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.

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.

Multi-wavelength HPLC fingerprints from complex substances: An exploratory chemometrics study of the Cassia seed example

Energy Technology Data Exchange (ETDEWEB)

Ni Yongnian, E-mail: ynni@ncu.edu.cn [Stake Laboratory of Food Science and Technology, Nanchang University, Nanchang, Jiangxi 330047 (China); Department of Chemistry, Nanchang University, Nanchang, Jiangxi 330047 (China); Lai Yanhua [Department of Chemistry, Nanchang University, Nanchang, Jiangxi 330047 (China); Brandes, Sarina; Kokot, Serge [Applied Chemistry Cluster, School of Physical and Chemical Sciences, Queensland University of Technology, Brisbane, Queensland 4001 (Australia)

2009-08-11

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.

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.

Multi-wavelength HPLC fingerprints from complex substances: An exploratory chemometrics study of the Cassia seed example.

Science.gov (United States)

Ni, Yongnian; Lai, Yanhua; Brandes, Sarina; Kokot, Serge

2009-08-11

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.

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.

Application of PCA and SIMCA statistical analysis of FT-IR spectra for the classification and identification of different slag types with environmental origin.

Science.gov (United States)

Stumpe, B; Engel, T; Steinweg, B; Marschner, B

2012-04-03

In the past, different slag materials were often used for landscaping and construction purposes or simply dumped. Nowadays German environmental laws strictly control the use of slags, but there is still a remaining part of 35% which is uncontrolled dumped in landfills. Since some slags have high heavy metal contents and different slag types have typical chemical and physical properties that will influence the risk potential and other characteristics of the deposits, an identification of the slag types is needed. We developed a FT-IR-based statistical method to identify different slags classes. Slags samples were collected at different sites throughout various cities within the industrial Ruhr area. Then, spectra of 35 samples from four different slags classes, ladle furnace (LF), blast furnace (BF), oxygen furnace steel (OF), and zinc furnace slags (ZF), were determined in the mid-infrared region (4000-400 cm(-1)). The spectra data sets were subject to statistical classification methods for the separation of separate spectral data of different slag classes. Principal component analysis (PCA) models for each slag class were developed and further used for soft independent modeling of class analogy (SIMCA). Precise classification of slag samples into four different slag classes were achieved using two different SIMCA models stepwise. At first, SIMCA 1 was used for classification of ZF as well as OF slags over the total spectral range. If no correct classification was found, then the spectrum was analyzed with SIMCA 2 at reduced wavenumbers for the classification of LF as well as BF spectra. As a result, we provide a time- and cost-efficient method based on FT-IR spectroscopy for processing and identifying large numbers of environmental slag samples.

Determination of Commercials Cooking Oils and Fats Using Chemometrics Methods

International Nuclear Information System (INIS)

Azwan Mat Lazim; Mohd Zuli Jaafar; Phang Wei Shong, P.W.; Suzereen Jamil

2013-01-01

In this study, chemometric method has been used in determining the oil quality. The samples used were olive oil, sunflower oil and butter from two different brands. Two different conditions were applied, either it was fresh or fried. Titratio, a conventional method was used to determine free fatty acids content (FFA), iodine value (IV), and peroxide value (PV). Twelve samples were then used for analysis and their FTIR spectra were measured at 4000-400 cm -1 . The computer stimulation was used to process the data based on their pattern recognition which optimized by principal component analysis (PCA) and partial least squares (PLS). PCA model was used to distinguish the properties between fresh and fried oil. The PLS model was used to predict the value for validation test in comparison with conventional results. Results showed the validation value for fresh oil was 0.90. This indicated the chemometric method was in agreement with conventional method. (author)

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

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

Chemometric methods and near-infrared spectroscopy applied to bioenergy production

International Nuclear Information System (INIS)

Liebmann, B.

2010-01-01

The present work examines bioenergy production from different viewpoints. The three main objectives are: (1) to reveal the relation of technology, sustainability and economy in bioenergy processes; (2) to investigate spectroscopic methods as a tool for analytical monitoring of bioenergy processes; and (3) to develop new chemometric methods for advanced analysis of spectroscopic data. At the first stage, this thesis investigates the technological, ecological, and economic features of renewable-resource-based and de-centralized bioenergy production systems. In different scenarios, small-scale bioethanol production is combined with other technologies that provide renewable energy from residuals of the bioethanol process. The general aim is to substitute fossil energy conventionally used within the bioethanol process. The investigated technologies are biogas production and straw incineration. Agricultural aspects are introduced by sustainable crop rotation concepts that reconcile food, feed, and biofuel production. The sustainability of small-scale bioethanol production in the different scenarios is quantified by an ecological footprint method, the sustainable process index, SPI, and compared to conventional fuels. The main findings are: (i) small-scaled bioethanol production can be operated with 100 % renewable energy supply, (ii) the SPI of bioethanol can be reduced up to 92 % compared to conventional fuels, (iii) a complex trade-off between ecology-of-scale and economy-of-scale is necessary. At the second stage, this thesis approaches bioenergy production processes from an analytical perspective, and presents near-infrared spectroscopy (NIR) as promising method for fast process monitoring of bioethanol production and biomass characterization. In addition, new analytical methods are presented for a fast determination of the heating value of solid biomass fuel, based on IR and NIR spectroscopy. The main findings are that NIR spectroscopy and appropriate chemometric

Non-targeted detection of chemical contamination in carbonated soft drinks using NMR spectroscopy, variable selection and chemometrics

Energy Technology Data Exchange (ETDEWEB)

Charlton, Adrian J. [Department for Environment, Food and Rural Affairs, Central Science Laboratory, Sand Hutton, York YO41 1LZ (United Kingdom)], E-mail: adrian.charlton@csl.gov.uk; Robb, Paul; Donarski, James A.; Godward, John [Department for Environment, Food and Rural Affairs, Central Science Laboratory, Sand Hutton, York YO41 1LZ (United Kingdom)

2008-06-23

An efficient method for detecting malicious and accidental contamination of foods has been developed using a combined {sup 1}H nuclear magnetic resonance (NMR) and chemometrics approach. The method has been demonstrated using a commercially available carbonated soft drink, as being capable of identifying atypical products and to identify contaminant resonances. Soft-independent modelling of class analogy (SIMCA) was used to compare {sup 1}H NMR profiles of genuine products (obtained from the manufacturer) against retail products spiked in the laboratory with impurities. The benefits of using feature selection for extracting contaminant NMR frequencies were also assessed. Using example impurities (paraquat, p-cresol and glyphosate) NMR spectra were analysed using multivariate methods resulting in detection limits of approximately 0.075, 0.2, and 0.06 mM for p-cresol, paraquat and glyphosate, respectively. These detection limits are shown to be approximately 100-fold lower than the minimum lethal dose for paraquat. The methodology presented here is used to assess the composition of complex matrices for the presence of contaminating molecules without a priori knowledge of the nature of potential contaminants. The ability to detect if a sample does not fit into the expected profile without recourse to multiple targeted analyses is a valuable tool for incident detection and forensic applications.

Non-targeted detection of chemical contamination in carbonated soft drinks using NMR spectroscopy, variable selection and chemometrics

International Nuclear Information System (INIS)

Charlton, Adrian J.; Robb, Paul; Donarski, James A.; Godward, John

2008-01-01

An efficient method for detecting malicious and accidental contamination of foods has been developed using a combined 1 H nuclear magnetic resonance (NMR) and chemometrics approach. The method has been demonstrated using a commercially available carbonated soft drink, as being capable of identifying atypical products and to identify contaminant resonances. Soft-independent modelling of class analogy (SIMCA) was used to compare 1 H NMR profiles of genuine products (obtained from the manufacturer) against retail products spiked in the laboratory with impurities. The benefits of using feature selection for extracting contaminant NMR frequencies were also assessed. Using example impurities (paraquat, p-cresol and glyphosate) NMR spectra were analysed using multivariate methods resulting in detection limits of approximately 0.075, 0.2, and 0.06 mM for p-cresol, paraquat and glyphosate, respectively. These detection limits are shown to be approximately 100-fold lower than the minimum lethal dose for paraquat. The methodology presented here is used to assess the composition of complex matrices for the presence of contaminating molecules without a priori knowledge of the nature of potential contaminants. The ability to detect if a sample does not fit into the expected profile without recourse to multiple targeted analyses is a valuable tool for incident detection and forensic applications

Chemometrics in spectroscopy. Part 1. Classical chemometrics

International Nuclear Information System (INIS)

Geladi, Paul

2003-01-01

An overview is given of chemometrics as it can be applied to spectroscopic and other multivariate data. Major chemometrics and data analysis techniques are described. An important aspect is the focus on soft modeling for situations that are too complicated for the traditional hard models to work. Also measurement noise is given due attention. A small example is used to illustrate some ways of working, mainly by using graphics. Selected literature references are given. Part 1 deals with classical chemometrics. Part 2 presents some newer developments and includes some more elaborated examples

Assessing the varietal origin of extra-virgin olive oil using liquid chromatography fingerprints of phenolic compound, data fusion and chemometrics.

Science.gov (United States)

Bajoub, Aadil; Medina-Rodríguez, Santiago; Gómez-Romero, María; Ajal, El Amine; Bagur-González, María Gracia; Fernández-Gutiérrez, Alberto; Carrasco-Pancorbo, Alegría

2017-01-15

High Performance Liquid Chromatography (HPLC) with diode array (DAD) and fluorescence (FLD) detection was used to acquire the fingerprints of the phenolic fraction of monovarietal extra-virgin olive oils (extra-VOOs) collected over three consecutive crop seasons (2011/2012-2013/2014). The chromatographic fingerprints of 140 extra-VOO samples processed from olive fruits of seven olive varieties, were recorded and statistically treated for varietal authentication purposes. First, DAD and FLD chromatographic-fingerprint datasets were separately processed and, subsequently, were joined using "Low-level" and "Mid-Level" data fusion methods. After the preliminary examination by principal component analysis (PCA), three supervised pattern recognition techniques, Partial Least Squares Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogies (SIMCA) and K-Nearest Neighbors (k-NN) were applied to the four chromatographic-fingerprinting matrices. The classification models built were very sensitive and selective, showing considerably good recognition and prediction abilities. The combination "chromatographic dataset+chemometric technique" allowing the most accurate classification for each monovarietal extra-VOO was highlighted. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Voltammetric fingerprinting of oils and its combination with chemometrics for the detection of extra virgin olive oil adulteration.

Science.gov (United States)

Tsopelas, Fotios; Konstantopoulos, Dimitris; Kakoulidou, Anna Tsantili

2018-07-26

In the present work, two approaches for the voltammetric fingerprinting of oils and their combination with chemometrics were investigated in order to detect the adulteration of extra virgin olive oil with olive pomace oil as well as the most common seed oils, namely sunflower, soybean and corn oil. In particular, cyclic voltammograms of diluted extra virgin olive oils, regular (pure) olive oils (blends of refined olive oils with virgin olive oils), olive pomace oils and seed oils in presence of dichloromethane and 0.1 M of LiClO 4 in EtOH as electrolyte were recorded at a glassy carbon working electrode. Cyclic voltammetry was also employed in methanolic extracts of olive and seed oils. Datapoints of cyclic voltammograms were exported and submitted to Principal Component Analysis (PCA), Partial Least Square- Discriminant Analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA). In diluted oils, PLS-DA provided a clear discrimination between olive oils (extra virgin and regular) and olive pomace/seed oils, while SIMCA showed a clear discrimination of extra virgin olive oil in regard to all other samples. Using methanolic extracts and considering datapoints recorded between 0.6 and 1.3 V, PLS-DA provided more information, resulting in three clusters-extra virgin olive oils, regular olive oils and seed/olive pomace oils-while SIMCA showed inferior performance. For the quantification of extra virgin olive oil adulteration with olive pomace oil or seed oils, a model based on Partial Least Square (PLS) analysis was developed. Detection limit of adulteration in olive oil was found to be 2% (v/v) and the linearity range up to 33% (v/v). Validation and applicability of all models was proved using a suitable test set. In the case of PLS, synthetic oil mixtures with 4 known adulteration levels in the range of 4-26% were also employed as a blind test set. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

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

2016-01-01

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. PMID:28231172

Chemometrics and chromatographic fingerprints to classify plant food supplements according to the content of regulated plants.

Science.gov (United States)

Deconinck, E; Sokeng Djiogo, C A; Courselle, P

2017-09-05

Plant food supplements are gaining popularity, resulting in a broader spectrum of available products and an increased consumption. Next to the problem of adulteration of these products with synthetic drugs the presence of regulated or toxic plants is an important issue, especially when the products are purchased from irregular sources. This paper focusses on this problem by using specific chromatographic fingerprints for five targeted plants and chemometric classification techniques in order to extract the important information from the fingerprints and determine the presence of the targeted plants in plant food supplements in an objective way. Two approaches were followed: (1) a multiclass model, (2) 2-class model for each of the targeted plants separately. For both approaches good classification models were obtained, especially when using SIMCA and PLS-DA. For each model, misclassification rates for the external test set of maximum one sample could be obtained. The models were applied to five real samples resulting in the identification of the correct plants, confirmed by mass spectrometry. Therefore chromatographic fingerprinting combined with chemometric modelling can be considered interesting to make a more objective decision on whether a regulated plant is present in a plant food supplement or not, especially when no mass spectrometry equipment is available. The results suggest also that the use of a battery of 2-class models to screen for several plants is the approach to be preferred. Copyright © 2017 Elsevier B.V. All rights reserved.

Qualitative analysis of pure and adulterated canola oil via SIMCA

Science.gov (United States)

Basri, Katrul Nadia; Khir, Mohd Fared Abdul; Rani, Rozina Abdul; Sharif, Zaiton; Rusop, M.; Zoolfakar, Ahmad Sabirin

2018-05-01

This paper demonstrates the utilization of near infrared (NIR) spectroscopy to classify pure and adulterated sample of canola oil. Soft Independent Modeling Class Analogies (SIMCA) algorithm was implemented to discriminate the samples to its classes. Spectral data obtained was divided using Kennard Stone algorithm into training and validation dataset by a fixed ratio of 7:3. The model accuracy obtained based on the model built is 0.99 whereas the sensitivity and precision are 0.92 and 1.00. The result showed the classification model is robust to perform qualitative analysis of canola oil for future application.

Laser-induced breakdown spectroscopy and chemometrics for classification of toys relying on toxic elements

International Nuclear Information System (INIS)

Godoi, Quienly; Leme, Flavio O.; Trevizan, Lilian C.; Pereira Filho, Edenir R.; Rufini, Iolanda A.; Santos, Dario; Krug, Francisco J.

2011-01-01

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.

Differentiation of Body Fluid Stains on Fabrics Using External Reflection Fourier Transform Infrared Spectroscopy (FT-IR) and Chemometrics.

Science.gov (United States)

Zapata, Félix; de la Ossa, Ma Ángeles Fernández; García-Ruiz, Carmen

2016-04-01

Body fluids are evidence of great forensic interest due to the DNA extracted from them, which allows genetic identification of people. This study focuses on the discrimination among semen, vaginal fluid, and urine stains (main fluids in sexual crimes) placed on different colored cotton fabrics by external reflection Fourier transform infrared spectroscopy (FT-IR) combined with chemometrics. Semen-vaginal fluid mixtures and potential false positive substances commonly found in daily life such as soaps, milk, juices, and lotions were also studied. Results demonstrated that the IR spectral signature obtained for each body fluid allowed its identification and the correct classification of unknown stains by means of principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA). Interestingly, results proved that these IR spectra did not show any bands due to the color of the fabric and no substance of those present in daily life which were analyzed, provided a false positive. © The Author(s) 2016.

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

International Nuclear Information System (INIS)

Santos, Maiara S.; Pereira-Filho, Edenir R.; Ferreira, Antonio G.; Boffo, Elisangela F.; Figueira, Glyn M.

2012-01-01

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, 1 H HR-MAS NMR and 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)

Análise multivariada aplicada na identificação de fármacos antidepressivos. Parte II: Análise por componentes principais (PCA e o método de classificação SIMCA Multivariate analysis to applied in the identification of antidepressants. Part II: principal components analysis (PCA and soft independent modeling of class analogies (SIMCA

Directory of Open Access Journals (Sweden)

Janusa Goelzer Sabin

2004-09-01

Full Text Available Neste trabalho a identificação e a discriminação de dois diferentes fármacos utilizados como antidepressivos foi estudada, empregando os espectros de reflexão difusa no infravermelho médio com transformada de Fourier (DRIFTS, juntamente com a análise de componentes principais (PCA e o método de classificação SIMCA. Os espectros no infravermelho de amostras contendo diferentes concentrações dos princípios ativos cloridrato de amitriptilina e cloridrato de imipramina, foram coletados em um espectrofotômetro NICOLET Magna 550, sendo realizadas 2 réplicas para cada amostra, com resolução de 4 cm-1 e 32 varreduras. A análise de componentes principais confirmou a existência de dois grupos distintos, correspondendo aos dois diferentes princípios ativos utilizados, além de evidenciar a presença de amostras anômalas no conjunto de dados que, possivelmente, iriam interferir na modelagem. Já o método de classificação SIMCA possibilitou o reconhecimento de amostras dos princípios ativos cloridrato de imipramina e cloridrato de amitriptilina com resultados indicando 100% de classificação correta das classes modeladas.In this work the certification of two different drugs used as antidepressants was studied, using diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS, together with the analysis of principal components (PCA and the method of soft independent modeling of class analogies (SIMCA. The DRIFT spectra of samples with different concentrations of the active principles amitriptiline and imipramine hydrochlorides had been collected in Magna 550 spectrofotometer, two spectra for each sample, with resolution of 4 cm-1 and 32 scans. The PCA confirmed the existence of two distinct groups, corresponding to the two different active principles used. Otherwise the method of classification SIMCA made possible the recognition of samples of the principles amitriptyline and imipramine hydrochlorides with results indicating

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)

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.

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)

Authenticity assessment of banknotes using portable near infrared spectrometer and chemometrics.

Science.gov (United States)

da Silva Oliveira, Vanessa; Honorato, Ricardo Saldanha; Honorato, Fernanda Araújo; Pereira, Claudete Fernandes

2018-05-01

Spectra recorded using a portable near infrared (NIR) spectrometer, Soft Independent Modeling of Class Analogy (SIMCA) and Linear Discriminant Analysis (LDA) associated to Successive Projections Algorithm (SPA) models were applied to identify counterfeit and authentic Brazilian Real (R$20, R$50 and R$100) banknotes, enabling a simple field analysis. NIR spectra (950-1650nm) were recorded from seven different areas of the banknotes (two with fluorescent ink, one over watermark, three with intaglio printing process and one over the serial numbers with typography printing). SIMCA and SPA-LDA models were built using 1st derivative preprocessed spectral data from one of the intaglio areas. For the SIMCA models, all authentic (300) banknotes were correctly classified and the counterfeits (227) were not classified. For the two classes SPA-LDA models (authentic and counterfeit currencies), all the test samples were correctly classified into their respective class. The number of selected variables by SPA varied from two to nineteen for R$20, R$50 and R$100 currencies. These results show that the use of the portable near-infrared with SIMCA or SPA-LDA models can be a completely effective, fast, and non-destructive way to identify authenticity of banknotes as well as permitting field analysis. Copyright © 2018 Elsevier B.V. All rights reserved.

Grading of Chinese Cantonese Sausage Using Hyperspectral Imaging Combined with Chemometric Methods

Science.gov (United States)

Gong, Aiping; Zhu, Susu; He, Yong; Zhang, Chu

2017-01-01

Fast and accurate grading of Chinese Cantonese sausage is an important concern for customers, organizations, and the industry. Hyperspectral imaging in the spectral range of 874–1734 nm, combined with chemometric methods, was applied to grade Chinese Cantonese sausage. Three grades of intact and sliced Cantonese sausages were studied, including the top, first, and second grades. Support vector machine (SVM) and random forests (RF) techniques were used to build two different models. Second derivative spectra and RF were applied to select optimal wavelengths. The optimal wavelengths were the same for intact and sliced sausages when selected from second derivative spectra, while the optimal wavelengths for intact and sliced sausages selected using RF were quite similar. The SVM and RF models, using full spectra and the optimal wavelengths, obtained acceptable results for intact and sliced sausages. Both models for intact sausages performed better than those for sliced sausages, with a classification accuracy of the calibration and prediction set of over 90%. The overall results indicated that hyperspectral imaging combined with chemometric methods could be used to grade Chinese Cantonese sausages, with intact sausages being better suited for grading. This study will help to develop fast and accurate online grading of Cantonese sausages, as well as other sausages. PMID:28757578

Fluorescence Spectroscopy and Chemometric Modeling for Bioprocess Monitoring

Directory of Open Access Journals (Sweden)

Saskia M. Faassen

2015-04-01

Full Text Available On-line sensors for the detection of crucial process parameters are desirable for the monitoring, control and automation of processes in the biotechnology, food and pharma industry. Fluorescence spectroscopy as a highly developed and non-invasive technique that enables the on-line measurements of substrate and product concentrations or the identification of characteristic process states. During a cultivation process significant changes occur in the fluorescence spectra. By means of chemometric modeling, prediction models can be calculated and applied for process supervision and control to provide increased quality and the productivity of bioprocesses. A range of applications for different microorganisms and analytes has been proposed during the last years. This contribution provides an overview of different analysis methods for the measured fluorescence spectra and the model-building chemometric methods used for various microbial cultivations. Most of these processes are observed using the BioView® Sensor, thanks to its robustness and insensitivity to adverse process conditions. Beyond that, the PLS-method is the most frequently used chemometric method for the calculation of process models and prediction of process variables.

Fluorescence Spectroscopy and Chemometric Modeling for Bioprocess Monitoring

Science.gov (United States)

Faassen, Saskia M.; Hitzmann, Bernd

2015-01-01

On-line sensors for the detection of crucial process parameters are desirable for the monitoring, control and automation of processes in the biotechnology, food and pharma industry. Fluorescence spectroscopy as a highly developed and non-invasive technique that enables the on-line measurements of substrate and product concentrations or the identification of characteristic process states. During a cultivation process significant changes occur in the fluorescence spectra. By means of chemometric modeling, prediction models can be calculated and applied for process supervision and control to provide increased quality and the productivity of bioprocesses. A range of applications for different microorganisms and analytes has been proposed during the last years. This contribution provides an overview of different analysis methods for the measured fluorescence spectra and the model-building chemometric methods used for various microbial cultivations. Most of these processes are observed using the BioView® Sensor, thanks to its robustness and insensitivity to adverse process conditions. Beyond that, the PLS-method is the most frequently used chemometric method for the calculation of process models and prediction of process variables. PMID:25942644

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.

Simultaneous chemometric determination of pyridoxine hydrochloride and isoniazid in tablets by multivariate regression methods.

Science.gov (United States)

Dinç, Erdal; Ustündağ, Ozgür; Baleanu, Dumitru

2010-08-01

The sole use of pyridoxine hydrochloride during treatment of tuberculosis gives rise to pyridoxine deficiency. Therefore, a combination of pyridoxine hydrochloride and isoniazid is used in pharmaceutical dosage form in tuberculosis treatment to reduce this side effect. In this study, two chemometric methods, partial least squares (PLS) and principal component regression (PCR), were applied to the simultaneous determination of pyridoxine (PYR) and isoniazid (ISO) in their tablets. A concentration training set comprising binary mixtures of PYR and ISO consisting of 20 different combinations were randomly prepared in 0.1 M HCl. Both multivariate calibration models were constructed using the relationships between the concentration data set (concentration data matrix) and absorbance data matrix in the spectral region 200-330 nm. The accuracy and the precision of the proposed chemometric methods were validated by analyzing synthetic mixtures containing the investigated drugs. The recovery results obtained by applying PCR and PLS calibrations to the artificial mixtures were found between 100.0 and 100.7%. Satisfactory results obtained by applying the PLS and PCR methods to both artificial and commercial samples were obtained. The results obtained in this manuscript strongly encourage us to use them for the quality control and the routine analysis of the marketing tablets containing PYR and ISO drugs. Copyright © 2010 John Wiley & Sons, Ltd.

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%).

[Application of Fourier transform infrared spectroscopy in identification of wine spoilage].

Science.gov (United States)

Zhao, Xian-De; Dong, Da-Ming; Zheng, Wen-Gang; Jiao, Lei-Zi; Lang, Yun

2014-10-01

In the present work, fresh and spoiled wine samples from three wines produced by different companies were studied u- sing Fourier transform infrared (FTIR) spectroscopy. We analyzed the physicochemical property change in the process of spoil- age, and then, gave out the attribution of some main FTIR absorption peaks. A novel determination method was explored based on the comparisons of some absorbance ratios at different wavebands although the absorbance ratios in this method were relative. Through the compare of the wine spectra before and after spoiled, the authors found that they were informative at the bands of 3,020~2,790, 1,760~1,620 and 1,550~800 cm(-1). In order to find the relation between these informative spectral bands and the wine deterioration and achieve the discriminant analysis, chemometrics methods were introduced. Principal compounds analysis (PCA) and soft independent modeling of class analogy (SIMCA) were used for classifying different-quality wines. And partial least squares discriminant analysis (PLS-DA) was applied to identify spoiled wines and good wines. Results showed that FTIR technique combined with chemometrics methods could effectively distinguish spoiled wines from fresh samples. The effect of classification at the wave band of 1 550-800 cm(-1) was the best. The recognition rate of SIMCA and PLSDA were respectively 94% and 100%. This study demonstrates that Fourier transform infrared spectroscopy is an effective tool for monitoring red wine's spoilage and provides theoretical support for developing early-warning equipments.

One input-class and two input-class classifications for differentiating olive oil from other edible vegetable oils by use of the normal-phase liquid chromatography fingerprint of the methyl-transesterified fraction.

Science.gov (United States)

Jiménez-Carvelo, Ana M; Pérez-Castaño, Estefanía; González-Casado, Antonio; Cuadros-Rodríguez, Luis

2017-04-15

A new method for differentiation of olive oil (independently of the quality category) from other vegetable oils (canola, safflower, corn, peanut, seeds, grapeseed, palm, linseed, sesame and soybean) has been developed. The analytical procedure for chromatographic fingerprinting of the methyl-transesterified fraction of each vegetable oil, using normal-phase liquid chromatography, is described and the chemometric strategies applied and discussed. Some chemometric methods, such as k-nearest neighbours (kNN), partial least squared-discriminant analysis (PLS-DA), support vector machine classification analysis (SVM-C), and soft independent modelling of class analogies (SIMCA), were applied to build classification models. Performance of the classification was evaluated and ranked using several classification quality metrics. The discriminant analysis, based on the use of one input-class, (plus a dummy class) was applied for the first time in this study. Copyright © 2016 Elsevier Ltd. All rights reserved.

Application of attenuated total reflectance Fourier Transform Infrared spectroscopy (ATR-FTIR) in MIR range coupled with chemometrics for detection of pig body fat in pure ghee (heat clarified milk fat)

Science.gov (United States)

Upadhyay, Neelam; Jaiswal, Pranita; Jha, Shyam Narayan

2018-02-01

Pure ghee is superior to other fats and oils due to the presence of bioactive lipids and its rich flavor. Adulteration of ghee with cheaper fats and oils is a prevalent fraudulent practice. ATR-FTIR spectroscopy was coupled with chemometrics for the purpose of detection of presence of pig body fat in pure ghee. Pure mixed ghee was spiked with pig body fat @ 3, 4, 5, 10, 15% level. The spectra of pure (ghee and pig body fat) along with the spiked samples was taken in MIR from 4000 to 500 cm-1. Some wavenumber ranges were selected on the basis of differences in the spectra obtained. Separate clusters of the samples were obtained by employing principal component analysis at 5% level of significance on the selected wavenumber range. Probable class membership was predicted by applying SIMCA approach. Approximately, 90% of the samples classified into their respective class and pure ghee and pig body fat never misclassified themselves. The value of R2 was >0.99 for both calibration and validation sets using partial least square method. The study concluded that spiking of pig body fat in pure ghee can be detected even at a level of 3%.

Identification, classification, and discrimination of agave syrups from natural sweeteners by infrared spectroscopy and HPAEC-PAD.

Science.gov (United States)

Mellado-Mojica, Erika; López, Mercedes G

2015-01-15

Agave syrups are gaining popularity as new natural sweeteners. Identification, classification and discrimination by infrared spectroscopy coupled to chemometrics (NIR-MIR-SIMCA-PCA) and HPAEC-PAD of agave syrups from natural sweeteners were achieved. MIR-SIMCA-PCA allowed us to classify the natural sweeteners according to their natural source. Natural syrups exhibited differences in the MIR spectra region 1500-900 cm(-1). The agave syrups displayed strong absorption in the MIR spectra region 1061-1,063 cm(-1), in agreement with their high fructose content. Additionally, MIR-SIMCA-PCA allowed us to differentiate among syrups from different Agave species (Agavetequilana and Agavesalmiana). Thin-layer chromatography and HPAEC-PAD revealed glucose, fructose, and sucrose as the principal carbohydrates in all of the syrups. Oligosaccharide profiles showed that A. tequilana syrups are mainly composed of fructose (>60%) and fructooligosaccharides, while A. salmiana syrups contain more sucrose (28-32%). We conclude that MIR-SIMCA-PCA and HPAEC-PAD can be used to unequivocally identify and classified agave syrups. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

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

[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.

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.

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.

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.

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.

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

Chemometric Strategies for Peak Detection and Profiling from Multidimensional Chromatography.

Science.gov (United States)

Navarro-Reig, Meritxell; Bedia, Carmen; Tauler, Romà; Jaumot, Joaquim

2018-04-03

The increasing complexity of omics research has encouraged the development of new instrumental technologies able to deal with these challenging samples. In this way, the rise of multidimensional separations should be highlighted due to the massive amounts of information that provide with an enhanced analyte determination. Both proteomics and metabolomics benefit from this higher separation capacity achieved when different chromatographic dimensions are combined, either in LC or GC. However, this vast quantity of experimental information requires the application of chemometric data analysis strategies to retrieve this hidden knowledge, especially in the case of nontargeted studies. In this work, the most common chemometric tools and approaches for the analysis of this multidimensional chromatographic data are reviewed. First, different options for data preprocessing and enhancement of the instrumental signal are introduced. Next, the most used chemometric methods for the detection of chromatographic peaks and the resolution of chromatographic and spectral contributions (profiling) are presented. The description of these data analysis approaches is complemented with enlightening examples from omics fields that demonstrate the exceptional potential of the combination of multidimensional separation techniques and chemometric tools of data analysis. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Use of ATR-FTIR spectroscopy coupled with chemometrics for the authentication of avocado oil in ternary mixtures with sunflower and soybean oils.

Science.gov (United States)

Jiménez-Sotelo, Paola; Hernández-Martínez, Maylet; Osorio-Revilla, Guillermo; Meza-Márquez, Ofelia Gabriela; García-Ochoa, Felipe; Gallardo-Velázquez, Tzayhrí

2016-07-01

Avocado oil is a high-value and nutraceutical oil whose authentication is very important since the addition of low-cost oils could lower its beneficial properties. Mid-FTIR spectroscopy combined with chemometrics was used to detect and quantify adulteration of avocado oil with sunflower and soybean oils in a ternary mixture. Thirty-seven laboratory-prepared adulterated samples and 20 pure avocado oil samples were evaluated. The adulterated oil amount ranged from 2% to 50% (w/w) in avocado oil. A soft independent modelling class analogy (SIMCA) model was developed to discriminate between pure and adulterated samples. The model showed recognition and rejection rate of 100% and proper classification in external validation. A partial least square (PLS) algorithm was used to estimate the percentage of adulteration. The PLS model showed values of R(2) > 0.9961, standard errors of calibration (SEC) in the range of 0.3963-0.7881, standard errors of prediction (SEP estimated) between 0.6483 and 0.9707, and good prediction performances in external validation. The results showed that mid-FTIR spectroscopy could be an accurate and reliable technique for qualitative and quantitative analysis of avocado oil in ternary mixtures.

Detection of Cyanuric Acid and Melamine in Infant Formula Powders by Mid-FTIR Spectroscopy and Multivariate Analysis

Directory of Open Access Journals (Sweden)

Edwin García-Miguel

2018-01-01

Full Text Available Chemometric methods using mid-FTIR spectroscopy were developed in order to reduce the time of study of melamine and cyanuric acid in infant formulas. Chemometric models were constructed using the algorithms Partial Least Squares (PLS1, PLS2 and Principal Component Regression (PCR in order to correlate the IR signal with the levels of melamine or cyanuric acid in the infant formula samples. Results showed that the best correlations were obtained using PLS1 (R2: 0.9998, SEC: 0.0793, and SEP: 0.5545 for melamine and R2: 0.9997, SEC: 0.1074, and SEP: 0.5021 for cyanuric acid. Also, the SIMCA model was studied to distinguish between adulterated formulas and nonadulterated samples, giving optimum discrimination and good interclass distances between samples. Results showed that chemometric models demonstrated a good predictive ability of melamine and cyanuric acid concentrations in infant formulas, showing that this is a rapid and accurate technique to be used in the identification and quantification of these adulterants in infant formulas.

Principal Component Analysis: Most Favourite Tool in Chemometrics

Indian Academy of Sciences (India)

GENERAL ARTICLE. Principal ... Chemometrics is a discipline that combines mathematics, statis- ... workers have used PCA for air quality monitoring [8]. ..... J S Verbeke, Handbook of Chemometrics and Qualimetrics, Elsevier, New York,.

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.

Chemometrics-assisted spectrophotometric green method for correcting interferences in biowaiver studies: Application to assay and dissolution profiling study of donepezil hydrochloride tablets

Science.gov (United States)

Korany, Mohamed A.; Mahgoub, Hoda; Haggag, Rim S.; Ragab, Marwa A. A.; Elmallah, Osama A.

2018-06-01

A green, simple and cost effective chemometric UV-Vis spectrophotometric method has been developed and validated for correcting interferences that arise during conducting biowaiver studies. Chemometric manipulation has been done for enhancing the results of direct absorbance, resulting from very low concentrations (high incidence of background noise interference) of earlier points in the dissolution timing in case of dissolution profile using first and second derivative (D1 & D2) methods and their corresponding Fourier function convoluted methods (D1/FF& D2/FF). The method applied for biowaiver study of Donepezil Hydrochloride (DH) as a representative model was done by comparing two different dosage forms containing 5 mg DH per tablet as an application of a developed chemometric method for correcting interferences as well as for the assay and dissolution testing in its tablet dosage form. The results showed that first derivative technique can be used for enhancement of the data in case of low concentration range of DH (1-8 μg mL-1) in the three different pH dissolution media which were used to estimate the low drug concentrations dissolved at the early points in the biowaiver study. Furthermore, the results showed similarity in phosphate buffer pH 6.8 and dissimilarity in the other 2 pH media. The method was validated according to ICH guidelines and USP monograph for both assays (HCl of pH 1.2) and dissolution study in 3 pH media (HCl of pH 1.2, acetate buffer of pH 4.5 and phosphate buffer of pH 6.8). Finally, the assessment of the method greenness was done using two different assessment techniques: National Environmental Method Index label and Eco scale methods. Both techniques ascertained the greenness of the proposed method.

Development and Validation of a Laser Induced Breakdown Spectrometry Method for Cancer Detection and Characterization

International Nuclear Information System (INIS)

Otieno, E.A.

2015-01-01

Laser Induced Breakdown Spectroscopy (LIBS) is a type of atomic emission spectroscopy which employs a highly energetic laser pulse to simultaneously prepare the sample and excite the species. The simplest calibration technique is based on the use of standard calibration curves. The phenomenon of self-absorption may be considered as a factor of linearity deviation in conventional calibration. Chemometrics has the ability to extract underlying phenomena from complex data with the help of multivariate techniques such as SIMCA, ICA, PCA, SVM and ANNs. The techniques are also capable of capturing information about correlated trends in a given dataset. It has been reported that in normal liver the zinc concentration is about 78ug/g, wet weight and the primary liver cancer itself is about 18ug/g

Spectroscopic and chemometric exploration of food quality

DEFF Research Database (Denmark)

Pedersen, Dorthe Kjær

2002-01-01

and multi-way chemometrics demonstrated the potential for screening of environmental contamination in complex food samples. Significant prediction models were established with correlation coefficients in the range from r = 0.69 to r = 0.97 for dioxin. Further development of the fluorescence measurements......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...

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®

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.

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.

Air quality modelling using chemometric techniques | Azid | Journal ...

African Journals Online (AJOL)

This study presents that the chemometric techniques and modelling become an excellent tool in API assessment, air pollution source identification, apportionment and can be setbacks in designing an API monitoring network for effective air pollution resources management. Keywords: air pollutant index; chemometric; ANN; ...

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...... regression (Unfold-PLSR) on the larger data set and parallel factor analysis (PARAFAC) of the six samples of the smaller set showed that there was no difference between the fluorescence landscapes of adrenaline and noradrenaline. It can be concluded that chemometric separation of adrenaline and noradrenaline...

Detection of Genetically Modified Sugarcane by Using Terahertz Spectroscopy and Chemometrics

Science.gov (United States)

Liu, J.; Xie, H.; Zha, B.; Ding, W.; Luo, J.; Hu, C.

2018-03-01

A methodology is proposed to identify genetically modified sugarcane from non-genetically modified sugarcane by using terahertz spectroscopy and chemometrics techniques, including linear discriminant analysis (LDA), support vector machine-discriminant analysis (SVM-DA), and partial least squares-discriminant analysis (PLS-DA). The classification rate of the above mentioned methods is compared, and different types of preprocessing are considered. According to the experimental results, the best option is PLS-DA, with an identification rate of 98%. The results indicated that THz spectroscopy and chemometrics techniques are a powerful tool to identify genetically modified and non-genetically modified sugarcane.

Quality Evaluation of Potentilla fruticosa L. by High Performance Liquid Chromatography Fingerprinting Associated with Chemometric Methods.

Science.gov (United States)

Liu, Wei; Wang, Dongmei; Liu, Jianjun; Li, Dengwu; Yin, Dongxue

2016-01-01

The present study was performed to assess the quality of Potentilla fruticosa L. sampled from distinct regions of China using high performance liquid chromatography (HPLC) fingerprinting coupled with a suite of chemometric methods. For this quantitative analysis, the main active phytochemical compositions and the antioxidant activity in P. fruticosa were also investigated. Considering the high percentages and antioxidant activities of phytochemicals, P. fruticosa samples from Kangding, Sichuan were selected as the most valuable raw materials. Similarity analysis (SA) of HPLC fingerprints, hierarchical cluster analysis (HCA), principle component analysis (PCA), and discriminant analysis (DA) were further employed to provide accurate classification and quality estimates of P. fruticosa. Two principal components (PCs) were collected by PCA. PC1 separated samples from Kangding, Sichuan, capturing 57.64% of the variance, whereas PC2 contributed to further separation, capturing 18.97% of the variance. Two kinds of discriminant functions with a 100% discrimination ratio were constructed. The results strongly supported the conclusion that the eight samples from different regions were clustered into three major groups, corresponding with their morphological classification, for which HPLC analysis confirmed the considerable variation in phytochemical compositions and that P. fruticosa samples from Kangding, Sichuan were of high quality. The results of SA, HCA, PCA, and DA were in agreement and performed well for the quality assessment of P. fruticosa. Consequently, HPLC fingerprinting coupled with chemometric techniques provides a highly flexible and reliable method for the quality evaluation of traditional Chinese medicines.

Quality Evaluation of Potentilla fruticosa L. by High Performance Liquid Chromatography Fingerprinting Associated with Chemometric Methods

Science.gov (United States)

Liu, Wei; Wang, Dongmei; Liu, Jianjun; Li, Dengwu; Yin, Dongxue

2016-01-01

The present study was performed to assess the quality of Potentilla fruticosa L. sampled from distinct regions of China using high performance liquid chromatography (HPLC) fingerprinting coupled with a suite of chemometric methods. For this quantitative analysis, the main active phytochemical compositions and the antioxidant activity in P. fruticosa were also investigated. Considering the high percentages and antioxidant activities of phytochemicals, P. fruticosa samples from Kangding, Sichuan were selected as the most valuable raw materials. Similarity analysis (SA) of HPLC fingerprints, hierarchical cluster analysis (HCA), principle component analysis (PCA), and discriminant analysis (DA) were further employed to provide accurate classification and quality estimates of P. fruticosa. Two principal components (PCs) were collected by PCA. PC1 separated samples from Kangding, Sichuan, capturing 57.64% of the variance, whereas PC2 contributed to further separation, capturing 18.97% of the variance. Two kinds of discriminant functions with a 100% discrimination ratio were constructed. The results strongly supported the conclusion that the eight samples from different regions were clustered into three major groups, corresponding with their morphological classification, for which HPLC analysis confirmed the considerable variation in phytochemical compositions and that P. fruticosa samples from Kangding, Sichuan were of high quality. The results of SA, HCA, PCA, and DA were in agreement and performed well for the quality assessment of P. fruticosa. Consequently, HPLC fingerprinting coupled with chemometric techniques provides a highly flexible and reliable method for the quality evaluation of traditional Chinese medicines. PMID:26890416

Detection of Lard in Ink Extracted from Printed Food Packaging Using Fourier Transform Infrared Spectroscopy and Multivariate Analysis

Directory of Open Access Journals (Sweden)

Syazwani Ramli

2015-01-01

Full Text Available Fourier transform infrared (FTIR spectroscopy combined with chemometrics was utilised to discriminate the presence of lard in extracted ink of printed food packaging. Two spectral regions (full spectra, 3999–649 cm−1, and combination of two regions, 3110–2630 cm−1 and 1940–649 cm−1 of lard, commercial gravure ink, and the blends of both were selected and used to develop a Soft Independent Modelling of Class Analogy (SIMCA model. The score plots obtained from the Principal Component Analysis (PCA revealed that the maximum number of factors (7 factors was needed to explain 84% of the total variance. SIMCA was employed as the method to classify the samples into their specific groups. Si versus Hi plots showed that the calibration standards can be classified as lard-containing standards. Sample 2 was deduced to have the highest possibility of containing lard, while only samples 5 and 7 cannot be classified as lard-containing samples. These results demonstrated that FTIR spectroscopy, when combined with multivariate analysis, can provide a rapid method with no excessive sample preparation to detect the presence of lard in ink of foodstuff packaging.

Classification of diesel pool refinery streams through near infrared spectroscopy and support vector machines using C-SVC and ν-SVC.

Science.gov (United States)

Alves, Julio Cesar L; Henriques, Claudete B; Poppi, Ronei J

2014-01-03

The use of near infrared (NIR) spectroscopy combined with chemometric methods have been widely used in petroleum and petrochemical industry and provides suitable methods for process control and quality control. The algorithm support vector machines (SVM) has demonstrated to be a powerful chemometric tool for development of classification models due to its ability to nonlinear modeling and with high generalization capability and these characteristics can be especially important for treating near infrared (NIR) spectroscopy data of complex mixtures such as petroleum refinery streams. In this work, a study on the performance of the support vector machines algorithm for classification was carried out, using C-SVC and ν-SVC, applied to near infrared (NIR) spectroscopy data of different types of streams that make up the diesel pool in a petroleum refinery: light gas oil, heavy gas oil, hydrotreated diesel, kerosene, heavy naphtha and external diesel. In addition to these six streams, the diesel final blend produced in the refinery was added to complete the data set. C-SVC and ν-SVC classification models with 2, 4, 6 and 7 classes were developed for comparison between its results and also for comparison with the soft independent modeling of class analogy (SIMCA) models results. It is demonstrated the superior performance of SVC models especially using ν-SVC for development of classification models for 6 and 7 classes leading to an improvement of sensitivity on validation sample sets of 24% and 15%, respectively, when compared to SIMCA models, providing better identification of chemical compositions of different diesel pool refinery streams. Copyright © 2013 Elsevier B.V. All rights reserved.

Multielement fingerprinting as a tool in origin authentication of PGI food products: Tropea red onion.

Science.gov (United States)

Furia, Emilia; Naccarato, Attilio; Sindona, Giovanni; Stabile, Gaetano; Tagarelli, Antonio

2011-08-10

Tropea red onion ( Allium cepa L. var. Tropea) is among the most highly appreciated Italian products. It is cultivated in specific areas of Calabria and, due to its characteristics, was recently awarded with the protected geographical indications (PGI) certification from the European Union. A reliable classification of onion samples in groups corresponding to "Tropea" and "non-Tropea" categories is now available to the producers. This important goal has been achieved through the evaluation of three supervised chemometric approaches. Onion samples with PGI brand (120) and onion samples not cultivated following the production regulations (80) were digested by a closed-vessel microwave oven system. ICP-MS equipped with a dynamic reaction cell was used to determine the concentrations of 25 elements (Al, Ba, Ca, Cd, Ce, Cr, Dy, Eu, Fe, Ga, Gd, Ho, La, Mg, Mn, Na, Nd, Ni, Pr, Rb, Sm, Sr, Tl, Y, and Zn). The multielement fingerprint was processed using linear discriminant analysis (LDA) (standard and stepwise), soft independent modeling of class analogy (SIMCA), and back-propagation artificial neural network (BP-ANN). The cross-validation procedure has shown good results in terms of the prediction ability for all of the chemometric models: standard LDA, 94.0%; stepwise LDA, 94.5%; SIMCA, 95.5%; and BP-ANN, 91.5%.

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

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.

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.

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.

Chemometric applications to assess quality and critical parameters of virgin and extra-virgin olive oil. A review.

Science.gov (United States)

Gómez-Caravaca, Ana M; Maggio, Rubén M; Cerretani, Lorenzo

2016-03-24

Today virgin and extra-virgin olive oil (VOO and EVOO) are food with a large number of analytical tests planned to ensure its quality and genuineness. Almost all official methods demand high use of reagents and manpower. Because of that, analytical development in this area is continuously evolving. Therefore, this review focuses on analytical methods for EVOO/VOO which use fast and smart approaches based on chemometric techniques in order to reduce time of analysis, reagent consumption, high cost equipment and manpower. Experimental approaches of chemometrics coupled with fast analytical techniques such as UV-Vis spectroscopy, fluorescence, vibrational spectroscopies (NIR, MIR and Raman fluorescence), NMR spectroscopy, and other more complex techniques like chromatography, calorimetry and electrochemical techniques applied to EVOO/VOO production and analysis have been discussed throughout this work. The advantages and drawbacks of this association have also been highlighted. Chemometrics has been evidenced as a powerful tool for the oil industry. In fact, it has been shown how chemometrics can be implemented all along the different steps of EVOO/VOO production: raw material input control, monitoring during process and quality control of final product. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Pre-analytical method for NMR-based grape metabolic fingerprinting and chemometrics.

Science.gov (United States)

Ali, Kashif; Maltese, Federica; Fortes, Ana Margarida; Pais, Maria Salomé; Verpoorte, Robert; Choi, Young Hae

2011-10-10

Although metabolomics aims at profiling all the metabolites in organisms, data quality is quite dependent on the pre-analytical methods employed. In order to evaluate current methods, different pre-analytical methods were compared and used for the metabolic profiling of grapevine as a model plant. Five grape cultivars from Portugal in combination with chemometrics were analyzed in this study. A common extraction method with deuterated water and methanol was found effective in the case of amino acids, organic acids, and sugars. For secondary metabolites like phenolics, solid phase extraction with C-18 cartridges showed good results. Principal component analysis, in combination with NMR spectroscopy, was applied and showed clear distinction among the cultivars. Primary metabolites such as choline, sucrose, and leucine were found discriminating for 'Alvarinho', while elevated levels of alanine, valine, and acetate were found in 'Arinto' (white varieties). Among the red cultivars, higher signals for citrate and GABA in 'Touriga Nacional', succinate and fumarate in 'Aragonês', and malate, ascorbate, fructose and glucose in 'Trincadeira', were observed. Based on the phenolic profile, 'Arinto' was found with higher levels of phenolics as compared to 'Alvarinho'. 'Trincadeira' showed lowest phenolics content while higher levels of flavonoids and phenylpropanoids were found in 'Aragonês' and 'Touriga Nacional', respectively. It is shown that the metabolite composition of the extract is highly affected by the extraction procedure and this consideration has to be taken in account for metabolomics studies. Copyright © 2011 Elsevier B.V. All rights reserved.

Probability of identification: adulteration of American Ginseng with Asian Ginseng.

Science.gov (United States)

Harnly, James; Chen, Pei; Harrington, Peter De B

2013-01-01

The AOAC INTERNATIONAL guidelines for validation of botanical identification methods were applied to the detection of Asian Ginseng [Panax ginseng (PG)] as an adulterant for American Ginseng [P. quinquefolius (PQ)] using spectral fingerprints obtained by flow injection mass spectrometry (FIMS). Samples of 100% PQ and 100% PG were physically mixed to provide 90, 80, and 50% PQ. The multivariate FIMS fingerprint data were analyzed using soft independent modeling of class analogy (SIMCA) based on 100% PQ. The Q statistic, a measure of the degree of non-fit of the test samples with the calibration model, was used as the analytical parameter. FIMS was able to discriminate between 100% PQ and 100% PG, and between 100% PQ and 90, 80, and 50% PQ. The probability of identification (POI) curve was estimated based on the SD of 90% PQ. A digital model of adulteration, obtained by mathematically summing the experimentally acquired spectra of 100% PQ and 100% PG in the desired ratios, agreed well with the physical data and provided an easy and more accurate method for constructing the POI curve. Two chemometric modeling methods, SIMCA and fuzzy optimal associative memories, and two classification methods, partial least squares-discriminant analysis and fuzzy rule-building expert systems, were applied to the data. The modeling methods correctly identified the adulterated samples; the classification methods did not.

Simultaneous determination of three herbicides by differential pulse voltammetry and chemometrics.

Science.gov (United States)

Ni, Yongnian; Wang, Lin; Kokot, Serge

2011-01-01

A novel differential pulse voltammetry method (DPV) was researched and developed for the simultaneous determination of Pendimethalin, Dinoseb and sodium 5-nitroguaiacolate (5NG) with the aid of chemometrics. The voltammograms of these three compounds overlapped significantly, and to facilitate the simultaneous determination of the three analytes, chemometrics methods were applied. These included classical least squares (CLS), principal component regression (PCR), partial least squares (PLS) and radial basis function-artificial neural networks (RBF-ANN). A separately prepared verification data set was used to confirm the calibrations, which were built from the original and first derivative data matrices of the voltammograms. On the basis relative prediction errors and recoveries of the analytes, the RBF-ANN and the DPLS (D - first derivative spectra) models performed best and are particularly recommended for application. The DPLS calibration model was applied satisfactorily for the prediction of the three analytes from market vegetables and lake water samples.

Development of a Direct Spectrophotometric and Chemometric Method for Determining Food Dye Concentrations.

Science.gov (United States)

Arroz, Erin; Jordan, Michael; Dumancas, Gerard G

2017-07-01

An ultraviolet visible (UV-Vis) spectrophotometric and partial least squares (PLS) chemometric method was developed for the simultaneous determination of erythrosine B (red), Brilliant Blue, and tartrazine (yellow) dyes. A training set (n = 64) was generated using a full factorial design and its accuracy was tested in a test set (n = 13) using a Box-Behnken design. The test set garnered a root mean square error (RMSE) of 1.79 × 10 -7 for blue, 4.59 × 10 -7 for red, and 1.13 × 10 -6 for yellow dyes. The relatively small RMSE suggests only a small difference between predicted versus measured concentrations, demonstrating the accuracy of our model. The relative error of prediction (REP) for the test set were 11.73%, 19.52%, 19.38%, for blue, red, and yellow dyes, respectively. A comparable overlay between the actual candy samples and their replicated synthetic spectra were also obtained indicating the model as a potentially accurate method for determining concentrations of dyes in food samples.

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.

Application of mass spectrometry based electronic nose and chemometrics for fingerprinting radiation treatment

International Nuclear Information System (INIS)

Gupta, Sumit; Variyar, Prasad S.; Sharma, Arun

2015-01-01

Volatile compounds were isolated from apples and grapes employing solid phase micro extraction (SPME) and subsequently analyzed by GC/MS equipped with a transfer line without stationary phase. Single peak obtained was integrated to obtain total mass spectrum of the volatile fraction of samples. A data matrix having relative abundance of all mass-to-charge ratios was subjected to principal component analysis (PCA) and linear discriminant analysis (LDA) to identify radiation treatment. PCA results suggested that there is sufficient variability between control and irradiated samples to build classification models based on supervised techniques. LDA successfully aided in segregating control from irradiated samples at all doses (0.1, 0.25, 0.5, 1.0, 1.5, 2.0 kGy). SPME-MS with chemometrics was successfully demonstrated as simple screening method for radiation treatment. - Highlights: • Total mass spectra obtained from HS-MS for control and irradiated fruits. • Grapes and apples are chosen for present study. • Total mass spectrum was analyzed by two chemometric techniques (PCA and LDA). • Successful segregation of control and irradiated samples achieved using chemometrics

Quality Assessment of Kumu Injection, a Traditional Chinese Medicine Preparation, Using HPLC Combined with Chemometric Methods and Qualitative and Quantitative Analysis of Multiple Alkaloids by Single Marker.

Science.gov (United States)

Wang, Ning; Li, Zhi-Yong; Zheng, Xiao-Li; Li, Qiao; Yang, Xin; Xu, Hui

2018-04-09

Kumu injection (KMI) is a common-used traditional Chinese medicine (TCM) preparation made from Picrasma quassioides (D. Don) Benn. rich in alkaloids. An innovative technique for quality assessment of KMI was developed using high performance liquid chromatography (HPLC) combined with chemometric methods and qualitative and quantitative analysis of multi-components by single marker (QAMS). Nigakinone (PQ-6, 5-hydroxy-4-methoxycanthin-6-one), one of the most abundant alkaloids responsible for the major pharmacological activities of Kumu, was used as a reference substance. Six alkaloids in KMI were quantified, including 6-hydroxy- β -carboline-1-carboxylic acid (PQ-1), 4,5-dimethoxycanthin-6-one (PQ-2), β -carboline-1-carboxylic acid (PQ-3), β -carboline-1-propanoic acid (PQ-4), 3-methylcanthin-5,6-dione (PQ-5), and PQ-6. Based on the outcomes of twenty batches of KMI samples, the contents of six alkaloids were used for further chemometric analysis. By hierarchical cluster analysis (HCA), radar plots, and principal component analysis (PCA), all the KMI samples could be categorized into three groups, which were closely related to production date and indicated the crucial influence of herbal raw material on end products of KMI. QAMS combined with chemometric analysis could accurately measure and clearly distinguish the different quality samples of KMI. Hence, QAMS is a feasible and promising method for the quality control of KMI.

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.

Protected Geographical Indication Identification of a Chinese Green Tea (Anji-White by Near-Infrared Spectroscopy and Chemometric Class Modeling Techniques

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Lu Xu

2013-01-01

Full Text Available This paper reports a rapid identification method for a Chinese green tea with PGI, Anji-white tea, by class modeling techniques and NIR spectroscopy. 167 real and representative Anji-white tea samples were collected from 8 tea plantations in their original producing areas for model training. Another 81 non-Anji-white tea samples of similar appearance were collected from 7 important tea producing areas and used for validation of model specificity. Diffuse NIR spectra were measured with finely ground tea powders. OCPLS and SIMCA were used to describe the distribution of representative Anji-white tea objects and predict the authenticity of new objects. For data preprocessing, smoothing, derivatives, and SNV were applied to improve the raw spectra and classification performance. It is demonstrated that taking derivatives and SNV can improve classification accuracy and reduce the complexity of class models by removing spectral background and baseline. For the best models, the sensitivity and specificity were 0.886 and 0.951 for OCPLS, 0.886 and 0.938 for SIMCA with SNV spectra, respectively. Although it is difficult to perform an exhaustive analysis of all types of potential false objects, the proposed method can detect most of the important non-Anji-white teas in the Chinese market.

A comparative study of three tissue-cultured Dendrobium species and their wild correspondences by headspace gas chromatography-mass spectrometry combined with chemometric methods.

Science.gov (United States)

Chen, Nai-Dong; You, Tao; Li, Jun; Bai, Li-Tao; Hao, Jing-Wen; Xu, Xiao-Yuan

2016-10-01

Plant tissue culture technique is widely used in the conservation and utilization of rare and endangered medicinal plants and it is crucial for tissue culture stocks to obtain the ability to produce similar bioactive components as their wild correspondences. In this paper, a headspace gas chromatography-mass spectrometry method combined with chemometric methods was applied to analyze and evaluate the volatile compounds in tissue-cultured and wild Dendrobium huoshanense Cheng and Tang, Dendrobium officinale Kimura et Migo and Dendrobium moniliforme (Linn.) Sw. In total, 63 volatile compounds were separated, with 53 being identified from the three Dendrobium spp. Different provenances of Dendrobiums had characteristic chemicals and showed remarkable quantity discrepancy of common compositions. The similarity evaluation disclosed that the accumulation of volatile compounds in Dendrobium samples might be affected by their provenance. Principal component analysis showed that the first three components explained 85.9% of data variance, demonstrating a good discrimination between samples. Gas chromatography-mass spectrometry techniques, combined with chemometrics, might be an effective strategy for identifying the species and their provenance, especially in the assessment of tissue-cultured Dendrobium quality for use in raw herbal medicines. Copyright © 2016. Published by Elsevier B.V.

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.

Chemometrics-Assisted UV Spectrophotometric and RP-HPLC Methods for the Simultaneous Determination of Tolperisone Hydrochloride and Diclofenac Sodium in their Combined Pharmaceutical Formulation.

Science.gov (United States)

Gohel, Nikunj Rameshbhai; Patel, Bhavin Kiritbhai; Parmar, Vijaykumar Kunvarji

2013-01-01

Chemometrics-assisted UV spectrophotometric and RP-HPLC methods are presented for the simultaneous determination of tolperisone hydrochloride (TOL) and diclofenac sodium (DIC) from their combined pharmaceutical dosage form. Chemometric methods are based on principal component regression and partial least-square regression models. Two sets of standard mixtures, calibration sets, and validation sets were prepared. Both models were optimized to quantify each drug in the mixture using the information included in the UV absorption spectra of the appropriate solution in the range 241-290 nm with the intervals λ = 1 nm at 50 wavelengths. The optimized models were successfully applied to the simultaneous determination of these drugs in synthetic mixture and pharmaceutical formulation. In addition, an HPLC method was developed using a reversed-phase C18 column at ambient temperature with a mobile phase consisting of methanol:acetonitrile:water (60:30:10 v/v/v), pH-adjusted to 3.0, with UV detection at 275 nm. The methods were validated in terms of linearity, accuracy, precision, sensitivity, specificity, and robustness in the range of 3-30 μg/mL for TOL and 1-10 μg/mL for DIC. The robustness of the HPLC method was tested using an experimental design approach. The developed HPLC method, and the PCR and PLS models were used to determine the amount of TOL and DIC in tablets. The data obtained from the PCR and PLS models were not significantly different from those obtained from the HPLC method at 95% confidence limit.

Chemometric strategy for automatic chromatographic peak detection and background drift correction in chromatographic data.

Science.gov (United States)

Yu, Yong-Jie; Xia, Qiao-Ling; Wang, Sheng; Wang, Bing; Xie, Fu-Wei; Zhang, Xiao-Bing; Ma, Yun-Ming; Wu, Hai-Long

2014-09-12

Peak detection and background drift correction (BDC) are the key stages in using chemometric methods to analyze chromatographic fingerprints of complex samples. This study developed a novel chemometric strategy for simultaneous automatic chromatographic peak detection and BDC. A robust statistical method was used for intelligent estimation of instrumental noise level coupled with first-order derivative of chromatographic signal to automatically extract chromatographic peaks in the data. A local curve-fitting strategy was then employed for BDC. Simulated and real liquid chromatographic data were designed with various kinds of background drift and degree of overlapped chromatographic peaks to verify the performance of the proposed strategy. The underlying chromatographic peaks can be automatically detected and reasonably integrated by this strategy. Meanwhile, chromatograms with BDC can be precisely obtained. The proposed method was used to analyze a complex gas chromatography dataset that monitored quality changes in plant extracts during storage procedure. Copyright © 2014 Elsevier B.V. All rights reserved.

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

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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

Interaction of norfloxacin with bovine serum albumin studied by different spectrometric methods; displacement studies, molecular modeling and chemometrics approaches

Energy Technology Data Exchange (ETDEWEB)

Naseri, Abdolhossein, E-mail: a_naseri@tabrizu.ac.ir [Departments of Analytical Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz 51666-16471 (Iran, Islamic Republic of); Hosseini, Soheila [Departments of Analytical Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz 51666-16471 (Iran, Islamic Republic of); Rasoulzadeh, Farzaneh [Drug Applied Research Center, Tabriz University of Medical Sciences, Tabriz 51644-14766 (Iran, Islamic Republic of); Rashidi, Mohammad-Reza [Research Center for Pharmaceutical Nanotechnology, Tabriz University of Medical Sciences, Tabriz 51644-14766 (Iran, Islamic Republic of); Zakery, Maryam; Khayamian, Taghi [Department of Chemistry, College of Chemistry, Isfahan University of Technology, Isfahan 84154 (Iran, Islamic Republic of)

2015-01-15

Serum albumins as major target proteins can bind to other ligands leading to alteration of their pharmacological properties. The mechanism of interaction between norfloxacin (NFLX) with bovine serum albumin (BSA) was investigated. Fuorescence quenching of serum albumin by this drug was found to be a static quenching process. The binding sites number, n, apparent binding constant, K, and thermodynamic parameters were calculated at different temperatures. The distance, r, between donor, BSA, and acceptor, NFLX, was calculated according to the Forster theory of non-radiation energy transfer. Also binding characteristics of NFLX with BSA together with its displacement from its binding site by kanamycin and effect of common metal ions on binding constant were investigated by the spectroscopic methods. The conformational change in the secondary structure of BSA upon interaction with NFLX was investigated qualitatively from synchronous fluorescence spectra, Fourier Transform Infrared (FTIR) and circular dichroism (CD) spectrometric methods. Molecular docking studies were performed to obtain information on the possible residues involved in the interaction process and changes in accessible surface area of the interacting residues. The results showed that the conformation of BSA changed in the presence of NFLX. For the first time, displacement studies were used for this interaction; displacement studies showed that NFLX was displaced by phenylbutazon and ketoprofen but was not displaced by ibuprofen indicating that the binding site of NFLX on albumin was site I. In addition a powerful chemometrics method, multivariate curve resolution-alternating least square, was used for resolution of spectroscopic augmented data obtained in two different titration modes in order to extract spectral information regardless of spectral overlapping of components. - Highlights: • Interaction between norfloxacin and BSA is studied by spectral methods. • Chemometrics methods are used to

HR-MAS NMR allied to chemometric on Hancornia speciosa varieties differentiation

Energy Technology Data Exchange (ETDEWEB)

Flores, Igor S. [Instituto Federal de Goiás (IFG), Luziânia, GO (Brazil); Silva, Andressa K.; Chaves, Lazaro J.; Collevatti, Rosane G.; Lião, Luciano M., E-mail: lucianoliao@ufg.br [Universidade Federal de Goiás (UFG), Goiânia, GO (Brazil); Furquim, Leonnardo C. [Faculdade Objetivo, GO (Brazil); Castro, Carlos F.S. [Instituto Federal de Educação, Ciência e Tecnologia Goiano (IFGoiano), GO (Brazil)

2018-05-01

This work describes the potential of chemometric analyses applied to {sup 1}H high-resolution magic angle spinning nuclear magnetic resonance ({sup 1}H HR-MAS NMR) data for the chemotaxonomic investigation of Hancornia speciosa (Apocynaceae) varieties. This plant, popularly known as mangaba, has a complex morphological differentiation and thus chemical analyses can be used for their taxonomic classification. In comparison to traditional techniques, {sup 1}H HR-MAS NMR allied with chemometrics provided a simple and low cost method for chemotaxonomy. Leaves of four varieties of H. speciosa from a common garden experiment was studied and demonstrated that H. speciosa var. speciosa differs from others due to its specific metabolic profile, and var. pubescens was discriminated based on its high phenolic compound content. The distinction between the latter variety and gardineri is important once it allows for the selection of samples with greater commercial value, once they produce the largest and heaviest fruits. (author)

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.

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

Quantitative analysis of multiple high-resolution mass spectrometry images using chemometric methods: quantitation of chlordecone in mouse liver.

Science.gov (United States)

Mohammadi, Saeedeh; Parastar, Hadi

2018-05-15

In this work, a chemometrics-based strategy is developed for quantitative mass spectrometry imaging (MSI). In this regard, quantification of chlordecone as a carcinogenic organochlorinated pesticide (C10Cll0O) in mouse liver using the matrix-assisted laser desorption ionization MSI (MALDI-MSI) method is used as a case study. The MSI datasets corresponded to 1, 5 and 10 days of mouse exposure to the standard chlordecone in the quantity range of 0 to 450 μg g-1. The binning approach in the m/z direction is used to group high resolution m/z values and to reduce the big data size. To consider the effect of bin size on the quality of results, three different bin sizes of 0.25, 0.5 and 1.0 were chosen. Afterwards, three-way MSI data arrays (two spatial and one m/z dimensions) for seven standards and four unknown samples were column-wise augmented with m/z values as the common mode. Then, these datasets were analyzed using multivariate curve resolution-alternating least squares (MCR-ALS) using proper constraints. The resolved mass spectra were used for identification of chlordecone in the presence of a complex background and interference. Additionally, the augmented spatial profiles were post-processed and 2D images for each component were obtained in calibration and unknown samples. The sum of these profiles was utilized to set the calibration curve and to obtain the analytical figures of merit (AFOMs). Inspection of the results showed that the lower bin size (i.e., 0.25) provides more accurate results. Finally, the obtained results by MCR for three datasets were compared with those of gas chromatography-mass spectrometry (GC-MS) and MALDI-MSI. The results showed that the MCR-assisted method gives a higher amount of chlordecone than MALDI-MSI and a lower amount than GC-MS. It is concluded that a combination of chemometric methods with MSI can be considered as an alternative way for MSI quantification.

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.

[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.

Chromatographic fingerprinting through chemometric techniques for herbal slimming pills: A way of adulterant identification.

Science.gov (United States)

Shekari, Nafiseh; Vosough, Maryam; Tabar Heidar, Kourosh

2018-05-01

In the current study, gas chromatography-mass spectrometry (GC-MS) fingerprinting of herbal slimming pills assisted by chemometric methods has been presented. Deconvolution of two-way chromatographic signals of nine herbal slimming pills into pure chromatographic and spectral patterns was performed. The peak clusters were resolved using multivariate curve resolution-alternating least squares (MCR-ALS) by employing appropriate constraints. It was revealed that more useful chemical information about the composition of the slimming pills can be obtained by employing sophisticated GC-MS method coupled with proper chemometric tools yielding the extended number of identified constituents. The thorough fingerprinting of the complex mixtures proved the presence of some toxic or carcinogen components, such as toluene, furfural, furfuryl alcohol, styrene, itaconic anhydride, citraconic anhydride, trimethyl phosphate, phenol, pyrocatechol, p-propenylanisole and pyrogallol. In addition, some samples were shown to be adulterated with undeclared ingredients, including stimulants, anorexiant and laxatives such as phenolphthalein, amfepramone, caffeine and sibutramine. Copyright © 2018 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

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

2016-10-01

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.

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)

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.

A Simple Photometer and Chemometrics Analysis for Quality Control of Sambiloto (Andrographis paniculata Raw Material

Directory of Open Access Journals (Sweden)

Rudi Heryanto

2017-09-01

Full Text Available In this paper, we described the use of a light emitting diode (LED-based photometer and chemometric analysis for quality control of king of bitter or sambiloto (Andrographis paniculata raw material. The quality of medicinal plants is determined by their chemical composition. The quantities of chemical components in medicinal plants can be assessed using spectroscopic technique. We used an “in house” photometer to generate spectra of sambiloto. The spectra were analyzed by chemometric methods, i.e. principal component analysis (PCA and partial least square discriminant analysis (PLS-DA, with the aim of herbal quality classification based on the harvesting time. From the results obtained, based on thin layer chromatography analysis, sambiloto with different collection times (1, 2, and 3 months contained different amounts of active compounds. Evaluation of sambiloto, using its spectra and chemometric analysis has successfully differentiated its quality based on harvesting time. PCA with the first two PC’s (PC-1 = 60% and PC-2 = 35% was able to differentiate according to the harvesting time of sambiloto. Three models were obtained by PLS-DA and could be used to predict unknown sample of sambiloto according to the harvesting time

Data-fusion for multiplatform characterization of an italian craft beer aimed at its authentication

Energy Technology Data Exchange (ETDEWEB)

Biancolillo, Alessandra; Bucci, Remo; Magrì, Antonio L.; Magrì, Andrea D.; Marini, Federico, E-mail: fmmonet@hotmail.com

2014-04-01

Highlights: • Characterization of beer samples by five different fingerprinting techniques. • Chemometric discriminant and class-modeling techniques used for their authentication. • Mid-level data fusion allowed correct classification of all samples. - Abstract: Five different instrumental techniques: thermogravimetry, mid-infrared, near-infrared, ultra-violet and visible spectroscopies, have been used to characterize a high quality beer (Reale) from an Italian craft brewery (Birra del Borgo) and to differentiate it from other competing and lower quality products. Chemometric classification models were built on the separate blocks using soft independent modeling of class analogies (SIMCA) and partial least squares-discriminant analysis (PLS-DA) obtaining good predictive ability on an external test set (75% or higher depending on the technique). The use of data fusion strategies – in particular, the mid-level one – to integrate the data from the different platforms allowed the correct classification of all the training and validation samples.

Data-fusion for multiplatform characterization of an italian craft beer aimed at its authentication

International Nuclear Information System (INIS)

Biancolillo, Alessandra; Bucci, Remo; Magrì, Antonio L.; Magrì, Andrea D.; Marini, Federico

2014-01-01

Highlights: • Characterization of beer samples by five different fingerprinting techniques. • Chemometric discriminant and class-modeling techniques used for their authentication. • Mid-level data fusion allowed correct classification of all samples. - Abstract: Five different instrumental techniques: thermogravimetry, mid-infrared, near-infrared, ultra-violet and visible spectroscopies, have been used to characterize a high quality beer (Reale) from an Italian craft brewery (Birra del Borgo) and to differentiate it from other competing and lower quality products. Chemometric classification models were built on the separate blocks using soft independent modeling of class analogies (SIMCA) and partial least squares-discriminant analysis (PLS-DA) obtaining good predictive ability on an external test set (75% or higher depending on the technique). The use of data fusion strategies – in particular, the mid-level one – to integrate the data from the different platforms allowed the correct classification of all the training and validation samples

Chemometric techniques in distribution, characterisation and source apportionment of polycyclic aromatic hydrocarbons (PAHS) in aquaculture sediments in Malaysia.

Science.gov (United States)

Retnam, Ananthy; Zakaria, Mohamad Pauzi; Juahir, Hafizan; Aris, Ahmad Zaharin; Zali, Munirah Abdul; Kasim, Mohd Fadhil

2013-04-15

This study investigated polycyclic aromatic hydrocarbons (PAHs) pollution in surface sediments within aquaculture areas in Peninsular Malaysia using chemometric techniques, forensics and univariate methods. The samples were analysed using soxhlet extraction, silica gel column clean-up and gas chromatography mass spectrometry. The total PAH concentrations ranged from 20 to 1841 ng/g with a mean of 363 ng/g dw. The application of chemometric techniques enabled clustering and discrimination of the aquaculture sediments into four groups according to the contamination levels. A combination of chemometric and molecular indices was used to identify the sources of PAHs, which could be attributed to vehicle emissions, oil combustion and biomass combustion. Source apportionment using absolute principle component scores-multiple linear regression showed that the main sources of PAHs are vehicle emissions 54%, oil 37% and biomass combustion 9%. Land-based pollution from vehicle emissions is the predominant contributor of PAHs in the aquaculture sediments of Peninsular Malaysia. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multi-component determination and chemometric analysis of Paris polyphylla by ultra high performance liquid chromatography with photodiode array detection.

Science.gov (United States)

Chen, Pei; Jin, Hong-Yu; Sun, Lei; Ma, Shuang-Cheng

2016-09-01

Multi-source analysis of traditional Chinese medicine is key to ensuring its safety and efficacy. Compared with traditional experimental differentiation, chemometric analysis is a simpler strategy to identify traditional Chinese medicines. Multi-component analysis plays an increasingly vital role in the quality control of traditional Chinese medicines. A novel strategy, based on chemometric analysis and quantitative analysis of multiple components, was proposed to easily and effectively control the quality of traditional Chinese medicines such as Chonglou. Ultra high performance liquid chromatography was more convenient and efficient. Five species of Chonglou were distinguished by chemometric analysis and nine saponins, including Chonglou saponins I, II, V, VI, VII, D, and H, as well as dioscin and gracillin, were determined in 18 min. The method is feasible and credible, and enables to improve quality control of traditional Chinese medicines and natural products. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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.

Non-destructive geographical traceability of sea cucumber (Apostichopus japonicus) using near infrared spectroscopy combined with chemometric methods.

Science.gov (United States)

Guo, Xiuhan; Cai, Rui; Wang, Shisheng; Tang, Bo; Li, Yueqing; Zhao, Weijie

2018-01-01

Sea cucumber is the major tonic seafood worldwide, and geographical origin traceability is an important part of its quality and safety control. In this work, a non-destructive method for origin traceability of sea cucumber ( Apostichopus japonicus ) from northern China Sea and East China Sea using near infrared spectroscopy (NIRS) and multivariate analysis methods was proposed. Total fat contents of 189 fresh sea cucumber samples were determined and partial least-squares (PLS) regression was used to establish the quantitative NIRS model. The ordered predictor selection algorithm was performed to select feasible wavelength regions for the construction of PLS and identification models. The identification model was developed by principal component analysis combined with Mahalanobis distance and scaling to the first range algorithms. In the test set of the optimum PLS models, the root mean square error of prediction was 0.45, and correlation coefficient was 0.90. The correct classification rates of 100% were obtained in both identification calibration model and test model. The overall results indicated that NIRS method combined with chemometric analysis was a suitable tool for origin traceability and identification of fresh sea cucumber samples from nine origins in China.

Chemometric analysis of mass spectra of cis and trans fatty acid picolinyl esters

DEFF Research Database (Denmark)

Leth, Torben

1997-01-01

and trans fatty acids of C16:1, C18:1,n-9, C18:1,n-12, C18:2 and C22:1 in two- and three-dimensional score plots. With Soft Independent Modelling of Class Analogy (SIMCA), it is possible to calculate models that can predict from the mass spectra of unknown fatty acids whether they are of the cis or trans...... configuration, which is demonstrated for C18:1 trans from hardened margarine and butter....

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.

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.

Early detection of emerging street drugs by near infrared spectroscopy and chemometrics.

Science.gov (United States)

Risoluti, R; Materazzi, S; Gregori, A; Ripani, L

2016-06-01

Near-infrared spectroscopy (NIRs) is spreading as the tool of choice for fast and non-destructive analysis and detection of different compounds in complex matrices. This paper investigated the feasibility of using near infrared (NIR) spectroscopy coupled to chemometrics calibration to detect new psychoactive substances in street samples. The capabilities of this approach in forensic chemistry were assessed in the determination of new molecules appeared in the illicit market and often claimed to contain "non-illegal" compounds, although exhibiting important psychoactive effects. The study focused on synthetic molecules belonging to the classes of synthetic cannabinoids and phenethylamines. The approach was validated comparing results with officials methods and has been successfully applied for "in site" determination of illicit drugs in confiscated real samples, in cooperation with the Scientific Investigation Department (Carabinieri-RIS) of Rome. The achieved results allow to consider NIR spectroscopy analysis followed by chemometrics as a fast, cost-effective and useful tool for the preliminary determination of new psychoactive substances in forensic science. Copyright © 2016 Elsevier B.V. All rights reserved.

Chemometrics-based process analytical technology (PAT) tools: applications and adaptation in pharmaceutical and biopharmaceutical industries.

Science.gov (United States)

Challa, Shruthi; Potumarthi, Ravichandra

2013-01-01

Process analytical technology (PAT) is used to monitor and control critical process parameters in raw materials and in-process products to maintain the critical quality attributes and build quality into the product. Process analytical technology can be successfully implemented in pharmaceutical and biopharmaceutical industries not only to impart quality into the products but also to prevent out-of-specifications and improve the productivity. PAT implementation eliminates the drawbacks of traditional methods which involves excessive sampling and facilitates rapid testing through direct sampling without any destruction of sample. However, to successfully adapt PAT tools into pharmaceutical and biopharmaceutical environment, thorough understanding of the process is needed along with mathematical and statistical tools to analyze large multidimensional spectral data generated by PAT tools. Chemometrics is a chemical discipline which incorporates both statistical and mathematical methods to obtain and analyze relevant information from PAT spectral tools. Applications of commonly used PAT tools in combination with appropriate chemometric method along with their advantages and working principle are discussed. Finally, systematic application of PAT tools in biopharmaceutical environment to control critical process parameters for achieving product quality is diagrammatically represented.

Evolving chemometric models for predicting dynamic process parameters in viscose production

Energy Technology Data Exchange (ETDEWEB)

Cernuda, Carlos [Department of Knowledge-Based Mathematical Systems, Johannes Kepler University Linz (Austria); Lughofer, Edwin, E-mail: edwin.lughofer@jku.at [Department of Knowledge-Based Mathematical Systems, Johannes Kepler University Linz (Austria); Suppan, Lisbeth [Kompetenzzentrum Holz GmbH, St. Peter-Str. 25, 4021 Linz (Austria); Roeder, Thomas; Schmuck, Roman [Lenzing AG, 4860 Lenzing (Austria); Hintenaus, Peter [Software Research Center, Paris Lodron University Salzburg (Austria); Maerzinger, Wolfgang [i-RED Infrarot Systeme GmbH, Linz (Austria); Kasberger, Juergen [Recendt GmbH, Linz (Austria)

2012-05-06

Highlights: Black-Right-Pointing-Pointer Quality assurance of process parameters in viscose production. Black-Right-Pointing-Pointer Automatic prediction of spin-bath concentrations based on FTNIR spectra. Black-Right-Pointing-Pointer Evolving chemometric models for efficiently handling changing system dynamics over time (no time-intensive re-calibration needed). Black-Right-Pointing-Pointer Significant reduction of huge errors produced by statistical state-of-the-art calibration methods. Black-Right-Pointing-Pointer Sufficient flexibility achieved by gradual forgetting mechanisms. - Abstract: In viscose production, it is important to monitor three process parameters in order to assure a high quality of the final product: the concentrations of H{sub 2}SO{sub 4}, Na{sub 2}SO{sub 4} and Z{sub n}SO{sub 4}. During on-line production these process parameters usually show a quite high dynamics depending on the fiber type that is produced. Thus, conventional chemometric models, which are trained based on collected calibration spectra from Fourier transform near infrared (FT-NIR) measurements and kept fixed during the whole life-time of the on-line process, show a quite imprecise and unreliable behavior when predicting the concentrations of new on-line data. In this paper, we are demonstrating evolving chemometric models which are able to adapt automatically to varying process dynamics by updating their inner structures and parameters in a single-pass incremental manner. These models exploit the Takagi-Sugeno fuzzy model architecture, being able to model flexibly different degrees of non-linearities implicitly contained in the mapping between near infrared spectra (NIR) and reference values. Updating the inner structures is achieved by moving the position of already existing local regions and by evolving (increasing non-linearity) or merging (decreasing non-linearity) new local linear predictors on demand, which are guided by distance-based and similarity criteria. Gradual

Application of class-modelling techniques to infrared spectra for analysis of pork adulteration in beef jerkys.

Science.gov (United States)

Kuswandi, Bambang; Putri, Fitra Karima; Gani, Agus Abdul; Ahmad, Musa

2015-12-01

The use of chemometrics to analyse infrared spectra to predict pork adulteration in the beef jerky (dendeng) was explored. In the first step, the analysis of pork in the beef jerky formulation was conducted by blending the beef jerky with pork at 5-80 % levels. Then, they were powdered and classified into training set and test set. The second step, the spectra of the two sets was recorded by Fourier Transform Infrared (FTIR) spectroscopy using atenuated total reflection (ATR) cell on the basis of spectral data at frequency region 4000-700 cm(-1). The spectra was categorised into four data sets, i.e. (a) spectra in the whole region as data set 1; (b) spectra in the fingerprint region (1500-600 cm(-1)) as data set 2; (c) spectra in the whole region with treatment as data set 3; and (d) spectra in the fingerprint region with treatment as data set 4. The third step, the chemometric analysis were employed using three class-modelling techniques (i.e. LDA, SIMCA, and SVM) toward the data sets. Finally, the best result of the models towards the data sets on the adulteration analysis of the samples were selected and the best model was compared with the ELISA method. From the chemometric results, the LDA model on the data set 1 was found to be the best model, since it could classify and predict 100 % accuracy of the sample tested. The LDA model was applied toward the real samples of the beef jerky marketed in Jember, and the results showed that the LDA model developed was in good agreement with the ELISA method.

Chemometric characterization of the hydrogen bonding complexes of secondary amides and aromatic hydrocarbons

OpenAIRE

Jović, Branislav; Nikolić, Aleksandar; Petrović, Slobodan

2012-01-01

The paper reports the results of the study of hydrogen bonding complexes between secondary amides and various aromatic hydrocarbons. The possibility of using chemometric methods was investigated in order to characterize N-H•••π hydrogen bonded complexes. Hierarchical clustering and Principal Component Analysis (PCA) have been applied on infrared spectroscopic and Taft parameters of 43 N-substituted amide complexes with different aromatic hydrocarbons. Results obtained in this report are...

Rapid Chemometric X-Ray Fluorescence approaches for spectral Diagnostics of Cancer utilizing Tissue Trace Metals and Speciation profiles

International Nuclear Information System (INIS)

Okonda, J.J.

2015-01-01

Energy dispersive X-ray fluorescence (EDXRF) spectroscopy is an analytical method for identification and quantification of elements in materials by measurement of their spectral energy and intensity. EDXRFS spectroscopic technique involves simultaneous non-invasive acquisition of both fluorescence and scatter spectra from samples for quantitative determination of trace elemental content in complex matrix materials. The objective is develop a chemometric-aided EDXRFS method for rapid diagnosis of cancer and its severity (staging) based on analysis of trace elements (Cu, Zn, Fe, Se and Mn), their speciation and multivariate alterations of the elements in cancerous body tissue samples as cancer biomarkers. The quest for early diagnosis of cancer is based on the fact that early intervention translates to higher survival rate and better quality of life. Chemometric aided EDXRFS cancer diagnostic model has been evaluated as a direct and rapid superior alternative for the traditional quantitative methods used in XRF such as FP method. PCA results of cultured samples indicate that it is possible to characterize cancer at early and late stage of development based on trace elemental profiles

Robust methods for multivariate data analysis A1

DEFF Research Database (Denmark)

Frosch, Stina; Von Frese, J.; Bro, Rasmus

2005-01-01

Outliers may hamper proper classical multivariate analysis, and lead to incorrect conclusions. To remedy the problem of outliers, robust methods are developed in statistics and chemometrics. Robust methods reduce or remove the effect of outlying data points and allow the ?good? data to primarily...... determine the result. This article reviews the most commonly used robust multivariate regression and exploratory methods that have appeared since 1996 in the field of chemometrics. Special emphasis is put on the robust versions of chemometric standard tools like PCA and PLS and the corresponding robust...

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.

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)

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)

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....

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...

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)

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

International Nuclear Information System (INIS)

Kaniu, M.I.; Angeyo, K.H.; Mwala, A.K.; Mangala, M.J.

2012-01-01

Highlights: ► Chemometrics-assisted EDXRFS spectroscopy realizes direct, rapid and accurate analysis of trace bioavailable macronutrients in soils. ► The method is minimally invasive, involves little sample preparation, short analysis times and is relatively insensitive to matrix effects. ► 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 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 2 > 0.9) and low SEP (0.01% for N and Na, 0.05% for C, 0.08% for Mg and 1.98 μg g −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 utility in trace analysis of macronutrients in soil or related matrices.

Discriminating the Geographical Origins of Chinese White Lotus Seeds by Near-Infrared Spectroscopy and Chemometrics

Directory of Open Access Journals (Sweden)

Lu Xu

2015-01-01

Full Text Available The traceability of a Chinese white lotus seed (WLS with Protected Designation of Origin (PDO was investigated using near-infrared (NIR spectroscopy and chemometrics. Three chemometrics methods, discrimination analysis (DA, class modeling, and a newly proposed strategy, the fusion of DA and class modeling, were investigated to compare their capacity to trace the geographical origins of WLS. Least squares support vector machine (LS-SVM was developed to distinguish the PDO WLS from non-PDO WLS of four main producing areas. A class modeling technique, one-class partial least squares (OCPLS, was developed only using the data of PDO WLS. By the fusion of LS-SVM and OCPLS, the best prediction sensitivity and specificity were 0.900 and 0.973, respectively. The results indicate that fusion of DA and class modeling can enhance the specificity for detection of non-PDO products. The conclusion is that DA and class modeling should be combined for tracing food geographical origins.

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

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.

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.

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...

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 174...

Acoustic chemometric prediction of total solids in bioslurry

DEFF Research Database (Denmark)

Ihunegbo, Felicia; Madsen, Michael; Esbensen, Kim

2012-01-01

.86%) in the range of 5.8–10.8% w/w dry matter. Based on these excellent prediction performance measures, it is concluded that acoustic chemometrics has come of age as a full grown PAT approach for on-line monitoring of dry matter (TS) in complex bioslurry, with a promising application potential in other biomass...

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.

Near Infrared Spectroscopy Calibration for Wood Chemistry: Which Chemometric Technique Is Best for Prediction and Interpretation?

Directory of Open Access Journals (Sweden)

Brian K. Via

2014-07-01

Full Text Available 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 after 1st derivative pretreatment, was utilized for model building and loadings investigation. As demonstrated by others, PLS was found to provide better predictive diagnostics. However, PCR exhibited a more precise estimate of loading peaks which makes PCR better for interpretation. Application of the 1st derivative appeared to assist in improving both PCR and PLS loading precision, but due to the small sample size, the two chemometric methods could not be compared statistically. This work is important because to date most research works have committed to PLS because it yields better predictive performance. But this research suggests there is a tradeoff between better prediction and model interpretation. Future work is needed to compare PLS and PCR for a suite of spectral pretreatment techniques.

Near infrared spectroscopy calibration for wood chemistry: which chemometric technique is best for prediction and interpretation?

Science.gov (United States)

Via, Brian K; Zhou, Chengfeng; Acquah, Gifty; Jiang, Wei; Eckhardt, Lori

2014-07-25

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 after 1st derivative pretreatment, was utilized for model building and loadings investigation. As demonstrated by others, PLS was found to provide better predictive diagnostics. However, PCR exhibited a more precise estimate of loading peaks which makes PCR better for interpretation. Application of the 1st derivative appeared to assist in improving both PCR and PLS loading precision, but due to the small sample size, the two chemometric methods could not be compared statistically. This work is important because to date most research works have committed to PLS because it yields better predictive performance. But this research suggests there is a tradeoff between better prediction and model interpretation. Future work is needed to compare PLS and PCR for a suite of spectral pretreatment techniques.

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

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...... metabolomics platform and highlights the opportunities that NMR spectra can provide in future nutrition studies. Three areas are emphasized: (1) NMR as an unbiased and non-destructive platform for providing an overview of the metabolome under investigation, (2) NMR for providing versatile information and data...... 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...

Chemometric modeling of thermogravimetric data for the compositional analysis of forest biomass.

Science.gov (United States)

Acquah, Gifty E; Via, Brian K; Fasina, Oladiran O; Adhikari, Sushil; Billor, Nedret; Eckhardt, Lori G

2017-01-01

The objective of this study was to investigated the use of chemometric modeling of thermogravimetric (TG) data as an alternative approach to estimate the chemical and proximate (i.e. volatile matter, fixed carbon and ash contents) composition of lignocellulosic biomass. Since these properties affect the conversion pathway, processing costs, yield and / or quality of products, a capability to rapidly determine these for biomass feedstock entering the process stream will be useful in the success and efficiency of bioconversion technologies. The 38-minute long methodology developed in this study enabled the simultaneous prediction of both the chemical and proximate properties of forest-derived biomass from the same TG data. Conventionally, two separate experiments had to be conducted to obtain such information. In addition, the chemometric models constructed with normalized TG data outperformed models developed via the traditional deconvolution of TG data. PLS and PCR models were especially robust in predicting the volatile matter (R2-0.92; RPD- 3.58) and lignin (R2-0.82; RPD- 2.40) contents of the biomass. The application of chemometrics to TG data also made it possible to predict some monomeric sugars in this study. Elucidation of PC loadings obtained from chemometric models also provided some insights into the thermal decomposition behavior of the chemical constituents of lignocellulosic biomass. For instance, similar loadings were noted for volatile matter and cellulose, and for fixed carbon and lignin. The findings indicate that common latent variables are shared between these chemical and thermal reactivity properties. Results from this study buttresses literature that have reported that the less thermally stable polysaccharides are responsible for the yield of volatiles whereas the more recalcitrant lignin with its higher percentage of elementary carbon contributes to the yield of fixed carbon.

Chemometric modeling of thermogravimetric data for the compositional analysis of forest biomass.

Directory of Open Access Journals (Sweden)

Gifty E Acquah

Full Text Available The objective of this study was to investigated the use of chemometric modeling of thermogravimetric (TG data as an alternative approach to estimate the chemical and proximate (i.e. volatile matter, fixed carbon and ash contents composition of lignocellulosic biomass. Since these properties affect the conversion pathway, processing costs, yield and / or quality of products, a capability to rapidly determine these for biomass feedstock entering the process stream will be useful in the success and efficiency of bioconversion technologies. The 38-minute long methodology developed in this study enabled the simultaneous prediction of both the chemical and proximate properties of forest-derived biomass from the same TG data. Conventionally, two separate experiments had to be conducted to obtain such information. In addition, the chemometric models constructed with normalized TG data outperformed models developed via the traditional deconvolution of TG data. PLS and PCR models were especially robust in predicting the volatile matter (R2-0.92; RPD- 3.58 and lignin (R2-0.82; RPD- 2.40 contents of the biomass. The application of chemometrics to TG data also made it possible to predict some monomeric sugars in this study. Elucidation of PC loadings obtained from chemometric models also provided some insights into the thermal decomposition behavior of the chemical constituents of lignocellulosic biomass. For instance, similar loadings were noted for volatile matter and cellulose, and for fixed carbon and lignin. The findings indicate that common latent variables are shared between these chemical and thermal reactivity properties. Results from this study buttresses literature that have reported that the less thermally stable polysaccharides are responsible for the yield of volatiles whereas the more recalcitrant lignin with its higher percentage of elementary carbon contributes to the yield of fixed carbon.

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

Energy Technology Data Exchange (ETDEWEB)

Rios-Corripio, M A; Rojas-Lopez, M; Delgado-Macuil, R [CIBA-Tlaxcala, IPN, Tlaxcala, Tlax. (Mexico); Rios-Leal, E [CINVESTAV, Zacatenco, Mexico D.F. (Mexico)

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.

Chemometric characterization of the hydrogen bonding complexes of secondary amides and aromatic hydrocarbons

Directory of Open Access Journals (Sweden)

Jović Branislav

2012-01-01

Full Text Available The paper reports the results of the study of hydrogen bonding complexes between secondary amides and various aromatic hydrocarbons. The possibility of using chemometric methods was investigated in order to characterize N-H•••π hydrogen bonded complexes. Hierarchical clustering and Principal Component Analysis (PCA have been applied on infrared spectroscopic and Taft parameters of 43 N-substituted amide complexes with different aromatic hydrocarbons. Results obtained in this report are in good agreement with conclusions of other spectroscopic and thermodynamic analysis.

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

The role of chemometrics in single and sequential extraction assays: a review. Part II. Cluster analysis, multiple linear regression, mixture resolution, experimental design and other techniques.

Science.gov (United States)

Giacomino, Agnese; Abollino, Ornella; Malandrino, Mery; Mentasti, Edoardo

2011-03-04

Single and sequential extraction procedures are used for studying element mobility and availability in solid matrices, like soils, sediments, sludge, and airborne particulate matter. In the first part of this review we reported an overview on these procedures and described the applications of chemometric uni- and bivariate techniques and of multivariate pattern recognition techniques based on variable reduction to the experimental results obtained. The second part of the review deals with the use of chemometrics not only for the visualization and interpretation of data, but also for the investigation of the effects of experimental conditions on the response, the optimization of their values and the calculation of element fractionation. We will describe the principles of the multivariate chemometric techniques considered, the aims for which they were applied and the key findings obtained. The following topics will be critically addressed: pattern recognition by cluster analysis (CA), linear discriminant analysis (LDA) and other less common techniques; modelling by multiple linear regression (MLR); investigation of spatial distribution of variables by geostatistics; calculation of fractionation patterns by a mixture resolution method (Chemometric Identification of Substrates and Element Distributions, CISED); optimization and characterization of extraction procedures by experimental design; other multivariate techniques less commonly applied. Copyright © 2010 Elsevier B.V. All rights reserved.

Determination of the geographic origin of rice by chemometrics with strontium and lead isotope ratios and multielement concentrations.

Science.gov (United States)

Ariyama, Kaoru; Shinozaki, Miyuki; Kawasaki, Akira

2012-02-22

The objective of this study was to develop a technique for determining the country of origin of rice in the Japanese market. The rice samples included a total of 350 products grown in Japan (n = 200), the United States (n = 50), China (n = 50), and Thailand (n = 50). In this study, (87)Sr/(86)Sr and Pb isotope ((204)Pb, (206)Pb, (207)Pb, and (208)Pb) ratios and multielement concentrations (Al, Fe, Co, Ni, Cu, Rb, Sr, and Ba) were determined by high-resolution inductively coupled plasma mass spectrometry. By combining three chemometric techniques based on different principles and determination criteria, the countries of origin of rice were determined. The predictions made by 10-fold cross-validation were around 97% accurate. The presented method demonstrated the effectiveness of determining the geographic origin of an agricultural product by combining several chemometric techniques using heavy element isotope ratios and multielement concentrations.

At-line determination of pharmaceuticals small molecule's blending end point using chemometric modeling combined with Fourier transform near infrared spectroscopy

Science.gov (United States)

Tewari, Jagdish; Strong, Richard; Boulas, Pierre

2017-02-01

This article summarizes the development and validation of a Fourier transform near infrared spectroscopy (FT-NIR) method for the rapid at-line prediction of active pharmaceutical ingredient (API) in a powder blend to optimize small molecule formulations. The method was used to determine the blend uniformity end-point for a pharmaceutical solid dosage formulation containing a range of API concentrations. A set of calibration spectra from samples with concentrations ranging from 1% to 15% of API (w/w) were collected at-line from 4000 to 12,500 cm- 1. The ability of the FT-NIR method to predict API concentration in the blend samples was validated against a reference high performance liquid chromatography (HPLC) method. The prediction efficiency of four different types of multivariate data modeling methods such as partial least-squares 1 (PLS1), partial least-squares 2 (PLS2), principal component regression (PCR) and artificial neural network (ANN), were compared using relevant multivariate figures of merit. The prediction ability of the regression models were cross validated against results generated with the reference HPLC method. PLS1 and ANN showed excellent and superior prediction abilities when compared to PLS2 and PCR. Based upon these results and because of its decreased complexity compared to ANN, PLS1 was selected as the best chemometric method to predict blend uniformity at-line. The FT-NIR measurement and the associated chemometric analysis were implemented in the production environment for rapid at-line determination of the end-point of the small molecule blending operation. FIGURE 1: Correlation coefficient vs Rank plot FIGURE 2: FT-NIR spectra of different steps of Blend and final blend FIGURE 3: Predictions ability of PCR FIGURE 4: Blend uniformity predication ability of PLS2 FIGURE 5: Prediction efficiency of blend uniformity using ANN FIGURE 6: Comparison of prediction efficiency of chemometric models TABLE 1: Order of Addition for Blending Steps

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...

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...

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.

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

Can spectroscopy in combination with chemometrics replace minks in digestibility tests?

DEFF Research Database (Denmark)

Dahl, P.L.; Christensen, B.M.; Munck, L.

2000-01-01

One of the most relevant but expensive methods of assessing the quality of fish meal is the physiological digestibility test with minks. The purpose of this study was to determine whether spectroscopic and chemical analyses evaluated with chemometrics can replace minks in digestibility tests....... The spectroscopic methods used were the two complementary techniques of fluorescence emission and near-infrared reflectance. The investigation included 54 samples of high-quality fish meal ranging from 89.6 to 93.9 on the mink digestibility index. The investigation also included determination of seven quality...... parameters in the fish meal to substantiate the spectroscopic models on the mink digestibility. These quality parameters include the content of protein, oil, water, water-soluble protein, ash and the biogenic substance cadaverine as well as the titration value. The study demonstrates that the mink...

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, ...

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.

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.

Incorporation of support vector machines in the LIBS toolbox for sensitive and robust classification amidst unexpected sample and system variability.

Science.gov (United States)

Dingari, Narahara Chari; Barman, Ishan; Myakalwar, Ashwin Kumar; Tewari, Surya P; Kumar Gundawar, Manoj

2012-03-20

Despite the intrinsic elemental analysis capability and lack of sample preparation requirements, laser-induced breakdown spectroscopy (LIBS) has not been extensively used for real-world applications, e.g., quality assurance and process monitoring. Specifically, variability in sample, system, and experimental parameters in LIBS studies present a substantive hurdle for robust classification, even when standard multivariate chemometric techniques are used for analysis. Considering pharmaceutical sample investigation as an example, we propose the use of support vector machines (SVM) as a nonlinear classification method over conventional linear techniques such as soft independent modeling of class analogy (SIMCA) and partial least-squares discriminant analysis (PLS-DA) for discrimination based on LIBS measurements. Using over-the-counter pharmaceutical samples, we demonstrate that the application of SVM enables statistically significant improvements in prospective classification accuracy (sensitivity), because of its ability to address variability in LIBS sample ablation and plasma self-absorption behavior. Furthermore, our results reveal that SVM provides nearly 10% improvement in correct allocation rate and a concomitant reduction in misclassification rates of 75% (cf. PLS-DA) and 80% (cf. SIMCA)-when measurements from samples not included in the training set are incorporated in the test data-highlighting its robustness. While further studies on a wider matrix of sample types performed using different LIBS systems is needed to fully characterize the capability of SVM to provide superior predictions, we anticipate that the improved sensitivity and robustness observed here will facilitate application of the proposed LIBS-SVM toolbox for screening drugs and detecting counterfeit samples, as well as in related areas of forensic and biological sample analysis.

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

DEFF Research Database (Denmark)

Shrestha, Santosh; Deleuran, Lise Christina; Gislum, René

2016-01-01

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...

Assessment of sediment quality in the Mediterranean Sea-Boughrara lagoon exchange areas (southeastern Tunisia): GIS approach-based chemometric methods.

Science.gov (United States)

Kharroubi, Adel; Gargouri, Dorra; Baati, Houda; Azri, Chafai

2012-06-01

Concentrations of selected heavy metals (Cd, Pb, Zn, Cu, Mn, and Fe) in surface sediments from 66 sites in both northern and eastern Mediterranean Sea-Boughrara lagoon exchange areas (southeastern Tunisia) were studied in order to understand current metal contamination due to the urbanization and economic development of nearby several coastal regions of the Gulf of Gabès. Multiple approaches were applied for the sediment quality assessment. These approaches were based on GIS coupled with chemometric methods (enrichment factors, geoaccumulation index, principal component analysis, and cluster analysis). Enrichment factors and principal component analysis revealed two distinct groups of metals. The first group corresponded to Fe and Mn derived from natural sources, and the second group contained Cd, Pb, Zn, and Cu originated from man-made sources. For these latter metals, cluster analysis showed two distinct distributions in the selected areas. They were attributed to temporal and spatial variations of contaminant sources input. The geoaccumulation index (I (geo)) values explained that only Cd, Pb, and Cu can be considered as moderate to extreme pollutants in the studied sediments.

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.

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.

Characterization of cider apples on the basis of their fatty acid profiles.

Science.gov (United States)

Blanco-Gomis, Domingo; Mangas Alonso, Juan J; Margolles Cabrales, Inmaculada; Arias Abrodo, Pilar

2002-02-27

In the current study, the fatty acids composition of 30 monovarietal apple juices from six cider apple varieties belonging to two categories was analyzed. The different apple juices were obtained from three consecutive harvests (1997, 1998, and 1999). The fatty acids concentration in apple juice together with chemometric techniques such as principal components analysis (PCA), soft independent modeling of class analogy (SIMCA), and linear discriminant analysis (LDA), allowed us to differentiate apple juices on the basis of the sweet or sharp category to which the cider apple variety belongs. Fatty acids such as the unsaturated oleic and linoleic acids, and saturated caprylic, capric, stearic, and palmitic acids were related to the sweet cider apple category, while pentadecanoic acid is related to the sharp class.

Rationalization of dye uptake on titania slides for dye-sensitized solar cells by a combined chemometric and structural approach.

Science.gov (United States)

Gianotti, Valentina; Favaro, Giada; Bonandini, Luca; Palin, Luca; Croce, Gianluca; Boccaleri, Enrico; Artuso, Emma; van Beek, Wouter; Barolo, Claudia; Milanesio, Marco

2014-11-01

A model photosensitizer (D5) for application in dye-sensitized solar cells has been studied by a combination of XRD, theoretical calculations, and spectroscopic/chemometric methods. The conformational stability and flexibility of D5 and molecular interactions between adjacent molecules were characterized to obtain the driving forces that govern D5 uptake and grafting and to infer the most likely arrangement of the molecules on the surface of TiO2. A spectroscopic/chemometric approach was then used to yield information about the correlations between three variables that govern the uptake itself: D5 concentration, dispersant (chenodeoxycholic acid; CDCA) concentration, and contact time. The obtained regression model shows that large uptakes can be obtained at high D5 concentrations in the presence of CDCA with a long contact time, or in absence of CDCA if the contact time is short, which suggests how dye uptake and photovoltaic device preparation can be optimized. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Chemometric assessment of enhanced bioremediation of oil contaminated soils.

Science.gov (United States)

Soleimani, Mohsen; Farhoudi, Majid; Christensen, Jan H

2013-06-15

Bioremediation is a promising technique for reclamation of oil polluted soils. In this study, six methods for enhancing bioremediation were tested on oil contaminated soils from three refinery areas in Iran (Isfahan, Arak, and Tehran). The methods included bacterial enrichment, planting, and addition of nitrogen and phosphorous, molasses, hydrogen peroxide, and a surfactant (Tween 80). Total petroleum hydrocarbon (TPH) concentrations and CHEMometric analysis of Selected Ion Chromatograms (SIC) termed CHEMSIC method of petroleum biomarkers including terpanes, regular, diaromatic and triaromatic steranes were used for determining the level and type of hydrocarbon contamination. The same methods were used to study oil weathering of 2 to 6 ring polycyclic aromatic compounds (PACs). Results demonstrated that bacterial enrichment and addition of nutrients were most efficient with 50% to 62% removal of TPH. Furthermore, the CHEMSIC results demonstrated that the bacterial enrichment was more efficient in degradation of n-alkanes and low molecular weight PACs as well as alkylated PACs (e.g. C₃-C₄ naphthalenes, C₂ phenanthrenes and C₂-C₃ dibenzothiophenes), while nutrient addition led to a larger relative removal of isoprenoids (e.g. norpristane, pristane and phytane). It is concluded that the CHEMSIC method is a valuable tool for assessing bioremediation efficiency. Copyright © 2013 Elsevier B.V. All rights reserved.

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

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Grandizoli, Caroline Werner Pereira da Silva; Campos, Francinete Ramos; Simonelli, Fabio; Barison, Andersson [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)

Spectrophotometric and chemometric methods for determination of imipenem, ciprofloxacin hydrochloride, dexamethasone sodium phosphate, paracetamol and cilastatin sodium in human urine

Science.gov (United States)

El-Kosasy, A. M.; Abdel-Aziz, Omar; Magdy, N.; El Zahar, N. M.

2016-03-01

New accurate, sensitive and selective spectrophotometric and chemometric methods were developed and subsequently validated for determination of Imipenem (IMP), ciprofloxacin hydrochloride (CIPRO), dexamethasone sodium phosphate (DEX), paracetamol (PAR) and cilastatin sodium (CIL) in human urine. These methods include a new derivative ratio method, namely extended derivative ratio (EDR), principal component regression (PCR) and partial least-squares (PLS) methods. A novel EDR method was developed for the determination of these drugs, where each component in the mixture was determined by using a mixture of the other four components as divisor. Peak amplitudes were recorded at 293.0 nm, 284.0 nm, 276.0 nm, 257.0 nm and 221.0 nm within linear concentration ranges 3.00-45.00, 1.00-15.00, 4.00-40.00, 1.50-25.00 and 4.00-50.00 μg mL- 1 for IMP, CIPRO, DEX, PAR and CIL, respectively. PCR and PLS-2 models were established for simultaneous determination of the studied drugs in the range of 3.00-15.00, 1.00-13.00, 4.00-12.00, 1.50-9.50, and 4.00-12.00 μg mL- 1 for IMP, CIPRO, DEX, PAR and CIL, respectively, by using eighteen mixtures as calibration set and seven mixtures as validation set. The suggested methods were validated according to the International Conference of Harmonization (ICH) guidelines and the results revealed that they were accurate, precise and reproducible. The obtained results were statistically compared with those of the published methods and there was no significant difference.

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.

Combined chemometric analysis of (1)H NMR, (13)C NMR and stable isotope data to differentiate organic and conventional milk.

Science.gov (United States)

Erich, Sarah; Schill, Sandra; Annweiler, Eva; Waiblinger, Hans-Ulrich; Kuballa, Thomas; Lachenmeier, Dirk W; Monakhova, Yulia B

2015-12-01

The increased sales of organically produced food create a strong need for analytical methods, which could authenticate organic and conventional products. Combined chemometric analysis of (1)H NMR-, (13)C NMR-spectroscopy data, stable-isotope data (IRMS) and α-linolenic acid content (gas chromatography) was used to differentiate organic and conventional milk. In total 85 raw, pasteurized and ultra-heat treated (UHT) milk samples (52 organic and 33 conventional) were collected between August 2013 and May 2014. The carbon isotope ratios of milk protein and milk fat as well as the α-linolenic acid content of these samples were determined. Additionally, the milk fat was analyzed by (1)H and (13)C NMR spectroscopy. The chemometric analysis of combined data (IRMS, GC, NMR) resulted in more precise authentication of German raw and retail milk with a considerably increased classification rate of 95% compared to 81% for NMR and 90% for IRMS using linear discriminate analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Simultaneous kinetic spectrometric determination of three flavonoid antioxidants in fruit with the aid of chemometrics

Science.gov (United States)

Sun, Ruiling; Wang, Yong; Ni, Yongnian; Kokot, Serge

2014-03-01

A simple, inexpensive and sensitive kinetic spectrophotometric method was developed for the simultaneous determination of three anti-carcinogenic flavonoids: catechin, quercetin and naringenin, in fruit samples. A yellow chelate product was produced in the presence neocuproine and Cu(I) - a reduction product of the reaction between the flavonoids with Cu(II), and this enabled the quantitative measurements with UV-vis spectrophotometry. The overlapping spectra obtained, were resolved with chemometrics calibration models, and the best performing method was the fast independent component analysis (fast-ICA/PCR (Principal component regression)); the limits of detection were 0.075, 0.057 and 0.063 mg L-1 for catechin, quercetin and naringenin, respectively. The novel method was found to outperform significantly the common HPLC procedure.

Spatial assessment and source identification of heavy metals pollution in surface water using several chemometric techniques.

Science.gov (United States)

Ismail, Azimah; Toriman, Mohd Ekhwan; Juahir, Hafizan; Zain, Sharifuddin Md; Habir, Nur Liyana Abdul; Retnam, Ananthy; Kamaruddin, Mohd Khairul Amri; Umar, Roslan; Azid, Azman

2016-05-15

This study presents the determination of the spatial variation and source identification of heavy metal pollution in surface water along the Straits of Malacca using several chemometric techniques. Clustering and discrimination of heavy metal compounds in surface water into two groups (northern and southern regions) are observed according to level of concentrations via the application of chemometric techniques. Principal component analysis (PCA) demonstrates that Cu and Cr dominate the source apportionment in northern region with a total variance of 57.62% and is identified with mining and shipping activities. These are the major contamination contributors in the Straits. Land-based pollution originating from vehicular emission with a total variance of 59.43% is attributed to the high level of Pb concentration in the southern region. The results revealed that one state representing each cluster (northern and southern regions) is significant as the main location for investigating heavy metal concentration in the Straits of Malacca which would save monitoring cost and time. The monitoring of spatial variation and source of heavy metals pollution at the northern and southern regions of the Straits of Malacca, Malaysia, using chemometric analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

UV-Vis spectroscopy with chemometric data treatment. An option for on-line control in nuclear industry

International Nuclear Information System (INIS)

Kirsanov, Dmitry; Legin, Andrey

2017-01-01

Chemometrics can be very useful for the classical field of UV-Vis determination of metals in aqueous solutions. A conventional approach consisting of using selective bands in a univariate mode is often not applicable to the real-world samples from e.g. hydrometallurgical processes, because of overlapping signals, light scattering on foreign particles, gas bubble formation, etc. And this is where chemometrics can do a good job. This paper overviews certain contributions to the field of multivariate data processing of UV-Vis spectra for seemingly simple case of metal detection in aqueous solutions. Special attention is given to applications in nuclear technology field. (author)

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.

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.

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)

Chemometric evaluation of trace elements in Brazilian medicinal plants

Energy Technology Data Exchange (ETDEWEB)

Silva, Paulo S.C. da; Francisconi, Lucilaine S.; Goncalves, Rodolfo D.M.R., E-mail: pscsilva@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil). Centro do Reator de Pesquisas

2013-07-01

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)

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.

Choice and validation of a near infrared spectroscopic application for the identity control of starting materials. practical experience with the EU draft Note for Guidance on the use of near infrared spectroscopy by the pharmaceutical industry and the data to be forwarded in part II of the dossier for a marketing authorization.

Science.gov (United States)

Vredenbregt, M J; Caspers, P W J; Hoogerbrugge, R; Barends, D M

2003-11-01

Recently the CPMP/CVMP sent out for consultation the draft Note for Guidance (dNfG) on the use of near infrared spectroscopy (NIRS) by the pharmaceutical industry and the data to be forwarded in part II of the dossier for a marketing authorization. We explored the practicability of this dNfG with respect to the verification of the correct identity of starting materials in a generic tablet-manufacturing site. Within the boundaries of the dNfG, a release procedure was developed for 12 substances containing structurally related compounds and substances differing only in particle size. For the method development literature data were also taken into consideration. Good results were obtained with wavelength correlation (WC), applied on raw spectra or second derivative spectra both without smoothing. The defined threshold of 0.98 for raw spectra differentiated between all molecular structures. Both methods were found to be robust over a period of 1 year. For the differentiation between the different particle sizes a subsequent second chemometric technique had to be used. Soft independent modelling of class analogy (SIMCA) with a probability level of 0.01 proved suitable. Internal and external validation I according to the dNfG showed no incorrect rejections or false acceptances. External validation II according to the dNfG was carried out with 95 potentially interfering substances from which 46 were tested experimentally. Macrogol 400 was not distinguished from macrogol 300. For the complete verification of the identity of macrogol 300 test A of the European Pharmacopoeia is needed in addition to the NIRS application. A release procedure developed with WC applied on raw spectra and SIMCA as a second method, which is different from the preferred method of the dNfG, was tested in practice with good results. We conclude that the dNfG has good practicability and that deviations from the preferred methods of the dNfG can also give good differentiation.

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

with multivariate chemometric methods is a nonsubjective, statistics-based approach for heparin quality control and purity assessment that, once standardized, minimizes the need for expert analysts. (orig.)

Chemometric techniques in oil classification from oil spill fingerprinting.

Science.gov (United States)

Ismail, Azimah; Toriman, Mohd Ekhwan; Juahir, Hafizan; Kassim, Azlina Md; Zain, Sharifuddin Md; Ahmad, Wan Kamaruzaman Wan; Wong, Kok Fah; Retnam, Ananthy; Zali, Munirah Abdul; Mokhtar, Mazlin; Yusri, Mohd Ayub

2016-10-15

Extended use of GC-FID and GC-MS in oil spill fingerprinting and matching is significantly important for oil classification from the oil spill sources collected from various areas of Peninsular Malaysia and Sabah (East Malaysia). Oil spill fingerprinting from GC-FID and GC-MS coupled with chemometric techniques (discriminant analysis and principal component analysis) is used as a diagnostic tool to classify the types of oil polluting the water. Clustering and discrimination of oil spill compounds in the water from the actual site of oil spill events are divided into four groups viz. diesel, Heavy Fuel Oil (HFO), Mixture Oil containing Light Fuel Oil (MOLFO) and Waste Oil (WO) according to the similarity of their intrinsic chemical properties. Principal component analysis (PCA) demonstrates that diesel, HFO, MOLFO and WO are types of oil or oil products from complex oil mixtures with a total variance of 85.34% and are identified with various anthropogenic activities related to either intentional releasing of oil or accidental discharge of oil into the environment. Our results show that the use of chemometric techniques is significant in providing independent validation for classifying the types of spilled oil in the investigation of oil spill pollution in Malaysia. This, in consequence would result in cost and time saving in identification of the oil spill sources. Copyright © 2016. Published by Elsevier Ltd.

Chemical composition analysis and authentication of whisky.

Science.gov (United States)

Wiśniewska, Paulina; Dymerski, Tomasz; Wardencki, Waldemar; Namieśnik, Jacek

2015-08-30

Whisky (whiskey) is one of the most popular spirit-based drinks made from malted or saccharified grains, which should mature for at least 3 years in wooden barrels. High popularity of products usually causes a potential risk of adulteration. Thus authenticity assessment is one of the key elements of food product marketing. Authentication of whisky is based on comparing the composition of this alcohol with other spirit drinks. The present review summarizes all information about the comparison of whisky and other alcoholic beverages, the identification of type of whisky or the assessment of its quality and finally the authentication of whisky. The article also presents the various techniques used for analyzing whisky, such as gas and liquid chromatography with different types of detectors (FID, AED, UV-Vis), electronic nose, atomic absorption spectroscopy and mass spectrometry. In some cases the application of chemometric methods is also described, namely PCA, DFA, LDA, ANOVA, SIMCA, PNN, k-NN and CA, as well as preparation techniques such SPME or SPE. © 2014 Society of Chemical Industry.

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.

Effect of emodin on Candida albicans growth investigated by microcalorimetry combined with chemometric analysis.

Science.gov (United States)

Kong, W J; Wang, J B; Jin, C; Zhao, Y L; Dai, C M; Xiao, X H; Li, Z L

2009-07-01

Using the 3114/3115 thermal activity monitor (TAM) air isothermal microcalorimeter, ampoule mode, the heat output of Candida albicans growth at 37 degrees C was measured, and the effect of emodin on C. albicans growth was evaluated by microcalorimetry coupled with chemometric methods. The similarities between the heat flow power (HFP)-time curves of C. albicans growth affected by different concentrations of emodin were calculated by similarity analysis (SA). In the correspondence analysis (CA) diagram of eight quantitative parameters taken from the HFP-time curves, it could be deduced that emodin had definite dose-effect relationship as the distance between different concentrations of it increased along with the dosage and the effect. From the principal component analysis (PCA) on eight quantitative parameters, the action of emodin on C. albicans growth could be easily evaluated by analyzing the change of values of the main two parameters, growth rate constant k (2) and maximum power output P(2)(m). The coherent results of SA, CA, and PCA showed that emodin at different concentrations had different effects on C. albicans growth metabolism: A low concentration (0-10 microg ml(-1)) poorly inhibited the growth of C. albicans, and a high concentration (15-35 microg ml(-1)) could notably inhibit growth of this fungus. This work provided a useful idea of the combination of microcalorimetry and chemometric analysis for investigating the effect of drug and other compounds on microbes.

Chemometrics methods for the investigation of methylmercury and total mercury contamination in mollusks samples collected from coastal sites along the Chinese Bohai Sea

International Nuclear Information System (INIS)

Wang Yawei; Liang Lina; Shi Jianbo; Jiang Guibin

2005-01-01

The development and application of chemometrics methods, principal component analysis (PCA), cluster analysis and correlation analysis for the determination of methylmercury (MeHg) and total mercury (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. - Rapana venosa might be used as a potential biomonitor for Hg pollution in the Bohai Sea, China

GC/MS analysis of pesticides in the Ferrara area (Italy) surface water: a chemometric study.

Science.gov (United States)

Pasti, Luisa; Nava, Elisabetta; Morelli, Marco; Bignami, Silvia; Dondi, Francesco

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.

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

Chemometric study of Maya Blue from the voltammetry of microparticles approach.

Science.gov (United States)

Doménech, Antonio; Doménech-Carbó, María Teresa; de Agredos Pascual, María Luisa Vazquez

2007-04-01

The use of the voltammetry of microparticles at paraffin-impregnated graphite electrodes allows for the characterization of different types of Maya Blue (MB) used in wall paintings from different archaeological sites of Campeche and YucatAn (Mexico). Using voltammetric signals for electron-transfer processes involving palygorskite-associated indigo and quinone functionalities generated by scratching the graphite surface, voltammograms provide information on the composition and texture of MB samples. Application of hierarchical cluster analysis and other chemometric methods allows us to characterize samples from different archaeological sites and to distinguish between samples proceeding from different chronological periods. Comparison between microscopic, spectroscopic, and electrochemical examination of genuine MB samples and synthetic specimens indicated that the preparation procedure of the pigment evolved in time via successive steps anticipating modern synthetic procedures, namely, hybrid organic-inorganic synthesis, temperature control of chemical reactivity, and template-like synthesis.

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

Science.gov (United States)

Kaniu, M I; Angeyo, K H; Mwala, A K; Mangala, M J

2012-06-04

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 (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(2)>0.9) and low SEP (0.01% for N and Na, 0.05% for C, 0.08% for Mg and 1.98 μg g(-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 utility in trace analysis of macronutrients in soil or related matrices. Copyright © 2012 Elsevier B.V. All rights reserved.

Forecast of the direction changes of meat products odor in the development of new recipes according to the results of “electronic nose” data treatment with chemometric methods

Directory of Open Access Journals (Sweden)

T. A. Kuchmenko

2016-01-01

Full Text Available The possibility of using new parameters of quartz crystal microbalance and methods of principal component analysis and discriminant analysis using regression to latent structures for processing the output data of piezosensors array for the detection of individual odor-forming compounds, quantitative assessment of odor properties in routine analysis, in the development of new recipes of food systems with the introduction of functional additives in the factory laboratories are discussed. Sorption of volatile organic compounds that make up the odor of meat products, on thin films of sorbents - modifiers of piezoelectric resonators electrodes, forming an array of sensors of gases analyzer "electronic nose" is studied. The resulting sensor array is trained on the main marker substances (distilled water, ethane, butyric acids, aliphatic alcohols (C2-C5 of normal and isomeric structure, dimethyl ketone, methyl ethyl ketone, alkyl acetates (C2-C5 methylpropionate. The effect of of water vapors as interfering factor in sorption of organic compounds was assessed. The parameters of the efficiency of volatile compounds sorption, allowing the identification of individual organic compounds or a class of similar to them in nature in gas mixtures were calculated. The use of discriminant analysis with regression to latent structures allowed the identification of individual organic compounds in the equilibrium gas phases over the real models for forecasting of change of direction of meat products odor with partial replacement of meat raw materials with functional preparations of plant origin (buckwheat and millet cereals, pickles of soybean and rapeseed protein and products of microbial synthesis (preparation of yeast and wheat bran. For a detailed study of the changes in odor direction _ during the introduction of different amounts of cereals in the product the principal components method was applied. As the input parameters for the chemometric methods

[Development of the soft independent modelling of class analogies model to discrimination Vibrio parahemolyticus by Smartongue].

Science.gov (United States)

Huang, Jianfeng; Zhao, Guangying; Dou, Wenchao

2011-04-01

To explore a new rapid detection method for detecting of Food pathogens. We used the Smartongue, to determine the composition informations of the liquid culture samples and combined with soft independent modelling of class analogies (SIMCA) to analyze their respective species, then set up a Smartongue -SIMCA model to discriminate the V. parahaemolyticus. The Smartongue has 6 working electrodes and three frequency segments, we can built 18 discrimination models in one detection. After comparing all the 18 discrimination models, the optimal working electrodes and frequency segments were selected out, they were: palladium electrode in 1 Hz frequency segment, tungsten electrode in 100 Hz and silver electrode in 100 Hz. Then 10 species of pathogenic Vibrio were discriminated by the 3 models. The V. damsela, V. metschnikovii, V. alginalyticus, V. cincinnatiensis, V. metschnikovii and V. cholerae O serogroup samples could be discriminated by the SIMCA model of V. parahaemolyticus with palladium electrode 1 Hz frequency segment; V. mimicus and V. vulnincus samples could be discriminated by the SIMCA model of V. parahaemolyticus with tungsten electrode 100 Hz frequency segment; V. carcariae and V. cholerae non-O serogroup samples could be discriminated with the SIMCA model of V. parahaemolyticus in silver electrode 100 Hz frequency segment. The accurate discrimination of ten species of Vibrio samples is 100%. The Smartongue combined with SIMCA can discriminate V. parahaemolyticus with other pathogenic Vibrio effectively. It has a promising future as a new rapid detection method for V. parahaemolyticus.

HPLC fingerprint analysis combined with chemometrics for pattern recognition of ginger.

Science.gov (United States)

Feng, Xu; Kong, Weijun; Wei, Jianhe; Ou-Yang, Zhen; Yang, Meihua

2014-03-01

Ginger, the fresh rhizome of Zingiber officinale Rosc. (Zingiberaceae), has been used worldwide; however, for a long time, there has been no standard approbated internationally for its quality control. To establish an efficacious and combinational method and pattern recognition technique for quality control of ginger. A simple, accurate and reliable method based on high-performance liquid chromatography with photodiode array (HPLC-PDA) detection was developed for establishing the chemical fingerprints of 10 batches of ginger from different markets in China. The method was validated in terms of precision, reproducibility and stability; and the relative standard deviations were all less than 1.57%. On the basis of this method, the fingerprints of 10 batches of ginger samples were obtained, which showed 16 common peaks. Coupled with similarity evaluation software, the similarities between each fingerprint of the sample and the simulative mean chromatogram were in the range of 0.998-1.000. Then, the chemometric techniques, including similarity analysis, hierarchical clustering analysis and principal component analysis were applied to classify the ginger samples. Consistent results were obtained to show that ginger samples could be successfully classified into two groups. This study revealed that HPLC-PDA method was simple, sensitive and reliable for fingerprint analysis, and moreover, for pattern recognition and quality control of ginger.

Advanced multivariate data evaluation for Fourier transform infrared spectroscopy

International Nuclear Information System (INIS)

Diewok, J.

2002-12-01

The objective of the presented dissertation was the evaluation, application and further development of advanced multivariate data evaluation methods for qualitative and quantitative Fourier transform infrared (FT-IR) measurements, especially of aqueous samples. The focus was set on 'evolving systems'; i.e. chemical systems that change gradually with a master variable, such as pH, reaction time, elution time, etc. and that are increasingly encountered in analytical chemistry. FT-IR measurements on such systems yield 2-way and 3-way data sets, i.e. data matrices and cubes. The chemometric methods used were soft-modeling techniques, like multivariate curve resolution - alternating least squares (MCR-ALS) or principal component analysis (PCA), hard modeling of equilibrium systems and two-dimensional correlation spectroscopy (2D-CoS). The research results are presented in six publications and comprise: A new combination of FT-IR flow titrations and second-order calibration by MCR-ALS for the quantitative analysis of mixture samples of organic acids and sugars. A novel combination of MCR-ALS with a hard-modeled equilibrium constraint for second-order quantitation in pH-modulated samples where analytes and interferences show very similar acid-base behavior. A detailed study in which MCR-ALS and 2D-CoS are directly compared for the first time. From the analysis of simulated and experimental acid-base equilibrium systems, the performance and interpretability of the two methods is evaluated. Investigation of the binding process of vancomycin, an important antibiotic, to a cell wall analogue tripeptide by time-resolved FT-IR spectroscopy and detailed chemometric evaluation. Determination of red wine constituents by liquid chromatography with FT-IR detection and MCR-ALS for resolution of overlapped peaks. Classification of red wine cultivars from FT-IR spectroscopy of phenolic wine extracts with hierarchical clustering and soft independent modeling of class analogy (SIMCA

Near infrared and acoustic chemometrics monitoring of volatile fatty acids and dry matter during co-digestion of manure and maize silage

DEFF Research Database (Denmark)

Lomborg, Carina J.; Holm-Nielsen, Jens Bo; Oleskowicz-Popiel, Piotr

2009-01-01

In this study, two process analytical technologies, near infrared spectroscopy and acoustic chemometrics, were investigated as means of monitoring a maize silage spiked biogas process. A reactor recirculation loop which enables sampling concomitant with on-line near infrared characterisation...... accuracy) and RPD between 2.8 and 3.6 (acceptable precision). A second experiment employed at-line monitoring with both near infrared spectroscopy and acoustic chemometrics. A larger calibration span was obtained for total solids by spiking. Both process analytical modalities were validated with respect...

A chemometric method to identify enzymatic reactions leading to the transition from glycolytic oscillations to waves

Science.gov (United States)

Zimányi, László; Khoroshyy, Petro; Mair, Thomas

2010-06-01

In the present work we demonstrate that FTIR-spectroscopy is a powerful tool for the time resolved and noninvasive measurement of multi-substrate/product interactions in complex metabolic networks as exemplified by the oscillating glycolysis in a yeast extract. Based on a spectral library constructed from the pure glycolytic intermediates, chemometric analysis of the complex spectra allowed us the identification of many of these intermediates. Singular value decomposition and multiple level wavelet decomposition were used to separate drifting substances from oscillating ones. This enabled us to identify slow and fast variables of glycolytic oscillations. Most importantly, we can attribute a qualitative change in the positive feedback regulation of the autocatalytic reaction to the transition from homogeneous oscillations to travelling waves. During the oscillatory phase the enzyme phosphofructokinase is mainly activated by its own product ADP, whereas the transition to waves is accompanied with a shift of the positive feedback from ADP to AMP. This indicates that the overall energetic state of the yeast extract determines the transition between spatially homogeneous oscillations and travelling waves.

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.

Application of mass spectrometry based electronic nose and chemometrics for fingerprinting radiation treatment

Science.gov (United States)

Gupta, Sumit; Variyar, Prasad S.; Sharma, Arun

2015-01-01

Volatile compounds were isolated from apples and grapes employing solid phase micro extraction (SPME) and subsequently analyzed by GC/MS equipped with a transfer line without stationary phase. Single peak obtained was integrated to obtain total mass spectrum of the volatile fraction of samples. A data matrix having relative abundance of all mass-to-charge ratios was subjected to principal component analysis (PCA) and linear discriminant analysis (LDA) to identify radiation treatment. PCA results suggested that there is sufficient variability between control and irradiated samples to build classification models based on supervised techniques. LDA successfully aided in segregating control from irradiated samples at all doses (0.1, 0.25, 0.5, 1.0, 1.5, 2.0 kGy). SPME-MS with chemometrics was successfully demonstrated as simple screening method for radiation treatment.

"Turn-off" fluorescent data array sensor based on double quantum dots coupled with chemometrics for highly sensitive and selective detection of multicomponent pesticides.

Science.gov (United States)

Fan, Yao; Liu, Li; Sun, Donglei; Lan, Hanyue; Fu, Haiyan; Yang, Tianming; She, Yuanbin; Ni, Chuang

2016-04-15

As a popular detection model, the fluorescence "turn-off" sensor based on quantum dots (QDs) has already been successfully employed in the detections of many materials, especially in the researches on the interactions between pesticides. However, the previous studies are mainly focused on simple single track or the comparison based on similar concentration of drugs. In this work, a new detection method based on the fluorescence "turn-off" model with water-soluble ZnCdSe and CdSe QDs simultaneously as the fluorescent probes is established to detect various pesticides. The fluorescence of the two QDs can be quenched by different pesticides with varying degrees, which leads to the differences in positions and intensities of two peaks. By combining with chemometrics methods, all the pesticides can be qualitative and quantitative respectively even in real samples with the limit of detection was 2 × 10(-8) mol L(-1) and a recognition rate of 100%. This work is, to the best of our knowledge, the first report on the detection of pesticides based on the fluorescence quenching phenomenon of double quantum dots combined with chemometrics methods. What's more, the excellent selectivity of the system has been verified in different mediums such as mixed ion disruption, waste water, tea and water extraction liquid drugs. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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.

Geographical traceability of Marsdenia tenacissima by Fourier transform infrared spectroscopy and chemometrics

Science.gov (United States)

Li, Chao; Yang, Sheng-Chao; Guo, Qiao-Sheng; Zheng, Kai-Yan; Wang, Ping-Li; Meng, Zhen-Gui

2016-01-01

A combination of Fourier transform infrared spectroscopy with chemometrics tools provided an approach for studying Marsdenia tenacissima according to its geographical origin. A total of 128 M. tenacissima samples from four provinces in China were analyzed with FTIR spectroscopy. Six pattern recognition methods were used to construct the discrimination models: support vector machine-genetic algorithms, support vector machine-particle swarm optimization, K-nearest neighbors, radial basis function neural network, random forest and support vector machine-grid search. Experimental results showed that K-nearest neighbors was superior to other mathematical algorithms after data were preprocessed with wavelet de-noising, with a discrimination rate of 100% in both the training and prediction sets. This study demonstrated that FTIR spectroscopy coupled with K-nearest neighbors could be successfully applied to determine the geographical origins of M. tenacissima samples, thereby providing reliable authentication in a rapid, cheap and noninvasive way.

Descriptive and predictive assessment of enzyme activity and enzyme related processes in biorefinery using IR spectroscopy and chemometrics

DEFF Research Database (Denmark)

Baum, Andreas

the understanding of the structural properties of the extracted pectin. Secondly, enzyme kinetics of biomass converting enzymes was examined in terms of measuring enzyme activity by spectral evolution profiling utilizing FTIR. Chemometric multiway methods were used to analyze the tensor datasets enabling the second......-order calibration advantage (reference Theory of Analytical chemistry). As PAPER 3 illustrates the method is universally applicable without the need of any external standards and was exemplified by performing quantitative enzyme activity determinations for glucose oxidase, pectin lyase and a cellolytic enzyme blend...... (Celluclast 1.5L). In PAPER 4, the concept is extended to quantify enzyme activity of two simultaneously acting enzymes, namely pectin lyase and pectin methyl esterase. By doing so the multiway methods PARAFAC, TUCKER3 and NPLS were compared and evaluated towards accuracy and precision....

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.

Enhanced Sensitivity to Detection Nanomolar Level of Cu2 + Compared to Spectrophotometry Method by Functionalized Gold Nanoparticles: Design of Sensor Assisted by Exploiting First-order Data with Chemometrics

Science.gov (United States)

Rasouli, Zolaikha; Ghavami, Raouf

2018-02-01

A simple, sensitive and efficient colorimetric assay platform for the determination of Cu2 + was proposed with the aim of developing sensitive detection based on the aggregation of AuNPs in presence of a histamine H2-receptor antagonist (famotidine, FAM) as recognition site. This study is the first to demonstrate that the molar extinction coefficients of the complexes formed by FAM and Cu2 + are very low (by analyzing the chemometrics methods on the first order data arising from different metal to ligand ratio method), leading to the undesirable sensitivity of FAM-based assays. To resolve the problem of low sensitivity, the colorimetry method based on the Cu2 +-induced aggregation of AuNPs functionalized with FAM was introduced. This procedure is accompanied by a color change from bright red to blue which can be observed with the naked eyes. Detection sensitivity obtained by the developed method increased about 100 fold compared with the spectrophotometry method. This sensor exhibited a good linear relation between the absorbance ratios at 670 to 520 nm (A670/520) and the concentration in the range 2-110 nM with LOD = 0.76 nM. The satisfactory analytical performance of the proposed sensor facilitates the development of simple and affordable UV-Vis chemosensors for environmental applications.

Process monitored spectrophotometric titration coupled with chemometrics for simultaneous determination of mixtures of weak acids.

Science.gov (United States)

Liao, Lifu; Yang, Jing; Yuan, Jintao

2007-05-15

A new spectrophotometric titration method coupled with chemometrics for the simultaneous determination of mixtures of weak acids has been developed. In this method, the titrant is a mixture of sodium hydroxide and an acid-base indicator, and the indicator is used to monitor the titration process. In a process of titration, both the added volume of titrant and the solution acidity at each titration point can be obtained simultaneously from an absorption spectrum by least square algorithm, and then the concentration of each component in the mixture can be obtained from the titration curves by principal component regression. The method only needs the information of absorbance spectra to obtain the analytical results, and is free of volumetric measurements. The analyses are independent of titration end point and do not need the accurate values of dissociation constants of the indicator and the acids. The method has been applied to the simultaneous determination of the mixtures of benzoic acid and salicylic acid, and the mixtures of phenol, o-chlorophenol and p-chlorophenol with satisfactory results.

A framework for sequential multiblock component methods

NARCIS (Netherlands)

Smilde, A.K.; Westerhuis, J.A.; Jong, S.de

2003-01-01

Multiblock or multiset methods are starting to be used in chemistry and biology to study complex data sets. In chemometrics, sequential multiblock methods are popular; that is, methods that calculate one component at a time and use deflation for finding the next component. In this paper a framework

Application of Raman spectroscopy and chemometric techniques to assess sensory characteristics of young dairy bull beef.

Science.gov (United States)

Zhao, Ming; Nian, Yingqun; Allen, Paul; Downey, Gerard; Kerry, Joseph P; O'Donnell, Colm P

2018-05-01

This work aims to develop a rapid analytical technique to predict beef sensory attributes using Raman spectroscopy (RS) and to investigate correlations between sensory attributes using chemometric analysis. Beef samples (n = 72) were obtained from young dairy bulls (Holstein-Friesian and Jersey×Holstein-Friesian) slaughtered at 15 and 19 months old. Trained sensory panel evaluation and Raman spectral data acquisition were both carried out on the same longissimus thoracis muscles after ageing for 21 days. The best prediction results were obtained using a Raman frequency range of 1300-2800 cm -1 . Prediction performance of partial least squares regression (PLSR) models developed using all samples were moderate to high for all sensory attributes (R 2 CV values of 0.50-0.84 and RMSECV values of 1.31-9.07) and were particularly high for desirable flavour attributes (R 2 CVs of 0.80-0.84, RMSECVs of 4.21-4.65). For PLSR models developed on subsets of beef samples i.e. beef of an identical age or breed type, significant improvements on prediction performances were achieved for overall sensory attributes (R 2 CVs of 0.63-0.89 and RMSECVs of 0.38-6.88 for each breed type; R 2 CVs of 0.52-0.89 and RMSECVs of 0.96-6.36 for each age group). Chemometric analysis revealed strong correlations between sensory attributes. Raman spectroscopy combined with chemometric analysis was demonstrated to have high potential as a rapid and non-destructive technique to predict the sensory quality traits of young dairy bull beef. Copyright © 2018. Published by Elsevier Ltd.

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…

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......, 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...... formation of fungi. For P. roqueforti, P. discolor, P. verrucosum and Aspergillus versicolor the substrate was less suitable as a model cheese substrate, which indicates great variation in nutritional demands of the fungi. Substrates suitable for studies of specific cheese types was found for P. roqueforti...

In-line and Real-time Monitoring of Resonant Acoustic Mixing by Near-infrared Spectroscopy Combined with Chemometric Technology for Process Analytical Technology Applications in Pharmaceutical Powder Blending Systems.

Science.gov (United States)

Tanaka, Ryoma; Takahashi, Naoyuki; Nakamura, Yasuaki; Hattori, Yusuke; Ashizawa, Kazuhide; Otsuka, Makoto

2017-01-01

Resonant acoustic ® mixing (RAM) technology is a system that performs high-speed mixing by vibration through the control of acceleration and frequency. In recent years, real-time process monitoring and prediction has become of increasing interest, and process analytical technology (PAT) systems will be increasingly introduced into actual manufacturing processes. This study examined the application of PAT with the combination of RAM, near-infrared spectroscopy, and chemometric technology as a set of PAT tools for introduction into actual pharmaceutical powder blending processes. Content uniformity was based on a robust partial least squares regression (PLSR) model constructed to manage the RAM configuration parameters and the changing concentration of the components. As a result, real-time monitoring may be possible and could be successfully demonstrated for in-line real-time prediction of active pharmaceutical ingredients and other additives using chemometric technology. This system is expected to be applicable to the RAM method for the risk management of quality.

Modelling of Hydrophilic Interaction Liquid Chromatography Stationary Phases Using Chemometric Approaches

Science.gov (United States)

Ortiz-Villanueva, Elena; Tauler, Romà

2017-01-01

Metabolomics is a powerful and widely used approach that aims to screen endogenous small molecules (metabolites) of different families present in biological samples. The large variety of compounds to be determined and their wide diversity of physical and chemical properties have promoted the development of different types of hydrophilic interaction liquid chromatography (HILIC) stationary phases. However, the selection of the most suitable HILIC stationary phase is not straightforward. In this work, four different HILIC stationary phases have been compared to evaluate their potential application for the analysis of a complex mixture of metabolites, a situation similar to that found in non-targeted metabolomics studies. The obtained chromatographic data were analyzed by different chemometric methods to explore the behavior of the considered stationary phases. ANOVA-simultaneous component analysis (ASCA), principal component analysis (PCA) and partial least squares regression (PLS) were used to explore the experimental factors affecting the stationary phase performance, the main similarities and differences among chromatographic conditions used (stationary phase and pH) and the molecular descriptors most useful to understand the behavior of each stationary phase. PMID:29064436

Traceability of Boletaceae mushrooms using data fusion of UV-visible and FTIR combined with chemometrics methods.

Science.gov (United States)

Yao, Sen; Li, Tao; Liu, HongGao; Li, JieQing; Wang, YuanZhong

2018-04-01

Boletaceae mushrooms are wild-grown edible mushrooms that have high nutrition, delicious flavor and large economic value distributing in Yunnan Province, China. Traceability is important for the authentication and quality assessment of Boletaceae mushrooms. In this study, UV-visible and Fourier transform infrared (FTIR) spectroscopies were applied for traceability of 247 Boletaceae mushroom samples in combination with chemometrics. Compared with a single spectroscopy technique, data fusion strategy can obviously improve the classification performance in partial least square discriminant analysis (PLS-DA) and grid-search support vector machine (GS-SVM) models, for both species and geographical origin traceability. In addition, PLS-DA and GS-SVM models can provide 100.00% accuracy for species traceability and have reliable evaluation parameters. For geographical origin traceability, the accuracy of prediction in the PLS-DA model by data fusion was just 64.63%, but the GS-SVM model based on data fusion was 100.00%. The results demonstrated that the data fusion strategy of UV-visible and FTIR combined with GS-SVM could provide a higher synergic effect for traceability of Boletaceae mushrooms and have a good generalization ability for the comprehensive quality control and evaluation of similar foods. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Reconhecimento de padrões por métodos não supervisionados: explorando procedimentos quimiométricos para tratamento de dados analíticos Non-supervised pattern recognition methods: exploring chemometrical procedures for evaluating analytical data

Directory of Open Access Journals (Sweden)

Paulo R. M. Correia

2007-04-01

Full Text Available An activity for introducing hierarchical cluster analysis (HCA and principal component analysis (PCA during the Instrumental Analytical Chemistry course is presented. The posed problem involves the discrimination of mineral water samples according to their geographical origin. Thirty-seven samples of 9 different brands were considered and the results from the determination of Na, K, Mg, Ca, Sr and Ba were taken into account. Non-supervised methods for pattern recognition were explored to construct a dendrogram, score and loading plots. The devised activity can be adopted for introducing Chemometrics devoted to data handling, stressing its importance in the context of modern Analytical Chemistry.

“Turn-off” fluorescent data array sensor based on double quantum dots coupled with chemometrics for highly sensitive and selective detection of multicomponent pesticides

Energy Technology Data Exchange (ETDEWEB)

Fan, Yao; Liu, Li; Sun, Donglei; Lan, Hanyue [The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, College of Pharmacy, South-Central University for Nationalities, Wuhan 430074 (China); Fu, Haiyan, E-mail: fuhaiyan@mail.scuec.edu.cn [The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, College of Pharmacy, South-Central University for Nationalities, Wuhan 430074 (China); Yang, Tianming, E-mail: tmyang@mail.scuec.edu.cn [The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, College of Pharmacy, South-Central University for Nationalities, Wuhan 430074 (China); She, Yuanbin, E-mail: sheyb@zjut.edu.cn [State Key Laboratory Breeding Base of Green Chemistry-Synthesis Technology, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310032 (China); Ni, Chuang [The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, College of Pharmacy, South-Central University for Nationalities, Wuhan 430074 (China)

2016-04-15

As a popular detection model, the fluorescence “turn-off” sensor based on quantum dots (QDs) has already been successfully employed in the detections of many materials, especially in the researches on the interactions between pesticides. However, the previous studies are mainly focused on simple single track or the comparison based on similar concentration of drugs. In this work, a new detection method based on the fluorescence “turn-off” model with water-soluble ZnCdSe and CdSe QDs simultaneously as the fluorescent probes is established to detect various pesticides. The fluorescence of the two QDs can be quenched by different pesticides with varying degrees, which leads to the differences in positions and intensities of two peaks. By combining with chemometrics methods, all the pesticides can be qualitative and quantitative respectively even in real samples with the limit of detection was 2 × 10{sup −8} mol L{sup −1} and a recognition rate of 100%. This work is, to the best of our knowledge, the first report on the detection of pesticides based on the fluorescence quenching phenomenon of double quantum dots combined with chemometrics methods. What's more, the excellent selectivity of the system has been verified in different mediums such as mixed ion disruption, waste water, tea and water extraction liquid drugs. - Highlights: • A new model based on double QDs is established for pesticide residues detection. • The fluorescent data array sensor is coupled with chmometrics methods. • The sensor can be highly sensitive and selective detection in actual samples.

“Turn-off” fluorescent data array sensor based on double quantum dots coupled with chemometrics for highly sensitive and selective detection of multicomponent pesticides

International Nuclear Information System (INIS)

Fan, Yao; Liu, Li; Sun, Donglei; Lan, Hanyue; Fu, Haiyan; Yang, Tianming; She, Yuanbin; Ni, Chuang

2016-01-01

As a popular detection model, the fluorescence “turn-off” sensor based on quantum dots (QDs) has already been successfully employed in the detections of many materials, especially in the researches on the interactions between pesticides. However, the previous studies are mainly focused on simple single track or the comparison based on similar concentration of drugs. In this work, a new detection method based on the fluorescence “turn-off” model with water-soluble ZnCdSe and CdSe QDs simultaneously as the fluorescent probes is established to detect various pesticides. The fluorescence of the two QDs can be quenched by different pesticides with varying degrees, which leads to the differences in positions and intensities of two peaks. By combining with chemometrics methods, all the pesticides can be qualitative and quantitative respectively even in real samples with the limit of detection was 2 × 10"−"8 mol L"−"1 and a recognition rate of 100%. This work is, to the best of our knowledge, the first report on the detection of pesticides based on the fluorescence quenching phenomenon of double quantum dots combined with chemometrics methods. What's more, the excellent selectivity of the system has been verified in different mediums such as mixed ion disruption, waste water, tea and water extraction liquid drugs. - Highlights: • A new model based on double QDs is established for pesticide residues detection. • The fluorescent data array sensor is coupled with chmometrics methods. • The sensor can be highly sensitive and selective detection in actual samples.

Microwave-assisted of dispersive liquid-liquid microextraction and spectrophotometric determination of uranium after optimization based on Box-Behnken design and chemometrics methods

Science.gov (United States)

Niazi, Ali; Khorshidi, Neda; Ghaemmaghami, Pegah

2015-01-01

In this study an analytical procedure based on microwave-assisted dispersive liquid-liquid microextraction (MA-DLLME) and spectrophotometric coupled with chemometrics methods is proposed to determine uranium. In the proposed method, 4-(2-pyridylazo) resorcinol (PAR) is used as a chelating agent, and chloroform and ethanol are selected as extraction and dispersive solvent. The optimization strategy is carried out by using two level full factorial designs. Results of the two level full factorial design (24) based on an analysis of variance demonstrated that the pH, concentration of PAR, amount of dispersive and extraction solvents are statistically significant. Optimal condition for three variables: pH, concentration of PAR, amount of dispersive and extraction solvents are obtained by using Box-Behnken design. Under the optimum conditions, the calibration graphs are linear in the range of 20.0-350.0 ng mL-1 with detection limit of 6.7 ng mL-1 (3δB/slope) and the enrichment factor of this method for uranium reached at 135. The relative standard deviation (R.S.D.) is 1.64% (n = 7, c = 50 ng mL-1). The partial least squares (PLS) modeling was used for multivariate calibration of the spectrophotometric data. The orthogonal signal correction (OSC) was used for preprocessing of data matrices and the prediction results of model, with and without using OSC, were statistically compared. MA-DLLME-OSC-PLS method was presented for the first time in this study. The root mean squares error of prediction (RMSEP) for uranium determination using PLS and OSC-PLS models were 4.63 and 0.98, respectively. This procedure allows the determination of uranium synthesis and real samples such as waste water with good reliability of the determination.

Microwave-assisted of dispersive liquid-liquid microextraction and spectrophotometric determination of uranium after optimization based on Box-Behnken design and chemometrics methods.

Science.gov (United States)

Niazi, Ali; Khorshidi, Neda; Ghaemmaghami, Pegah

2015-01-25

In this study an analytical procedure based on microwave-assisted dispersive liquid-liquid microextraction (MA-DLLME) and spectrophotometric coupled with chemometrics methods is proposed to determine uranium. In the proposed method, 4-(2-pyridylazo) resorcinol (PAR) is used as a chelating agent, and chloroform and ethanol are selected as extraction and dispersive solvent. The optimization strategy is carried out by using two level full factorial designs. Results of the two level full factorial design (2(4)) based on an analysis of variance demonstrated that the pH, concentration of PAR, amount of dispersive and extraction solvents are statistically significant. Optimal condition for three variables: pH, concentration of PAR, amount of dispersive and extraction solvents are obtained by using Box-Behnken design. Under the optimum conditions, the calibration graphs are linear in the range of 20.0-350.0 ng mL(-1) with detection limit of 6.7 ng mL(-1) (3δB/slope) and the enrichment factor of this method for uranium reached at 135. The relative standard deviation (R.S.D.) is 1.64% (n=7, c=50 ng mL(-1)). The partial least squares (PLS) modeling was used for multivariate calibration of the spectrophotometric data. The orthogonal signal correction (OSC) was used for preprocessing of data matrices and the prediction results of model, with and without using OSC, were statistically compared. MA-DLLME-OSC-PLS method was presented for the first time in this study. The root mean squares error of prediction (RMSEP) for uranium determination using PLS and OSC-PLS models were 4.63 and 0.98, respectively. This procedure allows the determination of uranium synthesis and real samples such as waste water with good reliability of the determination. Copyright © 2014. Published by Elsevier B.V.

Association and discrimination of diesel fuels using chemometric procedures.

Science.gov (United States)

Marshall, Lucas J; McIlroy, John W; McGuffin, Victoria L; Waddell Smith, Ruth

2009-08-01

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.

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)

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

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.

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.

Spectrophotometric and spectrofluorimetric investigation of different equilibria of a recently synthesized Schiff base with the aid of chemometric methods

Energy Technology Data Exchange (ETDEWEB)

Afkhami, Abbas, E-mail: afkhami@basu.ac.i [Faculty of Chemistry, Bu-Ali Sina University, Hamedan 65174 (Iran, Islamic Republic of); Keypour, Hasan; Khajavi, Farzad [Faculty of Chemistry, Bu-Ali Sina University, Hamedan 65174 (Iran, Islamic Republic of); Rezaeivala, Majid [Department of Chemical Engineering, Hamedan University of Technology, Hamedan 65155 (Iran, Islamic Republic of)

2011-07-15

In this study ground and excited states acidic dissociation constants of a recently synthesized Schiff base was obtained in a DMF:water mixture of 30:70 (v/v) using absorption and fluorescent spectra of the Schiff base in different pH values with the aid of chemometric methods. In addition, the fluorescent of the two kinds of tautomers of this Schiff base was investigated and the rate of tautomerization was obtained using rank annihilation factor analysis (RAFA). The effect of different kinds of surfactants such as sodium dodecyl sulfate (SDS), cetyltrimethylammonium bromide (CTAB) and Triton X-100 on fluorescence spectrum of the Schiff base in a DMF:water mixture of 2:98 (v/v) was investigated. CTAB increased the fluorescence intensity of the Schiff base while SDS and Triton X-100 had no significant effect on it. {beta}-Cyclodextrin increased the fluorescence intensity of the Schiff base. Also the sensing behavior of this Schiff base toward metal ions was studied in DMF and ethanol by fluorescence spectroscopy. The Schiff base showed prominent fluorescent signal in the presence of Zn{sup 2+}, whereas other metal ions failed to induce response and ground-state dissociation constant of the complex was determined by direct fluorimetric titration as a function of Zn{sup 2+} concentration. - Highlights: {yields} Acidity and rate of the tautomerization of a recently synthesized Schiff base were studied. {yields} Ground and excited states acidity constants and tautomerization rate constant were obtained. {yields} These parameters were obtained with the aid of hard model and Rank annihilation factor analysis. {yields} The effect of some factors on the fluorescence intensity of the Schiff base was studied.

Spectrophotometric and spectrofluorimetric investigation of different equilibria of a recently synthesized Schiff base with the aid of chemometric methods

International Nuclear Information System (INIS)

Afkhami, Abbas; Keypour, Hasan; Khajavi, Farzad; Rezaeivala, Majid

2011-01-01

In this study ground and excited states acidic dissociation constants of a recently synthesized Schiff base was obtained in a DMF:water mixture of 30:70 (v/v) using absorption and fluorescent spectra of the Schiff base in different pH values with the aid of chemometric methods. In addition, the fluorescent of the two kinds of tautomers of this Schiff base was investigated and the rate of tautomerization was obtained using rank annihilation factor analysis (RAFA). The effect of different kinds of surfactants such as sodium dodecyl sulfate (SDS), cetyltrimethylammonium bromide (CTAB) and Triton X-100 on fluorescence spectrum of the Schiff base in a DMF:water mixture of 2:98 (v/v) was investigated. CTAB increased the fluorescence intensity of the Schiff base while SDS and Triton X-100 had no significant effect on it. β-Cyclodextrin increased the fluorescence intensity of the Schiff base. Also the sensing behavior of this Schiff base toward metal ions was studied in DMF and ethanol by fluorescence spectroscopy. The Schiff base showed prominent fluorescent signal in the presence of Zn 2+ , whereas other metal ions failed to induce response and ground-state dissociation constant of the complex was determined by direct fluorimetric titration as a function of Zn 2+ concentration. - Highlights: → Acidity and rate of the tautomerization of a recently synthesized Schiff base were studied. → Ground and excited states acidity constants and tautomerization rate constant were obtained. → These parameters were obtained with the aid of hard model and Rank annihilation factor analysis. → The effect of some factors on the fluorescence intensity of the Schiff base was studied.

Quality evaluation of moluodan concentrated pill using high-performance liquid chromatography fingerprinting coupled with chemometrics.

Science.gov (United States)

Tao, Lingyan; Zhang, Qing; Wu, Yongjiang; Liu, Xuesong

2016-12-01

In this study, a fast and effective high-performance liquid chromatography method was developed to obtain a fingerprint chromatogram and quantitative analysis simultaneously of four indexes including gallic acid, chlorogenic acid, albiflorin and paeoniflorin of the traditional Chinese medicine Moluodan Concentrated Pill. The method was performed by using a Waters X-bridge C 18 reversed phase column on an Agilent 1200S high-performance liquid chromatography system coupled with diode array detection. The mobile phase of the high-performance liquid chromatography method was composed of 20 mmol/L phosphate solution and acetonitrile with a 1 mL/min eluent velocity, under a detection temperature of 30°C and a UV detection wavelength of 254 nm. After the methodology validation, 16 batches of Moluodan Concentrated Pill were analyzed by this high-performance liquid chromatography method and both qualitative and quantitative evaluation results were achieved by similarity analysis, principal component analysis and hierarchical cluster analysis. The results of these three chemometrics were in good agreement and all indicated that batch 10 and batch 16 showed significant differences with the other 14 batches. This suggested that the developed high-performance liquid chromatography method could be applied in the quality evaluation of Moluodan Concentrated Pill. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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...... resolved by chemometrics which enabled simultaneous determination of both the copper and the zinc concentrations, thereby eliminating the conventional necessary pretreatment of the sample solution, such as initial addition of Ga(III) or solvent extraction of copper. The brass samples were diluted...... 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....

Prediction of physicochemical properties of FCC feedstock by Chemometric analysis of their ultraviolet spectrum

International Nuclear Information System (INIS)

Baldrich Ferrer, Carlos A

2008-01-01

Chemometric analysis by Partial Least Squares (PLS) has been applied in this work to correlate the ultraviolet spectrum of combined Fluid Catalytic Cracking (FCC) feedstock with their physicochemical properties. The prediction errors obtained in the validation process using refinery samples demonstrate the accuracy of the predicted properties. This new analytical methodology allows obtaining in one analysis detailed information about the most important physicochemical properties of FCC feedstock and could be used as a valuable tool for operational analysis

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.

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.

Identification of Three Kinds of Citri Reticulatae Pericarpium Based on Deoxyribonucleic Acid Barcoding and High-performance Liquid Chromatography-diode Array Detection-electrospray Ionization/Mass Spectrometry/Mass Spectrometry Combined with Chemometric Analysis

Science.gov (United States)

Yu, Xiaoxue; Zhang, Yafeng; Wang, Dongmei; Jiang, Lin; Xu, Xinjun

2018-01-01

Background: Citri Reticulatae Pericarpium is the dried mature pericarp of Citrus reticulata Blanco which can be divided into “Chenpi” and “Guangchenpi.” “Guangchenpi” is the genuine Chinese medicinal material in Xinhui, Guangdong province; based on the greatest quality and least amount, it is most expensive among others. Hesperidin is used as the marker to identify Citri Reticulatae Pericarpium described in the Chinese Pharmacopoeia 2010. However, both “Chenpi” and “Guangchenpi” contain hesperidin so that it is impossible to differentiate them by measuring hesperidin. Objective: Our study aims to develop an efficient and accurate method to separate and identify “Guangchenpi” from other Citri Reticulatae Pericarpium. Materials and Methods: The genomic deoxyribonucleic acid (DNA) of all the materials was extracted and then the internal transcribed spacer 2 was amplified, sequenced, aligned, and analyzed. The secondary structures were created in terms of the database and website established by Jörg Schultz et al. High-performance liquid chromatography-diode array detection-electrospray Ionization/mass spectrometry (HPLC-DAD-ESI-MS)/MS coupled with chemometric analysis was applied to compare the differences in chemical profiles of the three kinds of Citri Reticulatae Pericarpium. Results: A total of 22 samples were classified into three groups. The results of DNA barcoding were in accordance with principal component analysis and hierarchical cluster analysis. Eight compounds were deduced from HPLC-DAD-ESI-MS/MS. Conclusions: This method is a reliable and effective tool to differentiate the three Citri Reticulatae Pericarpium. SUMMARY The internal transcribed spacer 2 regions and the secondary structure among three kinds of Citri Reticulatae Pericarpium varied considerablyAll the 22 samples were analyzed by high-performance liquid chromatography (HPLC) to obtain the chemical profilesPrincipal component analysis and hierarchical cluster analysis

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

Near infrared spectroscopy combined with chemometrics for growth stage classification of cannabis cultivated in a greenhouse from seized seeds

Science.gov (United States)

Borille, Bruna Tassi; Marcelo, Marcelo Caetano Alexandre; Ortiz, Rafael Scorsatto; Mariotti, Kristiane de Cássia; Ferrão, Marco Flôres; Limberger, Renata Pereira

2017-02-01

Cannabis sativa L. (cannabis, Cannabaceae), popularly called marijuana, is one of the oldest plants known to man and it is the illicit drug most used worldwide. It also has been the subject of increasing discussions from the scientific and political points of view due to its medicinal properties. In recent years in Brazil, the form of cannabis drug trafficking has been changing and the Brazilian Federal Police has exponentially increased the number of seizures of cannabis seeds sent by the mail. This new form of trafficking encouraged the study of cannabis seeds seized germinated in a greenhouse through NIR spectroscopy combined with chemometrics. The plants were cultivated in a homemade greenhouse under controlled conditions. In three different growth periods (5.5 weeks, 7.5 weeks and 10 weeks), they were harvested, dried, ground and directly analyzed. The iPCA was used to select the best NIR spectral range (4000-4375 cm- 1) in order to develop unsupervised and supervised methods. The PCA and HCA showed a good separation between the three groups of cannabis samples at different growth stages. The PLS-DA and SVM-DA classified the samples with good results in terms of sensitivity and specificity. The sensitivity and specificity for SVM-DA classification were equal to unity. This separation may be due to the correlation of cannabinoids and volatile compounds concentration during the growth of the cannabis plant. Therefore, the growth stage of cannabis can be predicted by NIR spectroscopy and chemometric tools in the early stages of indoor cannabis cultivation.

Detection of regulated herbs and plants in plant food supplements and traditional medicines using infrared spectroscopy.

Science.gov (United States)

Deconinck, E; Djiogo, C A Sokeng; Bothy, J L; Courselle, P

2017-08-05

The identification of a specific toxic or regulated plant in herbal preparations or plant food supplements is a real challenge, since they are often powdered, mixed with other herbal or synthetic powders and compressed into tablets or capsules. The classical identification approaches based on micro- and macroscopy are therefore not possible anymore. In this paper infrared spectroscopy, combined with attenuated total reflectance was evaluated for the screening of plant based preparations for nine specific plants (five regulated and four common plants for herbal supplements). IR and NIR spectra were recorded for a series of self-made triturations of the targeted plants. After pretreatment of the spectral data chemometric classification techniques were applied to both data sets (IR and NIR) separately and the combination of both. The results show that the screening of herbal preparations or plant food supplements for specific plants, using infrared spectroscopy, is feasible. The best model was obtained with the Mid-IR data, using SIMCA as modelling technique. During validation of the model, using an external test set, 21 of 25 were correctly classified and six of the nine targeted plants showed no misclassifications for the selected test set. For the other three a success rate of 50% was obtained. Mid-IR combined with SIMCA can therefore be applied as a first step in the screening of unknown samples, before applying more sophisticated fingerprint approaches or identification tests described in several national and international pharmacopoeia. As a proof of concept five real suspicious samples were successfully screened for the targeted regulated plants. Copyright © 2017 Elsevier B.V. All rights reserved.

Discrimination of Clover and Citrus Honeys from Egypt According to Floral Type Using Easily Assessable Physicochemical Parameters and Discriminant Analysis: An External Validation of the Chemometric Approach

Directory of Open Access Journals (Sweden)

Ioannis K. Karabagias

2018-05-01

Full Text Available Twenty-two honey samples, namely clover and citrus honeys, were collected from the greater Cairo area during the harvesting year 2014–2015. The main purpose of the present study was to characterize the aforementioned honey types and to investigate whether the use of easily assessable physicochemical parameters, including color attributes in combination with chemometrics, could differentiate honey floral origin. Parameters taken into account were: pH, electrical conductivity, ash, free acidity, lactonic acidity, total acidity, moisture content, total sugars (degrees Brix-°Bx, total dissolved solids and their ratio to total acidity, salinity, CIELAB color parameters, along with browning index values. Results showed that all honey samples analyzed met the European quality standards set for honey and had variations in the aforementioned physicochemical parameters depending on floral origin. Application of linear discriminant analysis showed that eight physicochemical parameters, including color, could classify Egyptian honeys according to floral origin (p < 0.05. Correct classification rate was 95.5% using the original method and 90.9% using the cross validation method. The discriminatory ability of the developed model was further validated using unknown honey samples. The overall correct classification rate was not affected. Specific physicochemical parameter analysis in combination with chemometrics has the potential to enhance the differences in floral honeys produced in a given geographical zone.

PARAFAC: uma ferramenta quimiométrica para tratamento de dados multidimensionais. Aplicações na determinação direta de fármacos em plasma humano por espectrofluorimetria PARAFAC: a chemometric tool for multi-dimensional data treatment. Applications in direct determination of drugs in human plasma by spectrofluorimetry

Directory of Open Access Journals (Sweden)

Marcelo M. Sena

2005-10-01

Full Text Available Since the last decade, the combined use of chemometrics and molecular spectroscopic techniques has become a new alternative for direct drug determination, without the need of physical separation. Among the new methodologies developed, the application of PARAFAC in the decomposition of spectrofluorimetric data should be highlighted. The first objective of this article is to describe the theoretical basis of PARAFAC. For this purpose, a discussion about the order of chemometric methods used in multivariate calibration and the development of multi-dimensional methods is presented first. The other objective of this article is to divulge for the Brazilian chemical community the potential of the combination PARAFAC/spectrofluorimetry for the determination of drugs in complex biological matrices. For this purpose, two applications aiming at determining, respectively, doxorrubicine and salicylate in human plasma are presented.

Source identification of petroleum hydrocarbons in soil and sediments from Iguaçu River Watershed, Paraná, Brazil using the CHEMSIC method (CHEMometric analysis of Selected Ion Chromatograms).

Science.gov (United States)

Gallotta, Fabiana D C; Christensen, Jan H

2012-04-27

A chemometric method based on principal component analysis (PCA) of pre-processed and combined sections of selected ion chromatograms (SICs) is used to characterise the hydrocarbon profiles in soil and sediment from Araucária, Guajuvira, General Lúcio and Balsa Nova Municipalities (Iguaçu River Watershed, Paraná, Brazil) and to indicate the main sources of hydrocarbon pollution. The study includes 38 SICs of polycyclic aromatic compounds (PACs) and four of petroleum biomarkers in two separate analyses. The most contaminated samples are inside the Presidente Getúlio Vargas Refinery area. These samples represent a petrogenic pattern and different weathering degrees. Samples from outside the refinery area are either less or not contaminated, or contain mixtures of diagenetic, pyrogenic and petrogenic inputs where different proportions predominate. The locations farthest away from industrial activity (Balsa Nova) contains the lowest levels of PAC contamination. There are no evidences to conclude positive matches between the samples from outside the refinery area and the Cusiana spilled oil. Copyright © 2012 Elsevier B.V. All rights reserved.

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 G; Pereira, Aline; Tomazzoli, Maíra; Nunes, Eduardo da C; Martins Peruch, Luiz Augusto; Gazzola, Jussara; Costa, Christopher; Rocha, Miguel; Maraschin, Marcelo

2015-12-01

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 (redfleshed) 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.

{sup 1}H qNMR and chemometric analyses of urban wastewater

Energy Technology Data Exchange (ETDEWEB)

Alves Filho, Elenilson G.; Silva, Lorena M. A.; Venâncio, Tiago; Carneiro, Renato L.; Ferreira, Antonio G., E-mail: elenilson.godoy@yahoo.com.br [Universidade Federal de São Carlos (UFSCar), São Carlos, SP (Brazil). Departamento de Química; Sartori, Luci [Serviço Autônomo de Água e Esgoto de São Carlos (SAAE), São Carlos, SP (Brazil)

2015-07-01

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 {sup 1}H 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 ranged with treatment and seasonality. Anomalous discharges and the influence of storm water on the sewage composition were further identified. All the variations indicated that the employed procedure might be useful to enhance the effectiveness of STPs, plan prevention actions for equipment protection and preserve the environment. (author)

Effects of growing location on the production of main active components and antioxidant activity of Dasiphora fruticosa (L.) Rydb. by chemometric methods.

Science.gov (United States)

Liu, Wei; Wang, Dongmei; Hou, Xiaogai; Yang, Yueqin; Xue, Xian; Jia, Qishi; Zhang, Lixia; Zhao, Wei; Yin, Dongxue

2018-05-17

Traditional Chinese medicine (TCM) plays a very important role in the health system of China. The content and activity of active component are main indexes that evaluate the quality of TCM, however they may vary with environmental factors in their growing locations. In this study, effects of environmental factors on the contents of active components and antioxidant activity of Dasiphora fruticosa from the five main production areas of China were investigated. The contents of tannin, total flavonoid and rutin were determined and varied within the range of 7.65-10.69%, 2.30-5.39% and 0.18-0.81%, respectively. Antioxidant activity was determined by DPPH assay, with the DPPH IC 50 values ranged from 8.791 to 32.534μg mL -1 . In order to further explore the cause of these significant geographical variations, the chemometric methods including correlation analysis, principal component analysis, gray correlation analysis, and path analysis were conducted. The results showed environmental factors had significant effect on the active component contents and antioxidant activity. Rapidly available phosphorus (RAP) and rapidly available nitrogen (RAN) were common dominant factors, and a significant positive correlation was observed between RAP and active components and antioxidant activity (Pcomponents and strong antioxidant activity, Bange in Tibet and Geermu in Qinghai Province was selected as a favorable growing location, respectively. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

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.

Application of chemometric analysis based on physicochemical and chromatographic data for the differentiation origin of plant protection products containing chlorpyrifos.

Science.gov (United States)

Miszczyk, Marek; Płonka, Marlena; Bober, Katarzyna; Dołowy, Małgorzata; Pyka, Alina; Pszczolińska, Klaudia

2015-01-01

The aim of this study was to investigate the similarities and dissimilarities between the pesticide samples in form of emulsifiable concentrates (EC) formulation containing chlorpyrifos as active ingredient coming from different sources (i.e., shops and wholesales) and also belonging to various series. The results obtained by the Headspace Gas Chromatography-Mass Spectrometry method and also some selected physicochemical properties of examined pesticides including pH, density, stability, active ingredient and water content in pesticides tested were compared using two chemometric methods. Applicability of simple cluster analysis and also principal component analysis of obtained data in differentiation of examined plant protection products coming from different sources was confirmed. It would be advantageous in the routine control of originality and also in the detection of counterfeit pesticides, respectively, among commercially available pesticides containing chlorpyrifos as an active ingredient.

Rapid Determination of the Geographical Origin of Chinese Red Peppers (Zanthoxylum Bungeanum Maxim.) Based on Sensory Characteristics and Chemometric Techniques.

Science.gov (United States)

Yin, Xiangqian; Xu, Xiaoxue; Zhang, Qiang; Xu, Jianguo

2018-04-24

In this paper, principal component analysis (PCA), linear discriminant analysis (LDAp, artificial neural networks (ANN), and support vector machine (SVM) were applied to discriminate the geographical origin of Chinese red peppers ( Zanthoxylum bungeanum Maxim.). The models based on color, smell and taste may discriminate quickly and effectively the geographical origin of Chinese red peppers from different regions, but the successful identification rates may vary with different kinds of parameters and chemometric methods. Among them, all models based on taste indexes showed an excellent ability to discriminate the geographical origin of Chinese red peppers with correct classifications of 100% for the training set and the 100% for test set. The present study provided a simple, efficient, inexpensive, practical and fast method to discriminate the geographical origin of Chinese red peppers from different regions, which was of great importance for both consumers and producers.

Mapping absolute tissue endogenous fluorophore concentrations with chemometric wide-field fluorescence microscopy

Science.gov (United States)

Xu, Zhang; Reilley, Michael; Li, Run; Xu, Min

2017-06-01

We report chemometric wide-field fluorescence microscopy for imaging the spatial distribution and concentration of endogenous fluorophores in thin tissue sections. Nonnegative factorization aided by spatial diversity is used to learn both the spectral signature and the spatial distribution of endogenous fluorophores from microscopic fluorescence color images obtained under broadband excitation and detection. The absolute concentration map of individual fluorophores is derived by comparing the fluorescence from "pure" fluorophores under the identical imaging condition following the identification of the fluorescence species by its spectral signature. This method is then demonstrated by characterizing the concentration map of endogenous fluorophores (including tryptophan, elastin, nicotinamide adenine dinucleotide, and flavin adenine dinucleotide) for lung tissue specimens. The absolute concentrations of these fluorophores are all found to decrease significantly from normal, perilesional, to cancerous (squamous cell carcinoma) tissue. Discriminating tissue types using the absolute fluorophore concentration is found to be significantly more accurate than that achievable with the relative fluorescence strength. Quantification of fluorophores in terms of the absolute concentration map is also advantageous in eliminating the uncertainties due to system responses or measurement details, yielding more biologically relevant data, and simplifying the assessment of competing imaging approaches.

A chemometric approach to the characterisation of historical mortars

International Nuclear Information System (INIS)

Rampazzi, L.; Pozzi, A.; Sansonetti, A.; Toniolo, L.; Giussani, B.

2006-01-01

The compositional knowledge of historical mortars is of great concern in case of provenance and dating investigations and of conservation works since the nature of the raw materials suggests the most compatible conservation products. The classic characterisation usually goes through various analytical determinations, while conservation laboratories call for simple and quick analyses able to enlighten the nature of mortars, usually in terms of the binder fraction. A chemometric approach to the matter is here undertaken. Specimens of mortars were prepared with calcitic and dolomitic binders and analysed by Atomic Spectroscopy. Principal Components Analysis (PCA) was used to investigate the features of specimens and samples. A Partial Least Square (PLS1) regression was done in order to predict the binder/aggregate ratio. The model was applied to historical mortars from the churches of St. Lorenzo (Milan) and St. Abbondio (Como). The accordance between the predictive model and the real samples is discussed

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 (porigin 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.

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…

[Prediction of Encapsulation Temperatures of Copolymer Films in Photovoltaic Cells Using Hyperspectral Imaging Techniques and Chemometrics].

Science.gov (United States)

Lin, Ping; Chen, Yong-ming; Yao, Zhi-lei

2015-11-01

A novel method of combination of the chemometrics and the hyperspectral imaging techniques was presented to detect the temperatures of Ethylene-Vinyl Acetate copolymer (EVA) films in photovoltaic cells during the thermal encapsulation process. Four varieties of the EVA films which had been heated at the temperatures of 128, 132, 142 and 148 °C during the photovoltaic cells production process were used for investigation in this paper. These copolymer encapsulation films were firstly scanned by the hyperspectral imaging equipment (Spectral Imaging Ltd. Oulu, Finland). The scanning band range of hyperspectral equipemnt was set between 904.58 and 1700.01 nm. The hyperspectral dataset of copolymer films was randomly divided into two parts for the training and test purpose. Each type of the training set and test set contained 90 and 10 instances, respectively. The obtained hyperspectral images of EVA films were dealt with by using the ENVI (Exelis Visual Information Solutions, USA) software. The size of region of interest (ROI) of each obtained hyperspectral image of EVA film was set as 150 x 150 pixels. The average of reflectance hyper spectra of all the pixels in the ROI was used as the characteristic curve to represent the instance. There kinds of chemometrics methods including partial least squares regression (PLSR), multi-class support vector machine (SVM) and large margin nearest neighbor (LMNN) were used to correlate the characteristic hyper spectra with the encapsulation temperatures of of copolymer films. The plot of weighted regression coefficients illustrated that both bands of short- and long-wave near infrared hyperspectral data contributed to enhancing the prediction accuracy of the forecast model. Because the attained reflectance hyperspectral data of EVA materials displayed the strong nonlinearity, the prediction performance of linear modeling method of PLSR declined and the prediction precision only reached to 95%. The kernel-based forecast models were

Study of the aroma formation and transformation during the manufacturing process of oolong tea by solid-phase micro-extraction and gas chromatography-mass spectrometry combined with chemometrics.

Science.gov (United States)

Ma, Chengying; Li, Junxing; Chen, Wei; Wang, Wenwen; Qi, Dandan; Pang, Shi; Miao, Aiqing

2018-06-01

Oolong tea is a typical semi-fermented tea and is famous for its unique aroma. The aim of this study was to compare the volatile compounds during manufacturing process to reveal the formation of aroma. In this paper, a method was developed based on head-space solid phase microextraction/gas chromatography-mass spectrometry (HS-SPME/GC-MS) combined with chemometrics to assess volatile profiles during manufacturing process (fresh leaves, sun-withered leaves, rocked leaves and leaves after de-enzyming). A total of 24 aroma compounds showing significant differences during manufacturing process were identified. Subsequently, according to these aroma compounds, principal component analysis and hierarchical cluster analysis showed that the four samples were clearly distinguished from each other, which suggested that the 24 identified volatile compounds can represent the changes of volatile compounds during the four steps. Additionally, sun-withering, rocking and de-enzyming can influence the variations of volatile compounds in different degree, and we found the changes of volatile compounds in withering step were less than other two manufacturing process, indicating that the characteristic volatile compounds of oolong tea might be mainly formed in rocking stage by biological reactions and de-enzyming stage through thermal chemical transformations rather than withering stage. This study suggested that HS-SPME/GC-MS combined with chemometrics methods is accurate, sensitive, fast and ideal for rapid routine analysis of the aroma compounds changes in oolong teas during manufacturing processing. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

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.

Rapid Determination of the Geographical Origin of Chinese Red Peppers (Zanthoxylum Bungeanum Maxim. Based on Sensory Characteristics and Chemometric Techniques

Directory of Open Access Journals (Sweden)

Xiangqian Yin

2018-04-01

Full Text Available In this paper, principal component analysis (PCA, linear discriminant analysis (LDAp, artificial neural networks (ANN, and support vector machine (SVM were applied to discriminate the geographical origin of Chinese red peppers (Zanthoxylum bungeanum Maxim.. The models based on color, smell and taste may discriminate quickly and effectively the geographical origin of Chinese red peppers from different regions, but the successful identification rates may vary with different kinds of parameters and chemometric methods. Among them, all models based on taste indexes showed an excellent ability to discriminate the geographical origin of Chinese red peppers with correct classifications of 100% for the training set and the 100% for test set. The present study provided a simple, efficient, inexpensive, practical and fast method to discriminate the geographical origin of Chinese red peppers from different regions, which was of great importance for both consumers and producers.

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.

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.

Application of FTIR Spectroscopy and Chemometrics for Halal Authentication of Beef Meatball Adulterated with Dog Meat

OpenAIRE

Rahayu, Wiranti Sri; Rohman, Abdul; Martono, Sudibyo; Sudjadi, Sudjadi

2018-01-01

Beef meatball is one of the favorite meat-based food products among Indonesian community. Currently, beef is very expensive in Indonesian market compared to other common meat types such as chicken and lamb. This situation has intrigued some unethical meatball producers to replace or adulterate beef with lower priced-meat like dog meat. The objective of this study was to evaluate the capability of FTIR spectroscopy combined with chemometrics for identification and quantification of dog meat (D...

Chemometric Analysis of Selected Organic Contaminants in Surface Water of Langat River Basin

International Nuclear Information System (INIS)

Mohamad Rafaie Mohamed Zubir; Rozita Osman; Norashikin Saim

2016-01-01

Chemometric techniques namely hierarchical agglomerative cluster analysis (HACA), discriminant analysis (DA), principal component analysis (PCA) and factor analysis (FA) were applied to the distribution of selected organic contaminants (polycyclic aromatic hydrocarbons (PAHs), sterols, pesticides (chloropyrifos), and phenol) to assess the potential of using these organic contaminants as chemical markers in Langat River Basin. Water samples were collected from February 2012 to January 2013 on a monthly basis for nine monitoring sites along Langat River Basin. HACA was able to classify the sampling sites into three clusters which can be correlated to the level of contamination (low, moderate and high contamination sites). DA was used to discriminate the sources of contamination using the selected organic contaminants and relate to the existing DOE local activities groupings. Forward and backward stepwise DA was able to discriminate two and five organic contaminants variables, respectively, from the original 13 selected variables. The five significant variables identified using backward stepwise DA were fluorene, pyrene, stigmastanol, stigmasterol and phenol. PCA and FA (varimax functionality) were used to identify the possible sources of each organic contaminant based on the inventory of local activities. Five principal components were obtained with 66.5 % of the total variation. Result from FA indicated that PAHs (pyrene, fluorene, acenaphthene, benzo[a]anthracene) originated from industrial activity and socio-economic activities; while sterols (coprostanol, stigmastanol and stigmasterol) were associated to domestic sewage and local socio-economic activities. The occurrence of chloropyrifos was correlated to agricultural activities, urban and domestic discharges. This study showed that the application of chemometrics on the distribution of selected organic contaminants was able to trace the sources of contamination in surface water. (author)

Quality control of the paracetamol drug by chemometrics and imaging spectroscopy in the near infrared region

Science.gov (United States)

Baptistao, Mariana; Rocha, Werickson Fortunato de Carvalho; Poppi, Ronei Jesus

2011-09-01

In this work, it was used imaging spectroscopy and chemometric tools for the development and analysis of paracetamol and excipients in pharmaceutical formulations. It was also built concentration maps to study the distribution of the drug in the tablets surface. Multivariate models based on PLS regression were developed for paracetamol and excipients concentrations prediction. For the construction of the models it was used 31 samples in the tablet form containing the active principle in a concentration range of 30.0-90.0% (w/w) and errors below to 5% were obtained for validation samples. Finally, the study of the distribution in the drug was performed through the distribution maps of concentration of active principle and excipients. The analysis of maps showed the complementarity between the active principle and excipients in the tablets. The region with a high concentration of a constituent must have, necessarily, absence or low concentration of the other one. Thus, an alternative method for the paracetamol drug quality monitoring is presented.

Effect of the addition of chia's by-product on the composition of fatty acids in hamburgers through chemometric methods.

Science.gov (United States)

Souza, Aloisio H P; Gohara, Aline K; Rotta, Eliza M; Chaves, Marcia A; Silva, Claudia M; Dias, Lucia F; Gomes, Sandra T M; Souza, Nilson E; Matsushita, Makoto

2015-03-30

Hamburger is a meat-based food that is easy to prepare and is widely consumed. It can be enriched using different ingredients, such as chia's by-product, which is rich in omega-3. Chemometrics is a very interesting tool to assess the influence of ingredients in the composition of foods. A complete factorial design 2(2) (two factors in two levels) with duplicate was performed to investigate the influence of the factors (1) concentration of textured soy proteins (TSP) and (2) concentration of chia flour partially defatted (CFPD) as a partial replacement for the bovine meat and porcine fat mix in hamburgers. The results of proximal composition, lipid oxidation, fatty acids sums, ratios, and nutritional indexes were used to propose statistical models. The factors TSP and CFPD were significant, and the increased values contributed to improve the composition in fatty acids, crude protein, and ash. Principal components analysis distinguished the samples with a higher content of chia. In desirability analysis, the highest level of TSP and CFPD was described as the optimal region, and it was not necessary to make another experimental point. The addition of chia's by-product is an alternative to increase the α-linolenic contents and to obtain nutritionally balanced food. © 2014 Society of Chemical Industry.

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.

Gastric cancer target detection using near-infrared hyperspectral imaging with chemometrics

Science.gov (United States)

Yi, Weisong; Zhang, Jian; Jiang, Houmin; Zhang, Niya

2014-09-01

Gastric cancer is one of the leading causes of cancer death in the world due to its high morbidity and mortality. Hyperspectral imaging (HSI) is an emerging, non-destructive, cutting edge analytical technology that combines conventional imaging and spectroscopy in one single system. The manuscript has investigated the application of near-infrared hyperspectral imaging (900-1700 nm) (NIR-HSI) for gastric cancer detection with algorithms. Major spectral differences were observed in three regions (950-1050, 1150-1250, and 1400-1500 nm). By inspecting cancerous mean spectrum three major absorption bands were observed around 975, 1215 and 1450 nm. Furthermore, the cancer target detection results are consistent and conformed with histopathological examination results. These results suggest that NIR-HSI is a simple, feasible and sensitive optical diagnostic technology for gastric cancer target detection with chemometrics.

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

2018-06-01

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.

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.

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....

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

OpenAIRE

Zorica Jurković; Rezica Sudar; Damir Magdić; Daniela Horvat; Želimir Kurtanjek

2002-01-01

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...

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)

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.

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.

Comparison between Two Linear Supervised Learning Machines' Methods with Principle Component Based Methods for the Spectrofluorimetric Determination of Agomelatine and Its Degradants.

Science.gov (United States)

Elkhoudary, Mahmoud M; Naguib, Ibrahim A; Abdel Salam, Randa A; Hadad, Ghada M

2017-05-01

Four accurate, sensitive and reliable stability indicating chemometric methods were developed for the quantitative determination of Agomelatine (AGM) whether in pure form or in pharmaceutical formulations. Two supervised learning machines' methods; linear artificial neural networks (PC-linANN) preceded by principle component analysis and linear support vector regression (linSVR), were compared with two principle component based methods; principle component regression (PCR) as well as partial least squares (PLS) for the spectrofluorimetric determination of AGM and its degradants. The results showed the benefits behind using linear learning machines' methods and the inherent merits of their algorithms in handling overlapped noisy spectral data especially during the challenging determination of AGM alkaline and acidic degradants (DG1 and DG2). Relative mean squared error of prediction (RMSEP) for the proposed models in the determination of AGM were 1.68, 1.72, 0.68 and 0.22 for PCR, PLS, SVR and PC-linANN; respectively. The results showed the superiority of supervised learning machines' methods over principle component based methods. Besides, the results suggested that linANN is the method of choice for determination of components in low amounts with similar overlapped spectra and narrow linearity range. Comparison between the proposed chemometric models and a reported HPLC method revealed the comparable performance and quantification power of the proposed models.

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.

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.

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.

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

A spectroscopic study of mechanochemically activated kaolinite with the aid of chemometrics.

Science.gov (United States)

Carmody, Onuma; Kristóf, János; Frost, Ray L; Makó, Eva; Kloprogge, J Theo; Kokot, Serge

2005-07-01

The study of kaolinite surfaces is of industrial importance. In this work we report the application of chemometrics to the study of modified kaolinite surfaces. DRIFT spectra of mechanochemically activated kaolinites (Kiralyhegy, Zettlitz, Szeg, and Birdwood) were analyzed using principal component analysis (PCA) and multicriteria decision making (MCDM) methods, PROMETHEE and GAIA. The clear discrimination of the Kiralyhegy spectral objects on the two PC scores plots (400-800 and 800-2030 cm(-1)) indicated the dominance of quartz. Importantly, no ordering of any spectral objects appeared to be related to grinding time in the PC plots of these spectral regions. Thus, neither the kaolinite nor the quartz, are systematically responsive to grinding time according to the spectral criteria investigated. The third spectral region (2600-3800 cm(-1)OH vibrations), showed apparent systematic ordering of the Kiralyhegy and, to a lesser extent, Zettlitz spectral objects with grinding time. This was attributed to the effect of the natural quartz on the delamination of kaolinite and the accompanying phenomena (i.e., formation of kaolinite spheres and water). With the MCDM methods, it was shown that useful information on the basis of chemical composition, physical properties and grinding time can be obtained. For example, the effects of the minor chemical components (e.g., MgO, K(2)O, etc.) indicated that the Birdwood kaolinite is arguably the most pure one analyzed. In another MCDM experiment, some support was obtained for the apparent trend with grinding time noted in the PC plot of the OH spectral region.

Chemotaxonomic Diversity of Three Ficus Species: Their Discrimination Using Chemometric Analysis and Their Role in Combating Oxidative Stress.

Science.gov (United States)

Al-Musayeib, Nawal; Ebada, Sherif S; Gad, Haidy A; Youssef, Fadia S; Ashour, Mohamed Lotfy

2017-10-01

Genus Ficus (Moraceae) constitutes more than 850 species and about 2000 varieties and it acts as a golden mine that could afford effective and safe remedies combating many health disorders. Discrimination of Ficus cordata , Ficus ingens , and Ficus palmata using chemometric analysis and assessment of their role in combating oxidative stress. Phytochemical profiling of the methanol extracts of the three Ficus species and their successive fractions was performed using high-performance liquid chromatography/electrospray ionization mass spectrometry. Their discrimination was carried out using the obtained spectral data applying chemometric unsupervised pattern-recognition techniques, namely, principal component analysis and hierarchical cluster analysis. In vitro hepatoprotective and antioxidant evaluation of the samples was performed using human hepatocellular carcinoma cells challenged by carbon tetrachloride (CCl 4 ). Altogether, 22 compounds belonging to polyphenolics, flavonoids, and furanocoumarins were identified in the three Ficus species. Aviprin is the most abundant compound in F. cordata while chlorogenic acid and psoralen were present in high percentages in F. ingens and F. palmata , respectively. Chemometric analyses showed that F. palmata and F. cordata are more closely related chemically to each other rather than F. ingens . The ethyl acetate fractions of all the examined species showed a marked hepatoprotective efficacy accounting for 54.78%, 55.46%, and 56.42% reduction in serum level of alanine transaminase and 56.82%, 54.16%, and 57.06% suppression in serum level of aspartate transaminase, respectively, at 100 μg/mL comparable to CCl 4 -treated cells. Ficus species exhibited a no table antioxidant and hepatoprotective activity owing to their richness in polyphenolics and furanocoumarins. Ficus cordata , Ficus ingens , and Ficus palmata were analyzed using high-performance liquid chromatography/electrospray ionization mass spectrometry that revealed

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_1_0 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)

Origin Discrimination of Osmanthus fragrans var. thunbergii Flowers using GC-MS and UPLC-PDA Combined with Multivariable Analysis Methods.

Science.gov (United States)

Zhou, Fei; Zhao, Yajing; Peng, Jiyu; Jiang, Yirong; Li, Maiquan; Jiang, Yuan; Lu, Baiyi

2017-07-01

Osmanthus fragrans flowers are used as folk medicine and additives for teas, beverages and foods. The metabolites of O. fragrans flowers from different geographical origins were inconsistent in some extent. Chromatography and mass spectrometry combined with multivariable analysis methods provides an approach for discriminating the origin of O. fragrans flowers. To discriminate the Osmanthus fragrans var. thunbergii flowers from different origins with the identified metabolites. GC-MS and UPLC-PDA were conducted to analyse the metabolites in O. fragrans var. thunbergii flowers (in total 150 samples). Principal component analysis (PCA), soft independent modelling of class analogy analysis (SIMCA) and random forest (RF) analysis were applied to group the GC-MS and UPLC-PDA data. GC-MS identified 32 compounds common to all samples while UPLC-PDA/QTOF-MS identified 16 common compounds. PCA of the UPLC-PDA data generated a better clustering than PCA of the GC-MS data. Ten metabolites (six from GC-MS and four from UPLC-PDA) were selected as effective compounds for discrimination by PCA loadings. SIMCA and RF analysis were used to build classification models, and the RF model, based on the four effective compounds (caffeic acid derivative, acteoside, ligustroside and compound 15), yielded better results with the classification rate of 100% in the calibration set and 97.8% in the prediction set. GC-MS and UPLC-PDA combined with multivariable analysis methods can discriminate the origin of Osmanthus fragrans var. thunbergii flowers. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Chemometrics Optimized Extraction Procedures, Phytosynergistic Blending and in vitro Screening of Natural Enzyme Inhibitors Amongst Leaves of Tulsi, Banyan and Jamun.

Science.gov (United States)

De, Baishakhi; Bhandari, Koushik; Singla, Rajeev K; Katakam, Prakash; Samanta, Tanmoy; Kushwaha, Dilip Kumar; Gundamaraju, Rohit; Mitra, Analava

2015-10-01

targeted enzymes expressed in terms of IC50 values have shown that hydro-ethanolic extracts in all cases whether individual species or composites in varying ratios gave higher IC50 values thus showing greater effectivity. Current research provides the state-of-the-art of search of NEIs amongst three species by in-vitro assays which can be further utilized for bioactivity-guided isolations of such enzyme inhibitors. Further, it reports the optimized phyto-blend ratios so as to achieve synergistic anti-oxidative actions. The current research work focuses on the optimization of the extraction process parameters and the ratios of phyto-synergistic blends of the leaves of three common medicinal plants viz. banyan, jamun and tulsi by chemometrics. Qualitative and quantitative chemo profiling of the extracts were done by different phytochemical tests and UV spectrophotometric methods. Enzymes like alpha amylase, alpha glucosidase, aldose reductase, dipeptidyl peptidase 4, angiotensin converting enzymes are found to be pathogenic in type 2 diabetes. In vitro screening of natural enzyme inhibitors amongst individual extracts and composite blends were carried out by different assay procedures and the potency expressed in terms of IC50 values. Antioxidant potentials were estimated by DPPH radical scavenging, ABTS, FRAP and Dot Blot assay. Hydroalcoholic solvent (50:50) gave maximal yield of bio-actives with minimal chlorophyll leaching. Hydroethanolic extract of tulsi showed maximal antioxidant effect. Though all composites showed synergism, maximal effects were shown by the composite (1:1:2) in terms of polyphenol yield, antioxidant effect and inhibitory actions against the targeted enzymes. Abbreviations used: DPP4- dipeptidyl peptidase 4; AR- aldose reductase; ACE- angiotensin converting enzyme; PPAR-γ- peroxisome proliferator activated receptor-γ; NEIs- natural enzyme inhibitors; BE- binding energy; GLP-1- Glucagon like peptide -1; ROS- Reactive oxygen species; CAT- catalase

Metals and organic compounds in the biosynthesis of cannabinoids: a chemometric approach to the analysis of Cannabis sativa samples.

Science.gov (United States)

Radosavljevic-Stevanovic, Natasa; Markovic, Jelena; Agatonovic-Kustrin, Snezana; Razic, Slavica

2014-01-01

Illicit production and trade of Cannabis sativa affect many societies. This drug is the most popular and easy to produce. Important information for the authorities is the production locality and the indicators of a particular production. This work is an attempt to recognise correlations between the metal content in the different parts of C. sativa L., in soils where plants were cultivated and the cannabinoids content, as a potential indicator. The organic fraction of the leaves of Cannabis plants was investigated by GC-FID analysis. In addition, the determination of Cu, Fe, Cr, Mn, Zn, Ca and Mg was realised by spectroscopic techniques (FAAS and GFAAS). In this study, numerous correlations between metal content in plants and soil, already confirmed in previous publications, were analysed applying chemometric unsupervised methods, that is, principal component analysis, factor analysis and cluster analysis, in order to highlight their role in the biosynthesis of cannabinoids.

Identification of syrup type using fourier transform-near infrared spectroscopy with multivariate classification methods

Directory of Open Access Journals (Sweden)

Ravipat Lapcharoensuk

2018-03-01

Full Text Available This research aimed to establish near infrared (NIR spectroscopy models for identification of syrup types in which the maple syrup was discriminated from other syrup types. Thirty syrup types were used in this research; the NIR spectra of each type were recorded with 10 replicates. The repeatability and reproducibility of NIR scanning were performed, and the absorbance at 6940cm−1 was used for calculation. Principal component analysis was used to group the syrup type. Identification models were developed by soft independent modeling by class analogy (SIMCA and partial least-squares discriminant analysis (PLS-DA. The SIMCA models of all syrup types exhibited accuracy percentage of 93.3–100% for identifying syrup types, whereas maple syrup discrimination models showed percentage of accuracy between 83.2% and 100%. The PLS-DA technique gave the accuracy of syrup types classification between 96.6% and 100% and presented ability on discrimination of maple syrup form other types of syrup with accuracy of 100%. The finding presented the potential of NIR spectroscopy for the syrup type identification.

The Use of Raman Tweezers and Chemometric Analysis to Discriminate the Urological Cell Lines, PC-3, LNCaP, BPH and MGH-U1

Science.gov (United States)

Harvey, T. J.; Hughes, C.; Ward, A. D.; Gazi, E.; Faria, E. Correia; Clarke, N. W.; Brown, M.; Snook, R.; Gardner, P.

2008-11-01

Here we report on investigations into using Raman optical tweezers to analyse both live and chemically fixed prostate and bladder cells. Spectra were subjected to chemometric analysis to discriminate and classify the cell types based on their spectra. Subsequent results revealed the potential of Raman tweezers as a potential clinical diagnostic tool.

Chemometrics applications in biotechnology processes: predicting column integrity and impurity clearance during reuse of chromatography resin.

Science.gov (United States)

Rathore, Anurag S; Mittal, Shachi; Lute, Scott; Brorson, Kurt

2012-01-01

Separation media, in particular chromatography media, is typically one of the major contributors to the cost of goods for production of a biotechnology therapeutic. To be cost-effective, it is industry practice that media be reused over several cycles before being discarded. The traditional approach for estimating the number of cycles a particular media can be reused for involves performing laboratory scale experiments that monitor column performance and carryover. This dataset is then used to predict the number of cycles the media can be used at manufacturing scale (concurrent validation). Although, well accepted and widely practiced, there are challenges associated with extrapolating the laboratory scale data to manufacturing scale due to differences that may exist across scales. Factors that may be different include: level of impurities in the feed material, lot to lot variability in feedstock impurities, design of the column housing unit with respect to cleanability, and homogeneity of the column packing. In view of these challenges, there is a need for approaches that may be able to predict column underperformance at the manufacturing scale over the product lifecycle. In case such an underperformance is predicted, the operators can unpack and repack the chromatography column beforehand and thus avoid batch loss. Chemometrics offers one such solution. In this article, we present an application of chemometrics toward the analysis of a set of chromatography profiles with the intention of predicting the various events of column underperformance including the backpressure buildup and inefficient deoxyribonucleic acid clearance. Copyright © 2012 American Institute of Chemical Engineers (AIChE).

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

[Studies on the brand traceability of milk powder based on NIR spectroscopy technology].

Science.gov (United States)

Guan, Xiao; Gu, Fang-Qing; Liu, Jing; Yang, Yong-Jian

2013-10-01

Brand traceability of several different kinds of milk powder was studied by combining near infrared spectroscopy diffuse reflectance mode with soft independent modeling of class analogy (SIMCA) in the present paper. The near infrared spectrum of 138 samples, including 54 Guangming milk powder samples, 43 Netherlands samples, and 33 Nestle samples and 8 Yili samples, were collected. After pretreatment of full spectrum data variables in training set, principal component analysis was performed, and the contribution rate of the cumulative variance of the first three principal components was about 99.07%. Milk powder principal component regression model based on SIMCA was established, and used to classify the milk powder samples in prediction sets. The results showed that the recognition rate of Guangming milk powder, Netherlands milk powder and Nestle milk powder was 78%, 75% and 100%, the rejection rate was 100%, 87%, and 88%, respectively. Therefore, the near infrared spectroscopy combined with SIMCA model can classify milk powder with high accuracy, and is a promising identification method of milk powder variety.

Online estimation of wax deposition thickness in single-phase sub-sea pipelines based on acoustic chemometrics: A feasibility study

OpenAIRE

Halstensen, Maths; Arvoh, Benjamin Kaku; Amundsen, Lene; Hoffmann, Rainer

2012-01-01

Wax deposition in sub-sea oil producing pipelines is a concern to the oil producing companies. The deposition of wax in pipelines can cause serious economic implications if not monitored and controlled. Several researchers have developed models and investigated the deposition of wax in crude oil pipelines. As of today, there is no off the shelf instrument available for reliable online estimation of the wax depo- sition thickness in sub-sea pipelines. Acoustic chemometrics was applied to inves...

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.

Authentication of vegetable oils on the basis of their physico-chemical properties with the aid of chemometrics.

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Zhang, Guowen; Ni, Yongnian; Churchill, Jane; Kokot, Serge

2006-09-15

In food production, reliable analytical methods for confirmation of purity or degree of spoilage are required by growers, food quality assessors, processors, and consumers. Seven parameters of physico-chemical properties, such as acid number, colority, density, refractive index, moisture and volatility, saponification value and peroxide value, were measured for quality and adulterated soybean, as well as quality and rancid rapeseed oils. Chemometrics methods were then applied for qualitative and quantitative discrimination and prediction of the oils by methods such exploratory principal component analysis (PCA), partial least squares (PLS), radial basis function-artificial neural networks (RBF-ANN), and multi-criteria decision making methods (MCDM), PROMETHEE and GAIA. In general, the soybean and rapeseed oils were discriminated by PCA, and the two spoilt oils behaved differently with the rancid rapeseed samples exhibiting more object scatter on the PC-scores plot, than the adulterated soybean oil. For the PLS and RBF-ANN prediction methods, suitable training models were devised, which were able to predict satisfactorily the category of the four different oil samples in the verification set. Rank ordering with the use of MCDM models indicated that the oil types can be discriminated on the PROMETHEE II scale. For the first time, it was demonstrated how ranking of oil objects with the use of PROMETHEE and GAIA could be utilized as a versatile indicator of quality performance of products on the basis of a standard selected by the stakeholder. In principle, this approach provides a very flexible method for assessment of product quality directly from the measured data.

UV-Vis spectroscopy combined with chemometric study on the interactions of three dietary flavonoids with copper ions.

Science.gov (United States)

Zhang, Liangliang; Liu, Yuchen; Wang, Yongmei; Xu, Man; Hu, Xinyu

2018-10-15

The complex formation between a copper ion and the dietary flavonoid quercetin (QU) and its two glycosides hyperin (HY) and rutin (RU) was studied by the combined use of spectroscopic measurement and the chemometric method. The spectral changes of pH titration revealed two successively formed deprotonated species of QU: the first formed species was proposed to be the 3-hydroxyl group deprotonated QU, and the second was the quinone form QU, which was formed by oxidation after the hydroxyl groups in the B-ring were deprotonated at high pH values. Similar results were obtained for HY and RU with two deprotonated species forming at high pH values. UV/visible spectroscopy showed successive formation of CuL 2 and CuL species of QU at pH 6.0, while only Cu 2 L was formed for HY and RU at this pH. Glycoside moieties in the C-ring of flavonoids decrease the conditional associated constants between flavonoids and Cu 2+ . Copyright © 2018 Elsevier Ltd. All rights reserved.

Chromatographic profiles of Phyllanthus aqueous extracts samples: a proposition of classification using chemometric models.

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Martins, Lucia Regina Rocha; Pereira-Filho, Edenir Rodrigues; Cass, Quezia Bezerra

2011-04-01

Taking in consideration the global analysis of complex samples, proposed by the metabolomic approach, the chromatographic fingerprint encompasses an attractive chemical characterization of herbal medicines. Thus, it can be used as a tool in quality control analysis of phytomedicines. The generated multivariate data are better evaluated by chemometric analyses, and they can be modeled by classification methods. "Stone breaker" is a popular Brazilian plant of Phyllanthus genus, used worldwide to treat renal calculus, hepatitis, and many other diseases. In this study, gradient elution at reversed-phase conditions with detection at ultraviolet region were used to obtain chemical profiles (fingerprints) of botanically identified samples of six Phyllanthus species. The obtained chromatograms, at 275 nm, were organized in data matrices, and the time shifts of peaks were adjusted using the Correlation Optimized Warping algorithm. Principal Component Analyses were performed to evaluate similarities among cultivated and uncultivated samples and the discrimination among the species and, after that, the samples were used to compose three classification models using Soft Independent Modeling of Class analogy, K-Nearest Neighbor, and Partial Least Squares for Discriminant Analysis. The ability of classification models were discussed after their successful application for authenticity evaluation of 25 commercial samples of "stone breaker."

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.

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)

Dataset of Fourier transform-infrared coupled with chemometric analysis used to distinguish accessions of Garcinia mangostana L. in Peninsular Malaysia

OpenAIRE

Samsir, Sri A’jilah; Bunawan, Hamidun; Yen, Choong Chee; Noor, Normah Mohd

2016-01-01

In this dataset, we distinguish 15 accessions of Garcinia mangostana from Peninsular Malaysia using Fourier transform-infrared spectroscopy coupled with chemometric analysis. We found that the position and intensity of characteristic peaks at 3600–3100 cm−1 in IR spectra allowed discrimination of G. mangostana from different locations. Further principal component analysis (PCA) of all the accessions suggests the two main clusters were formed: samples from Johor, Melaka, and Negeri Sembilan (S...

Chemometric expertise of the quality of groundwater sources for domestic use.

Science.gov (United States)

Spanos, Thomas; Ene, Antoaneta; Simeonova, Pavlina

2015-01-01

In the present study 49 representative sites have been selected for the collection of water samples from central water supplies with different geographical locations in the region of Kavala, Northern Greece. Ten physicochemical parameters (pH, electric conductivity, nitrate, chloride, sodium, potassium, total alkalinity, total hardness, bicarbonate and calcium) were analyzed monthly, in the period from January 2010 to December 2010. Chemometric methods were used for monitoring data mining and interpretation (cluster analysis, principal components analysis and source apportioning by principal components regression). The clustering of the chemical indicators delivers two major clusters related to the water hardness and the mineral components (impacted by sea, bedrock and acidity factors). The sampling locations are separated into three major clusters corresponding to the spatial distribution of the sites - coastal, lowland and semi-mountainous. The principal components analysis reveals two latent factors responsible for the data structures, which are also an indication for the sources determining the groundwater quality of the region (conditionally named "mineral" factor and "water hardness" factor). By the apportionment approach it is shown what the contribution is of each of the identified sources to the formation of the total concentration of each one of the chemical parameters. The mean values of the studied physicochemical parameters were found to be within the limits given in the 98/83/EC Directive. The water samples are appropriate for human consumption. The results of this study provide an overview of the hydrogeological profile of water supply system for the studied area.

Rapid discrimination of bergamot essential oil by paper spray mass spectrometry and chemometric analysis.

Science.gov (United States)

Taverna, Domenico; Di Donna, Leonardo; Mazzotti, Fabio; Tagarelli, Antonio; Napoli, Anna; Furia, Emilia; Sindona, Giovanni

2016-09-01

A novel approach for the rapid discrimination of bergamot essential oil from other citrus fruits oils is presented. The method was developed using paper spray mass spectrometry (PS-MS) allowing for a rapid molecular profiling coupled with a statistic tool for a precise and reliable discrimination between the bergamot complex matrix and other similar matrices, commonly used for its reconstitution. Ambient mass spectrometry possesses the ability to record mass spectra of ordinary samples, in their native environment, without sample preparation or pre-separation by creating ions outside the instrument. The present study reports a PS-MS method for the determination of oxygen heterocyclic compounds such as furocoumarins, psoralens and flavonoids present in the non-volatile fraction of citrus fruits essential oils followed by chemometric analysis. The volatile fraction of Bergamot is one of the most known and fashionable natural products, which found applications in flavoring industry as ingredient in beverages and flavored foodstuff. The development of the presented method employed bergamot, sweet orange, orange, cedar, grapefruit and mandarin essential oils. PS-MS measurements were carried out in full scan mode for a total run time of 2 min. The capability of PS-MS profiling to act as marker for the classification of bergamot essential oils was evaluated by using multivariate statistical analysis. Two pattern recognition techniques, linear discriminant analysis and soft independent modeling of class analogy, were applied to MS data. The cross-validation procedure has shown excellent results in terms of the prediction ability because both models have correctly classified all samples for each category. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Evaluation of thermal and non-thermal processing effect on non-prebiotic and prebiotic acerola juices using 1H qNMR and GC-MS coupled to chemometrics.

Science.gov (United States)

Alves Filho, Elenilson G; Silva, Lorena Mara A; de Brito, Edy S; Wurlitzer, Nedio Jair; Fernandes, Fabiano A N; Rabelo, Maria Cristiane; Fonteles, Thatyane V; Rodrigues, Sueli

2018-11-01

The effects of thermal (pasteurization and sterilization) and non-thermal (ultrasound and plasma) processing on the composition of prebiotic and non-prebiotic acerola juices were evaluated using NMR and GC-MS coupled to chemometrics. The increase in the amount of Vitamin C was the main feature observed after thermal processing, followed by malic acid, choline, trigonelline, and acetaldehyde. On the other hand, thermal processing increased the amount of 2-furoic acid, a degradation product from ascorbic acid, as well as influenced the decrease in the amount of esters and alcohols. In general, the non-thermal processing did not present relevant effect on juices composition. The addition of prebiotics (inulin and gluco-oligosaccharides) decreased the effect of processing on juices composition, which suggested a protective effect by microencapsulation. Therefore, chemometric evaluation of the 1 H qNMR and GC-MS dataset was suitable to follow changes in acerola juice under different processing. Copyright © 2018 Elsevier Ltd. All rights reserved.

(Poly)phenolic fingerprint and chemometric analysis of white (Morus alba L.) and black (Morus nigra L.) mulberry leaves by using a non-targeted UHPLC-MS approach.

Science.gov (United States)

Sánchez-Salcedo, Eva M; Tassotti, Michele; Del Rio, Daniele; Hernández, Francisca; Martínez, Juan José; Mena, Pedro

2016-12-01

This study reports the (poly)phenolic fingerprinting and chemometric discrimination of leaves of eight mulberry clones from Morus alba and Morus nigra cultivated in Spain. UHPLC-MS(n) (Ultra High Performance Liquid Chromatography-Mass Spectrometry) high-throughput analysis allowed the tentative identification of a total of 31 compounds. The phenolic profile of mulberry leaf was characterized by the presence of a high number of flavonol derivatives, mainly glycosylated forms of quercetin and kaempferol. Caffeoylquinic acids, simple phenolic acids, and some organic acids were also detected. Seven compounds were identified for the first time in mulberry leaves. The chemometric analysis (cluster analysis and principal component analysis) of the chromatographic data allowed the characterization of the different mulberry clones and served to explain the great intraspecific variability in mulberry secondary metabolism. This screening of the complete phenolic profile of mulberry leaves can assist the increasing interest for purposes related to quality control, germplasm screening, and bioactivity evaluation. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Application of multivariate chemometric techniques for simultaneous determination of five parameters of cottonseed oil by single bounce attenuated total reflectance Fourier transform infrared spectroscopy.

Science.gov (United States)

Talpur, M Younis; Kara, Huseyin; Sherazi, S T H; Ayyildiz, H Filiz; Topkafa, Mustafa; Arslan, Fatma Nur; Naz, Saba; Durmaz, Fatih; Sirajuddin

2014-11-01

Single bounce attenuated total reflectance (SB-ATR) Fourier transform infrared (FTIR) spectroscopy in conjunction with chemometrics was used for accurate determination of free fatty acid (FFA), peroxide value (PV), iodine value (IV), conjugated diene (CD) and conjugated triene (CT) of cottonseed oil (CSO) during potato chips frying. Partial least square (PLS), stepwise multiple linear regression (SMLR), principal component regression (PCR) and simple Beer׳s law (SBL) were applied to develop the calibrations for simultaneous evaluation of five stated parameters of cottonseed oil (CSO) during frying of French frozen potato chips at 170°C. Good regression coefficients (R(2)) were achieved for FFA, PV, IV, CD and CT with value of >0.992 by PLS, SMLR, PCR, and SBL. Root mean square error of prediction (RMSEP) was found to be less than 1.95% for all determinations. Result of the study indicated that SB-ATR FTIR in combination with multivariate chemometrics could be used for accurate and simultaneous determination of different parameters during the frying process without using any toxic organic solvent. Copyright © 2014 Elsevier B.V. All rights reserved.

Mapping gas-phase organic reactivity and concomitant secondary organic aerosol formation: chemometric dimension reduction techniques for the deconvolution of complex atmospheric data sets

Science.gov (United States)

Wyche, K. P.; Monks, P. S.; Smallbone, K. L.; Hamilton, J. F.; Alfarra, M. R.; Rickard, A. R.; McFiggans, G. B.; Jenkin, M. E.; Bloss, W. J.; Ryan, A. C.; Hewitt, C. N.; MacKenzie, A. R.

2015-07-01

Highly non-linear dynamical systems, such as those found in atmospheric chemistry, necessitate hierarchical approaches to both experiment and modelling in order to ultimately identify and achieve fundamental process-understanding in the full open system. Atmospheric simulation chambers comprise an intermediate in complexity, between a classical laboratory experiment and the full, ambient system. As such, they can generate large volumes of difficult-to-interpret data. Here we describe and implement a chemometric dimension reduction methodology for the deconvolution and interpretation of complex gas- and particle-phase composition spectra. The methodology comprises principal component analysis (PCA), hierarchical cluster analysis (HCA) and positive least-squares discriminant analysis (PLS-DA). These methods are, for the first time, applied to simultaneous gas- and particle-phase composition data obtained from a comprehensive series of environmental simulation chamber experiments focused on biogenic volatile organic compound (BVOC) photooxidation and associated secondary organic aerosol (SOA) formation. We primarily investigated the biogenic SOA precursors isoprene, α-pinene, limonene, myrcene, linalool and β-caryophyllene. The chemometric analysis is used to classify the oxidation systems and resultant SOA according to the controlling chemistry and the products formed. Results show that "model" biogenic oxidative systems can be successfully separated and classified according to their oxidation products. Furthermore, a holistic view of results obtained across both the gas- and particle-phases shows the different SOA formation chemistry, initiating in the gas-phase, proceeding to govern the differences between the various BVOC SOA compositions. The results obtained are used to describe the particle composition in the context of the oxidised gas-phase matrix. An extension of the technique, which incorporates into the statistical models data from anthropogenic (i

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.

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.

Rapid differentiation of Listeria monocytogenes epidemic clones III and IV and their intact compared with heat-killed populations using Fourier transform infrared spectroscopy and chemometrics.

Science.gov (United States)

Nyarko, Esmond B; Puzey, Kenneth A; Donnelly, Catherine W

2014-06-01

The objectives of this study were to determine if Fourier transform infrared (FT-IR) spectroscopy and multivariate statistical analysis (chemometrics) could be used to rapidly differentiate epidemic clones (ECs) of Listeria monocytogenes, as well as their intact compared with heat-killed populations. FT-IR spectra were collected from dried thin smears on infrared slides prepared from aliquots of 10 μL of each L. monocytogenes ECs (ECIII: J1-101 and R2-499; ECIV: J1-129 and J1-220), and also from intact and heat-killed cell populations of each EC strain using 250 scans at a resolution of 4 cm(-1) in the mid-infrared region in a reflectance mode. Chemometric analysis of spectra involved the application of the multivariate discriminant method for canonical variate analysis (CVA) and linear discriminant analysis (LDA). CVA of the spectra in the wavelength region 4000 to 600 cm(-1) separated the EC strains while LDA resulted in a 100% accurate classification of all spectra in the data set. Further, CVA separated intact and heat-killed cells of each EC strain and there was 100% accuracy in the classification of all spectra when LDA was applied. FT-IR spectral wavenumbers 1650 to 1390 cm(-1) were used to separate heat-killed and intact populations of L. monocytogenes. The FT-IR spectroscopy method allowed discrimination between strains that belong to the same EC. FT-IR is a highly discriminatory and reproducible method that can be used for the rapid subtyping of L. monocytogenes, as well as for the detection of live compared with dead populations of the organism. Fourier transform infrared (FT-IR) spectroscopy and multivariate statistical analysis can be used for L. monocytogenes source tracking and for clinical case isolate comparison during epidemiological investigations since the method is capable of differentiating epidemic clones and it uses a library of well-characterized strains. The FT-IR method is potentially less expensive and more rapid compared to genetic

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.

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.

Comprehensive analysis of yeast metabolite GC x GC-TOFMS data: combining discovery-mode and deconvolution chemometric software.

Science.gov (United States)

Mohler, Rachel E; Dombek, Kenneth M; Hoggard, Jamin C; Pierce, Karisa M; Young, Elton T; Synovec, Robert E

2007-08-01

The first extensive study of yeast metabolite GC x GC-TOFMS data from cells grown under fermenting, R, and respiring, DR, conditions is reported. In this study, recently developed chemometric software for use with three-dimensional instrumentation data was implemented, using a statistically-based Fisher ratio method. The Fisher ratio method is fully automated and will rapidly reduce the data to pinpoint two-dimensional chromatographic peaks differentiating sample types while utilizing all the mass channels. The effect of lowering the Fisher ratio threshold on peak identification was studied. At the lowest threshold (just above the noise level), 73 metabolite peaks were identified, nearly three-fold greater than the number of previously reported metabolite peaks identified (26). In addition to the 73 identified metabolites, 81 unknown metabolites were also located. A Parallel Factor Analysis graphical user interface (PARAFAC GUI) was applied to selected mass channels to obtain a concentration ratio, for each metabolite under the two growth conditions. Of the 73 known metabolites identified by the Fisher ratio method, 54 were statistically changing to the 95% confidence limit between the DR and R conditions according to the rigorous Student's t-test. PARAFAC determined the concentration ratio and provided a fully-deconvoluted (i.e. mathematically resolved) mass spectrum for each of the metabolites. The combination of the Fisher ratio method with the PARAFAC GUI provides high-throughput software for discovery-based metabolomics research, and is novel for GC x GC-TOFMS data due to the use of the entire data set in the analysis (640 MB x 70 runs, double precision floating point).

Chemometric profile of root extracts of Rhodiola imbricata Edgew. with hyphenated gas chromatography mass spectrometric technique.

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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

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

Nontargeted, Rapid Screening of Extra Virgin Olive Oil Products for Authenticity Using Near-Infrared Spectroscopy in Combination with Conformity Index and Multivariate Statistical Analyses.

Science.gov (United States)

Karunathilaka, Sanjeewa R; Kia, Ali-Reza Fardin; Srigley, Cynthia; Chung, Jin Kyu; Mossoba, Magdi M

2016-10-01

A rapid tool for evaluating authenticity was developed and applied to the screening of extra virgin olive oil (EVOO) retail products by using Fourier-transform near infrared (FT-NIR) spectroscopy in combination with univariate and multivariate data analysis methods. Using disposable glass tubes, spectra for 62 reference EVOO, 10 edible oil adulterants, 20 blends consisting of EVOO spiked with adulterants, 88 retail EVOO products and other test samples were rapidly measured in the transmission mode without any sample preparation. The univariate conformity index (CI) and the multivariate supervised soft independent modeling of class analogy (SIMCA) classification tool were used to analyze the various olive oil products which were tested for authenticity against a library of reference EVOO. Better discrimination between the authentic EVOO and some commercial EVOO products was observed with SIMCA than with CI analysis. Approximately 61% of all EVOO commercial products were flagged by SIMCA analysis, suggesting that further analysis be performed to identify quality issues and/or potential adulterants. Due to its simplicity and speed, FT-NIR spectroscopy in combination with multivariate data analysis can be used as a complementary tool to conventional official methods of analysis to rapidly flag EVOO products that may not belong to the class of authentic EVOO. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Application of FTIR Spectroscopy and Chemometrics for Halal Authentication of Beef Meatball Adulterated with Dog Meat

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Wiranti Sri Rahayu

2018-05-01

Full Text Available Beef meatball is one of the favorite meat-based food products among Indonesian community. Currently, beef is very expensive in Indonesian market compared to other common meat types such as chicken and lamb. This situation has intrigued some unethical meatball producers to replace or adulterate beef with lower priced-meat like dog meat. The objective of this study was to evaluate the capability of FTIR spectroscopy combined with chemometrics for identification and quantification of dog meat (DM in beef meatball (BM. Meatball samples were prepared by adding DM into BM ingredients in the range of 0–100% wt/wt and were subjected to extraction using Folch method. Lipid extracts obtained from the samples were scanned using FTIR spectrophotometer at 4000–650 cm-1. Partial least square (PLS calibration was used to quantify DM in the meatball. The results showed that combined frequency regions of 1782–1623 cm-1 and 1485-659 cm-1 using detrending treatment gave optimum prediction of DM in BM. Coefficient of determination (R2 for correlation between the actual value of DM and FTIR predicted value was 0.993 in calibration model and 0.995 in validation model. The root mean square error of calibration (RMSEC and standard error of cross validation (SECV were 1.63% and 2.68%, respectively. FTIR spectroscopy combined with multivariate analysis can serve as an accurate and reliable method for analysis of DM in meatball.

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.

Carbon nuclear magnetic resonance spectroscopic fingerprinting of commercial gasoline: pattern-recognition analyses for screening quality control purposes.

Science.gov (United States)

Flumignan, Danilo Luiz; Boralle, Nivaldo; Oliveira, José Eduardo de

2010-06-30

In this work, the combination of carbon nuclear magnetic resonance ((13)C NMR) fingerprinting with pattern-recognition analyses provides an original and alternative approach to screening commercial gasoline quality. Soft Independent Modelling of Class Analogy (SIMCA) was performed on spectroscopic fingerprints to classify representative commercial gasoline samples, which were selected by Hierarchical Cluster Analyses (HCA) over several months in retails services of gas stations, into previously quality-defined classes. Following optimized (13)C NMR-SIMCA algorithm, sensitivity values were obtained in the training set (99.0%), with leave-one-out cross-validation, and external prediction set (92.0%). Governmental laboratories could employ this method as a rapid screening analysis to discourage adulteration practices. Copyright 2010 Elsevier B.V. All rights reserved.

Chemometric formulation of bacterial consortium-AVS for improved decolorization of resonance-stabilized and heteropolyaromatic dyes.

Science.gov (United States)

Kumar, Madhava Anil; Kumar, Vaidyanathan Vinoth; Premkumar, Manickam Periyaraman; Baskaralingam, Palanichamy; Thiruvengadaravi, Kadathur Varathachary; Dhanasekaran, Anuradha; Sivanesan, Subramanian

2012-11-01

A bacterial consortium-AVS, consisting of Pseudomonas desmolyticum NCIM 2112, Kocuria rosea MTCC 1532 and Micrococcus glutamicus NCIM 2168 was formulated chemometrically, using the mixture design matrix based on the design of experiments methodology. The formulated consortium-AVS decolorized acid blue 15 and methylene blue with a higher average decolorization rate, which is more rapid than that of the pure cultures. The UV-vis spectrophotometric, Fourier transform infra red spectrophotometric and high performance liquid chromatographic analysis confirm that the decolorization was due to biodegradation by oxido-reductive enzymes, produced by the consortium-AVS. The toxicological assessment of plant growth parameters and the chlorophyll pigment concentrations of Phaseolus mungo and Triticum aestivum seedlings revealed the reduced toxic nature of the biodegraded products. Copyright © 2012 Elsevier Ltd. All rights reserved.

Combination of Analytical and Chemometric Methods as a Useful Tool for the Characterization of Extra Virgin Argan Oil and Other Edible Virgin Oils. Role of Polyphenols and Tocopherols.

Science.gov (United States)

Rueda, Ascensión; Samaniego-Sánchez, Cristina; Olalla, Manuel; Giménez, Rafael; Cabrera-Vique, Carmen; Seiquer, Isabel; Lara, Luis

2016-01-01

Analysis of phenolic profile and tocopherol fractions in conjunction with chemometrics techniques were used for the accurate characterization of extra virgin argan oil and eight other edible vegetable virgin oils (olive, soybean, wheat germ, walnut, almond, sesame, avocado, and linseed) and to establish similarities among them. Phenolic profile and tocopherols were determined by HPLC coupled with diode-array and fluorescence detectors, respectively. Multivariate factor analysis (MFA) and linear correlations were applied. Significant negative correlations were found between tocopherols and some of the polyphenols identified, but more intensely (P tocopherol and oleuropein, pinoresinol, and luteolin. MFA revealed that tocopherols, especially γ-fraction, most strongly influenced the oil characterization. Among the phenolic compounds, syringic acid, dihydroxybenzoic acid, oleuropein, pinoresinol, and luteolin also contributed to the discrimination of the oils. According to the variables analyzed in the present study, argan oil presented the greatest similarity with walnut oil, followed by sesame and linseed oils. Olive, avocado, and almond oils showed close similarities.

Distribution and mobility of metals in contaminated sites. chemometric investigation of pollutant profiles.

Science.gov (United States)

Abollino, Ornella; Aceto, Maurizio; Malandrino, Mery; Mentasti, Edoardo; Sarzanini, Corrado; Barberis, Renzo

2002-01-01

The distribution and mobility of heavy metals in the soils of two contaminated sites in Piedmont (Italy) was investigated, evaluating the horizontal and vertical profiles of 15 metals, namely Al, Cd, Cu, Cr, Fe. La, Mn, Ni, Pb, Sc, Ti, V, Y, Zn and Zr. The concentrations in the most polluted areas of the sites were higher than the acceptable limits reported in Italian and Dutch legislations for soil reclamation. Chemometric elaboration of the results by pattern recognition techniques allowed us to identify groups of samples with similar characteristics and to find correlations among the variables. The pollutant mobility was studied by extraction with water, dilute acetic acid and EDTA and by applying Tessier's procedure. The fraction of mobile species, which potentially is the most harmful for the environment, was found to be higher than the one normally present in unpolluted soils, where heavy metals are, to a higher extent, strongly bound to the matrix.

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.

Chemometric approach for prediction of uranium pathways in the soil

International Nuclear Information System (INIS)

Stojanovic, Mirjana; Nihajlovic, Marija; Petrovic, Jelena; Petrovic, Marija; Sostaric, Tanja; Milojkovic, Jelena; Pezo, Lato

2014-01-01

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.

Assessing therapeutic relevance of biologically interesting, ampholytic substances based on their physicochemical and spectral characteristics with chemometric tools

Science.gov (United States)

Judycka, U.; Jagiello, K.; Bober, L.; Błażejowski, J.; Puzyn, T.

2018-06-01

Chemometric tools were applied to investigate the biological behaviour of ampholytic substances in relation to their physicochemical and spectral properties. Results of the Principal Component Analysis suggest that size of molecules and their electronic and spectral characteristics are the key properties required to predict therapeutic relevance of the compounds examined. These properties were used for developing the structure-activity classification model. The classification model allows assessing the therapeutic behaviour of ampholytic substances on the basis of solely values of descriptors that can be obtained computationally. Thus, the prediction is possible without necessity of carrying out time-consuming and expensive laboratory tests, which is its main advantage.

Classification of Brazilian and foreign gasolines adulterated with alcohol using infrared spectroscopy.

Science.gov (United States)

da Silva, Neirivaldo C; Pimentel, Maria Fernanda; Honorato, Ricardo S; Talhavini, Marcio; Maldaner, Adriano O; Honorato, Fernanda A

2015-08-01

The smuggling of products across the border regions of many countries is a practice to be fought. Brazilian authorities are increasingly worried about the illicit trade of fuels along the frontiers of the country. In order to confirm this as a crime, the Federal Police must have a means of identifying the origin of the fuel. This work describes the development of a rapid and nondestructive methodology to classify gasoline as to its origin (Brazil, Venezuela and Peru), using infrared spectroscopy and multivariate classification. Partial Least Squares Discriminant Analysis (PLS-DA) and Soft Independent Modeling Class Analogy (SIMCA) models were built. Direct standardization (DS) was employed aiming to standardize the spectra obtained in different laboratories of the border units of the Federal Police. Two approaches were considered in this work: (1) local and (2) global classification models. When using Approach 1, the PLS-DA achieved 100% correct classification, and the deviation of the predicted values for the secondary instrument considerably decreased after performing DS. In this case, SIMCA models were not efficient in the classification, even after standardization. Using a global model (Approach 2), both PLS-DA and SIMCA techniques were effective after performing DS. Considering that real situations may involve questioned samples from other nations (such as Peru), the SIMCA method developed according to Approach 2 is a more adequate, since the sample will be classified neither as Brazil nor Venezuelan. This methodology could be applied to other forensic problems involving the chemical classification of a product, provided that a specific modeling is performed. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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.

Chemometric methods for the simultaneous determination of some water-soluble vitamins.

Science.gov (United States)

Mohamed, Abdel-Maaboud I; Mohamed, Horria A; Mohamed, Niveen A; El-Zahery, Marwa R

2011-01-01

Two spectrophotometric methods, derivative and multivariate methods, were applied for the determination of binary, ternary, and quaternary mixtures of the water-soluble vitamins thiamine HCI (I), pyridoxine HCI (II), riboflavin (III), and cyanocobalamin (IV). The first method is divided into first derivative and first derivative of ratio spectra methods, and the second into classical least squares and principal components regression methods. Both methods are based on spectrophotometric measurements of the studied vitamins in 0.1 M HCl solution in the range of 200-500 nm for all components. The linear calibration curves were obtained from 2.5-90 microg/mL, and the correlation coefficients ranged from 0.9991 to 0.9999. These methods were applied for the analysis of the following mixtures: (I) and (II); (I), (II), and (III); (I), (II), and (IV); and (I), (II), (III), and (IV). The described methods were successfully applied for the determination of vitamin combinations in synthetic mixtures and dosage forms from different manufacturers. The recovery ranged from 96.1 +/- 1.2 to 101.2 +/- 1.0% for derivative methods and 97.0 +/- 0.5 to 101.9 +/- 1.3% for multivariate methods. The results of the developed methods were compared with those of reported methods, and gave good accuracy and precision.

Chemometric profile, antioxidant and tyrosinase inhibitory activity of Camel's foot creeper leaves (Bauhinia vahlii).

Science.gov (United States)

Panda, Pritipadma; Dash, Priyanka; Ghosh, Goutam

2018-03-01

The present study is the first effort to a comprehensive evaluation of antityrosinase activity and chemometric analysis of Bauhinia vahlii. The experimental results revealed that the methanol extract of Bauhinia vahlii (BVM) possesses higher polyphenolic compounds and total antioxidant activity than those reported elsewhere for other more conventionally and geographically different varieties. The BVM contain saturated fatty acids such as hexadecanoic acid (10.15%), octadecanoic acid (1.97%), oleic acid (0.61%) and cis-vaccenic acid (2.43%) along with vitamin E (12.71%), α-amyrin (9.84%), methyl salicylate (2.39%) and β-sitosterol (17.35%), which were mainly responsible for antioxidant as well as tyrosinase inhibitory activity. Tyrosinase inhibitory activity of this extract was comparable to that of Kojic acid. These findings suggested that the B. vahlii leaves could be exploited as potential source of natural antioxidant and tyrosinase inhibitory agent, as well.

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.

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.

Real-Time Label-Free Detection of Suspicious Powders Using Noncontact Optical Methods

Science.gov (United States)

2013-11-05

PCA). Care was taken to ensure that all microbes were vetted to be pure and well washed of media . This process is described in detail in...surface. The color rendition on Fig. 8 is determined by the RGB position in a chemometric space determined by a band difference analysis ( BDA ...Band Difference Analysis ( BDA ) chemometric-space spatial maps of dilute streaks of 4 microbes on a stainless steel substrate. BS= B. subtilis, EC= E

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.

Rapid authentication and identification of different types of A. roxburghii by Tri-step FT-IR spectroscopy

Science.gov (United States)

Chen, Ying; Huang, Jinfang; Yeap, Zhao Qin; Zhang, Xue; Wu, Shuisheng; Ng, Chiew Hoong; Yam, Mun Fei

2018-06-01

Anoectochilus roxburghii (Wall.) Lindl. (Orchidaceae) is a precious traditional Chinese medicinal herb and has been perennially used to treat various illness. However, there were unethical sellers who adulterated wild A. roxburghii with tissue cultured and cultivated ones. Therefore, there is an urgent need for an effective authentication method to differentiate between these different types of A. roxburghii. In this research, the infrared spectroscopic tri-step identification approach including Fourier transform infrared spectroscopy (FT-IR), Second derivative infrared spectra (SD-IR) and two-dimensional correlation infrared spectra (2D-IR) was used to develop a simple and rapid method to discriminate between wild, cultivated and tissue cultivated A. roxburghii plant. Through this study, all three types of A. roxburghii plant were successfully identified and discriminated through the infrared spectroscopic tri-step identification method. Besides that, all the samples of wild, cultivated and tissue cultivated A. roxburghii plant were analysed with the Soft Independent Modelling of Class Analogy (SIMCA) pattern recognition technique to test and verify the experimental results. The results showed that the three types of A. roxburghii can be discriminated clearly as the recognition rate was 100% for all three types and the rejection rate was more than 60%. 70% of the validated samples were also identified correctly by the SIMCA model. The SIMCA model was also validated by comparing 70 standard herbs to the model. As a result, it was demonstrated that the macroscopic IR fingerprint method and the classification analysis could discriminate not only between the A. roxburghi samples and the standard herbs, it could also distinguish between the three different types of A. roxburghi plant in a direct, rapid and holistic manner.

Modification of kaolinite surfaces through mechanochemical activation with quartz: A diffuse reflectance infrared fourier transform and chemometrics study.

Science.gov (United States)

Carmody, Onuma; Frost, Ray L; Kristóf, János; Kokot, Serge; Kloprogge, J Theo; Makó, Eva

2006-12-01

Studies of kaolinite surfaces are of industrial importance. One useful method for studying the changes in kaolinite surface properties is to apply chemometric analyses to the kaolinite surface infrared spectra. A comparison is made between the mechanochemical activation of Kiralyhegy kaolinites with significant amounts of natural quartz and the mechanochemical activation of Zettlitz kaolinite with added quartz. Diffuse reflectance infrared Fourier transform (DRIFT) spectra were analyzed using principal component analysis (PCA) and multi-criteria decision making (MCDM) methods, the preference ranking organization method for enrichment evaluations (PROMETHEE) and geometrical analysis for interactive assistance (GAIA). The clear discrimination of the Kiralyhegy spectral objects on the two PC scores plots (400-800 and 800-2030 cm(-1)) indicated the dominance of quartz. Importantly, no ordering of any spectral objects appeared to be related to grinding time in the PC plots of these spectral regions. Thus, neither the kaolinite nor the quartz are systematically responsive to grinding time according to the spectral criteria investigated. The third spectral region (2600-3800 cm(-1), OH vibrations), showed apparent systematic ordering of the Kiralyhegy and, to a lesser extent, Zettlitz spectral objects with grinding time. This was attributed to the effect of the natural quartz on the delamination of kaolinite and the accompanying phenomena (i.e., formation of kaolinite spheres and water). The mechanochemical activation of kaolinite and quartz, through dry grinding, results in changes to the surface structure. Different grinding times were adopted to study the rate of destruction of the kaolinite and quartz structures. This relationship (i.e., grinding time) was classified using PROMETHEE and GAIA methodology.

Rapid qualitative and quantitative analysis of opiates in extract of poppy head via FTIR and chemometrics: towards in-field sensors.

Science.gov (United States)

Turner, Nicholas W; Cauchi, Michael; Piletska, Elena V; Preston, Christopher; Piletsky, Sergey A

2009-07-15

Identification and quantification of the opiates morphine and thebaine has been achieved in three commercial poppy cultivars using FTIR-ATR spectroscopy, from a simple and rapid methanolic extraction, suitable for field analysis. The limits of detection were 0.13 mg/ml (0.013%, w/v) and 0.3 mg/ml (0.03%, w/v) respectively. The concentrations of opiates present were verified with HPLC-MS. The chemometrics has been used to identify specific "signature" peaks in the poppy IR spectra for characterisation of cultivar by its unique fingerprint offering a potential forensic application in opiate crop analysis.

Dataset of Fourier transform-infrared coupled with chemometric analysis used to distinguish accessions of Garcinia mangostana L. in Peninsular Malaysia.

Science.gov (United States)

Samsir, Sri A'jilah; Bunawan, Hamidun; Yen, Choong Chee; Noor, Normah Mohd

2016-09-01

In this dataset, we distinguish 15 accessions of Garcinia mangostana from Peninsular Malaysia using Fourier transform-infrared spectroscopy coupled with chemometric analysis. We found that the position and intensity of characteristic peaks at 3600-3100 cm(-) (1) in IR spectra allowed discrimination of G. mangostana from different locations. Further principal component analysis (PCA) of all the accessions suggests the two main clusters were formed: samples from Johor, Melaka, and Negeri Sembilan (South) were clustered together in one group while samples from Perak, Kedah, Penang, Selangor, Kelantan, and Terengganu (North and East Coast) were in another clustered group.

UHPLC-MS/MS Quantification Combined with Chemometrics for Comparative Analysis of Different Batches of Raw, Wine-Processed, and Salt-Processed Radix Achyranthis Bidentatae

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Liu Yang

2018-03-01

Full Text Available An accurate and reliable method using ultra-high performance liquid chromatography combined with triple quadrupole tandem mass spectrometry (UHPLC–MS/MS was established for simultaneous quantification of five major bioactive analytes in raw, wine-processed, and salt-processed Radix Achyranthis bidentatae (RAB. The results showed that this method exhibited desirable sensitivity, precision, stability, and repeatability. The overall intra-day and inter-day variations (RSD were in the range of 1.57–2.46 and 1.51–3.00%, respectively. The overall recoveries were 98.58–101.48% with a relative standard deviation (RSD of 0.01–1.86%. In addition, the developed approach was applied to 21 batches of raw, wine-processed, and salt-processed samples of RAB. Hierarchical clustering analysis (HCA, principal component analysis (PCA, heat map, and boxplot analysis were performed to evaluate the quality of raw, wine-processed, and salt-processed RAB collected from different regions. The chemometrics combined with the quantitative analysis based on UHPLC–MS/MS results indicated that the content of five analytes increased significantly in processed RAB compared to raw RAB.

Chemometric study of the effects of PtRu:BH4-molar ratio and solvent used in the preparation of PtRu/C electrocatalysts for for direct methanol fuel cell anodes

Energy Technology Data Exchange (ETDEWEB)

Polanco, N.S.O.; Neto, A.O.; Spinace, E.V. [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Tusi, M.M. [Universidade Regional Integrada do Alto Uruguai e das Missoes (URI), Santiago, RS (Brazil); Brandalise, M. [Instituto Federal Fluminense (IFF), Campos dos Goyracazes, RJ (Brazil)

2014-07-01

PtRu/C electrocatalysts were prepared by borohydride reduction method and a chemometric study was performed to evaluate the influence of the solvent (water and isopropyl alcohol) and amount of reducing agent (PtRu:BH4- molar ratios of 5 and 15) in maximum power density. In borohydride reduction method, a solution containing sodium hydroxide and sodium borohydride (NaBH4) is added to a mixture containing water, isopropyl alcohol, metallic precursors and the carbon support Vulcan XC72. The obtained materials were characterized by energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD) and transmission electron microscopy (TEM). Membrane Electrode Assemblies (MEA's) were produced and tests in single direct methanol fuel cells were performed. The amount of sodium borohydride used in the reduction showed more influence on the maximum power density than the change of solvent of the reaction. (author)

CHEMOMETRICS IN BIOANALYTICAL SAMPLE PREPARATION - A FRACTIONATED COMBINED MIXTURE AND FACTORIAL DESIGN FOR THE MODELING OF THE RECOVERY OF 5 TRICYCLIC AMINES FROM PLASMA AFTER LIQUID-LIQUID-EXTRACTION PRIOR TO HIGH-PERFORMANCE LIQUID-CHROMATOGRAPHY

NARCIS (Netherlands)

WIELING, J; MENSINK, CK; JONKMAN, JHG; COENEGRACHT, PMJ; DUINEVELD, CAA; DOORNBOS, DA

1993-01-01

A general systematic approach is described for the chemometric modelling of liquid-liquid extraction data of drugs from biological fluids. Extraction solvents were selected from Snyder's solvent selectivity triangle: methyl tert.-butyl ether, methylene chloride and chloroform. The composition of a

Gasoline classification using near infrared (NIR) spectroscopy data: Comparison of multivariate techniques

Energy Technology Data Exchange (ETDEWEB)

Balabin, Roman M., E-mail: balabin@org.chem.ethz.ch [Department of Chemistry and Applied Biosciences, ETH Zurich, 8093 Zurich (Switzerland); Safieva, Ravilya Z. [Gubkin Russian State University of Oil and Gas, 119991 Moscow (Russian Federation); Lomakina, Ekaterina I. [Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, 119992 Moscow (Russian Federation)

2010-06-25

Near infrared (NIR) spectroscopy is a non-destructive (vibrational spectroscopy based) measurement technique for many multicomponent chemical systems, including products of petroleum (crude oil) refining and petrochemicals, food products (tea, fruits, e.g., apples, milk, wine, spirits, meat, bread, cheese, etc.), pharmaceuticals (drugs, tablets, bioreactor monitoring, etc.), and combustion products. In this paper we have compared the abilities of nine different multivariate classification methods: linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), regularized discriminant analysis (RDA), soft independent modeling of class analogy (SIMCA), partial least squares (PLS) classification, K-nearest neighbor (KNN), support vector machines (SVM), probabilistic neural network (PNN), and multilayer perceptron (ANN-MLP) - for gasoline classification. Three sets of near infrared (NIR) spectra (450, 415, and 345 spectra) were used for classification of gasolines into 3, 6, and 3 classes, respectively, according to their source (refinery or process) and type. The 14,000-8000 cm{sup -1} NIR spectral region was chosen. In all cases NIR spectroscopy was found to be effective for gasoline classification purposes, when compared with nuclear magnetic resonance (NMR) spectroscopy or gas chromatography (GC). KNN, SVM, and PNN techniques for classification were found to be among the most effective ones. Artificial neural network (ANN-MLP) approach based on principal component analysis (PCA), which was believed to be efficient, has shown much worse results. We hope that the results obtained in this study will help both further chemometric (multivariate data analysis) investigations and investigations in the sphere of applied vibrational (infrared/IR, near-IR, and Raman) spectroscopy of sophisticated multicomponent systems.

Gasoline classification using near infrared (NIR) spectroscopy data: Comparison of multivariate techniques

International Nuclear Information System (INIS)

Balabin, Roman M.; Safieva, Ravilya Z.; Lomakina, Ekaterina I.

2010-01-01

Near infrared (NIR) spectroscopy is a non-destructive (vibrational spectroscopy based) measurement technique for many multicomponent chemical systems, including products of petroleum (crude oil) refining and petrochemicals, food products (tea, fruits, e.g., apples, milk, wine, spirits, meat, bread, cheese, etc.), pharmaceuticals (drugs, tablets, bioreactor monitoring, etc.), and combustion products. In this paper we have compared the abilities of nine different multivariate classification methods: linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), regularized discriminant analysis (RDA), soft independent modeling of class analogy (SIMCA), partial least squares (PLS) classification, K-nearest neighbor (KNN), support vector machines (SVM), probabilistic neural network (PNN), and multilayer perceptron (ANN-MLP) - for gasoline classification. Three sets of near infrared (NIR) spectra (450, 415, and 345 spectra) were used for classification of gasolines into 3, 6, and 3 classes, respectively, according to their source (refinery or process) and type. The 14,000-8000 cm -1 NIR spectral region was chosen. In all cases NIR spectroscopy was found to be effective for gasoline classification purposes, when compared with nuclear magnetic resonance (NMR) spectroscopy or gas chromatography (GC). KNN, SVM, and PNN techniques for classification were found to be among the most effective ones. Artificial neural network (ANN-MLP) approach based on principal component analysis (PCA), which was believed to be efficient, has shown much worse results. We hope that the results obtained in this study will help both further chemometric (multivariate data analysis) investigations and investigations in the sphere of applied vibrational (infrared/IR, near-IR, and Raman) spectroscopy of sophisticated multicomponent systems.

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

FT-Raman and chemometric tools for rapid determination of quality parameters in milk powder: Classification of samples for the presence of lactose and fraud detection by addition of maltodextrin.

Science.gov (United States)

Rodrigues Júnior, Paulo Henrique; de Sá Oliveira, Kamila; de Almeida, Carlos Eduardo Rocha; De Oliveira, Luiz Fernando Cappa; Stephani, Rodrigo; Pinto, Michele da Silva; de Carvalho, Antônio Fernandes; Perrone, Ítalo Tuler

2016-04-01

FT-Raman spectroscopy has been explored as a quick screening method to evaluate the presence of lactose and identify milk powder samples adulterated with maltodextrin (2.5-50% w/w). Raman measurements can easily differentiate samples of milk powder, without the need for sample preparation, while traditional quality control methods, including high performance liquid chromatography, are cumbersome and slow. FT-Raman spectra were obtained from samples of whole lactose and low-lactose milk powder, both without and with addition of maltodextrin. Differences were observed between the spectra involved in identifying samples with low lactose content, as well as adulterated samples. Exploratory data analysis using Raman spectroscopy and multivariate analysis was also developed to classify samples with PCA and PLS-DA. The PLS-DA models obtained allowed to correctly classify all samples. These results demonstrate the utility of FT-Raman spectroscopy in combination with chemometrics to infer about the quality of milk powder. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Simultaneous spectrophotometric determination of copper, cobalt, nickel and iron in foodstuffs and vegetables with a new bis thiosemicarbazone ligand using chemometric approaches.

Science.gov (United States)

Rohani Moghadam, Masoud; Poorakbarian Jahromi, Sayedeh Maria; Darehkordi, Ali

2016-02-01

A newly synthesized bis thiosemicarbazone ligand, (2Z,2'Z)-2,2'-((4S,5R)-4,5,6-trihydroxyhexane-1,2-diylidene)bis(N-phenylhydrazinecarbothioamide), was used to make a complex with Cu(2+), Ni(2+), Co(2+) and Fe(3+) for their simultaneous spectrophotometric determination using chemometric methods. By Job's method, the ratio of metal to ligand in Ni(2+) was found to be 1:2, whereas it was 1:4 for the others. The effect of pH on the sensitivity and selectivity of the formed complexes was studied according to the net analyte signal (NAS). Under optimum conditions, the calibration graphs were linear in the ranges of 0.10-3.83, 0.20-3.83, 0.23-5.23 and 0.32-8.12 mg L(-1) with the detection limits of 2, 3, 4 and 10 μg L(-1) for Cu(2+), Co(2+), Ni(2+) and Fe(3+) respectively. The OSC-PLS1 for Cu(2+) and Ni(2+), the PLS1 for Co(2+) and the PC-FFANN for Fe(3+) were selected as the best models. The selected models were successfully applied for the simultaneous determination of elements in some foodstuffs and vegetables. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dataset of Fourier transform-infrared coupled with chemometric analysis used to distinguish accessions of Garcinia mangostana L. in Peninsular Malaysia

Directory of Open Access Journals (Sweden)

Sri A’jilah Samsir

2016-09-01

Full Text Available In this dataset, we distinguish 15 accessions of Garcinia mangostana from Peninsular Malaysia using Fourier transform-infrared spectroscopy coupled with chemometric analysis. We found that the position and intensity of characteristic peaks at 3600–3100 cm−1 in IR spectra allowed discrimination of G. mangostana from different locations. Further principal component analysis (PCA of all the accessions suggests the two main clusters were formed: samples from Johor, Melaka, and Negeri Sembilan (South were clustered together in one group while samples from Perak, Kedah, Penang, Selangor, Kelantan, and Terengganu (North and East Coast were in another clustered group. Keywords: Apomictic, Mangosteen, Fourier Transformed-Infrared, Peninsular Malaysia

Authentication and distinction of Shenmai injection with HPLC fingerprint analysis assisted by pattern recognition techniques

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Xue-Feng Lu

2012-10-01

Full Text Available In this paper, the feasibility and advantages of employing high performance liquid chromatographic (HPLC fingerprints combined with pattern recognition techniques for quality control of Shenmai injection were investigated and demonstrated. The Similarity Evaluation System was employed to evaluate the similarities of samples of Shenmai injection, and the HPLC generated chromatographic data were analyzed using hierarchical clustering analysis (HCA and soft independent modeling of class analogy (SIMCA. Consistent results were obtained to show that the authentic samples and the blended samples were successfully classified by SIMCA, which could be applied to accurate discrimination and quality control of Shenmai injection. Furthermore, samples could also be grouped in accordance with manufacturers. Our results revealed that the developed method has potential perspective for the original discrimination and quality control of Shenmai injection. Keywords: Shenmai injection, High performance liquid chromatography, Fingerprint, Pattern recognition

Solid phase excitation-emission fluorescence method for the classification of complex substances: Cortex Phellodendri and other traditional Chinese medicines as examples.

Science.gov (United States)

Gu, Yao; Ni, Yongnian; Kokot, Serge

2012-09-13

A novel, simple and direct fluorescence method for analysis of complex substances and their potential substitutes has been researched and developed. Measurements involved excitation and emission (EEM) fluorescence spectra of powdered, complex, medicinal herbs, Cortex Phellodendri Chinensis (CPC) and the similar Cortex Phellodendri Amurensis (CPA); these substances were compared and discriminated from each other and the potentially adulterated samples (Caulis mahoniae (CM) and David poplar bark (DPB)). Different chemometrics methods were applied for resolution of the complex spectra, and the excitation spectra were found to be the most informative; only the rank-ordering PROMETHEE method was able to classify the samples with single ingredients (CPA, CPC, CM) or those with binary mixtures (CPA/CPC, CPA/CM, CPC/CM). Interestingly, it was essential to use the geometrical analysis for interactive aid (GAIA) display for a full understanding of the classification results. However, these two methods, like the other chemometrics models, were unable to classify composite spectral matrices consisting of data from samples of single ingredients and binary mixtures; this suggested that the excitation spectra of the different samples were very similar. However, the method is useful for classification of single-ingredient samples and, separately, their binary mixtures; it may also be applied for similar classification work with other complex substances.

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.

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.

Chemometric classification of apple juices according to variety and geographical origin based on polyphenolic profiles.

Science.gov (United States)

Guo, Jing; Yue, Tianli; Yuan, Yahong; Wang, Yutang

2013-07-17

To characterize and classify apple juices according to apple variety and geographical origin on the basis of their polyphenol composition, the polyphenolic profiles of 58 apple juice samples belonging to 5 apple varieties and from 6 regions in Shaanxi province of China were assessed. Fifty-one of the samples were from protected designation of origin (PDO) districts. Polyphenols were determined by high-performance liquid chromatography coupled to photodiode array detection (HPLC-PDA) and to a Q Exactive quadrupole-Orbitrap mass spectrometer. Chemometric techniques including principal component analysis (PCA) and stepwise linear discriminant analysis (SLDA) were carried out on polyphenolic profiles of the samples to develop discrimination models. SLDA achieved satisfactory discriminations of apple juices according to variety and geographical origin, providing respectively 98.3 and 91.2% success rate in terms of prediction ability. This result demonstrated that polyphenols could served as characteristic indices to verify the variety and geographical origin of apple juices.

Differentiation of fresh and frozen-thawed fish samples using Raman spectroscopy coupled with chemometric analysis.

Science.gov (United States)

Velioğlu, Hasan Murat; Temiz, Havva Tümay; Boyaci, Ismail Hakki

2015-04-01

The potential of Raman spectroscopy was investigated in terms of its capability to discriminate the species of the fish samples and determine their freshness according to the number of freezing/thawing cycles they exposed. Species discrimination analysis was carried out on sixty-four fish samples from six different species, namely horse mackerel (Trachurus trachurus), European anchovy (Engraulis encrasicolus), red mullet (Mullus surmuletus), Bluefish (Pomatamus saltatrix), Atlantic salmon (Salmo salar) and flying gurnard (Trigla lucerna). Afterwards, fish samples were exposed to different numbers of freezing/thawing cycles and separated into three batches, namely (i) fresh, (ii) once frozen-thawed (OF) and (iii) twice frozen-thawed (TF) samples, in order to perform the freshness analysis. Raman data collected were used as inputs for chemometric analysis, which enabled us to develop two main PCA models to successfully terminate the studies for both species discrimination and freshness determination analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

Analysis of the polymeric fractions of scrap from mobile phones using laser-induced breakdown spectroscopy: chemometric applications for better data interpretation.

Science.gov (United States)

Aquino, Francisco W B; Pereira-Filho, Edenir R

2015-03-01

Because of their short life span and high production and consumption rates, mobile phones are one of the contributors to WEEE (waste electrical and electronic equipment) growth in many countries. If incorrectly managed, the hazardous materials used in the assembly of these devices can pollute the environment and pose dangers for workers involved in the recycling of these materials. In this study, 144 polymer fragments originating from 50 broken or obsolete mobile phones were analyzed via laser-induced breakdown spectroscopy (LIBS) without previous treatment. The coated polymers were mainly characterized by the presence of Ag, whereas the uncoated polymers were related to the presence of Al, K, Na, Si and Ti. Classification models were proposed using black and white polymers separately in order to identify the manufacturer and origin using KNN (K-nearest neighbor), SIMCA (Soft Independent Modeling of Class Analogy) and PLS-DA (Partial Least Squares for Discriminant Analysis). For the black polymers the percentage of correct predictions was, in average, 58% taking into consideration the models for manufacturer and origin identification. In the case of white polymers, the percentage of correct predictions ranged from 72.8% (PLS-DA) to 100% (KNN). Copyright © 2014 Elsevier B.V. All rights reserved.

Detection and differentiation of bacterial spores in a mineral matrix by Fourier transform infrared spectroscopy (FTIR and chemometrical data treatment

Directory of Open Access Journals (Sweden)

Brandes Ammann Andrea

2011-07-01

Full Text Available Abstract Background Fourier transform infrared spectroscopy (FTIR has been used as analytical tool in chemistry for many years. In addition, FTIR can also be applied as a rapid and non-invasive method to detect and identify microorganisms. The specific and fingerprint-like spectra allow - under optimal conditions - discrimination down to the species level. The aim of this study was to develop a fast and reproducible non-molecular method to differentiate pure samples of Bacillus spores originating from different species as well as to identify spores in a simple matrix, such as the clay mineral, bentonite. Results We investigated spores from pure cultures of seven different Bacillus species by FTIR in reflection or transmission mode followed by chemometrical data treatment. All species investigated (B. atrophaeus, B. brevis, B. circulans, B. lentus, B. megaterium, B. subtilis, B. thuringiensis are typical aerobic soil-borne spore formers. Additionally, a solid matrix (bentonite and mixtures of benonite with spores of B. megaterium at various wt/wt ratios were included in the study. Both hierarchical cluster analysis and principal component analysis of the spectra along with multidimensional scaling allowed the discrimination of different species and spore-matrix-mixtures. Conclusions Our results show that FTIR spectroscopy is a fast method for species-level discrimination of Bacillus spores. Spores were still detectable in the presence of the clay mineral bentonite. Even a tenfold excess of bentonite (corresponding to 2.1 × 1010 colony forming units per gram of mineral matrix still resulted in an unambiguous identification of B. megaterium spores.

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.

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®

Chemometric study of Andalusian extra virgin olive oils Raman spectra: Qualitative and quantitative information.

Science.gov (United States)

Sánchez-López, E; Sánchez-Rodríguez, M I; Marinas, A; Marinas, J M; Urbano, F J; Caridad, J M; Moalem, M

2016-08-15

Authentication of extra virgin olive oil (EVOO) is an important topic for olive oil industry. The fraudulent practices in this sector are a major problem affecting both producers and consumers. This study analyzes the capability of FT-Raman combined with chemometric treatments of prediction of the fatty acid contents (quantitative information), using gas chromatography as the reference technique, and classification of diverse EVOOs as a function of the harvest year, olive variety, geographical origin and Andalusian PDO (qualitative information). The optimal number of PLS components that summarizes the spectral information was introduced progressively. For the estimation of the fatty acid composition, the lowest error (both in fitting and prediction) corresponded to MUFA, followed by SAFA and PUFA though such errors were close to zero in all cases. As regards the qualitative variables, discriminant analysis allowed a correct classification of 94.3%, 84.0%, 89.0% and 86.6% of samples for harvest year, olive variety, geographical origin and PDO, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

Diagnosis of oral lichen planus from analysis of saliva samples using terahertz time-domain spectroscopy and chemometrics

Science.gov (United States)

Kistenev, Yury V.; Borisov, Alexey V.; Titarenko, Maria A.; Baydik, Olga D.; Shapovalov, Alexander V.

2018-04-01

The ability to diagnose oral lichen planus (OLP) based on saliva analysis using THz time-domain spectroscopy and chemometrics is discussed. The study involved 30 patients (2 male and 28 female) with OLP. This group consisted of two subgroups with the erosive form of OLP (n = 15) and with the reticular and papular forms of OLP (n = 15). The control group consisted of six healthy volunteers (one male and five females) without inflammation in the mucous membrane in the oral cavity and without periodontitis. Principal component analysis was used to reveal informative features in the experimental data. The one-versus-one multiclass classifier using support vector machine binary classifiers was used. The two-stage classification approach using several absorption spectra scans for an individual saliva sample provided 100% accuracy of differential classification between OLP subgroups and control group.

Authentication of Whey Protein Powders by Portable Mid-Infrared Spectrometers Combined with Pattern Recognition Analysis.

Science.gov (United States)

Wang, Ting; Tan, Siow Ying; Mutilangi, William; Aykas, Didem P; Rodriguez-Saona, Luis E

2015-10-01

The objective of this study was to develop a simple and rapid method to differentiate whey protein types (WPC, WPI, and WPH) used for beverage manufacturing by combining the spectral signature collected from portable mid-infrared spectrometers and pattern recognition analysis. Whey protein powders from different suppliers are produced using a large number of processing and compositional variables, resulting in variation in composition, concentration, protein structure, and thus functionality. Whey protein powders including whey protein isolates, whey protein concentrates and whey protein hydrolysates were obtained from different suppliers and their spectra collected using portable mid-infrared spectrometers (single and triple reflection) by pressing the powder onto an Attenuated Total Reflectance (ATR) diamond crystal with a pressure clamp. Spectra were analyzed by soft independent modeling of class analogy (SIMCA) generating a classification model showing the ability to differentiate whey protein types by forming tight clusters with interclass distance values of >3, considered to be significantly different from each other. The major bands centered at 1640 and 1580 cm(-1) were responsible for separation and were associated with differences in amide I and amide II vibrations of proteins, respectively. Another important band in whey protein clustering was associated with carboxylate vibrations of acidic amino acids (∼1570 cm(-1)). The use of a portable mid-IR spectrometer combined with pattern recognition analysis showed potential for discriminating whey protein ingredients that can help to streamline the analytical procedure so that it is more applicable for field-based screening of ingredients. A rapid, simple and accurate method was developed to authenticate commercial whey protein products by using portable mid-infrared spectrometers combined with chemometrics, which could help ensure the functionality of whey protein ingredients in food applications. © 2015

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)

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.

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).

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.

Multi-Response Extraction Optimization Based on Anti-Oxidative Activity and Quality Evaluation by Main Indicator Ingredients Coupled with Chemometric Analysis on Thymus quinquecostatus Celak.

Science.gov (United States)

Chang, Yan-Li; Shen, Meng; Ren, Xue-Yang; He, Ting; Wang, Le; Fan, Shu-Sheng; Wang, Xiu-Huan; Li, Xiao; Wang, Xiao-Ping; Chen, Xiao-Yi; Sui, Hong; She, Gai-Mei

2018-04-19

Thymus quinquecostatus Celak is a species of thyme in China and it used as condiment and herbal medicine for a long time. To set up the quality evaluation of T. quinquecostatus , the response surface methodology (RSM) based on its 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity was introduced to optimize the extraction condition, and the main indicator components were found through an UPLC-LTQ-Orbitrap MS n method. The ethanol concentration, solid-liquid ratio, and extraction time on optimum conditions were 42.32%, 1:17.51, and 1.8 h, respectively. 35 components having 12 phenolic acids and 23 flavonoids were unambiguously or tentatively identified both positive and negative modes to employ for the comprehensive analysis in the optimum anti-oxidative part. A simple, reliable, and sensitive HPLC method was performed for the multi-component quantitative analysis of T. quinquecostatus using six characteristic and principal phenolic acids and flavonoids as reference compounds. Furthermore, the chemometrics methods (principal components analysis (PCA) and hierarchical clustering analysis (HCA)) appraised the growing areas and harvest time of this herb closely relative to the quality-controlled. This study provided full-scale qualitative and quantitative information for the quality evaluation of T. quinquecostatus , which would be a valuable reference for further study and development of this herb and related laid the foundation of further study on its pharmacological efficacy.

Multivariate Approaches for Simultaneous Determination of Avanafil and Dapoxetine by UV Chemometrics and HPLC-QbD in Binary Mixtures and Pharmaceutical Product.

Science.gov (United States)

2016-04-07

Multivariate UV-spectrophotometric methods and Quality by Design (QbD) HPLC are described for concurrent estimation of avanafil (AV) and dapoxetine (DP) in the binary mixture and in the dosage form. Chemometric methods have been developed, including classical least-squares, principal component regression, partial least-squares, and multiway partial least-squares. Analytical figures of merit, such as sensitivity, selectivity, analytical sensitivity, LOD, and LOQ were determined. QbD consists of three steps, starting with the screening approach to determine the critical process parameter and response variables. This is followed by understanding of factors and levels, and lastly the application of a Box-Behnken design containing four critical factors that affect the method. From an Ishikawa diagram and a risk assessment tool, four main factors were selected for optimization. Design optimization, statistical calculation, and final-condition optimization of all the reactions were Carried out. Twenty-five experiments were done, and a quadratic model was used for all response variables. Desirability plot, surface plot, design space, and three-dimensional plots were calculated. In the optimized condition, HPLC separation was achieved on Phenomenex Gemini C18 column (250 × 4.6 mm, 5 μm) using acetonitrile-buffer (ammonium acetate buffer at pH 3.7 with acetic acid) as a mobile phase at flow rate of 0.7 mL/min. Quantification was done at 239 nm, and temperature was set at 20°C. The developed methods were validated and successfully applied for simultaneous determination of AV and DP in the dosage form.

Rapid monitoring of the spoilage of minced beef stored under conventionally and active packaging conditions using Fourier transform infrared spectroscopy in tandem with chemometrics.

Science.gov (United States)

Ammor, Mohammed Salim; Argyri, Anthoula; Nychas, George-John E

2009-03-01

Fourier transform infrared (FTIR) spectroscopy was exploited to measure biochemical changes within fresh minced beef in an attempt to rapidly monitor beef spoilage. Minced beef packaged either aerobically, under modified atmosphere and using an active packaging were held from freshness to spoilage at 0, 5, 10, and 15°C. Frequent FTIR measurements were collected directly from the sample surface using attenuated total reflectance, in parallel the total viable counts of bacteria, the sensory quality and the pH were also determined. Principal components analysis allowed illuminating the wavenumbers potentially correlated with the spoilage process. Qualitative interpretation of spectral data was carried out using discriminant factorial analysis and used to corroborate sensory data and to accurately determine samples freshness and packaging. Partial least-squares regressions permitted estimates of bacterial loads and pH values from the spectral data with a fit of R(2)=0.80 for total viable counts and fit of R(2)=0.92 for the pH. Obtained results demonstrated that a FTIR spectrum may be considered as a metabolic fingerprint and that the method in tandem with chemometrics represents a powerful, rapid, economical and non-invasive method for monitoring minced beef freshness regardless the storage conditions (e.g. packaging and temperature).

Data preprocessing methods of FT-NIR spectral data for the classification cooking oil

Science.gov (United States)

Ruah, Mas Ezatul Nadia Mohd; Rasaruddin, Nor Fazila; Fong, Sim Siong; Jaafar, Mohd Zuli

2014-12-01

This recent work describes the data pre-processing method of FT-NIR spectroscopy datasets of cooking oil and its quality parameters with chemometrics method. Pre-processing of near-infrared (NIR) spectral data has become an integral part of chemometrics modelling. Hence, this work is dedicated to investigate the utility and effectiveness of pre-processing algorithms namely row scaling, column scaling and single scaling process with Standard Normal Variate (SNV). The combinations of these scaling methods have impact on exploratory analysis and classification via Principle Component Analysis plot (PCA). The samples were divided into palm oil and non-palm cooking oil. The classification model was build using FT-NIR cooking oil spectra datasets in absorbance mode at the range of 4000cm-1-14000cm-1. Savitzky Golay derivative was applied before developing the classification model. Then, the data was separated into two sets which were training set and test set by using Duplex method. The number of each class was kept equal to 2/3 of the class that has the minimum number of sample. Then, the sample was employed t-statistic as variable selection method in order to select which variable is significant towards the classification models. The evaluation of data pre-processing were looking at value of modified silhouette width (mSW), PCA and also Percentage Correctly Classified (%CC). The results show that different data processing strategies resulting to substantial amount of model performances quality. The effects of several data pre-processing i.e. row scaling, column standardisation and single scaling process with Standard Normal Variate indicated by mSW and %CC. At two PCs model, all five classifier gave high %CC except Quadratic Distance Analysis.

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)

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)

Multivariate Analyses and Evaluation of Heavy Metals by Chemometric BCR Sequential Extraction Method in Surface Sediments from Lingdingyang Bay, South China

Directory of Open Access Journals (Sweden)

Linglong Cao

2015-04-01

Full Text Available Sediments in estuary areas are recognized as the ultimate reservoirs for numerous contaminants, e.g., toxic metals. Multivariate analyses by chemometric evaluation were performed to classify metal ions (Cu, Zn, As, Cr, Pb, Ni and Cd in superficial sediments from Lingdingyang Bay and to determine whether or not there were potential contamination risks based on the BCR sequential extraction scheme. The results revealed that Cd was mainly in acid-soluble form with an average of 75.99% of its total contents and thus of high potential availability, indicating significant anthropogenic sources, while Cr, As, Ni were enriched in the residual fraction which could be considered as the safest ingredients to the environment. According to the proportion of secondary to primary phases (KRSP, Cd had the highest bioavailable fraction and represented high or very high risk, followed by Pb and Cu with medium risks in most of samples. The combined evaluation of the Pollution Load Index (PLI and the mean Effect Range Median Quotient (mERM-Q highlighted that the greatest potential environmental risk area was in the northwest of Lingdingyang Bay. Almost all of the sediments had a 21% probability of toxicity. Additionally, Principal Component Analysis (PCA revealed that the survey region was significantly affected by two main sources of anthropogenic contributions: PC1 showed increased loadings of variables in acid-soluble and reducible fractions that were consistent with the input from industrial wastes (such as manufacturing, metallurgy, chemical industry and domestic sewages; PC2 was characterized by increased loadings of variables in residual fraction that could be attributed to leaching and weathering of parent rocks. The results obtained demonstrated the need for appropriate remediation measures to alleviate soil pollution problem due to the more aggregation of potentially risky metals. Therefore, it is of crucial significance to implement the targeted

Influence of genotype and crop year in the chemometrics of almond and pistachio oils.

Science.gov (United States)

Rabadán, Adrián; Álvarez-Ortí, Manuel; Gómez, Ricardo; de Miguel, Concepción; Pardo, José E

2018-04-01

Almond and pistachio oils can be considered as interesting products to produce and commercialize owing to their health-promoting properties. However, these properties are not consistent because of the differences that appear in oils as a result of the genotype and the crop year. The analysis of these variations and their origin is decisive in ensuring the commercial future prospects of these nut oils. Although significant variability has been reported in almond and pistachio oils as a result of the crop year and the interaction between crop year and genotype, the genotype itself remains the main factor determining oil chemometrics. Oil fatty acid profile has been mainly determined by the genotype, with the exception of palmitic fatty acid in pistachio oil. However, the crop year affects the concentration of some minor components of crucial nutritional interest as total polyphenols and phytosterols. Regarding reported differences in oil, some almond and pistachio genotypes should be prioritized for oil extraction. Breeding programmes focused on the improvement of specific characteristics of almond and pistachio oils should focus on chemical parameters mainly determined by the genotype. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

[Application of FT-IR pattern recognition method for the quality control of pharmaceutical ingredients].

Science.gov (United States)

Horgos, József; Kóger, Péter; Zelkó, Romána

2009-01-01

Nowadays infrared spectroscopy and chemometrics have proven their effectiveness for both qualitative and quantitative analyses in different fields like agriculture, food, chemical and oil industry. Furier Transformation Infrared Spectroscopy (FT-IR) combined with Attenuated Total Reflectance (ATR) plate is a fast identification instrument. It is suitable for analysis of solid and liquid phase, too. Associated with chemometrics, it would be a powerful tool for the pharmaceutical wholesalers to detect the insufficient quality of pharmaceutical ingredients. In the present study beside the review of the infra red technology, pharmaceutical ingredients were examined with the help of our spectra library.

Feature Fusion of ICP-AES, UV-Vis and FT-MIR for Origin Traceability of Boletus edulis Mushrooms in Combination with Chemometrics.

Science.gov (United States)

Qi, Luming; Liu, Honggao; Li, Jieqing; Li, Tao; Wang, Yuanzhong

2018-01-15

Origin traceability is an important step to control the nutritional and pharmacological quality of food products. Boletus edulis mushroom is a well-known food resource in the world. Its nutritional and medicinal properties are drastically varied depending on geographical origins. In this study, three sensor systems (inductively coupled plasma atomic emission spectrophotometer (ICP-AES), ultraviolet-visible (UV-Vis) and Fourier transform mid-infrared spectroscopy (FT-MIR)) were applied for the origin traceability of 192 mushroom samples (caps and stipes) in combination with chemometrics. The difference between cap and stipe was clearly illustrated based on a single sensor technique, respectively. Feature variables from three instruments were used for origin traceability. Two supervised classification methods, partial least square discriminant analysis (FLS-DA) and grid search support vector machine (GS-SVM), were applied to develop mathematical models. Two steps (internal cross-validation and external prediction for unknown samples) were used to evaluate the performance of a classification model. The result is satisfactory with high accuracies ranging from 90.625% to 100%. These models also have an excellent generalization ability with the optimal parameters. Based on the combination of three sensory systems, our study provides a multi-sensory and comprehensive origin traceability of B. edulis mushrooms.

Feature Fusion of ICP-AES, UV-Vis and FT-MIR for Origin Traceability of Boletus edulis Mushrooms in Combination with Chemometrics

Directory of Open Access Journals (Sweden)

Luming Qi

2018-01-01

Full Text Available Origin traceability is an important step to control the nutritional and pharmacological quality of food products. Boletus edulis mushroom is a well-known food resource in the world. Its nutritional and medicinal properties are drastically varied depending on geographical origins. In this study, three sensor systems (inductively coupled plasma atomic emission spectrophotometer (ICP-AES, ultraviolet-visible (UV-Vis and Fourier transform mid-infrared spectroscopy (FT-MIR were applied for the origin traceability of 184 mushroom samples (caps and stipes in combination with chemometrics. The difference between cap and stipe was clearly illustrated based on a single sensor technique, respectively. Feature variables from three instruments were used for origin traceability. Two supervised classification methods, partial least square discriminant analysis (FLS-DA and grid search support vector machine (GS-SVM, were applied to develop mathematical models. Two steps (internal cross-validation and external prediction for unknown samples were used to evaluate the performance of a classification model. The result is satisfactory with high accuracies ranging from 90.625% to 100%. These models also have an excellent generalization ability with the optimal parameters. Based on the combination of three sensory systems, our study provides a multi-sensory and comprehensive origin traceability of B. edulis mushrooms.

Detection of sunn pest-damaged wheat samples using visible/near-infrared spectroscopy based on pattern recognition.

Science.gov (United States)

Basati, Zahra; Jamshidi, Bahareh; Rasekh, Mansour; Abbaspour-Gilandeh, Yousef

2018-05-30

The presence of sunn pest-damaged grains in wheat mass reduces the quality of flour and bread produced from it. Therefore, it is essential to assess the quality of the samples in collecting and storage centers of wheat and flour mills. In this research, the capability of visible/near-infrared (Vis/NIR) spectroscopy combined with pattern recognition methods was investigated for discrimination of wheat samples with different percentages of sunn pest-damaged. To this end, various samples belonging to five classes (healthy and 5%, 10%, 15% and 20% unhealthy) were analyzed using Vis/NIR spectroscopy (wavelength range of 350-1000 nm) based on both supervised and unsupervised pattern recognition methods. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) as the unsupervised techniques and soft independent modeling of class analogies (SIMCA) and partial least squares-discriminant analysis (PLS-DA) as supervised methods were used. The results showed that Vis/NIR spectra of healthy samples were correctly clustered using both PCA and HCA. Due to the high overlapping between the four unhealthy classes (5%, 10%, 15% and 20%), it was not possible to discriminate all the unhealthy samples in individual classes. However, when considering only the two main categories of healthy and unhealthy, an acceptable degree of separation between the classes can be obtained after classification with supervised pattern recognition methods of SIMCA and PLS-DA. SIMCA based on PCA modeling correctly classified samples in two classes of healthy and unhealthy with classification accuracy of 100%. Moreover, the power of the wavelengths of 839 nm, 918 nm and 995 nm were more than other wavelengths to discriminate two classes of healthy and unhealthy. It was also concluded that PLS-DA provides excellent classification results of healthy and unhealthy samples (R 2  = 0.973 and RMSECV = 0.057). Therefore, Vis/NIR spectroscopy based on pattern recognition techniques

Multi-block methods in multivariate process control

DEFF Research Database (Denmark)

Kohonen, J.; Reinikainen, S.P.; Aaljoki, K.

2008-01-01

methods the effect of a sub-process can be seen and an example with two blocks, near infra-red, NIR, and process data, is shown. The results show improvements in modelling task, when a MB-based approach is used. This way of working with data gives more information on the process than if all data...... are in one X-matrix. The procedure is demonstrated by an industrial continuous process, where knowledge about the sub-processes is available and X-matrix can be divided into blocks between process variables and NIR spectra.......In chemometric studies all predictor variables are usually collected in one data matrix X. This matrix is then analyzed by PLS regression or other methods. When data from several different sub-processes are collected in one matrix, there is a possibility that the effects of some sub-processes may...

Determination of toxic and essential trace elements in serum of healthy and hypothyroid respondents by ICP-MS: A chemometric approach for discrimination of hypothyroidism.

Science.gov (United States)

Stojsavljević, Aleksandar; Trifković, Jelena; Rasić-Milutinović, Zorica; Jovanović, Dragana; Bogdanović, Gradimir; Mutić, Jelena; Manojlović, Dragan

2018-07-01

Inductively coupled plasma-mass spectrometry ((ICP-MS)) was used to determine three toxic (Ni, As, Cd) and six essential trace elements (Cr, Mn, Co, Cu, Zn, Se) in blood serum of patients with hypothyroidism (Hy group) and healthy people (control group), in order to set the experimental conditions for accurate determination of a unique profile of these elements in hypothyroidism. Method validation was performed with standard reference material of the serum by varying the sample treatment with both standard and collision mode for analysis of elements isotopes. Quadratic curvilinear functions with good performances of models and the lowest detection limits were obtained for 52 Cr, 66 Zn, 75 As, 112 Cd in collision mode, and 55 Mn, 59 Co, 60 Ni, 65 Cu, 78 Se in standard mode. Treatment of serum samples with aqueous solution containing nitric acid, Triton X-100 and n-butanol gave the best results. Chemometric tools were applied for discrimination of patients with hypothyroidism. All nine elements discriminated Hy group of samples with almost the same discriminating power as indicated by their higher values for this group of patients. Statistically significant correlation (p hypothyroid state. Copyright © 2018 Elsevier GmbH. All rights reserved.

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

Science.gov (United States)

2013-01-01

Background 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. Results 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. Conclusion 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

Application of high performance liquid chromatography for the profiling of complex chemical mixtures with the aid of chemometrics.

Science.gov (United States)

Ni, Yongnian; Zhang, Liangsheng; Churchill, Jane; Kokot, Serge

2007-06-15

In this paper, chemometrics methods were applied to resolve the high performance liquid chromatography (HPLC) fingerprints of complex, many-component substances to compare samples from a batch from a given manufacturer, or from those of different producers. As an example of such complex substances, we used a common Chinese traditional medicine, Huoxiang Zhengqi Tincture (HZT) for this research. Twenty-one samples, each representing a separate HZT production batch from one of three manufacturers were analyzed by HPLC with the aid of a diode array detector (DAD). An Agilent Zorbax Eclipse XDB-C18 column with an Agilent Zorbax high pressure reliance cartridge guard-column were used. The mobile phase consisted of water (A) and methanol (B) with a gradient program of 25-65% (v/v, B) during 0-30min, 65-55% (v/v, B) during 30-35min and 55-100% (v/v, B) during 35-60min (flow rate, 1.0mlmin(-1); injection volume, 20mul; and column temperature-ambient). The detection wavelength was adjusted for maximum sensitivity at different time periods. A peak area matrix with 21objectsx14HPLC variables was obtained by sampling each chromatogram at 14 common retention times. Similarities were then calculated to discriminate the batch-to-batch samples and also, a more informative multi-criteria decision making methodology (MCDM), PROMETHEE and GAIA, was applied to obtain more information from the chromatograms in order to rank and compare the complex HZT profiles. The results showed that with the MCDM analysis, it was possible to match and discriminate correctly the batch samples from the three different manufacturers. Fourier transform infrared (FT-IR) spectra taken from samples from several batches were compared by the common similarity method with the HPLC results. It was found that the FT-IR spectra did not discriminate the samples from the different batches.

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

Absolutely nondestructive discrimination of Huoshan Dendrobium nobile species with miniature near-infrared (NIR) spectrometer engine.

Science.gov (United States)

Hu, Tian; Yang, Hai-Long; Tang, Qing; Zhang, Hui; Nie, Lei; Li, Lian; Wang, Jin-Feng; Liu, Dong-Ming; Jiang, Wei; Wang, Fei; Zang, Heng-Chang

2014-10-01

As one very precious traditional Chinese medicine (TCM), Huoshan Dendrobium has not only high price, but also significant pharmaceutical efficacy. However, different species of Huoshan Dendrobium exhibit considerable difference in pharmaceutical efficacy, so rapid and absolutely non-destructive discrimination of Huoshan Dendrobium nobile according to different species is crucial to quality control and pharmaceutical effect. In this study, as one type of miniature near-infrared (NIR) spectrometer, MicroNIR 1700 was used for absolutely nondestructive determination of NIR spectra of 90 batches of Dendrobium from five species of differ- ent commodity grades. The samples were intact and not smashed. Soft independent modeling of class analogy (SIMCA) pattern recognition based on principal component analysis (PCA) was used to classify and recognize different species of Dendrobium samples. The results indicated that the SIMCA qualitative models established with pretreatment method of standard normal variate transformation (SNV) in the spectra range selected by Qs method had 100% recognition rates and 100% rejection rates. This study demonstrated that a rapid and absolutely non-destructive analytical technique based on MicroNIR 1700 spectrometer was developed for successful discrimination of five different species of Huoshan Dendrobium with acceptable accuracy.

Exploring abiotic stress on asynchronous protein metabolism in single kernels of wheat studied by NMR spectroscopy and chemometrics

DEFF Research Database (Denmark)

Winning, H.; Viereck, N.; Wollenweber, B.

2009-01-01

at the vegetative growth stage had little effect on the parameters investigated. For the first time, H-1 HR-MAS NMR spectra of grains taken during grain-filling were analysed by an advanced multiway model. In addition to the results from the chemical protein analysis and the H-1 HR-MAS NMR spectra of single kernels...... was to examine the implications of different drought treatments on the protein fractions in grains of winter wheat using H-1 nuclear magnetic resonance spectroscopy followed by chemometric analysis. Triticum aestivum L. cv. Vinjett was studied in a semi-field experiment and subjected to drought episodes either...... at terminal spikelet, during grain-filling or at both stages. Principal component trajectories of the total protein content and the protein fractions of flour as well as the H-1 NMR spectra of single wheat kernels, wheat flour, and wheat methanol extracts were analysed to elucidate the metabolic development...

The application of NMR and MS methods for detection of adulteration of wine, fruit juices, and olive oil. A review.

Science.gov (United States)

Ogrinc, N; Kosir, I J; Spangenberg, J E; Kidric, J

2003-06-01

This review covers two important techniques, high resolution nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), used to characterize food products and detect possible adulteration of wine, fruit juices, and olive oil, all important products of the Mediterranean Basin. Emphasis is placed on the complementary use of SNIF-NMR (site-specific natural isotopic fractionation nuclear magnetic resonance) and IRMS (isotope-ratio mass spectrometry) in association with chemometric methods for detecting the adulteration.

Chemometric classification of Chinese lager beers according to manufacturer based on data fusion of fluorescence, UV and visible spectroscopies.

Science.gov (United States)

Tan, Jin; Li, Rong; Jiang, Zi-Tao

2015-10-01

We report an application of data fusion for chemometric classification of 135 canned samples of Chinese lager beers by manufacturer based on the combination of fluorescence, UV and visible spectroscopies. Right-angle synchronous fluorescence spectra (SFS) at three wavelength difference Δλ=30, 60 and 80 nm and visible spectra in the range 380-700 nm of undiluted beers were recorded. UV spectra in the range 240-400 nm of diluted beers were measured. A classification model was built using principal component analysis (PCA) and linear discriminant analysis (LDA). LDA with cross-validation showed that the data fusion could achieve 78.5-86.7% correct classification (sensitivity), while those rates using individual spectroscopies ranged from 42.2% to 70.4%. The results demonstrated that the fluorescence, UV and visible spectroscopies complemented each other, yielding higher synergic effect. Copyright © 2015 Elsevier Ltd. All rights reserved.

Is it possible to find presence of lactose in pharmaceuticals? - Preliminary studies by ATR-FTIR spectroscopy and chemometrics

Science.gov (United States)

Banas, A.; Banas, K.; Kalaiselvi, S. M. P.; Pawlicki, B.; Kwiatek, W. M.; Breese, M. B. H.

2017-01-01

Lactose and saccharose have the same molecular formula; however, the arrangement of their atoms is different. A major difference between lactose and saccharose with regard to digestion and processing is that it is not uncommon for individuals to be lactose intolerant (around two thirds of the population has a limited ability to digest lactose after infancy), but it is rather unlikely to be saccharose intolerant. The pharmaceutical industry uses lactose and saccharose as inactive ingredients of drugs to help form tablets because of their excellent compressibility properties. Some patients with severe lactose intolerance may experience symptoms of many allergic reactions after taking medicine that contains this substance. People who are specifically "allergic" to lactose (not just lactose intolerant) should not use tablets containing this ingredient. Fourier Transform Infrared (FTIR) spectroscopy has a unique chemical fingerprinting capability and plays a significant important role in the identification and characterization of analyzed samples and hence has been widely used in pharmaceutical science. However, a typical FTIR spectrum collected from tablets contains a myriad of valuable information hidden in a family of tiny peaks. Powerful multivariate spectral data processing can transform FTIR spectroscopy into an ideal tool for high volume, rapid screening and characterization of even minor tablet components. In this paper a method for distinction between FTIR spectra collected for tablets with or without lactose is presented. The results seem to indicate that the success of identifying one component in FTIR spectra collected for pharmaceutical composition (that is tablet) is largely dependent on the choice of the chemometric technique applied.

New insight into protein-nanomaterial interactions with UV-visible spectroscopy and chemometrics: human serum albumin and silver nanoparticles.

Science.gov (United States)

Wang, Yong; Ni, Yongnian

2014-01-21

In recent years, great efforts have focused on the exploration and fabrication of protein nanoconjugates due to potential applications in many fields including bioanalytical science, biosensors, biocatalysis, biofuel cells and bio-based nanodevices. An important aspect of our understanding of protein nanoconjugates is to quantitatively understand how proteins interact with nanomaterials. In this report, human serum albumin (HSA) and citrate-coated silver nanoparticles (AgNPs) are selected as a case study of protein-nanomaterial interactions. UV-visible spectroscopy together with multivariate curve resolution by alternating least squares (MCR-ALS) algorithm is first exploited for the detailed study of AgNPs-HSA interactions. Introduction of the chemometrics tool allows extracting the kinetic profiles, spectra and distribution diagrams of two major absorbing pure species (AgNPs and AgNPs-HSA conjugate). These resolved profiles are then analysed to give the thermodynamic, kinetic and structural information of HSA binding to AgNPs. Transmission electron microscopy, circular dichroism spectroscopy and Fourier transform infrared spectroscopy are used to further characterize the complex system. Moreover, a sensitive spectroscopic biosensor for HSA is fabricated with the MCR-ALS resolved concentration of absorbing pure species. It is found that the linear range for the HSA nanosensor was from 1.9 nM to 45.0 nM with a detection limit of 0.9 nM. It is believed that the proposed method will play an important role in the fabrication and optimization of a robust nanobiosensor or cross-reactive sensors array for the detection and identification of biocomponents.

Improving tomato seed quality- challenges and possibilities

DEFF Research Database (Denmark)

Shrestha, Santosh

The thesis investigates the possibility of using single seed near-infrared (NIR) spectroscopy, multispectral imaging (MSI) and NIR hyperspectral imaging (NIR-HSI) in combination with chemometrics for rapid determination of the tomato seed quality. The results of the PhD study are compiled in four...... manuscripts (MS). These non-destructive methods show the potential of sorting tomato seeds as per their viability and varietal identity. The results are discussed in the context of possible contribution from these methods in the improvement of the seed quality in Nepal. In MS I, potential application of NIR...... spectroscopy in combination with chemometrics for prediction of tomato seed viability is demonstrated. The work in MS I also emphasises on identifying the important NIR spectral regions for the chemometric model that are relevant to the separation of viable and non-viable seeds. The NIR-HIS method was also...

Near infrared system coupled chemometric algorithms for enumeration of total fungi count in cocoa beans neat solution.

Science.gov (United States)

Kutsanedzie, Felix Y H; Chen, Quansheng; Hassan, Md Mehedi; Yang, Mingxiu; Sun, Hao; Rahman, Md Hafizur

2018-02-01

Total fungi count (TFC) is a quality indicator of cocoa beans when unmonitored leads to quality and safety problems. Fourier transform near infrared spectroscopy (FT-NIRS) combined with chemometric algorithms like partial least square (PLS); synergy interval-PLS (Si-PLS); synergy interval-genetic algorithm-PLS (Si-GAPLS); Ant colony optimization - PLS (ACO-PLS) and competitive-adaptive reweighted sampling-PLS (CARS-PLS) was employed to predict TFC in cocoa beans neat solution. Model results were evaluated using the correlation coefficients of the prediction (Rp) and calibration (Rc); root mean square error of prediction (RMSEP), and the ratio of sample standard deviation to RMSEP (RPD). The developed models performance yielded 0.951≤Rp≤0.975; and 3.15≤RPD≤4.32. The models' prediction stability improved in the order of PLS

Testing of complementarity of PDA and MS detectors using chromatographic fingerprinting of genuine and counterfeit samples containing sildenafil citrate.

Science.gov (United States)

Custers, Deborah; Krakowska, Barbara; De Beer, Jacques O; Courselle, Patricia; Daszykowski, Michal; Apers, Sandra; Deconinck, Eric

2016-02-01

Counterfeit medicines are a global threat to public health. High amounts enter the European market, which is why characterization of these products is a very important issue. In this study, a high-performance liquid chromatography-photodiode array (HPLC-PDA) and high-performance liquid chromatography-mass spectrometry (HPLC-MS) method were developed for the analysis of genuine Viagra®, generic products of Viagra®, and counterfeit samples in order to obtain different types of fingerprints. These data were included in the chemometric data analysis, aiming to test whether PDA and MS are complementary detection techniques. The MS data comprise both MS1 and MS2 fingerprints; the PDA data consist of fingerprints measured at three different wavelengths, i.e., 254, 270, and 290 nm, and all possible combinations of these wavelengths. First, it was verified if both groups of fingerprints can discriminate between genuine, generic, and counterfeit medicines separately; next, it was studied if the obtained results could be ameliorated by combining both fingerprint types. This data analysis showed that MS1 does not provide suitable classification models since several genuines and generics are classified as counterfeits and vice versa. However, when analyzing the MS1_MS2 data in combination with partial least squares-discriminant analysis (PLS-DA), a perfect discrimination was obtained. When only using data measured at 254 nm, good classification models can be obtained by k nearest neighbors (kNN) and soft independent modelling of class analogy (SIMCA), which might be interesting for the characterization of counterfeit drugs in developing countries. However, in general, the combination of PDA and MS data (254 nm_MS1) is preferred due to less classification errors between the genuines/generics and counterfeits compared to PDA and MS data separately.

Application of Fourier transform infrared spectroscopy and chemometrics for differentiation of Salmonella enterica serovar Enteritidis phage types.

Science.gov (United States)

Preisner, Ornella; Guiomar, Raquel; Machado, Jorge; Menezes, José Cardoso; Lopes, João Almeida

2010-06-01

Fourier transform infrared (FT-IR) spectroscopy and chemometric techniques were used to discriminate five closely related Salmonella enterica serotype Enteritidis phage types, phage type 1 (PT1), PT1b, PT4b, PT6, and PT6a. Intact cells and outer membrane protein (OMP) extracts from bacterial cell membranes were subjected to FT-IR analysis in transmittance mode. Spectra were collected over a wavenumber range from 4,000 to 600 cm(-1). Partial least-squares discriminant analysis (PLS-DA) was used to develop calibration models based on preprocessed FT-IR spectra. The analysis based on OMP extracts provided greater separation between the Salmonella Enteritidis PT1-PT1b, PT4b, and PT6-PT6a groups than the intact cell analysis. When these three phage type groups were considered, the method based on OMP extract FT-IR spectra was 100% accurate. Moreover, complementary local models that considered only the PT1-PT1b and PT6-PT6a groups were developed, and the level of discrimination increased. PT1 and PT1b isolates were differentiated successfully with the local model using the entire OMP extract spectrum (98.3% correct predictions), whereas the accuracy of discrimination between PT6 and PT6a isolates was 86.0%. Isolates belonging to different phage types (PT19, PT20, and PT21) were used with the model to test its robustness. For the first time it was demonstrated that FT-IR analysis of OMP extracts can be used for construction of robust models that allow fast and accurate discrimination of different Salmonella Enteritidis phage types.

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

Non-targeted volatile profiles for the classification of the botanical origin of Chinese honey by solid-phase microextraction and gas chromatography-mass spectrometry combined with chemometrics.

Science.gov (United States)

Chen, Hui; Jin, Linghe; Fan, Chunlin; Wang, Wenwen

2017-11-01

A potential method for the discrimination and prediction of honey samples of various botanical origins was developed based on the non-targeted volatile profiles obtained by solid-phase microextraction with gas chromatography and mass spectrometry combined with chemometrics. The blind analysis of non-targeted volatile profiles was carried out using solid-phase microextraction with gas chromatography and mass spectrometry for 87 authentic honey samples from four botanical origins (acacia, linden, vitex, and rape). The number of variables was reduced from 2734 to 70 by using a series of filters. Based on the optimized 70 variables, 79.12% of the variance was explained by the first four principal components. Partial least squares discriminant analysis, naïve Bayes analysis, and back-propagation artificial neural network were used to develop the classification and prediction models. The 100% accuracy revealed a perfect classification of the botanical origins. In addition, the reliability and practicability of the models were validated by an independent set of additional 20 authentic honey samples. All 20 samples were accurately classified. The confidence measures indicated that the performance of the naïve Bayes model was better than the other two models. Finally, the characteristic volatile compounds of linden honey were tentatively identified. The proposed method is reliable and accurate for the classification of honey of various botanical origins. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Chemical Profiling of the Essential Oils of Syzygium aqueum, Syzygium samarangense and Eugenia uniflora and Their Discrimination Using Chemometric Analysis.

Science.gov (United States)

Sobeh, Mansour; Braun, Markus Santhosh; Krstin, Sonja; Youssef, Fadia S; Ashour, Mohamed L; Wink, Michael

2016-11-01

The essential oil compositions of the leaves of three related Myrtaceae species, namely Syzygium aqueum, Syzygium samarangense and Eugenia uniflora, were investigated using GLC/MS and GLC/FID. Altogether, 125 compounds were identified: α-Selinene (13.85%), β-caryophyllene (12.72%) and β-selinene constitute the most abundant constituents in S. aqueum. Germacrene D (21.62%) represents the major compound in S. samarangense whereas in E. uniflora, spathulenol (15.80%) represents the predominant component. Multivariate chemometric analyses were used to discriminate the essential oils using hierarchical cluster analysis (HCA) and principal component analysis (PCA) based on the chromatographic results. The antimicrobial activity of the popularly used E. uniflora essential oil was assessed using broth microdilution method against six Gram-positive, three Gram-negative bacteria and two fungi. The oil showed moderate antimicrobial activity against Bacillus licheniformis exhibiting MIC and MMC of 0.63 mg/ml. The cytotoxic activity of E. uniflora essential oil was investigated against Trypanosoma brucei brucei (T. b. brucei) and MCF-7 cancer cell line using MTT assay. It showed moderate activity against MCF-7 cells with an IC 50 value of 76.40 μg/ml. On the other hand, T. brucei was highly susceptible to E. uniflora essential oil with IC 50 of 11.20 μg/ml, and a selectivity index of 6.82. © 2016 Wiley-VHCA AG, Zurich, Switzerland.

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.

Essential Oil Variation from Twenty Two Genotypes of Citrus in Brazil-Chemometric Approach and Repellency Against Diaphorina citri Kuwayama.

Science.gov (United States)

Andrade, Moacir Dos Santos; Ribeiro, Leandro do Prado; Borgoni, Paulo Cesar; Silva, Maria Fátima das Graças Fernandes da; Forim, Moacir Rossi; Fernandes, João Batista; Vieira, Paulo Cezar; Vendramin, José Djair; Machado, Marcos Antônio

2016-06-22

The chemical composition of volatile oils from 22 genotypes of Citrus and related genera was poorly differentiated, but chemometric techniques have clarified the relationships between the 22 genotypes, and allowed us to understand their resistance to D. citri. The most convincing similarities include the synthesis of (Z)-β-ocimene and (E)-caryophyllene for all 11 genotypes of group A. Genotypes of group B are not uniformly characterized by essential oil compounds. When stimulated with odor sources of 22 genotypes in a Y-tube olfactometer D. citri preferentially entered the arm containing the volatile oils of Murraya paniculata, confirming orange jasmine as its best host. C. reticulata × C. sinensis was the least preferred genotype, and is characterized by the presence of phytol, (Z)-β-ocimene, and β-elemene, which were not found in the most preferred genotype. We speculate that these three compounds may act as a repellent, making these oils less attractive to D. citri.

Essential Oil Variation from Twenty Two Genotypes of Citrus in Brazil—Chemometric Approach and Repellency Against Diaphorina citri Kuwayama

Directory of Open Access Journals (Sweden)

Moacir dos Santos Andrade

2016-06-01

Full Text Available The chemical composition of volatile oils from 22 genotypes of Citrus and related genera was poorly differentiated, but chemometric techniques have clarified the relationships between the 22 genotypes, and allowed us to understand their resistance to D. citri. The most convincing similarities include the synthesis of (Z-β-ocimene and (E-caryophyllene for all 11 genotypes of group A. Genotypes of group B are not uniformly characterized by essential oil compounds. When stimulated with odor sources of 22 genotypes in a Y-tube olfactometer D. citri preferentially entered the arm containing the volatile oils of Murraya paniculata, confirming orange jasmine as its best host. C. reticulata × C. sinensis was the least preferred genotype, and is characterized by the presence of phytol, (Z-β-ocimene, and β-elemene, which were not found in the most preferred genotype. We speculate that these three compounds may act as a repellent, making these oils less attractive to D. citri.

Different approaches in Partial Least Squares and Artificial Neural Network models applied for the analysis of a ternary mixture of Amlodipine, Valsartan and Hydrochlorothiazide

Science.gov (United States)

Darwish, Hany W.; Hassan, Said A.; Salem, Maissa Y.; El-Zeany, Badr A.

2014-03-01

Different chemometric models were applied for the quantitative analysis of Amlodipine (AML), Valsartan (VAL) and Hydrochlorothiazide (HCT) in ternary mixture, namely, Partial Least Squares (PLS) as traditional chemometric model and Artificial Neural Networks (ANN) as advanced model. PLS and ANN were applied with and without variable selection procedure (Genetic Algorithm GA) and data compression procedure (Principal Component Analysis PCA). The chemometric methods applied are PLS-1, GA-PLS, ANN, GA-ANN and PCA-ANN. The methods were used for the quantitative analysis of the drugs in raw materials and pharmaceutical dosage form via handling the UV spectral data. A 3-factor 5-level experimental design was established resulting in 25 mixtures containing different ratios of the drugs. Fifteen mixtures were used as a calibration set and the other ten mixtures were used as validation set to validate the prediction ability of the suggested methods. The validity of the proposed methods was assessed using the standard addition technique.

Classification of archaeological pieces into their respective stratum by a chemometric model based on the soil concentration of 25 selected elements

International Nuclear Information System (INIS)

Carrero, J.A.; Goienaga, N.; Fdez-Ortiz de Vallejuelo, S.; Arana, G.; Madariaga, J.M.

2010-01-01

The aim of this work was to demonstrate that an archaeological ceramic piece has remained buried underground in the same stratum for centuries without being removed. For this purpose, a chemometric model based on Principal Component Analysis, Soft Independent Modelling of Class Analogy and Linear Discriminant Analysis classification techniques was created with the concentration of some selected elements of both soil of the stratum and soil adhered to the ceramic piece. Some ceramic pieces from four different stratigraphic units, coming from a roman archaeological site in Alava (North of Spain), and its respective stratum soils were collected. The soil adhered to the ceramic pieces was removed and treated in the same way as the soil from its respective stratum. The digestion was carried out following the US Environmental Pollution Agency EPA 3051A method. A total of 54 elements were determined in the extracts by a rapid screening inductively coupled plasma mass spectrometry method. After rejecting the major elements and those which could have changed from the original composition of the soils (migration or retention from/to the buried objects), the following elements (25) were finally taken into account to construct the model: Li, V, Co, As, Y, Nb, Sn, Ba, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, Au, Th and U. A total of 33 subsamples were treated from 10 soils belonging to 4 different stratigraphic units. The final model groups and discriminate them in four groups, according to the stratigraphic unit, having both the stratum and soils adhered to the pieces falling down in the same group.

Triglyceride dependent differentiation of obesity in adipose tissues by FTIR spectroscopy coupled with chemometrics.

Science.gov (United States)

Kucuk Baloglu, Fatma; Baloglu, Onur; Heise, Sebastian; Brockmann, Gudrun; Severcan, Feride

2017-10-01

The excess deposition of triglycerides in adipose tissue is the main reason of obesity and causes excess release of fatty acids to the circulatory system resulting in obesity and insulin resistance. Body mass index and waist circumference are not precise measure of obesity and obesity related metabolic diseases. Therefore, in the current study, it was aimed to propose triglyceride bands located at 1770-1720 cm -1 spectral region as a more sensitive obesity related biomarker using the diagnostic potential of Fourier Transform Infrared (FTIR) spectroscopy in subcutaneous (SCAT) and visceral (VAT) adipose tissues. The adipose tissue samples were obtained from 10 weeks old male control (DBA/2J) (n = 6) and four different obese BFMI mice lines (n = 6 per group). FTIR spectroscopy coupled with hierarchical cluster analysis (HCA) and principal component analysis (PCA) was applied to the spectra of triglyceride bands as a diagnostic tool in the discrimination of the samples. Successful discrimination of the obese, obesity related insulin resistant and control groups were achieved with high sensitivity and specificity. The results revealed the power of FTIR spectroscopy coupled with chemometric approaches in internal diagnosis of abdominal obesity based on the spectral differences in the triglyceride region that can be used as a spectral marker. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

ASTM clustering for improving coal analysis by near-infrared spectroscopy.

Science.gov (United States)

Andrés, J M; Bona, M T

2006-11-15

Multivariate analysis techniques have been applied to near-infrared (NIR) spectra coals to investigate the relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding predictor variables. In this work, a whole set of coal samples was grouped into six more homogeneous clusters following the ASTM reference method for classification prior to the application of calibration methods to each coal set. The results obtained showed a considerable improvement of the error determination compared with the calibration for the whole sample set. For some groups, the established calibrations approached the quality required by the ASTM/ISO norms for laboratory analysis. To predict property values for a new coal sample it is necessary the assignation of that sample to its respective group. Thus, the discrimination and classification ability of coal samples by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) in the NIR range was also studied by applying Soft Independent Modelling of Class Analogy (SIMCA) and Linear Discriminant Analysis (LDA) techniques. Modelling of the groups by SIMCA led to overlapping models that cannot discriminate for unique classification. On the other hand, the application of Linear Discriminant Analysis improved the classification of the samples but not enough to be satisfactory for every group considered.

New spectroscopic techniques for wine analysis and characterization

International Nuclear Information System (INIS)

Edelmann, A.

2003-01-01

The objective of the presented thesis was the development of new, rapid tools for wine analysis based on Fourier transform infrared (FTIR) and Ultraviolet/Visible (UV/Vis) - spectroscopy. The results of this thesis are presented in the form of five publications. In publication I a sensor for assessing the main sensory property of red wine polyphenols (tannins), namely astringency, was developed on basis of the underlying chemical reaction between the tannins and the proline-rich proteins in the saliva. The interaction of polyphenols (tannins) with proline rich proteins (gelatin) has been studied using an automated flow injection system with FTIR detection. In Publication II FTIR-spectroscopy of polyphenolic wine extracts combined with multivariate data analysis was applied for the varietal discrimination of Austrian red wines. By hierarchical clustering it could be shown that the mid-infrared spectra of the dry extracts contain information on the varietal origin of wines. The classification of the wines was successfully performed by soft independent modeling of class analogies (SIMCA). Publication III describes the determination of carbohydrates, alcohols and organic acids in red wine by Ion-exchange high performance liquid chromatography hyphenated with FTIR-detection, where a diamond attenuated total reflectance (ATR)-element was employed for the design of a rugged detector. Partly or completely co-eluting peaks were chemometrically resolved by multivariate curve resolution - alternating least squares (MCR-ALS). Publication IV reports the first application of a mid-infrared quantum cascade laser (QCL) for molecular specific laser detection in liquid chromatography. Using a laser wavelength of 9.3721 μm glucose and fructose could be specifically detected and quantified in red wine in spite of the presence of organic acids. Publication V presents the development of an automated method for measuring the primary amino acid concentration in wines and musts by

Comparative study of wine tannin classification using Fourier transform mid-infrared spectrometry and sensory analysis.

Science.gov (United States)

Fernández, Katherina; Labarca, Ximena; Bordeu, Edmundo; Guesalaga, Andrés; Agosin, Eduardo

2007-11-01

Wine tannins are fundamental to the determination of wine quality. However, the chemical and sensorial analysis of these compounds is not straightforward and a simple and rapid technique is necessary. We analyzed the mid-infrared spectra of white, red, and model wines spiked with known amounts of skin or seed tannins, collected using Fourier transform mid-infrared (FT-MIR) transmission spectroscopy (400-4000 cm(-1)). The spectral data were classified according to their tannin source, skin or seed, and tannin concentration by means of discriminant analysis (DA) and soft independent modeling of class analogy (SIMCA) to obtain a probabilistic classification. Wines were also classified sensorially by a trained panel and compared with FT-MIR. SIMCA models gave the most accurate classification (over 97%) and prediction (over 60%) among the wine samples. The prediction was increased (over 73%) using the leave-one-out cross-validation technique. Sensory classification of the wines was less accurate than that obtained with FT-MIR and SIMCA. Overall, these results show the potential of FT-MIR spectroscopy, in combination with adequate statistical tools, to discriminate wines with different tannin levels.

The employment of FTIR spectroscopy in combination with chemometrics for analysis of rat meat in meatball formulation.

Science.gov (United States)

Rahmania, Halida; Sudjadi; Rohman, Abdul

2015-02-01

For Indonesian community, meatball is one of the favorite meat food products. In order to gain economical benefits, the substitution of beef meat with rat meat can happen due to the different prices between rat meat and beef. In this present research, the feasibility of FTIR spectroscopy in combination with multivariate calibration of partial least square (PLS) was used for the quantitative analysis of rat meat in the binary mixture of beef in meatball formulation. Meanwhile, the chemometrics of principal component analysis (PCA) was used for the classification between rat meat and beef meatballs. Some frequency regions in mid infrared region were optimized, and finally, the frequency region of 750-1000 cm(-1) was selected during PLS and PCA modeling.For quantitative analysis, the relationship between actual values (x-axis) and FTIR predicted values (y-axis) of rat meat is described by the equation of y= 0.9417x+ 2.8410 with coefficient of determination (R2) of 0.993, and root mean square error of calibration (RMSEC) of 1.79%. Furthermore, PCA was successfully used for the classification of rat meat meatball and beef meatball.

Authentication of animal fats using direct analysis in real time (DART) ionization-mass spectrometry and chemometric tools.

Science.gov (United States)

Vaclavik, Lukas; Hrbek, Vojtech; Cajka, Tomas; Rohlik, Bo-Anne; Pipek, Petr; Hajslova, Jana

2011-06-08

A combination of direct analysis in real time (DART) ionization coupled to time-of-flight mass spectrometry (TOFMS) and chemometrics was used for animal fat (lard and beef tallow) authentication. This novel instrumentation was employed for rapid profiling of triacylglycerols (TAGs) and polar compounds present in fat samples and their mixtures. Additionally, fat isolated from pork, beef, and pork/beef admixtures was analyzed. Mass spectral records were processed by principal component analysis (PCA) and stepwise linear discriminant analysis (LDA). DART-TOFMS profiles of TAGs were found to be more suitable for the purpose of discrimination among the examined fat types as compared to profiles of polar compounds. The LDA model developed using TAG data enabled not only reliable classification of samples representing neat fats but also detection of admixed lard and tallow at adulteration levels of 5 and 10% (w/w), respectively. The presented approach was also successfully applied to minced meat prepared from pork and beef with comparable fat content. Using the DART-TOFMS TAG profiles of fat isolated from meat mixtures, detection of 10% pork added to beef and vice versa was possible.

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)

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.

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.

Discrimination of genetically modified sugar beets based on terahertz spectroscopy

Science.gov (United States)

Chen, Tao; Li, Zhi; Yin, Xianhua; Hu, Fangrong; Hu, Cong

2016-01-01

The objective of this paper was to apply terahertz (THz) spectroscopy combined with chemometrics techniques for discrimination of genetically modified (GM) and non-GM sugar beets. In this paper, the THz spectra of 84 sugar beet samples (36 GM sugar beets and 48 non-GM ones) were obtained by using terahertz time-domain spectroscopy (THz-TDS) system in the frequency range from 0.2 to 1.2 THz. Three chemometrics methods, principal component analysis (PCA), discriminant analysis (DA) and discriminant partial least squares (DPLS), were employed to classify sugar beet samples into two groups: genetically modified organisms (GMOs) and non-GMOs. The DPLS method yielded the best classification result, and the percentages of successful classification for GM and non-GM sugar beets were both 100%. Results of the present study demonstrate the usefulness of THz spectroscopy together with chemometrics methods as a powerful tool to distinguish GM and non-GM sugar beets.

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.

A novel combined approach of diffuse reflectance UV-Vis-NIR spectroscopy and multivariate analysis for non-destructive examination of blue ballpoint pen inks in forensic application.

Science.gov (United States)

Kumar, Raj; Sharma, Vishal

2017-03-15

The present research is focused on the analysis of writing inks using destructive UV-Vis spectroscopy (dissolution of ink by the solvent) and non-destructive diffuse reflectance UV-Vis-NIR spectroscopy along with Chemometrics. Fifty seven samples of blue ballpoint pen inks were analyzed under optimum conditions to determine the differences in spectral features of inks among same and different manufacturers. Normalization was performed on the spectroscopic data before chemometric analysis. Principal Component Analysis (PCA) and K-mean cluster analysis were used on the data to ascertain whether the blue ballpoint pen inks could be differentiated by their UV-Vis/UV-Vis NIR spectra. The discriminating power is calculated by qualitative analysis by the visual comparison of the spectra (absorbance peaks), produced by the destructive and non-destructive methods. In the latter two methods, the pairwise comparison is made by incorporating the clustering method. It is found that chemometric method provides better discriminating power (98.72% and 99.46%, in destructive and non-destructive, respectively) in comparison to the qualitative analysis (69.67%). Copyright © 2016 Elsevier B.V. All rights reserved.

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

Tracking the degradation of fresh orange juice and discrimination of orange varieties: an example of NMR in coordination with chemometrics analyses.

Science.gov (United States)

de Oliveira, Clayton R; Carneiro, Renato L; Ferreira, Antonio G

2014-12-01

Brazil is currently the largest exporter of concentrated orange juice and, unlike the other exporter countries, the domestic consumption is mainly based on the fresh orange juice. The quality control by evaluating the major chemical constituents under the influence of the most important factors, such as temperature and storage time of the product, is very important in this context. Therefore, the objective of this study was to evaluate the influence of temperature and time on the degradation of fresh orange juice for 24h, by using (1)H NMR technique and chemometric tools for data mining. The storage conditions at 24h led to the production of the formic, fumaric and acetic acids; and an increase of succinic and lactic acids and ethanol, which were observed at low concentration at the initial time. Furthermore, analysis by PCA has successfully distinguished the juice of different species/varieties as well as the metabolites responsible for their separation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Collision cross section prediction of deprotonated phenolics in a travelling-wave ion mobility spectrometer using molecular descriptors and chemometrics

Energy Technology Data Exchange (ETDEWEB)

Gonzales, Gerard Bryan, E-mail: gerard.gonzales@ugent.be [Food Chemistry and Human Nutrition (NutriFOODChem), Department of Food Safety and Food Quality, Faculty of Bioscience Engineering, Ghent University (Belgium); Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University (Belgium); Department of Applied Biological Science, Faculty of Bioscience Engineering, Ghent University (Belgium); Smagghe, Guy [Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University (Belgium); Coelus, Sofie; Adriaenssens, Dieter [Food Chemistry and Human Nutrition (NutriFOODChem), Department of Food Safety and Food Quality, Faculty of Bioscience Engineering, Ghent University (Belgium); De Winter, Karel; Desmet, Tom [Center for Industrial Biotechnology and Biocatalysis, Faculty of Bioscience Engineering, Ghent University (Belgium); Raes, Katleen [Department of Applied Biological Science, Faculty of Bioscience Engineering, Ghent University (Belgium); Van Camp, John, E-mail: john.vancamp@ugent.be [Food Chemistry and Human Nutrition (NutriFOODChem), Department of Food Safety and Food Quality, Faculty of Bioscience Engineering, Ghent University (Belgium)

2016-06-14

The combination of ion mobility and mass spectrometry (MS) affords significant improvements over conventional MS/MS, especially in the characterization of isomeric metabolites due to the differences in their collision cross sections (CCS). Experimentally obtained CCS values are typically matched with theoretical CCS values from Trajectory Method (TM) and/or Projection Approximation (PA) calculations. In this paper, predictive models for CCS of deprotonated phenolics were developed using molecular descriptors and chemometric tools, stepwise multiple linear regression (SMLR), principal components regression (PCR), and partial least squares regression (PLS). A total of 102 molecular descriptors were generated and reduced to 28 after employing a feature selection tool, composed of mass, topological descriptors, Jurs descriptors and shadow indices. Therefore, the generated models considered the effects of mass, 3D conformation and partial charge distribution on CCS, which are the main parameters for either TM or PA (only 3D conformation) calculations. All three techniques yielded highly predictive models for both the training (R{sup 2}{sub SMLR} = 0.9911; R{sup 2}{sub PCR} = 0.9917; R{sup 2}{sub PLS} = 0.9918) and validation datasets (R{sup 2}{sub SMLR} = 0.9489; R{sup 2}{sub PCR} = 0.9761; R{sup 2}{sub PLS} = 0.9760). Also, the high cross validated R{sup 2} values indicate that the generated models are robust and highly predictive (Q{sup 2}{sub SMLR} = 0.9859; Q{sup 2}{sub PCR} = 0.9748; Q{sup 2}{sub PLS} = 0.9760). The predictions were also very comparable to the results from TM calculations using modified mobcal (N2). Most importantly, this method offered a rapid (<10 min) alternative to TM calculations without compromising predictive ability. These methods could therefore be used in routine analysis and could be easily integrated to metabolite identification platforms. - Highlights: • CCS for deprotonated phenolics were measured using TWIMS. �

Collision cross section prediction of deprotonated phenolics in a travelling-wave ion mobility spectrometer using molecular descriptors and chemometrics

International Nuclear Information System (INIS)

Gonzales, Gerard Bryan; Smagghe, Guy; Coelus, Sofie; Adriaenssens, Dieter; De Winter, Karel; Desmet, Tom; Raes, Katleen; Van Camp, John

2016-01-01

The combination of ion mobility and mass spectrometry (MS) affords significant improvements over conventional MS/MS, especially in the characterization of isomeric metabolites due to the differences in their collision cross sections (CCS). Experimentally obtained CCS values are typically matched with theoretical CCS values from Trajectory Method (TM) and/or Projection Approximation (PA) calculations. In this paper, predictive models for CCS of deprotonated phenolics were developed using molecular descriptors and chemometric tools, stepwise multiple linear regression (SMLR), principal components regression (PCR), and partial least squares regression (PLS). A total of 102 molecular descriptors were generated and reduced to 28 after employing a feature selection tool, composed of mass, topological descriptors, Jurs descriptors and shadow indices. Therefore, the generated models considered the effects of mass, 3D conformation and partial charge distribution on CCS, which are the main parameters for either TM or PA (only 3D conformation) calculations. All three techniques yielded highly predictive models for both the training (R"2_S_M_L_R = 0.9911; R"2_P_C_R = 0.9917; R"2_P_L_S = 0.9918) and validation datasets (R"2_S_M_L_R = 0.9489; R"2_P_C_R = 0.9761; R"2_P_L_S = 0.9760). Also, the high cross validated R"2 values indicate that the generated models are robust and highly predictive (Q"2_S_M_L_R = 0.9859; Q"2_P_C_R = 0.9748; Q"2_P_L_S = 0.9760). The predictions were also very comparable to the results from TM calculations using modified mobcal (N2). Most importantly, this method offered a rapid (<10 min) alternative to TM calculations without compromising predictive ability. These methods could therefore be used in routine analysis and could be easily integrated to metabolite identification platforms. - Highlights: • CCS for deprotonated phenolics were measured using TWIMS. • Isomeric phenolics were separated in the IMS based on their CCS. • SMLR

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.

Investigating Antibacterial Effects of Garlic (Allium sativum) Concentrate and Garlic-Derived Organosulfur Compounds on Campylobacter jejuni by Using Fourier Transform Infrared Spectroscopy, Raman Spectroscopy, and Electron Microscopy ▿ †

Science.gov (United States)

Lu, Xiaonan; Rasco, Barbara A.; Jabal, Jamie M. F.; Aston, D. Eric; Lin, Mengshi; Konkel, Michael E.

2011-01-01

Fourier transform infrared (FT-IR) spectroscopy and Raman spectroscopy were used to study the cell injury and inactivation of Campylobacter jejuni from exposure to antioxidants from garlic. C. jejuni was treated with various concentrations of garlic concentrate and garlic-derived organosulfur compounds in growth media and saline at 4, 22, and 35°C. The antimicrobial activities of the diallyl sulfides increased with the number of sulfur atoms (diallyl sulfide garlic, much greater than those of garlic phenolic compounds, as indicated by changes in the spectral features of proteins, lipids, and polysaccharides in the bacterial cell membranes. Confocal Raman microscopy (532-nm-gold-particle substrate) and Raman mapping of a single bacterium confirmed the intracellular uptake of sulfur and phenolic components. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were employed to verify cell damage. Principal-component analysis (PCA), discriminant function analysis (DFA), and soft independent modeling of class analogs (SIMCA) were performed, and results were cross validated to differentiate bacteria based upon the degree of cell injury. Partial least-squares regression (PLSR) was employed to quantify and predict actual numbers of healthy and injured bacterial cells remaining following treatment. PLSR-based loading plots were investigated to further verify the changes in the cell membrane of C. jejuni treated with organosulfur compounds. We demonstrated that bacterial injury and inactivation could be accurately investigated by complementary infrared and Raman spectroscopies using a chemical-based, “whole-organism fingerprint” with the aid of chemometrics and electron microscopy. PMID:21642409

Fast-HPLC Fingerprinting to Discriminate Olive Oil from Other Edible Vegetable Oils by Multivariate Classification Methods.

Science.gov (United States)

Jiménez-Carvelo, Ana M; González-Casado, Antonio; Pérez-Castaño, Estefanía; Cuadros-Rodríguez, Luis

2017-03-01

A new analytical method for the differentiation of olive oil from other vegetable oils using reversed-phase LC and applying chemometric techniques was developed. A 3 cm short column was used to obtain the chromatographic fingerprint of the methyl-transesterified fraction of each vegetable oil. The chromatographic analysis took only 4 min. The multivariate classification methods used were k-nearest neighbors, partial least-squares (PLS) discriminant analysis, one-class PLS, support vector machine classification, and soft independent modeling of class analogies. The discrimination of olive oil from other vegetable edible oils was evaluated by several classification quality metrics. Several strategies for the classification of the olive oil were used: one input-class, two input-class, and pseudo two input-class.

Discussion on Regression Methods Based on Ensemble Learning and Applicability Domains of Linear Submodels.

Science.gov (United States)

Kaneko, Hiromasa

2018-02-26

To develop a new ensemble learning method and construct highly predictive regression models in chemoinformatics and chemometrics, applicability domains (ADs) are introduced into the ensemble learning process of prediction. When estimating values of an objective variable using subregression models, only the submodels with ADs that cover a query sample, i.e., the sample is inside the model's AD, are used. By constructing submodels and changing a list of selected explanatory variables, the union of the submodels' ADs, which defines the overall AD, becomes large, and the prediction performance is enhanced for diverse compounds. By analyzing a quantitative structure-activity relationship data set and a quantitative structure-property relationship data set, it is confirmed that the ADs can be enlarged and the estimation performance of regression models is improved compared with traditional methods.

Modern analytical methods for the detection of food fraud and adulteration by food category.

Science.gov (United States)

Hong, Eunyoung; Lee, Sang Yoo; Jeong, Jae Yun; Park, Jung Min; Kim, Byung Hee; Kwon, Kisung; Chun, Hyang Sook

2017-09-01

This review provides current information on the analytical methods used to identify food adulteration in the six most adulterated food categories: animal origin and seafood, oils and fats, beverages, spices and sweet foods (e.g. honey), grain-based food, and others (organic food and dietary supplements). The analytical techniques (both conventional and emerging) used to identify adulteration in these six food categories involve sensory, physicochemical, DNA-based, chromatographic and spectroscopic methods, and have been combined with chemometrics, making these techniques more convenient and effective for the analysis of a broad variety of food products. Despite recent advances, the need remains for suitably sensitive and widely applicable methodologies that encompass all the various aspects of food adulteration. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

FT-Raman and NIR spectroscopy data fusion strategy for multivariate qualitative analysis of food fraud.

Science.gov (United States)

Márquez, Cristina; López, M Isabel; Ruisánchez, Itziar; Callao, M Pilar

2016-12-01

Two data fusion strategies (high- and mid-level) combined with a multivariate classification approach (Soft Independent Modelling of Class Analogy, SIMCA) have been applied to take advantage of the synergistic effect of the information obtained from two spectroscopic techniques: FT-Raman and NIR. Mid-level data fusion consists of merging some of the previous selected variables from the spectra obtained from each spectroscopic technique and then applying the classification technique. High-level data fusion combines the SIMCA classification results obtained individually from each spectroscopic technique. Of the possible ways to make the necessary combinations, we decided to use fuzzy aggregation connective operators. As a case study, we considered the possible adulteration of hazelnut paste with almond. Using the two-class SIMCA approach, class 1 consisted of unadulterated hazelnut samples and class 2 of samples adulterated with almond. Models performance was also studied with samples adulterated with chickpea. The results show that data fusion is an effective strategy since the performance parameters are better than the individual ones: sensitivity and specificity values between 75% and 100% for the individual techniques and between 96-100% and 88-100% for the mid- and high-level data fusion strategies, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

Classification of juices and fermented beverages made from unripe, ripe and senescent apples based on the aromatic profile using chemometrics.

Science.gov (United States)

Braga, Cíntia Maia; Zielinski, Acácio Antonio Ferreira; Silva, Karolline Marques da; de Souza, Frederico Koch Fernandes; Pietrowski, Giovana de Arruda Moura; Couto, Marcelo; Granato, Daniel; Wosiacki, Gilvan; Nogueira, Alessandro

2013-11-15

The aim of this study was to assess differences between apple juices and fermented apple beverages elaborated with fruits from different varieties and at different ripening stages in the aroma profile by using chemometrics. Ripening influenced the aroma composition of the apple juice and fermented apple. For all varieties, senescent fruits provided more aromatic fermented apple beverages. However, no significant difference was noticed in samples made of senescent or ripe fruits of the Lisgala variety. Regarding the juices, ripe Gala apple had the highest total aroma concentration. Ethanal was the major compound identified in all the samples, with values between 11.83mg/L (unripe Lisgala juice) and 81.05mg/L (ripe Gala juice). 3-Methyl-1-butanol was the major compound identified in the fermented juices. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were applied and classified the juices and fermented juices based on physicochemical and aroma profile, demonstrating their applicability as tools to monitor the quality of apple-based products. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

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.

HPLC-PDA Combined with Chemometrics for Quantitation of Active Components and Quality Assessment of Raw and Processed Fruits of Xanthium strumarium L.

Directory of Open Access Journals (Sweden)

Hai Jiang

2018-01-01

Full Text Available 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.

A comparative study of PCA, SIMCA and Cole model for classification of bioimpedance spectroscopy measurements.

Science.gov (United States)

Nejadgholi, Isar; Bolic, Miodrag

2015-08-01

Due to safety and low cost of bioimpedance spectroscopy (BIS), classification of BIS can be potentially a preferred way of detecting changes in living tissues. However, for longitudinal datasets linear classifiers fail to classify conventional Cole parameters extracted from BIS measurements because of their high variability. In some applications, linear classification based on Principal Component Analysis (PCA) has shown more accurate results. Yet, these methods have not been established for BIS classification, since PCA features have neither been investigated in combination with other classifiers nor have been compared to conventional Cole features in benchmark classification tasks. In this work, PCA and Cole features are compared in three synthesized benchmark classification tasks which are expected to be detected by BIS. These three tasks are classification of before and after geometry change, relative composition change and blood perfusion in a cylindrical organ. Our results show that in all tasks the features extracted by PCA are more discriminant than Cole parameters. Moreover, a pilot study was done on a longitudinal arm BIS dataset including eight subjects and three arm positions. The goal of the study was to compare different methods in arm position classification which includes all three synthesized changes mentioned above. Our comparative study on various classification methods shows that the best classification accuracy is obtained when PCA features are classified by a K-Nearest Neighbors (KNN) classifier. The results of this work suggest that PCA+KNN is a promising method to be considered for classification of BIS datasets that deal with subject and time variability. Copyright © 2015 Elsevier Ltd. All rights reserved.

Characterization and classification of uranium ore concentrates (yellow cakes) using infrared spectrometry

Energy Technology Data Exchange (ETDEWEB)

Varga, Z.; Oeztuerk, B.; Mayer, K.; Wallenius, M.; Apostolidis, C. [Joint Research Centre, Karlsruhe (Germany). Inst. for Transuranium Elements; Meppen, M. [Carl Friedrich von Weizsaecker-Zentrum fuer Naturwissenschaft und Friedensforschung, Hamburg (Germany)

2011-07-01

In this work the applicability of Fourier-transform infrared spectrometry (FTIR) for nuclear forensic studies of uranium ore concentrates (UOC) are investigated. The technique was used for the identification of the type of uranium compound and various process-related impurities, which can give information on the production method of the material. The measured spectra were evaluated also by statistical means, using the soft independent modelling of class analogy (SIMCA) technique to reveal less apparent similarities between the measured UOC samples.

Classification of monofloral honeys by voltammetric electronic tongue with chemometrics method

Energy Technology Data Exchange (ETDEWEB)

Wei Zhenbo [Department of Bio-systems Engineering, Zhejiang University, 268 Kaixuan Road, Hangzhou 310029, Zhejiang (China); Wang Jun, E-mail: jwang@zju.edu.cn [Department of Bio-systems Engineering, Zhejiang University, 268 Kaixuan Road, Hangzhou 310029, Zhejiang (China)

2011-05-01

Highlights: > We self-developed a voltammetric electronic tongue based on new sensors array. > We advanced a new method to extract eigenvalues from signals obtained by VE-tongue. > We first detected the monofloral honeys of different floral origins using VE-tongue. - Abstract: A voltammetric electronic tongue (VE-tongue) based on multifrequency large amplitude pulse voltammetry (MLAPV) was developed to classify monofloral honeys of seven kinds of floral origins. The VE-tongue was composed of six working electrodes (gold, silver, platinum, palladium, tungsten, and titanium) in a standard three-electrode configuration. The applied waveform of MLAPV was composed of four individual frequencies: 1 Hz, 10 Hz, 100 Hz, and 1000 Hz. Two eigenvalues (the maximum value and the minimum value) of each cycle were extracted for building the first database (FDB); four eigenvalues (the maximum value, the minimum value, and two inflexion values) were exacted for building the second database (SDB). The two databases were analyzed by three-pattern recognition techniques: principal component analysis (PCA), discriminant function analysis (DFA) and cluster analysis (CA), respectively. It was possible to discriminate the seven kinds of honeys of different floral origins completely based on FDB and SDB by PCA, DFA and CA, and FDB was certificated as an efficient database by contrasting with the SDB. Moreover, the effective working electrodes and frequencies were picked out as the best experimental project for the further study.

Identification of sources of tar balls deposited along the Goa coast, India, using fingerprinting techniques

Digital Repository Service at National Institute of Oceanography (India)

Suneel, V.; Vethamony, P.; Zakaria, M.P.; Naik, B.G.; Prasad, K.V.

. Christensen et al (2007) reviewed the practical aspects of chemometrics for oil spill fingerprinting and provided a basis for the use of chemometric 3    methods in tiered oil spill fingerprinting. Biomarker compounds such as isoprenoid alkanes, hopanes... deposited along the Malaysian beaches. Low molecular weight/high molecular weight ratios (L/H) of both alkanes and PAHs together are useful in categorizing the weathering effects of tar balls (Chandru et al., 2008). However, in cases...

Combining vibrational biomolecular spectroscopy with chemometric techniques for the study of response and sensitivity of molecular structures/functional groups mainly related to lipid biopolymer to various processing applications.

Science.gov (United States)

Yu, Gloria Qingyu; Yu, Peiqiang

2015-09-01

The objectives of this project were to (1) combine vibrational spectroscopy with chemometric multivariate techniques to determine the effect of processing applications on molecular structural changes of lipid biopolymer that mainly related to functional groups in green- and yellow-type Crop Development Centre (CDC) pea varieties [CDC strike (green-type) vs. CDC meadow (yellow-type)] that occurred during various processing applications; (2) relatively quantify the effect of processing applications on the antisymmetric CH3 ("CH3as") and CH2 ("CH2as") (ca. 2960 and 2923 cm(-1), respectively), symmetric CH3 ("CH3s") and CH2 ("CH2s") (ca. 2873 and 2954 cm(-1), respectively) functional groups and carbonyl C=O ester (ca. 1745 cm(-1)) spectral intensities as well as their ratios of antisymmetric CH3 to antisymmetric CH2 (ratio of CH3as to CH2as), ratios of symmetric CH3 to symmetric CH2 (ratio of CH3s to CH2s), and ratios of carbonyl C=O ester peak area to total CH peak area (ratio of C=O ester to CH); and (3) illustrate non-invasive techniques to detect the sensitivity of individual molecular functional group to the various processing applications in the recently developed different types of pea varieties. The hypothesis of this research was that processing applications modified the molecular structure profiles in the processed products as opposed to original unprocessed pea seeds. The results showed that the different processing methods had different impacts on lipid molecular functional groups. Different lipid functional groups had different sensitivity to various heat processing applications. These changes were detected by advanced molecular spectroscopy with chemometric techniques which may be highly related to lipid utilization and availability. The multivariate molecular spectral analyses, cluster analysis, and principal component analysis of original spectra (without spectral parameterization) are unable to fully distinguish the structural differences in the

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.

Estimation of raw material performance in mammalian cell culture using near infrared spectra combined with chemometrics approaches.

Science.gov (United States)

Lee, Hae Woo; Christie, Andrew; Liu, Jun Jay; Yoon, Seongkyu

2012-01-01

Understanding variability in raw materials and their impacts on product quality is of critical importance in the biopharmaceutical manufacturing processes. For this purpose, several spectroscopic techniques have been studied for raw material characterization, providing fast and nondestructive ways to measure quality of raw materials. However, investigations of correlation between spectra of raw materials and cell culture performance have been scarce due to their complexity and uncertainty. In this study, near-infrared spectra and bioassays of multiple soy hydrolysate lots manufactured by different vendors were analyzed using chemometrics approaches in order to address variability of raw materials as well as correlation between raw material properties and corresponding cell culture performance. Principal component analysis revealed that near-infrared spectra of different soy lots contain enough physicochemical information about soy hydrolysates to allow identification of lot-to-lot variability as well as vendor-to-vendor differences. The identified compositional variability was further analyzed in order to estimate cell growth and protein production of two mammalian cell lines under the condition of varying soy dosages using partial least square regression combined with optimal variable selection. The performance of the resulting models demonstrates the potential of near-infrared spectroscopy as a robust lot selection tool for raw materials while providing a biological link between chemical composition of raw materials and cell culture performance. Copyright © 2012 American Institute of Chemical Engineers (AIChE).

Markers of typical red wine varieties from the Valley of Tulum (San Juan-Argentina) based on VOCs profile and chemometrics.

Science.gov (United States)

Fabani, María P; Ravera, Mario J A; Wunderlin, Daniel A

2013-11-15

We studied the VOCs profile of three red wine varieties, produced in the Valley of Tulum (San Juan-Argentina), over 4 consecutive years. Our main goal was to verify if different wine varieties could be differentiated from their VOCs profile, considering changes induced by their age, the yeast inoculated and the type of alcoholic fermentation, establishing those compounds that could be used as chemical markers of a particular variety. Stepwise LDA of selected VOCs allowed 100% differentiation between studied wines, showing that high levels of 1-hexanol were characteristic for Malbec, while low level of ethyl caproate was characteristic for Bonarda. Using controlled fermentations, 1-hexanol, a pre-fermentative VOC, presented a similar trend in wines produced from different yeast; while other fermentative VOCs, like ethyl caproate and ethyl caprilate, presented lower levels for Bonarda but also for Syrah. To our knowledge, this is the first report on characterization of VOCs from Bonarda. Additionally, the quantitative analysis of VOCs profile, coupled to chemometrics, present a good alternative to differentiate wines from different varieties and also for studying wine fermentation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Overview on Untargeted Methods to Combat Food Frauds: A Focus on Fishery Products

Directory of Open Access Journals (Sweden)

Giuseppina M. Fiorino

2018-01-01

Full Text Available Authenticity and traceability of food products are of primary importance at all levels of the production process, from raw materials to finished products. Authentication is also a key aspect for accurate labeling of food, which is required to help consumers in selecting appropriate types of food products. With the aim of guaranteeing the authenticity of foods, various methodological approaches have been devised over the past years, mainly based on either targeted or untargeted analyses. In this review, a brief overview of current analytical methods tailored to authenticity studies, with special regard to fishery products, is provided. Focus is placed on untargeted methods that are attracting the interest of the analytical community thanks to their rapidity and high throughput; such methods enable a fast collection of “fingerprinting signals” referred to each authentic food, subsequently stored into large database for the construction of specific information repositories. In the present case, methods capable of detecting fish adulteration/substitution and involving sensory, physicochemical, DNA-based, chromatographic, and spectroscopic measurements, combined with chemometric tools, are illustrated and commented on.

application of chemometric methods to resolve intermediates formed

African Journals Online (AJOL)

1Department of Chemistry, Addis Ababa University, P.O. Box 1176, Addis ... degradation of methyl orange dye and wastewaters from Ethiopian textile ... These effluents carry the potential toxic organic compounds to cause environmental.

PROPOSTA EXPERIMENTAL DIDÁTICA PARA O ENSINO DE ANÁLISE DE COMPONENTES PRINCIPAIS

Directory of Open Access Journals (Sweden)

Leonardo Valderrama

2016-02-01

Full Text Available Principal component analysis (PCA is a chemometric method that allows for the extraction of chemical information that would otherwise be impossible to determine. Teaching chemometrics to undergraduates can contribute to the overall professional development and training of new teachers, whose profiles have been gaining attention due to the current demand for data interpretation. In this study, a didactic experiment involving PCA is proposed. Spectrophotometry was used in the ultraviolet-visible (UV-Vis region to assess the behavior of anthocyanins extracted from red cabbage at different pH values. The results suggest the possible separation of anthocyanin structures into three distinct groups, according to their chemical characteristics displayed in acid, neutral, and basic media. The objective is to develop educational materials targeted to undergraduate courses, which encompass a larger number of concepts and introduce instrumental techniques currently being employed in both academic research and the industrial sector. Specifically, the proposed experiment introduces concepts related to spectrophotometry in the UV-Vis range and the PCA chemometric method. The materials used are easily accessible, and UV-Vis spectroscopy equipment is less expensive in comparison with other spectroscopy methods.

Integrated HPTLC-based Methodology for the Tracing of Bioactive Compounds in Herbal Extracts Employing Multivariate Chemometrics. A Case Study on Morus alba.

Science.gov (United States)

Chaita, Eliza; Gikas, Evagelos; Aligiannis, Nektarios

2017-03-01

In drug discovery, bioassay-guided isolation is a well-established procedure, and still the basic approach for the discovery of natural products with desired biological properties. However, in these procedures, the most laborious and time-consuming step is the isolation of the bioactive constituents. A prior identification of the compounds that contribute to the demonstrated activity of the fractions would enable the selection of proper chromatographic techniques and lead to targeted isolation. The development of an integrated HPTLC-based methodology for the rapid tracing of the bioactive compounds during bioassay-guided processes, using multivariate statistics. Materials and Methods - The methanol extract of Morus alba was fractionated employing CPC. Subsequently, fractions were assayed for tyrosinase inhibition and analyzed with HPTLC. PLS-R algorithm was performed in order to correlate the analytical data with the biological response of the fractions and identify the compounds with the highest contribution. Two methodologies were developed for the generation of the dataset; one based on manual peak picking and the second based on chromatogram binning. Results and Discussion - Both methodologies afforded comparable results and were able to trace the bioactive constituents (e.g. oxyresveratrol, trans-dihydromorin, 2,4,3'-trihydroxydihydrostilbene). The suggested compounds were compared in terms of R f values and UV spectra with compounds isolated from M. alba using typical bioassay-guided process. Chemometric tools supported the development of a novel HPTLC-based methodology for the tracing of tyrosinase inhibitors in M. alba extract. All steps of the experimental procedure implemented techniques that afford essential key elements for application in high-throughput screening procedures for drug discovery purposes. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Aligning of single and multiple wavelength chromatographic

DEFF Research Database (Denmark)

Nielsen, Niels-Peter Vest; Carstensen, Jens Michael; Smedsgaard, Jørn

1998-01-01

optimised warping (COW) using two input parameters which can be estimated from the observed peak width. COW is demonstrated on constructed single trace chromatograms and on single and multiple wavelength chromatograms obtained from HPLC diode detection analyses of fungal extractsA copy of the C program......The use of chemometric data processing is becoming an important part of modern chromatography. Most chemometric analyses are performed on reduced data sets using areas of selected peaks detected in the chromatograms, which means a loss of data and introduces the problem of extracting peak data from...... to utilise the entire data matrix or rely on peak detection, thus having the same limitations as the commonly used chemometric procedures. The method presented uses the entire chromatographic data matrices and does not require any preprocessing e.g., peak detection. It relies on piecewise linear correlation...

Fingerprints for main varieties of argentinean wines: terroir differentiation by inorganic, organic, and stable isotopic analyses coupled to chemometrics.

Science.gov (United States)

Di Paola-Naranjo, Romina D; Baroni, Maria V; Podio, Natalia S; Rubinstein, Hector R; Fabani, Maria P; Badini, Raul G; Inga, Marcela; Ostera, Hector A; Cagnoni, Mariana; Gallegos, Ernesto; Gautier, Eduardo; Peral-Garcia, Pilar; Hoogewerff, Jurian; Wunderlin, Daniel A

2011-07-27

Our main goal was to investigate if robust chemical fingerprints could be developed for three Argentinean red wines based on organic, inorganic, and isotopic patterns, in relation to the regional soil composition. Soils and wines from three regions (Mendoza, San Juan, and Córdoba) and three varieties (Cabernet Sauvignon, Malbec, and Syrah) were collected. The phenolic profile was determined by HPLC-MS/MS and multielemental composition by ICP-MS; (87)Sr/(86)Sr and δ(13)C were determined by TIMS and IRMS, respectively. Chemometrics allowed robust differentiation between regions, wine varieties, and the same variety from different regions. Among phenolic compounds, resveratrol concentration was the most useful marker for wine differentiation, whereas Mg, K/Rb, Ca/Sr, and (87)Sr/(86)Sr were the main inorganic and isotopic parameters selected. Generalized Procrustes analysis (GPA) using two studied matrices (wine and soil) shows consensus between them and clear differences between studied areas. Finally, we applied a canonical correlation analysis, demonstrating significant correlation (r = 0.99; p wine composition. To our knowledge this is the first report combining independent variables, constructing a fingerprint including elemental composition, isotopic, and polyphenol patterns to differentiate wines, matching part of this fingerprint with the soil provenance.

Development of a HS-SPME-GC/MS protocol assisted by chemometric tools to study herbivore-induced volatiles in Myrcia splendens.

Science.gov (United States)

Souza Silva, Érica A; Saboia, Giovanni; Jorge, Nina C; Hoffmann, Camila; Dos Santos Isaias, Rosy Mary; Soares, Geraldo L G; Zini, Claudia A

2017-12-01

A headspace solid phase microextraction (HS-SPME) method combined with gas chromatography-mass spectrometry (GC/MS) was developed and optimized for extraction and analysis of volatile organic compounds (VOC) of leaves and galls of Myrcia splendens. Through a process of optimization of main factors affecting HS-SPME efficiency, the coating divivnilbenzene-carboxen-polydimethylsiloxane (DVB/Car/PDMS) was chosen as the optimum extraction phase, not only in terms of extraction efficiency, but also for its broader analyte coverage. Optimum extraction temperature was 30°C, while an extraction time of 15min provided the best compromise between extraction efficiencies of lower and higher molecular weight compounds. The optimized protocol was demonstrated to be capable of sampling plant material with high reproducibility, considering that most classes of analytes met the 20% RSD FDA criterion. The optimized method was employed for the analysis of three classes of M. splendens samples, generating a final list of 65 tentatively identified VOC, including alcohols, aldehydes, esters, ketones, phenol derivatives, as well as mono and sesquiterpenes. Significant differences were evident amongst the volatile profiles obtained from non-galled leaves (NGL) and leaf-folding galls (LFG) of M. splendens. Several differences pertaining to amounts of alcohols and aldehydes were detected between samples, particularly regarding quantities of green leaf volatiles (GLV). Alcohols represented about 14% of compounds detected in gall samples, whereas in non-galled samples, alcohol content was below 5%. Phenolic derived compounds were virtually absent in reference samples, while in non-galled leaves and galls their content ranged around 0.2% and 0.4%, respectively. Likewise, methyl salicylate, a well-known signal of plant distress, amounted for 1.2% of the sample content of galls, whereas it was only present in trace levels in reference samples. Chemometric analysis based on Heatmap associated

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.

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.

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.

Ratio manipulating spectrophotometry versus chemometry as stability indicating methods for cefquinome sulfate determination.

Science.gov (United States)

Yehia, Ali M; Arafa, Reham M; Abbas, Samah S; Amer, Sawsan M

2016-01-15

Spectral resolution of cefquinome sulfate (CFQ) in the presence of its degradation products was studied. Three selective, accurate and rapid spectrophotometric methods were performed for the determination of CFQ in the presence of either its hydrolytic, oxidative or photo-degradation products. The proposed ratio difference, derivative ratio and mean centering are ratio manipulating spectrophotometric methods that were satisfactorily applied for selective determination of CFQ within linear range of 5.0-40.0 μg mL(-1). Concentration Residuals Augmented Classical Least Squares was applied and evaluated for the determination of the cited drug in the presence of its all degradation products. Traditional Partial Least Squares regression was also applied and benchmarked against the proposed advanced multivariate calibration. Experimentally designed 25 synthetic mixtures of three factors at five levels were used to calibrate and validate the multivariate models. Advanced chemometrics succeeded in quantitative and qualitative analyses of CFQ along with its hydrolytic, oxidative and photo-degradation products. The proposed methods were applied successfully for different pharmaceutical formulations analyses. These developed methods were simple and cost-effective compared with the manufacturer's RP-HPLC method. Copyright © 2015 Elsevier B.V. All rights reserved.

Linear support vector regression and partial least squares chemometric models for determination of Hydrochlorothiazide and Benazepril hydrochloride in presence of related impurities: A comparative study

Science.gov (United States)

Naguib, Ibrahim A.; Abdelaleem, Eglal A.; Draz, Mohammed E.; Zaazaa, Hala E.

2014-09-01

Partial least squares regression (PLSR) and support vector regression (SVR) are two popular chemometric models that are being subjected to a comparative study in the presented work. The comparison shows their characteristics via applying them to analyze Hydrochlorothiazide (HCZ) and Benazepril hydrochloride (BZ) in presence of HCZ impurities; Chlorothiazide (CT) and Salamide (DSA) as a case study. The analysis results prove to be valid for analysis of the two active ingredients in raw materials and pharmaceutical dosage form through handling UV spectral data in range (220-350 nm). For proper analysis a 4 factor 4 level experimental design was established resulting in a training set consisting of 16 mixtures containing different ratios of interfering species. An independent test set consisting of 8 mixtures was used to validate the prediction ability of the suggested models. The results presented indicate the ability of mentioned multivariate calibration models to analyze HCZ and BZ in presence of HCZ impurities CT and DSA with high selectivity and accuracy of mean percentage recoveries of (101.01 ± 0.80) and (100.01 ± 0.87) for HCZ and BZ respectively using PLSR model and of (99.78 ± 0.80) and (99.85 ± 1.08) for HCZ and BZ respectively using SVR model. The analysis results of the dosage form were statistically compared to the reference HPLC method with no significant differences regarding accuracy and precision. SVR model gives more accurate results compared to PLSR model and show high generalization ability, however, PLSR still keeps the advantage of being fast to optimize and implement.

Quantitative assessment of metal dysregulation in β-thalassemia patients in comparison with healthy controls by ICP-MS and chemometric analyses.

Science.gov (United States)

Farooq, Sabiha; Mazhar, Wardah; Siddiqui, Amna Jabbar; Ansari, Saqib Hussain; Musharraf, Syed Ghulam

2018-01-31

β-Thalassemia is one of the most common inherited disorders and is widely distributed throughout the world. Owing to severe deficiencies in red blood cell production, blood transfusion is required to correct anemia for normal growth and development but causes additional complications owing to iron overload. The aim of this study is to quantify the biometal dysregulations in β-thalassemia patients as compared with healthy controls. A total of 17 elements were analyzed in serum samples of β-thalassemia patients and healthy controls using ICP-MS followed by chemometric analyses. Out of these analyzed elements, 14 showed a significant difference between healthy and disease groups at p 3. A PLS-DA model revealed an excellent separation with 89.8% sensitivity and 97.2% specificity and the overall accuracy of the model was 92.2%. This metallomic study revealed that there is major difference in metallomic profiling of β-thalassemia patients specifically in Co, Mn, Ni, V and Ba, whereas the fold changes in Co, Mn, V and Ba were found to be greater than that in Fe, providing evidence that, in addition to Fe, other metals are also altered significantly and therefore chelation therapy for other metals may also needed in β-thalassemia patients. Copyright © 2018 John Wiley & Sons, Ltd.

Linking the Resource Description Framework to cheminformatics and proteochemometrics

Directory of Open Access Journals (Sweden)

Willighagen Egon L

2011-03-01

Full Text Available Abstract Background Semantic web technologies are finding their way into the life sciences. Ontologies and semantic markup have already been used for more than a decade in molecular sciences, but have not found widespread use yet. The semantic web technology Resource Description Framework (RDF and related methods show to be sufficiently versatile to change that situation. Results The work presented here focuses on linking RDF approaches to existing molecular chemometrics fields, including cheminformatics, QSAR modeling and proteochemometrics. Applications are presented that link RDF technologies to methods from statistics and cheminformatics, including data aggregation, visualization, chemical identification, and property prediction. They demonstrate how this can be done using various existing RDF standards and cheminformatics libraries. For example, we show how IC50 and Ki values are modeled for a number of biological targets using data from the ChEMBL database. Conclusions We have shown that existing RDF standards can suitably be integrated into existing molecular chemometrics methods. Platforms that unite these technologies, like Bioclipse, makes this even simpler and more transparent. Being able to create and share workflows that integrate data aggregation and analysis (visual and statistical is beneficial to interoperability and reproducibility. The current work shows that RDF approaches are sufficiently powerful to support molecular chemometrics workflows.

Toward an integrative social identity model of collective action : A quantitative research synthesis of three socio-psychological perspectives

NARCIS (Netherlands)

Van Zomeren, M.; Postmes, T.; Spears, R.

An integrative social identity model of collective action (SIMCA) is developed that incorporates 3 socio-psychological perspectives on collective action. Three meta-analyses synthesized a total of 182 effects of perceived injustice, efficacy, and identity on collective action (corresponding to these

Toward an integrative Social Identity model of Collective Action: A quantitative research synthesis of three socio-psychological perspectives.

NARCIS (Netherlands)

van Zomeren, M.; Postmes, T.; Spears, R.

2008-01-01

An integrative social identity model of collective action (SIMCA) is developed that incorporates 3 socio-psychological perspectives on collective action. Three meta-analyses synthesized a total of 182 effects of perceived injustice, efficacy, and identity on collective action (corresponding to these

Antioxidant capacity of cornelian cherry (Cornus mas L.) - comparison between permanganate reducing antioxidant capacity and other antioxidant methods.

Science.gov (United States)

Popović, Boris M; Stajner, Dubravka; Slavko, Kevrešan; Sandra, Bijelić

2012-09-15

Ethanol extracts (80% in water) of 10 cornelian cherry (Cornus mas L.) genotypes were studied for antioxidant properties, using methods including DPPH(), ()NO, O(2)(-) and ()OH antiradical powers, FRAP, total phenolic and anthocyanin content (TPC and ACC) and also one relatively new, permanganate method (permanganate reducing antioxidant capacity-PRAC). Lipid peroxidation (LP) was also determined as an indicator of oxidative stress. The data from different procedures were compared and analysed by multivariate techniques (correlation matrix calculation and principal component analysis (PCA)). Significant positive correlations were obtained between TPC, ACC and DPPH(), ()NO, O(2)(-), and ()OH antiradical powers, and also between PRAC and TPC, ACC and FRAP. PCA found two major clusters of cornelian cherry, based on antiradical power, FRAP and PRAC and also on chemical composition. Chemometric evaluation showed close interdependence between PRAC method and FRAP and ACC. There was a huge variation between C. mas genotypes in terms of antioxidant activity. Copyright © 2012 Elsevier Ltd. All rights reserved.

Chemometric classification of potatoes with protected designation of origin according to their producing area and variety.

Science.gov (United States)

Herrero Latorre, Carlos; Barciela García, Julia; García Martín, Sagrario; Peña Crecente, Rosa M

2013-09-04

Potatoes from Galicia (northwestern Spain) are subjected to a Protected Geographic Indication (PGI) according to European legislation. Ten trace elements (Li, Na, K, Rb, Ca, Fe, Mg, Mn, Cu, and Zn) have been determined by atomic spectrometry in two sets of potato samples: Geo-Origin.set and Variety.set. The first data set is composed of samples of the only variety authorized by PGI (Kennebec) with two geographical origins: Galician and non-Galician. The second set corresponds to samples from different varieties but with only Galician geographical origin. Chemometric pattern recognition techniques have been applied to the study of potato geographical and varietal origins in relation to their capability for translocating metals from soil to tuber. Also, authentication models for classifying potato samples with Galician PGI based on metal fingerprints have been developed. The results obtained showed that samples of the same variety, Kennebec, have different metal fingerprints when they have been produced in different geographic locations. Also, diverse potato varieties cultivated on equal geographic Galician origin presented different metal profiles as well. Therefore, it can be concluded that classification studies on the differentiation of geographical origin of foods should take into account information of production area together with varietal data. Otherwise, classification obtained on the basis of the geographical origin could be due to the different variety or vice versa. Finally, two models were constructed for Kennebec Galician samples against Kennebec from other origins as well as against other varieties cultivated in Galicia (Liseta and Baraka). Both models achieved adequate classification rates (93-100%), good sensitivities, and total specificities (100%), allowing the fraud detection in the PGI label.

Discrimination between authentic and false tax stamps from liquor bottles using laser-induced breakdown spectroscopy and chemometrics

International Nuclear Information System (INIS)

Gonzaga, Fabiano Barbieri; Rocha, Werickson Fortunato de Carvalho; Correa, Deleon Nascimento

2015-01-01

This work describes the preliminary application of a compact and low-cost laser-induced breakdown spectroscopy (LIBS) instrument for falsification detection of tax stamps used in alcoholic beverages. The new instrument was based on a diode-pumped passively Q-switched Nd:YLF microchip laser and a mini-spectrometer containing a Czerny–Turner polichromator coupled to a non-intensified, non-gated, and non-cooled 2048 pixel linear sensor array (200 to 850 nm spectral range). Twenty-three tax stamp samples were analyzed by firing laser pulses within two different regions of each sample: a hologram and a blank paper region. For each acquired spectrum, the emitted radiation was integrated for 3000 ms under the continuous application of laser pulses at 100 Hz (integration of 300 plasmas). Principal component analysis (PCA) or hierarchical cluster analysis (HCA) of all emission spectra from the hologram or blank paper region revealed two well-defined groups of authentic and false samples. Moreover, for the hologram data, three subgroups of false samples were found. Additionally, partial least squares discriminant analysis (PLS-DA) was successfully applied for the detection of the false tax stamps using all emission spectra from hologram or blank paper region. The discrimination between the samples was mostly ascribed to different levels of calcium concentration in the samples. - Highlights: • Compact and low-cost laser-induced breakdown spectrometer • Analysis of tax stamps used in alcoholic beverages • Detection of false tax stamps using the LIBS spectra and chemometrics • Falsification detection ascribed to different levels of calcium concentration

Discrimination between authentic and false tax stamps from liquor bottles using laser-induced breakdown spectroscopy and chemometrics

Energy Technology Data Exchange (ETDEWEB)

Gonzaga, Fabiano Barbieri, E-mail: fbgonzaga@inmetro.gov.br [Chemical Metrology Division, National Institute of Metrology, Quality and Technology (INMETRO), Av. Nossa Senhora das Graças, 50, Xerém, 25250-020 Duque de Caxias, RJ (Brazil); Rocha, Werickson Fortunato de Carvalho [Chemical Metrology Division, National Institute of Metrology, Quality and Technology (INMETRO), Av. Nossa Senhora das Graças, 50, Xerém, 25250-020 Duque de Caxias, RJ (Brazil); Correa, Deleon Nascimento [Technical–Scientific Police Superintendency, Criminalistic Institute Dr. Octávio Eduardo de Brito Alvarenga—IC-SPTC-SP, 05507-060 São Paulo, SP (Brazil)

2015-07-01

This work describes the preliminary application of a compact and low-cost laser-induced breakdown spectroscopy (LIBS) instrument for falsification detection of tax stamps used in alcoholic beverages. The new instrument was based on a diode-pumped passively Q-switched Nd:YLF microchip laser and a mini-spectrometer containing a Czerny–Turner polichromator coupled to a non-intensified, non-gated, and non-cooled 2048 pixel linear sensor array (200 to 850 nm spectral range). Twenty-three tax stamp samples were analyzed by firing laser pulses within two different regions of each sample: a hologram and a blank paper region. For each acquired spectrum, the emitted radiation was integrated for 3000 ms under the continuous application of laser pulses at 100 Hz (integration of 300 plasmas). Principal component analysis (PCA) or hierarchical cluster analysis (HCA) of all emission spectra from the hologram or blank paper region revealed two well-defined groups of authentic and false samples. Moreover, for the hologram data, three subgroups of false samples were found. Additionally, partial least squares discriminant analysis (PLS-DA) was successfully applied for the detection of the false tax stamps using all emission spectra from hologram or blank paper region. The discrimination between the samples was mostly ascribed to different levels of calcium concentration in the samples. - Highlights: • Compact and low-cost laser-induced breakdown spectrometer • Analysis of tax stamps used in alcoholic beverages • Detection of false tax stamps using the LIBS spectra and chemometrics • Falsification detection ascribed to different levels of calcium concentration.

Two and three way spectrophotometric-assisted multivariate determination of linezolid in the presence of its alkaline and oxidative degradation products and application to pharmaceutical formulation

Science.gov (United States)

Hegazy, Maha Abd El-Monem; Eissa, Maya Shaaban; Abd El-Sattar, Osama Ibrahim; Abd El-Kawy, Mohammad

2014-07-01

Linezolid (LIN) is determined in the presence of its alkaline (ALK) and oxidative (OXD) degradation products without preliminary separation based on ultraviolet spectrophotometry using two-way chemometric methods; principal component regression (PCR) and partial least-squares (PLS), and three-way chemometric methods; parallel factor analysis (PARAFAC) and multi-way partial least squares (N-PLS). A training set of mixtures containing LIN, ALK and OXD; was prepared in the concentration ranges of 12-18, 2.4-3.6 and 1.2-1.8 μg mL-1, respectively according to a multilevel multifactor experimental design. The multivariate calibrations were obtained by measuring the zero-order absorbance from 220 to 320 nm using the training set. The validation of the multivariate methods was realized by analyzing their synthetic mixtures. The capabilities of the chemometric analysis methods for the analysis of real samples were evaluated by determination of LIN in its pharmaceutical preparation with satisfactory results. The accuracy of the methods, evaluated through the root mean square error of prediction (RMSEP), was 0.058, 0.026, 0.101 and 0.026 for LIN using PCR, PLS, PARAFAC and N-PLS, respectively. Protolytic equilibria of LIN and its degradation products were evaluated using the corresponding absorption spectra-pH data obtained with PARAFAC. The obtained pKa values of LIN, ALK and OXD are 5.70, 8.90 and 6.15, respectively. The results obtained were statistically compared to that of a reported HPLC method, and there was no significant difference between the proposed methods and the reported method regarding both accuracy and precision.

Optimal Optimisation in Chemometrics

NARCIS (Netherlands)

Hageman, J.A.

2004-01-01

The use of global optimisation methods is not straightforward, especially for the more difficult optimisation problems. Solutions have to be found for items such as the evaluation function, representation, step function and meta-parameters, before any useful results can be obtained. This thesis aims

Development of Process Analytical Technology (PAT) methods for controlled release pellet coating.

Science.gov (United States)

Avalle, P; Pollitt, M J; Bradley, K; Cooper, B; Pearce, G; Djemai, A; Fitzpatrick, S

2014-07-01

This work focused on the control of the manufacturing process for a controlled release (CR) pellet product, within a Quality by Design (QbD) framework. The manufacturing process was Wurster coating: firstly layering active pharmaceutical ingredient (API) onto sugar pellet cores and secondly a controlled release (CR) coating. For each of these two steps, development of a Process Analytical Technology (PAT) method is discussed and also a novel application of automated microscopy as the reference method. Ultimately, PAT methods should link to product performance and the two key Critical Quality Attributes (CQAs) for this CR product are assay and release rate, linked to the API and CR coating steps respectively. In this work, the link between near infra-red (NIR) spectra and those attributes was explored by chemometrics over the course of the coating process in a pilot scale industrial environment. Correlations were built between the NIR spectra and coating weight (for API amount), CR coating thickness and dissolution performance. These correlations allow the coating process to be monitored at-line and so better control of the product performance in line with QbD requirements. Copyright © 2014 Elsevier B.V. All rights reserved.

Preparation of Gold Nanoparticles for Biomedical Applications Using ...

African Journals Online (AJOL)

HP

Tropical Journal of Pharmaceutical Research June 2013; 12 (3): 295-298 ... Applications Using Chemometric Technique. Soheila Honary. 1* ... approach for optimizing and testing the robustness of gold nanoparticle preparation method.

Discrimination of Apple Liqueurs (Nalewka) Using a Voltammetric Electronic Tongue, UV-Vis and Raman Spectroscopy.

Science.gov (United States)

Śliwińska, Magdalena; Garcia-Hernandez, Celia; Kościński, Mikołaj; Dymerski, Tomasz; Wardencki, Waldemar; Namieśnik, Jacek; Śliwińska-Bartkowiak, Małgorzata; Jurga, Stefan; Garcia-Cabezon, Cristina; Rodriguez-Mendez, Maria Luz

2016-10-09

The capability of a phthalocyanine-based voltammetric electronic tongue to analyze strong alcoholic beverages has been evaluated and compared with the performance of spectroscopic techniques coupled to chemometrics. Nalewka Polish liqueurs prepared from five apple varieties have been used as a model of strong liqueurs. Principal Component Analysis has demonstrated that the best discrimination between liqueurs prepared from different apple varieties is achieved using the e-tongue and UV-Vis spectroscopy. Raman spectra coupled to chemometrics have not been efficient in discriminating liqueurs. The calculated Euclidean distances and the k-Nearest Neighbors algorithm (kNN) confirmed these results. The main advantage of the e-tongue is that, using PLS-1, good correlations have been found simultaneously with the phenolic content measured by the Folin-Ciocalteu method (R² of 0.97 in calibration and R² of 0.93 in validation) and also with the density, a marker of the alcoholic content method (R² of 0.93 in calibration and R² of 0.88 in validation). UV-Vis coupled with chemometrics has shown good correlations only with the phenolic content (R² of 0.99 in calibration and R² of 0.99 in validation) but correlations with the alcoholic content were low. Raman coupled with chemometrics has shown good correlations only with density (R² of 0.96 in calibration and R² of 0.85 in validation). In summary, from the three holistic methods evaluated to analyze strong alcoholic liqueurs, the voltammetric electronic tongue using phthalocyanines as sensing elements is superior to Raman or UV-Vis techniques because it shows an excellent discrimination capability and remarkable correlations with both antioxidant capacity and alcoholic content-the most important parameters to be measured in this type of liqueurs.

Robust procedures in chemometrics

DEFF Research Database (Denmark)

Kotwa, Ewelina

properties of the analysed data. The broad theoretical background of robust procedures was given as a very useful supplement to the classical methods, and a new tool, based on robust PCA, aiming at identifying Rayleigh and Raman scatters in excitation-mission (EEM) data was developed. The results show...

A PLS-based extractive spectrophotometric method for simultaneous determination of carbamazepine and carbamazepine-10,11-epoxide in plasma and comparison with HPLC

Science.gov (United States)

Hemmateenejad, Bahram; Rezaei, Zahra; Khabnadideh, Soghra; Saffari, Maryam

2007-11-01

Carbamazepine (CBZ) undergoes enzyme biotransformation through epoxidation with the formation of its metabolite, carbamazepine-10,11-epoxide (CBZE). A simple chemometrics-assisted spectrophotometric method has been proposed for simultaneous determination of CBZ and CBZE in plasma. A liquid extraction procedure was operated to separate the analytes from plasma, and the UV absorbance spectra of the resultant solutions were subjected to partial least squares (PLS) regression. The optimum number of PLS latent variables was selected according to the PRESS values of leave-one-out cross-validation. A HPLC method was also employed for comparison. The respective mean recoveries for analysis of CBZ and CBZE in synthetic mixtures were 102.57 (±0.25)% and 103.00 (±0.09)% for PLS and 99.40 (±0.15)% and 102.20 (±0.02)%. The concentrations of CBZ and CBZE were also determined in five patients using the PLS and HPLC methods. The results showed that the data obtained by PLS were comparable with those obtained by HPLC method.

Verification of rapid method for estimation of added food colorant type in boiled sausages based on measurement of cross section color

Science.gov (United States)

Jovanović, J.; Petronijević, R. B.; Lukić, M.; Karan, D.; Parunović, N.; Branković-Lazić, I.

2017-09-01

During the previous development of a chemometric method for estimating the amount of added colorant in meat products, it was noticed that the natural colorant most commonly added to boiled sausages, E 120, has different CIE-LAB behavior compared to artificial colors that are used for the same purpose. This has opened the possibility of transforming the developed method into a method for identifying the addition of natural or synthetic colorants in boiled sausages based on the measurement of the color of the cross-section. After recalibration of the CIE-LAB method using linear discriminant analysis, verification was performed on 76 boiled sausages, of either frankfurters or Parisian sausage types. The accuracy and reliability of the classification was confirmed by comparison with the standard HPLC method. Results showed that the LDA + CIE-LAB method can be applied with high accuracy, 93.42 %, to estimate food color type in boiled sausages. Natural orange colors can give false positive results. Pigments from spice mixtures had no significant effect on CIE-LAB results.

Micro-Raman spectroscopy of natural and synthetic indigo samples.

Science.gov (United States)

Vandenabeele, Peter; Moens, Luc

2003-02-01

In this work indigo samples from three different sources are studied by using Raman spectroscopy: the synthetic pigment and pigments from the woad (Isatis tinctoria) and the indigo plant (Indigofera tinctoria). 21 samples were obtained from 8 suppliers; for each sample 5 Raman spectra were recorded and used for further chemometrical analysis. Principal components analysis (PCA) was performed as data reduction method before applying hierarchical cluster analysis. Linear discriminant analysis (LDA) was implemented as a non-hierarchical supervised pattern recognition method to build a classification model. In order to avoid broad-shaped interferences from the fluorescence background, the influence of 1st and 2nd derivatives on the classification was studied by using cross-validation. Although chemically identical, it is shown that Raman spectroscopy in combination with suitable chemometric methods has the potential to discriminate between synthetic and natural indigo samples.

Developmental changes in leaf phenolics composition from three artichoke cvs. (Cynara scolymus) as determined via UHPLC-MS and chemometrics.

Science.gov (United States)

El Senousy, Amira S; Farag, Mohamed A; Al-Mahdy, Dalia A; Wessjohann, Ludger A

2014-12-01

The metabolomic differences in phenolics from leaves derived from 3 artichoke cultivars (Cynara scolymus): American Green Globe, French Hyrious and Egyptian Baladi, collected at different developmental stages, were assessed using UHPLC-MS coupled to chemometrics. Ontogenic changes were considered as leaves were collected at four different time intervals and positions (top and basal) during artichoke development. Unsupervised principal component analysis (PCA) and supervised orthogonal projection to latent structures-discriminant analysis (O2PLS-DA) were used for comparing and classification of samples harvested from different cultivars at different time points and positions. A clear separation among the three investigated cultivars was revealed, with the American Green Globe samples found most enriched in caffeic acid conjugates and flavonoids vs. other cultivars. Furthermore, these metabolites also showed a marked effect on the discrimination between leaf samples from cultivars harvested at different positions, regardless of the plant age. Metabolite absolute quantifications further confirmed that discrimination was mostly influenced by phenolic compounds, namely caffeoylquinic acids and flavonoids. This study demonstrates an effect of artichoke leaf position, regardless of plant age, on its secondary metabolites composition. To the best of our knowledge, this is the first report for compositional differences among artichoke leaves, based on their positions, via a metabolomic approach and suggesting that top positioned artichoke leaves present a better source of caffeoylquinic acids, compared to basal ones. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.)

Screening for dioxin contamination in fish oil by PARAFAC and N-PLSR analysis of fluorescence landscapes

DEFF Research Database (Denmark)

Kjær Pedersen, D.; Munck, L.; Balling Engelsen, S.

2002-01-01

A preliminary investigation of fish oils demonstrates that fluorescence excitation-emission landscapes evaluated by 3-way chemometric methods may be a candidate for an inexpensive screening method to indicate the level of contamination by dioxins and PCB’s which are normally analysed with expensive...

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.

Development and validation of green method for estimation of clarithromycin in pharmaceutical formulation by transmission fourier transform infrared spectroscopy

International Nuclear Information System (INIS)

Mallah, M.A.; Sherazi, S.T.H.; Mahesar, S.A.; Rauf, A.

2012-01-01

A rapid, sensitive and environmental friendly analytical method for the direct determination of clarithromycin in tablet formulations through transmission Fourier Transform Infrared (FT-IR) spectroscopy has been successfully developed for routine quality control analysis. This method avoids any sample pretreatment except grinding or use of any solvent as extraction is no more required. Standards and samples were analysed in the form of KBr pellet for recording FT-IR spectra. In the final step, chemometric method was used to filter out unmatched spectral features and the converted and filtered spectra were used to build a calibration model based on partial least square (PLS) using the FT-IR carbonyl region (C=O) from 2965-1662 cm/sup -1/. The excellent correlation coefficient (R2) was achieved (0.9999). This also fulfills the ever increasing demand of pharmaceutical industries for developing sensitive, economical and less time consuming methods for the quantification of Active Pharmaceutical Ingredients (API) while monitoring quality of finished product with total analysis time of less than three minutes. (author)

Atmospheric pressure chemical ionisation mass spectrometry analysis linked with chemometrics for food classification - a case study: geographical provenance and cultivar classification of monovarietal clarified apple juices.

Science.gov (United States)

Gan, Heng-Hui; Soukoulis, Christos; Fisk, Ian

2014-03-01

In the present work, we have evaluated for first time the feasibility of APCI-MS volatile compound fingerprinting in conjunction with chemometrics (PLS-DA) as a new strategy for rapid and non-destructive food classification. For this purpose 202 clarified monovarietal juices extracted from apples differing in their botanical and geographical origin were used for evaluation of the performance of APCI-MS as a classification tool. For an independent test set PLS-DA analyses of pre-treated spectral data gave 100% and 94.2% correct classification rate for the classification by cultivar and geographical origin, respectively. Moreover, PLS-DA analysis of APCI-MS in conjunction with GC-MS data revealed that masses within the spectral ACPI-MS data set were related with parent ions or fragments of alkyesters, carbonyl compounds (hexanal, trans-2-hexenal) and alcohols (1-hexanol, 1-butanol, cis-3-hexenol) and had significant discriminating power both in terms of cultivar and geographical origin. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Different Spectrophotometric Methods for Simultaneous Determination of Trelagliptin and Its Acid Degradation Product

Science.gov (United States)

Hassan, Mostafa A.; Zaghary, Wafaa A.

2018-01-01

New spectrophotometric and chemometric methods were carried out for the simultaneous assay of trelagliptin (TRG) and its acid degradation product (TAD) and applied successfully as a stability indicating assay to recently approved Zafatek® tablets. TAD was monitored using TLC to ensure complete degradation. Furthermore, HPLC was used to confirm dealing with one major acid degradation product. The proposed methods were developed by manipulating zero-order, first-derivative, and ratio spectra of TRG and TAD using simultaneous equation, first-derivative, and mean-centering methods, respectively. Using Spectra Manager II and Minitab v.14 software, the absorbance at 274 nm–260.4 nm, amplitudes at 260.4 nm–274.0 nm, and mean-centered values at 287.6 nm–257.2 nm were measured against methanol as a blank for TRG and TAD, respectively. Linearity and the other validation parameters were acceptable at concentration ranges of 5–50 μg/mL and 2.5–25 μg/mL for TRG and TAD, respectively. Using one-way analysis of variance (ANOVA), the optimized methods were compared and proved to be accurate for the simultaneous assay of TRG and TAD. PMID:29629213

Detection of Poisonous Herbs by Terahertz Time-Domain Spectroscopy

Science.gov (United States)

Zhang, H.; Li, Z.; Chen, T.; Liu, J.-J.

2018-03-01

The aim of this paper is the application of terahertz (THz) spectroscopy combined with chemometrics techniques to distinguish poisonous and non-poisonous herbs which both have a similar appearance. Spectra of one poisonous and two non-poisonous herbs (Gelsemium elegans, Lonicera japonica Thunb, and Ficus Hirta Vahl) were obtained in the range 0.2-1.4 THz by using a THz time-domain spectroscopy system. Principal component analysis (PCA) was used for feature extraction. The prediction accuracy of classification is between 97.78 to 100%. The results demonstrate an efficient and applicative method to distinguish poisonous herbs, and it may be implemented by using THz spectroscopy combined with chemometric algorithms.

Single excitation-emission fluorescence spectrum (EEF) for determination of cetane improver in diesel fuel.

Science.gov (United States)

Insausti, Matías; Fernández Band, Beatriz S

2015-04-05

A highly sensitive spectrofluorimetric method has been developed for the determination of 2-ethylhexyl nitrate in diesel fuel. Usually, this compound is used as an additive in order to improve cetane number. The analytical method consists in building the chemometric model as a first step. Then, it is possible to quantify the analyte with only recording a single excitation-emission fluorescence spectrum (EEF), whose data are introduced in the chemometric model above mentioned. Another important characteristic of this method is that the fuel sample was used without any pre-treatment for EEF. This work provides an interest improvement to fluorescence techniques using the rapid and easily applicable EEF approach to analyze such complex matrices. Exploding EEF was the key to a successful determination, obtaining a detection limit of 0.00434% (v/v) and a limit of quantification of 0.01446% (v/v). Copyright © 2015 Elsevier B.V. All rights reserved.

Investigation of the equality constraint effect on the reduction of the rotational ambiguity in three-component system using a novel grid search method.

Science.gov (United States)

Beyramysoltan, Samira; Rajkó, Róbert; Abdollahi, Hamid

2013-08-12

The obtained results by soft modeling multivariate curve resolution methods often are not unique and are questionable because of rotational ambiguity. It means a range of feasible solutions equally fit experimental data and fulfill the constraints. Regarding to chemometric literature, a survey of useful constraints for the reduction of the rotational ambiguity is a big challenge for chemometrician. It is worth to study the effects of applying constraints on the reduction of rotational ambiguity, since it can help us to choose the useful constraints in order to impose in multivariate curve resolution methods for analyzing data sets. In this work, we have investigated the effect of equality constraint on decreasing of the rotational ambiguity. For calculation of all feasible solutions corresponding with known spectrum, a novel systematic grid search method based on Species-based Particle Swarm Optimization is proposed in a three-component system. Copyright © 2013 Elsevier B.V. All rights reserved.

Discrimination of edible oils and fats by combination of multivariate pattern recognition and FT-IR spectroscopy: A comparative study between different modeling methods

Science.gov (United States)

Javidnia, Katayoun; Parish, Maryam; Karimi, Sadegh; Hemmateenejad, Bahram

2013-03-01

By using FT-IR spectroscopy, many researchers from different disciplines enrich the experimental complexity of their research for obtaining more precise information. Moreover chemometrics techniques have boosted the use of IR instruments. In the present study we aimed to emphasize on the power of FT-IR spectroscopy for discrimination between different oil samples (especially fat from vegetable oils). Also our data were used to compare the performance of different classification methods. FT-IR transmittance spectra of oil samples (Corn, Colona, Sunflower, Soya, Olive, and Butter) were measured in the wave-number interval of 450-4000 cm-1. Classification analysis was performed utilizing PLS-DA, interval PLS-DA, extended canonical variate analysis (ECVA) and interval ECVA methods. The effect of data preprocessing by extended multiplicative signal correction was investigated. Whilst all employed method could distinguish butter from vegetable oils, iECVA resulted in the best performances for calibration and external test set with 100% sensitivity and specificity.

Characterization of edible seaweed harvested on the Galician coast (northwestern Spain) using pattern recognition techniques and major and trace element data.

Science.gov (United States)

Romarís-Hortas, Vanessa; García-Sartal, Cristina; Barciela-Alonso, María Carmen; Moreda-Piñeiro, Antonio; Bermejo-Barrera, Pilar

2010-02-10

Major and trace elements in North Atlantic seaweed originating from Galicia (northwestern Spain) were determined by using inductively coupled plasma-optical emission spectrometry (ICP-OES) (Ba, Ca, Cu, K, Mg, Mn, Na, Sr, and Zn), inductively coupled plasma-mass spectrometry (ICP-MS) (Br and I) and hydride generation-atomic fluorescence spectrometry (HG-AFS) (As). Pattern recognition techniques were then used to classify the edible seaweed according to their type (red, brown, and green seaweed) and also their variety (Wakame, Fucus, Sea Spaghetti, Kombu, Dulse, Nori, and Sea Lettuce). Principal component analysis (PCA) and cluster analysis (CA) were used as exploratory techniques, and linear discriminant analysis (LDA) and soft independent modeling of class analogy (SIMCA) were used as classification procedures. In total, t12 elements were determined in a range of 35 edible seaweed samples (20 brown seaweed, 10 red seaweed, 4 green seaweed, and 1 canned seaweed). Natural groupings of the samples (brown, red, and green types) were observed using PCA and CA (squared Euclidean distance between objects and Ward method as clustering procedure). The application of LDA gave correct assignation percentages of 100% for brown, red, and green types at a significance level of 5%. However, a satisfactory classification (recognition and prediction) using SIMCA was obtained only for red seaweed (100% of cases correctly classified), whereas percentages of 89 and 80% were obtained for brown seaweed for recognition (training set) and prediction (testing set), respectively.

A chemometric method for correcting FTIR spectra of biomaterials for interference from water in KBr discs

Science.gov (United States)

FTIR analysis of solid biomaterials by the familiar KBr disc technique is very often frustrated by water interference in the important protein (amide I) and carbohydrate (hydroxyl) regions of their spectra. A method was therefore devised that overcomes the difficulty and measures FTIR spectra of so...

Browse Title Index

African Journals Online (AJOL)

Items 401 - 450 of 1007 ... Vol 4, No 2 (1990), An efficient algorithm for chemical potential computation ... chemometric methods to resolve intermediates formed during photo- catalytic .... Vol 16, No 2 (2002), Characterization of CRUDE OILS and ...

Monitoring multiple components in vinegar fermentation using Raman spectroscopy.

Science.gov (United States)

Uysal, Reyhan Selin; Soykut, Esra Acar; Boyaci, Ismail Hakki; Topcu, Ali

2013-12-15

In this study, the utility of Raman spectroscopy (RS) with chemometric methods for quantification of multiple components in the fermentation process was investigated. Vinegar, the product of a two stage fermentation, was used as a model and glucose and fructose consumption, ethanol production and consumption and acetic acid production were followed using RS and the partial least squares (PLS) method. Calibration of the PLS method was performed using model solutions. The prediction capability of the method was then investigated with both model and real samples. HPLC was used as a reference method. The results from comparing RS-PLS and HPLC with each other showed good correlations were obtained between predicted and actual sample values for glucose (R(2)=0.973), fructose (R(2)=0.988), ethanol (R(2)=0.996) and acetic acid (R(2)=0.983). In conclusion, a combination of RS with chemometric methods can be applied to monitor multiple components of the fermentation process from start to finish with a single measurement in a short time. Copyright © 2013 Elsevier Ltd. All rights reserved.

Chemometric approach to evaluate element distribution in muscle, liver and fish bone of roach (Rutilus rutilus), silver bream (Blicca bjoerkna) and crucian carp (Carassius carassius) from Swarzędzkie Lake (Poland) using ICP-MS and FIAS-CVAAS techniques.

Science.gov (United States)

Chudzińska, Maria; Komorowicz, Izabela; Hanć, Anetta; Gołdyn, Ryszard; Barałkiewicz, Danuta

2016-11-01

The content of elements in fish tissues and organs from Swarzędzkie Lake was investigated in order to evaluate the possible risk associated with their consumption by animals as well as humans. Samples of muscle, liver and fish bone of three fish species; roach (Rutilus rutilus), silver bream (Blicca bjoerkna) and crucian carp (Carassius carassius) were collected from seine catches undertaken as part of the biomanipulation of Swarzędzkie Lake. Element concentration (Al, As, Cd, Co, Cr, Cu, Hg, Ni, Pb, Zn) was determined by inductively coupled plasma mass spectrometry (ICP-MS), with the exception of Hg where the flow injection analysis system cold vapour atomic absorption spectrometry (FIAS-CVAAS) was applied. The study indicated a large variation in the occurrence of the investigated elements in different parts of the fish body. The highest content of Al and Zn was stated in all fish organs for each fish species. The majority of the applied statistical and chemometric methods (e.g., PCA, CA) refer to roach since we had a large number of data for this species. The obtained results were assessed in terms of their accuracy and precision using certified reference material of Fish Muscle ERM BB422.

Shedding light on food fraud: spectrophotometric and spectroscopic methods as a tool against economically motivated adulteration of food

Science.gov (United States)

Petronijević, R. B.; Velebit, B.; Baltić, T.

2017-09-01

Intentional modification of food or substitution of food ingredients with the aim of gaining profit is food fraud or economically motivated adulteration (EMA). EMA appeared in the food supply chain, and following the global expansion of the food market, has become a world-scale problem for the global economy. Food frauds have involved oils, milk and meat products, infant formula, honey, juices, spices, etc. New legislation was enacted in the last decade in order to fight EMA. Effective analytical methods for food fraud detection are few and still in development. The majority of the methods in common use today for EMA detection are time consuming and inappropriate for use on the production line or out of the laboratory. The next step in the evolution of analytical techniques to combat food fraud is development of fast, accurate methods applicable using portable or handheld devices. Spectrophotometric and spectroscopic methods combined with chemometric analysis, and perhaps in combination with other rapid physico-chemical techniques, could be the answer. This review discusses some analytical techniques based on spectrophotometry and spectroscopy, which are used to reveal food fraud and EMA.

A new analytical method for quantification of olive and palm oil in blends with other vegetable edible oils based on the chromatographic fingerprints from the methyl-transesterified fraction.

Science.gov (United States)

Jiménez-Carvelo, Ana M; González-Casado, Antonio; Cuadros-Rodríguez, Luis

2017-03-01

A new analytical method for the quantification of olive oil and palm oil in blends with other vegetable edible oils (canola, safflower, corn, peanut, seeds, grapeseed, linseed, sesame and soybean) using normal phase liquid chromatography, and applying chemometric tools was developed. The procedure for obtaining of chromatographic fingerprint from the methyl-transesterified fraction from each blend is described. The multivariate quantification methods used were Partial Least Square-Regression (PLS-R) and Support Vector Regression (SVR). The quantification results were evaluated by several parameters as the Root Mean Square Error of Validation (RMSEV), Mean Absolute Error of Validation (MAEV) and Median Absolute Error of Validation (MdAEV). It has to be highlighted that the new proposed analytical method, the chromatographic analysis takes only eight minutes and the results obtained showed the potential of this method and allowed quantification of mixtures of olive oil and palm oil with other vegetable oils. Copyright © 2016 Elsevier B.V. All rights reserved.

Sparse Mbplsr for Metabolomics Data and Biomarker Discovery

DEFF Research Database (Denmark)

Karaman, İbrahim

2014-01-01

the link between high throughput metabolomics data generated on different analytical platforms, discover important metabolites deriving from the digestion processes in the gut, and automate metabolic pathway discovery from mass spectrometry. PLS (partial least squares) based chemometric methods were...

In-Depth Two-Year Study of Phenolic Profile Variability among Olive Oils from Autochthonous and Mediterranean Varieties in Morocco, as Revealed by a LC-MS Chemometric Profiling Approach

Directory of Open Access Journals (Sweden)

Aadil Bajoub

2016-12-01

Full Text Available Olive oil phenolic fraction considerably contributes to the sensory quality and nutritional value of this foodstuff. Herein, the phenolic fraction of 203 olive oil samples extracted from fruits of four autochthonous Moroccan cultivars (“Picholine Marocaine”, “Dahbia”, “Haouzia” and “Menara”, and nine Mediterranean varieties recently introduced in Morocco (“Arbequina”, “Arbosana”, “Cornicabra”, “Frantoio”, “Hojiblanca”, “Koroneiki”, “Manzanilla”, “Picholine de Languedoc” and “Picual”, were explored over two consecutive crop seasons (2012/2013 and 2013/2014 by using liquid chromatography-mass spectrometry. A total of 32 phenolic compounds (and quinic acid, belonging to five chemical classes (secoiridoids, simple phenols, flavonoids, lignans and phenolic acids were identified and quantified. Phenolic profiling revealed that the determined phenolic compounds showed variety-dependent levels, being, at the same time, significantly affected by the crop season. Moreover, based on the obtained phenolic composition and chemometric linear discriminant analysis, statistical models were obtained allowing a very satisfactory classification and prediction of the varietal origin of the studied oils.

Liquid chromatographic and spectrophotometric methods for the determination of erythromycin stearate and trimethoprim in tablets

Directory of Open Access Journals (Sweden)

Sonia T. Hassib

2011-12-01

Full Text Available Simple, accurate and precise reversed-phase liquid chromatographic (LC and spectrophotometric methods have been developed and validated for the determination of erythromycin stearate (ERS and trimethoprim (TMP in mixture. In LC method, chromatographic separation was achieved on a Symmetry® Waters C18 column (150 × 4.6 mm, 5 μm based on isocratic elution using a mobile phase consisting of potassium dihydrogen phosphate buffer pH (9:acetonitrile:water (25:100:50, v/v/v at a flow rate of 1.6 ml min−1 with UV detection at 210 nm for ERS and 280 nm for TMP. Besides, two spectrophotometric methods were applied after reaction with perchloric acid (12 M which gives a colored product with ERS. Then, the spectral interference between the colored product of ERS and TMP was resolved by either ratio spectra derivative spectrophotometry in the first spectrophotometric method or chemometric techniques, namely classical least-squares (CLS, principal component regression (PCR and partial least-squares regression (PLS in the second spectrophotometric method. The results were statistically compared using one-way analysis of variance (ANOVA. The methods developed were satisfactorily applied to the analysis of the pharmaceutical preparation containing the two drugs and proved to be specific and accurate for the quality control of the cited drugs in pharmaceutical dosage forms.

[Study of near infrared spectral preprocessing and wavelength selection methods for endometrial cancer tissue].

Science.gov (United States)

Zhao, Li-Ting; Xiang, Yu-Hong; Dai, Yin-Mei; Zhang, Zhuo-Yong

2010-04-01

Near infrared spectroscopy was applied to measure the tissue slice of endometrial tissues for collecting the spectra. A total of 154 spectra were obtained from 154 samples. The number of normal, hyperplasia, and malignant samples was 36, 60, and 58, respectively. Original near infrared spectra are composed of many variables, for example, interference information including instrument errors and physical effects such as particle size and light scatter. In order to reduce these influences, original spectra data should be performed with different spectral preprocessing methods to compress variables and extract useful information. So the methods of spectral preprocessing and wavelength selection have played an important role in near infrared spectroscopy technique. In the present paper the raw spectra were processed using various preprocessing methods including first derivative, multiplication scatter correction, Savitzky-Golay first derivative algorithm, standard normal variate, smoothing, and moving-window median. Standard deviation was used to select the optimal spectral region of 4 000-6 000 cm(-1). Then principal component analysis was used for classification. Principal component analysis results showed that three types of samples could be discriminated completely and the accuracy almost achieved 100%. This study demonstrated that near infrared spectroscopy technology and chemometrics method could be a fast, efficient, and novel means to diagnose cancer. The proposed methods would be a promising and significant diagnosis technique of early stage cancer.

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

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.

A rapid ATR-FTIR spectroscopic method for detection of sibutramine adulteration in tea and coffee based on hierarchical cluster and principal component analyses.

Science.gov (United States)

Cebi, Nur; Yilmaz, Mustafa Tahsin; Sagdic, Osman

2017-08-15

Sibutramine may be illicitly included in herbal slimming foods and supplements marketed as "100% natural" to enhance weight loss. Considering public health and legal regulations, there is an urgent need for effective, rapid and reliable techniques to detect sibutramine in dietetic herbal foods, teas and dietary supplements. This research comprehensively explored, for the first time, detection of sibutramine in green tea, green coffee and mixed herbal tea using ATR-FTIR spectroscopic technique combined with chemometrics. Hierarchical cluster analysis and PCA principle component analysis techniques were employed in spectral range (2746-2656cm -1 ) for classification and discrimination through Euclidian distance and Ward's algorithm. Unadulterated and adulterated samples were classified and discriminated with respect to their sibutramine contents with perfect accuracy without any false prediction. The results suggest that existence of the active substance could be successfully determined at the levels in the range of 0.375-12mg in totally 1.75g of green tea, green coffee and mixed herbal tea by using FTIR-ATR technique combined with chemometrics. Copyright © 2017 Elsevier Ltd. All rights reserved.

Validation of Fluorescence Spectroscopy to Detect Adulteration of Edible Oil in Extra Virgin Olive Oil (EVOO) by Applying Chemometrics.

Science.gov (United States)

Ali, Hina; Saleem, Muhammad; Anser, Muhammad Ramzan; Khan, Saranjam; Ullah, Rahat; Bilal, Muhammad

2018-01-01

Due to high price and nutritional values of extra virgin olive oil (EVOO), it is vulnerable to adulteration internationally. Refined oil or other vegetable oils are commonly blended with EVOO and to unmask such fraud, quick, and reliable technique needs to be standardized and developed. Therefore, in this study, adulteration of edible oil (sunflower oil) is made with pure EVOO and analyzed using fluorescence spectroscopy (excitation wavelength at 350 nm) in conjunction with principal component analysis (PCA) and partial least squares (PLS) regression. Fluorescent spectra contain fingerprints of chlorophyll and carotenoids that are characteristics of EVOO and differentiated it from sunflower oil. A broad intense hump corresponding to conjugated hydroperoxides is seen in sunflower oil in the range of 441-489 nm with the maximum at 469 nm whereas pure EVOO has low intensity doublet peaks in this region at 441 nm and 469 nm. Visible changes in spectra are observed in adulterated EVOO by increasing the concentration of sunflower oil, with an increase in doublet peak and correspondingly decrease in chlorophyll peak intensity. Principal component analysis showed a distinct clustering of adulterated samples of different concentrations. Subsequently, the PLS regression model was best fitted over the complete data set on the basis of coefficient of determination (R 2 ), standard error of calibration (SEC), and standard error of prediction (SEP) of values 0.99, 0.617, and 0.623 respectively. In addition to adulterant, test samples and imported commercial brands of EVOO were also used for prediction and validation of the models. Fluorescence spectroscopy combined with chemometrics showed its robustness to identify and quantify the specified adulterant in pure EVOO.

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.

Determination of ion mobility collision cross sections for unresolved isomeric mixtures using tandem mass spectrometry and chemometric deconvolution

Energy Technology Data Exchange (ETDEWEB)

Harper, Brett [Institute of Biomedical Studies, Baylor University, Waco, TX 76798 (United States); Neumann, Elizabeth K. [Department of Chemistry and Biochemistry, Baylor University, Waco, TX 76798 (United States); Stow, Sarah M.; May, Jody C.; McLean, John A. [Department of Chemistry, Vanderbilt University, Nashville, TN 37235 (United States); Vanderbilt Institute of Chemical Biology, Nashville, TN 37235 (United States); Vanderbilt Institute for Integrative Biosystems Research and Education, Nashville, TN 37235 (United States); Center for Innovative Technology, Nashville, TN 37235 (United States); Solouki, Touradj, E-mail: Touradj_Solouki@baylor.edu [Department of Chemistry and Biochemistry, Baylor University, Waco, TX 76798 (United States)

2016-10-05

Ion mobility (IM) is an important analytical technique for determining ion collision cross section (CCS) values in the gas-phase and gaining insight into molecular structures and conformations. However, limited instrument resolving powers for IM may restrict adequate characterization of conformationally similar ions, such as structural isomers, and reduce the accuracy of IM-based CCS calculations. Recently, we introduced an automated technique for extracting “pure” IM and collision-induced dissociation (CID) mass spectra of IM overlapping species using chemometric deconvolution of post-IM/CID mass spectrometry (MS) data [J. Am. Soc. Mass Spectrom., 2014, 25, 1810–1819]. Here we extend those capabilities to demonstrate how extracted IM profiles can be used to calculate accurate CCS values of peptide isomer ions which are not fully resolved by IM. We show that CCS values obtained from deconvoluted IM spectra match with CCS values measured from the individually analyzed corresponding peptides on uniform field IM instrumentation. We introduce an approach that utilizes experimentally determined IM arrival time (AT) “shift factors” to compensate for ion acceleration variations during post-IM/CID and significantly improve the accuracy of the calculated CCS values. Also, we discuss details of this IM deconvolution approach and compare empirical CCS values from traveling wave (TW)IM-MS and drift tube (DT)IM-MS with theoretically calculated CCS values using the projected superposition approximation (PSA). For example, experimentally measured deconvoluted TWIM-MS mean CCS values for doubly-protonated RYGGFM, RMFGYG, MFRYGG, and FRMYGG peptide isomers were 288.{sub 8} Å{sup 2}, 295.{sub 1} Å{sup 2}, 296.{sub 8} Å{sup 2}, and 300.{sub 1} Å{sup 2}; all four of these CCS values were within 1.5% of independently measured DTIM-MS values.

Determination of ion mobility collision cross sections for unresolved isomeric mixtures using tandem mass spectrometry and chemometric deconvolution

International Nuclear Information System (INIS)

Harper, Brett; Neumann, Elizabeth K.; Stow, Sarah M.; May, Jody C.; McLean, John A.; Solouki, Touradj

2016-01-01

Ion mobility (IM) is an important analytical technique for determining ion collision cross section (CCS) values in the gas-phase and gaining insight into molecular structures and conformations. However, limited instrument resolving powers for IM may restrict adequate characterization of conformationally similar ions, such as structural isomers, and reduce the accuracy of IM-based CCS calculations. Recently, we introduced an automated technique for extracting “pure” IM and collision-induced dissociation (CID) mass spectra of IM overlapping species using chemometric deconvolution of post-IM/CID mass spectrometry (MS) data [J. Am. Soc. Mass Spectrom., 2014, 25, 1810–1819]. Here we extend those capabilities to demonstrate how extracted IM profiles can be used to calculate accurate CCS values of peptide isomer ions which are not fully resolved by IM. We show that CCS values obtained from deconvoluted IM spectra match with CCS values measured from the individually analyzed corresponding peptides on uniform field IM instrumentation. We introduce an approach that utilizes experimentally determined IM arrival time (AT) “shift factors” to compensate for ion acceleration variations during post-IM/CID and significantly improve the accuracy of the calculated CCS values. Also, we discuss details of this IM deconvolution approach and compare empirical CCS values from traveling wave (TW)IM-MS and drift tube (DT)IM-MS with theoretically calculated CCS values using the projected superposition approximation (PSA). For example, experimentally measured deconvoluted TWIM-MS mean CCS values for doubly-protonated RYGGFM, RMFGYG, MFRYGG, and FRMYGG peptide isomers were 288._8 Å"2, 295._1 Å"2, 296._8 Å"2, and 300._1 Å"2; all four of these CCS values were within 1.5% of independently measured DTIM-MS values.

Authentication of fattening diet of Iberian pigs according to their volatile compounds profile from raw subcutaneous fat.

Science.gov (United States)

Narváez-Rivas, M; Pablos, F; Jurado, J M; León-Camacho, M

2011-02-01

The composition of volatile components of subcutaneous fat from Iberian pig has been studied. Purge and trap gas chromatography-mass spectrometry has been used. The composition of the volatile fraction of subcutaneous fat has been used for authentication purposes of different types of Iberian pig fat. Three types of this product have been considered, montanera, extensive cebo and intensive cebo. With classification purposes, several pattern recognition techniques have been applied. In order to find out possible tendencies in the sample distribution as well as the discriminant power of the variables, principal component analysis was applied as visualisation technique. Linear discriminant analysis (LDA) and soft independent modelling by class analogy (SIMCA) were used to obtain suitable classification models. LDA and SIMCA allowed the differentiation of three fattening diets by using the contents in 2,2,4,6,6-pentamethyl-heptane, m-xylene, 2,4-dimethyl-heptane, 6-methyl-tridecane, 1-methoxy-2-propanol, isopropyl alcohol, o-xylene, 3-ethyl-2,2-dimethyl-oxirane, 2,6-dimethyl-undecane, 3-methyl-3-pentanol and limonene.

Metabolite Profiling and Classification of DNA-Authenticated Licorice Botanicals

Science.gov (United States)

Simmler, Charlotte; Anderson, Jeffrey R.; Gauthier, Laura; Lankin, David C.; McAlpine, James B.; Chen, Shao-Nong; Pauli, Guido F.

2015-01-01

Raw licorice roots represent heterogeneous materials obtained from mainly three Glycyrrhiza species. G. glabra, G. uralensis, and G. inflata exhibit marked metabolite differences in terms of flavanones (Fs), chalcones (Cs), and other phenolic constituents. The principal objective of this work was to develop complementary chemometric models for the metabolite profiling, classification, and quality control of authenticated licorice. A total of 51 commercial and macroscopically verified samples were DNA authenticated. Principal component analysis and canonical discriminant analysis were performed on 1H NMR spectra and area under the curve values obtained from UHPLC-UV chromatograms, respectively. The developed chemometric models enable the identification and classification of Glycyrrhiza species according to their composition in major Fs, Cs, and species specific phenolic compounds. Further key outcomes demonstrated that DNA authentication combined with chemometric analyses enabled the characterization of mixtures, hybrids, and species outliers. This study provides a new foundation for the botanical and chemical authentication, classification, and metabolomic characterization of crude licorice botanicals and derived materials. Collectively, the proposed methods offer a comprehensive approach for the quality control of licorice as one of the most widely used botanical dietary supplements. PMID:26244884

Verification of Organic Feed Identity by Fatty Acid Fingerprinting

NARCIS (Netherlands)

Tres, A.; Ruth, van S.M.

2011-01-01

The origin and authenticity of feed for laying hens is an important and fraud-susceptible aspect in the production of organic eggs. Chemical fingerprinting in combination with chemometric methods is increasingly used in conjunction with administrative controls to verify and safeguard the

Botanical supplements: detecting the transition from ingredients to supplements

Science.gov (United States)

Methods were developed using flow injection mass spectrometry (FIMS) and chemometrics for the comparison of spectral similarities and differences of 3 botanical ingredients and their supplements: Echinacea purpurea aerial samples and solid and liquid supplements, E. purpurea root samples and solid s...

Canonical correlation analysis of multiple sensory directed metabolomics data blocks reveals corresponding parts between data blocks.

NARCIS (Netherlands)

Doeswijk, T. G.; Hageman, J.A.; Westerhuis, J.A.; Tikunov, Y.; Bovy, A.; van Eeuwijk, F.A.

2011-01-01

Multiple analytical platforms are frequently used in metabolomics studies. The resulting multiple data blocks contain, in general, similar parts of information which can be disclosed by chemometric methods. The metabolites of interest, however, are usually just a minor part of the complete data

Assessment of repeatability of composition of perfumed waters by high-performance liquid chromatography combined with numerical data analysis based on cluster analysis (HPLC UV/VIS - CA).

Science.gov (United States)

Ruzik, L; Obarski, N; Papierz, A; Mojski, M

2015-06-01

High-performance liquid chromatography (HPLC) with UV/VIS spectrophotometric detection combined with the chemometric method of cluster analysis (CA) was used for the assessment of repeatability of composition of nine types of perfumed waters. In addition, the chromatographic method of separating components of the perfume waters under analysis was subjected to an optimization procedure. The chromatograms thus obtained were used as sources of data for the chemometric method of cluster analysis (CA). The result was a classification of a set comprising 39 perfumed water samples with a similar composition at a specified level of probability (level of agglomeration). A comparison of the classification with the manufacturer's declarations reveals a good degree of consistency and demonstrates similarity between samples in different classes. A combination of the chromatographic method with cluster analysis (HPLC UV/VIS - CA) makes it possible to quickly assess the repeatability of composition of perfumed waters at selected levels of probability. © 2014 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Towards the identification of plant and animal binders on Australian stone knives.

Science.gov (United States)

Blee, Alisa J; Walshe, Keryn; Pring, Allan; Quinton, Jamie S; Lenehan, Claire E

2010-07-15

There is limited information regarding the nature of plant and animal residues used as adhesives, fixatives and pigments found on Australian Aboriginal artefacts. This paper reports the use of FTIR in combination with the chemometric tools principal component analysis (PCA) and hierarchical clustering (HC) for the analysis and identification of Australian plant and animal fixatives on Australian stone artefacts. Ten different plant and animal residues were able to be discriminated from each other at a species level by combining FTIR spectroscopy with the chemometric data analysis methods, principal component analysis (PCA) and hierarchical clustering (HC). Application of this method to residues from three broken stone knives from the collections of the South Australian Museum indicated that two of the handles of knives were likely to have contained beeswax as the fixative whilst Spinifex resin was the probable binder on the third. Copyright 2010 Elsevier B.V. All rights reserved.