLSDA for effective classification analysis. This study demonstrates the strength of ToF-SIMS combined with multivariate statistical and chemometric techniques to classify increasingly complex biological samples

  18. Authentication of animal origin of heparin and low molecular weight heparin including ovine, porcine and bovine species using 1D NMR spectroscopy and chemometric tools.

    Science.gov (United States)

    Monakhova, Yulia B; Diehl, Bernd W K; Fareed, Jawed

    2018-02-05

    High resolution (600MHz) nuclear magnetic resonance (NMR) spectroscopy is used to distinguish heparin and low-molecular weight heparins (LMWHs) produced from porcine, bovine and ovine mucosal tissues as well as their blends. For multivariate analysis several statistical methods such as principal component analysis (PCA), factor discriminant analysis (FDA), partial least squares - discriminant analysis (PLS-DA), linear discriminant analysis (LDA) were utilized for the modeling of NMR data of more than 100 authentic samples. Heparin and LMWH samples from the independent test set (n=15) were 100% correctly classified according to its animal origin. Moreover, by using 1 H NMR coupled with chemometrics and several batches of bovine heparins from two producers were differentiated. Thus, NMR spectroscopy combined with chemometrics is an efficient tool for simultaneous identification of animal origin and process based manufacturing difference in heparin products. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Identification of anisodamine tablets by Raman and near-infrared spectroscopy with chemometrics.

    Science.gov (United States)

    Li, Lian; Zang, Hengchang; Li, Jun; Chen, Dejun; Li, Tao; Wang, Fengshan

    2014-06-05

    Vibrational spectroscopy including Raman and near-infrared (NIR) spectroscopy has become an attractive tool for pharmaceutical analysis. In this study, effective calibration models for the identification of anisodamine tablet and its counterfeit and the distinguishment of manufacturing plants, based on Raman and NIR spectroscopy, were built, respectively. Anisodamine counterfeit tablets were identified by Raman spectroscopy with correlation coefficient method, and the results showed that the predictive accuracy was 100%. The genuine anisodamine tablets from 5 different manufacturing plants were distinguished by NIR spectroscopy using partial least squares discriminant analysis (PLS-DA) models based on interval principal component analysis (iPCA) method. And the results showed the recognition rate and rejection rate were 100% respectively. In conclusion, Raman spectroscopy and NIR spectroscopy combined with chemometrics are feasible and potential tools for rapid pharmaceutical tablet discrimination. Copyright © 2014 Elsevier B.V. All rights reserved.

  20. FTIR characterization of Mexican honey and its adulteration with sugar syrups by using chemometric methods

    International Nuclear Information System (INIS)

    Rios-Corripio, M A; Rojas-Lopez, M; Delgado-Macuil, R; Rios-Leal, E

    2011-01-01

    A chemometric analysis of adulteration of Mexican honey by sugar syrups such as corn syrup and cane sugar syrup was realized. Fourier transform infrared spectroscopy (FTIR) was used to measure the absorption of a group of bee honey samples from central region of Mexico. Principal component analysis (PCA) was used to process FTIR spectra to determine the adulteration of bee honey. In addition to that, the content of individual sugars from honey samples: glucose, fructose, sucrose and monosaccharides was determined by using PLS-FTIR analysis validated by HPLC measurements. This analytical methodology which is based in infrared spectroscopy and chemometry can be an alternative technique to characterize and also to determine the purity and authenticity of nutritional products as bee honey and other natural products.

  1. Combining Electronic Tongue Array and Chemometrics for Discriminating the Specific Geographical Origins of Green Tea

    Directory of Open Access Journals (Sweden)

    Lu Xu

    2013-01-01

    Full Text Available The feasibility of electronic tongue and multivariate analysis was investigated for discriminating the specific geographical origins of a Chinese green tea with Protected Designation of Origin (PDO. 155 Longjing tea samples from three subareas were collected and analyzed by an electronic tongue array of 7 sensors. To remove the influence of abnormal measurements and samples, robust principal component analysis (ROBPCA was used to detect outliers in each class. Partial least squares discriminant analysis (PLSDA was then used to develop a classification model. The prediction sensitivity/specificity of PLSDA was 1.000/1.000, 1.000/0.967, and 0.950/1.000 for longjing from Xihu, Qiantang, and Yuezhou, respectively. Electronic tongue and chemometrics can provide a rapid and reliable tool for discriminating the specific producing areas of Longjing.

  2. Combining Electronic Tongue Array and Chemometrics for Discriminating the Specific Geographical Origins of Green Tea

    Science.gov (United States)

    Xu, Lu; Yan, Si-Min; Ye, Zi-Hong; Fu, Xian-Shu; Yu, Xiao-Ping

    2013-01-01

    The feasibility of electronic tongue and multivariate analysis was investigated for discriminating the specific geographical origins of a Chinese green tea with Protected Designation of Origin (PDO). 155 Longjing tea samples from three subareas were collected and analyzed by an electronic tongue array of 7 sensors. To remove the influence of abnormal measurements and samples, robust principal component analysis (ROBPCA) was used to detect outliers in each class. Partial least squares discriminant analysis (PLSDA) was then used to develop a classification model. The prediction sensitivity/specificity of PLSDA was 1.000/1.000, 1.000/0.967, and 0.950/1.000 for longjing from Xihu, Qiantang, and Yuezhou, respectively. Electronic tongue and chemometrics can provide a rapid and reliable tool for discriminating the specific producing areas of Longjing. PMID:23956928

  3. Detection of irradiated beef by nuclear magnetic resonance lipid profiling combined with chemometric techniques.

    Science.gov (United States)

    Zanardi, Emanuela; Caligiani, Augusta; Padovani, Enrico; Mariani, Mario; Ghidini, Sergio; Palla, Gerardo; Ianieri, Adriana

    2013-02-01

    The combination of (1)H NMR lipid profiling with multivariate analysis was applied to differentiate irradiated and non-irradiated beef. Two pattern recognition chemometric procedures, stepwise linear discriminant analysis (sLDA) and artificial neural networks (ANNs), provided a successful discrimination between the groups investigated. sLDA allowed the classification of 100% of the samples into irradiated or non-irradiated beef groups; the same result was obtained by ANNs using the 1 kGy irradiation dose as discriminant value suggested by the network. Furthermore, sLDA allowed the classification of 81.9% of the beef samples according to the irradiation dose (0, 2.5, 4.5 and 8 kGy). (1)H NMR lipid profiling, coupled with multivariate analysis may be considered a suitable and promising screening tool for the rapid detection of irradiated meat in official control of food. Copyright © 2012 Elsevier Ltd. All rights reserved.

  4. Online Variety Discrimination of Rice Seeds Using Multispectral Imaging and Chemometric Methods

    Science.gov (United States)

    Liu, W.; Liu, Ch.; Ma, F.; Lu, X.; Yang, J.; Zheng, L.

    2016-01-01

    Variety identification plays an important role in ensuring the quality and quantity of yield in rice production. The feasibility of a rapid and nondestructive determination of varieties of rice seeds was examined by using a multispectral imaging system combined with chemometric data analysis. Methods of the partial least squares discriminant analysis (PLSDA), principal component analysis-back propagation neural network (PCA-BPNN), and least squares-support vector machines (LS-SVM) were applied to classify varieties of rice seeds. The results demonstrate that clear differences among varieties of rice seeds could be easily visualized using the multispectral imaging technique and an excellent classification could be achieved combining data of the spectral and morphological features. The classification accuracy was up to 94% in a validation set with the LS-SVM model, which was better than the PLSDA (62%) and PCA-BPNN (84%) models.

  5. Synergistic effect of the simultaneous chemometric analysis of ¹H NMR spectroscopic and stable isotope (SNIF-NMR, ¹⁸O, ¹³C) data: application to wine analysis.

    Science.gov (United States)

    Monakhova, Yulia B; Godelmann, Rolf; Hermann, Armin; Kuballa, Thomas; Cannet, Claire; Schäfer, Hartmut; Spraul, Manfred; Rutledge, Douglas N

    2014-06-23

    It is known that (1)H NMR spectroscopy represents a good tool for predicting the grape variety, the geographical origin, and the year of vintage of wine. In the present study we have shown that classification models can be improved when (1)H NMR profiles are fused with stable isotope (SNIF-NMR, (18)O, (13)C) data. Variable selection based on clustering of latent variables was performed on (1)H NMR data. Afterwards, the combined data of 718 wine samples from Germany were analyzed using linear discriminant analysis (LDA), partial least squares-discriminant analysis (PLS-DA), factorial discriminant analysis (FDA) and independent components analysis (ICA). Moreover, several specialized multiblock methods (common components and specific weights analysis (ComDim), consensus PCA and consensus PLS-DA) were applied to the data. The best improvement in comparison with (1)H NMR data was obtained for prediction of the geographical origin (up to 100% for the fused data, whereas stable isotope data resulted only in 60-70% correct prediction and (1)H NMR data alone in 82-89% respectively). Certain enhancement was obtained also for the year of vintage (from 88 to 97% for (1)H NMR to 99% for the fused data), whereas in case of grape varieties improved models were not obtained. The combination of (1)H NMR data with stable isotope data improves efficiency of classification models for geographical origin and vintage of wine and can be potentially used for other food products as well. Copyright © 2014 Elsevier B.V. All rights reserved.

  6. Classification of Tropical River Using Chemometrics Technique: Case Study in Pahang River, Malaysia

    International Nuclear Information System (INIS)

    Mohd Khairul Amri Kamarudin; Mohd Ekhwan Toriman; Nur Hishaam Sulaiman

    2015-01-01

    River classification is very important to know the river characteristic in study areas, where this database can help to understand the behaviour of the river. This article discusses about river classification using Chemometrics techniques in mainstream of Pahang River. Based on river survey, GIS and Remote Sensing database, the chemometric analysis techniques have been used to identify the cluster on the Pahang River using Hierarchical Agglomerative Cluster Analysis (HACA). Calibration and validation process using Discriminant Analysis (DA) has been used to confirm the HACA result. Principal Component Analysis (PCA) study to see the strong coefficient where the Pahang River has been classed. The results indicated the main of Pahang River has been classed to three main clusters as upstream, middle stream and downstream. Base on DA analysis, the calibration and validation model shows 100 % convinced. While the PCA indicates there are three variables that have a significant correlation, domination slope with R 2 0.796, L/D ratio with R 2 -0868 and sinuosity with R 2 0.557. Map of the river classification with moving class also was produced. Where the green colour considered in valley erosion zone, yellow in a low terrace of land near the channels and red colour class in flood plain and valley deposition zone. From this result, the basic information can be produced to understand the characteristics of the main Pahang River. This result is important to local authorities to make decisions according to the cluster or guidelines for future study in Pahang River, Malaysia specifically and for Tropical River generally. The research findings are important to local authorities by providing basic data as a guidelines to the integrated river management at Pahang River, and Tropical River in general. (author)

  7. Chemometric approach to evaluate heavy metals’ content in Daucus Carota from different localities in Serbia

    Directory of Open Access Journals (Sweden)

    Mitic Violeta D.

    2015-01-01

    Full Text Available The aim of this study was to evaluate heavy metal content in carrots (Daucus carota from the different localities in Serbia and assess by the cluster analysis (CA and principal components analysis (PCA the heavy metal contamination of carrots from these areas. Carrot was collected at 13 locations in five districts. Chemometric methods (CA and PCA were applied to classify localities according to heavy metal content in carrots. CA separated localities into two statistical significant clusters. PCA permitted the reduction of 12 variables to four principal components explaining 79.94% of the total variance. The first most important principal component was strongly associated with the value of Cu, Sb, Pb and Tl. This study revealed that CA and PCA appear useful tools for differentiation of localities in different districts using the profile of heavy metal in carrot samples. [Projekat Ministarstva nauke Republike Srbije, br. 172051

  8. Grouping of residual solvents present in pharmaceuticals using experimental planning and chemometric methods.

    Science.gov (United States)

    Grodowska, Katarzyna; Parczewski, Andrzej

    2013-01-01

    The main effects of six experimental factors on the efficiency of HS (headspace) extraction in headspace gas chromatography--flame ionization detector (HS-GC-FID) determination of twenty organic solvents routinely used in production of pharmaceuticals were obtained on the basis of the results of experiments carried out according to the Plackett-Burman factorial design. The effects were used as a basis for grouping the solvents into five groups, the solvents belonging to a group responded similarly to changes of HS conditions. To this end, visualization approaches were used as well as chemometric methods: cluster analysis (CA) and principal component analysis (PCA). Moreover, the most important HS experimental factors were selected for further optimization of the HS-GC determination procedure.

  9. Chemometric classification of casework arson samples based on gasoline content.

    Science.gov (United States)

    Sinkov, Nikolai A; Sandercock, P Mark L; Harynuk, James J

    2014-02-01

    Detection and identification of ignitable liquids (ILs) in arson debris is a critical part of arson investigations. The challenge of this task is due to the complex and unpredictable chemical nature of arson debris, which also contains pyrolysis products from the fire. ILs, most commonly gasoline, are complex chemical mixtures containing hundreds of compounds that will be consumed or otherwise weathered by the fire to varying extents depending on factors such as temperature, air flow, the surface on which IL was placed, etc. While methods such as ASTM E-1618 are effective, data interpretation can be a costly bottleneck in the analytical process for some laboratories. In this study, we address this issue through the application of chemometric tools. Prior to the application of chemometric tools such as PLS-DA and SIMCA, issues of chromatographic alignment and variable selection need to be addressed. Here we use an alignment strategy based on a ladder consisting of perdeuterated n-alkanes. Variable selection and model optimization was automated using a hybrid backward elimination (BE) and forward selection (FS) approach guided by the cluster resolution (CR) metric. In this work, we demonstrate the automated construction, optimization, and application of chemometric tools to casework arson data. The resulting PLS-DA and SIMCA classification models, trained with 165 training set samples, have provided classification of 55 validation set samples based on gasoline content with 100% specificity and sensitivity. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  10. Application of SWIR hyperspectral imaging and chemometrics for identification of aflatoxin B1 contaminated maize kernels

    Science.gov (United States)

    Kimuli, Daniel; Wang, Wei; Wang, Wei; Jiang, Hongzhe; Zhao, Xin; Chu, Xuan

    2018-03-01

    A short-wave infrared (SWIR) hyperspectral imaging system (1000-2500 nm) combined with chemometric data analysis was used to detect aflatoxin B1 (AFB1) on surfaces of 600 kernels of four yellow maize varieties from different States of the USA (Georgia, Illinois, Indiana and Nebraska). For each variety, four AFB1 solutions (10, 20, 100 and 500 ppb) were artificially deposited on kernels and a control group was generated from kernels treated with methanol solution. Principal component analysis (PCA), partial least squares discriminant analysis (PLSDA) and factorial discriminant analysis (FDA) were applied to explore and classify maize kernels according to AFB1 contamination. PCA results revealed partial separation of control kernels from AFB1 contaminated kernels for each variety while no pattern of separation was observed among pooled samples. A combination of standard normal variate and first derivative pre-treatments produced the best PLSDA classification model with accuracy of 100% and 96% in calibration and validation, respectively, from Illinois variety. The best AFB1 classification results came from FDA on raw spectra with accuracy of 100% in calibration and validation for Illinois and Nebraska varieties. However, for both PLSDA and FDA models, poor AFB1 classification results were obtained for pooled samples relative to individual varieties. SWIR spectra combined with chemometrics and spectra pre-treatments showed the possibility of detecting maize kernels of different varieties coated with AFB1. The study further suggests that increase of maize kernel constituents like water, protein, starch and lipid in a pooled sample may have influence on detection accuracy of AFB1 contamination.

  11. Characterization and Classification of Crude Oils Using a Combination of Spectroscopy and Chemometrics

    NARCIS (Netherlands)

    Peinder, Peter de

    2009-01-01

    Research has been carried out to the utility of chemometric models to predict long residue (LR) and short residue (SR) properties of a crude oil directly from its absorption or magnetic resonance spectrum. Such a combined spectroscopic-chemometric approach might offer a fast alternative for the

  12. Usefulness of near infrared spectroscopy and chemometrics in screening of the quality of dessert wine Prošek

    Directory of Open Access Journals (Sweden)

    T. Lovrić

    2011-01-01

    Full Text Available NIRS has been applied for the analysis of dessert wine Prošek produced from dried grapes of Pošip and Plavac mali cv. in a semi-scaled fermentation. It is a fast and non-destructive analytical method that in association with chemometrics is becoming more frequently used technique. NIR spectra were measured and the relative density, alcohol content, dry extract, reducing sugars, pH, total acidity, volatile acidity, ash, free sulphur dioxide and total sulphur dioxide were determined. The range of NIRS used in this paper was 904–1699 nm (i.e. 11062–5886 cm−1 because in this range vibrations of C–H, O–H, S–H and N–H bonds can mainly be observed. Using the basic principles of multivariate analysis, principal component analysis (PCA, was used to reduce the input matrix in order to look for significant relationships between the NIR spectra and the observed characteristics of wine Prošek. Chemometrics applied here resulted in further discrimination between samples. The main features of the spectra are absorption bands at 1580 and 1670 nm, which are related to the first overtone of the C–H stretch. Absorption bands around 908 nm, present the stretches related to the 3rd C–H overtone and 2nd overtone of the O–H stretch of H2O and ethanol. PC1 and PC2, the first two components, gave the highest level of classification (≈95 % based on the grape used for wine production as well as on the added yeast. The potential of NIRS, as a non-destructive method, is screening of basic parameters that are usually determined during the winemaking and ageing of wine. The results of investigations confirm that NIRS combined with chemometric analysis is a promising tool for quality control and for on-line application in the control of the final product, Prošek.

  13. Chemometrics and theoretical approaches for evaluation of matrix effect in laser ablation and ionization of metal samples

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Shudi; Zhang, Bochao [Department of Chemistry, The MOE Key Lab of Spectrochemical Analysis & Instrumentation, College of Chemistry and Chemical Engineering, Xiamen University (China); Hang, Wei, E-mail: weihang@xmu.edu.cn [Department of Chemistry, The MOE Key Lab of Spectrochemical Analysis & Instrumentation, College of Chemistry and Chemical Engineering, Xiamen University (China); State Key Laboratory of Marine Environmental Science, Xiamen University (China); Huang, Benli [Department of Chemistry, The MOE Key Lab of Spectrochemical Analysis & Instrumentation, College of Chemistry and Chemical Engineering, Xiamen University (China)

    2015-05-01

    Matrix effect is one of the shortcomings of direct solid analysis which makes the quantitative analysis a great challenge. All of the physical properties of solid and laser parameters could make contributions to the matrix effect. For better understanding and controlling laser ablation process, it is of great importance to investigate how and to what extent these factors would affect matrix effect, through simulation and chemometrics works. In this study, twenty-three solid standards of six types of metal matrices were analyzed, including aluminum, copper, iron, nickel, tungsten and zinc. The influence of laser pulse duration was investigated by applying nanosecond (ns) and femtosecond (fs) lasers to a buffer-gas-assisted ionization source coupled with an orthogonal time-of-flight mass spectrometer. After relative sensitivity coefficients (RSCs) of each element in different matrices were calculated, they were combined with the physical property values of the matrices to form a dataset which was analyzed by the chemometrics tool of orthogonal partial least-squares (OPLSs). The S-plot result reveals that thermal properties of solid play vital roles in the matrix effect induced by ns-laser ablation, while fs-laser could significantly reduce the thermal effect. Additionally, a theoretical model was figured out to simulate the RSCs by combining the laser–solid interaction process and plasma expansion process. The model prediction shows a relatively close agreement with experimental result, revealing that the model could reasonably explain the process of matrix effect. - Highlights: • Matrix effect is one of the obstacles in direct solid analysis. • RSCs combined with physical properties were analyzed by chemometrics tool. • S-plot reveals thermal property playing vital role in matrix effect in ns-laser ablation. • Theoretical model was built to simulate RSCs. • Model prediction of RSCs shows a relatively close agreement with experimental result.

  14. Chemometric optimization of a low-temperature plasma source design for ambient desorption/ionization mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Albert, Anastasia [University of Muenster, Institute of Inorganic and Analytical Chemistry, Corrensstraße 30, 48149 Muenster (Germany); Engelhard, Carsten, E-mail: engelhard@chemie.uni-siegen.de [University of Siegen, Department of Chemistry and Biology, Adolf-Reichwein-Straße 2, 57076 Siegen (Germany)

    2015-03-01

    Low-temperature plasmas (LTPs) are attractive sources for atomic and molecular mass spectrometry (MS). In the past, the LTP probe, which was first described by Harper et al., was used successfully for direct molecular mass spectrometric analysis with minimal sample pretreatment in a variety of applications. Unfortunately, the desorption/ionization source itself is commercially not available and custom-built LTP set-ups with varying geometry and operational configurations were utilized in the past. In the present study, a rapid chemometrics approach based on systematic experiments and multivariate data analysis was used to optimize the LTP probe geometry and positioning relative to the atmospheric-pressure inlet of a mass spectrometer. Several parameters were studied including the probe geometry, electrode configuration, quartz tube dimensions, probe positioning and operating conditions. It was found that the plasma-to-MS-inlet distance, the plasma-to-sample-plate distance, and the angle between the latter are very important. Additional effects on the analytical performance were found for the outer electrode width, the positioning of the electrodes, the inner diameter of the quartz tube, the quartz wall thickness, and the gas flow. All experiments were performed using additional heating of the sample to enhance thermal desorption and maximize the signal (T = 150 °C). After software-assisted optimization, attractive detection limits were achieved (e.g., 1.8 × 10{sup −7} mol/L for 4-acetamidothiophenol). Moreover, relative standard deviation (RSD) improved from values of up to 30% before optimization to < 15% RSD after the procedure was completed. This chemometrics approach for method optimization is not limited to LTP-MS and considered to be attractive for other plasma-based instrumentation as well. - Highlights: • Plasmas are useful in ambient desorption/ionization mass spectrometry. • Rapid and direct analysis is performed without sample preparation.

  15. 1H nuclear magnetic resonance spectra of chloroform extracts of honey for chemometric determination of its botanical origin.

    Science.gov (United States)

    Schievano, Elisabetta; Peggion, Evaristo; Mammi, Stefano

    2010-01-13

    In this work, we present a new NMR study, coupled with chemometric analysis, on nonvolatile organic honey components. The extraction method is simple and reproducible. The 1H NMR spectra of chloroform extracts acquired with a fast and new pulse sequence were used to characterize and differentiate by chemometric analysis 118 honey samples of four different botanical origins (chestnut, acacia, linden, and polyfloral). The spectra collection, processing, and analysis require only 30 min. The 1H spectrum provides a fingerprint for each honey type, showing many characteristic peaks in all spectral regions. Principal component analysis (PCA) and projection to latent structures by partial least squares-discriminant analysis (PLS-DA) were performed on selected signals of the spectra to discriminate the different botanical types and to identify characteristic metabolites for each honey type. A distinct discrimination among samples was achieved. According to the distance to model criterion, there was no overlap between the four models, which proved to be specific for each honey type. The PLS-DA model obtained has a correlation coefficient R2 of 0.67 and a validation correlation coefficient Q2 of 0.77. The discriminant analysis allowed us to classify correctly 100% of the samples. A classification index can be calculated and used to determine the floral origin of honey as an alternative to the melissopalinology test and possibly to determine the percentage of various botanical species in polyfloral samples. Preliminary data on the identification of marker compounds for each botanical origin are presented.

  16. Application of chemometric methods for assessment and modelling of microbiological quality data concerning coastal bathing water in Greece

    Directory of Open Access Journals (Sweden)

    Agelos Papaioannou

    2014-12-01

    Full Text Available Background. Worldwide, the aim of managing water is to safeguard human health whilst maintaining sustainable aquatic and associated terrestrial, ecosystems. Because human enteric viruses are the most likely pathogens responsible for waterborne diseases from recreational water use, but detection methods are complex and costly for routine monitoring, it is of great interest to determine the quality of coastal bathing water with a minimum cost and maximum safety. Design and methods. This study handles the assessment and modelling of the microbiological quality data of 2149 seawater bathing areas in Greece over 10-year period (1997-2006 by chemometric methods. Results. Cluster analysis results indicated that the studied bathing beaches are classified in accordance with the seasonality in three groups. Factor analysis was applied to investigate possible determining factors in the groups resulted from the cluster analysis, and also two new parameters were created in each group; VF1 includes E. coli, faecal coliforms and total coliforms and VF2 includes faecal streptococci/enterococci. By applying the cluster analysis in each seasonal group, three new groups of coasts were generated, group A (ultraclean, group B (clean and group C (contaminated. Conclusions. The above analysis is confirmed by the application of discriminant analysis, and proves that chemometric methods are useful tools for assessment and modeling microbiological quality data of coastal bathing water on a large scale, and thus could attribute to effective and economical monitoring of the quality of coastal bathing water in a country with a big number of bathing coasts, like Greece.

  17. Metabolomics combined with chemometric tools (PCA, HCA, PLS-DA and SVM) for screening cassava (Manihot esculenta Crantz) roots during postharvest physiological deterioration.

    Science.gov (United States)

    Uarrota, Virgílio Gavicho; Moresco, Rodolfo; Coelho, Bianca; Nunes, Eduardo da Costa; Peruch, Luiz Augusto Martins; Neubert, Enilto de Oliveira; Rocha, Miguel; Maraschin, Marcelo

    2014-10-15

    Cassava roots are an important source of dietary and industrial carbohydrates and suffer markedly from postharvest physiological deterioration (PPD). This paper deals with metabolomics combined with chemometric tools for screening the chemical and enzymatic composition in several genotypes of cassava roots during PPD. Metabolome analyses showed increases in carotenoids, flavonoids, anthocyanins, phenolics, reactive scavenging species, and enzymes (superoxide dismutase family, hydrogen peroxide, and catalase) until 3-5days postharvest. PPD correlated negatively with phenolics and carotenoids and positively with anthocyanins and flavonoids. Chemometric tools such as principal component analysis, partial least squares discriminant analysis, and support vector machines discriminated well cassava samples and enabled a good prediction of samples. Hierarchical clustering analyses grouped samples according to their levels of PPD and chemical compositions. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Differentiating Organically Farmed Rice from Conventional and Green Rice Harvested from an Experimental Field Trial Using Stable Isotopes and Multi-Element Chemometrics.

    Science.gov (United States)

    Yuan, Yuwei; Zhang, Weixing; Zhang, Yongzhi; Liu, Zhi; Shao, Shengzhi; Zhou, Li; Rogers, Karyne M

    2018-03-21

    Chemometric methods using stable isotopes and elemental fingerprinting were used to characterize organically grown rice from green and conventionally grown rice in experimental field trials in China. Carbon, nitrogen, hydrogen, and oxygen stable isotopes as well as 26 other elements were determined. Organic rice was found to be more depleted in 13 C than green or conventionally grown rice because of the uptake of enriched 13 C from carbon dioxide and methane respiring bacteria and more enriched in 15 N because of the volatilization of the nitrogen from the urea and ammonium of the animal manures used to manufacture the organic composts. Chemometrics (principal-component analysis and linear-discriminant analysis) were used to separate the three farming methods and provided a promising scientific tool to authenticate the farming methods of different rice cultivars fertilized with animal manures, green composts, and synthetic fertilizers in China or elsewhere.

  19. A new simplex chemometric approach to identify olive oil blends with potentially high traceability.

    Science.gov (United States)

    Semmar, N; Laroussi-Mezghani, S; Grati-Kamoun, N; Hammami, M; Artaud, J

    2016-10-01

    Olive oil blends (OOBs) are complex matrices combining different cultivars at variable proportions. Although qualitative determinations of OOBs have been subjected to several chemometric works, quantitative evaluations of their contents remain poorly developed because of traceability difficulties concerning co-occurring cultivars. Around this question, we recently published an original simplex approach helping to develop predictive models of the proportions of co-occurring cultivars from chemical profiles of resulting blends (Semmar & Artaud, 2015). Beyond predictive model construction and validation, this paper presents an extension based on prediction errors' analysis to statistically define the blends with the highest predictability among all the possible ones that can be made by mixing cultivars at different proportions. This provides an interesting way to identify a priori labeled commercial products with potentially high traceability taking into account the natural chemical variability of different constitutive cultivars. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Chinese vinegar classification via volatiles using long-optical-path infrared spectroscopy and chemometrics.

    Science.gov (United States)

    Dong, D; Zheng, W; Jiao, L; Lang, Y; Zhao, X

    2016-03-01

    Different brands of Chinese vinegar are similar in appearance, color and aroma, making their discrimination difficult. The compositions and concentrations of the volatiles released from different vinegars vary by raw material and brewing process and thus offer a means to discriminate vinegars. In this study, we enhanced the detection sensitivity of the infrared spectrometer by extending its optical path. We measured the infrared spectra of the volatiles from 5 brands of Chinese vinegar and observed the spectral characteristics corresponding to alcohols, esters, acids, furfural, etc. Different brands of Chinese vinegar had obviously different infrared spectra and could be classified through chemometrics analysis. Furthermore, we established classification models and demonstrated their effectiveness for classifying different brands of vinegar. This study demonstrates that long-optical-path infrared spectroscopy has the ability to discriminate Chinese vinegars with the advantages that it is fast and non-destructive and eliminates the need for sampling. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Chemometrics applied to the incorporation of omega-3 in tilapia fillet feed flaxseed flour

    Directory of Open Access Journals (Sweden)

    Márcia Fernandes Nishiyama

    2014-09-01

    Full Text Available This study evaluated the effect of adding flaxseed flour to the diet of Nile tilapia on the fatty acid composition of fillets using chemometrics. A traditional and an experimental diet containing flaxseed flour were used to feed the fish for 60 days. An increase of 18:3 n-3 and 22:6 n-3 and a decrease of 18:2 n-6 were observed in the tilapia fillets fed the experimental diet. There was a reduction in the n-6:n-3 ratio. A period of 45 days of incorporation caused a significant change in tilapia chemical composition. Principal Component Analysis showed that the time periods of 45 and 60 days positively contributed to the total content of n-3, LNA, and DHA, highlighting the effect of omega-3 incorporation in the treatment containing flaxseed flour.

  2. Determination and discrimination of biodiesel fuels by gas chromatographic and chemometric methods

    Directory of Open Access Journals (Sweden)

    Milina R.

    2016-03-01

    Full Text Available Pattern recognition method (PRM was applied to gas chromatographic (GC data for a fatty acid methyl esters (FAME composition of commercial and laboratory synthesized biodiesel fuels from vegetable oils including sunflower, rapeseed, corn and palm oils. Two GC quantitative methods to calculate individual fames were compared: Area % and internal standard. The both methods were applied for analysis of two certified reference materials. The statistical processing of the obtained results demonstrates the accuracy and precision of the two methods and allows them to be compared. For further chemometric investigations of biodiesel fuels by their FAME-profiles any of those methods can be used. PRM results of FAME profiles of samples from different vegetable oils show a successful recognition of biodiesels according to the feedstock. The information obtained can be used for selection of feedstock to produce biodiesels with certain properties, for assessing their interchangeability, for fuel spillage and remedial actions in the environment.

  3. Determination and discrimination of biodiesel fuels by gas chromatographic and chemometric methods

    Science.gov (United States)

    Milina, R.; Mustafa, Z.; Bojilov, D.; Dagnon, S.; Moskovkina, M.

    2016-03-01

    Pattern recognition method (PRM) was applied to gas chromatographic (GC) data for a fatty acid methyl esters (FAME) composition of commercial and laboratory synthesized biodiesel fuels from vegetable oils including sunflower, rapeseed, corn and palm oils. Two GC quantitative methods to calculate individual fames were compared: Area % and internal standard. The both methods were applied for analysis of two certified reference materials. The statistical processing of the obtained results demonstrates the accuracy and precision of the two methods and allows them to be compared. For further chemometric investigations of biodiesel fuels by their FAME-profiles any of those methods can be used. PRM results of FAME profiles of samples from different vegetable oils show a successful recognition of biodiesels according to the feedstock. The information obtained can be used for selection of feedstock to produce biodiesels with certain properties, for assessing their interchangeability, for fuel spillage and remedial actions in the environment.

  4. MATHEMATICAL AND CHEMOMETRICAL MODELS – TOOLS TO EVALUATE HEAVY METALS CONTAMINATION

    Directory of Open Access Journals (Sweden)

    Despina Maria Bordean

    2017-11-01

    Full Text Available The aim of the this study is to present a combined view of bio – geo - chemistry, soil – plant interactions, mathematic models and statistic analysis, based on the correlation between the levels of soil contamination, and the remanence of polluting substances in soil and respectively in harvested fruits and vegetables. Most of the mathematical models which describe plant - soil interactions are integrated in plant growth models or climate change models. The models presented by this paper are Soil – Plant Interaction Models, Pollution Indices, The Indices for Evaluating the Adaptative Strategies of Plants and Chemo-metrical Methods, and they have the role to synthesize and evaluate the information regarding heavy metals contamination.

  5. Chemometric profile of root extracts of Rhodiola imbricata Edgew. with hyphenated gas chromatography mass spectrometric technique.

    Directory of Open Access Journals (Sweden)

    Amol B Tayade

    Full Text Available Rhodiola imbricata Edgew. (Rose root or Arctic root or Golden root or Shrolo, belonging to the family Crassulaceae, is an important food crop and medicinal plant in the Indian trans-Himalayan cold desert. Chemometric profile of the n-hexane, chloroform, dichloroethane, ethyl acetate, methanol, and 60% ethanol root extracts of R. imbricata were performed by hyphenated gas chromatography mass spectrometry (GC/MS technique. GC/MS analysis was carried out using Thermo Finnigan PolarisQ Ion Trap GC/MS MS system comprising of an AS2000 liquid autosampler. Interpretation on mass spectrum of GC/MS was done using the NIST/EPA/NIH Mass Spectral Database, with NIST MS search program v.2.0g. Chemometric profile of root extracts revealed the presence of 63 phyto-chemotypes, among them, 1-pentacosanol; stigmast-5-en-3-ol, (3β,24S; 1-teracosanol; 1-henteracontanol; 17-pentatriacontene; 13-tetradecen-1-ol acetate; methyl tri-butyl ammonium chloride; bis(2-ethylhexyl phthalate; 7,8-dimethylbenzocyclooctene; ethyl linoleate; 3-methoxy-5-methylphenol; hexadecanoic acid; camphor; 1,3-dimethoxybenzene; thujone; 1,3-benzenediol, 5-pentadecyl; benzenemethanol, 3-hydroxy, 5-methoxy; cholest-4-ene-3,6-dione; dodecanoic acid, 3-hydroxy; octadecane, 1-chloro; ethanone, 1-(4-hydroxyphenyl; α-tocopherol; ascaridole; campesterol; 1-dotriacontane; heptadecane, 9-hexyl were found to be present in major amount. Eventually, in the present study we have found phytosterols, terpenoids, fatty acids, fatty acid esters, alkyl halides, phenols, alcohols, ethers, alkanes, and alkenes as the major group of phyto-chemotypes in the different root extracts of R. imbricata. All these compounds identified by GC/MS analysis were further investigated for their biological activities and it was found that they possess a diverse range of positive pharmacological actions. In future, isolation of individual phyto-chemotypes and subjecting them to biological activity will definitely prove fruitful

  6. Ion mobility based on column leaching of South African gold tailings dam with chemometric evaluation.

    Science.gov (United States)

    Cukrowska, Ewa M; Govender, Koovila; Viljoen, Morris

    2004-07-01

    New column leaching experiments were designed and used as an alternative rapid screening approach to element mobility assessment. In these experiments, field-moist material was treated with an extracting solution to assess the effects of acidification on element mobility in mine tailings. The main advantage of this version of column leaching experiments with partitioned segments is that they give quick information on current element mobility in conditions closely simulating field conditions to compare with common unrepresentative air-dried, sieved samples used for column leaching experiments. Layers from the tailings dump material were sampled and packed into columns. The design of columns allows extracting leachates from each layer. The extracting solutions used were natural (pH 6.8) and acidified (pH 4.2) rainwater. Metals and anions were determined in the leachates. The concentrations of metals (Ca, Mg, Fe, Mn, Al, Cr, Ni, Co, Zn, and Cu) in sample leachates were determined using ICP OES. The most important anions (NO3-, Cl-, and SO4(2)-) were determined using the closed system izotacophoresis ITP analyser. The chemical analytical data from tailings leaching and physico-chemical data from field measurements (including pH, conductivity, redox potential, temperature) were used for chemometric evaluation of element mobility. Principal factor analysis (PFA) was used to evaluate ions mobility from different layers of tailings dump arising from varied pH and redox conditions. It was found that the results from the partitioned column leaching illustrate much better complex processes of metals mobility from tailings dump than the total column. The chemometric data analysis (PFA) proofed the differences in the various layers leachability that are arising from physico-chemical processes due to chemical composition of tailings dump deposit. Copyright 2004 Elsevier Ltd.

  7. Diffuse reflectance near infrared-chemometric methods development and validation of amoxicillin capsule formulations

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    Ahmed Nawaz Khan

    2016-01-01

    Full Text Available Objective: The aim of present study was to establish near infrared-chemometric methods that could be effectively used for quality profiling through identification and quantification of amoxicillin (AMOX in formulated capsule which were similar to commercial products. In order to evaluate a large number of market products easily and quickly, these methods were modeled. Materials and Methods: Thermo Scientific Antaris II near infrared analyzer with TQ Analyst Chemometric Software were used for the development and validation of the identification and quantification models. Several AMOX formulations were composed with four excipients microcrystalline cellulose, magnesium stearate, croscarmellose sodium and colloidal silicon dioxide. Development includes quadratic mixture formulation design, near infrared spectrum acquisition, spectral pretreatment and outlier detection. According to prescribed guidelines by International Conference on Harmonization (ICH and European Medicine Agency (EMA developed methods were validated in terms of specificity, accuracy, precision, linearity, and robustness. Results: On diffuse reflectance mode, an identification model based on discriminant analysis was successfully processed with 76 formulations; and same samples were also used for quantitative analysis using partial least square algorithm with four latent variables and 0.9937 correlation of coefficient followed by 2.17% root mean square error of calibration (RMSEC, 2.38% root mean square error of prediction (RMSEP, 2.43% root mean square error of cross-validation (RMSECV. Conclusion: Proposed model established a good relationship between the spectral information and AMOX identity as well as content. Resulted values show the performance of the proposed models which offers alternate choice for AMOX capsule evaluation, relative to that of well-established high-performance liquid chromatography method. Ultimately three commercial products were successfully evaluated

  8. Combining Near-Infrared Spectroscopy and Chemometrics for Rapid Recognition of an Hg-Contaminated Plant

    Directory of Open Access Journals (Sweden)

    Bang-Cheng Tang

    2016-01-01

    Full Text Available The feasibility of rapid recognition of an Hg-contaminated plant as a soil pollution indicator was investigated using near-infrared spectroscopy (NIRS and chemometrics. The stem and leave of a native plant, Miscanthus floridulus (Labill. Warb. (MFLW, were collected from Hg-contaminated areas (n1=125 as well as from regular areas (n2=116. The samples were dried and crushed and the powders were sieved through an 80-mesh sieve. Reference analysis of Hg levels was performed using inductively coupled plasma-atomic emission spectrometry (ICP-AES. The actual Hg contents of contaminated and normal samples were 16.2–30.5 and 0.0–0.1 mg/Kg, respectively. The NIRS measurements of impacted sample powders were collected in the mode of reflectance. The DUPLEX algorithm was utilized to split the NIRS data into representative training and test sets. Different spectral preprocessing methods were performed to remove the unwanted and noncomposition-correlated spectral variations. Classification models were developed using partial least squares discrimination analysis (PLSDA based on the raw, smoothed, second-order derivative (D2, and standard normal variate (SNV data, respectively. The prediction accuracy obtained by PLSDA with each data preprocessing option was 100%, indicating pattern recognition of Hg-contaminated MFLW samples using NIRS data was in perfect consistence with the ICP-AES results. NIRS combined with chemometrics will provide a tool to screen the Hg-contaminated MFLW, which can be potentially used as an indicator of soil pollution.

  9. Chemometric comparison of polychlorinated biphenyl residues and toxicologically active polychlorinated biphenyl congeners in the eggs of Forster's Terns (Sterna fosteri)

    Science.gov (United States)

    Schwartz, Ted R.; Stalling, David L.

    1991-01-01

    The separation and characterization of complex mixtures of polychlorinated biphenyls (PCBs) is approached from the perspective of a problem in chemometrics. A technique for quantitative determination of PCB congeners is described as well as an enrichment technique designed to isolate only those congener residues which induce mixed aryl hydrocarbon hydroxylase enzyme activity. A congener-specific procedure is utilized for the determination of PCBs in whichn-alkyl trichloroacetates are used as retention index marker compounds. Retention indices are reproducible in the range of ±0.05 to ±0.7 depending on the specific congener. A laboratory data base system developed to aid in the editing and quantitation of data generated from capillary gas chromatography was employed to quantitate chromatographic data. Data base management was provided by computer programs written in VAX-DSM (Digital Standard MUMPS) for the VAX-DEC (Digital Equipment Corp.) family of computers.In the chemometric evaluation of these complex chromatographic profiles, data are viewed from a single analysis as a point in multi-dimensional space. Principal Components Analysis was used to obtain a representation of the data in a lower dimensional space. Two-and three-dimensional proections based on sample scores from the principal components models were used to visualize the behavior of Aroclor® mixtures. These models can be used to determine if new sample profiles may be represented by Aroclor profiles. Concentrations of individual congeners of a given chlorine substitution may be summed to form homologue concentration. However, the use of homologue concentrations in classification studies with environmental samples can lead to erroneous conclusions about sample similarity. Chemometric applications are discussed for evaluation of Aroclor mixture analysis and compositional description of environmental residues of PCBs in eggs of Forster's terns (Sterna fosteri) collected from colonies near Lake Poygan

  10. Fourier transform infrared spectroscopy and chemometrics for the characterization and discrimination of writing/photocopier paper types: Application in forensic document examinations

    Science.gov (United States)

    Kumar, Raj; Kumar, Vinay; Sharma, Vishal

    2017-01-01

    The aim of the present work is to explore the non-destructive application of ATR-FTIR technique for characterization and discrimination of paper samples which could be helpful to give forensic aid in resolving legal cases. Twenty-four types of paper brands were purchased from local market in and around Chandigarh, India. All the paper samples were subjected to ATR-FTIR analysis from 400 to 4000 cm- 1 wavenumber range. The qualitative feature and Chemometrics of the obtained spectral data are used for characterization and discrimination. Characterization is achieved by matching the peaks with standards of cellulose and inorganic fillers, a usual constituents of paper. Three different regions of IR, i.e. 400-2000 cm- 1, 2000-4000 cm- 1 and 400-4000 cm- 1 were selected for differentiation by Chemometrics analysis. The discrimination is achieved on the basis of three principal components, i.e. PC 1, PC 2 and PC 3. It is observed that maximum discrimination was procured in the wave number range of i.e. 2000-4000 cm- 1. Discriminating power was calculated on the basis of qualitative features as well, and it is found that the discrimination of paper samples was better achieved by Chemometrics analysis rather than qualitative features. The discriminating power by Chemometrics is 99.64% and which is larger as ever achieved by any group for present number of samples. The present result confirms that this study will be highly useful in forensic document examination work in the legal cases, where the authenticity of the document is challenged. The results are completely analytical and, therefore, overcome the problem encounter in traditional routine light/radiation scanning methods which are still in practice by various questioned document laboratories.

  11. Fourier transform infrared spectroscopy and chemometrics for the characterization and discrimination of writing/photocopier paper types: Application in forensic document examinations.

    Science.gov (United States)

    Kumar, Raj; Kumar, Vinay; Sharma, Vishal

    2017-01-05

    The aim of the present work is to explore the non-destructive application of ATR-FTIR technique for characterization and discrimination of paper samples which could be helpful to give forensic aid in resolving legal cases. Twenty-four types of paper brands were purchased from local market in and around Chandigarh, India. All the paper samples were subjected to ATR-FTIR analysis from 400 to 4000cm(-1) wavenumber range. The qualitative feature and Chemometrics of the obtained spectral data are used for characterization and discrimination. Characterization is achieved by matching the peaks with standards of cellulose and inorganic fillers, a usual constituents of paper. Three different regions of IR, i.e. 400-2000cm(-1), 2000-4000cm(-1) and 400-4000cm(-1) were selected for differentiation by Chemometrics analysis. The discrimination is achieved on the basis of three principal components, i.e. PC 1, PC 2 and PC 3. It is observed that maximum discrimination was procured in the wave number range of i.e. 2000-4000cm(-1). Discriminating power was calculated on the basis of qualitative features as well, and it is found that the discrimination of paper samples was better achieved by Chemometrics analysis rather than qualitative features. The discriminating power by Chemometrics is 99.64% and which is larger as ever achieved by any group for present number of samples. The present result confirms that this study will be highly useful in forensic document examination work in the legal cases, where the authenticity of the document is challenged. The results are completely analytical and, therefore, overcome the problem encounter in traditional routine light/radiation scanning methods which are still in practice by various questioned document laboratories. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. Nondestructive determination of transgenic Bacillus thuringiensis rice seeds (Oryza sativa L.) using multispectral imaging and chemometric methods.

    Science.gov (United States)

    Liu, Changhong; Liu, Wei; Lu, Xuzhong; Chen, Wei; Yang, Jianbo; Zheng, Lei

    2014-06-15

    Crop-to-crop transgene flow may affect the seed purity of non-transgenic rice varieties, resulting in unwanted biosafety consequences. The feasibility of a rapid and nondestructive determination of transgenic rice seeds from its non-transgenic counterparts was examined by using multispectral imaging system combined with chemometric data analysis. Principal component analysis (PCA), partial least squares discriminant analysis (PLSDA), least squares-support vector machines (LS-SVM), and PCA-back propagation neural network (PCA-BPNN) methods were applied to classify rice seeds according to their genetic origins. The results demonstrated that clear differences between non-transgenic and transgenic rice seeds could be easily visualized with the nondestructive determination method developed through this study and an excellent classification (up to 100% with LS-SVM model) can be achieved. It is concluded that multispectral imaging together with chemometric data analysis is a promising technique to identify transgenic rice seeds with high efficiency, providing bright prospects for future applications. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. Automated optimization and construction of chemometric models based on highly variable raw chromatographic data.

    Science.gov (United States)

    Sinkov, Nikolai A; Johnston, Brandon M; Sandercock, P Mark L; Harynuk, James J

    2011-07-04

    Direct chemometric interpretation of raw chromatographic data (as opposed to integrated peak tables) has been shown to be advantageous in many circumstances. However, this approach presents two significant challenges: data alignment and feature selection. In order to interpret the data, the time axes must be precisely aligned so that the signal from each analyte is recorded at the same coordinates in the data matrix for each and every analyzed sample. Several alignment approaches exist in the literature and they work well when the samples being aligned are reasonably similar. In cases where the background matrix for a series of samples to be modeled is highly variable, the performance of these approaches suffers. Considering the challenge of feature selection, when the raw data are used each signal at each time is viewed as an individual, independent variable; with the data rates of modern chromatographic systems, this generates hundreds of thousands of candidate variables, or tens of millions of candidate variables if multivariate detectors such as mass spectrometers are utilized. Consequently, an automated approach to identify and select appropriate variables for inclusion in a model is desirable. In this research we present an alignment approach that relies on a series of deuterated alkanes which act as retention anchors for an alignment signal, and couple this with an automated feature selection routine based on our novel cluster resolution metric for the construction of a chemometric model. The model system that we use to demonstrate these approaches is a series of simulated arson debris samples analyzed by passive headspace extraction, GC-MS, and interpreted using partial least squares discriminant analysis (PLS-DA). Copyright © 2011 Elsevier B.V. All rights reserved.

  14. Mid-infrared spectroscopy combined with chemometrics to detect Sclerotinia stem rot on oilseed rape (Brassica napusL.) leaves.

    Science.gov (United States)

    Zhang, Chu; Feng, Xuping; Wang, Jian; Liu, Fei; He, Yong; Zhou, Weijun

    2017-01-01

    Detection of plant diseases in a fast and simple way is crucial for timely disease control. Conventionally, plant diseases are accurately identified by DNA, RNA or serology based methods which are time consuming, complex and expensive. Mid-infrared spectroscopy is a promising technique that simplifies the detection procedure for the disease. Mid-infrared spectroscopy was used to identify the spectral differences between healthy and infected oilseed rape leaves. Two different sample sets from two experiments were used to explore and validate the feasibility of using mid-infrared spectroscopy in detecting Sclerotinia stem rot (SSR) on oilseed rape leaves. The average mid-infrared spectra showed differences between healthy and infected leaves, and the differences varied among different sample sets. Optimal wavenumbers for the 2 sample sets selected by the second derivative spectra were similar, indicating the efficacy of selecting optimal wavenumbers. Chemometric methods were further used to quantitatively detect the oilseed rape leaves infected by SSR, including the partial least squares-discriminant analysis, support vector machine and extreme learning machine. The discriminant models using the full spectra and the optimal wavenumbers of the 2 sample sets were effective for classification accuracies over 80%. The discriminant results for the 2 sample sets varied due to variations in the samples. The use of two sample sets proved and validated the feasibility of using mid-infrared spectroscopy and chemometric methods for detecting SSR on oilseed rape leaves. The similarities among the selected optimal wavenumbers in different sample sets made it feasible to simplify the models and build practical models. Mid-infrared spectroscopy is a reliable and promising technique for SSR control. This study helps in developing practical application of using mid-infrared spectroscopy combined with chemometrics to detect plant disease.

  15. Chemometrics-assisted microfluidic paper-based analytical device for the determination of uric acid by silver nanoparticle plasmon resonance.

    Science.gov (United States)

    Hamedpour, Vahid; Postma, Geert J; van den Heuvel, Edwin; Jansen, Jeroen J; Suzuki, Koji; Citterio, Daniel

    2018-03-01

    This manuscript reports on the application of chemometric methods for the development of an optimized microfluidic paper-based analytical device (μPAD). As an example, we applied chemometric methods for both device optimization and data processing of results of a colorimetric uric acid assay. Box-Behnken designs (BBD) were utilized for the optimization of the device geometry and the amount of thermal inkjet-deposited assay reagents, which affect the assay performance. Measurement outliers were detected in real time by partial least squares discriminant analysis (PLS-DA) of scanned images. The colorimetric assay mechanism is based on the on-device formation of silver nanoparticles (AgNPs) through the interaction of uric acid, ammonia, and poly(vinyl alcohol) with silver ions under mild basic conditions. The yellow color originating from visible light absorption by localized surface plasmon resonance of AgNPs can be detected by the naked eye or, more quantitatively, with a simple flat-bed scanner. Under optimized conditions, the linearity of the calibration curve ranges from 0.1-5 × 10 -3 mol L -1 of uric acid with a limit of detection of 33.9 × 10 -6 mol L -1 and a relative standard of deviation 4.5% (n = 3 for determination of 5.0 × 10 -3 mol L -1 uric acid). Graphical abstract A chemometrics-assisted microfluidic paper-based analytical device was developed as a low-cost and rapid platform for the determination of uric acid (UA). The detection method is based on the chemical interaction of UA, ammonia, and polyvinyl alcohol under mild basic condition with silver ions inducing formation of yellow silver nanoparticles (AgNPs).

  16. Doehlert matrix: a chemometric tool for analytical chemistry-review.

    Science.gov (United States)

    Ferreira, Sérgio L C; Dos Santos, Walter N L; Quintella, Cristina M; Neto, Benício B; Bosque-Sendra, Juan M

    2004-07-08

    A review of the use of the Doehlert matrix as a chemometric tool for the optimization of methods in analytical chemistry and other sciences is presented. The theoretical principles of Doehlert designs are described, including the coded values for the use of this matrix involving two, three, four and five variables. The advantages of this matrix in comparison with other response surface designs, such as central composite and Box-Behnken, designs are discussed. Finally, 57 references concerning the application of Doehlert matrices in the optimization of procedures involving spectroanalytical, electroanalytical and chromatographic techniques are considered.

  17. A primer to nutritional metabolomics by NMR spectroscopy and chemometrics

    DEFF Research Database (Denmark)

    Savorani, Francesco; Rasmussen, Morten Arendt; Mikkelsen, Mette Skau

    2013-01-01

    structures for multivariate pattern recognition methods and (3) NMR for providing a unique fingerprint of the lipoprotein status of the subject. For the first time in history, by combining NMR spectroscopy and chemometrics we are able to perform inductive nutritional research as a complement to the deductive......This paper outlines the advantages and disadvantages of using high throughput NMR metabolomics for nutritional studies with emphasis on the workflow and data analytical methods for generation of new knowledge. The paper describes one-by-one the major research activities in the interdisciplinary...

  18. Total detection of Tianma Toutong tablets for quality consistency by a five-wavelength fusion fingerprint and chemometrics.

    Science.gov (United States)

    Yang, Zhe; Sun, Guo-Xiang

    2017-07-01

    A fingerprint method was developed and combined with chemometrics for quality evaluation of Tianma Toutong tablets, which are herbal medicine tablets used to treat migraine. Samples were analyzed by high-performance liquid chromatography, where five single-wavelength profiles (203, 232, 254, 280 and 310 nm) were fused to generate a five-wavelength fusion fingerprint and were also used for the quantitative analysis of seven chemical markers (gastrodin, caffeic acid, hesperidin, isoimperatorin, chlorogenic acid, ferulic acid and imperatorin). A systematic quantitative fingerprint method and principal component analysis were used to analyze the generated data. Samples could be well distinguished from different manufacturers by analyzing the chromatographic data sets. In addition, the partial least squares model can serve as an antioxidant activity evaluation of Tianma Toutong tablets, as well as a reference for the selection of active constituents to analyze the spectrum-activity relationship. In summary, the integrated use of the fingerprint and chemometric analysis provides a reliable method for the identification of markers and the quality control of Tianma Toutong tablets. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Determination of phenolic compounds and authentication of PDO Lambrusco wines by HPLC-DAD and chemometric techniques.

    Science.gov (United States)

    Salvatore, Elisa; Cocchi, Marina; Marchetti, Andrea; Marini, Federico; de Juan, Anna

    2013-01-25

    This work proposes a fast and simple method for detection and quantification of phenolic compounds in PDO Lambrusco wines using HPLC-DAD and chemometric techniques. Samples belonging to three different varieties of Lambrusco (Grasparossa, Salamino and Sorbara) were analyzed to provide a methodology appropriate for routine analysis. Given the high complexity of the sample and the coelution among chromatographic peaks, the use of chemometric techniques to extract the information of the individual eluting compounds was needed. Multivariate curve resolution-alternating least squares (MCR-ALS) allowed the resolution of the chromatographic peaks obtained and the use of this information for the quantification of the phenolic analytes in the presence of interferences. Use of multiset analysis and local rank/selectivity information was proven to be crucial for the correct resolution and quantification of compounds. The quantitative data provided by MCR-ALS about the phenolic targets and additional compounds present in the samples analyzed provided wine composition profiles, which were afterwards used to distinguish among wine varieties. Principal component analysis applied to the wine profiles allowed characterizing the wines according to their varieties. Copyright © 2012 Elsevier B.V. All rights reserved.

  20. Liquid Chromatographic-Chemometric Techniques for the Simultaneous HPLC Determination of Lansoprazole, Amoxicillin and Clarithromycin in Commercial Preparation.

    Science.gov (United States)

    Aktas, A Hakan; Saridag, Ayse Mine

    2017-09-01

    Two multivariate calibration-prediction techniques, principal component regression (PCR) and partial least-squares regression (PLSR) were applied to the chromatographic multicomponent analysis of the drug containing lansoprazole (LAN), clarithromycin (CLA) and amoxicillin (AMO). Optimum chromatographic separation of LAN, CLA and AMO with atorvastatin as the internal standard (IS) was obtained by using Xterra® RP18 column 5 μm 4.6 × 250 mm2, and 25 mM ammonium chloride buffer prepared ammonium chloride, acetonitrile and bidistilled water (45:45:10 v/v) as the mobile phase at flow rate 1.0 mL/min. The high pressure liquid chromatography data sets consisting of the ratios of analyte peak areas to the IS peak area were obtained by using diode array detector detection at five wavelengths (205, 210, 215, 220 and 225 nm). LC-chemometric calibration for LAN, CLA and AMO were separately constructed by using the relationship between the peak-area ratio and training sets for each analyte. A series of synthetic solutions containing different concentrations of LAN, CLA and AMO were used to check the prediction ability of the PCR and PLS. Both of the two-chemometric methods in this study can be satisfactorily used for the quantitative analysis and for dissolutions tests of multicomponent commercial drug. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  1. Chemical characterization complemented with chemometrics for the botanical origin identification of unifloral and multifloral honeys from India.

    Science.gov (United States)

    Devi, Apramita; Jangir, Jitender; K A, Anu-Appaiah

    2018-05-01

    Chemical fingerprints based on FTIR spectra, phenolics and volatiles were studied for a total of 30 honey types of eight different botanical origin i.e. litchi, neem, ginger, eucalyptus, lemon (unifloral) and Kashmiri white, BR Hills & Pan India honey (Multifloral). Chemometrics based on principal component analysis (PCA) was used as a complementary tool for chemical fingerprint of honey. ATR-FTIR had a good predictive capability to discriminate among honey when conjugated with chemometric tools, providing the rapid first-line of classification for honey. The specific phenolic compounds identified were homovanillic acid for neem, zingerone and gingerol for ginger, tricetin for eucalyptus, hesperitin and naringenin for lemon honey. Analysis of volatiles led to identification of odor active compounds such as azadirachtin for neem and zingiberene in ginger honey for the first time, whereas cis-rose oxide for litchi, 2-hydroxycineole for eucalyptus and methyl anthranilate & limonene diol for lemon honey as per previous studies which were well correlated with PCA of phenolics and volatiles. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. Robust and Automated Internal Quality Grading of a Chinese Green Tea (Longjing by Near-Infrared Spectroscopy and Chemometrics

    Directory of Open Access Journals (Sweden)

    Xian-Shu Fu

    2013-01-01

    Full Text Available Near-infrared (NIR spectroscopy and chemometric methods were applied to internal quality control of a Chinese green tea, Longjing, with Protected Geographical Indication (PGI. A total of 2745 authentic Longjing tea samples of three different grades were analyzed by NIR spectroscopy. To remove the influence of abnormal samples, The Stahel-Donoho estimate (SDE of outlyingness was used for outlier analysis. Partial least squares discriminant analysis (PLSDA was then used to classify the grades of tea based on NIR spectra. Different data preprocessing methods, including smoothing, taking second-order derivative (D2 spectra, and standard normal variate (SNV transformation, were performed to reduce unwanted spectral variations in samples of the same grade before classification models were developed. The results demonstrate that smoothing, taking D2 spectra, and SNV can improve the performance of PLSDA models. With SNV spectra, the model sensitivity was 1.000, 0.955, and 0.924, and the model specificity was 0.979, 0.952, and 0.996 for samples of three grades, respectively. FT-NIR spectrometry and chemometrics can provide a robust and effective tool for rapid internal quality control of Longjing green tea.

  3. Chemometric resolution approaches in characterisation of volatile constituents in Plantago ovata seeds using gas chromatography-mass spectrometry: methodology and performance assessment.

    Science.gov (United States)

    Seifi, Hooman; Masoum, Saeed; Seifi, Soodabe; Ebrahimabadi, Ebrahim Haghir

    2014-01-01

    Comprehensive chemical profiling of herbal medicines (HMs) is a major challenge in chemical characterisation of source materials. Many analytical platforms such as gas chromatography-mass spectrometry (GC-MS) have been applied to the characterisation. However, the great complexity of analytical results has been an obstacle. Chemometric resolution methods as a supplementary tool for data processing are proposed for solving this problem. To develop and demonstrate the ability of chemometric techniques in the characterisation of volatile components in herbal medicines. The volatile components of Plantago ovata were extracted using a solvent extraction method. GC-MS analysis were performed using an Agilent HP-6890 gas chromatograph equipped with a HP-5MS capillary, interfaced with an Agilent HP- 5973 mass selective detector. Resolved spectra were identified by matching against the standard mass spectral database of the National Institute of Standards and Technology (NIST). Results of this study show that the 71 constituents that are qualitatively recognised represent 94.53% of the total relative content of constituents from Plantago ovata oil, whereas without applying the chemometric methods only 51 constituents were recognised by direct searching utilising a mass database. In addition the presence of valuable components such as thymol, 2,4-decadienal, linoleic acid and oleic acid in Plantago ovata oil has been demonstrated. GC-MS combined with chemometric resolution methods, such as multivariate curve resolution-alternating least squares (MCR-ALS), will provide a reliable means for rapid and accurate analyses of unknown complicated practical systems. Copyright © 2014 John Wiley & Sons, Ltd.

  4. Classification of Argentinean Sauvignon blanc wines by UV spectroscopy and chemometric methods.

    Science.gov (United States)

    Azcarate, Silvana Mariela; Cantarelli, Miguel Ángel; Pellerano, Roberto Gerardo; Marchevsky, Eduardo Jorge; Camiña, José Manuel

    2013-03-01

    Argentina is an important worldwide wine producer. In this country, there are several recognizable provinces that produce Sauvignon blanc wines: Neuquén, Río Negro, Mendoza, and San Juan. The analysis of the provenance of these white wines is complex and requires the use of expensive and time-consuming techniques. For this reason, this work discusses the determination of the provenance of Argentinean Sauvignon blanc wines by the use of UV spectroscopy and chemometric methods, such as principal component analysis (PCA), cluster analysis (CA), linear discriminant analysis (LDA), and partial least square discriminant analysis (PLS-DA). The proposed method requires low-cost equipment and short-time analysis in comparison with other techniques. The results are in very good agreement with results based on the geographical origin of Sauvignon blanc wines. This manuscript describes a method to determine the geographical origin of Sauvignon wines from Argentina. The main advantage of this method is the use of nonexpensive techniques, such as UV-Vis spectroscopy. © 2013 Institute of Food Technologists®

  5. Teaching Chemometrics: A Course on Application of Mathematical Techniques to Chemistry.

    Science.gov (United States)

    Delaney, Michael F.; Warren, F. Vincent, Jr.

    1981-01-01

    Describes a course in chemometrics offered at Tufts University which is designed to provide college chemistry majors with an understanding of potential roles which computers might play in chemical research. (CS)

  6. Chemometric classification techniques as a tool for solving problems in analytical chemistry.

    Science.gov (United States)

    Bevilacqua, Marta; Nescatelli, Riccardo; Bucci, Remo; Magrì, Andrea D; Magrì, Antonio L; Marini, Federico

    2014-01-01

    Supervised pattern recognition (classification) techniques, i.e., the family of chemometric methods whose aim is the prediction of a qualitative response on a set of samples, represent a very important assortment of tools for solving problems in several areas of applied analytical chemistry. This paper describes the theory behind the chemometric classification techniques most frequently used in analytical chemistry together with some examples of their application to real-world problems.

  7. Nondestructive prediction of oren extract powder, a herbal medicine, in suppositories by chemometric near-infrared spectroscopy.

    Science.gov (United States)

    Teraoka, Ryutaro; Abe, Hiroyuki; Sugama, Tadaaki; Ito, Kiyomi; Aburada, Masaki; Otsuka, Makoto

    2012-04-01

    Near-infrared (NIR) spectroscopy combined with chemometrics has been utilized in predictions of natural medicine content without destroying samples. Suppositories (oren powdered extract content 0, 0.5, 1.0, 2.5, 10, 12.5, and 15%) were produced by mixing oren powdered extract with macrogol mixture consisting of 1 part macrogol 1500 and 2.5 parts macrogol 4000 at 54°C, and pouring the melt mixture into a plastic container. NIR spectra of the 10 prepared samples were recorded 10 times, and a total of 100 spectra were randomly divided into two data sets, one for calibration and the other for validation. The calibration model for the oren content of the suppository was calculated based on NIR spectra using a partial least-squares regression analysis after pre-treatment (smoothing and the multiplicative scatter correction). The relationship between the actual and predicted values for calibration and validation models had a straight line with correlation coefficients of 0.9936 and 0.9898, respectively. The regression vector result of the calibration model indicates that the peaks at 6945, 5747, and 5160 cm(-1) in the regression vector were consistent with those in oren powder extracts. NIR spectroscopy combined with chemometrics offers promise as a method of predicting the oren powder content in suppositories without destroying the samples.

  8. Neurochemostat: A Neural Interface SoC with Integrated Chemometrics for Closed-Loop Regulation of Brain Dopamine

    Science.gov (United States)

    Bozorgzadeh, Bardia; Schuweiler, Douglas R.; Bobak, Martin J.; Garris, Paul A.; Mohseni, Pedram

    2016-01-01

    This paper presents a 3.3 × 3.2mm2 system-on-chip (SoC) fabricated in AMS 0.35µm 2P/4M CMOS for closed-loop regulation of brain dopamine. The SoC uniquely integrates neurochemical sensing, on-the-fly chemometrics, and feedback-controlled electrical stimulation to realize a “neurochemostat” by maintaining brain levels of electrically evoked dopamine between two user-set thresholds. The SoC incorporates a 90µW, custom-designed, digital signal processing (DSP) unit for real-time processing of neurochemical data obtained by 400V/s fast-scan cyclic voltammetry (FSCV) with a carbon-fiber microelectrode (CFM). Specifically, the DSP unit executes a chemometrics algorithm based upon principal component regression (PCR) to resolve in real time electrically evoked brain dopamine levels from pH change and CFM background-current drift, two common interferents encountered using FSCV with a CFM in vivo. Further, the DSP unit directly links the chemically resolved dopamine levels to the activation of the electrical microstimulator in on-off-keying (OOK) fashion. Measured results from benchtop testing, flow injection analysis (FIA), and biological experiments with an anesthetized rat are presented. PMID:26390501

  9. NMR and Chemometric Characterization of Vacuum Residues and Vacuum Gas Oils from Crude Oils of Different Origin

    Directory of Open Access Journals (Sweden)

    Jelena Parlov Vuković

    2015-03-01

    Full Text Available NMR spectroscopy in combination with statistical methods was used to study vacuum residues and vacuum gas oils from 32 crude oils of different origin. Two chemometric metodes were applied. Firstly, principal component analysis on complete spectra was used to perform classification of samples and clear distinction between vacuum residues and vacuum light and heavy gas oils were obtained. To quantitatively predict the composition of asphaltenes, principal component regression models using areas of resonance signals spaned by 11 frequency bins of the 1H NMR spectra were build. The first 5 principal components accounted for more than 94 % of variations in the input data set and coefficient of determination for correlation between measured and predicted values was R2 = 0.7421. Although this value is not significant, it shows the underlying linear dependence in the data. Pseudo two-dimensional DOSY NMR experiments were used to assess the composition and structural properties of asphaltenes in a selected crude oil and its vacuum residue on the basis of their different hydrodynamic behavior and translational diffusion coefficients. DOSY spectra showed the presence of several asphaltene aggregates differing in size and interactions they formed. The obtained results have shown that NMR techniques in combination with chemometrics are very useful to analyze vacuum residues and vacuum gas oils. Furthermore, we expect that our ongoing investigation of asphaltenes from crude oils of different origin will elucidate in more details composition, structure and properties of these complex molecular systems.

  10. Fast data preprocessing for chromatographic fingerprints of tomato cell wall polysaccharides using chemometric methods.

    Science.gov (United States)

    Quéméner, Bernard; Bertrand, Dominique; Marty, Isabelle; Causse, Mathilde; Lahaye, Marc

    2007-02-02

    The variability in the chemistry of cell wall polysaccharides in pericarp tissue of red-ripe tomato fruit (Solanum lycopersicon Mill.) was characterized by chemical methods and enzymatic degradations coupled to high performance anion exchange chromatography (HPAEC) and mass spectrometry analysis. Large fruited line, Levovil (LEV) carrying introgressed chromosome fragments from a cherry tomato line Cervil (CER) on chromosomes 4 (LC4), 9 (LC9), or on chromosomes 1, 2, 4 and 9 (LCX) and containing quantitative trait loci (QTLs) for texture traits, was studied. In order to differentiate cell wall polysaccharide modifications in the tomato fruit collection by multivariate analysis, chromatograms were corrected for baseline drift and shift of the component elution time using an approach derived from image analysis and mathematical morphology. The baseline was first corrected by using a "moving window" approach while the peak-matching method developed was based upon location of peaks as local maxima within a window of a definite size. The fast chromatographic data preprocessing proposed was a prerequisite for the different chemometric treatments, such as variance and principal component analysis applied herein to the analysis. Applied to the tomato collection, the combined enzymatic degradations and HPAEC analyses revealed that the firm LCX and CER genotypes showed a higher proportion of glucuronoxylans and pectic arabinan side chains while the mealy LC9 genotype demonstrated the highest content of pectic galactan side chains. QTLs on tomato chromosomes 1, 2, 4 and 9 contain important genes controlling glucuronoxylan and pectic neutral side chains biosynthesis and/or metabolism.

  11. Oxidação de glicerol sobre nanopartículas de ouro suportadas em carvão ativado: monitoramento quimiométrico da reação por ESI-MS e MIR Glycerol oxidation over gold nanoparticles supported on activated carbon: chemometric monitoring of the reaction by ESI-MS and MIR

    Directory of Open Access Journals (Sweden)

    Cleiton A. Nunes

    2013-01-01

    Full Text Available A study on the monitoring of glycerol oxidation catalyzed by gold nanoparticles supported on activated carbon under mild conditions by chemometric methods is presented. The reaction was monitored by mass spectrometry-electrospray ionization (ESI-MS and comparatively by mid infrared spectroscopy (MIR. Concentration profiles of reagent and products were determined by chemometric tools such as Principal Component Analysis (PCA, Evolving Factor Analysis (EFA and Multivariate Curve Resolution (MCR. The gold nanoparticle catalyst was relatively active in glycerol oxidation, favoring formation of high added value products. It was found that the reaction stabilization was reached at four hours, with approximately 70% glycerol conversion and high selectivity for glycerate.

  12. Comparisons of large (Vaccinium macrocarpon Ait.) and small (Vaccinium oxycoccos L., Vaccinium vitis-idaea L.) cranberry in British Columbia by phytochemical determination, antioxidant potential, and metabolomic profiling with chemometric analysis.

    Science.gov (United States)

    Brown, Paula N; Turi, Christina E; Shipley, Paul R; Murch, Susan J

    2012-04-01

    There is a long history of use and modern commercial importance of large and small cranberries in North America. The central objective of the current research was to characterize and compare the chemical composition of 2 west coast small cranberry species traditionally used (Vaccinium oxycoccos L. and Vaccinium vitis-idaea L.) with the commercially cultivated large cranberry (Vaccinium macrocarpon Ait.) indigenous to the east coast of North America. V. oxycoccos and V. macrocarpon contained the 5 major anthocyanins known in cranberry; however, the ratio of glycosylated peonidins to cyanidins varied, and V. vitis-idaea did not contain measurable amounts of glycosylated peonidins. Extracts of all three berries were found to contain serotonin, melatonin, and ascorbic acid. Antioxidant activity was not found to correlate with indolamine levels while anthocyanin content showed a negative correlation, and vitamin C content positively correlated. From the metabolomics profiles, 4624 compounds were found conserved across V. macrocarpon, V. oxycoccoS, and V. vitis-idaea with a total of approximately 8000-10 000 phytochemicals detected in each species. From significance analysis, it was found that 2 compounds in V. macrocarpoN, 3 in V. oxycoccos, and 5 in V. vitis-idaea were key to the characterization and differentiation of these cranberry metabolomes. Through multivariate modeling, differentiation of the species was observed, and univariate statistical analysis was employed to provide a quality assessment of the models developed for the metabolomics data. © Georg Thieme Verlag KG Stuttgart · New York.

  13. Assay of 44 compounds in the cortex and xylem from roots and branches of Ginkgo biloba L. by ultra high performance liquid chromatography coupled with tandem mass spectrometry and chemometric analysis.

    Science.gov (United States)

    Liu, Pei; Zhao, Jin-Long; Duan, Jin-Ao; Qian, Da-Wei; Guo, Sheng; Tang, Yu-Ping

    2015-09-01

    The leaves of Ginkgo biloba L. have received much attention, whereas there has been little systematic analysis of the cortex and xylem from roots and branches. A comprehensive evaluation of the 44 compounds in the cortex and xylem would thus be of value to fully understand the potential medicinal properties of roots and branches. An assay of amino acids, terpene lactones, flavones, and phenolic acids was accomplished using ultra high performance liquid chromatography with tandem mass spectrometry. All of the calibration curves showed good linear regression (R 2 > 0.9902) within the tested ranges. The intra- and interday precision was less than 4.9% and the accuracy was within ±6.8%. The amount of terpene lactones in the cortex was 1.75-2.07-fold higher than that in the leaves. The amount of glutamine (360 μg/g) in the taproot xylem was 2.64-fold higher than that in the leaves (136 μg/g). Principal component analysis decreased in the order leaves > taproot cortex > rootlet > laterals cortex > branch cortex > stem cortex > taproot xylem > branch xylem > laterals xylem > stem xylem. The taproot of G. biloba might provide a supplementary source of terpene lactones, especially ginkgolide A and C, and of glutamine. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Application of chemometric techniques to classify the quality of surface water in the watershed of the river Bermudez in Heredia, Costa Rica

    International Nuclear Information System (INIS)

    Herrera Murillo, Jorge; Rodriguez Roman, Susana; Solis Torres, Ligia Dina; Castro Delgado, Francisco

    2009-01-01

    The application of selected chemometric techniques have been investigated: cluster analysis, principal component analysis and factor analysis, to classify the quality of rivers water and evaluate pollution data. Fourteen physicochemical parameters were monitored at 10 stations located in the watershed of the river Bermudez, from August 2005 to February 2007. The results have identified the existence of two natural clusters of monitoring sites with similar characteristics of contamination and identify the DQO, DBO, NO 3 - , SO 4 -2 and SST, as the main variables that discriminate between sampling sites. (author) [es

  15. Acoustic chemometric prediction of total solids in bioslurry

    DEFF Research Database (Denmark)

    Ihunegbo, Felicia; Madsen, Michael; Esbensen, Kim

    2012-01-01

    Dry matter is an important process control parameter in the bioconversion application field. Acoustic chemometrics, as a Process Analytical Technology (PAT) modality for quantitative characterisation of dry matter in complex bioslurry systems (biogas fermentation), has not been successful despite...... several earlier dedicated attempts. A full-scale feasibility study based on standard addition experiments involving natural plant biomass was conducted using multivariate calibration (Partial Least Squares Regression, PLS-R) of acoustic signatures against dry matter content (total solids, TS). Prediction...... performance of the optimised process implementation was evaluated using independent test set validation, with estimates of accuracy (slope of predicted vs. reference values) and precision (squared correlation coefficient, r2) of 0.94 and 0.97 respectively, with RMSEP of 0.32% w/w (RMSEPrel = 3...

  16. Investigation of production method, geographical origin and species authentication in commercially relevant shrimps using stable isotope ratio and/or multi-element analyses combined with chemometrics: an exploratory analysis.

    Science.gov (United States)

    Ortea, Ignacio; Gallardo, José M

    2015-03-01

    Three factors defining the traceability of a food product are production method (wild or farmed), geographical origin and biological species, which have to be checked and guaranteed, not only in order to avoid mislabelling and commercial fraud, but also to address food safety issues and to comply with legal regulations. The aim of this study was to determine whether these three factors could be differentiated in shrimps using stable isotope ratio analysis of carbon and nitrogen and/or multi-element composition. Different multivariate statistics methods were applied to different data subsets in order to evaluate their performance in terms of classification or predictive ability. Although the success rates varied depending on the dataset used, the combination of both techniques allowed the correct classification of 100% of the samples according to their actual origin and method of production, and 93.5% according to biological species. Even though further studies including a larger number of samples in each group are needed in order to validate these findings, we can conclude that these methodologies should be considered for studies regarding seafood product authenticity. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Spatial Air Quality Modelling Using Chemometrics Techniques: A Case Study in Peninsular Malaysia

    International Nuclear Information System (INIS)

    Azman Azid; Hafizan Juahir; Mohammad Azizi Amran; Zarizal Suhaili; Mohamad Romizan Osman; Asyaari Muhamad; Asyaari Muhamad; Ismail Zainal Abidin; Nur Hishaam Sulaiman; Ahmad Shakir Mohd Saudi

    2015-01-01

    This study shows the effectiveness of hierarchical agglomerative cluster analysis (HACA), discriminant analysis (DA), principal component analysis (PCA), and multiple linear regressions (MLR) for assessment of air quality data and recognition of air pollution sources. 12 months data (January-December 2007) consisting of 14 stations in Peninsular Malaysia with 14 parameters were applied. Three significant clusters - low pollution source (LPS), moderate pollution source (MPS), and slightly high pollution source (SHPS) were generated via HACA. Forward stepwise of DA managed to discriminate eight variables, whereas backward stepwise of DA managed to discriminate nine variables out of fourteen variables. The PCA and FA results show the main contributor of air pollution in Peninsular Malaysia is the combustion of fossil fuel from industrial activities, transportation and agriculture systems. Four MLR models show that PM 10 account as the most and the highest pollution contributor to Malaysian air quality. From the study, it can be stipulated that the application of chemometrics techniques can disclose meaningful information on the spatial variability of a large and complex air quality data. A clearer review about the air quality and a novelty design of air quality monitoring network for better management of air pollution can be achieved via these methods. (author)

  18. Differentiation of Crataegus spp. guided by nuclear magnetic resonance spectrometry with chemometric analyses.

    Science.gov (United States)

    Lund, Jensen A; Brown, Paula N; Shipley, Paul R

    2017-09-01

    For compliance with US Current Good Manufacturing Practice regulations for dietary supplements, manufacturers must provide identity of source plant material. Despite the popularity of hawthorn as a dietary supplement, relatively little is known about the comparative phytochemistry of different hawthorn species, and in particular North American hawthorns. The combination of NMR spectrometry with chemometric analyses offers an innovative approach to differentiating hawthorn species and exploring the phytochemistry. Two European and two North American species, harvested from a farm trial in late summer 2008, were analyzed by standard 1D 1 H and J-resolved (JRES) experiments. The data were preprocessed and modelled by principal component analysis (PCA). A supervised model was then generated by partial least squares-discriminant analysis (PLS-DA) for classification and evaluated by cross validation. Supervised random forests models were constructed from the dataset to explore the potential of machine learning for identification of unique patterns across species. 1D 1 H NMR data yielded increased differentiation over the JRES data. The random forests results correlated with PLS-DA results and outperformed PLS-DA in classification accuracy. In all of these analyses differentiation of the Crataegus spp. was best achieved by focusing on the NMR spectral region that contains signals unique to plant phenolic compounds. Identification of potentially significant metabolites for differentiation between species was approached using univariate techniques including significance analysis of microarrays and Kruskall-Wallis tests. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Spatial assessment of water quality using chemometrics in the Pearl River Estuary, China

    Science.gov (United States)

    Wu, Meilin; Wang, Youshao; Dong, Junde; Sun, Fulin; Wang, Yutu; Hong, Yiguo

    2017-03-01

    A cruise was commissioned in the summer of 2009 to evaluate water quality in the Pearl River Estuary (PRE). Chemometrics such as Principal Component Analysis (PCA), Cluster analysis (CA) and Self-Organizing Map (SOM) were employed to identify anthropogenic and natural influences on estuary water quality. The scores of stations in the surface layer in the first principal component (PC1) were related to NH4-N, PO4-P, NO2-N, NO3-N, TP, and Chlorophyll a while salinity, turbidity, and SiO3-Si in the second principal component (PC2). Similarly, the scores of stations in the bottom layers in PC1 were related to PO4-P, NO2-N, NO3-N, and TP, while salinity, Chlorophyll a, NH4-N, and SiO3-Si in PC2. Results of the PCA identified the spatial distribution of the surface and bottom water quality, namely the Guangzhou urban reach, Middle reach, and Lower reach of the estuary. Both cluster analysis and PCA produced the similar results. Self-organizing map delineated the Guangzhou urban reach of the Pearl River that was mainly influenced by human activities. The middle and lower reaches of the PRE were mainly influenced by the waters in the South China Sea. The information extracted by PCA, CA, and SOM would be very useful to regional agencies in developing a strategy to carry out scientific plans for resource use based on marine system functions.

  20. Evaluation of chemical components and properties of the jujube fruit using near infrared spectroscopy and chemometrics.

    Science.gov (United States)

    Guo, Ying; Ni, Yongnian; Kokot, Serge

    2016-01-15

    Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of spectra of the jujube (Zizyphus jujuba Mill.) fruit samples from four geographical regions. Prediction models were developed for the quantitative prediction of the contents of jujube fruit, i.e., total sugar, total acid, total phenolic content, and total antioxidant activity. Four pattern recognition methods, principal component analysis (PCA), linear discriminant analysis (LDA), least squares-support vector machines (LS-SVM), and back propagation-artificial neural networks (BP-ANN), were used for the geographical origin classification. Furthermore, three multivariate calibration models based on the standard normal variate (SNV) pretreated NIR spectroscopy, partial least squares (PLS), BP-ANN, and LS-SVM were constructed for quantitative analysis of the four analytes described above. PCA provided a useful qualitative plot of the four types of NIR spectra from the fruit. The LS-SVM model produced best quantitative prediction results. Thus, NIR spectroscopy in conjunction with chemometrics, is a very useful and rapid technique for the discrimination of jujube fruit. Copyright © 2015 Elsevier B.V. All rights reserved.

  1. Characterization and authentication of Spanish PDO wine vinegars using multidimensional fluorescence and chemometrics.

    Science.gov (United States)

    Ríos-Reina, Rocío; Elcoroaristizabal, Saioa; Ocaña-González, Juan A; García-González, Diego L; Amigo, José M; Callejón, Raquel M

    2017-09-01

    This work assesses the potential of multidimensional fluorescence spectroscopy combined with chemometrics for characterization and authentication of Spanish Protected Designation of Origin (PDO) wine vinegars. Seventy-nine vinegars of different categories (aged and sweet) belonging to the Spanish PDOs "Vinagre de Jerez", "Vinagre de Montilla-Moriles" and "Vinagre de Condado de Huelva", were analyzed by excitation-emission fluorescence spectroscopy. A visual assessment of fluorescence landscapes pointed out different trends with vinegar categories. PARAllel FACtor analysis (PARAFAC) extracted the potential fluorophores and their values in the PDO vinegars. This information, coupled with different classification methods (Partial Least Square Discrimination Analysis "PLS-DA" and Support Vectors Machines "SVM"), was able to discriminate the wine vinegar category within each PDO, for which SVM models obtained better results (>92% of classification). In each category, SVM also allows the differentiation between PDOs. The proposed methodology could be used as an analysis method for the authentication of Spanish PDO wine vinegars. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Targeted and non-targeted detection of lemon juice adulteration by LC-MS and chemometrics.

    Science.gov (United States)

    Wang, Zhengfang; Jablonski, Joseph E

    2016-01-01

    Economically motivated adulteration (EMA) of lemon juice was detected by LC-MS and principal component analysis (PCA). Twenty-two batches of freshly squeezed lemon juice were adulterated by adding an aqueous solution containing 5% citric acid and 6% sucrose to pure lemon juice to obtain 30%, 60% and 100% lemon juice samples. Their total titratable acidities, °Brix and pH values were measured, and then all the lemon juice samples were subject to LC-MS analysis. Concentrations of hesperidin and eriocitrin, major phenolic components of lemon juice, were quantified. The PCA score plots for LC-MS datasets were used to preview the classification of pure and adulterated lemon juice samples. Results showed a large inherent variability in the chemical properties among 22 batches of 100% lemon juice samples. Measurement or quantitation of one or several chemical properties (targeted detection) was not effective in detecting lemon juice adulteration. However, by using the LC-MS datasets, including both chromatographic and mass spectrometric information, 100% lemon juice samples were successfully differentiated from adulterated samples containing 30% lemon juice in the PCA score plot. LC-MS coupled with chemometric analysis can be a complement to existing methods for detecting juice adulteration.

  3. Nondestructive determination of compound amoxicillin powder by NIR spectroscopy with the aid of chemometrics

    Science.gov (United States)

    Qu, Nan; Zhu, Mingchao; Mi, Hong; Dou, Ying; Ren, Yulin

    2008-10-01

    Near-infrared (NIR) spectroscopy, in combination with chemometrics, enables nondestructive analysis of solid samples without time-consuming sample preparation methods. A new method for the nondestructive determination of compound amoxicillin powder drug via NIR spectroscopy combined with an improved neural network model based on principal component analysis (PCA) and radial basis function (RBF) neural networks is investigated. The PCA technique is applied to extraction relevant features from lots of spectra data in order to reduce the input variables of the RBF neural networks. Various optimum principal component analysis-radial basis function (PCA-RBF) network models based on conventional spectra and preprocessing spectra (standard normal variate (SNV) and multiplicative scatter correction (MSC)) have been established and compared. Principal component regression (PCR) and partial least squares (PLS) multivariate calibrations are also used, which are compared with PCA-RBF neural networks. Experiment results show that the proposed PCA-RBF method is more efficient than PCR and PLS multivariate calibrations. And the PCA-RBF approach with SNV preprocessing spectra is found to provide the best performance.

  4. Botanical discrimination of Greek unifloral honeys with physico-chemical and chemometric analyses.

    Science.gov (United States)

    Karabagias, Ioannis K; Badeka, Anastasia V; Kontakos, Stavros; Karabournioti, Sofia; Kontominas, Michael G

    2014-12-15

    The aim of the present study was to investigate the possibility of characterisation and classification of Greek unifloral honeys (pine, thyme, fir and orange blossom) according to botanical origin using volatile compounds, conventional physico-chemical parameters and chemometric analyses (MANOVA and Linear Discriminant Analysis). For this purpose, 119 honey samples were collected during the harvesting period 2011 from 14 different regions in Greece known to produce unifloral honey of good quality. Physico-chemical analysis included the identification and semi quantification of fifty five volatile compounds performed by Headspace Solid Phase Microextraction coupled to gas chromatography/mass spectroscopy and the determination of conventional quality parameters such as pH, free, lactonic, total acidity, electrical conductivity, moisture, ash, lactonic/free acidity ratio and colour parameters L, a, b. Results showed that using 40 diverse variables (30 volatile compounds of different classes and 10 physico-chemical parameters) the honey samples were satisfactorily classified according to botanical origin using volatile compounds (84.0% correct prediction), physicochemical parameters (97.5% correct prediction), and the combination of both (95.8% correct prediction) indicating that multi element analysis comprises a powerful tool for honey discrimination purposes. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Evaluation of chemical components and properties of the jujube fruit using near infrared spectroscopy and chemometrics

    Science.gov (United States)

    Guo, Ying; Ni, Yongnian; Kokot, Serge

    2016-01-01

    Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of spectra of the jujube (Zizyphus jujuba Mill.) fruit samples from four geographical regions. Prediction models were developed for the quantitative prediction of the contents of jujube fruit, i.e., total sugar, total acid, total phenolic content, and total antioxidant activity. Four pattern recognition methods, principal component analysis (PCA), linear discriminant analysis (LDA), least squares-support vector machines (LS-SVM), and back propagation-artificial neural networks (BP-ANN), were used for the geographical origin classification. Furthermore, three multivariate calibration models based on the standard normal variate (SNV) pretreated NIR spectroscopy, partial least squares (PLS), BP-ANN, and LS-SVM were constructed for quantitative analysis of the four analytes described above. PCA provided a useful qualitative plot of the four types of NIR spectra from the fruit. The LS-SVM model produced best quantitative prediction results. Thus, NIR spectroscopy in conjunction with chemometrics, is a very useful and rapid technique for the discrimination of jujube fruit.

  6. Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data.

    Science.gov (United States)

    Tomazzoli, Maíra Maciel; Pai Neto, Remi Dal; Moresco, Rodolfo; Westphal, Larissa; Zeggio, Amélia Regina Somensi; Specht, Leandro; Costa, Christopher; Rocha, Miguel; Maraschin, Marcelo

    2015-10-21

    Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plant's resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis' chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds (λ = 280-400ηm), suggesting that besides the biological activities of those

  7. Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data.

    Science.gov (United States)

    Tomazzoli, Maíra M; Pai Neto, Remi D; Moresco, Rodolfo; Westphal, Larissa; Zeggio, Amelia R S; Specht, Leandro; Costa, Christopher; Rocha, Miguel; Maraschin, Marcelo

    2015-12-01

    Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plant's resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( λ= 280-400 ηm), suggesting that besides the biological activities of those

  8. Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

    Directory of Open Access Journals (Sweden)

    Tomazzoli Maíra M.

    2015-12-01

    Full Text Available Propolis is a chemically complex biomass produced by honeybees (Apis mellifera from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plant’s resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (abiotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis scanning spectrophotometry of hydroalcoholic extracts (HE of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter and 2015 (summer and autumn in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA and hierarchical clustering analysis (HCA supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( λ= 280-400 ηm, suggesting that besides the biological

  9. 1H HRMAS NMR spectroscopy and chemometrics for evaluation of metabolic changes in citrus sinensis Caused by Xanthomonas axonopodis pv. citri

    International Nuclear Information System (INIS)

    Silva, Lorena M.A.; Alves Filho, Elenilson G.; Choze, Rafael; Liao, Luciano M.; Alcantara, Glaucia B.

    2012-01-01

    Xanthomonas axonopodis (Xac) bacterium causes one of the most feared and untreatable diseases in citriculture: citrus canker. To understand the response mechanisms of orange trees when attacked by Xac, leaves and fruits of Citrus sinensis were directly evaluated by HRMAS NMR (high resolution magic angle spinning nuclear magnetic resonance) spectroscopy. This technique allows the analysis of samples without laborious pre-treatments and also allows access to important information about chemical composition of samples. The orange tree leaves and fruit peels investigated in this study demonstrated the biochemical changes caused by Xac. Aided by chemometric analysis, the HRMAS NMR results show relevant changes in amino acids, carbohydrates, organic acids and terpenoids content. (author)

  10. Discrimination and identification of RDX/PETN explosives by chemometrics applied to terahertz time-domain spectral imaging

    Science.gov (United States)

    Bou-Sleiman, J.; Perraud, J.-B.; Bousquet, B.; Guillet, J.-P.; Palka, N.; Mounaix, P.

    2015-10-01

    Detection of explosives has always been a priority for homeland security. Jointly, terahertz spectroscopy and imaging are emerging and promising candidates as contactless and safe systems. In this work, we treated data resulting from hyperspectral imaging obtained by THz-time domain spectroscopy, with chemometric tools. We found efficient identification and sorting of targeted explosives in the case of pure and mixture samples. In this aim, we applied to images Principal Component Analysis (PCA) to discriminate between RDX, PETN and mixtures of the two materials, using the absorbance as the key-parameter. Then we applied Partial Least Squares-Discriminant Analysis (PLS-DA) to each pixel of the hyperspectral images to sort the explosives into different classes. The results clearly show successful identification and categorization of the explosives under study.

  11. An integrated approach combining HPLC, GC/MS, NIRS, and chemometrics for the geographical discrimination and commercial categorization of saffron.

    Science.gov (United States)

    Liu, Jiangdi; Chen, Na; Yang, Jian; Yang, Bin; Ouyang, Zhen; Wu, Changxun; Yuan, Yuan; Wang, Weihao; Chen, Min

    2018-07-01

    In the present study, an integrated approach combining HPLC/DAD, GC/MS, near infrared (NIR) spectroscopy, and chemometrics was used to geographically discriminate saffron samples from Iran and China. Chinese and Iranian samples can be well-separated based on HPLC data analysed by a principal component analysis and an orthogonal partial least squares discriminant analysis. Picrocrocin and two types of crocins were found to be the discriminating variables, and the Chinese samples had higher contents of safranal and picrocrocin but lower cis-crocin 3Gg, kaempferol-3-O-sophoroside and isophorone. Furthermore, an NIR method was successfully established to rapidly distinguish the Chinese and Iranian samples. The relationship between an ISO standard and the contents of the chemical indices was also studied. The results indicated that the ISO standard should be revised, especially for analysing safranal. Copyright © 2018 Elsevier Ltd. All rights reserved.

  12. Cancer Discrimination Using Fourier Transform Near-Infrared Spectroscopy with Chemometric Models

    Directory of Open Access Journals (Sweden)

    Hui Chen

    2015-01-01

    Full Text Available Near-infrared (NIR spectroscopy technique offers many potential advantages as tool for biomedical analysis since it enables the subtle biochemical signatures related to pathology to be detected and extracted. In conjunction with advanced chemometrics, NIR spectroscopy opens the possibility of their use in cancer diagnosis. The study focuses on the application of near-infrared (NIR spectroscopy and classification models for discriminating colorectal cancer. A total of 107 surgical specimens and a corresponding NIR diffuse reflection spectral dataset were prepared. Three preprocessing methods were attempted and least-squares support vector machine (LS-SVM was used to build a classification model. The hybrid preprocessing of first derivative and principal component analysis (PCA resulted in the best LS-SVM model with the sensitivity and specificity of 0.96 and 0.96 for the training and 0.94 and 0.96 for test sets, respectively. The similarity performance on both subsets indicated that overfitting did not occur, assuring the robustness and reliability of the developed LS-SVM model. The area of receiver operating characteristic (ROC curve was 0.99, demonstrating once again the high prediction power of the model. The result confirms the applicability of the combination of NIR spectroscopy, LS-SVM, PCA, and first derivative preprocessing for cancer diagnosis.

  13. Investigation of the chemical composition-antibacterial activity relationship of essential oils by chemometric methods.

    Science.gov (United States)

    Miladinović, Dragoljub L; Ilić, Budimir S; Mihajilov-Krstev, Tatjana M; Nikolić, Nikola D; Miladinović, Ljiljana C; Cvetković, Olga G

    2012-05-01

    The antibacterial effects of Thymus vulgaris (Lamiaceae), Lavandula angustifolia (Lamiaceae), and Calamintha nepeta (Lamiaceae) Savi subsp. nepeta var. subisodonda (Borb.) Hayek essential oils on five different bacteria were estimated. Laboratory control strain and clinical isolates from different pathogenic media were researched by broth microdilution method, with an emphasis on a chemical composition-antibacterial activity relationship. The main constituents of thyme oil were thymol (59.95%) and p-cymene (18.34%). Linalool acetate (38.23%) and β-linalool (35.01%) were main compounds in lavender oil. C. nepeta essential oil was characterized by a high percentage of piperitone oxide (59.07%) and limonene (9.05%). Essential oils have been found to have antimicrobial activity against all tested microorganisms. Classification and comparison of essential oils on the basis of their chemical composition and antibacterial activity were made by utilization of appropriate chemometric methods. The chemical principal component analysis (PCA) and hierachical cluster analysis (HCA) separated essential oils into two groups and two sub-groups. Thyme essential oil forms separate chemical HCA group and exhibits highest antibacterial activity, similar to tetracycline. Essential oils of lavender and C. nepeta in the same chemical HCA group were classified in different groups, within antibacterial PCA and HCA analyses. Lavender oil exhibits higher antibacterial ability in comparison with C. nepeta essential oil, probably based on the concept of synergistic activity of essential oil components.

  14. Chemometric dissimilarity in nutritive value of popularly consumed Nigerian brown and white common beans.

    Science.gov (United States)

    Moyib, Oluwasayo Kehinde; Alashiri, Ganiyy Olasunkanmi; Adejoye, Oluseyi Damilola

    2015-01-01

    Brown beans are the preferred varieties over the white beans in Nigeria due to their assumed richer nutrients. This study was aimed at assessing and characterising some popular Nigerian common beans for their nutritive value based on seed coat colour. Three varieties, each, of Nigerian brown and white beans, and one, each, of French bean and soybean were analysed for 19 nutrients. Z-statistics test showed that Nigerian beans are nutritionally analogous to French bean and soybean. Analysis of variance showed that seed coat colour varied with proximate nutrients, Ca, Fe, and Vit C. Chemometric analysis methods revealed superior beans for macro and micro nutrients and presented clearer groupings among the beans for seed coat colour. The study estimated a moderate genetic distance (GD) that will facilitate transfer of useful genes and intercrossing among the beans. It also offers an opportunity to integrate French bean and soybean into genetic improvement programs in Nigerian common beans. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Laser-induced breakdown spectroscopy and chemometrics for classification of toys relying on toxic elements

    Energy Technology Data Exchange (ETDEWEB)

    Godoi, Quienly [Departamento de Quimica, Universidade Federal de Sao Carlos, Rod. Washington Luis, km 235, 13565-905, Sao Carlos-SP (Brazil); Centro de Energia Nuclear na Agricultura, Universidade de Sao Paulo, Av. Centenario 303, 13416-000, Piracicaba-SP (Brazil); Leme, Flavio O.; Trevizan, Lilian C. [Centro de Energia Nuclear na Agricultura, Universidade de Sao Paulo, Av. Centenario 303, 13416-000, Piracicaba-SP (Brazil); Pereira Filho, Edenir R., E-mail: erpf@ufscar.br [Departamento de Quimica, Universidade Federal de Sao Carlos, Rod. Washington Luis, km 235, 13565-905, Sao Carlos-SP (Brazil); Rufini, Iolanda A. [Centro de Energia Nuclear na Agricultura, Universidade de Sao Paulo, Av. Centenario 303, 13416-000, Piracicaba-SP (Brazil); Santos, Dario [Universidade Federal de Sao Paulo, UNIFESP, Rua Prof. Artur Riedel 275, 09972-270, Diadema-SP (Brazil); Krug, Francisco J. [Centro de Energia Nuclear na Agricultura, Universidade de Sao Paulo, Av. Centenario 303, 13416-000, Piracicaba-SP (Brazil)

    2011-02-15

    Quality control of toys for avoiding children exposure to potentially toxic elements is of utmost relevance and it is a common requirement in national and/or international norms for health and safety reasons. Laser-induced breakdown spectroscopy (LIBS) was recently evaluated at authors' laboratory for direct analysis of plastic toys and one of the main difficulties for the determination of Cd, Cr and Pb was the variety of mixtures and types of polymers. As most norms rely on migration (lixiviation) protocols, chemometric classification models from LIBS spectra were tested for sampling toys that present potential risk of Cd, Cr and Pb contamination. The classification models were generated from the emission spectra of 51 polymeric toys and by using Partial Least Squares - Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogy (SIMCA) and K-Nearest Neighbor (KNN). The classification models and validations were carried out with 40 and 11 test samples, respectively. Best results were obtained when KNN was used, with corrected predictions varying from 95% for Cd to 100% for Cr and Pb.

  16. Rapid authentication of edible bird's nest by FTIR spectroscopy combined with chemometrics.

    Science.gov (United States)

    Guo, Lili; Wu, Yajun; Liu, Mingchang; Ge, Yiqiang; Chen, Ying

    2017-11-30

    Edible bird's nests (EBNs) have been traditionally regarded as a kind of medicinal and healthy food in China. For economic reasons, they are frequently subjected to adulteration with some cheaper substitutes, such as Tremella fungus, agar, fried pigskin, and egg white. As a kind of precious and functional product, it is necessary to establish a robust method for the rapid authentication of EBNs with small amounts of samples by simple processes. In this study, the Fourier transform infrared spectroscopy (FTIR) system was utilized and its feasibility for identification of EBNs was verified. FTIR spectra data of authentic and adulterated EBNs were analyzed by chemometrics analyses including principal component analysis, linear discriminant analysis (LDA), support vector machine (SVM) and one-class partial least squares (OCPLS). The results showed that the established LDA and SVM models performed well and had satisfactory classification ability, with the former 94.12% and the latter 100%. The OCPLS model was developed with prediction sensitivity of 0.937 and specificity of 0.886. Further detection of commercial EBN samples confirmed these results. FTIR is applicable in the scene of rapid authentication of EBNs, especially for quality supervision departments, entry-exit inspection and quarantine, and customs administration. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  17. Automatic Discrimination of the Geographical Origins of Milks by Excitation-Emission Fluorescence Spectrometry and Chemometrics

    Science.gov (United States)

    Xu, Lu; Deng, De-Hua; Cai, Chen-Bo; Yang, Hong-Wei

    2011-01-01

    This paper presents the automatic discrimination of geographical origins of milks from Western Yunnan Plateau areas and eastern China by excitation-emission fluorescence spectrometry and chemometrics. Genuine plateau milks (n = 60) and milks from eastern China (n = 89) are scanned in the regions of 180–300 nm for excitation and 200–800 nm for emission. Different options of data analysis are investigated and compared in terms of their performance in discriminating milks of different geographical origins: (1) two-way partial least squares discriminant analysis (PLSDA) based on excitation and emission spectra, respectively; (2) two-way PLSDA based on fusion of excitation and emission spectra; (3) three-way PLSDA based on excitation-emission matrix spectra. The two-way PLSDA methods with excitation spectra, emission spectra, and fusion of excitation and emission spectra correctly classify 91.3%, 88.6%, and 95.3% of the milk samples, respectively; while the total accuracy of three-way PLSDA is 96.0%. The results demonstrate the two-way data combining excitation and emission spectra are sufficient to characterize and identify the plateau milks. Considering both model accuracy and the analytical time required, two-way PLS-DA with fusion of excitation and emission spectra is recommended as a reliable and quick method to discriminate plateau milks from ordinary milks. PMID:21904469

  18. Optimisation of the formulation of a bubble bath by a chemometric approach market segmentation and optimisation.

    Science.gov (United States)

    Marengo, Emilio; Robotti, Elisa; Gennaro, Maria Carla; Bertetto, Mariella

    2003-03-01

    The optimisation of the formulation of a commercial bubble bath was performed by chemometric analysis of Panel Tests results. A first Panel Test was performed to choose the best essence, among four proposed to the consumers; the best essence chosen was used in the revised commercial bubble bath. Afterwards, the effect of changing the amount of four components (the amount of primary surfactant, the essence, the hydratant and the colouring agent) of the bubble bath was studied by a fractional factorial design. The segmentation of the bubble bath market was performed by a second Panel Test, in which the consumers were requested to evaluate the samples coming from the experimental design. The results were then treated by Principal Component Analysis. The market had two segments: people preferring a product with a rich formulation and people preferring a poor product. The final target, i.e. the optimisation of the formulation for each segment, was obtained by the calculation of regression models relating the subjective evaluations given by the Panel and the compositions of the samples. The regression models allowed to identify the best formulations for the two segments ofthe market.

  19. Quality assessment of crude and processed ginger by high-performance liquid chromatography with diode array detection and mass spectrometry combined with chemometrics.

    Science.gov (United States)

    Deng, Xianmei; Yu, Jiangyong; Zhao, Ming; Zhao, Bin; Xue, Xingyang; Che, ChunTao; Meng, Jiang; Wang, Shumei

    2015-09-01

    A sensitive, simple, and validated high-performance liquid chromatography with diode array detection and mass spectrometry detection method was developed for three ginger-based traditional Chinese herbal drugs, Zingiberis Rhizoma, Zingiberis Rhizome Preparatum, and Zingiberis Rhizome Carbonisata. Chemometrics methods, such as principal component analysis, hierarchical cluster analysis, and analysis of variance, were also employed in the data analysis. The results clearly revealed significant differences among Zingiberis Rhizoma, Zingiberis Rhizome Preparatum, and Zingiberis Rhizome Carbonisata, indicating variations in their chemical compositions during the processing, which may elucidate the relationship of the thermal treatment with the change of the constituents and interpret their different clinical uses. Furthermore, the sample consistency of Zingiberis Rhizoma, Zingiberis Rhizome Preparatum, and Zingiberis Rhizome Carbonisata can also be visualized by high-performance liquid chromatography with diode array detection and mass spectrometry analysis followed by principal component analysis/hierarchical cluster analysis. The comprehensive strategy of liquid chromatography with mass spectrometry analysis coupled with chemometrics should be useful in quality assurance for ginger-based herbal drugs and other herbal medicines. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. NMR spectroscopy and chemometrics-based analysis of grapevine

    NARCIS (Netherlands)

    Ali, Kashif

    2011-01-01

    Undoubtedly, grapes and wine are globally the most important fruit and food commodities, respectively. The first objective of this research is to optimize an extraction protocol suitable for grape metabolic profiling followed by the application of that protocol to perform metabolic characterization

  1. Principal Component Analysis: Most Favourite Tool in Chemometrics

    Indian Academy of Sciences (India)

    Data compression by. PCA involves finding a new space spanned by fewer number of dimensions over which original data set is projected. The dimensions of the ... The variable that ex- plains the maximum variation is called the first principal compo- nent. Second principal component explains the second highest variation ...

  2. Chemometric analysis of acid-base measurements : a multivariate approach

    NARCIS (Netherlands)

    M. Hekking (Marcel)

    1999-01-01

    textabstractMedicine is an art and a science in the service of fellow human beings. On the basis of collected empirical data and information, clinicians select specific diagnoses, rule out other differential diagnoses and eventually make decisions about which and how specific therapeutic

  3. Principal Component Analysis: Most Favourite Tool in Chemometrics

    Indian Academy of Sciences (India)

    Resonance – Journal of Science Education. Current Issue : Vol. 23, Issue 2 · Current Issue Volume 23 | Issue 2. February 2018. Home · Volumes & Issues · Categories · Special Issues · Search · Editorial Board · Information for Authors · Subscription ...

  4. Chemometrics-assisted solid-state characterization of pharmaceutically relevant materials. Polymorphic substances.

    Science.gov (United States)

    Calvo, Natalia L; Maggio, Rubén M; Kaufman, Teodoro S

    2018-01-05

    Current regulations command to properly characterize pharmaceutically relevant solid systems. Chemometrics comprise a range of valuable tools, suitable to process large amounts of data and extract valuable information hidden in their structure. This review aims to detail the results of the fruitful association between analytical techniques and chemometrics methods, focusing on those which help to gain insight into the characteristics of drug polymorphism as an important aspect of the solid state of bulk drugs and drug products. Hence, the combination of Raman, terahertz, mid- and near- infrared spectroscopies, as well as instrumental signals resulting from X-ray powder diffraction, 13 C solid state nuclear magnetic resonance spectroscopy and thermal methods with quali-and quantitative chemometrics methodologies are examined. The main issues reviewed, concerning pharmaceutical drug polymorphism, include the use of chemometrics-based approaches to perform polymorph classification and assignment of polymorphic identity, as well as the determination of given polymorphs in simple mixtures and complex systems. Aspects such as the solvation/desolvation of solids, phase transformation, crystallinity and the recrystallization from the amorphous state are also discussed. A brief perspective of the field for the next future is provided, based on the developments of the last decade and the current state of the art of analytical instrumentation and chemometrics methodologies. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Fast determination of beef quality parameters with time-domain nuclear magnetic resonance spectroscopy and chemometrics.

    Science.gov (United States)

    Pereira, Fabíola Manhas Verbi; Bertelli Pflanzer, Sérgio; Gomig, Thaísa; Lugnani Gomes, Carolina; de Felício, Pedro Eduardo; Colnago, Luiz Alberto

    2013-04-15

    The noteworthy of this study is to predict seven quality parameters for beef samples using time-domain nuclear magnetic resonance (TD-NMR) relaxometry data and multivariate models. Samples from 61 Bonsmara heifers were separated into five groups based on genetic (breeding composition) and feed system (grain and grass feed). Seven sample parameters were analyzed by reference methods; among them, three sensorial parameters, flavor, juiciness and tenderness and four physicochemical parameters, cooking loss, fat and moisture content and instrumental tenderness using Warner Bratzler shear force (WBSF). The raw beef samples of the same animals were analyzed by TD-NMR relaxometry using Carr-Purcell-Meiboom-Gill (CPMG) and Continuous Wave-Free Precession (CWFP) sequences. Regression models computed by partial least squares (PLS) chemometric technique using CPMG and CWFP data and the results of the classical analysis were constructed. The results allowed for the prediction of aforementioned seven properties. The predictive ability of the method was evaluated using the root mean square error (RMSE) for the calibration (RMSEC) and validation (RMSEP) data sets. The reference and predicted values showed no significant differences at a 95% confidence level. Copyright © 2013 Elsevier B.V. All rights reserved.

  6. Identification and Quantitation of Melamine in Milk by Near-Infrared Spectroscopy and Chemometrics

    Directory of Open Access Journals (Sweden)

    Tong Wu

    2016-01-01

    Full Text Available Melamine is a nitrogen-rich substance and has been illegally used to increase the apparent protein content in food products such as milk. Therefore, it is imperative to develop sensitive and reliable analytical methods to determine melamine in human foods. Current analytical methods for melamine are mainly chromatography-based methods, which are time-consuming and expensive and require complex pretreatment and well-trained technicians. The present paper investigated the feasibility of using near-infrared (NIR spectroscopy and chemometrics for identifying and quantifying melamine in liquor milk. A total of 75 samples were prepared. Uninformative variable elimination-partial least square (UVE-PLS and partial least squares-discriminant analysis (PLS-DA were used to construct quantitative and qualitative models, respectively. Based on the ratio of performance to standard deviate (RPD, UVE-PLS model with 3 components resulted in a better solution. The PLS-DA model achieved an accuracy of 100% and outperformed the optimal reference model of soft independent modeling of class analogy (SIMCA. Such a method can serve as a potential tool for rapid screening of melamine in milk products.

  7. Discrimination and Measurements of Three Flavonols with Similar Structure Using Terahertz Spectroscopy and Chemometrics

    Science.gov (United States)

    Yan, Ling; Liu, Changhong; Qu, Hao; Liu, Wei; Zhang, Yan; Yang, Jianbo; Zheng, Lei

    2018-03-01

    Terahertz (THz) technique, a recently developed spectral method, has been researched and used for the rapid discrimination and measurements of food compositions due to its low-energy and non-ionizing characteristics. In this study, THz spectroscopy combined with chemometrics has been utilized for qualitative and quantitative analysis of myricetin, quercetin, and kaempferol with concentrations of 0.025, 0.05, and 0.1 mg/mL. The qualitative discrimination was achieved by KNN, ELM, and RF models with the spectra pre-treatments. An excellent discrimination (100% CCR in the prediction set) could be achieved using the RF model. Furthermore, the quantitative analyses were performed by partial least square regression (PLSR) and least squares support vector machine (LS-SVM). Comparing to the PLSR models, the LS-SVM yielded better results with low RMSEP (0.0044, 0.0039, and 0.0048), higher Rp (0.9601, 0.9688, and 0.9359), and higher RPD (8.6272, 9.6333, and 7.9083) for myricetin, quercetin, and kaempferol, respectively. Our results demonstrate that THz spectroscopy technique is a powerful tool for identification of three flavonols with similar chemical structures and quantitative determination of their concentrations.

  8. Early detection of germinated wheat grains using terahertz image and chemometrics

    Science.gov (United States)

    Jiang, Yuying; Ge, Hongyi; Lian, Feiyu; Zhang, Yuan; Xia, Shanhong

    2016-02-01

    In this paper, we propose a feasible tool that uses a terahertz (THz) imaging system for identifying wheat grains at different stages of germination. The THz spectra of the main changed components of wheat grains, maltose and starch, which were obtained by THz time spectroscopy, were distinctly different. Used for original data compression and feature extraction, principal component analysis (PCA) revealed the changes that occurred in the inner chemical structure during germination. Two thresholds, one indicating the start of the release of α-amylase and the second when it reaches the steady state, were obtained through the first five score images. Thus, the first five PCs were input for the partial least-squares regression (PLSR), least-squares support vector machine (LS-SVM), and back-propagation neural network (BPNN) models, which were used to classify seven different germination times between 0 and 48 h, with a prediction accuracy of 92.85%, 93.57%, and 90.71%, respectively. The experimental results indicated that the combination of THz imaging technology and chemometrics could be a new effective way to discriminate wheat grains at the early germination stage of approximately 6 h.

  9. Mebendazole crystal forms in tablet formulations. An ATR-FTIR/chemometrics approach to polymorph assignment.

    Science.gov (United States)

    Calvo, Natalia L; Kaufman, Teodoro S; Maggio, Rubén M

    2016-04-15

    Structural polymorphism of active pharmaceutical ingredients (API) is a relevant concern for the modern pharmaceutical industry, since different polymorphic forms may display dissimilar properties, critically affecting the performance of the corresponding drug products. Mebendazole (MEB) is a widely used broad spectrum anthelmintic drug of the benzimidazole class, which exhibits structural polymorphism (Forms A-C). Form C, which displays the best pharmaceutical profile, is the recommended one for clinical use. The polymorphs of MEB were prepared and characterized by spectroscopic, calorimetric and microscopic means. The polymorphs were employed to develop a suitable chemometrics-assisted sample display model based on the first two principal components of their ATR-FTIR spectra in the 4000-600 cm(-1) region. The model was internally and externally validated employing the leave-one-out procedure and an external validation set, respectively. Its suitability for revealing the polymorphic identity of MEB in tablets was successfully assessed analyzing commercial tablets under different physical forms (whole, powdered, dried, sieved and aged). It was concluded that the ATR-FTIR/PCA (principal component analysis) association is a fast, efficient and non-destructive technique for assigning the solid-state forms of MEB in its drug products, with minimum sample pre-treatment. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Spectroscopic investigations of crude oil and petroleum products in combination with chemometric methods

    International Nuclear Information System (INIS)

    Tuechler, W.

    1997-11-01

    In the present work, chemometric methods were used for investigations of crude oils and petroleum products by statistical evaluation of spectroscopic data. The spectroscopic information was obtained by 1 H-Nuclear Magnetic Resonance and infrared experiments. Research octane numbers (RON) and motor octane numbers (MON), representing important characteristics for knocking behavior,were calculated by multilinear regression. In the period of two years it was tested whether the precision of such models was negatively influenced by varying chemical composition of the commercial gasoline. A Partial Least Squares model (PLS) was created to calculate MON. The model based on infrared spectroscopic data in the spectral region of 1400 to 650 cm 1 . The standard deviation between PLS-method and the standard method ASTM D 2700 was 0,6. Another PLS-model in combination with spectroscopic data was used for calculating cetane numbers of diesel fuels. Using the spectral region of 1650 to 650 cm 1 the content of the cetane improver 2-ethyl-hexyl-nitrate could be detected. A standard deviation of 1,8 to ASTM D 613 has been achieved. An additional aim of the work was to identify crude oils by the means of principal component analysis of spectroscopic data in the near infrared region. The investigations included the determination of negative effects on data acquisition like varying temperature, water-, salt-, and sediment content. Furthermore, the density and the boiling yields in distillation of crude oils were calculated with PLS-models. (author)

  11. Comprehensive description of the photodegradation of bromophenols using chromatographic monitoring and chemometric tools.

    Science.gov (United States)

    Mas, Sílvia; Carbó, Albert; Lacorte, Sílvia; de Juan, Anna; Tauler, Romà

    2011-01-30

    A general procedure for the study of complex photodegradation processes of environmental pollutants based on chromatographic monitoring and chemometric method is proposed. The procedure consists of multiset data analysis of aliquots collected at different reaction times and injected in High-Performance Liquid Chromatography coupled to diode array detection and mass spectrometry (HPLC-DAD-MS). In this study, photodegradation of six bromophenols with different degrees of bromination has been investigated in order to find out their photodegradation pathways and kinetics and to show the potential of the procedure proposed. Multivariate curve resolution-alternating least squares (MCR-ALS) has been used to resolve chromatographic elution profiles and pure spectra of species involved in the photodegradation process and, hence, to elucidate the photodegradation mechanism and to propose the chemical structure of the main photoproducts. This study shows that chromatographic monitoring is the preferred option when photochemical systems with large number of components with similar spectra and kinetic evolution are analyzed. This work reveals the advantages of the double DAD and MS detection to provide mechanistic and structural information about these complex photodegradation processes. Copyright © 2010 Elsevier B.V. All rights reserved.

  12. Development and validation of NIR-chemometric methods for chemical and pharmaceutical characterization of meloxicam tablets.

    Science.gov (United States)

    Tomuta, Ioan; Iovanov, Rares; Bodoki, Ede; Vonica, Loredana

    2014-04-01

    Near-Infrared (NIR) spectroscopy is an important component of a Process Analytical Technology (PAT) toolbox and is a key technology for enabling the rapid analysis of pharmaceutical tablets. The aim of this research work was to develop and validate NIR-chemometric methods not only for the determination of active pharmaceutical ingredients content but also pharmaceutical properties (crushing strength, disintegration time) of meloxicam tablets. The development of the method for active content assay was performed on samples corresponding to 80%, 90%, 100%, 110% and 120% of meloxicam content and the development of the methods for pharmaceutical characterization was performed on samples prepared at seven different compression forces (ranging from 7 to 45 kN) using NIR transmission spectra of intact tablets and PLS as a regression method. The results show that the developed methods have good trueness, precision and accuracy and are appropriate for direct active content assay in tablets (ranging from 12 to 18 mg/tablet) and also for predicting crushing strength and disintegration time of intact meloxicam tablets. The comparative data show that the proposed methods are in good agreement with the reference methods currently used for the characterization of meloxicam tablets (HPLC-UV methods for the assay and European Pharmacopeia methods for determining the crushing strength and disintegration time). The results show the possibility to predict both chemical properties (active content) and physical/pharmaceutical properties (crushing strength and disintegration time) directly, without any sample preparation, from the same NIR transmission spectrum of meloxicam tablets.

  13. Dynamic surface-enhanced Raman spectroscopy and Chemometric methods for fast detection and intelligent identification of methamphetamine and 3, 4-Methylenedioxy methamphetamine in human urine

    Science.gov (United States)

    Weng, Shizhuang; Dong, Ronglu; Zhu, Zede; Zhang, Dongyan; Zhao, Jinling; Huang, Linsheng; Liang, Dong

    2018-01-01

    Conventional Surface-Enhanced Raman Spectroscopy (SERS) for fast detection of drugs in urine on the portable Raman spectrometer remains challenges because of low sensitivity and unreliable Raman signal, and spectra process with manual intervention. Here, we develop a novel detection method of drugs in urine using chemometric methods and dynamic SERS (D-SERS) with mPEG-SH coated gold nanorods (GNRs). D-SERS combined with the uniform GNRs can obtain giant enhancement, and the signal is also of high reproducibility. On the basis of the above advantages, we obtained the spectra of urine, urine with methamphetamine (MAMP), urine with 3, 4-Methylenedioxy Methamphetamine (MDMA) using D-SERS. Simultaneously, some chemometric methods were introduced for the intelligent and automatic analysis of spectra. Firstly, the spectra at the critical state were selected through using K-means. Then, the spectra were proposed by random forest (RF) with feature selection and principal component analysis (PCA) to develop the recognition model. And the identification accuracy of model were 100%, 98.7% and 96.7%, respectively. To validate the effect in practical issue further, the drug abusers'urine samples with 0.4, 3, 30 ppm MAMP were detected using D-SERS and identified by the classification model. The high recognition accuracy of > 92.0% can meet the demand of practical application. Additionally, the parameter optimization of RF classification model was simple. Compared with the general laboratory method, the detection process of urine's spectra using D-SERS only need 2 mins and 2 μL samples volume, and the identification of spectra based on chemometric methods can be finish in seconds. It is verified that the proposed approach can provide the accurate, convenient and rapid detection of drugs in urine.

  14. Chemometric approach for prediction of uranium pathways in the soil

    Energy Technology Data Exchange (ETDEWEB)

    Stojanovic, Mirjana; Nihajlovic, Marija; Petrovic, Jelena; Petrovic, Marija; Sostaric, Tanja; Milojkovic, Jelena [Inst. for Technology of Nuclear and Other Mineral Raw Materials, Belgrad (Serbia); Pezo, Lato [Univ. Belgrad (Serbia). Inst. of General and Physical Chemistry

    2014-10-01

    Understanding the effect of soil parameters (pH, Eh and organic and inorganic ligands availability) on uranium mobility under different geochemical conditions is fundamental for reliable prediction of its behaviour and fate in the environment. In this study, the impact of total and available phosphorus content, humus and acidity of Serbian agricultural soils on the content of total and available uranium were evaluated by Response Surface Methodology (RSM), second order polynomial regression models (SOPs) and artificial neural networks (ANNs). The performance of ANNs was compared with the performance of SOPs and experimental results. SOPs showed high coefficients of determination (0.785-0.956), while ANN model performed high prediction accuracy: 0.8893-0.904. According to the results, total and available uranium content in the soil were mostly affected by pH, statistically significant at p < 0.05 level. For the same responses the total phosphorus was found to be also very influential, statistically significant at p < 0.05 and p < 0.10 levels. The impact of available phosphorus and humus was much more influential on total and available uranium content, compared to total phosphorus content. Proposed chemometric approach will be very helpful in preserving the natural resources and practical application for risk assessment modeling of uranium environmental pathways.

  15. Design of natural food antioxidant ingredients through a chemometric approach.

    Science.gov (United States)

    Mendiola, Jose A; Martín-Alvarez, Pedro J; Señoráns, F Javier; Reglero, Guillermo; Capodicasa, Alessandro; Nazzaro, Filomena; Sada, Alfonso; Cifuentes, Alejandro; Ibáñez, Elena

    2010-01-27

    In the present work, an environmentally friendly extraction process using subcritical conditions has been tested to obtain potential natural food ingredients from natural sources such as plants, fruits, spirulina, propolis, and tuber, with the scope of substituting synthetic antioxidants, which are subject to regulation restrictions and might be harmful for human health. A full characterization has been undertaken from the chemical and biochemical point of view to be able to understand their mechanism of action. Thus, an analytical method for profiling the compounds responsible for the antioxidant activity has been used, allowing the simultaneous determination of water-soluble vitamins, fat-soluble vitamins, phenolic compounds, carotenoids, and chlorophylls in a single run. This information has been integrated and analyzed using a chemometrical approach to correlate the bioactive compounds profile with the antioxidant activity and thus to be able to predict antioxidant activities of complex formulations. As a further step, a simplex centroid mixture design has been tested to find the optimal formulation and to calculate the effect of the interaction among individual extracts in the mixture.

  16. Quality Evaluation and Chemical Markers Screening of Salvia miltiorrhiza Bge. (Danshen Based on HPLC Fingerprints and HPLC-MSn Coupled with Chemometrics

    Directory of Open Access Journals (Sweden)

    Wenyi Liang

    2017-03-01

    Full Text Available Danshen, the dried root of Salvia miltiorrhiza Bge., is a widely used commercially available herbal drug, and unstable quality of different samples is a current issue. This study focused on a comprehensive and systematic method combining fingerprints and chemical identification with chemometrics for discrimination and quality assessment of Danshen samples. Twenty-five samples were analyzed by HPLC-PAD and HPLC-MSn. Forty-nine components were identified and characteristic fragmentation regularities were summarized for further interpretation of bioactive components. Chemometric analysis was employed to differentiate samples and clarify the quality differences of Danshen including hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis. Consistent results were that the samples were divided into three categories which reflected the difference in quality of Danshen samples. By analyzing the reasons for sample classification, it was revealed that the processing method had a more obvious impact on sample classification than the geographical origin, it induced the different content of bioactive compounds and finally lead to different qualities. Cryptotanshinone, trijuganone B, and 15,16-dihydrotanshinone I were screened out as markers to distinguish samples by different processing methods. The developed strategy could provide a reference for evaluation and discrimination of other traditional herbal medicines.

  17. Chemometric evaluation of different experimental conditions on wheat (Triticum aestivum L.) development using liquid chromatography mass spectrometry (LC-MS) profiles of benzoxazinone derivatives.

    Science.gov (United States)

    Farrés, Mireia; Villagrasa, Marta; Eljarrat, Ethel; Barceló, Damià; Tauler, Romà

    2012-06-20

    Different chemometric techniques have been used to evaluate the effect of distinct experimental conditions and factors on Triticum aestivum L. plant development. The study was conducted using three wheat varieties, Astron, Ritmo and Stakado. These varieties were grown under organic and conventional cultivation systems. Samples were collected at five growth stages. Shoots and roots of each plant at these stages were analysed. Three replicates of each analysed sample were performed to improve representativeness and to allow for the evaluation of natural variability and interaction effects. All samples were analysed using Liquid Chromatography Mass-Spectrometry (LC-MS), and the Total Ion Current (TIC) profiles of benzoxazinone derivatives obtained for each sample were investigated. Qualitative and quantitative assessments of these TIC profiles and of their changes in the analysed samples were carried out using different chemometric techniques. Estimation of main effects, and of their possible interaction, was performed by means of Analysis of Variance combined to Principal Component Analysis (ANOVA-PCA) and of Analysis of Variance combined to Simultaneous Component Analysis (ASCA). Copyright © 2012 Elsevier B.V. All rights reserved.

  18. Towards the determination of the geographical origin of yellow cake samples by laser-induced breakdown spectroscopy and chemometrics

    International Nuclear Information System (INIS)

    Sirven, J.B.; Pailloux, A.; M'Baye, Y.; Coulon, N.; Alpettaz, Th.; Gosse, St.

    2009-01-01

    Yellow cake is a commonly used name for powdered uranium concentrate, produced with the uranium ore. It is the first step in the fabrication of nuclear fuel. As it contains fissile material its circulation needs to be controlled in order to avoid proliferation. In particular there is an interest in onsite determination of the geographical origin of a sample. The yellow cake elemental composition depends on its production site and can therefore be used to identify its origin. In this work laser-induced breakdown spectroscopy (LIBS) associated with chemometrics techniques is used to discriminate yellow cake samples of different geographical origin. 11 samples, one per origin, are analyzed by a commercial equipment in laboratory experimental conditions. Spectra are then processed by multivariate techniques like Principal Components Analysis (PCA) and Soft Independent Modeling of Class Analogy (SIMCA). Successive global PCAs are first performed on the whole spectra and enable one to discriminate all samples. The method is then refined by selecting several emission lines in the spectra and by using them as input data of the chemometric treatments. With a SIMCA model applied to these data a rate of correct identification of 100% is obtained for all classes. Then to define the specifications of a future onsite LIBS system, the use of a more compact spectrometer is simulated by a numerical treatment of experimental spectra. Simultaneously the reduction of spectral data used by the model is also investigated to decrease the spectral bandwidth of the measurement. The rate of correct identification remains very high. This work shows the very good ability of SIMCA associated with LIBS to discriminate yellow cake samples with a very high rate of success, in controlled laboratory conditions. (authors)

  19. Blends of olive oil and seeds oils: characterisation and olive oil quantification using fatty acids composition and chemometric tools. Part II.

    Science.gov (United States)

    Monfreda, M; Gobbi, L; Grippa, A

    2014-02-15

    A method to verify the percentage of olive oil in a blend, in compliance with the Commission Regulation EU No. 29/2012, was developed by GC-FID analysis of methyl esters of fatty acids, followed by chemometric tools (PCA, TFA, SIMCA and PLS). First of all, binary blends of twelve olive oils and one sunflower oil were studied, in order to evaluate the variability associated to the fatty acids profile of olive oils (Monfreda, Gobbi, & Grippa, 2012). In this study, binary blends of twelve olive oils with four types of seeds oils (peanut, corn, rice and grape seed oils) were evaluated. These four groups of blends were analysed and processed separately, each group consisting of 36 samples with 40%, 50% and 60% of olive oil content. Chemometric tools were also applied to the global data set (180 samples, including those analysed in the previous paper). Outstanding results were achieved, showing that the proposed method would be capable to discriminate blends with a difference in concentration of olive oil lower than 5% (a standard error of prediction of 3.97% was obtained with PLS). Therefore blends containing 45% and 55% of olive oil were also analysed with the current method and added to the data sets for chemometric assessment with supervised tools. SIMCA still provided good models; however the best performance was achieved by processing each group of binary blends (consisting of 60 samples) separately, rather than applying SIMCA to the overall data set (300 samples). On the other hand PLS did not show significant improvements. Copyright © 2013. Published by Elsevier Ltd.

  20. Diagnosis of human malignancies using laser-induced breakdown spectroscopy in combination with chemometric methods

    Science.gov (United States)

    Chen, Xue; Li, Xiaohui; Yu, Xin; Chen, Deying; Liu, Aichun

    2018-01-01

    Diagnosis of malignancies is a challenging clinical issue. In this work, we present quick and robust diagnosis and discrimination of lymphoma and multiple myeloma (MM) using laser-induced breakdown spectroscopy (LIBS) conducted on human serum samples, in combination with chemometric methods. The serum samples collected from lymphoma and MM cancer patients and healthy controls were deposited on filter papers and ablated with a pulsed 1064 nm Nd:YAG laser. 24 atomic lines of Ca, Na, K, H, O, and N were selected for malignancy diagnosis. Principal component analysis (PCA), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and k nearest neighbors (kNN) classification were applied to build the malignancy diagnosis and discrimination models. The performances of the models were evaluated using 10-fold cross validation. The discrimination accuracy, confusion matrix and receiver operating characteristic (ROC) curves were obtained. The values of area under the ROC curve (AUC), sensitivity and specificity at the cut-points were determined. The kNN model exhibits the best performances with overall discrimination accuracy of 96.0%. Distinct discrimination between malignancies and healthy controls has been achieved with AUC, sensitivity and specificity for healthy controls all approaching 1. For lymphoma, the best discrimination performance values are AUC = 0.990, sensitivity = 0.970 and specificity = 0.956. For MM, the corresponding values are AUC = 0.986, sensitivity = 0.892 and specificity = 0.994. The results show that the serum-LIBS technique can serve as a quick, less invasive and robust method for diagnosis and discrimination of human malignancies.

  1. Characteristic Fingerprint Based on Low Polar Constituents for Discrimination of Wolfiporia extensa according to Geographical Origin Using UV Spectroscopy and Chemometrics Methods

    Science.gov (United States)

    Li, Yan; Zhao, Yanli; Li, Zhimin; Li, Tao

    2014-01-01

    The fungus species Wolfiporia extensa has a long history of medicinal usage and has also been commercially used to formulate nutraceuticals and functional foods in certain Asian countries. In the present study, a practical and promising method has been developed to discriminate the dried sclerotium of W. extensa collected from different geographical sites based on UV spectroscopy together with chemometrics methods. Characteristic fingerprint of low polar constituents of sample extracts that originated from chloroform has been obtained in the interval 250–400 nm. Chemometric pattern recognition methods such as partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) were applied to enhance the authenticity of discrimination of the specimens. The results showed that W. extensa samples were well classified according to their geographical origins. The proposed method can fully utilize diversified fingerprint characteristics of sclerotium of W. extensa and requires low-cost equipment and short-time analysis in comparison with other techniques. Meanwhile, this simple and efficient method may serve as a basis for the authentication of other medicinal fungi. PMID:25544933

  2. A metabolic fingerprinting approach based on selected ion flow tube mass spectrometry (SIFT-MS) and chemometrics: A reliable tool for Mediterranean origin-labeled olive oils authentication.

    Science.gov (United States)

    Bajoub, Aadil; Medina-Rodríguez, Santiago; Ajal, El Amine; Cuadros-Rodríguez, Luis; Monasterio, Romina Paula; Vercammen, Joeri; Fernández-Gutiérrez, Alberto; Carrasco-Pancorbo, Alegría

    2018-04-01

    Selected Ion flow tube mass spectrometry (SIFT-MS) in combination with chemometrics was used to authenticate the geographical origin of Mediterranean virgin olive oils (VOOs) produced under geographical origin labels. In particular, 130 oil samples from six different Mediterranean regions (Kalamata (Greece); Toscana (Italy); Meknès and Tyout (Morocco); and Priego de Córdoba and Baena (Spain)) were considered. The headspace volatile fingerprints were measured by SIFT-MS in full scan with H 3 O + , NO + and O 2 + as precursor ions and the results were subjected to chemometric treatments. Principal Component Analysis (PCA) was used for preliminary multivariate data analysis and Partial Least Squares-Discriminant Analysis (PLS-DA) was applied to build different models (considering the three reagent ions) to classify samples according to the country of origin and regions (within the same country). The multi-class PLS-DA models showed very good performance in terms of fitting accuracy (98.90-100%) and prediction accuracy (96.70-100% accuracy for cross validation and 97.30-100% accuracy for external validation (test set)). Considering the two-class PLS-DA models, the one for the Spanish samples showed 100% sensitivity, specificity and accuracy in calibration, cross validation and external validation; the model for Moroccan oils also showed very satisfactory results (with perfect scores for almost every parameter in all the cases). Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Improving reliability of chemometric models for authentication of species origin of heparin by switching from 1D to 2D NMR experiments.

    Science.gov (United States)

    Monakhova, Yulia B; Fareed, Jawed; Yao, Yiming; Diehl, Bernd W K

    2018-05-10

    Nuclear magnetic resonance (NMR) spectroscopy is regarded as one of the most powerful and versatile analytical approaches to assure the quality of heparin preparations. In particular, it was recently demonstrated that by using 1 H NMR coupled with chemometrics heparin and low molecular weight heparin (LMWH) samples derived from three major animal species (porcine, ovine and bovine) can be differentiated [Y.B. Monakhova et al. J. Pharm. Anal. 149 (2018) 114-119]. In this study, significant improvement of existing chemometric models was achieved by switching to 2D NMR experiments (heteronuclear multiple-quantum correlation (HMQC) and diffusion-ordered spectroscopy (DOSY)). Two representative data sets (sixty-nine heparin and twenty-two LMWH) belonged to different batches and distributed by different commercial companies were investigated. A trend for animal species differentiation was observed in the principal component analysis (PCA) score plot built based on the DOSY data. A superior model was constructed using HMQC experiments, where individual heparin (LMWH) clusters as well as their blends were clearly differentiated. The predictive power of different classification methods as well as unsupervised techniques (independent components analysis, ICA) clearly proved applicability of the model for routine heparin and LMWH analysis. The switch from 1D to 2D NMR techniques provides a wealth of additional information, which is beneficial for multivariate modeling of NMR spectroscopic data for heparin preparations. Copyright © 2018 Elsevier B.V. All rights reserved.

  4. Characteristic Fingerprint Based on Low Polar Constituents for Discrimination of Wolfiporia extensa according to Geographical Origin Using UV Spectroscopy and Chemometrics Methods

    Directory of Open Access Journals (Sweden)

    Yan Li

    2014-01-01

    Full Text Available The fungus species Wolfiporia extensa has a long history of medicinal usage and has also been commercially used to formulate nutraceuticals and functional foods in certain Asian countries. In the present study, a practical and promising method has been developed to discriminate the dried sclerotium of W. extensa collected from different geographical sites based on UV spectroscopy together with chemometrics methods. Characteristic fingerprint of low polar constituents of sample extracts that originated from chloroform has been obtained in the interval 250–400 nm. Chemometric pattern recognition methods such as partial least squares discriminant analysis (PLS-DA and hierarchical cluster analysis (HCA were applied to enhance the authenticity of discrimination of the specimens. The results showed that W. extensa samples were well classified according to their geographical origins. The proposed method can fully utilize diversified fingerprint characteristics of sclerotium of W. extensa and requires low-cost equipment and short-time analysis in comparison with other techniques. Meanwhile, this simple and efficient method may serve as a basis for the authentication of other medicinal fungi.

  5. Simple and rapid simultaneous profiling of minor components of honey by size exclusion chromatography (SEC) coupled to ultraviolet diode array detection (UV-DAD), combined with chemometric methods.

    Science.gov (United States)

    Beretta, Giangiacomo; Fermo, Paola; Maffei Facino, Roberto

    2012-01-25

    This paper discusses the importance of profiling UV-responsive components, properly integrated with chemometric techniques, in detecting indicative parameters for quality control of honey. The minor components in honeys of different botanical and geographical origins were investigated by size SEC-UV-DAD. We diluted honey with mobile phase before injection into the chromatographic apparatus and a single chromatographic run gave a fast profile of high- (proteins and enzymes), intermediate- (e.g. terpenoid glycosides in lime tree honey) and low-molecular-weight components (secondary metabolites, e.g. kynurenic acid in chestnut honey). The analysis of a total number of 32 honey samples from different regions (Italy, Western Balkan countries, Brazil, Cameroon, Kenya) and of different botanical origins (herbal flower and arboreal flower nectars/honeydews) showed peculiar and characteristic distribution of these markers, which were basically related to their floral origin. Chemometric examination carried out using principal component analysis (PCA) and hierarchical cluster analysis (HCA) of the chromatograms (RT vs. absorption) detected four main clusters in which the groups of (i) chestnut honeys, (ii) honeys from rain forests and (iii) counterfeit/adulterated honeys were clearly separated from the main group of flower nectar honeys. The method is fast, requiring minimal sample handling, and the chromatographic data can be analyzed by multivariate statistical techniques to obtain descriptive information about the honey's quality and composition. Copyright © 2011 Elsevier B.V. All rights reserved.

  6. Chemometrics applications in biotech processes: assessing process comparability.

    Science.gov (United States)

    Bhushan, Nitish; Hadpe, Sandip; Rathore, Anurag S

    2012-01-01

    A typical biotech process starts with the vial of the cell bank, ends with the final product and has anywhere from 15 to 30 unit operations in series. The total number of process variables (input and output parameters) and other variables (raw materials) can add up to several hundred variables. As the manufacturing process is widely accepted to have significant impact on the quality of the product, the regulatory agencies require an assessment of process comparability across different phases of manufacturing (Phase I vs. Phase II vs. Phase III vs. Commercial) as well as other key activities during product commercialization (process scale-up, technology transfer, and process improvement). However, assessing comparability for a process with such a large number of variables is nontrivial and often companies resort to qualitative comparisons. In this article, we present a quantitative approach for assessing process comparability via use of chemometrics. To our knowledge this is the first time that such an approach has been published for biotech processing. The approach has been applied to an industrial case study involving evaluation of two processes that are being used for commercial manufacturing of a major biosimilar product. It has been demonstrated that the proposed approach is able to successfully identify the unit operations in the two processes that are operating differently. We expect this approach, which can also be applied toward assessing product comparability, to be of great use to both the regulators and the industry which otherwise struggle to assess comparability. Copyright © 2011 American Institute of Chemical Engineers (AIChE).

  7. Chemometric approach for development, optimization, and validation of different chromatographic methods for separation of opium alkaloids.

    Science.gov (United States)

    Acevska, J; Stefkov, G; Petkovska, R; Kulevanova, S; Dimitrovska, A

    2012-05-01

    The excessive and continuously growing interest in the simultaneous determination of poppy alkaloids imposes the development and optimization of convenient high-throughput methods for the assessment of the qualitative and quantitative profile of alkaloids in poppy straw. Systematic optimization of two chromatographic methods (gas chromatography (GC)/flame ionization detector (FID)/mass spectrometry (MS) and reversed-phase (RP)-high-performance liquid chromatography (HPLC)/diode array detector (DAD)) for the separation of alkaloids from Papaver somniferum L. (Papaveraceae) was carried out. The effects of various conditions on the predefined chromatographic descriptors were investigated using chemometrics. A full factorial linear design of experiments for determining the relationship between chromatographic conditions and the retention behavior of the analytes was used. Central composite circumscribed design was utilized for the final method optimization. By conducting the optimization of the methods in very rational manner, a great deal of excessive and unproductive laboratory research work was avoided. The developed chromatographic methods were validated and compared in line with the resolving power, sensitivity, accuracy, speed, cost, ecological aspects, and compatibility with the poppy straw extraction procedure. The separation of the opium alkaloids using the GC/FID/MS method was achieved within 10 min, avoiding any derivatization step. This method has a stronger resolving power, shorter analysis time, better cost/effectiveness factor than the RP-HPLC/DAD method and is in line with the "green trend" of the analysis. The RP-HPLC/DAD method on the other hand displayed better sensitivity for all tested alkaloids. The proposed methods provide both fast screening and an accurate content assessment of the six alkaloids in the poppy samples obtained from the selection program of Papaver strains.

  8. Introducing Chemometrics to the Analytical Curriculum: Combining Theory and Lab Experience

    Science.gov (United States)

    Gilbert, Michael K.; Luttrell, Robert D.; Stout, David; Vogt, Frank

    2008-01-01

    Beer's law is an ideal technique that works only in certain situations. A method for dealing with more complex conditions needs to be integrated into the analytical chemistry curriculum. For that reason, the capabilities and limitations of two common chemometric algorithms, classical least squares (CLS) and principal component regression (PCR),…

  9. Chemometrics for ion mobility spectrometry data: recent advances and future prospects

    NARCIS (Netherlands)

    Szymanska, E.; Davies, Antony N.; Buydens, L.M.C.

    2016-01-01

    Historically, advances in the field of ion mobility spectrometry have been hindered by the variation in measured signals between instruments developed by different research laboratories or manufacturers. This has triggered the development and application of chemometric techniques able to reveal and

  10. Experimental Design, Near-Infrared Spectroscopy, and Multivariate Calibration: An Advanced Project in a Chemometrics Course

    Science.gov (United States)

    de Oliveira, Rodrigo R.; das Neves, Luiz S.; de Lima, Kassio M. G.

    2012-01-01

    A chemometrics course is offered to students in their fifth semester of the chemistry undergraduate program that includes an in-depth project. Students carry out the project over five weeks (three 8-h sessions per week) and conduct it in parallel to other courses or other practical work. The students conduct a literature search, carry out…

  11. The dimerization study of some cationic monomethine cyanine dyes by chemometrics method

    Czech Academy of Sciences Publication Activity Database

    Ahmadi, S.; Deligeorgiev, T.G.; Vasilev, A.; Kubista, Mikael

    2012-01-01

    Roč. 86, č. 13 (2012), s. 1974-1981 ISSN 0036-0244 Institutional research plan: CEZ:AV0Z50520701 Keywords : dimerization * chemometrics * UV-vis spectroscopy * monomethine cyanine dyes Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 0.386, year: 2012

  12. Determination of two antibacterial binary mixtures by chemometrics-assisted spectrophotometry.

    Science.gov (United States)

    Mohamed, Abd El-Maaboud I; Abdelmageed, Osama H; Refaat, Ibrahim H

    2007-01-01

    Simple chemometrics-assisted spectrophotometric methods are described for determination of 2 antibacterial binary mixtures. The mixtures are composed of norfloxacin in combination with tinidazole and erythromycin (as ethylsuccinate ester or stearate salt) in combination with trimethoprim. The normal UV absorption spectra of each pair of drugs in the studied mixtures, in the range of 200-400 nm, showed a considerable degree of spectral overlapping: 77.5% for the norfloxacin-tinidazole mixture and 84.3% for the erythromycin-trimethoprim mixture. Resolution of the norfloxacin-tinidazole mixture and trimethoprim in the presence of erythromycin was accomplished successfully by using zero-crossing first derivative (1D), classical least-squares (CLS) regression analysis, and principal component regression (PCR) analysis methods. In addition, an alternative simple and accurate colorimetric method was developed for the determination of erythromycin in the presence of trimethoprim using 2,4-dinitrophenylhydrazine. All variables affecting the development of the colored chromogen were studied and optimized, and the product was measured at 526-529 and 538-542 nm for erythromycin stearate and erythromycin ethylsuccinate, respectively. For zero-crossing, first derivative technique Beer's law was obeyed in the general concentration range of 2-50 microg/mL for norfloxacin, tinidazole, and trimethoprim with good correlation coefficients (0.9994-0.9996). Overall limits of detection (LOD) and quantification (LOQ) ranged from 0.59 to 2.81 and 1.96 to 9.33 microg/mL, respectively. The obtained results from CLS and PCR were compared with those obtained from a 1D spectrophotometric method. With the exception of erythromycin, overall recoveries in the average range of 97.33-103.0% were obtained with a considerable degree of accuracy when the suggested methods were applied to analysis of synthetic binary mixtures, some commercial dosage forms such as tablets and oral suspension without

  13. The Chemometric Approach as a Useful Tool in the Identification of Metal Pollution Sources of Riverine-Mangrove Sediment of Kota Marudu, Sabah, Malaysia

    Directory of Open Access Journals (Sweden)

    Nadzhratul Husna Ahmad Puad

    2014-06-01

    Full Text Available The chemometric statistical approach was applied to evaluate the level of metals accumulation in sediment and to identify the probable pollution sources in the riverine-mangrove ecosystem of Kota Marudu, East Malaysia. Parameters, such as pH, electrical conductivity, salinity, organic matter, lead (Pb, cadmium (Cd, copper (Cu, chromium (Cr, zinc (Zn, aluminum (Al, nickel (Ni and iron (Fe were determined from sediment samples collected from 17 sampling points located throughout the district of Kota Marudu, Sabah. The results from cluster analysis indicate the presence of two prominent clusters that represent sources of pollution that might be induced from natural sources and human activities. Meanwhile, principal analysis from this study has proven that pH, electrical conductivity, salinity, Cd and Cr are responsible for the large spatial variations explaining 31.73% of the total variance, whilst organic matter, Fe and Al explain 24.75% of the total variance. The third factor is followed by Cu and Zn with 15.35% whereas Pb and Ni account for a total variance of 14.44%. The present study reveals the usefulness of the chemometric statistical approach as a remarkable and useful tool to reveal meaningful information concerning the spatial variability of large and complex riverine-mangrove data.

  14. A comprehensive quality evaluation method by FT-NIR spectroscopy and chemometric: Fine classification and untargeted authentication against multiple frauds for Chinese Ganoderma lucidum

    Science.gov (United States)

    Fu, Haiyan; Yin, Qiaobo; Xu, Lu; Wang, Weizheng; Chen, Feng; Yang, Tianming

    2017-07-01

    The origins and authenticity against frauds are two essential aspects of food quality. In this work, a comprehensive quality evaluation method by FT-NIR spectroscopy and chemometrics were suggested to address the geographical origins and authentication of Chinese Ganoderma lucidum (GL). Classification for 25 groups of GL samples (7 common species from 15 producing areas) was performed using near-infrared spectroscopy and interval-combination One-Versus-One least squares support vector machine (IC-OVO-LS-SVM). Untargeted analysis of 4 adulterants of cheaper mushrooms was performed by one-class partial least squares (OCPLS) modeling for each of the 7 GL species. After outlier diagnosis and comparing the influences of different preprocessing methods and spectral intervals on classification, IC-OVO-LS-SVM with standard normal variate (SNV) spectra obtained a total classification accuracy of 0.9317, an average sensitivity and specificity of 0.9306 and 0.9971, respectively. With SNV or second-order derivative (D2) spectra, OCPLS could detect at least 2% or more doping levels of adulterants for 5 of the 7 GL species and 5% or more doping levels for the other 2 GL species. This study demonstrates the feasibility of using new chemometrics and NIR spectroscopy for fine classification of GL geographical origins and species as well as for untargeted analysis of multiple adulterants.

  15. Chemical constituents and quality control of two Dracocephalum species based on high-performance liquid chromatographic fingerprints coupled with tandem mass spectrometry and chemometrics.

    Science.gov (United States)

    Li, Qi; Liu, Yiqi; Han, Lingfei; Liu, Jiazhuo; Liu, Wenyuan; Feng, Feng; Zhang, Jie; Xie, Ning

    2016-11-01

    Two similar Dracocephalum species, namely, Dracocephalum tanguticum Maxim and Dracocephalum moldavica L, are commonly used as ethnic medicines in China. Here we describe a strategy of combining high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry, as well as fingerprints and chemometrics for characterization and discrimination of chemical constituents on the two herbs. A total of 49 compounds including 33 flavonoids, 5 phenylethanol glycosides, 1 coumarin glycoside, 8 organic acids, and 2 other types of compounds were unambiguously or tentatively identified from the two Dracocephalum species. Among the compounds identified, 26 were characterized for the first time and 4 compounds, rosmarinic acid (7), salvianolic acid B (10), luteoloside (22), diosmetin-7-O-glucoside (28), were inferred as common constituents for the two herbs. Flavonoids featured in these two Dracocephalum species while their types presented significant differences. Acacetin (45) and acacetin glycosides (acatetin-7-O-glucuronide (30), acacetin-7-O-(6"-O-malonyl) glucoside (33), buddleoside (34), tilianin (35), and agastachoside (42)) were detected only in D. moldavica, which can be used to discriminate two herbal medicines. In addition, six characteristic constitutes in D. tanguticum were simultaneously quantified. Moreover, the induced chemometrics methods including similarity analysis and hierarchical clustering analysis were successfully applied for origin discrimination and quality evaluation of D. tanguticum and D. moldavica. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. The application and comparison of several chemometric methods of excitation-emission matrix spectra in studying the interactions of metal complexes with DNA

    International Nuclear Information System (INIS)

    Zhang Fang; Zhang Qianqian; Wang Weiguo; Zhu Chenjian; Wang Xiulin

    2007-01-01

    The interactions of fs DNA and two metal complexes [Cu(phen)SO 4 ].2H 2 O and [Ni(phen)SO 4 ].2H 2 O were explored by several chemometric methods, including parallel factor (PARAFAC), singular value decomposition-least squares (SVD-LS), and singular value decomposition-nonnegative least squares (SVD-NNLS) of excitation-emission matrix spectra (EEMs). The applications of SVD-LS and SVD-NNLS in this domain have been discussed. Rayleigh scatter part is avoided by ordered zero and reconstructed by linear interpolation. The importance of avoiding Rayleigh scatter has also been discussed. All the three methods do well in qualitative analysis. SVD-LS does best in present small changes of ethidium bromide (EB). In order to get accurate results, PARAFAC and SVD-NNLS can be utilized together in quantitative analysis. All the three chemometric methods indicate that the DNA binding modes of [Cu(phen)SO 4 ].2H 2 O are hydrogen bond effect and intercalation, while intercalation is the only DNA binding mode for [Ni(phen)SO 4 ].2H 2 O. These results are verified by the electronic absorption and emission fluorescence spectra. Just like PARAFAC, both SVD-LS and SVD-NNLS are proven to be convenient and convincing in studying the interactions between nucleic acids and complexes

  17. Application of total reflection X-ray spectrometry in combination with chemometric methods for determination of the botanical origin of Slovenian honey.

    Science.gov (United States)

    Necemer, Marijan; Kosir, Iztok J; Kump, Peter; Kropf, Urska; Jamnik, Mojca; Bertoncelj, Jasna; Ogrinc, Nives; Golob, Terezija

    2009-05-27

    This work on the botanical origin of various types of honey produced in Slovenia and based on the mineral content analyses by the total reflection X-ray spectrometry (TXRF) is a continuation of this group's preliminary work (Golob, T.; Doberšek, U.; Kump, P.; Nečemer, M. Food Chem. 2005, 91, 593-600), which introduced the analytical methodology and employed only a simple statistical evaluation and which examined the possibility to determine the botanical origin of honey samples via elemental content. A much more comprehensive study on a total of 264 major types of honey samples harvested in 2004, 2005, and 2006 and interpreting the results with up to date chemometric methods was performed in this work. Slovenia is a small country by surface area, but it is pedologically and climatically diverse, therefore offering interesting possibilities for studying the influence of these diversities on the elemental content of natural products. By employing principal component analysis (PCA) and regularized discriminant analysis (RDA) it was established that from all of the measured elements only the four characteristic key elements Cl, K, Mn, and Rb could be used to best discriminate the types of honey. It was established that the employed combination of a simple, fast, and inexpensive multielement TXRF analytical approach and the evaluation of data by chemometric methods has the potential to discriminate the botanical origins of various types of honey.

  18. Principal component analysis

    NARCIS (Netherlands)

    Bro, R.; Smilde, A.K.

    2014-01-01

    Principal component analysis is one of the most important and powerful methods in chemometrics as well as in a wealth of other areas. This paper provides a description of how to understand, use, and interpret principal component analysis. The paper focuses on the use of principal component analysis

  19. Thermally induced solid-state transformation of cimetidine. A multi-spectroscopic/chemometrics determination of the kinetics of the process and structural elucidation of one of the products as a stable N{sub 3}-enamino tautomer

    Energy Technology Data Exchange (ETDEWEB)

    Calvo, Natalia L.; Simonetti, Sebastian O.; Maggio, Rubén M.; Kaufman, Teodoro S., E-mail: kaufman@iquir-conicet.gov.ar

    2015-05-22

    Highlights: • Thermally stressed cimetidine above its melting point affords a stable N{sub 3} tautomer. • Multi-spectroscopic/chemometric approach developed to monitor tautomerization. • First combined use of NMR, UV and IR spectroscopies with chemometrics. • Solid cimetidine suffers first order degradation upon submission to dry heat. • Theoretical chemistry analysis confirmed the relative stability of cimetidine tautomer. - Abstract: Exposure of cimetidine (CIM) to dry heat (160–180 °C) afforded, upon cooling, a glassy solid containing new and hitherto unknown products. The kinetics of this process was studied by a second order chemometrics-assisted multi-spectroscopic approach. Proton and carbon-13 nuclear magnetic resonance (NMR), as well as ultraviolet and infrared spectroscopic data were jointly used, whereas multivariate curve resolution with alternating least squares (MCR-ALS) was employed as the chemometrics method to extract process information. It was established that drug degradation follows a first order kinetics. One of the products was structurally characterized by mono- and bi-dimensional NMR experiments. It was found to be the N{sub 3}-enamino tautomer (TAU) of CIM, resulting from the thermal isomerization of the double bond of the cyanoguanidine moiety of the drug, from the imine form to its N{sub 3}-enamine state. The thus generated tautomer demonstrated to be stable for months in the glassy solid and in methanolic solutions. A theoretical study of CIM and TAU revealed that the latter is less stable; however, the energy barrier for tautomer interconversion is high enough, precluding the process to proceed rapidly at room temperature.

  20. Chemometrics methods for the investigation of methylmercury and total mercury contamination in mollusks samples collected from coastal sites along the Chinese Bohai Sea.

    Science.gov (United States)

    Yawei, Wang; Lina, Liang; Jianbo, Shi; Guibin, Jiang

    2005-06-01

    The development and application of chemometrics methods, principal component analysis (PCA), cluster analysis and correlation analysis for the determination of methylmercury (MeHg) and total mecury (HgT) in gastropod and bivalve species collected from eight coastal sites along the Chinese Bohai Sea are described. HgT is directly determined by atomic fluorescence spectrometry (AFS), while MeHg is measured by a laboratory established high performance liquid chromatography-atomic fluorescence spectrometry system (HPLC-AFS). One-way ANOVA and cluster analysis indicated that the bioaccumulation of Rap to accumulate Hg was significantly (P<0.05) different from other mollusks. Correlation analysis shows that there is linear relationship between MeHg and HgT in mollusks samples collected from coastal sites along the Chinese Bohai Sea, while in mollusks samples collected from Hongqiao market in Beijing City, there is not any linear relationship.

  1. Quality assessment of crude and processed Arecae semen based on colorimeter and HPLC combined with chemometrics methods.

    Science.gov (United States)

    Sun, Meng; Yan, Donghui; Yang, Xiaolu; Xue, Xingyang; Zhou, Sujuan; Liang, Shengwang; Wang, Shumei; Meng, Jiang

    2017-05-01

    Raw Arecae Semen, the seed of Areca catechu L., as well as Arecae Semen Tostum and Arecae semen carbonisata are traditionally processed by stir-baking for subsequent use in a variety of clinical applications. These three Arecae semen types, important Chinese herbal drugs, have been used in China and other Asian countries for thousands of years. In this study, the sensory technologies of a colorimeter and sensitive validated high-performance liquid chromatography with diode array detection were employed to discriminate raw Arecae semen and its processed drugs. The color parameters of the samples were determined by a colorimeter instrument CR-410. Moreover, the fingerprints of the four alkaloids of arecaidine, guvacine, arecoline and guvacoline were surveyed by high-performance liquid chromatography. Subsequently, Student's t test, the analysis of variance, fingerprint similarity analysis, hierarchical cluster analysis, principal component analysis, factor analysis and Pearson's correlation test were performed for final data analysis. The results obtained demonstrated a significant color change characteristic for components in raw Arecae semen and its processed drugs. Crude and processed Arecae semen could be determined based on colorimetry and high-performance liquid chromatography with a diode array detector coupled with chemometrics methods for a comprehensive quality evaluation. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Binding of 8-methoxypsoralen to DNA in vitro: Monitoring by spectroscopic and chemometrics approaches

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Xiaoyue; Zhang, Guowen, E-mail: gwzhang@ncu.edu.cn; Wang, Langhong

    2014-10-15

    8-Methoxypsoralen (8-MOP) is a naturally occurring furanocoumarin with a variety of biological and pharmacological activities. The binding mechanism of 8-MOP to calf thymus DNA (ctDNA) at physiological pH was investigated by multi-spectroscopic techniques including UV–vis absorption, fluorescence, circular dichroism (CD) and Fourier transform infrared (FT-IR) spectroscopy along with DNA melting studies and viscosity measurements. The multivariate curve resolution-alternating least squares (MCR-ALS) chemometrics approach was introduced to resolve the expanded UV–vis spectral data matrix, and both the pure spectra and the equilibrium concentration profiles for the components (8-MOP, ctDNA and 8-MOP-ctDNA complex) in the system were successfully obtained to monitor the 8-MOP-ctDNA interaction. The results suggested that 8-MOP could bind to ctDNA via intercalation binding as evidenced by significant increases in melting and relative viscosity of ctDNA and competitive study using acridine orange (AO) as a fluorescence probe. The positive values of enthalpy and entropy change suggested that hydrogen bonds and van der Waals forces played a predominant role in the binding process. Further, FT-IR and CD spectra analysis indicated that 8-MOP preferentially bound to A–T base pairs with no major perturbation in ctDNA double helix conformation. Moreover, molecular docking was employed to exhibit the specific binding mode of 8-MOP to ctDNA intuitively. - Highlights: • The interaction processes of 8-MOP with ctDNA was monitored by MCR-ALS approach. • The binding mode of 8-MOP to ctDNA was an intercalation. • 8-MOP most likely bound to adenine and thymine base pairs of ctDNA. • Molecular docking illustrated the specific binding.

  3. Interaction between 8-methoxypsoralen and trypsin: Monitoring by spectroscopic, chemometrics and molecular docking approaches

    Science.gov (United States)

    Liu, Yingying; Zhang, Guowen; Zeng, Ni; Hu, Song

    2017-02-01

    8-Methoxypsoralen (8-MOP) is a naturally occurring furanocoumarin with various biological activities. However, there is little information on the binding mechanism of 8-MOP with trypsin. Here, the interaction between 8-MOP and trypsin in vitro was determined by multi-spectroscopic methods combined with the multivariate curve resolution-alternating least squares (MCR-ALS) chemometrics approach. An expanded UV-vis spectral data matrix was analysed by MCR-ALS, the concentration profiles and pure spectra for the three reaction species (trypsin, 8-MOP and 8-MOP-trypsin) were obtained to monitor the interaction between 8-MOP and trypsin. The fluorescence data suggested that a static type of quenching mechanism occurred in the binding of 8-MOP to trypsin. Hydrophobic interaction dominated the formation of the 8-MOP-trypsin complex on account of the positive enthalpy and entropy changes, and trypsin had one high affinity binding site for 8-MOP with a binding constant of 3.81 × 104 L mol- 1 at 298 K. Analysis of three dimensional fluorescence, UV-vis absorption and circular dichroism spectra indicated that the addition of 8-MOP induced the rearrangement of the polypeptides carbonyl hydrogen-bonding network and the conformational changes in trypsin. The molecular docking predicted that 8-MOP interacted with the catalytic residues His57, Asp102 and Ser195 in trypsin. The binding patterns and trypsin conformational changes may result in the inhibition of trypsin activity. This study has provided insights into the binding mechanism of 8-MOP with trypsin.

  4. Investigation of Drug–Polymer Compatibility Using Chemometric-Assisted UV-Spectrophotometry

    Directory of Open Access Journals (Sweden)

    Amir Ibrahim Mohamed

    2017-01-01

    Full Text Available A simple chemometric-assisted UV-spectrophotometric method was used to study the compatibility of clindamycin hydrochloride (HC1 with two commonly used natural controlled-release polymers, alginate (Ag and chitosan (Ch. Standard mixtures containing 1:1, 1:2, and 1:0.5 w/w drug–polymer ratios were prepared and UV scanned. A calibration model was developed with partial least square (PLS regression analysis for each polymer separately. Then, test mixtures containing 1:1 w/w drug–polymer ratios with different sets of drug concentrations were prepared. These were UV scanned initially and after three and seven days of storage at 25 °C. Using the calibration model, the drug recovery percent was estimated and a decrease in concentration of 10% or more from initial concentration was considered to indicate instability. PLS models with PC3 (for Ag and PC2 (for Ch showed a good correlation between actual and found values with root mean square error of cross validation (RMSECV of 0.00284 and 0.01228, and calibration coefficient (R2 values of 0.996 and 0.942, respectively. The average drug recovery percent after three and seven days was 98.1 ± 2.9 and 95.4 ± 4.0 (for Ag, and 97.3 ± 2.1 and 91.4 ± 3.8 (for Ch, which suggests more drug compatibility with an Ag than a Ch polymer. Conventional techniques including DSC, XRD, FTIR, and in vitro minimum inhibitory concentration (MIC for (1:1 drug–polymer mixtures were also performed to confirm clindamycin compatibility with Ag and Ch polymers.

  5. Relationships between volatile compounds and sensory characteristics in virgin olive oil by analytical and chemometric approaches.

    Science.gov (United States)

    Procida, Giuseppe; Cichelli, Angelo; Lagazio, Corrado; Conte, Lanfranco S

    2016-01-15

    The volatile fraction of virgin olive oil is characterised by low molecular weight compounds that vaporise at room temperature. In order to obtain an aroma profile similar to natural olfactory perception, the composition of the volatile compounds was determined by applying dynamic headspace gas chromatography, performed at room temperature, with a cryogenic trap directly connected to a gas chromatograph-mass spectrometer system. Samples were also evaluated according to European Union and International Olive Council official methods for sensory evaluation. In this paper, the composition of the volatile fraction of 25 extra virgin olive oils from different regions of Italy was analysed and some preliminary considerations on relationships between chemical composition of volatile fraction and sensory characteristics are reported. Forty-two compounds were identified by means of the particular analytical technique used. All the analysed samples, classified as extra virgin by the panel test, never present peaks whose magnitude is important enough in defected oils. The study was focused on the evaluation of volatile compounds responsible for the positive impact on olive odour properties ('green-fruity' and 'sweet') and olfactory perception. Chemometric evaluation of data, obtained through headspace analysis and the panel test evaluation, showed a correlation between chemical compounds and sensory properties. On the basis of the results, the positive attributes of virgin olive oil are divided into two separated groups: sweet types or green types. Sixteen volatile compounds with known positive impact on odour properties were extracted and identified. In particular, eight compounds seem correlated with sweet properties whereas the green sensation appears to be correlated with eight other different substances. The content of the compounds at six carbon atoms proves to be very important in defining positive attributes of extra virgin olive oils and sensory evaluation. © 2015

  6. Ghanaian cocoa bean fermentation characterized by spectroscopic and chromatographic methods and chemometrics.

    Science.gov (United States)

    Aculey, Patrick C; Snitkjaer, Pia; Owusu, Margaret; Bassompiere, Marc; Takrama, Jemmy; Nørgaard, Lars; Petersen, Mikael A; Nielsen, Dennis S

    2010-08-01

    Export of cocoa beans is of great economic importance in Ghana and several other tropical countries. Raw cocoa has an astringent, unpleasant taste, and flavor, and has to be fermented, dried, and roasted to obtain the characteristic cocoa flavor and taste. In an attempt to obtain a deeper understanding of the changes in the cocoa beans during fermentation and investigate the possibility of future development of objective methods for assessing the degree of fermentation, a novel combination of methods including cut test, colorimetry, fluorescence spectroscopy, NIR spectroscopy, and GC-MS evaluated by chemometric methods was used to examine cocoa beans sampled at different durations of fermentation and samples representing fully fermented and dried beans from all cocoa growing regions of Ghana. Using colorimetry it was found that samples moved towards higher a* and b* values as fermentation progressed. Furthermore, the degree of fermentation could, in general, be well described by the spectroscopic methods used. In addition, it was possible to link analysis of volatile compounds with predictions of fermentation time. Fermented and dried cocoa beans from the Volta and the Western regions clustered separately in the score plots based on colorimetric, fluorescence, NIR, and GC-MS indicating regional differences in the composition of Ghanaian cocoa beans. The study demonstrates the potential of colorimetry and spectroscopic methods as valuable tools for determining the fermentation degree of cocoa beans. Using GC-MS it was possible to demonstrate the formation of several important aroma compounds such 2-phenylethyl acetate, propionic acid, and acetoin and the breakdown of others like diacetyl during fermentation. Practical Application: The present study demonstrates the potential of using colorimetry and spectroscopic methods as objective methods for determining cocoa bean quality along the processing chain. Development of objective methods for determining cocoa bean

  7. Determination of the colorants in a beverage sample by chemometrıc methods using an ultraviolet spectrophotometer

    OpenAIRE

    Pekcan Ertokuş, Güzide

    2018-01-01

    In this study, color materials in powdered beverage samples weredetermined by chemometric methods using and UV/VIS spectrophotometer. From thechemometric methods, the principal component regression  (PCR) and the partial least squares method(PLS) were successfully applied in the determination of the amount of sunsetyellow and β-carotene contained in a powdered beverage. The results obtainedwith the help ofapplied chemometric methods are extremely fast, simple and reliable results.

  8. Chemometrical strategies for feature selection and data compression applied to NIR and MIR spectra of extra virgin olive oils for cultivar identification.

    Science.gov (United States)

    Casale, Monica; Sinelli, Nicoletta; Oliveri, Paolo; Di Egidio, Valentina; Lanteri, Silvia

    2010-03-15

    The possibility provided by Chemometrics to extract and combine (fusion) information contained in NIR and MIR spectra in order to discriminate monovarietal extra virgin olive oils according to olive cultivar (Casaliva, Leccino, Frantoio) has been investigated. Linear discriminant analysis (LDA) was applied as a classification technique on these multivariate and non-specific spectral data both separately and jointly (NIR and MIR data together). In order to ensure a more appropriate ratio between the number of objects (samples) and number of variables (absorbance at different wavenumbers), LDA was preceded either by feature selection or variable compression. For feature selection, the SELECT algorithm was used while a wavelet transform was applied for data compression. Correct classification rates obtained by cross-validation varied between 60% and 90% depending on the followed procedure. Most accurate results were obtained using the fused NIR and MIR data, with either feature selection or data compression. Chemometrical strategies applied to fused NIR and MIR spectra represent an effective method for classification of extra virgin olive oils on the basis of the olive cultivar. Copyright (c) 2009 Elsevier B.V. All rights reserved.

  9. Simultaneous determination of α-asarone and β-asarone in Acorus tatarinowii using excitation-emission matrix fluorescence coupled with chemometrics methods.

    Science.gov (United States)

    Bai, Xue-Mei; Liu, Tie; Liu, De-Long; Wei, Yong-Ju

    2018-02-15

    A chemometrics-assisted excitation-emission matrix (EEM) fluorescence method was proposed for simultaneous determination of α-asarone and β-asarone in Acorus tatarinowii. Using the strategy of combining EEM data with chemometrics methods, the simultaneous determination of α-asarone and β-asarone in the complex Traditional Chinese medicine system was achieved successfully, even in the presence of unexpected interferents. The physical or chemical separation step was avoided due to the use of "mathematical separation". Six second-order calibration methods were used including parallel factor analysis (PARAFAC), alternating trilinear decomposition (ATLD), alternating penalty trilinear decomposition (APTLD), self-weighted alternating trilinear decomposition (SWATLD), the unfolded partial least-squares (U-PLS) and multidimensional partial least-squares (N-PLS) with residual bilinearization (RBL). In addition, HPLC method was developed to further validate the presented strategy. Consequently, for the validation samples, the analytical results obtained by six second-order calibration methods were almost accurate. But for the Acorus tatarinowii samples, the results indicated a slightly better predictive ability of N-PLS/RBL procedure over other methods. Copyright © 2017. Published by Elsevier B.V.

  10. Simultaneous determination of α-asarone and β-asarone in Acorus tatarinowii using excitation-emission matrix fluorescence coupled with chemometrics methods

    Science.gov (United States)

    Bai, Xue-Mei; Liu, Tie; Liu, De-Long; Wei, Yong-Ju

    2018-02-01

    A chemometrics-assisted excitation-emission matrix (EEM) fluorescence method was proposed for simultaneous determination of α-asarone and β-asarone in Acorus tatarinowii. Using the strategy of combining EEM data with chemometrics methods, the simultaneous determination of α-asarone and β-asarone in the complex Traditional Chinese medicine system was achieved successfully, even in the presence of unexpected interferents. The physical or chemical separation step was avoided due to the use of ;mathematical separation;. Six second-order calibration methods were used including parallel factor analysis (PARAFAC), alternating trilinear decomposition (ATLD), alternating penalty trilinear decomposition (APTLD), self-weighted alternating trilinear decomposition (SWATLD), the unfolded partial least-squares (U-PLS) and multidimensional partial least-squares (N-PLS) with residual bilinearization (RBL). In addition, HPLC method was developed to further validate the presented strategy. Consequently, for the validation samples, the analytical results obtained by six second-order calibration methods were almost accurate. But for the Acorus tatarinowii samples, the results indicated a slightly better predictive ability of N-PLS/RBL procedure over other methods.

  11. A study on the discrimination of human skeletons using X-ray fluorescence and chemometric tools in chemical anthropology.

    Science.gov (United States)

    Gonzalez-Rodriguez, J; Fowler, G

    2013-09-10

    Forensic anthropological investigations are often restricted in their outcomes by the resources allocated to them, especially in terms of positively identifying the victims exhumed from commingled mass graves. Commingled mass graves can be defined as those graves that contain a number of disarticulated human remains from different individuals that have been mixed by either natural processes or human interventions. The research developed aimed to apply the technique of non-destructive XRF analysis to test whether there is substantial differentiation within the trace elemental composition and their ratios of individuals to separate them using chemometric analysis. The results of the different atomic spectroscopic analyses combined with the use of multivariate analysis on a set of 5 skeletons produced a series of plots using Principal Component Analysis that helped to separate them with a high percentage of accuracy when two, three or four skeletons needed to be separated. Also, two new elemental ratios, Zn/Fe related to metabolic activities and K/Fe related to blood flow into the bone, have been defined for their use in forensic anthropology for the first time to aid in the separation. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  12. Combination of near infrared spectroscopy and chemometrics for authentication of taro flour from wheat and sago flour

    Science.gov (United States)

    Rachmawati; Rohaeti, E.; Rafi, M.

    2017-05-01

    Taro flour on the market is usually sold at higher price than wheat and sago flour. This situation could be a cause for adulteration of taro flour from wheat and sago flour. For this reason, we will need an identification and authentication. Combination of near infrared (NIR) spectrum with multivariate analysis was used in this study to identify and authenticate taro flour from wheat and sago flour. The authentication model of taro flour was developed by using a mixture of 5%, 25%, and 50% of adulterated taro flour from wheat and sago flour. Before subjected to multivariate analysis, an initial preprocessing signal was used namely normalization and standard normal variate to the NIR spectrum. We used principal component analysis followed by discriminant analysis to make an identification and authentication model of taro flour. From the result obtained, about 90.48% of the taro flour mixed with wheat flour and 85% of taro flour mixed with sago flour were successfully classified into their groups. So the combination of NIR spectrum with chemometrics could be used for identification and authentication of taro flour from wheat and sago flour.

  13. Combination of near infrared spectroscopy and chemometrics for authentication of taro flour from wheat and sago flour

    International Nuclear Information System (INIS)

    Rachmawati; Rohaeti, E; Rafi, M

    2017-01-01

    Taro flour on the market is usually sold at higher price than wheat and sago flour. This situation could be a cause for adulteration of taro flour from wheat and sago flour. For this reason, we will need an identification and authentication. Combination of near infrared (NIR) spectrum with multivariate analysis was used in this study to identify and authenticate taro flour from wheat and sago flour. The authentication model of taro flour was developed by using a mixture of 5%, 25%, and 50% of adulterated taro flour from wheat and sago flour. Before subjected to multivariate analysis, an initial preprocessing signal was used namely normalization and standard normal variate to the NIR spectrum. We used principal component analysis followed by discriminant analysis to make an identification and authentication model of taro flour. From the result obtained, about 90.48% of the taro flour mixed with wheat flour and 85% of taro flour mixed with sago flour were successfully classified into their groups. So the combination of NIR spectrum with chemometrics could be used for identification and authentication of taro flour from wheat and sago flour. (paper)

  14. Olive oil authenticity studies by target and nontarget LC-QTOF-MS combined with advanced chemometric techniques.

    Science.gov (United States)

    Kalogiouri, Natasa P; Alygizakis, Nikiforos A; Aalizadeh, Reza; Thomaidis, Nikolaos S

    2016-11-01

    Food analysis is continuously requiring the development of more robust, efficient, and cost-effective food authentication analytical methods to guarantee the safety, quality, and traceability of food commodities with respect to legislation and consumer demands. Hence, a novel reversed-phase ultra high performance liquid chromatography-electrospray ionization quadrupole time of flight tandem mass spectrometry analytical method was developed that uses target, suspect, and nontarget screening strategies coupled with advanced chemometric tools for the investigation of the authenticity of extra virgin olive oil. The proposed method was successfully applied in real olive oil samples for the identification of markers responsible for the sensory profile. The proposed target analytical method includes the determination of 14 phenolic compounds and demonstrated low limits of detection ranging from 0.015 μg mL -1 (apigenin) to 0.039 μg mL -1 (vanillin) and adequate recoveries (96-107 %). A suspect list of 60 relevant compounds was compiled, and suspect screening was then applied to all the samples. Semiquantitation of the suspect compounds was performed with the calibration curves of target compounds having similar structures. Then, a nontarget screening workflow was applied with the aim to identify additional compounds so as to differentiate extra virgin olive oils from defective olive oils. Robust classification-based models were built with the use of supervised discrimination techniques, partial least squares-discriminant analysis and counterpropagation artificial neural networks, for the classification of olive oils into extra virgin olive oils or defective olive oils. Variable importance in projection scores were calculated to select the most significant features that affect the discrimination. Overall, 51 compounds were identified and suggested as markers, among which 14, 26, and 11 compounds were identified by target, suspect, and nontarget screening

  15. Chemometrics application in fuel's MTR type chemical characterization by X-ray fluorescence

    International Nuclear Information System (INIS)

    Silva, Clayton Pereira da

    2012-01-01

    , digesting, and others). To corrections like effects of spectral and matrix were applied and evaluated the fundamental parameter method, univariate calibration curve and multivariate calibration. The results were compared by means of statistical tests in accordance with ISO 17025 in MRCs (123 (1-7) and 124 (1-7)) MCRs of U 3 O 8 from New Brunswick Laboratory (NBL) and 16 U 3 Si 2 samples provided by CC of IPEN/CNEN-SP. The chemometrics is a promising method to determination of minor and major constituents on the U3Si2 and U3O8 basis nuclear fuel, because the precision and accuracy are statistically equal volumetric analysis, gravimetric and ICPOES methods. (author)

  16. Fourier transform infrared spectroscopy combined with chemometrics for discrimination of Curcuma longa, Curcuma xanthorrhiza and Zingiber cassumunar.

    Science.gov (United States)

    Rohaeti, Eti; Rafi, Mohamad; Syafitri, Utami Dyah; Heryanto, Rudi

    2015-02-25

    Turmeric (Curcuma longa), java turmeric (Curcuma xanthorrhiza) and cassumunar ginger (Zingiber cassumunar) are widely used in traditional Indonesian medicines (jamu). They have similar color for their rhizome and possess some similar uses, so it is possible to substitute one for the other. The identification and discrimination of these closely-related plants is a crucial task to ensure the quality of the raw materials. Therefore, an analytical method which is rapid, simple and accurate for discriminating these species using Fourier transform infrared spectroscopy (FTIR) combined with some chemometrics methods was developed. FTIR spectra were acquired in the mid-IR region (4000-400 cm(-1)). Standard normal variate, first and second order derivative spectra were compared for the spectral data. Principal component analysis (PCA) and canonical variate analysis (CVA) were used for the classification of the three species. Samples could be discriminated by visual analysis of the FTIR spectra by using their marker bands. Discrimination of the three species was also possible through the combination of the pre-processed FTIR spectra with PCA and CVA, in which CVA gave clearer discrimination. Subsequently, the developed method could be used for the identification and discrimination of the three closely-related plant species. Copyright © 2014 Elsevier B.V. All rights reserved.

  17. Classification of Tempranillo wines according to geographic origin: Combination of mass spectrometry based electronic nose and chemometrics

    International Nuclear Information System (INIS)

    Cynkar, Wies; Dambergs, Robert; Smith, Paul; Cozzolino, Daniel

    2010-01-01

    Rapid methods employing instruments such as electronic noses (EN) or gas sensors are used in the food and beverage industries to monitor and assess the composition and quality of products. Similar to other food industries, the wine industry has a clear need for simple, rapid and cost effective techniques for objectively evaluating the quality of grapes, wine and spirits. In this study a mass spectrometry based electronic nose (MS-EN) instrument combined with chemometrics was used to predict the geographical origin of Tempranillo wines produced in Australia and Spain. The MS-EN data generated were analyzed using principal components analysis (PCA), partial least squares discriminant analysis (PLS-DA) and stepwise linear discriminant analysis (SLDA) with full cross validation (leave-one-out method). The SLDA classified correctly 86% of the samples while PLS-DA 85% of Tempranillo wines according to their geographical origin. The relative benefits of using MS-EN will provide capability for rapid screening of wines. However, this technique does not provide the identification and quantitative determination of individual compounds responsible for the different aroma notes in the wine.

  18. Chemometric investigation of light-shade effects on essential oil yield and morphology of Moroccan Myrtus communis L.

    Science.gov (United States)

    Fadil, Mouhcine; Farah, Abdellah; Ihssane, Bouchaib; Haloui, Taoufik; Lebrazi, Sara; Zghari, Badreddine; Rachiq, Saâd

    2016-01-01

    To investigate the effect of environmental factors such as light and shade on essential oil yield and morphological traits of Moroccan Myrtus communis, a chemometric study was conducted on 20 individuals growing under two contrasting light environments. The study of individual's parameters by principal component analysis has shown that essential oil yield, altitude, and leaves thickness were positively correlated between them and negatively correlated with plants height, leaves length and leaves width. Principal component analysis and hierarchical cluster analysis have also shown that the individuals of each sampling site were grouped separately. The one-way ANOVA test has confirmed the effect of light and shade on essential oil yield and morphological parameters by showing a statistically significant difference between them from the shaded side to the sunny one. Finally, the multiple linear model containing main, interaction and quadratic terms was chosen for the modeling of essential oil yield in terms of morphological parameters. Sun plants have a small height, small leaves length and width, but they are thicker and richer in essential oil than shade plants which have shown almost the opposite. The highlighted multiple linear model can be used to predict essential oil yield in the studied area.

  19. Classification of Tempranillo wines according to geographic origin: Combination of mass spectrometry based electronic nose and chemometrics

    Energy Technology Data Exchange (ETDEWEB)

    Cynkar, Wies, E-mail: wies.cynkar@awri.com.au [Australian Wine Research Institute, PO Box 197, Glen Osmond, SA 5064 (Australia); Dambergs, Robert [Australian Wine Research Institute, Tasmanian Institute of Agricultural Research, University of Tasmania, Private Bag 98, Hobart Tasmania 7001 (Australia); Smith, Paul; Cozzolino, Daniel [Australian Wine Research Institute, PO Box 197, Glen Osmond, SA 5064 (Australia)

    2010-02-15

    Rapid methods employing instruments such as electronic noses (EN) or gas sensors are used in the food and beverage industries to monitor and assess the composition and quality of products. Similar to other food industries, the wine industry has a clear need for simple, rapid and cost effective techniques for objectively evaluating the quality of grapes, wine and spirits. In this study a mass spectrometry based electronic nose (MS-EN) instrument combined with chemometrics was used to predict the geographical origin of Tempranillo wines produced in Australia and Spain. The MS-EN data generated were analyzed using principal components analysis (PCA), partial least squares discriminant analysis (PLS-DA) and stepwise linear discriminant analysis (SLDA) with full cross validation (leave-one-out method). The SLDA classified correctly 86% of the samples while PLS-DA 85% of Tempranillo wines according to their geographical origin. The relative benefits of using MS-EN will provide capability for rapid screening of wines. However, this technique does not provide the identification and quantitative determination of individual compounds responsible for the different aroma notes in the wine.

  20. Examination of the regional distribution of minor and trace elements in normal human brain by PIXE and chemometric techniques

    International Nuclear Information System (INIS)

    Maenhaut, W.; Hebbrecht, G.; Reuck, J. de

    1993-01-01

    Particle-induced X-ray emission (PIXE) was used to measure two minor and six trace elements, i.e. K, Ca, Mn, Fe, Cu, Zn, Se, and Rb, in up to 50 different structures (regions) of brains from Belgian individuals without neurological disorders. The data matrix with the mean dry-weight elemental concentrations and mean wet-to-dry weight ratio (means over 18 brains) for the various structures was subjected to two chemometric techniques, i.e., VARIMAX rotated absolute principal component analysis (APCA) and hierarchical cluster analysis. Three components were identified by APCA: Components 1 and 3 represented aqueous fractions of the brain (respectively the intracellular and extracellular fluid), whereas component 2 apparently represented the solid brain fraction. The elements K, Cu, Zn, Se, and Rb were predominantly attributed to component 1, Ca to component 3, and Fe to component 2. In the hierarchical cluster analysis seven different agglomerative cluster strategies were compared. The dendrograms obtained from the furthest neighbor and Ward's error sum strategy were virtually identical, and they consisted of two large clusters with 30 and 16 structures, respectively. The first cluster included all gray matter structures, while the second comprised all white matter. Furthermore, structures involved in the same physiological function or morphologically similar regions often conglomerated in one subcluster. This strongly suggests that there is some relationship between the trace element profile of a brain structure and its function. (orig.)

  1. Detection of l-Cysteine in wheat flour by Raman microspectroscopy combined chemometrics of HCA and PCA.

    Science.gov (United States)

    Cebi, Nur; Dogan, Canan Ekinci; Develioglu, Ayşen; Yayla, Mediha Esra Altuntop; Sagdic, Osman

    2017-08-01

    l-Cysteine is deliberately added to various flour types since l-Cysteine has enabled favorable baking conditions such as low viscosity, increased elasticity and rise during baking. In Turkey, usage of l-Cysteine as a food additive isn't allowed in wheat flour according to the Turkish Food Codex Regulation on food additives. There is an urgent need for effective methods to detect l-Cysteine in wheat flour. In this study, for the first time, a new, rapid, effective, non-destructive and cost-effective method was developed for detection of l-Cysteine in wheat flour using Raman microscopy. Detection of l-Cysteine in wheat flour was accomplished successfully using Raman microscopy combined chemometrics of PCA (Principal Component Analysis) and HCA (Hierarchical Cluster Analysis). In this work, 500-2000cm -1 spectral range (fingerprint region) was determined to perform PCA and HCA analysis. l-Cysteine and l-Cystine were determined with detection limit of 0.125% (w/w) in different wheat flour samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Fourier transform infrared spectroscopy combined with chemometrics for discrimination of Curcuma longa, Curcuma xanthorrhiza and Zingiber cassumunar

    Science.gov (United States)

    Rohaeti, Eti; Rafi, Mohamad; Syafitri, Utami Dyah; Heryanto, Rudi

    2015-02-01

    Turmeric (Curcuma longa), java turmeric (Curcuma xanthorrhiza) and cassumunar ginger (Zingiber cassumunar) are widely used in traditional Indonesian medicines (jamu). They have similar color for their rhizome and possess some similar uses, so it is possible to substitute one for the other. The identification and discrimination of these closely-related plants is a crucial task to ensure the quality of the raw materials. Therefore, an analytical method which is rapid, simple and accurate for discriminating these species using Fourier transform infrared spectroscopy (FTIR) combined with some chemometrics methods was developed. FTIR spectra were acquired in the mid-IR region (4000-400 cm-1). Standard normal variate, first and second order derivative spectra were compared for the spectral data. Principal component analysis (PCA) and canonical variate analysis (CVA) were used for the classification of the three species. Samples could be discriminated by visual analysis of the FTIR spectra by using their marker bands. Discrimination of the three species was also possible through the combination of the pre-processed FTIR spectra with PCA and CVA, in which CVA gave clearer discrimination. Subsequently, the developed method could be used for the identification and discrimination of the three closely-related plant species.

  3. Application of chemometric techniques in studies of toxicity of selected commercially available products for infants and children.

    Science.gov (United States)

    Szczepańska, Natalia; Kudłak, Błażej; Nedyalkova, Miroslava; Simeonov, Vasil; Namieśnik, Jacek

    2017-07-01

    The goal of the present study is to assess the impact of the experimental conditions for extraction procedures (time of extraction, thermal treatment and type of extraction media) as applied to several baby and infant products checked for their possible ecotoxicological response when tested by various ecotoxicity tests (Microtox ® , Ostracodtoxkit F™ and Xenoscreen YES/YAS™). The systems under consideration are multidimensional by nature and, therefore, the appropriate assessment approach was intelligent data analysis (chemometrics). Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were selected as reliable data mining methods for the interpretation of the ecotoxicity data. We show that the different experimental conditions have a significant impact on the ecotoxicity levels observed, especially those measured by Microtox ® and Ostracodtoxkit F™ tests. The time of contact proves to be a very significant factor for all extraction media and ecotoxicity test procedures. The present study is a pioneering effort to offer a specific expert approach for analysing links between the type of test measurement methodology and imposed experimental conditions to mimic real-life circumstances in the use of baby and infant products.

  4. Discrimination of tomatoes bred by spaceflight mutagenesis using visible/near infrared spectroscopy and chemometrics.

    Science.gov (United States)

    Shao, Yongni; Xie, Chuanqi; Jiang, Linjun; Shi, Jiahui; Zhu, Jiajin; He, Yong

    2015-04-05

    Visible/near infrared spectroscopy (Vis/NIR) based on sensitive wavelengths (SWs) and chemometrics was proposed to discriminate different tomatoes bred by spaceflight mutagenesis from their leafs or fruits (green or mature). The tomato breeds were mutant M1, M2 and their parent. Partial least squares (PLS) analysis and least squares-support vector machine (LS-SVM) were implemented for calibration models. PLS analysis was implemented for calibration models with different wavebands including the visible region (400-700 nm) and the near infrared region (700-1000 nm). The best PLS models were achieved in the visible region for the leaf and green fruit samples and in the near infrared region for the mature fruit samples. Furthermore, different latent variables (4-8 LVs for leafs, 5-9 LVs for green fruits, and 4-9 LVs for mature fruits) were used as inputs of LS-SVM to develop the LV-LS-SVM models with the grid search technique and radial basis function (RBF) kernel. The optimal LV-LS-SVM models were achieved with six LVs for the leaf samples, seven LVs for green fruits, and six LVs for mature fruits, respectively, and they outperformed the PLS models. Moreover, independent component analysis (ICA) was executed to select several SWs based on loading weights. The optimal LS-SVM model was achieved with SWs of 550-560 nm, 562-574 nm, 670-680 nm and 705-71 5 nm for the leaf samples; 548-556 nm, 559-564 nm, 678-685 nm and 962-974 nm for the green fruit samples; and 712-718 nm, 720-729 nm, 968-978 nm and 820-830 nm for the mature fruit samples. All of them had better performance than PLS and LV-LS-SVM, with the parameters of correlation coefficient (rp), root mean square error of prediction (RMSEP) and bias of 0.9792, 0.2632 and 0.0901 based on leaf discrimination, 0.9837, 0.2783 and 0.1758 based on green fruit discrimination, 0.9804, 0.2215 and -0.0035 based on mature fruit discrimination, respectively. The overall results indicated that ICA was an effective way for the

  5. Chilean flour and wheat grain: tracing their origin using near infrared spectroscopy and chemometrics.

    Science.gov (United States)

    González-Martín, Ma Inmaculada; Wells Moncada, Guillermo; González-Pérez, Claudio; Zapata San Martín, Nelson; López-González, Fernando; Lobos Ortega, Iris; Hernández-Hierro, Jose-Miguel

    2014-02-15

    Instrumental techniques such a near-infrared spectroscopy (NIRS) are used in industry to monitor and establish product composition and quality. As occurs with other food industries, the Chilean flour industry needs simple, rapid techniques to objectively assess the origin of different products, which is often related to their quality. In this sense, NIRS has been used in combination with chemometric methods to predict the geographic origin of wheat grain and flour samples produced in different regions of Chile. Here, the spectral data obtained with NIRS were analysed using a supervised pattern recognition method, Discriminat Partial Least Squares (DPLS). The method correctly classified 76% of the wheat grain samples and between 90% and 96% of the flour samples according to their geographic origin. The results show that NIRS, together with chemometric methods, provides a rapid tool for the classification of wheat grain and flour samples according to their geographic origin. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. Near Infrared Spectroscopy Calibration for Wood Chemistry: Which Chemometric Technique Is Best for Prediction and Interpretation?

    OpenAIRE

    Via, Brian K.; Zhou, Chengfeng; Acquah, Gifty; Jiang, Wei; Eckhardt, Lori

    2014-01-01

    This paper addresses the precision in factor loadings during partial least squares (PLS) and principal components regression (PCR) of wood chemistry content from near infrared reflectance (NIR) spectra. The precision of the loadings is considered important because these estimates are often utilized to interpret chemometric models or selection of meaningful wavenumbers. Standard laboratory chemistry methods were employed on a mixed genus/species hardwood sample set. PLS and PCR, before and af...

  7. 1H qNMR and Chemometric Analyses of Urban Wastewater

    OpenAIRE

    Alves Filho,Elenilson G.; Sartori,Luci; Silva,Lorena M. A.; Venâncio,Tiago; Carneiro,Renato L.; Ferreira,Antonio G.

    2015-01-01

    The industrial development, urbanization and agriculture play a major role in the degradation of the global environmental. Thus, the wastewater treatments need to be monitored continuously to ensure efficient operation. This manuscript presents an application of 1H nuclear magnetic resonance (NMR) associated with chemometric and quantitative analyses to study the wastewater before and after the sewage treatment plant (STP). The concentration of compounds related to organic matter degradation ...

  8. Attempt to separate the fluorescence spectra of adrenaline and noradrenaline using chemometrics

    DEFF Research Database (Denmark)

    Nikolajsen, Rikke P; Hansen, Åse Marie; Bro, R

    2000-01-01

    An investigation was conducted on whether the fluorescence spectra of the very similar catecholamines adrenaline and noradrenaline could be separated using chemometric methods. The fluorescence landscapes (several excitation and emission spectra were measured) of two data sets with respectively 16...... is not obtainable using this type of fluorescence measurement. Raman scatter, which overlaps the catecholamine spectra, was shown not to have any influence on the models calculated....

  9. New liquid chromatographic-chemometric approach for the determination of sunset yellow and tartrazine in commercial preparation.

    Science.gov (United States)

    Dinç, Erdal; Aktaş, A Hakan; Ustündağ, Ozgür

    2005-01-01

    A new liquid chromatographic (LC)-chemometric approach was developed for the determination of sunset yellow (SUN) and tartrazine (TAR) in commercial preparations. This approach uses LC and chemometric calibration methods, i.e., classical least-squares (CLS), principal component regression (PCR), and partial-least squares (PLS), simultaneously. The combined LC-chemometric approaches, denoted as LC-CLS, LC-PCR, and LC-PLS, are based on photodiode array (PDA) detection at multiple wavelengths. Optimum chromatographic separation of SUN and TAR with allura red as the internal standard (IS) was obtained by using a Waters Symmetry C18 column, 5 microm, 4.6 x 250 mm, and 0.2 M acetate buffer (pH 5)-acetonitrile-methano-bidistilled water (55 + 20 + 15 + 10, v/v) as the mobile phase at a flow rate of 1.9 mL/min. The LC data sets consisting of the ratios of analyte peak areas to the IS peak area were obtained by using PDA detection at 5 wavelengths (465, 470, 475, 480, and 485 nm). LC-chemometric calibrations for SUN and TAR were separately constructed by using the relationship between the peak-area ratio and the training sets for each colorant. LC-chemometric approaches were tested for different synthetic mixtures containing SUN and TAR in the presence of the IS. These LC-chemometric calibrations were applied to a commercial preparation of the 2 colorants. The experimental results of the LC-chemometric approaches were compared with those obtained by a developed classical LC method using single-wavelength detection.

  10. Development of a directly correlated Raman and uHPLC-MS content uniformity method for dry powder inhalers through statistical design, chemometrics and mathematical modeling.

    Science.gov (United States)

    Seabrooks, Lauren; Canfield, Nicole; Pennington, Justin

    2016-09-01

    Content uniformity (CU) is a critical quality attribute measured and monitored throughout the development and commercial supply of pharmaceutical products. Traditional high-performance liquid chromatography (HPLC) methods are time-consuming in both sample preparation and analysis. Thus, a rapid, nondestructive and preparation free spectroscopy based method such as Raman is preferred. Multiple mathematical algorithms were used to establish robust and directly correlated Raman and ultra-HPLC-mass spectrometry (uHPLC-MS) CU methods for the rapid analysis of blends and agglomerates formulated for dry powder inhalers (DPIs). Model samples included blends of caffeine and lactose; albuterol and lactose; and albuterol and lactose agglomerates. Design of experiments (DoE) was employed to optimize Raman spectra. Multivariate curve resolution (MCR) was leveraged to assess Raman method robustness. Mathematical modeling provided direct method to method correlation by allowing samples to be scanned first for Raman spectra and then dissolved for uHPLC-MS analysis. Several chemometric models were developed and evaluated for the quantitative analysis of CU. The DoE revealed Raman power and exposure time were negatively correlated when optimizing albuterol and caffeine spectra but positively correlated for lactose. MCR revealed regions in which small changes to power and time resulted in an 8-10% change in concentration predictions. A PCR model worked well for the analysis of caffeine blend samples and a PLS model worked best for both albuterol blends and agglomerates. Utilization of DoE, chemometrics and mathematical modeling provided a robust and directly correlated CU method for DPIs.

  11. Chemometric evaluation for the relation of BCR sequential extraction method and in vitro gastro-intestinal method for the assessment of metal bioavailability in contaminated soils in Turkey.

    Science.gov (United States)

    Karadaş, Cennet; Kara, Derya

    2012-05-01

    A chemometric evaluation has been done to classify metal ions in soils and to determine whether or not the gastric and intestinal phases of a physiologically based extraction test bear any relation to any of the phases of the four-stage Community Bureau of Reference (BCR) extraction protocol. Nine trace analytes (As, Ba, Cd, Cr, Cu, Mn, Ni, Pb and Zn) were determined in extracts obtained from the BCR sequential extraction procedure as well as from in vitro gastro-intestinal experiments. The results showed that high As, Pb, Zn and Cd concentrations were found in these soils. Principal component analysis (PCA) and linear discriminant analysis were used as classification techniques. Stepwise multiple linear regression analysis was applied to the data set to determine how the bioaccessibility of a metal is linked to the operationally defined fractions of metal speciation in soil. This analysis showed that the metal concentrations in the intestinal and gastric extracts are mainly dependent on the concentrations found in BCR phases 1 and 2 for each metal ion except for Cr, which was mainly dependent on the concentrations found in BCR phase 3. From the chemometric technique of correlation analysis, it was concluded that the metals extracted using BCR phases 1 and 2 are more likely to be bioaccessible, i.e. are also extracted by gastric and intestinal digestion solutions. When the correlation and PCA results were interpreted together, it indicated that the bioaccessiblity of Zn, Pb, Mn and Cd were higher than As, Ba, Cr, Ni and Cu for these soils.

  12. A chemometric approach to the evaluation of atmospheric and fluvial pollutant inputs in aquatic systems: The Guadalquivir River estuary as a case study

    International Nuclear Information System (INIS)

    Lopez-Lopez, Jose A.; Garcia-Vargas, Manuel; Moreno, Carlos

    2011-01-01

    To establish the quality of waters it is necessary to identify both point and non-point pollution sources. In this work, we propose the combination of clean analytical methodologies and chemometric tools to study discrete and diffuse pollution caused in a river by tributaries and precipitations, respectively. During a two-year period, water samples were taken in the Guadalquivir river (selected as a case study) and its main tributaries before and after precipitations. Samples were characterized by analysing nutrients, pH, dissolved oxygen, total and volatile suspended solids, carbon species, and heavy metals. Results were used to estimate fluvial and atmospheric inputs and as tracers for anthropic activities. Multivariate analysis was used to estimate the background pollution, and to identify pollution inputs. Principal Component Analysis and Cluster Analysis were used as data exploratory tools, while box-whiskers plots and Linear Discriminant Analysis were used to analyse and distinguish the different types of water samples. - Highlights: → Atmospheric and fluvial inputs of pollutants in Guadalquivir River were identified. → Point (tributary rivers) and non-point sources (rains) were studied. → Nature and extension of anthropogenic pollution in the river were established. - By combining trace environmental analysis and selected chemometric tools atmospheric and fluvial inputs of pollutants in rivers may be identified. The extension of the pollution originated by each anthropic activity developed along the River may be established, as well as the identification of the pollution introduced into the river by the tributary rivers (point sources) and by rains (non-point sources).

  13. Exploring authentic skim and nonfat dry milk powder variance for the development of nontargeted adulterant detection methods using near-infrared spectroscopy and chemometrics.

    Science.gov (United States)

    Botros, Lucy L; Jablonski, Joseph; Chang, Claire; Bergana, Marti Mamula; Wehling, Paul; Harnly, James M; Downey, Gerard; Harrington, Peter; Potts, Alan R; Moore, Jeffrey C

    2013-10-16

    A multinational collaborative team led by the U.S. Pharmacopeial Convention is currently investigating the potential of near-infrared (NIR) spectroscopy for nontargeted detection of adulterants in skim and nonfat dry milk powder. The development of a compendial method is challenged by the range of authentic or nonadulterated milk powders available worldwide. This paper investigates the sources of variance in 41 authentic bovine skim and nonfat milk powders as detected by NIR diffuse reflectance spectroscopy and chemometrics. Exploratory analysis by principal component analysis and varimax factor rotation revealed significant variance in authentic samples and highlighted outliers from a single manufacturer. Spectral preprocessing and outlier removal methods reduced ambient and measurement sources of variance, most likely linked to changes in moisture together with sampling, preparation, and presentation factors. Results indicate that significant chemical variance exists in different skim and nonfat milk powders that will likely affect the performance of adulterant detection methods by NIR spectroscopy.

  14. HPLC-PDA Combined with Chemometrics for Quantitation of Active Components and Quality Assessment of Raw and Processed Fruits of Xanthium strumarium L.

    Science.gov (United States)

    Jiang, Hai; Yang, Liu; Xing, Xudong; Yan, Meiling; Guo, Xinyue; Yang, Bingyou; Wang, Qiuhong; Kuang, Haixue

    2018-01-25

    As a valuable herbal medicine, the fruits of Xanthium strumarium L. (Xanthii Fructus) have been widely used in raw and processed forms to achieve different therapeutic effects in practice. In this study, a comprehensive strategy was proposed for evaluating the active components in 30 batches of raw and processed Xanthii Fructus (RXF and PXF) samples, based on high-performance liquid chromatography coupled with photodiode array detection (HPLC-PDA). Twelve common peaks were detected and eight compounds of caffeoylquinic acids were simultaneously quantified in RXF and PXF. All the analytes were detected with satisfactory linearity (R² > 0.9991) over wide concentration ranges. Simultaneously, the chemically latent information was revealed by hierarchical cluster analysis (HCA) and principal component analysis (PCA). The results suggest that there were significant differences between RXF and PXF from different regions in terms of the content of eight caffeoylquinic acids. Potential chemical markers for XF were found during processing by chemometrics.

  15. On the use of the fluorescence, ultraviolet-visible and near infrared spectroscopy with chemometrics for the discrimination between plum brandies of different varietal origins.

    Science.gov (United States)

    Jakubíková, M; Sádecká, J; Kleinová, A

    2018-01-15

    This paper investigates the use of synchronous fluorescence, UV-Vis and near infrared (NIR) spectroscopy coupled with chemometric methods to discriminate samples of high-quality plum brandies (Slivovica) of different varietal origins (Prunus domestica L.). Synchronous fluorescence spectra (SFS) for wavelength differences in the range of 70-100nm, NIR spectra in the wavenumber range of 4000-7500cm -1 and UV-Vis spectra in the wavelength interval of 220-320nm were compared. The best discrimination models were created by linear discriminant analysis based on principal component analysis applied to SFS recorded with wavelength difference either 80nm or 100nm, allowing the classification of plum brandy according to harvest time as early (summer) and late (autumn) plum varieties; the total correct classifications were 96% and 100% for the calibration and prediction steps, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Chemometrics-assisted spectrophotometry method for the determination of chemical oxygen demand in pulping effluent.

    Science.gov (United States)

    Chen, Honglei; Chen, Yuancai; Zhan, Huaiyu; Fu, Shiyu

    2011-04-01

    A new method has been developed for the determination of chemical oxygen demand (COD) in pulping effluent using chemometrics-assisted spectrophotometry. Two calibration models were established by inducing UV-visible spectroscopy (model 1) and derivative spectroscopy (model 2), combined with the chemometrics software Smica-P. Correlation coefficients of the two models are 0.9954 (model 1) and 0.9963 (model 2) when COD of samples is in the range of 0 to 405 mg/L. Sensitivities of the two models are 0.0061 (model 1) and 0.0056 (model 2) and method detection limits are 2.02-2.45 mg/L (model 1) and 2.13-2.51 mg/L (model 2). Validation experiment showed that the average standard deviation of model 2 was 1.11 and that of model 1 was 1.54. Similarly, average relative error of model 2 (4.25%) was lower than model 1 (5.00%), which indicated that the predictability of model 2 was better than that of model 1. Chemometrics-assisted spectrophotometry method did not need chemical reagents and digestion which were required in the conventional methods, and the testing time of the new method was significantly shorter than the conventional ones. The proposed method can be used to measure COD in pulping effluent as an environmentally friendly approach with satisfactory results.

  17. Simulated aging of lubricant oils by chemometric treatment of infrared spectra: potential antioxidant properties of sulfur structures.

    Science.gov (United States)

    Amat, Sandrine; Braham, Zeineb; Le Dréau, Yveline; Kister, Jacky; Dupuy, Nathalie

    2013-03-30

    Lubricant oils are complex mixtures of base oils and additives. The evolution of their performance over time strongly depends on its resistance to thermal oxidation. Sulfur compounds revealed interesting antioxidant properties. This study presents a method to evaluate the lubricant oil oxidation. Two samples, a synthetic and a paraffinic base oils, were tested pure and supplemented with seven different sulfur compounds. An aging cell adapted to a Fourier Transform InfraRed (FT-IR) spectrometer allows the continuous and direct analysis of the oxidative aging of base oils. Two approaches were applied to study the oxidation/anti-oxidation phenomena. The first one leads to define a new oxidative spectroscopic index based on a reduced spectral range where the modifications have been noticed (from 3050 to 2750 cm(-1)). The second method is based on chemometric treatments of whole spectra (from 4000 to 400 cm(-1)) to extract underlying information. A SIMPLe-to-use Interactive Self Modeling Analysis (SIMPLISMA) method has been used to identify more precisely the chemical species produced or degraded during the thermal treatment and to follow their evolution. Pure spectra of different species present in oil were obtained without prior information of their existence. The interest of this tool is to supply relative quantitative information reflecting evolution of the relative abundance of the different products over thermal aging. Results obtained by these two ways have been compared to estimate their concordance. Copyright © 2013 Elsevier B.V. All rights reserved.

  18. Determination of Cefoperazone Sodium in Presence of Related Impurities by Linear Support Vector Regression and Partial Least Squares Chemometric Models

    Directory of Open Access Journals (Sweden)

    Ibrahim A. Naguib

    2015-01-01

    Full Text Available A comparison between partial least squares regression and support vector regression chemometric models is introduced in this study. The two models are implemented to analyze cefoperazone sodium in presence of its reported impurities, 7-aminocephalosporanic acid and 5-mercapto-1-methyl-tetrazole, in pure powders and in pharmaceutical formulations through processing UV spectroscopic data. For best results, a 3-factor 4-level experimental design was used, resulting in a training set of 16 mixtures containing different ratios of interfering moieties. For method validation, an independent test set consisting of 9 mixtures was used to test predictive ability of established models. The introduced results show the capability of the two proposed models to analyze cefoperazone in presence of its impurities 7-aminocephalosporanic acid and 5-mercapto-1-methyl-tetrazole with high trueness and selectivity (101.87 ± 0.708 and 101.43 ± 0.536 for PLSR and linear SVR, resp.. Analysis results of drug products were statistically compared to a reported HPLC method showing no significant difference in trueness and precision, indicating the capability of the suggested multivariate calibration models to be reliable and adequate for routine quality control analysis of drug product. SVR offers more accurate results with lower prediction error compared to PLSR model; however, PLSR is easy to handle and fast to optimize.

  19. Discrimination of geographical origin of lentils (Lens culinaris Medik.) using isotope ratio mass spectrometry combined with chemometrics.

    Science.gov (United States)

    Longobardi, F; Casiello, G; Cortese, M; Perini, M; Camin, F; Catucci, L; Agostiano, A

    2015-12-01

    The aim of this study was to predict the geographic origin of lentils by using isotope ratio mass spectrometry (IRMS) in combination with chemometrics. Lentil samples from two origins, i.e. Italy and Canada, were analysed obtaining the stable isotope ratios of δ(13)C, δ(15)N, δ(2)H, δ(18)O, and δ(34)S. A comparison between median values (U-test) highlighted statistically significant differences (p<0.05) for all isotopic parameters between the lentils produced in these two different geographic areas, except for δ(15)N. Applying principal component analysis, grouping of samples was observed on the basis of origin but with overlapping zones; consequently, two supervised discriminant techniques, i.e. partial least squares discriminant analysis and k-nearest neighbours algorithm were used. Both models showed good performances with external prediction abilities of about 93% demonstrating the suitability of the methods developed. Subsequently, isotopic determinations were also performed on the protein and starch fractions and the relevant results are reported. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Isotope ratio mass spectrometry in combination with chemometrics for characterization of geographical origin and agronomic practices of table grape.

    Science.gov (United States)

    Longobardi, Francesco; Casiello, Grazia; Centonze, Valentina; Catucci, Lucia; Agostiano, Angela

    2017-08-01

    Although table grape is one of the most cultivated and consumed fruits worldwide, no study has been reported on its geographical origin or agronomic practice based on stable isotope ratios. This study aimed to evaluate the usefulness of isotopic ratios (i.e. 2 H/ 1 H, 13 C/ 12 C, 15 N/ 14 N and 18 O/ 16 O) as possible markers to discriminate the agronomic practice (conventional versus organic farming) and provenance of table grape. In order to quantitatively evaluate which of the isotopic variables were more discriminating, a t test was carried out, in light of which only δ 13 C and δ 18 O provided statistically significant differences (P ≤ 0.05) for the discrimination of geographical origin and farming method. Principal component analysis (PCA) showed no good separation of samples differing in geographical area and agronomic practice; thus, for classification purposes, supervised approaches were carried out. In particular, general discriminant analysis (GDA) was used, resulting in prediction abilities of 75.0 and 92.2% for the discrimination of farming method and origin respectively. The present findings suggest that stable isotopes (i.e. δ 18 O, δ 2 H and δ 13 C) combined with chemometrics can be successfully applied to discriminate the provenance of table grape. However, the use of bulk nitrogen isotopes was not effective for farming method discrimination. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  1. The differentiation of fibre- and drug type Cannabis seedlings by gas chromatography/mass spectrometry and chemometric tools.

    Science.gov (United States)

    Broséus, Julian; Anglada, Frédéric; Esseiva, Pierre

    2010-07-15

    Cannabis cultivation in order to produce drugs is forbidden in Switzerland. Thus, law enforcement authorities regularly ask forensic laboratories to determinate cannabis plant's chemotype from seized material in order to ascertain that the plantation is legal or not. As required by the EU official analysis protocol the THC rate of cannabis is measured from the flowers at maturity. When laboratories are confronted to seedlings, they have to lead the plant to maturity, meaning a time consuming and costly procedure. This study investigated the discrimination of fibre type from drug type Cannabis seedlings by analysing the compounds found in their leaves and using chemometrics tools. 11 legal varieties allowed by the Swiss Federal Office for Agriculture and 13 illegal ones were greenhouse grown and analysed using a gas chromatograph interfaced with a mass spectrometer. Compounds that show high discrimination capabilities in the seedlings have been identified and a support vector machines (SVMs) analysis was used to classify the cannabis samples. The overall set of samples shows a classification rate above 99% with false positive rates less than 2%. This model allows then discrimination between fibre and drug type Cannabis at an early stage of growth. Therefore it is not necessary to wait plants' maturity to quantify their amount of THC in order to determine their chemotype. This procedure could be used for the control of legal (fibre type) and illegal (drug type) Cannabis production. (c) 2010 Elsevier Ireland Ltd. All rights reserved.

  2. Source contributions and mass loadings for chemicals of emerging concern: Chemometric application of pharmaco-signature in different aquatic systems

    International Nuclear Information System (INIS)

    Jiang, Jheng-Jie; Lee, Chon-Lin; Brimblecombe, Peter; Vydrova, Lucie; Fang, Meng-Der

    2016-01-01

    To characterize the source contributions of chemicals of emerging concern (CECs) from different aquatic environments of Taiwan, we collected water samples from different aquatic systems, which were screened for 30 pharmaceuticals and illicit drugs. The total estimated mass loadings of CECs were 23.1 g/d in southern aquatic systems and 133 g/d in central aquatic systems. We developed an analytical framework combining pollutant fingerprinting, hierarchical cluster analysis (HCA), and principal component analysis with multiple linear regression (PCA-MLR) to infer the pharmaco-signature and source contributions of CECs. Based on this approach, we estimate source contributions of 62.2% for domestic inputs, 16.9% for antibiotics application, and 20.9% for drug abuse/medication in southern aquatic system, compared with 47.3% domestic, 35.1% antibiotic, and 17.6% drug abuse/medication inputs to central aquatic systems. The proposed pharmaco-signature method provides initial insights into the profile and source apportionment of CECs in complex aquatic systems, which are of importance for environmental management. - Highlights: • Pharmaco-signature provides first insights into the profile and source apportionment of CECs. • Performing HCA and PCA-MLR can discern the potential source of CECs in different aquatic systems. • Chemometric results resolved 3 factors: domestic inputs, antibiotic application and drug abuse. - The proposed pharmaco-signature method provides initial insights into the profile and source apportionment of CECs in complex aquatic systems.

  3. Essential oil composition and variability of Laurus nobilis L. growing in Tunisia, comparison and chemometric investigation of different plant organs.

    Science.gov (United States)

    Marzouki, H; Piras, A; Salah, K Bel Haj; Medini, H; Pivetta, T; Bouzid, S; Marongiu, B; Falconieri, D

    2009-01-01

    Stems, leaves, buds and flowers of Laurus nobilis L. growing wild in Tunisia were analysed for their essential oil composition. The essential oil of Laurus nobilis L. gathered from different stations were isolated by hydrodistillation and analysed by GC/MS. The oil yields on a dry weight basis ranged between 0.4% and 1.1%. The major component identified was 1,8-cineole, other predominant components were alpha-terpinyl acetate, methyl eugenol, eugenol and linalool. Although the same compounds were present in all plant organs, the leaves differed from the stems in the concentration of 1,8-cineole and methyl eugenol, buds and flowers in the concentration of 1,8-cineole and the stem's oil composition differs from the others in content of methyl eugenol. The results obtained from GC/MS analysis of the volatile oils from individual plant organs were submitted to principal component analysis. Chemometric investigations led to differentiation of stems, leaves and buds-flowers with the respect to the content of 1,8-cineole, metyhyl eugenol and alpha-terpynil acetate; flowers and buds were non-differentiated. Finally, the antibacterial activity of the leaves' essential oils has been assayed.

  4. MALDI-TOF MS and chemometric based identification of the Acinetobacter calcoaceticus-Acinetobacter baumannii complex species.

    Science.gov (United States)

    Sousa, Clara; Botelho, João; Silva, Liliana; Grosso, Filipa; Nemec, Alexandr; Lopes, João; Peixe, Luísa

    2014-07-01

    MALDI-TOF MS is becoming the technique of choice for rapid bacterial identification at species level in routine diagnostics. However, some drawbacks concerning the identification of closely related species such as those belonging to the Acinetobacter calcoaceticus-Acinetobacter baumannii (Acb) complex lead to high rates of misidentifications. In this work we successfully developed an approach that combines MALDI-TOF MS and chemometric tools to discriminate the six Acb complex species (A. baumannii, Acinetobacter nosocomialis, Acinetobacter pittii, A. calcoaceticus, genomic species "Close to 13TU" and genomic species "Between 1 and 3"). Mass spectra of 83 taxonomically well characterized clinical strains, reflecting the breadth of currently known phenetic diversity within the Acb complex, were achieved from intact cells and cell extracts and analyzed with hierarchical cluster analysis (HCA) and partial least squares discriminant analysis (PLSDA). This combined approach lead to 100% of correct species identification using mass spectra obtained from intact cells. Moreover, it was possible to discriminate two Acb complex species (genomic species "Close to 13TU" and genomic species "Between 1 and 3") not included in the MALDI Biotyper database. Copyright © 2014 Elsevier GmbH. All rights reserved.

  5. Quality Evaluation ofJuniperus rigidaSieb. et Zucc. Based on Phenolic Profiles, Bioactivity, and HPLC Fingerprint Combined with Chemometrics.

    Science.gov (United States)

    Liu, Zehua; Wang, Dongmei; Li, Dengwu; Zhang, Shuai

    2017-01-01

    Juniperus rigida ( J. rigida ) which is endemic to East Asia, has traditionally been used as an ethnomedicinal plant in China. This study was undertaken to evaluate the quality of J. rigida samples derived from 11 primary regions in China. Ten phenolic compounds were simultaneously quantified using reversed-phase high-performance liquid chromatography (RP-HPLC), and chlorogenic acid, catechin, podophyllotoxin, and amentoflavone were found to be the main compounds in J. rigida needles, with the highest contents detected for catechin and podophyllotoxin. J. rigida from Jilin (S9, S10) and Liaoning (S11) exhibited the highest contents of phenolic profiles (total phenolics, total flavonoids and 10 phenolic compounds) and the strongest antioxidant and antibacterial activities, followed by Shaanxi (S2, S3). A similarity analysis (SA) demonstrated substantial similarities in fingerprint chromatograms, from which 14 common peaks were selected. The similarity values varied from 0.85 to 0.98. Chemometrics techniques, including hierarchical cluster analysis (HCA), principal component analysis (PCA), and discriminant analysis (DA), were further applied to facilitate accurate classification and quantification of the J. rigida samples derived from the 11 regions. The results supported HPLC data showing that all J. rigida samples exhibit considerable variations in phenolic profiles, and the samples were further clustered into three major groups coincident with their geographical regions of origin. In addition, two discriminant functions with a 100% discrimination ratio were constructed to further distinguish and classify samples with unknown membership on the basis of eigenvalues to allow optimal discrimination among the groups. Our comprehensive findings on matching phenolic profiles and bioactivities along with data from fingerprint chromatograms with chemometrics provide an effective tool for screening and quality evaluation of J. rigida and related medicinal preparations.

  6. Characterization of mammalian cell culture raw materials by combining spectroscopy and chemometrics

    Science.gov (United States)

    Trunfio, Nicholas; Lee, Haewoo; Starkey, Jason; Agarabi, Cyrus; Liu, Jay

    2017-01-01

    Two of the primary issues with characterizing the variability of raw materials used in mammalian cell culture, such as wheat hydrolysate, is that the analyses of these materials can be time consuming, and the results of the analyses are not straightforward to interpret. To solve these issues, spectroscopy can be combined with chemometrics to provide a quick, robust and easy to understand methodology for the characterization of raw materials; which will improve cell culture performance by providing an assessment of the impact that a given raw material will have on final product quality. In this study, four spectroscopic technologies: near infrared spectroscopy, middle infrared spectroscopy, Raman spectroscopy, and fluorescence spectroscopy were used in conjunction with principal component analysis to characterize the variability of wheat hydrolysates, and to provide evidence that the classification of good and bad lots of raw material is possible. Then, the same spectroscopic platforms are combined with partial least squares regressions to quantitatively predict two cell culture critical quality attributes (CQA): integrated viable cell density and IgG titer. The results showed that near infrared (NIR) spectroscopy and fluorescence spectroscopy are capable of characterizing the wheat hydrolysate's chemical structure, with NIR performing slightly better; and that they can be used to estimate the raw materials’ impact on the CQAs. These results were justified by demonstrating that of all the components present in the wheat hydrolysates, six amino acids: arginine, glycine, phenylalanine, tyrosine, isoleucine and threonine; and five trace elements: copper, phosphorus, molybdenum, arsenic and aluminum, had a large, statistically significant effect on the CQAs, and that NIR and fluorescence spectroscopy performed the best for characterizing the important amino acids. It was also found that the trace elements of interest were not characterized well by any of the spectral

  7. Characterization of mammalian cell culture raw materials by combining spectroscopy and chemometrics.

    Science.gov (United States)

    Trunfio, Nicholas; Lee, Haewoo; Starkey, Jason; Agarabi, Cyrus; Liu, Jay; Yoon, Seongkyu

    2017-07-01

    Two of the primary issues with characterizing the variability of raw materials used in mammalian cell culture, such as wheat hydrolysate, is that the analyses of these materials can be time consuming, and the results of the analyses are not straightforward to interpret. To solve these issues, spectroscopy can be combined with chemometrics to provide a quick, robust and easy to understand methodology for the characterization of raw materials; which will improve cell culture performance by providing an assessment of the impact that a given raw material will have on final product quality. In this study, four spectroscopic technologies: near infrared spectroscopy, middle infrared spectroscopy, Raman spectroscopy, and fluorescence spectroscopy were used in conjunction with principal component analysis to characterize the variability of wheat hydrolysates, and to provide evidence that the classification of good and bad lots of raw material is possible. Then, the same spectroscopic platforms are combined with partial least squares regressions to quantitatively predict two cell culture critical quality attributes (CQA): integrated viable cell density and IgG titer. The results showed that near infrared (NIR) spectroscopy and fluorescence spectroscopy are capable of characterizing the wheat hydrolysate's chemical structure, with NIR performing slightly better; and that they can be used to estimate the raw materials' impact on the CQAs. These results were justified by demonstrating that of all the components present in the wheat hydrolysates, six amino acids: arginine, glycine, phenylalanine, tyrosine, isoleucine and threonine; and five trace elements: copper, phosphorus, molybdenum, arsenic and aluminum, had a large, statistically significant effect on the CQAs, and that NIR and fluorescence spectroscopy performed the best for characterizing the important amino acids. It was also found that the trace elements of interest were not characterized well by any of the spectral

  8. Traceability of Opuntia ficus-indica L. Miller by ICP-MS multi-element profile and chemometric approach.

    Science.gov (United States)

    Mottese, Antonio Francesco; Naccari, Clara; Vadalà, Rossella; Bua, Giuseppe Daniel; Bartolomeo, Giovanni; Rando, Rossana; Cicero, Nicola; Dugo, Giacomo

    2018-01-01

    Opuntia ficus-indica L. Miller fruits, particularly 'Ficodindia dell'Etna' of Biancavilla (POD), 'Fico d'india tradizionale di Roccapalumba' with protected brand and samples from an experimental field in Pezzolo (Sicily) were analyzed by inductively coupled plasma mass spectrometry in order to determine the multi-element profile. A multivariate chemometric approach, specifically principal component analysis (PCA), was applied to individuate how mineral elements may represent a marker of geographic origin, which would be useful for traceability. PCA has allowed us to verify that the geographical origin of prickly pear fruits is significantly influenced by trace element content, and the results found in Biancavilla PDO samples were linked to the geological composition of this volcanic areas. It was observed that two principal components accounted for 72.03% of the total variance in the data and, in more detail, PC1 explains 45.51% and PC2 26.52%, respectively. This study demonstrated that PCA is an integrated tool for the traceability of food products and, at the same time, a useful method of authentication of typical local fruits such as prickly pear. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  9. Chemometric-assisted QuEChERS extraction method for post-harvest pesticide determination in fruits and vegetables

    Science.gov (United States)

    Li, Minmin; Dai, Chao; Wang, Fengzhong; Kong, Zhiqiang; He, Yan; Huang, Ya Tao; Fan, Bei

    2017-02-01

    An effective analysis method was developed based on a chemometric tool for the simultaneous quantification of five different post-harvest pesticides (2,4-dichlorophenoxyacetic acid (2,4-D), carbendazim, thiabendazole, iprodione, and prochloraz) in fruits and vegetables. In the modified QuEChERS (quick, easy, cheap, effective, rugged and safe) method, the factors and responses for optimization of the extraction and cleanup analyses were compared using the Plackett-Burman (P-B) screening design. Furthermore, the significant factors (toluene percentage, hydrochloric acid (HCl) percentage, and graphitized carbon black (GCB) amount) were optimized using a central composite design (CCD) combined with Derringer’s desirability function (DF). The limits of quantification (LOQs) were estimated to be 1.0 μg/kg for 2,4-D, carbendazim, thiabendazole, and prochloraz, and 1.5 μg/kg for iprodione in food matrices. The mean recoveries were in the range of 70.4-113.9% with relative standard deviations (RSDs) of less than 16.9% at three spiking levels. The measurement uncertainty of the analytical method was determined using the bottom-up approach, which yielded an average value of 7.6%. Carbendazim was most frequently found in real samples analyzed using the developed method. Consequently, the analytical method can serve as an advantageous and rapid tool for determination of five preservative pesticides in fruits and vegetables.

  10. Rapid Quantification of Methamphetamine: Using Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR) and Chemometrics

    Science.gov (United States)

    Hughes, Juanita; Ayoko, Godwin; Collett, Simon; Golding, Gary

    2013-01-01

    In Australia and increasingly worldwide, methamphetamine is one of the most commonly seized drugs analysed by forensic chemists. The current well-established GC/MS methods used to identify and quantify methamphetamine are lengthy, expensive processes, but often rapid analysis is requested by undercover police leading to an interest in developing this new analytical technique. Ninety six illicit drug seizures containing methamphetamine (0.1%–78.6%) were analysed using Fourier Transform Infrared Spectroscopy with an Attenuated Total Reflectance attachment and Chemometrics. Two Partial Least Squares models were developed, one using the principal Infrared Spectroscopy peaks of methamphetamine and the other a Hierarchical Partial Least Squares model. Both of these models were refined to choose the variables that were most closely associated with the methamphetamine % vector. Both of the models were excellent, with the principal peaks in the Partial Least Squares model having Root Mean Square Error of Prediction 3.8, R2 0.9779 and lower limit of quantification 7% methamphetamine. The Hierarchical Partial Least Squares model had lower limit of quantification 0.3% methamphetamine, Root Mean Square Error of Prediction 5.2 and R2 0.9637. Such models offer rapid and effective methods for screening illicit drug samples to determine the percentage of methamphetamine they contain. PMID:23936058

  11. A Chemometrics Approach for Nuclear Magnetic Resonance Data to Characterize the Partial Metabolome Banana Peels from Southern Brazil.

    Science.gov (United States)

    Cardoso, Sara; Maraschin, Marcelo; Peruch, Luiz Augusto Martins; Rocha, Miguel; Pereira, Aline

    2017-12-13

    Banana peels are well recognized as a source of important bioactive compounds, such as phenolics, carotenoids, biogenic amines, among others. As such, they have recently started to be used for industrial purposes. However, its composition seems to be strongly affected by biotic or abiotic ecological factors. Thus, this study aimed to investigate banana peels chemical composition, not only to get insights on eventual metabolic changes caused by the seasons, in southern Brazil, but also to identify the most relevant metabolites for these processes. To achieve this, a Nuclear magnetic resonance (NMR)-based metabolic profiling strategy was adopted, followed by chemometrics analysis, using the specmine package for the R environment, and metabolite identification. The results showed that the metabolomic approach adopted allowed identifying a series of primary and secondary metabolites in the aqueous extracts investigated. Besides, over the seasons the metabolic profiles of the banana peels showed to contain biologically active compounds relevant to the skin wound healing process, indicating the biotechnological potential of that raw material.

  12. Prediction of peroxide value in omega-3 rich microalgae oil by ATR-FTIR spectroscopy combined with chemometrics.

    Science.gov (United States)

    Cebi, Nur; Yilmaz, Mustafa Tahsin; Sagdic, Osman; Yuce, Hande; Yelboga, Emrah

    2017-06-15

    Our work explored, for the first time, monitoring peroxide value (PV) of omega-3 rich algae oil using ATR-FTIR spectroscopic technique. The PV of the developed method was compared by that obtained by standard method of Association of Official Analytical Chemists (AOAC). In this study, peak area integration (PAI), Partial Least Squares Regression (PLSR), and Principal Component Regression (PCR) were used as the calibration techniques. PV obtained by the AOAC method and by FTIR-ATR technique were well correlated considering the peak area related to trans double bonds and chemometrics techniques of PLSR and PCR. Calibration model was established using the band with a peak point at 966cm -1 (990-940cm -1 ) related to CH out of plane deformation vibration of trans double bond. Algae oil oxidation could be successfully quantified using PAI, PLSR and PCR techniques. Additionally, hierarchical cluster analysis was performed and significant discrimination was observed coherently with oxidation process. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Quantification and Classification of Corn and Sunflower Oils as Adulterants in Olive Oil Using Chemometrics and FTIR Spectra

    Science.gov (United States)

    Rohman, Abdul; Che Man, Y. B.

    2012-01-01

    Commercially, extra virgin olive oil (EVOO) is subjected to be adulterated with low-price oils having similar color to EVOO. Fourier transform infrared (FTIR) spectroscopy combined with chemometrics has been successfully used for classification and quantification of corn (CO) and sunflower oils (SFOs) in EVOO sets. The combined frequency regions of 3027–3000, 1076–860, and 790–698 cm−1 were used for classification and quantification of CO in EVOO; meanwhile, SFO was analyzed using frequency regions of 3025–3000 and 1400–985 cm−1. Discriminant analysis can make classification of pure EVOO and EVOO adulterated with CO and SFO with no misclassification reported. The presence of CO in EVOO was determined with the aid of partial least square calibration using FTIR normal spectra. The calibration and validation errors obtained in CO's quantification are 0.404 and 1.13%, respectively. Meanwhile, the first derivative FTIR spectra and PLS calibration model were preferred for quantification of SFO in EVOO with high coefficient of determination (R 2) and low errors, either in calibration or in validation sample sets. PMID:22448127

  14. PG-Metrics: A chemometric-based approach for classifying bacterial peptidoglycan data sets and uncovering their subjacent chemical variability.

    Directory of Open Access Journals (Sweden)

    Keshav Kumar

    Full Text Available Bacteria cells are protected from osmotic and environmental stresses by an exoskeleton-like polymeric structure called peptidoglycan (PG or murein sacculus. This structure is fundamental for bacteria's viability and thus, the mechanisms underlying cell wall assembly and how it is modulated serve as targets for many of our most successful antibiotics. Therefore, it is now more important than ever to understand the genetics and structural chemistry of the bacterial cell walls in order to find new and effective methods of blocking it for the treatment of disease. In the last decades, liquid chromatography and mass spectrometry have been demonstrated to provide the required resolution and sensitivity to characterize the fine chemical structure of PG. However, the large volume of data sets that can be produced by these instruments today are difficult to handle without a proper data analysis workflow. Here, we present PG-metrics, a chemometric based pipeline that allows fast and easy classification of bacteria according to their muropeptide chromatographic profiles and identification of the subjacent PG chemical variability between e.g. bacterial species, growth conditions and, mutant libraries. The pipeline is successfully validated here using PG samples from different bacterial species and mutants in cell wall proteins. The obtained results clearly demonstrated that PG-metrics pipeline is a valuable bioanalytical tool that can lead us to cell wall classification and biomarker discovery.

  15. Application of chemometric methods to resolve intermediates formed during photo- catalytic degradation of methyl orange and textile wastewater from Ethiopia

    Directory of Open Access Journals (Sweden)

    Z. Aregahegn

    2017-11-01

    Full Text Available The efficiency of two catalysts (TiO2 and TiO2 supported on zeolite for the photocatalytic degradation of methyl orange dye and wastewaters from Ethiopian textile industry was evaluated by chemometric methods from UV/Vis data of the reaction mixtures at different times. Multivariate curve resolution statistical analysis combined with an alternating least squares algorithm (MCR-ALS proved to be an efficient method to resolve the different intermediates present during the photocatalytic degradation of the pollutants and to provide information about their evolution with time. Methyl orange photodegradation at pH = 3 showed different intermediate and concentration profiles than at pH = 6. The evolution of intermediates from textile wastewater photodegradation could also be resolved by this method. From the concentration profile or the reactants, a kinetic study was done. Results revealed that all the photodegradation reactions followed a first order kinetics. When TiO2 supported in Zeolite is used, reactions are in general slower, probably due to a mechanism of adsorption/desorption.

  16. Utilization of Chemometric Technique to Determine the Quality of Fresh and Used Palm, Corn and Coconut Oil

    International Nuclear Information System (INIS)

    Hamizah Mat Agil; Mohd Zuli Jaafar; Suzeren Jamil; Azwan Mat Lazim

    2014-01-01

    This study was conducted to evaluate the quality of natural oil and the deterioration of frying oil. A total of 12 different oil samples from palm oil, corn oil and coconut oil were used. The frying process was repeated four times at 180 degree Celsius in order to observe the stability of the oil towards oxidation. Three main parameters have been studied to determine oil qualities which were peroxide value, iodine value and acid value. This study emphasized on the usage of FTIR in the range of 4000-700 cm -1 . Alternatively, the chemometrics method based on pattern recognition has been used to determination the oil quality. Data analysis were conducted by using PCA and PLS method in the Matlab modeling. The PCA provided data classification according to types of oil while PLS predicted the oil quality of the parameters studied. For the classification of pure oil, the variance for PC1 was 70 % while PC2 was 15 %. For the fried/ used oil, PC1 gave 57 % while PC2 gave 25 %. By using PLS, the iodine the best model for pure oils value model variable based on correlation with R2CV > 0.984. Whereas, the peroxide value model for fried/ used oils, was the best obtained R 2 CV > 0.7423. (author)

  17. PG-Metrics: A chemometric-based approach for classifying bacterial peptidoglycan data sets and uncovering their subjacent chemical variability.

    Science.gov (United States)

    Kumar, Keshav; Espaillat, Akbar; Cava, Felipe

    2017-01-01

    Bacteria cells are protected from osmotic and environmental stresses by an exoskeleton-like polymeric structure called peptidoglycan (PG) or murein sacculus. This structure is fundamental for bacteria's viability and thus, the mechanisms underlying cell wall assembly and how it is modulated serve as targets for many of our most successful antibiotics. Therefore, it is now more important than ever to understand the genetics and structural chemistry of the bacterial cell walls in order to find new and effective methods of blocking it for the treatment of disease. In the last decades, liquid chromatography and mass spectrometry have been demonstrated to provide the required resolution and sensitivity to characterize the fine chemical structure of PG. However, the large volume of data sets that can be produced by these instruments today are difficult to handle without a proper data analysis workflow. Here, we present PG-metrics, a chemometric based pipeline that allows fast and easy classification of bacteria according to their muropeptide chromatographic profiles and identification of the subjacent PG chemical variability between e.g. bacterial species, growth conditions and, mutant libraries. The pipeline is successfully validated here using PG samples from different bacterial species and mutants in cell wall proteins. The obtained results clearly demonstrated that PG-metrics pipeline is a valuable bioanalytical tool that can lead us to cell wall classification and biomarker discovery.

  18. Multi-wavelength HPLC fingerprints from complex substances: An exploratory chemometrics study of the Cassia seed example

    International Nuclear Information System (INIS)

    Ni Yongnian; Lai Yanhua; Brandes, Sarina; Kokot, Serge

    2009-01-01

    Multi-wavelength fingerprints of Cassia seed, a traditional Chinese medicine (TCM), were collected by high-performance liquid chromatography (HPLC) at two wavelengths with the use of diode array detection. The two data sets of chromatograms were combined by the data fusion-based method. This data set of fingerprints was compared separately with the two data sets collected at each of the two wavelengths. It was demonstrated with the use of principal component analysis (PCA), that multi-wavelength fingerprints provided a much improved representation of the differences in the samples. Thereafter, the multi-wavelength fingerprint data set was submitted for classification to a suite of chemometrics methods viz. fuzzy clustering (FC), SIMCA and the rank ordering MCDM PROMETHEE and GAIA. Each method highlighted different properties of the data matrix according to the fingerprints from different types of Cassia seeds. In general, the PROMETHEE and GAIA MCDM methods provided the most comprehensive information for matching and discrimination of the fingerprints, and appeared to be best suited for quality assurance purposes for these and similar types of sample.

  19. Comprehensive two-dimensional gas chromatographic profiling and chemometric interpretation of the volatile profiles of sweat in knit fabrics.

    Science.gov (United States)

    de la Mata, A Paulina; McQueen, Rachel H; Nam, Seo Lin; Harynuk, James J

    2017-03-01

    Human axillary sweat is a poorly explored biofluid within the context of metabolomics when compared to other fluids such as blood and urine. In this paper, we explore the volatile organic compounds emitted from two different types of fabric samples (cotton and polyester) which had been worn repeatedly during exercise by participants. Headspace solid-phase microextraction (SPME) and comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) were employed to profile the (semi)volatile compounds on the fabric. Principal component analysis models were applied to the data to aid in visualizing differences between types of fabrics, wash treatment, and the gender of the subject who had worn the fabric. Statistical tools included with commercial chromatography software (ChromaTOF) and a simple Fisher ratio threshold-based feature selection for model optimization are compared with a custom-written algorithm that uses cluster resolution as an objective function to maximize in a hybrid backward-elimination forward-selection approach for optimizing the chemometric models in an effort to identify some compounds that correlate to differences between fabric types. The custom algorithm is shown to generate better models than the simple Fisher ratio approach. Graphical Abstract A route from samples and questions to data and then answers.