Single-Kernel FT-NIR Spectroscopy for Detecting Supersweet Corn (Zea mays L. Saccharata Sturt) Seed Viability with Multivariate Data Analysis.

Science.gov (United States)

Qiu, Guangjun; Lü, Enli; Lu, Huazhong; Xu, Sai; Zeng, Fanguo; Shui, Qin

2018-03-28

The viability and vigor of crop seeds are crucial indicators for evaluating seed quality, and high-quality seeds can increase agricultural yield. The conventional methods for assessing seed viability are time consuming, destructive, and labor intensive. Therefore, a rapid and nondestructive technique for testing seed viability has great potential benefits for agriculture. In this study, single-kernel Fourier transform near-infrared (FT-NIR) spectroscopy with a wavelength range of 1000-2500 nm was used to distinguish viable and nonviable supersweet corn seeds. Various preprocessing algorithms coupled with partial least squares discriminant analysis (PLS-DA) were implemented to test the performance of classification models. The FT-NIR spectroscopy technique successfully differentiated viable seeds from seeds that were nonviable due to overheating or artificial aging. Correct classification rates for both heat-damaged kernels and artificially aged kernels reached 98.0%. The comprehensive model could also attain an accuracy of 98.7% when combining heat-damaged samples and artificially aged samples into one category. Overall, the FT-NIR technique with multivariate data analysis methods showed great potential capacity in rapidly and nondestructively detecting seed viability in supersweet corn.

Monitoring of whey quality with NIR spectroscopy

DEFF Research Database (Denmark)

Kucheryavskiy, Sergey; Lomborg, Carina

2015-01-01

The possibility of using near-infrared (NIR) spectroscopy for monitoring of liquid whey quality parameters during protein production process has been tested. The parameters included total solids, lactose, protein and fat content. The samples for the experiment were taken from real industrial...

Quantification of fructan concentration in grasses using NIR spectroscopy and PLSR

DEFF Research Database (Denmark)

Shetty, Nisha; Gislum, Rene

2011-01-01

Near-infrared reflectance (NIR) spectroscopy combined with chemometrics was used to quantify fructan concentration in samples from seven grass species. Savitzky-Golay first derivative with filter width 7 and polynomial order 2 with mean centering was applied as a spectral pre-treatment method...... to remove unimportant baseline signals. In order to model the NIR spectroscopy data the partial least squares regression (PLSR) approach was used on the full spectra. Variable selection based on PLSR by jack-knifing within a cross-model validation (CMV) framework was applied in order to remove non...... quantification of fructans by NIR spectroscopy is possible and that jack-knifing PLSR within a CMV framework is an effective way to eliminate the wavelengths of no interest. Jack-knifing PLSR did not improve the predictive ability because the root mean square error of prediction (RMSEP) increased (1.37) compared...

Study of Vis/NIR spectroscopy measurement on acidity of yogurt

Science.gov (United States)

He, Yong; Feng, Shuijuan; Wu, Di; Li, Xiaoli

2006-09-01

A fast measurement of pH of yogurt using Vis/NIR-spectroscopy techniques was established in order to measuring the acidity of yogurt rapidly. 27 samples selected separately from five different brands of yogurt were measured by Vis/NIR-spectroscopy. The pH of yogurt on positions scanned by spectrum was measured by a pH meter. The mathematical model between pH and Vis/NIR spectral measurements was established and developed based on partial least squares (PLS) by using Unscramble V9.2. Then 25 unknown samples from 5 different brands were predicted based on the mathematical model. The result shows that The correlation coefficient of pH based on PLS model is more than 0.890, and standard error of calibration (SEC) is 0.037, standard error of prediction (SEP) is 0.043. Through predicting the pH of 25 samples of yogurt from 5 different brands, the correlation coefficient between predictive value and measured value of those samples is more than 0918. The results show the good to excellent prediction performances. The Vis/NIR spectroscopy technique had a significant greater accuracy for determining the value of pH. It was concluded that the VisINIRS measurement technique can be used to measure pH of yogurt fast and accurately, and a new method for the measurement of pH of yogurt was established.

[Identification of varieties of textile fibers by using Vis/NIR infrared spectroscopy technique].

Science.gov (United States)

Wu, Gui-Fang; He, Yong

2010-02-01

The aim of the present paper was to provide new insight into Vis/NIR spectroscopic analysis of textile fibers. In order to achieve rapid identification of the varieties of fibers, the authors selected 5 kinds of fibers of cotton, flax, wool, silk and tencel to do a study with Vis/NIR spectroscopy. Firstly, the spectra of each kind of fiber were scanned by spectrometer, and principal component analysis (PCA) method was used to analyze the characteristics of the pattern of Vis/NIR spectra. Principal component scores scatter plot (PC1 x PC2 x PC3) of fiber indicated the classification effect of five varieties of fibers. The former 6 principal components (PCs) were selected according to the quantity and size of PCs. The PCA classification model was optimized by using the least-squares support vector machines (LS-SVM) method. The authors used the 6 PCs extracted by PCA as the inputs of LS-SVM, and PCA-LS-SVM model was built to achieve varieties validation as well as mathematical model building and optimization analysis. Two hundred samples (40 samples for each variety of fibers) of five varieties of fibers were used for calibration of PCA-LS-SVM model, and the other 50 samples (10 samples for each variety of fibers) were used for validation. The result of validation showed that Vis/NIR spectroscopy technique based on PCA-LS-SVM had a powerful classification capability. It provides a new method for identifying varieties of fibers rapidly and real time, so it has important significance for protecting the rights of consumers, ensuring the quality of textiles, and implementing rationalization production and transaction of textile materials and its production.

Age determination of bottled Chinese rice wine by VIS-NIR spectroscopy

Science.gov (United States)

Yu, Haiyan; Lin, Tao; Ying, Yibin; Pan, Xingxiang

2006-10-01

The feasibility of non-invasive visible and near infrared (VIS-NIR) spectroscopy for determining wine age (1, 2, 3, 4, and 5 years) of Chinese rice wine was investigated. Samples of Chinese rice wine were analyzed in 600 mL square brown glass bottles with side length of approximately 64 mm at room temperature. VIS-NIR spectra of 100 bottled Chinese rice wine samples were collected in transmission mode in the wavelength range of 350-1200 nm by a fiber spectrometer system. Discriminant models were developed based on discriminant analysis (DA) together with raw, first and second derivative spectra. The concentration of alcoholic degree, total acid, and °Brix was determined to validate the NIR results. The calibration result for raw spectra was better than that for first and second derivative spectra. The percentage of samples correctly classified for raw spectra was 98%. For 1-, 2-, and 3-year-old sample groups, the sample were all correctly classified, and for 4- and 5-year-old sample groups, the percentage of samples correctly classified was 92.9%, respectively. In validation analysis, the percentage of samples correctly classified was 100%. The results demonstrated that VIS-NIR spectroscopic technique could be used as a non-invasive, rapid and reliable method for predicting wine age of bottled Chinese rice wine.

PENENTUAN BAHAN KERING BUAH SAWO SECARA TIDAK MERUSAK MENGGUNAKAN NIR SPECTROSCOPY

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Diding Suhandy

2012-12-01

Full Text Available This work was conducted to develop a new measuring system for nondestructive dry matter prediction in sawo fruit using short wavelength near infrared (SW-NIR spectroscopy. In this research, a number of 100 sawo fruits were used as samples. Spectra were acquired using a portable spectrometer (VIS-NIR USB4000, The Ocean Optics, USA with 100 ms integration time and 50 scans for number of scanning. Dry matter was measured using oven drying. The calibration and validation model was developed using the partial least squares (PLS regression method. The result showed that the best calibration model could be developed for original spectra in the wavelength range of  700-990 nm with F= 8, r = 0.92, SEC = 0.68 and  SEP = 0.86. Keywords:   Absorbance mode, dry matter, nondestructive method, sawo fruit, SW-NIR spectroscopy.

Rapid characterization of transgenic and non-transgenic soybean oils by chemometric methods using NIR spectroscopy

Science.gov (United States)

Luna, Aderval S.; da Silva, Arnaldo P.; Pinho, Jéssica S. A.; Ferré, Joan; Boqué, Ricard

Near infrared (NIR) spectroscopy and multivariate classification were applied to discriminate soybean oil samples into non-transgenic and transgenic. Principal Component Analysis (PCA) was applied to extract relevant features from the spectral data and to remove the anomalous samples. The best results were obtained when with Support Vectors Machine-Discriminant Analysis (SVM-DA) and Partial Least Squares-Discriminant Analysis (PLS-DA) after mean centering plus multiplicative scatter correction. For SVM-DA the percentage of successful classification was 100% for the training group and 100% and 90% in validation group for non transgenic and transgenic soybean oil samples respectively. For PLS-DA the percentage of successful classification was 95% and 100% in training group for non transgenic and transgenic soybean oil samples respectively and 100% and 80% in validation group for non transgenic and transgenic respectively. The results demonstrate that NIR spectroscopy can provide a rapid, nondestructive and reliable method to distinguish non-transgenic and transgenic soybean oils.

WIRELESS DISTRIBUTED ACQUISITION SYSTEM FOR NEAR INFRARED SPECTROSCOPY – WDA-NIRS

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J. SAFAIE

2013-07-01

Full Text Available The wireless distributed acquisition system for near infrared spectroscopy (WDA-NIRS is a portable, ultra-compact, continuous wave (CW NIRS system. Its main advantage is that it allows continuous synchronized multi-site hemodynamic monitoring. The WDA-NIRS system calculates online changes in hemoglobin concentration based on modified Beer–Lambert law and the tissue oxygenation index based on the spatial-resolved spectroscopy method. It consists of up to seven signal acquisition units, sufficiently small to be easily attached to any part of the body. These units are remotely synchronized by a PC base station for independent acquisition of NIRS signals. Each acquisition module can be freely adapted to individual requirements such as local skin properties and the microcirculation of interest, e.g., different muscles, brain, skin, etc. For this purpose, the light emitted by each LED can be individually, interactively or automatically adjusted to local needs. Furthermore, the user can freely create an emitter time-multiplexing protocol and choose the detector sensitivity most suitable to a particular situation. The potential diagnostic value of this advanced device is demonstrated by three typical applications.

2D Vis/NIR correlation spectroscopy of cooked chicken meats

Science.gov (United States)

Liu, Yongliang; Chen, Yud-Ren; Ozaki, Yukihiro

2000-03-01

Cooking of chicken meats was investigated by the generalized two-dimensional visible/near-infrared (2D Vis/NIR) correlation spectroscopy. Synchronous and asynchronous spectra in the 400-700 nm visible region suggested that the 445 and 560 nm bands be ascribed to deoxymyoglobin and oxymyoglobin, and at least one of the 475, 520, and 585 nm bands is assignable to the denatured species (metmyoglobin). The asynchronous 2D NIR correlation spectrum showed that CH bands change their spectral intensities before the OH/NH groups during the cooking process, indicating that CH fractions are easily oxidized and degraded. In addition, strong correlation peaks were observed correlating the bands in the visible and NIR spectral regions.

Prediction of pH and color in pork meat using VIS-NIR Near-infrared Spectroscopy (NIRS

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Elton Jhones Granemann FURTADO

2018-06-01

Full Text Available Abstract The potential of near-infrared spectroscopy (NIRS to predict the physicochemical characteristics of the porcine longissimus dorsi (LD muscle was evaluated in comparison to the standard methods of pH and color for meat quality analysis compared to the pH results with Colorimeter and pH meter. Spectral information from each sample (n = 77 was obtained as the average of 32 successive scans acquired over a spectral range from 400 - 2498 nm with a 2 - nm gap for calibration and validation models. Partial least squares (PLS regression was used for each individual model. An R2 and a residual predictive deviation (RPD of 0.67/1.7, 0.86/2, and 0.76/1.9 were estimated for color parameters L*, a *, and b*, respectively. Final pH had an R2 of 0.67 and a RPD of 1.6. NIRS showed great potential to predict color parameter a * of porcine LD muscle. Further studies with larger samples should help improve model quality.

MONITORING ON PLANT LEAF WATER POTENTIAL USING NIR SPECTROSCOPY FOR WATER STRESS MANAGEMENT

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Diding Suhandy

2012-12-01

Full Text Available The performance of the calibration model with temperature compensation for on-plant leaf water potential (LWP determination in tomato plants was evaluated. During a cycle of water stress, the on-plant LWP measurement was conducted. The result showed that the LWP values under water stress and recovery from water stress could be monitored well. It showed that a real time monitoring of the LWP values using NIR spectroscopy could be possible.   Keywords: water stress, real time monitoring of leaf water potential, NIR spectroscopy, plant response-based

Determination of soil content in chlordecone (organochlorine pesticide) using near infrared reflectance spectroscopy (NIRS)

International Nuclear Information System (INIS)

Brunet, Didier; Woignier, Thierry; Lesueur-Jannoyer, Magalie; Achard, Raphael; Rangon, Luc; Barthes, Bernard G.

2009-01-01

Chlordecone is a toxic organochlorine insecticide that was used in banana plantations until 1993 in the French West Indies. This study aimed at assessing the potential of near infrared reflectance spectroscopy (NIRS) for determining chlordecone content in Andosols, Nitisols and Ferralsols from Martinique. Using partial least square regression, chlordecone content conventionally determined through gas chromatography-mass spectrometry could be correctly predicted by NIRS (Q 2 = 0.75, R 2 = 0.82 for the total set), especially for samples with chlordecone content -1 or when the sample set was rather homogeneous (Q 2 = 0.91, R 2 = 0.82 for the Andosols). Conventional measures and NIRS predictions were poorly correlated for chlordecone content >12 mg kg -1 , nevertheless ca. 80% samples were correctly predicted when the set was divided into three or four classes of chlordecone content. Thus NIRS could be considered a time- and cost-effective method for characterising soil contamination by chlordecone. - Soil content in chlordecone, an organochlorine insecticide, can be determined time- and cost-effectively using near infrared reflectance spectroscopy (NIRS).

Determination of soil content in chlordecone (organochlorine pesticide) using near infrared reflectance spectroscopy (NIRS)

Energy Technology Data Exchange (ETDEWEB)

Brunet, Didier, E-mail: didier.brunet@ird.f [IRD - Institut de Recherche pour le Developpement, UMR Eco and Sols (Ecologie Fonctionnelle et Biogeochimie des Sols), Montpellier SupAgro, Batiment 12, 2 place Viala, 34060 Montpellier Cedex 1 (France); Woignier, Thierry [IRD, UMR Eco and Sols, PRAM (Pole de Recherche Agronomique de la Martinique), BP 213, Petit Morne, 97232 Le Lamentin, Martinique (French West Indies) (France); CNRS - Centre National de la Recherche Scientifique, Universite Montpellier 2, place Eugene Bataillon, 34095 Montpellier Cedex 5 (France); Lesueur-Jannoyer, Magalie; Achard, Raphael [CIRAD (Centre de Cooperation Internationale en Recherche Agronomique pour le Developpement), PRAM, BP 213, Petit Morne, 97232 Le Lamentin, Martinique (French West Indies) (France); Rangon, Luc [IRD, UMR Eco and Sols, PRAM (Pole de Recherche Agronomique de la Martinique), BP 213, Petit Morne, 97232 Le Lamentin, Martinique (French West Indies) (France); Barthes, Bernard G. [IRD - Institut de Recherche pour le Developpement, UMR Eco and Sols (Ecologie Fonctionnelle et Biogeochimie des Sols), Montpellier SupAgro, Batiment 12, 2 place Viala, 34060 Montpellier Cedex 1 (France)

2009-11-15

Chlordecone is a toxic organochlorine insecticide that was used in banana plantations until 1993 in the French West Indies. This study aimed at assessing the potential of near infrared reflectance spectroscopy (NIRS) for determining chlordecone content in Andosols, Nitisols and Ferralsols from Martinique. Using partial least square regression, chlordecone content conventionally determined through gas chromatography-mass spectrometry could be correctly predicted by NIRS (Q{sup 2} = 0.75, R{sup 2} = 0.82 for the total set), especially for samples with chlordecone content <12 mg kg{sup -1} or when the sample set was rather homogeneous (Q{sup 2} = 0.91, R{sup 2} = 0.82 for the Andosols). Conventional measures and NIRS predictions were poorly correlated for chlordecone content >12 mg kg{sup -1}, nevertheless ca. 80% samples were correctly predicted when the set was divided into three or four classes of chlordecone content. Thus NIRS could be considered a time- and cost-effective method for characterising soil contamination by chlordecone. - Soil content in chlordecone, an organochlorine insecticide, can be determined time- and cost-effectively using near infrared reflectance spectroscopy (NIRS).

Supplementing predictive mapping of acid sulfate soil occurrence with Vis-NIR spectroscopy

DEFF Research Database (Denmark)

Beucher, Amélie; Peng, Yi; Knadel, Maria

, including geology, landscape type and terrain parameters. Visible-Near-Infrared (Vis-NIR) spectroscopy constitutes a rapid and cheap alternative to soil analysis, and was successfully utilized for the prediction of soil chemical, physical and biological properties. In particular, the Vis-NIR spectra contain......Releasing acidity and metals into watercourses, acid sulfate soils represent a critical environmental problem worldwide. Identifying the spatial distribution of these soils enables to target the strategic areas for risk management. In Denmark, the occurrence of acid sulfate soils was first studied...... during the 1980’s through conventional mapping (i.e. soil sampling and the subsequent determination of pH at the time of sampling and after incubation, the pyrite content and the acid-neutralizing capacity). Since acid sulfate soils mostly occur in wetlands, the survey specifically targeted these areas...

Design of experiments-based monitoring of critical quality attributes for the spray-drying process of insulin by NIR spectroscopy

DEFF Research Database (Denmark)

Maltesen, Morten Jonas; van de Weert, Marco; Grohganz, Holger

2012-01-01

Moisture content and aerodynamic particle size are critical quality attributes for spray-dried protein formulations. In this study, spray-dried insulin powders intended for pulmonary delivery were produced applying design of experiments methodology. Near infrared spectroscopy (NIR) in combination...... on the chemical information of the water molecules in the NIR spectrum. Models yielded prediction errors (RMSEP) between 0.39% and 0.48% with thermal gravimetric analysis used as reference method. The PLS models predicting the aerodynamic particle size were based on baseline offset in the NIR spectra and yielded...... less robust models with a Q (2) of 0.69. Based on the results in this study, NIR is a suitable tool for process analysis of the spray-drying process and for control of moisture content and particle size, in particular for smooth and spherical particles....

[Near infrared reflectance spectroscopy (NIRS): a novel approach to reconstructing historical changes of primary productivity in Antarctic lake].

Science.gov (United States)

Chen, Qian-Qian; Liu, Xiao-Dong; Liu, Wen-Qi; Jiang, Shan

2011-10-01

Compared with traditional chemical analysis methods, reflectance spectroscopy has the advantages of speed, minimal or no sample preparation, non-destruction, and low cost. In order to explore the potential application of spectroscopy technology in the paleolimnological study on Antarctic lakes, we took a lake sediment core in Mochou Lake at Zhongshan Station of Antarctic, and analyzed the near infrared reflectance spectroscopy (NIRS) data in the sedimentary samples. The results showed that the factor loadings of principal component analysis (PCA) displayed very similar depth-profile change pattern with the S2 index, a reliable proxy for the change in historical lake primary productivity. The correlation analysis showed that the values of PCA factor loading and S2 were correlated significantly, suggesting that it is feasible to infer paleoproductivity changes recorded in Antarctic lakes using NIRS technology. Compared to the traditional method of the trough area between 650 and 700 nm, the authors found that the PCA statistical approach was more accurate for reconstructing the change in historical lake primary productivity. The results reported here demonstrate that reflectance spectroscopy can provide a rapid method for the reconstruction of lake palaeoenviro nmental change in the remote Antarctic regions.

[Induction and analysis for NIR features of frequently-used mineral traditional Chinese medicines].

Science.gov (United States)

Chen, Long; Yuan, Ming-Yang; Chen, Ke-Li

2016-10-01

In order to provide theoretical basis for the rapid identification of mineral traditional Chinese medicines(TCM) with near infrared (NIR)diffuse reflectance spectroscopy, Characteristic NIR spectra of 51 kinds of mineral TCMs were generalized and compared on the basis of the previous research, and the characteristic spectral bands were determined and analyzed by referring to mineralogical and geological literatures. It turned out that the NIR features of mineral TCMs were mainly at 8 000-4 000 cm ⁻¹ wavebands, which can be assigned as the absorption of water, -OH and[CO3 ²⁻] and so on. Absorption peaks of water has regularity as follows, the structure water and -OH had a combined peak which was strong and keen-edged around 7 000 cm ⁻¹, the crystal water had two strong peak around 7 000 cm ⁻¹ and 5 100 cm ⁻¹, and water only has a broad peak around 5 100 cm ⁻¹. Due to the differences in the crystal form and the contents of water in mineral TCMs, NIR features of water in mineral TCMs which could be used for identification were different. Mineral TCMs containing sulfate are rich in crystal water, mineral TCMs containing silicate generally had structure water, and mineral TCMs containing carbonate merely had a little of water, so it was reasonable for the use of NIR spectroscopy to classify mineral TCMs with anionic type. In addition, because of the differences in cationic type, impurities, crystal form and crystallinity, mineral TCMs have exclusive NIR features at 4 600-4 000 cm ⁻¹, which can be assigned as Al-OH, Mg-OH, Fe-OH, Si-OH,[CO3 ²⁻] and so on. Calcined mineral TCMs are often associated with water and main composition changes, also changes of the NIR features, which could be used for the monitoring of the processing, and to provide references for the quality control of mineral TCMs. The adaptability and limitation of NIR analysis for mineral TCMs were also discussed:the majority of mineral TCMs had noteworthy NIR features which could be

The Effect of Motion Artifacts on Near-Infrared Spectroscopy (NIRS Data and Proposal of a Video-NIRS System

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Masayuki Satoh

2017-11-01

Full Text Available Aims: The aims of this study were (1 to investigate the influence of physical movement on near-infrared spectroscopy (NIRS data, (2 to establish a video-NIRS system which simultaneously records NIRS data and the subject’s movement, and (3 to measure the oxygenated hemoglobin (oxy-Hb concentration change (Δoxy-Hb during a word fluency (WF task. Experiment 1: In 5 healthy volunteers, we measured the oxy-Hb and deoxygenated hemoglobin (deoxy-Hb concentrations during 11 kinds of facial, head, and extremity movements. The probes were set in the bilateral frontal regions. The deoxy-Hb concentration was increased in 85% of the measurements. Experiment 2: Using a pillow on the backrest of the chair, we established the video-NIRS system with data acquisition and video capture software. One hundred and seventy-six elderly people performed the WF task. The deoxy-Hb concentration was decreased in 167 subjects (95%. Experiment 3: Using the video-NIRS system, we measured the Δoxy-Hb, and compared it with the results of the WF task. Δoxy-Hb was significantly correlated with the number of words. Conclusion: Like the blood oxygen level-dependent imaging effect in functional MRI, the deoxy-Hb concentration will decrease if the data correctly reflect the change in neural activity. The video-NIRS system might be useful to collect NIRS data by recording the waveforms and the subject’s appearance simultaneously.

Classification and Processing Optimization of Barley Milk Production Using NIR Spectroscopy, Particle Size, and Total Dissolved Solids Analysis

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Jasenka Gajdoš Kljusurić

2015-01-01

Full Text Available Barley is a grain whose consumption has a significant nutritional benefit for human health as a very good source of dietary fibre, minerals, vitamins, and phenolic and phytic acids. Nowadays, it is more and more often used in the production of plant milk, which is used to replace cow milk in the diet by an increasing number of consumers. The aim of the study was to classify barley milk and determine the optimal processing conditions in barley milk production based on NIR spectra, particle size, and total dissolved solids analysis. Standard recipe for barley milk was used without added additives. Barley grain was ground and mixed in a blender for 15, 30, 45, and 60 seconds. The samples were filtered and particle size of the grains was determined by laser diffraction particle sizing. The plant milk was also analysed using near infrared spectroscopy (NIRS, in the range from 904 to 1699 nm. Furthermore, conductivity of each sample was determined and microphotographs were taken in order to identify the structure of fat globules and particles in the barley milk. NIR spectra, particle size distribution, and conductivity results all point to 45 seconds as the optimal blending time, since further blending results in the saturation of the samples.

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.

Quantitative Analysis of Adulterations in Oat Flour by FT-NIR Spectroscopy, Incomplete Unbalanced Randomized Block Design, and Partial Least Squares

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Ning Wang

2014-01-01

Full Text Available This paper developed a rapid and nondestructive method for quantitative analysis of a cheaper adulterant (wheat flour in oat flour by NIR spectroscopy and chemometrics. Reflectance FT-NIR spectra in the range of 4000 to 12000 cm−1 of 300 oat flour objects adulterated with wheat flour were measured. The doping levels of wheat flour ranged from 5% to 50% (w/w. To ensure the generalization performance of the method, both the oat and the wheat flour samples were collected from different producing areas and an incomplete unbalanced randomized block (IURB design was performed to include the significant variations that may be encountered in future samples. Partial least squares regression (PLSR was used to develop calibration models for predicting the levels of wheat flour. Different preprocessing methods including smoothing, taking second-order derivative (D2, and standard normal variate (SNV transformation were investigated to improve the model accuracy of PLS. The root mean squared error of Monte Carlo cross-validation (RMSEMCCV and root mean squared error of prediction (RMSEP were 1.921 and 1.975 (%, w/w by D2-PLS, respectively. The results indicate that NIR and chemometrics can provide a rapid method for quantitative analysis of wheat flour in oat flour.

Two-dimensional correlation spectroscopy reveals the underlying compositions for FT-NIR identification of the medicinal bulbs of the genus Fritillaria

Science.gov (United States)

Chen, Jianbo; Wang, Yue; Liu, Aoxue; Rong, Lixin; Wang, Jingjuan

2018-03-01

Fritillariae Bulbus, the dried bulbs of several species of the genus Fritillaria, is often used in traditional Chinese medicine for the treatment of cough and pulmonary diseases. However, the similar appearances make it difficult to identify different kinds of Fritillariae Bulbus. In this research, Fourier transform near-infrared (FT-NIR) spectroscopy with a reflection fiber probe is employed for the direct testing and automatic identification of different kinds of Fritillariae Bulbus to ensure the authenticity, efficacy and safety. The bulbs can be measured directly without pulverizing. According to the two-dimensional (2D) correlation analysis and statistical analysis, the height ratio of the two peaks near 4860 cm-1 and 4750 cm-1 in the second derivative spectra is specific to the species of Fritillariae Bulbus. This indicates that the relative amount of protein and carbohydrate may be critical to identify Fritillariae Bulbus. With the help of the SIMCA model, the four kinds of Fritillariae Bulbus can be identified correctly by FT-NIR spectroscopy. The results show the potential of FT-NIR spectroscopy with a reflection fiber probe in the rapid testing and identification of Fritillariae Bulbus.

Portable NIR-AOTF spectroscopy combined with winery FTIR spectroscopy for an easy, rapid, in-field monitoring of Sangiovese grape quality.

Science.gov (United States)

Barnaba, Federico Emanuele; Bellincontro, Andrea; Mencarelli, Fabio

2014-04-01

A near infrared acousto-optically tunable filter (NIR-AOTF) spectrophotometer was tested for three seasons on four different vineyards with the aim of monitoring the ripening evolution of the Italian red wine grape variety Sangiovese. Predictive models for the estimation of several enological parameters were carried out applying the partial least squares chemometric approach. Reference analysis was conducted using Fourier transform infrared spectroscopy (FTIR). Spectral detections were obtained working on whole grape berries. A global set of 96 samples (n = 76 in 2009, and n = 20 in 2010) each one represented by 100 intact grape berries was tested. Finally, in 2011, an external validation on an independent data set of 25 samples (50 grape berries per set) was carried out. Coupling the two spectroscopic applications, the following enological parameters were tested: °Brix, °Babo, total sugars (g L(-1)), glucose (g L(-1)), fructose (g L(-1)), density (g mL(-1)), titratable acidity (g L(-1)), tartaric acid (g L(-1)), pH, malic acid (g L(-1)), gluconic acid (g L(-1)), assumable nitrogen (mg L(-1) ), anthocyanins (mg L(-1)), and total phenols (mg L(-1)). NIR-AOTF spectroscopy was able to predict with a high correlation versus the measured data: °Brix, °Babo, total sugars, glucose, fructose and density. The coefficient of determination (R(2)) and the standard error in prediction were: 0.93 and 0.73 for °Brix; 0.93 and 0.62 for °Babo; 0.94 and 7.39 g L(-1) for total sugars; 0.93 and 5.39 g L(-1) for glucose; 0.92 and 5.07 g L(-1) for fructose; and 0.91 and 0.004 g mL(-1) for density, respectively. Significant correlations were found in prediction for tartaric acid and pH value. Promising validation results were recorded for anthocyanins and total phenols, even though predictive models were affected by the method of sample preparation in compound extraction. This study shows how NIR-AOTF spectroscopy can be used in viticulture to

Near-infrared spectroscopy (NIRS) as a new tool for neuroeconomic research

Science.gov (United States)

Kopton, Isabella M.; Kenning, Peter

2014-01-01

Over the last decade, the application of neuroscience to economic research has gained in importance and the number of neuroeconomic studies has grown extensively. The most common method for these investigations is fMRI. However, fMRI has limitations (particularly concerning situational factors) that should be countered with other methods. This review elaborates on the use of functional Near-Infrared Spectroscopy (fNIRS) as a new and promising tool for investigating economic decision making both in field experiments and outside the laboratory. We describe results of studies investigating the reliability of prototype NIRS studies, as well as detailing experiments using conventional and stationary fNIRS devices to analyze this potential. This review article shows that further research using mobile fNIRS for studies on economic decision making outside the laboratory could be a fruitful avenue helping to develop the potential of a new method for field experiments outside the laboratory. PMID:25147517

Evaluation of Pleasure-Displeasure Induced by Use of Lipsticks with Near-Infrared Spectroscopy (NIRS): Usefulness of 2-Channel NIRS in Neuromarketing.

Science.gov (United States)

Tanida, M; Okabe, M; Tagai, K; Sakatani, K

2017-01-01

In order to examine whether near-infrared spectroscopy (NIRS) would be a useful neuromarketing tool, we employed NIRS to evaluate the difference of pleasure-displeasure in women, induced by the use of different types of lipsticks. The subjects used lipsticks A and B; A is softer than B. Concentration changes of oxy-Hb were measured in the bilateral prefrontal cortex (PFC) during use of lipsticks A and B. We evaluated the right and left dominancy of PFC activity by calculating the Laterality Index (LI) (LI = leftΔoxy-Hb - rightΔoxy-Hb); positive LI indicates left-dominant activity while negative LI indicate right-dominant activity. We found a significant interaction between the use of lipsticks A and B, using a two-way factorial analysis of variance [F(1,13) = 9.63, p neuromarketing tool, since it allows objective assessment of pleasure-unpleasure.

Suitability of faecal near-infrared reflectance spectroscopy (NIRS) predictions for estimating gross calorific value

Energy Technology Data Exchange (ETDEWEB)

De la Roza-Delgado, B.; Modroño, S.; Vicente, F.; Martínez-Fernández, A.; Soldado, A.

2015-07-01

A total of 220 faecal pig and poultry samples, collected from different experimental trials were employed with the aim to demonstrate the suitability of Near Infrared Reflectance Spectroscopy (NIRS) technology for estimation of gross calorific value on faeces as output products in energy balances studies. NIR spectra from dried and grounded faeces samples were analyzed using a Foss NIRSystem 6500 instrument, scanning over the wavelength range 400-2500 nm. Validation studies for quantitative analytical models were carried out to estimate the relevance of method performance associated to reference values to obtain an appropriate, accuracy and precision. The results for prediction of gross calorific value (GCV) of NIRS calibrations obtained for individual species showed high correlation coefficients comparing chemical analysis and NIRS predictions, ranged from 0.92 to 0.97 for poultry and pig. For external validation, the ratio between the standard error of cross validation (SECV) and the standard error of prediction (SEP) varied between 0.73 and 0.86 for poultry and pig respectively, indicating a sufficiently precision of calibrations. In addition a global model to estimate GCV in both species was developed and externally validated. It showed correlation coefficients of 0.99 for calibration, 0.98 for cross-validation and 0.97 for external validation. Finally, relative uncertainty was calculated for NIRS developed prediction models with the final value when applying individual NIRS species model of 1.3% and 1.5% for NIRS global prediction. This study suggests that NIRS is a suitable and accurate method for the determination of GCV in faeces, decreasing cost, timeless and for convenient handling of unpleasant samples.. (Author)

Acrylamide inverse miniemulsion polymerization: in situ, real-time monitoring using nir spectroscopy

Directory of Open Access Journals (Sweden)

M. M. E. Colmán

2014-12-01

Full Text Available In this work, the ability of on-line NIR spectroscopy for the prediction of the evolution of monomer concentration, conversion and average particle diameter in acrylamide inverse miniemulsion polymerization was evaluated. The spectral ranges were chosen as those representing the decrease in concentration of monomer. An increase in the baseline shift indicated that the NIR spectra were affected by particle size. Multivariate partial least squares calibration models were developed to relate NIR spectra collected by the immersion probe with off-line conversion and polymer particle size data. The results showed good agreement between off-line data and values predicted by the NIR calibration models and these latter were also able to detect different types of operational disturbances. These results indicate that it is possible to monitor variables of interest during acrylamide inverse miniemulsion polymerizations.

Combined optimal-pathlengths method for near-infrared spectroscopy analysis

International Nuclear Information System (INIS)

Liu Rong; Xu Kexin; Lu Yanhui; Sun Huili

2004-01-01

Near-infrared (NIR) spectroscopy is a rapid, reagent-less and nondestructive analytical technique, which is being increasingly employed for quantitative application in chemistry, pharmaceutics and food industry, and for the optical analysis of biological tissue. The performance of NIR technology greatly depends on the abilities to control and acquire data from the instrument and to calibrate and analyse data. Optical pathlength is a key parameter of the NIR instrument, which has been thoroughly discussed in univariate quantitative analysis in the presence of photometric errors. Although multiple wavelengths can provide more chemical information, it is difficult to determine a single pathlength that is suitable for each wavelength region. A theoretical investigation of a selection procedure for multiple pathlengths, called the combined optimal-pathlengths (COP) method, is identified in this paper and an extensive comparison with the single pathlength method is also performed on simulated and experimental NIR spectral data sets. The results obtained show that the COP method can greatly improve the prediction accuracy in NIR spectroscopy quantitative analysis

Near-infrared spectroscopy (NIRS) in a piglet model

DEFF Research Database (Denmark)

Clausen, Nicola Groes; Spielmann, Nelly; Ringer, Simone K.

2017-01-01

Near-infrared spectroscopy (NIRS) in a piglet model: readings are influenced by the colour of the cover Clausen NG1,2, Spielmann N1,3, Weiss M1,3, Ringer SK4 1Children’s Research Center, University Children’s Hospital of Zurich, Switzerland; 2Department of Anaesthesiology and Intensive Care, Odense....... The rSO2 was measured by placing NIRS sensors in the supra glabellar region. In 12 animals sensors were covered with a uni-coloured pink (P) napkin and a turquoise (T) napkin in a random order (Setting A). In further 13 animals sensors were covered with blue-coloured surgical drape (SD) and a napkin...... with a reddish SantaClaus (SC) motive (Setting B). Uncovered (UC) baseline values were captured and measurements obtained for a period of three minutes. During measurements, the animals were kept in normoterm, normotensive, normoglycaemic and normoxic condition. Inspired oxygen fraction and ventilatory settings...

[Determination of wine original regions using information fusion of NIR and MIR spectroscopy].

Science.gov (United States)

Xiang, Ling-Li; Li, Meng-Hua; Li, Jing-Mingz; Li, Jun-Hui; Zhang, Lu-Da; Zhao, Long-Lian

2014-10-01

Geographical origins of wine grapes are significant factors affecting wine quality and wine prices. Tasters' evaluation is a good method but has some limitations. It is important to discriminate different wine original regions quickly and accurately. The present paper proposed a method to determine wine original regions based on Bayesian information fusion that fused near-infrared (NIR) transmission spectra information and mid-infrared (MIR) ATR spectra information of wines. This method improved the determination results by expanding the sources of analysis information. NIR spectra and MIR spectra of 153 wine samples from four different regions of grape growing were collected by near-infrared and mid-infrared Fourier transform spe trometer separately. These four different regions are Huailai, Yantai, Gansu and Changli, which areall typical geographical originals for Chinese wines. NIR and MIR discriminant models for wine regions were established using partial least squares discriminant analysis (PLS-DA) based on NIR spectra and MIR spectra separately. In PLS-DA, the regions of wine samples are presented in group of binary code. There are four wine regions in this paper, thereby using four nodes standing for categorical variables. The output nodes values for each sample in NIR and MIR models were normalized first. These values stand for the probabilities of each sample belonging to each category. They seemed as the input to the Bayesian discriminant formula as a priori probability value. The probabilities were substituteed into the Bayesian formula to get posterior probabilities, by which we can judge the new class characteristics of these samples. Considering the stability of PLS-DA models, all the wine samples were divided into calibration sets and validation sets randomly for ten times. The results of NIR and MIR discriminant models of four wine regions were as follows: the average accuracy rates of calibration sets were 78.21% (NIR) and 82.57% (MIR), and the

Prediction of ethanol in bottled Chinese rice wine by NIR spectroscopy

Science.gov (United States)

Ying, Yibin; Yu, Haiyan; Pan, Xingxiang; Lin, Tao

2006-10-01

To evaluate the applicability of non-invasive visible and near infrared (VIS-NIR) spectroscopy for determining ethanol concentration of Chinese rice wine in square brown glass bottle, transmission spectra of 100 bottled Chinese rice wine samples were collected in the spectral range of 350-1200 nm. Statistical equations were established between the reference data and VIS-NIR spectra by partial least squares (PLS) regression method. Performance of three kinds of mathematical treatment of spectra (original spectra, first derivative spectra and second derivative spectra) were also discussed. The PLS models of original spectra turned out better results, with higher correlation coefficient in calibration (R cal) of 0.89, lower root mean standard error of calibration (RMSEC) of 0.165, and lower root mean standard error of cross validation (RMSECV) of 0.179. Using original spectra, PLS models for ethanol concentration prediction were developed. The R cal and the correlation coefficient in validation (R val) were 0.928 and 0.875, respectively; and the RMSEC and the root mean standard error of validation (RMSEP) were 0.135 (%, v v -1) and 0.177 (%, v v -1), respectively. The results demonstrated that VIS-NIR spectroscopy could be used to predict ethanol concentration in bottled Chinese rice wine.

[A review on studies and applications of near infrared spectroscopy technique(NIRS) in detecting quality of hay].

Science.gov (United States)

Ding, Wu-Rong; Gan, You-Min; Guo, Xu-Sheng; Yang, Fu-Yu

2009-02-01

The quality of hay can directly affect the price of hay and also livestock productivity. Many kinds of methods have been developed for detecting the quality of hay and the method of near infrared spectroscopy (NIRS) has been widely used with consideration of its fast, effective and nondestructive characteristics during detecting process. In the present paper, the feasibility and effectiveness of application of NIRS to detecting hay quality were expounded. Meanwhile, the advance in the study of using NIRS to detect chemical compositions, extent of incursion by epiphyte, amount of toxicant excreted by endogenetic epiphyte and some minim components that can not be detected by using chemical methods were also introduced detailedly. Based on the review of the progresses in using NIRS to detect the quality of hay, it can be concluded that using NIRS to detect hay quality can avoid the disadvantages of time wasting, complication and high cost when using traditional chemical method. And for better utilization of NIRS in practice, some more studies still need to be implemented to further perfect and improve the utilization of NIRS for detecting forage quality, and more accurate modes and systematic analysis software need to be established in times to come.

Near infrared spectroscopy (NIRS) to monitor tissue haemoglobin (and myoglobin) oxygenation

NARCIS (Netherlands)

Scheeren, T. W. L.

2010-01-01

Introduction: Tissue oxygenation may be monitored noninvasively by near infrared spectroscopy (NIRS) both on the thenar eminescence (muscle) and on the forehead (brain). Thenar measurement have been used to guide therapy in trauma patients ( 1 ) and to determine the prognosis of septic patients ( 2

Monitoring tissue oxygen availability with near infrared spectroscopy (NIRS) in health and disease

DEFF Research Database (Denmark)

Boushel, Robert Christopher; Langberg, H; Olesen, J

2001-01-01

, brain and connective tissue, and more recently it has been used in the clinical setting to assess circulatory and metabolic abnormalities. Quantitative measures of blood flow are also possible using NIRS and a light-absorbing tracer, which can be applied to evaluate circulatory responses to exercise......Near infrared spectroscopy (NIRS) is becoming a widely used research instrument to measure tissue oxygen (O2) status non-invasively. Continuous-wave spectrometers are the most commonly used devices, which provide semi-quantitative changes in oxygenated and deoxygenated hemoglobin in small blood...... vessels (arterioles, capillaries and venules). Refinement of NIRS hardware and the algorithms used to deconvolute the light absorption signal have improved the resolution and validity of cytochrome oxidase measurements. NIRS has been applied to measure oxygenation in a variety of tissues including muscle...

Crop/weed discrimination using near-infrared reflectance spectroscopy (NIRS)

Science.gov (United States)

Zhang, Yun; He, Yong

2006-09-01

The traditional uniform herbicide application often results in an over chemical residues on soil, crop plants and agriculture produce, which have imperiled the environment and food security. Near-infrared reflectance spectroscopy (NIRS) offers a promising means for weed detection and site-specific herbicide application. In laboratory, a total of 90 samples (30 for each species) of the detached leaves of two weeds, i.e., threeseeded mercury (Acalypha australis L.) and fourleafed duckweed (Marsilea quadrfolia L.), and one crop soybean (Glycine max) was investigated for NIRS on 325- 1075 nm using a field spectroradiometer. 20 absorbance samples of each species after pretreatment were exported and the lacked Y variables were assigned independent values for partial least squares (PLS) analysis. During the combined principle component analysis (PCA) on 400-1000 nm, the PC1 and PC2 could together explain over 91% of the total variance and detect the three plant species with 98.3% accuracy. The full-cross validation results of PLS, i.e., standard error of prediction (SEP) 0.247, correlation coefficient (r) 0.954 and root mean square error of prediction (RMSEP) 0.245, indicated an optimum model for weed identification. By predicting the remaining 10 samples of each species in the PLS model, the results with deviation presented a 100% crop/weed detection rate. Thus, it could be concluded that PLS was an available alternative of for qualitative weed discrimination on NTRS.

NIR analysis of cellulose and lactose--application to ecstasy tablet analysis.

Science.gov (United States)

Baer, Ines; Gurny, Robert; Margot, Pierre

2007-04-11

Cellulose and lactose are the most frequently used excipients in illicit ecstasy production. The aim of this project was to use near infrared reflectance spectroscopy (NIRS) for the determination of the different chemical forms of these two substances, as well as for the differentiation of their origin (producer). It was possible to distinguish between the different chemical forms of both compounds, as well as between their origins (producers), although within limits. Furthermore, the possibilities to apply NIR for the analysis of substances such as found in illicit tablets were studied. First, a few cellulose and lactose samples were chosen to make mixtures with amphetamine at three degrees of purity (5, 10 and 15%), in order to study the resulting changes in the spectra as well as to simultaneously quantify amphetamine and identify the excipient. A PLS2 model could be build to predict concentrations and excipient. Secondarily, the technique was to be applied to real ecstasy tablets. About 40 ecstasy seizures were analysed with the aim to determine the excipient and to check them against each other. Identification of the excipients was not always obvious, especially when more than one excipient were present. However, a comparison between tablets appeared to give groups of similar samples. NIR analysis results in spectra representing the tablet blend as a whole taking into account all absorbing compounds. Although NIRS seems to be an appropriate method for ecstasy profiling, little is known about intra- and intervariability of compression batches.

[Advances of NIR spectroscopy technology applied in seed quality detection].

Science.gov (United States)

Zhu, Li-wei; Ma, Wen-guang; Hu, Jin; Zheng, Yun-ye; Tian, Yi-xin; Guan, Ya-jing; Hu, Wei-min

2015-02-01

Near infrared spectroscopy (NIRS) technology developed fast in recent years, due to its rapid speed, less pollution, high-efficiency and other advantages. It has been widely used in many fields such as food, chemical industry, pharmacy, agriculture and so on. The seed is the most basic and important agricultural capital goods, and seed quality is important for agricultural production. Most methods presently used for seed quality detecting were destructive, slow and needed pretreatment, therefore, developing one kind of method that is simple and rapid has great significance for seed quality testing. This article reviewed the application and trends of NIRS technology in testing of seed constituents, vigor, disease and insect pests etc. For moisture, starch, protein, fatty acid and carotene content, the model identification rates were high as their relative contents were high; for trace organic, the identification rates were low as their relative content were low. The heat-damaged seeds with low vigor were discriminated by NIRS, the seeds stored for different time could also been identified. The discrimination of frost-damaged seeds was impossible. The NIRS could be used to identify health and infected disease seeds, and did the classification for the health degree; it could identify parts of the fungal pathogens. The NIRS could identify worm-eaten and health seeds, and further distinguished the insect species, however the identification effects for small larval and low injury level of insect pests was not good enough. Finally, in present paper existing problems and development trends for NIRS in seed quality detection was discussed, especially the single seed detecting technology which was characteristic of the seed industry, the standardization of its spectral acquisition accessories will greatly improve its applicability.

Rapid analysis of hay attributes using NIRS. Final report, Task II alfalfa supply system

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-10-24

This final report provides technical information on the development of a near infrared reflectance spectroscopy (NIRS) system for the analysis of alfalfa hay. The purpose of the system is to provide consistent quality for processing alfalfa stems for fuel and alfalfa leaf meal products for livestock feed. Project tasks were to: (1) develop an NIRS driven analytical system for analysis of alfalfa hay and processed alfalfa products; (2) assist in hiring a qualified NIRS technician and recommend changes in testing equipment necessary to provide accurate analysis; (3) calibrate the NIRS instrument for accurate analyses; and (4) develop prototype equipment and sampling procedures as a first step towards development of a totally automated sampling system that would rapidly sample and record incoming feedstock and outbound product. An accurate hay testing program was developed, along with calibration equations for analyzing alfalfa hay and sun-cured alfalfa pellets. A preliminary leaf steam calibration protocol was also developed. 7 refs., 11 figs., 10 tabs.

The use of near infrared spectroscopy (NIRS) to predict the chemical ...

African Journals Online (AJOL)

resias

Keywords: NIRS, ostrich TMR, chemical composition, nutritive value ... For adequate feeding of livestock, farmers need information about the nutritive value of available .... presented a SD/SECV ratio value of less than three, which is regarded as fair, .... The current and future role of near infrared reflectance spectroscopy in.

Cost Effective Process Monitoring using UV-VIS-NIR Spectroscopy

International Nuclear Information System (INIS)

Cipiti, B.; McDaniel, M.; Bryan, S.; Pratt, S.

2015-01-01

UV-VIS-NIR Spectroscopy is a simple and inexpensive measurement technology which has been proposed for process monitoring applications at reprocessing plants. The purpose of this work was to examine if spectroscopy could replace more costly analytical measurements to reduce the safeguards burden to the operator or inspector. Recognizing that the higher measurement uncertainty of spectroscopy makes it unsuited for the accountability tanks, the approach instead was to focus on replacing mass spectrometry for random samples that are taken in a plant. The Interim Inventory Verification and Short Inventory Verification (IIV/SIV) at the Rokkasho Reprocessing Plant utilize random sampling of internal process vessels and laboratory measurement using Isotope Dilution Mass Spectrometry (IDMS) to account for plutonium on a timely basis. These measurements are time-consuming, and the low uncertainty may not always be required. For this work, modelling was used to examine if spectroscopy could be used without adversely affecting the safeguards of the plant. The Separation and Safeguards Performance Model (SSPM), developed at Sandia National Laboratories, was utilized to examine the replacement of IDMS measurements with spectroscopy. Modeling results showed that complete replacement of IDMS with spectroscopy lowered the detection probability for diversion by an unacceptable amount. However, partial replacement (only for samples from vessels with low plutonium content) did not adversely affect the detection probability. This partial replacement covers roughly half of the twenty or so sampling points used for the IIV/SIVA cost-benefit analysis was completed to determine the cost savings that this approach can provide based on lower equipment costs, maintenance, and reduction of analysts' time. This work envisions working with the existing sampling system and performing the spectroscopic measurements in the analytical laboratory, but future work could examine incorporating

Effective Identification of Low-Gliadin Wheat Lines by Near Infrared Spectroscopy (NIRS: Implications for the Development and Analysis of Foodstuffs Suitable for Celiac Patients.

Directory of Open Access Journals (Sweden)

María Dolores García-Molina

Full Text Available The aim of this work was to assess the ability of Near Infrared Spectroscopy (NIRS to distinguish wheat lines with low gliadin content, obtained by RNA interference (RNAi, from non-transgenic wheat lines. The discriminant analysis was performed using both whole grain and flour. The transgenic sample set included 409 samples for whole grain sorting and 414 samples for flour experiments, while the non-transgenic set consisted of 126 and 156 samples for whole grain and flour, respectively.Samples were scanned using a Foss-NIR Systems 6500 System II instrument. Discrimination models were developed using the entire spectral range (400-2500 nm and ranges of 400-780 nm, 800-1098 nm and 1100-2500 nm, followed by analysis of means of partial least square (PLS. Two external validations were made, using samples from the years 2013 and 2014 and a minimum of 99% of the flour samples and 96% of the whole grain samples were classified correctly.The results demonstrate the ability of NIRS to successfully discriminate between wheat samples with low-gliadin content and wild types. These findings are important for the development and analysis of foodstuff for celiac disease (CD patients to achieve better dietary composition and a reduction in disease incidence.

Combined data mining/NIR spectroscopy for purity assessment of lime juice

Science.gov (United States)

Shafiee, Sahameh; Minaei, Saeid

2018-06-01

This paper reports the data mining study on the NIR spectrum of lime juice samples to determine their purity (natural or synthetic). NIR spectra for 72 pure and synthetic lime juice samples were recorded in reflectance mode. Sample outliers were removed using PCA analysis. Different data mining techniques for feature selection (Genetic Algorithm (GA)) and classification (including the radial basis function (RBF) network, Support Vector Machine (SVM), and Random Forest (RF) tree) were employed. Based on the results, SVM proved to be the most accurate classifier as it achieved the highest accuracy (97%) using the raw spectrum information. The classifier accuracy dropped to 93% when selected feature vector by GA search method was applied as classifier input. It can be concluded that some relevant features which produce good performance with the SVM classifier are removed by feature selection. Also, reduced spectra using PCA do not show acceptable performance (total accuracy of 66% by RBFNN), which indicates that dimensional reduction methods such as PCA do not always lead to more accurate results. These findings demonstrate the potential of data mining combination with near-infrared spectroscopy for monitoring lime juice quality in terms of natural or synthetic nature.

Near infrared spectroscopic (NIRS) analysis of grapes and red-wines

International Nuclear Information System (INIS)

Guggenbichler, W.

2003-04-01

In this work vine varieties of the genus Vitis as well as grape-must and fully developed wines were examined by Near Infrared Spectroscopy (NIRS). The spectra were obtained by methods of transflection and transmission measurements. It was shown, that spectra of different varieties of grapes and red-wines can be combined in clusters by means of NIR spectroscopy and subsequent principle components analysis (PCA). In addition to this, it was possible to identify blends of two different varieties of wines as such and to determine the ratio of mixture. In several varieties of grape-must these NIR spectroscopic measurements further allowed a quantitative determination of important parameters concerning the quality of grapes, such as: sugar, total acidity, tartaric acid, malic acid, and pH-value. The content of polyphenols in grapes was also analyzed by this method. The total parameter for polyphenols in grapes is a helpful indicator for the optimal harvest time and the quality of grapes. All quantitative calculations were made by the method of partial least square regression (PLS). As these spectroscopic measurements require minimal sample preparations and due to the fact that measurements can be accomplished and results obtained within a few seconds, this method turned out to be a promising option in order to classify wines and to quantify relevant ingredients in grapes. (author)

Determination of Free Fatty Acid by FT-NIR Spectroscopy in Esterification Reaction for Biodiesel Production

Directory of Open Access Journals (Sweden)

Djéssica Tatiana Raspe

2013-01-01

Full Text Available This work reports the use of FT-NIR spectroscopy coupled with multivariate calibration to determine the percentage of free fatty acids (FFA in samples obtained by the esterification of FFA in vegetable oils. The analytical method used as calibration matrix samples of the reaction medium of esterification of oleic acid in soybean oil in proportions of 0.3 to 40 wt% (by weight of oleic acid obtained under different experimental conditions and utilized the partial least squares (PLS regression. The efficiency of the method was tested to predict the content of FFA in reactions of esterification of oleic acid in soybean oil catalysed by KSF clay and Amberlyst 15 commercial resin, both in a batch mode. Good Correlations were observed between the FT-NIR/PLS method and the reference method (AOCS. The results confirm that FT-NIR spectroscopy, in combination with multivariate calibration, is a promising technique for monitoring esterification reaction for biodiesel production.

Automatic moisture content determination on biomass with NIR and radio frequency spectroscopy; Automatisk fukthaltsmaetning paa biobraenslen med NIR samt radiofrekvent spektroskopi

Energy Technology Data Exchange (ETDEWEB)

Dahlquist, Erik; Nystroem, Jenny; Thorin, Eva; Paz, Ana de la [Maelardalen Univ. (Sweden). Dept. of Public Technology; Axrup, Lars [Stora Enso AB (Sweden)

2005-08-01

The goal with the project has been to evaluate two methods for determination of moisture content in biomass fuels and to determine if these methods can be used in practice in connection with delivery control of biomass at power plants. Tests have been performed with different biomass qualities and with two different measurement methods within a large moisture span, 0.6-72%. The two methods have been NIR (Near Infrared spectroscopy), and RF (Radio Frequency spectroscopy). The NIR-method is a surface analysis method, where hydro-carbons like wood have a different absorption pattern than water. The RF-method is a bulk method and utilizes that wood and water have different dielectric constants. Radio waves thus are affected differently by transportation through wet and dry biomass. In this project we have studied how representative sampling can be achieved from a large volume of delivered biomass fuel. We also have performed calibration with mixtures of the different fuels. Sampling has been performed by extracting biomass in a four meter long screw from the large volume as it is poured into a storage vessel. A conveyor belt is then transporting the material to the measurement systems. Two different NIR-instruments, DA (Diod Array) -NIR respective FT (Fourier Transform)- NIR, were placed above the conveyor belt. The material was collected from the belt into the measuring vessel for the RF, a 200 liter 'oil barrel'. The radio waves were sent from the transceiver into the sample from above without direct contact between the biomass and the transceiver antenna. Six different fuels were studied separately. Calibration was performed where the moisture content was varied by mixing relatively dry fuel with humidified biomass in different proportions a day before the measurements. Samples were taken from each mixture in connection with the measurements, from the conveyor belt. The samples were made in such a way that they represented the whole volume as good as

Feasibility of field portable near infrared (NIR) spectroscopy to determine cyanide concentrations in soil

Science.gov (United States)

Sut, Magdalena; Fischer, Thomas; Repmann, Frank; Raab, Thomas

2013-04-01

In Germany, at more than 1000 sites, soil is polluted with an anthropogenic contaminant in form of iron-cyanide complexes. These contaminations are caused by former Manufactured Gas Plants (MGPs), where electricity for lighting was produced in the process of coal gasification. The production of manufactured gas was restrained in 1950, which caused cessation of MGPs. Our study describes the application of Polychromix Handheld Field Portable Near-Infrared (NIR) Analyzer to predict the cyanide concentrations in soil. In recent times, when the soil remediation is of major importance, there is a need to develop rapid and non-destructive methods for contaminant determination in the field. In situ analysis enables determination of 'hot spots', is cheap and time saving in comparison to laboratory methods. This paper presents a novel usage of NIR spectroscopy, where a calibration model was developed, using multivariate calibration algorithms, in order to determine NIR spectral response to the cyanide concentration in soil samples. As a control, the contaminant concentration was determined using conventional Flow Injection Analysis (FIA). The experiments revealed that portable near-infrared spectrometers could be a reliable device for identification of contamination 'hot spots', where cyanide concentration are higher than 2400 mg kg-1 in the field and >1750 mg kg-1 after sample preparation in the laboratory, but cannot replace traditional laboratory analyses due to high limits of detection.

Pharmaceutical Raw Material Identification Using Miniature Near-Infrared (MicroNIR) Spectroscopy and Supervised Pattern Recognition Using Support Vector Machine.

Science.gov (United States)

Sun, Lan; Hsiung, Chang; Pederson, Christopher G; Zou, Peng; Smith, Valton; von Gunten, Marc; O'Brien, Nada A

2016-05-01

Near-infrared spectroscopy as a rapid and non-destructive analytical technique offers great advantages for pharmaceutical raw material identification (RMID) to fulfill the quality and safety requirements in pharmaceutical industry. In this study, we demonstrated the use of portable miniature near-infrared (MicroNIR) spectrometers for NIR-based pharmaceutical RMID and solved two challenges in this area, model transferability and large-scale classification, with the aid of support vector machine (SVM) modeling. We used a set of 19 pharmaceutical compounds including various active pharmaceutical ingredients (APIs) and excipients and six MicroNIR spectrometers to test model transferability. For the test of large-scale classification, we used another set of 253 pharmaceutical compounds comprised of both chemically and physically different APIs and excipients. We compared SVM with conventional chemometric modeling techniques, including soft independent modeling of class analogy, partial least squares discriminant analysis, linear discriminant analysis, and quadratic discriminant analysis. Support vector machine modeling using a linear kernel, especially when combined with a hierarchical scheme, exhibited excellent performance in both model transferability and large-scale classification. Hence, ultra-compact, portable and robust MicroNIR spectrometers coupled with SVM modeling can make on-site and in situ pharmaceutical RMID for large-volume applications highly achievable. © The Author(s) 2016.

Near-infrared spectroscopy (NIRS evaluation and regional analysis of Chinese faba bean (Vicia faba L.

Directory of Open Access Journals (Sweden)

Jiaojiao Wang

2014-02-01

Full Text Available To analyze the nutritional composition of faba bean (Vicia faba L. seed, estimation models were developed for protein, starch, oil, and total polyphenol using near infrared spectroscopy (NIRS. Two hundred and forty-four samples from twelve producing regions were measured in both milled powder and intact seed forms. Partial least squares (PLS regression was applied for model development. The model based on ground seed powder was generally superior to that based on the intact seed. The optimal seed powder-based models for protein, starch, and total polyphenol had coefficients of correlation (r2 of 0.97, 0.93 and 0.89, respectively. The relationship between nutrient contents and twelve producing areas was determined by two-step cluster analysis. Three distinct groupings were obtained with region-constituent features, i.e., Group 1 of high oil, Group 2 of high protein, and Group 3 of high starch as well as total polyphenol. The clustering accuracy was 79.5%. Moreover, the nutrition contents were affected by seeding date, longitude, latitude, and altitude of plant location. Cluster analysis revealed that the differences in the seed were strongly influenced by geographical factors.

Analysis of Selected Properties of Fibreboard Panels Manufactured from Wood and Leather Using the Near Infrared Spectroscopy

Directory of Open Access Journals (Sweden)

Kerstin Wagner

2015-01-01

Full Text Available This paper deals with the characterization of the properties of wood fibres leather shavings composite board by using the near infrared spectroscopy (NIRS and multivariate data analysis. In this study fibreboards were manufactured with different leather amounts by using spruce fibres, as well as vegetable and mineral tanned leather shavings (wet white and wet blue. The NIR spectroscopy was used to analyse the raw materials as well as the wood leather fibreboards. Moreover, the physical and mechanical features of the wood leather composite fibreboards were determined to characterize their properties for the further data analysis. The NIR spectra were analysed by univariate and multivariate methods using the Principal Component Analysis (PCA and the Partial Least Squares Regression (PLSR method. These results demonstrate the potential of FT-NIR spectroscopy to estimate the physical and mechanical properties (e.g., bending strength. This phenomenon provides a possibility for quality assurance systems by using the NIRS.

Dissolution testing of isoniazid, rifampicin, pyrazinamide and ethambutol tablets using near-infrared spectroscopy (NIRS) and multivariate calibration.

Science.gov (United States)

de Oliveira Neves, Ana Carolina; Soares, Gustavo Mesquita; de Morais, Stéphanie Cavalcante; da Costa, Fernanda Saadna Lopes; Porto, Dayanne Lopes; de Lima, Kássio Michell Gomes

2012-01-05

This work utilized the near-infrared spectroscopy (NIRS) and multivariate calibration to measure the percentage drug dissolution of four active pharmaceutical ingredients (APIs) (isoniazid, rifampicin, pyrazinamide and ethambutol) in finished pharmaceutical products produced in the Federal University of Rio Grande do Norte (Brazil). The conventional analytical method employed in quality control tests of the dissolution by the pharmaceutical industry is high-performance liquid chromatography (HPLC). The NIRS is a reliable method that offers important advantages for the large-scale production of tablets and for non-destructive analysis. NIR spectra of 38 samples (in triplicate) were measured using a Bomen FT-NIR 160 MB in the range 1100-2500nm. Each spectrum was the average of 50 scans obtained in the diffuse reflectance mode. The dissolution test, which was initially carried out in 900mL of 0.1N hydrochloric acid at 37±0.5°C, was used to determine the percentage a drug that dissolved from each tablet measured at the same time interval (45min) at pH 6.8. The measurement of the four API was performed by HPLC (Shimadzu, Japan) in the gradiente mode. The influence of various spectral pretreatments (Savitzky-Golay smoothing, Multiplicative Scatter Correction (MSC), and Savitzky-Golay derivatives) and multivariate analysis using the partial least squares (PLS) regression algorithm was calculated by the Unscrambler 9.8 (Camo) software. The correlation coefficient (R(2)) for the HPLC determination versus predicted values (NIRS) ranged from 0.88 to 0.98. The root-mean-square error of prediction (RMSEP) obtained from PLS models were 9.99%, 8.63%, 8.57% and 9.97% for isoniazid, rifampicin, ethambutol and pyrazinamide, respectively, indicating that the NIR method is an effective and non-destructive tool for measurement of drug dissolution from tablets. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.

Quality evaluation of frozen guava and yellow passion fruit pulps by NIR spectroscopy and chemometrics.

Science.gov (United States)

Alamar, Priscila D; Caramês, Elem T S; Poppi, Ronei J; Pallone, Juliana A L

2016-07-01

The present study investigated the application of near infrared spectroscopy as a green, quick, and efficient alternative to analytical methods currently used to evaluate the quality (moisture, total sugars, acidity, soluble solids, pH and ascorbic acid) of frozen guava and passion fruit pulps. Fifty samples were analyzed by near infrared spectroscopy (NIR) and reference methods. Partial least square regression (PLSR) was used to develop calibration models to relate the NIR spectra and the reference values. Reference methods indicated adulteration by water addition in 58% of guava pulp samples and 44% of yellow passion fruit pulp samples. The PLS models produced lower values of root mean squares error of calibration (RMSEC), root mean squares error of prediction (RMSEP), and coefficient of determination above 0.7. Moisture and total sugars presented the best calibration models (RMSEP of 0.240 and 0.269, respectively, for guava pulp; RMSEP of 0.401 and 0.413, respectively, for passion fruit pulp) which enables the application of these models to determine adulteration in guava and yellow passion fruit pulp by water or sugar addition. The models constructed for calibration of quality parameters of frozen fruit pulps in this study indicate that NIR spectroscopy coupled with the multivariate calibration technique could be applied to determine the quality of guava and yellow passion fruit pulp. Copyright © 2016 Elsevier Ltd. All rights reserved.

Monitoring lipase-catalyzed interesterification for bulky fats modification with FT-IR/NIR spectroscopy

DEFF Research Database (Denmark)

Chang, Tinghong; Lai, Xuxin; Zhang, Hong

2005-01-01

This work demonstrates the application of FT-IR and FT-NIR spectroscopy to monitor the enzymatic interesterification process for bulky fat modification. The reaction was conducted between palm stearin and coconut oil (70/30, w/w) with the catalysis of Lipozyme TL IM at 70°C in a batch reactor...

Determination of moisture content of lyophilized allergen vaccines by NIR spectroscopy

DEFF Research Database (Denmark)

Zheng, Yiwu; Lai, Xuxin; Bruun, Susanne Wrang

2008-01-01

Moisture content is an important parameter for lyophilized vaccines. Currently, Karl Fischer titration is widely used for moisture determination in routine analysis. However, this method is time-consuming, sample destructive and requires environment polluting reagents, as well as the results rely...... on the random samplings. In this study, near infrared spectroscopy was used as a fast, non-invasive and non-destructive method to determine the moisture content in lyophilized allergy vaccines. Five different vaccine products were investigated, which contained water in the range of 0.17-1.51% (w/w, KF......). Different data pre-treatments, wavelength selection and partial least squares regression were applied to construct calibration models. Multi-products model and product-specific models were obtained, which show the possibility of NIR as a rapid method to discriminate whether moisture content fit...

Measurements of coherent hemodynamics to enrich the physiological information provided by near-infrared spectroscopy (NIRS) and functional MRI

Science.gov (United States)

Sassaroli, Angelo; Tgavalekos, Kristen; Pham, Thao; Krishnamurthy, Nishanth; Fantini, Sergio

2018-02-01

Hemodynamic-based neuroimaging techniques such as functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS) sense hemoglobin concentration in cerebral tissue. The local concentration of hemoglobin, which is differentiated into oxy- and deoxy-hemoglobin by NIRS, features spontaneous oscillations over time scales of 10-100 s in response to a number of local and systemic physiological processes. If one of such processes becomes the dominant source of cerebral hemodynamics, there is a high coherence between this process and the associated hemodynamics. In this work, we report a method to identify such conditions of coherent hemodynamics, which may be exploited to study and quantify microvasculature and microcirculation properties. We discuss how a critical value of significant coherence may depend on the specific data collection scheme (for example, the total acquisition time) and the nature of the hemodynamic data (in particular, oxy- and deoxy-hemoglobin concentrations measured with NIRS show an intrinsic level of correlation that must be taken into account). A frequency-resolved study of coherent hemodynamics is the basis for the new technique of coherent hemodynamics spectroscopy (CHS), which aims to provide measures of cerebral blood flow and cerebral autoregulation. While these concepts apply in principle to both fMRI and NIRS data, in this article we focus on NIRS data.

Predicting water-holding capacity of intact chicken broiler breast fillets with Vis/NIR spectroscopy

Science.gov (United States)

The ability of using visible and near-infrared (Vis/NIR) spectroscopy to predict water-holding capacity (WHC) of intact chicken broiler breast fillets (pectoralis major) was assessed in this study. Boneless and skinless chicken fillets (214 in total) were procured from a commercial processing plant ...

Characterizing and Authenticating Montilla-Moriles PDO Vinegars Using Near Infrared Reflectance Spectroscopy (NIRS Technology

Directory of Open Access Journals (Sweden)

María-José De la Haba

2014-02-01

Full Text Available This study assessed the potential of near infrared (NIR spectroscopy as a non-destructive method for characterizing Protected Designation of Origin (PDO “Vinagres de Montilla-Moriles” wine vinegars and for classifying them as a function of the manufacturing process used. Three spectrophotometers were evaluated for this purpose: two monochromator instruments (Foss NIRSystems 6500 SY-I and Foss NIRSystems 6500 SY-II; spectral range 400–2,500 nm in both cases and a diode-array instrument (Corona 45 VIS/NIR; spectral range 380–1,700 nm. A total of 70 samples were used to predict major chemical quality parameters (total acidity, fixed acidity, volatile acidity, pH, dry extract, ash, acetoin, methanol, total polyphenols, color (tonality and intensity, and alcohol content, and to construct models for the classification of vinegars as a function of the manufacturing method used. The results obtained indicate that this non-invasive technology can be used successfully by the vinegar industry and by PDO regulators for the routine analysis of vinegars in order to authenticate them and to detect potential fraud. Slightly better results were achieved with the two monochromator instruments. The findings also highlight the potential of these NIR instruments for predicting the manufacturing process used, this being of particular value for the industrial authentication of traditional wine vinegars.

NIR spectroscopic properties of aqueous acids solutions.

Science.gov (United States)

Omar, Ahmad Fairuz; Atan, Hanafi; Matjafri, Mohd Zubir

2012-06-15

Acid content is one of the important quality attributes in determining the maturity index of agricultural product, particularly fruits. Despite the fact that much research on the measurement of acidity in fruits through non-destructive spectroscopy analysis at NIR wavelengths between 700 to 1,000 nm has been conducted, the same response towards individual acids is not well known. This paper presents NIR spectroscopy analysis on aqueous citric, tartaric, malic and oxalic solutions through quantitative analysis by selecting a set of wavelengths that can best be used to measure the pH of the solutions. The aquaphotomics study of the acid solutions has generated R² above 0.9 for the measurement of all acids. The most important wavelengths for pH are located at 918-925 nm and 990-996 nm, while at 975 nm for water.

7 CFR 801.7 - Reference methods and tolerances for near-infrared spectroscopy (NIRS) analyzers.

Science.gov (United States)

2010-01-01

... 7 Agriculture 7 2010-01-01 2010-01-01 false Reference methods and tolerances for near-infrared spectroscopy (NIRS) analyzers. 801.7 Section 801.7 Agriculture Regulations of the Department of Agriculture...), DEPARTMENT OF AGRICULTURE OFFICIAL PERFORMANCE REQUIREMENTS FOR GRAIN INSPECTION EQUIPMENT § 801.7 Reference...

Handling of uncertainty due to interference fringe in FT-NIR transmittance spectroscopy - Performance comparison of interference elimination techniques using glucose-water system

Science.gov (United States)

Beganović, Anel; Beć, Krzysztof B.; Henn, Raphael; Huck, Christian W.

2018-05-01

The applicability of two elimination techniques for interferences occurring in measurements with cells of short pathlength using Fourier transform near-infrared (FT-NIR) spectroscopy was evaluated. Due to the growing interest in the field of vibrational spectroscopy in aqueous biological fluids (e.g. glucose in blood), aqueous solutions of D-(+)-glucose were prepared and split into a calibration set and an independent validation set. All samples were measured with two FT-NIR spectrometers at various spectral resolutions. Moving average smoothing (MAS) and fast Fourier transform filter (FFT filter) were applied to the interference affected FT-NIR spectra in order to eliminate the interference pattern. After data pre-treatment, partial least squares regression (PLSR) models using different NIR regions were constructed using untreated (interference affected) spectra and spectra treated with MAS and FFT filter. The prediction of the independent validation set revealed information about the performance of the utilized interference elimination techniques, as well as the different NIR regions. The results showed that the combination band of water at approx. 5200 cm-1 is of great importance since its performance was superior to the one of the so-called first overtone of water at approx. 6800 cm-1. Furthermore, this work demonstrated that MAS and FFT filter are fast and easy-to-use techniques for the elimination of interference fringes in FT-NIR transmittance spectroscopy.

Application of process analytical technology in tablet process development using NIR spectroscopy : Blend uniformity, content uniformity and coating thickness measurements

NARCIS (Netherlands)

Moes, Johannes J; Ruijken, Marco M; Gout, Erik; Frijlink, Henderik W; Ugwoke, Michael I

2008-01-01

Near-infrared (NIR)spectroscopy was employed as a process analytical technique in three steps of tabletting process: to monitor the blend homogeneity, evaluate the content uniformity of tablets and determine the tablets coating thickness. A diode-array spectrometer mounted on a lab blender (SP15 NIR

Prediction of Caffeine Content in Java Preanger Coffee Beans by NIR Spectroscopy Using PLS and MLR Method

Science.gov (United States)

Budiastra, I. W.; Sutrisno; Widyotomo, S.; Ayu, P. C.

2018-05-01

Caffeine is one of important components in coffee that contributes to the coffee beverages flavor. Caffeine concentration in coffee bean is usually determined by chemical method which is time consuming and destructive method. A nondestructive method using NIR spectroscopy was successfully applied to determine the caffeine concentration of Arabica gayo coffee bean. In this study, NIR Spectroscopy was assessed to determine the caffeine concentration of java preanger coffee bean. A hundred samples, each consist of 96 g coffee beans were prepared for reflectance and chemical measurement. Reflectance of the sample was measured by FT-NIR spectrometer in the wavelength of 1000-2500 nm (10000-4000 cm-1) followed by determination of caffeine content using LCMS method. Calibration of NIR spectra and the caffeine content was carried out using PLS and MLR methods. Several spectra data processing was conducted to increase the accuracy of prediction. The result of the study showed that caffeine content could be determined by PLS model using 7 factors and spectra data processing of combination of the first derivative and MSC of spectra absorbance (r = 0.946; CV = 1.54 %; RPD = 2.28). A lower accuracy was obtained by MLR model consisted of three caffeine and other four absorption wavelengths (r = 0.683; CV = 3.31%; RPD = 1.18).

Using an optimal CC-PLSR-RBFNN model and NIR spectroscopy for the starch content determination in corn

Science.gov (United States)

Jiang, Hao; Lu, Jiangang

2018-05-01

Corn starch is an important material which has been traditionally used in the fields of food and chemical industry. In order to enhance the rapidness and reliability of the determination for starch content in corn, a methodology is proposed in this work, using an optimal CC-PLSR-RBFNN calibration model and near-infrared (NIR) spectroscopy. The proposed model was developed based on the optimal selection of crucial parameters and the combination of correlation coefficient method (CC), partial least squares regression (PLSR) and radial basis function neural network (RBFNN). To test the performance of the model, a standard NIR spectroscopy data set was introduced, containing spectral information and chemical reference measurements of 80 corn samples. For comparison, several other models based on the identical data set were also briefly discussed. In this process, the root mean square error of prediction (RMSEP) and coefficient of determination (Rp2) in the prediction set were used to make evaluations. As a result, the proposed model presented the best predictive performance with the smallest RMSEP (0.0497%) and the highest Rp2 (0.9968). Therefore, the proposed method combining NIR spectroscopy with the optimal CC-PLSR-RBFNN model can be helpful to determine starch content in corn.

NIR spectroscopy as a tool for discriminating between lichens exposed to air pollution.

Science.gov (United States)

Casale, Monica; Bagnasco, Lucia; Giordani, Paolo; Mariotti, Mauro Giorgio; Malaspina, Paola

2015-09-01

Lichens are used as biomonitors of air pollution because they are extremely sensitive to the presence of substances that alter atmospheric composition. Fifty-one thalli of two different varieties of Pseudevernia furfuracea (var. furfuracea and var. ceratea) were collected far from local sources of air pollution. Twenty-six of these thalli were then exposed to the air for one month in the industrial port of Genoa, which has high levels of environmental pollution. The possibility of using Near-infrared spectroscopy (NIRS) for generating a 'fingerprint' of lichens was investigated. Chemometric methods were successfully applied to discriminate between samples from polluted and non-polluted areas. In particular, Principal Component Analysis (PCA) was applied as a multivariate display method on the NIR spectra to visualise the data structure. This showed that the difference between samples of different varieties was not significant in comparison to the difference between samples exposed to different levels of environmental pollution. Then Linear Discriminant Analysis (LDA) was carried out to discriminate between lichens based on their exposure to pollutants. The distinction between control samples (not exposed) and samples exposed to the air in the industrial port of Genoa was evaluated. On average, 95.2% of samples were correctly classified, 93.0% of total internal prediction (5 cross-validation groups) and 100.0% of external prediction (on the test set) was achieved. Copyright © 2015 Elsevier Ltd. All rights reserved.

In-line monitoring and interpretation of an indomethacin anti-solvent crystallization process by near-infrared spectroscopy (NIRS).

Science.gov (United States)

Lee, Hea-Eun; Lee, Min-Jeong; Kim, Woo-Sik; Jeong, Myung-Yung; Cho, Young-Sang; Choi, Guang Jin

2011-11-28

PAT (process analytical technology) has been emphasized as one of key elements for the full implementation of QbD (quality-by-design) in the pharmaceutical area. NIRS (near-infrared spectroscopy) has been studied intensively as an in-line/on-line monitoring tool in chemical and biomedical industries. A precise and reliable monitoring of the particle characteristics during crystallization along with a suitable control strategy should be highly encouraged for the conformance to new quality system of pharmaceutical products. In this study, the anti-solvent crystallization process of indomethacin (IMC) was monitored using an in-line NIRS. IMC powders were produced via anti-solvent crystallization using two schemes; 'S-to-A' (solvent-to-antisolvent) and 'A-to-S' (antisolvent-to-solvent). In-line NIR spectra were analyzed by a PCA (principal component analysis) method. Although pure α-form IMC powder was resulted under A-to-S scheme, a mixture of the α-form and γ-form was produced for S-to-A case. By integrating the PCA results with off-line characterization (SEM, XRD, DSC) data, the crystallization process under each scheme was elucidated by three distinct consecutive steps. It was demonstrated that in-line NIRS, combined with PCA, can be very useful to monitor in real time and interpret the anti-solvent crystallization process with respect to the polymorphism and particle size. Copyright © 2011 Elsevier B.V. All rights reserved.

Feasibility of Functional Near-Infrared Spectroscopy (fNIRS) to Investigate the Mirror Neuron System: An Experimental Study in a Real-Life Situation

Science.gov (United States)

Sun, Pei-Pei; Tan, Fu-Lun; Zhang, Zong; Jiang, Yi-Han; Zhao, Yang; Zhu, Chao-Zhe

2018-01-01

The mirror neuron system (MNS), mainly including the premotor cortex (PMC), inferior frontal gyrus (IFG), superior parietal lobule (SPL), and rostral inferior parietal lobule (IPL), has attracted extensive attention as a possible neural mechanism of social interaction. Owing to high ecological validity, functional near-infrared spectroscopy (fNIRS) has become an ideal approach for exploring the MNS. Unfortunately, for the feasibility of fNIRS to detect the MNS, none of the four dominant regions were found in previous studies, implying a very limited capacity of fNIRS to investigate the MNS. Here, we adopted an experimental paradigm in a real-life situation to evaluate whether the MNS activity, including four dominant regions, can be detected by using fNIRS. Specifically, 30 right-handed subjects were asked to complete a table-setting task that included action execution and action observation. A double density probe configuration covered the four regions of the MNS in the left hemisphere. We used a traditional channel-based group analysis and also a ROI-based group analysis to find which regions are activated during both action execution and action observation. The results showed that the IFG, adjacent PMC, SPL, and IPL were involved in both conditions, indicating the feasibility of fNIRS to detect the MNS. Our findings provide a foundation for future research to explore the functional role of the MNS in social interaction and various disorders using fNIRS. PMID:29556185

Feasibility of Functional Near-Infrared Spectroscopy (fNIRS to Investigate the Mirror Neuron System: An Experimental Study in a Real-Life Situation

Directory of Open Access Journals (Sweden)

Pei-Pei Sun

2018-03-01

Full Text Available The mirror neuron system (MNS, mainly including the premotor cortex (PMC, inferior frontal gyrus (IFG, superior parietal lobule (SPL, and rostral inferior parietal lobule (IPL, has attracted extensive attention as a possible neural mechanism of social interaction. Owing to high ecological validity, functional near-infrared spectroscopy (fNIRS has become an ideal approach for exploring the MNS. Unfortunately, for the feasibility of fNIRS to detect the MNS, none of the four dominant regions were found in previous studies, implying a very limited capacity of fNIRS to investigate the MNS. Here, we adopted an experimental paradigm in a real-life situation to evaluate whether the MNS activity, including four dominant regions, can be detected by using fNIRS. Specifically, 30 right-handed subjects were asked to complete a table-setting task that included action execution and action observation. A double density probe configuration covered the four regions of the MNS in the left hemisphere. We used a traditional channel-based group analysis and also a ROI-based group analysis to find which regions are activated during both action execution and action observation. The results showed that the IFG, adjacent PMC, SPL, and IPL were involved in both conditions, indicating the feasibility of fNIRS to detect the MNS. Our findings provide a foundation for future research to explore the functional role of the MNS in social interaction and various disorders using fNIRS.

Near-infrared spectroscopy for cocrystal screening. A comparative study with Raman spectroscopy.

Science.gov (United States)

Allesø, Morten; Velaga, Sitaram; Alhalaweh, Amjad; Cornett, Claus; Rasmussen, Morten A; van den Berg, Frans; de Diego, Heidi Lopez; Rantanen, Jukka

2008-10-15

Near-infrared (NIR) spectroscopy is a well-established technique for solid-state analysis, providing fast, noninvasive measurements. The use of NIR spectroscopy for polymorph screening and the associated advantages have recently been demonstrated. The objective of this work was to evaluate the analytical potential of NIR spectroscopy for cocrystal screening using Raman spectroscopy as a comparative method. Indomethacin was used as the parent molecule, while saccharin and l-aspartic acid were chosen as guest molecules. Molar ratios of 1:1 for each system were subjected to two types of preparative methods. In the case of saccharin, liquid-assisted cogrinding as well as cocrystallization from solution resulted in a stable 1:1 cocrystalline phase termed IND-SAC cocrystal. For l-aspartic acid, the solution-based method resulted in a polymorphic transition of indomethacin into the metastable alpha form retained in a physical mixture with the guest molecule, while liquid-assisted cogrinding did not induce any changes in the crystal lattice. The good chemical peak selectivity of Raman spectroscopy allowed a straightforward interpretation of sample data by analyzing peak positions and comparing to those of pure references. In addition, Raman spectroscopy provided additional information on the crystal structure of the IND-SAC cocrystal. The broad spectral line shapes of NIR spectra make visual interpretation of the spectra difficult, and consequently, multivariate modeling by principal component analysis (PCA) was applied. Successful use of NIR/PCA was possible only through the inclusion of a set of reference mixtures of parent and guest molecules representing possible solid-state outcomes from the cocrystal screening. The practical hurdle related to the need for reference mixtures seems to restrict the applicability of NIR spectroscopy in cocrystal screening.

Multivariate analysis of nystatin and metronidazole in a semi-solid matrix by means of diffuse reflectance NIR spectroscopy and PLS regression.

Science.gov (United States)

Baratieri, Sabrina C; Barbosa, Juliana M; Freitas, Matheus P; Martins, José A

2006-01-23

A multivariate method of analysis of nystatin and metronidazole in a semi-solid matrix, based on diffuse reflectance NIR measurements and partial least squares regression, is reported. The product, a vaginal cream used in the antifungal and antibacterial treatment, is usually, quantitatively analyzed through microbiological tests (nystatin) and HPLC technique (metronidazole), according to pharmacopeial procedures. However, near infrared spectroscopy has demonstrated to be a valuable tool for content determination, given the rapidity and scope of the method. In the present study, it was successfully applied in the prediction of nystatin (even in low concentrations, ca. 0.3-0.4%, w/w, which is around 100,000 IU/5g) and metronidazole contents, as demonstrated by some figures of merit, namely linearity, precision (mean and repeatability) and accuracy.

Applications of Functional Near-Infrared Spectroscopy (fNIRS) in Studying Cognitive Development: The Case of Mathematics and Language.

Science.gov (United States)

Soltanlou, Mojtaba; Sitnikova, Maria A; Nuerk, Hans-Christoph; Dresler, Thomas

2018-01-01

In this review, we aim to highlight the application of functional near-infrared spectroscopy (fNIRS) as a useful neuroimaging technique for the investigation of cognitive development. We focus on brain activation changes during the development of mathematics and language skills in schoolchildren. We discuss how technical limitations of common neuroimaging techniques such as functional magnetic resonance imaging (fMRI) have resulted in our limited understanding of neural changes during development, while fNIRS would be a suitable and child-friendly method to examine cognitive development. Moreover, this technique enables us to go to schools to collect large samples of data from children in ecologically valid settings. Furthermore, we report findings of fNIRS studies in the fields of mathematics and language, followed by a discussion of the outlook of fNIRS in these fields. We suggest fNIRS as an additional technique to track brain activation changes in the field of educational neuroscience.

Concurrent fNIRS-fMRI measurement to validate a method for separating deep and shallow fNIRS signals by using multidistance optodes

Science.gov (United States)

Funane, Tsukasa; Sato, Hiroki; Yahata, Noriaki; Takizawa, Ryu; Nishimura, Yukika; Kinoshita, Akihide; Katura, Takusige; Atsumori, Hirokazu; Fukuda, Masato; Kasai, Kiyoto; Koizumi, Hideaki; Kiguchi, Masashi

2015-01-01

Abstract. It has been reported that a functional near-infrared spectroscopy (fNIRS) signal can be contaminated by extracerebral contributions. Many algorithms using multidistance separations to address this issue have been proposed, but their spatial separation performance has rarely been validated with simultaneous measurements of fNIRS and functional magnetic resonance imaging (fMRI). We previously proposed a method for discriminating between deep and shallow contributions in fNIRS signals, referred to as the multidistance independent component analysis (MD-ICA) method. In this study, to validate the MD-ICA method from the spatial aspect, multidistance fNIRS, fMRI, and laser-Doppler-flowmetry signals were simultaneously obtained for 12 healthy adult males during three tasks. The fNIRS signal was separated into deep and shallow signals by using the MD-ICA method, and the correlation between the waveforms of the separated fNIRS signals and the gray matter blood oxygenation level–dependent signals was analyzed. A three-way analysis of variance (signal depth×Hb kind×task) indicated that the main effect of fNIRS signal depth on the correlation is significant [F(1,1286)=5.34, pdeep and shallow signals, and the accuracy and reliability of the fNIRS signal will be improved with the method. PMID:26157983

NIR monitoring of in-service wood structures

Science.gov (United States)

Michela Zanetti; Timothy G. Rials; Douglas Rammer

2005-01-01

Near infrared spectroscopy (NIRS) was used to study a set of Southern Yellow Pine boards exposed to natural weathering for different periods of exposure time. This non-destructive spectroscopic technique is a very powerful tool to predict the weathering of wood when used in combination with multivariate analysis (Principal Component Analysis, PCA, and Projection to...

Comparison of causality analysis on simultaneously measured fMRI and NIRS signals during motor tasks.

Science.gov (United States)

Anwar, Abdul Rauf; Muthalib, Makii; Perrey, Stephane; Galka, Andreas; Granert, Oliver; Wolff, Stephan; Deuschl, Guenther; Raethjen, Jan; Heute, Ulrich; Muthuraman, Muthuraman

2013-01-01

Brain activity can be measured using different modalities. Since most of the modalities tend to complement each other, it seems promising to measure them simultaneously. In to be presented research, the data recorded from Functional Magnetic Resonance Imaging (fMRI) and Near Infrared Spectroscopy (NIRS), simultaneously, are subjected to causality analysis using time-resolved partial directed coherence (tPDC). Time-resolved partial directed coherence uses the principle of state space modelling to estimate Multivariate Autoregressive (MVAR) coefficients. This method is useful to visualize both frequency and time dynamics of causality between the time series. Afterwards, causality results from different modalities are compared by estimating the Spearman correlation. In to be presented study, we used directionality vectors to analyze correlation, rather than actual signal vectors. Results show that causality analysis of the fMRI correlates more closely to causality results of oxy-NIRS as compared to deoxy-NIRS in case of a finger sequencing task. However, in case of simple finger tapping, no clear difference between oxy-fMRI and deoxy-fMRI correlation is identified.

Pharmaceutical Raw Material Identification Using Miniature Near-Infrared (MicroNIR) Spectroscopy and Supervised Pattern Recognition Using Support Vector Machine

OpenAIRE

Sun, Lan; Hsiung, Chang; Pederson, Christopher G.; Zou, Peng; Smith, Valton; von Gunten, Marc; O?Brien, Nada A.

2016-01-01

Near-infrared spectroscopy as a rapid and non-destructive analytical technique offers great advantages for pharmaceutical raw material identification (RMID) to fulfill the quality and safety requirements in pharmaceutical industry. In this study, we demonstrated the use of portable miniature near-infrared (MicroNIR) spectrometers for NIR-based pharmaceutical RMID and solved two challenges in this area, model transferability and large-scale classification, with the aid of support vector machin...

A Brief Review on the Use of Functional Near-Infrared Spectroscopy (fNIRS) for Language Imaging Studies in Human Newborns and Adults

Science.gov (United States)

Quaresima, Valentina; Bisconti, Silvia; Ferrari, Marco

2012-01-01

Upon stimulation, real time maps of cortical hemodynamic responses can be obtained by non-invasive functional near-infrared spectroscopy (fNIRS) which measures changes in oxygenated and deoxygenated hemoglobin after positioning multiple sources and detectors over the human scalp. The current commercially available transportable fNIRS systems have…

A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application.

Science.gov (United States)

Ferrari, Marco; Quaresima, Valentina

2012-11-01

This review is aimed at celebrating the upcoming 20th anniversary of the birth of human functional near-infrared spectroscopy (fNIRS). After the discovery in 1992 that the functional activation of the human cerebral cortex (due to oxygenation and hemodynamic changes) can be explored by NIRS, human functional brain mapping research has gained a new dimension. fNIRS or optical topography, or near-infrared imaging or diffuse optical imaging is used mainly to detect simultaneous changes in optical properties of the human cortex from multiple measurement sites and displays the results in the form of a map or image over a specific area. In order to place current fNIRS research in its proper context, this paper presents a brief historical overview of the events that have shaped the present status of fNIRS. In particular, technological progresses of fNIRS are highlighted (i.e., from single-site to multi-site functional cortical measurements (images)), introduction of the commercial multi-channel systems, recent commercial wireless instrumentation and more advanced prototypes. Copyright © 2012 Elsevier Inc. All rights reserved.

Application of reflectance spectroscopies (FTIR-ATR & FT-NIR) coupled with multivariate methods for robust in vivo detection of begomovirus infection in papaya leaves

Science.gov (United States)

Haq, Quazi M. I.; Mabood, Fazal; Naureen, Zakira; Al-Harrasi, Ahmed; Gilani, Sayed A.; Hussain, Javid; Jabeen, Farah; Khan, Ajmal; Al-Sabari, Ruqaya S. M.; Al-khanbashi, Fatema H. S.; Al-Fahdi, Amira A. M.; Al-Zaabi, Ahoud K. A.; Al-Shuraiqi, Fatma A. M.; Al-Bahaisi, Iman M.

2018-06-01

Nucleic acid & serology based methods have revolutionized plant disease detection, however, they are not very reliable at asymptomatic stage, especially in case of pathogen with systemic infection, in addition, they need at least 1-2 days for sample harvesting, processing, and analysis. In this study, two reflectance spectroscopies i.e. Near Infrared reflectance spectroscopy (NIR) and Fourier-Transform-Infrared spectroscopy with Attenuated Total Reflection (FT-IR, ATR) coupled with multivariate exploratory methods like Principle Component Analysis (PCA) and Partial least square discriminant analysis (PLS-DA) have been deployed to detect begomovirus infection in papaya leaves. The application of those techniques demonstrates that they are very useful for robust in vivo detection of plant begomovirus infection. These methods are simple, sensitive, reproducible, precise, and do not require any lengthy samples preparation procedures.

NIRS as an alternative to conventional soil analysis for Greenland soils (focus on SOC)

DEFF Research Database (Denmark)

Knadel, Maria; Ogric, Mateja; Adhikari, Kabindra

Soil organic carbon (SOC) is an important soil property. It is the main constituents of soil organic matter and a good indicator of soil quality. The estimation and mapping of SOC content could be used to select potential agricultural areas in the Arctic areas. However, conventional analysis of SOC...... are time consuming and expensive. They involve a lot of sample preparation, and chemicals and are destructive. Near infrared spectroscopy (NIRS) in the range between 400 and 2500 nm is an alternative method for SOC analysis. It is fast and non-destructive. The aims of this study where to test...... the feasibility of using NIRS to estimate SOC content on a landscape and field scale in Greenland. Partial Least squares regression models were built to correlated soil spectra and their reference SOC data to develop calibration models. Very good predictive ability for both landscape and field scale were obtained...

NIR spectroscopy for the in-line monitoring of a multicomponent formulation during the entire freeze-drying process

NARCIS (Netherlands)

Rosas, Juan G; de Waard, Hans; De Beer, Thomas; Vervaet, Chris; Remon, Jean Paul; Hinrichs, Wouter L J; Frijlink, Henderik W; Blanco, Marcel

2014-01-01

Freeze drying is a complex, time consuming and thus expensive process, hence creating a need for understanding the material behaviour in the process environment and for process optimization. Near-infrared (NIR) spectroscopy offers the opportunity to monitor physicochemical changes of the formulation

Time domain functional NIRS imaging for human brain mapping.

Science.gov (United States)

Torricelli, Alessandro; Contini, Davide; Pifferi, Antonio; Caffini, Matteo; Re, Rebecca; Zucchelli, Lucia; Spinelli, Lorenzo

2014-01-15

This review is aimed at presenting the state-of-the-art of time domain (TD) functional near-infrared spectroscopy (fNIRS). We first introduce the physical principles, the basics of modeling and data analysis. Basic instrumentation components (light sources, detection techniques, and delivery and collection systems) of a TD fNIRS system are described. A survey of past, existing and next generation TD fNIRS systems used for research and clinical studies is presented. Performance assessment of TD fNIRS systems and standardization issues are also discussed. Main strengths and weakness of TD fNIRS are highlighted, also in comparison with continuous wave (CW) fNIRS. Issues like quantification of the hemodynamic response, penetration depth, depth selectivity, spatial resolution and contrast-to-noise ratio are critically examined, with the help of experimental results performed on phantoms or in vivo. Finally we give an account on the technological developments that would pave the way for a broader use of TD fNIRS in the neuroimaging community. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Laboratory spectroscopy of meteorite samples at UV-vis-NIR wavelengths: Analysis and discrimination by principal components analysis

Science.gov (United States)

Penttilä, Antti; Martikainen, Julia; Gritsevich, Maria; Muinonen, Karri

2018-02-01

Meteorite samples are measured with the University of Helsinki integrating-sphere UV-vis-NIR spectrometer. The resulting spectra of 30 meteorites are compared with selected spectra from the NASA Planetary Data System meteorite spectra database. The spectral measurements are transformed with the principal component analysis, and it is shown that different meteorite types can be distinguished from the transformed data. The motivation is to improve the link between asteroid spectral observations and meteorite spectral measurements.

Application of reflectance spectroscopies (FTIR-ATR & FT-NIR) coupled with multivariate methods for robust in vivo detection of begomovirus infection in papaya leaves.

Science.gov (United States)

Haq, Quazi M I; Mabood, Fazal; Naureen, Zakira; Al-Harrasi, Ahmed; Gilani, Sayed A; Hussain, Javid; Jabeen, Farah; Khan, Ajmal; Al-Sabari, Ruqaya S M; Al-Khanbashi, Fatema H S; Al-Fahdi, Amira A M; Al-Zaabi, Ahoud K A; Al-Shuraiqi, Fatma A M; Al-Bahaisi, Iman M

2018-06-05

Nucleic acid & serology based methods have revolutionized plant disease detection, however, they are not very reliable at asymptomatic stage, especially in case of pathogen with systemic infection, in addition, they need at least 1-2days for sample harvesting, processing, and analysis. In this study, two reflectance spectroscopies i.e. Near Infrared reflectance spectroscopy (NIR) and Fourier-Transform-Infrared spectroscopy with Attenuated Total Reflection (FT-IR, ATR) coupled with multivariate exploratory methods like Principle Component Analysis (PCA) and Partial least square discriminant analysis (PLS-DA) have been deployed to detect begomovirus infection in papaya leaves. The application of those techniques demonstrates that they are very useful for robust in vivo detection of plant begomovirus infection. These methods are simple, sensitive, reproducible, precise, and do not require any lengthy samples preparation procedures. Copyright © 2018 Elsevier B.V. All rights reserved.

Measurement of process variables in solid-state fermentation of wheat straw using FT-NIR spectroscopy and synergy interval PLS algorithm

Science.gov (United States)

Jiang, Hui; Liu, Guohai; Mei, Congli; Yu, Shuang; Xiao, Xiahong; Ding, Yuhan

2012-11-01

The feasibility of rapid determination of the process variables (i.e. pH and moisture content) in solid-state fermentation (SSF) of wheat straw using Fourier transform near infrared (FT-NIR) spectroscopy was studied. Synergy interval partial least squares (siPLS) algorithm was implemented to calibrate regression model. The number of PLS factors and the number of subintervals were optimized simultaneously by cross-validation. The performance of the prediction model was evaluated according to the root mean square error of cross-validation (RMSECV), the root mean square error of prediction (RMSEP) and the correlation coefficient (R). The measurement results of the optimal model were obtained as follows: RMSECV = 0.0776, Rc = 0.9777, RMSEP = 0.0963, and Rp = 0.9686 for pH model; RMSECV = 1.3544% w/w, Rc = 0.8871, RMSEP = 1.4946% w/w, and Rp = 0.8684 for moisture content model. Finally, compared with classic PLS and iPLS models, the siPLS model revealed its superior performance. The overall results demonstrate that FT-NIR spectroscopy combined with siPLS algorithm can be used to measure process variables in solid-state fermentation of wheat straw, and NIR spectroscopy technique has a potential to be utilized in SSF industry.

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.

Predicting glycogen concentration in the foot muscle of abalone using near infrared reflectance spectroscopy (NIRS).

Science.gov (United States)

Fluckiger, Miriam; Brown, Malcolm R; Ward, Louise R; Moltschaniwskyj, Natalie A

2011-06-15

Near infrared reflectance spectroscopy (NIRS) was used to predict glycogen concentrations in the foot muscle of cultured abalone. NIR spectra of live, shucked and freeze-dried abalones were modelled against chemically measured glycogen data (range: 0.77-40.9% of dry weight (DW)) using partial least squares (PLS) regression. The calibration models were then used to predict glycogen concentrations of test abalone samples and model robustness was assessed from coefficient of determination of the validation (R2(val)) and standard error of prediction (SEP) values. The model for freeze-dried abalone gave the best prediction (R2(val) 0.97, SEP=1.71), making it suitable for quantifying glycogen. Models for live and shucked abalones had R2(val) of 0.86 and 0.90, and SEP of 3.46 and 3.07 respectively, making them suitable for producing estimations of glycogen concentration. As glycogen is a taste-active component associated with palatability in abalone, this study demonstrated the potential of NIRS as a rapid method to monitor the factors associated with abalone quality. Copyright © 2011 Elsevier Ltd. All rights reserved.

Quality assessment of pharmaceutical tablet samples using Fourier transform near infrared spectroscopy and multivariate analysis

Science.gov (United States)

Kandpal, Lalit Mohan; Tewari, Jagdish; Gopinathan, Nishanth; Stolee, Jessica; Strong, Rick; Boulas, Pierre; Cho, Byoung-Kwan

2017-09-01

Determination of the content uniformity, assessed by the amount of an active pharmaceutical ingredient (API), and hardness of pharmaceutical materials is important for achieving a high-quality formulation and to ensure the intended therapeutic effects of the end-product. In this work, Fourier transform near infrared (FT-NIR) spectroscopy was used to determine the content uniformity and hardness of a pharmaceutical mini-tablet and standard tablet samples. Tablet samples were scanned using an FT-NIR instrument and tablet spectra were collected at wavelengths of 1000-2500 nm. Furthermore, multivariate analysis was applied to extract the relationship between the FT-NIR spectra and the measured parameters. The results of FT-NIR spectroscopy for API and hardness prediction were as precise as the reference high-performance liquid chromatography and mechanical hardness tests. For the prediction of mini-tablet API content, the highest coefficient of determination for the prediction (R2p) was found to be 0.99 with a standard error of prediction (SEP) of 0.72 mg. Moreover, the standard tablet hardness measurement had a R2p value of 0.91 with an SEP of 0.25 kg. These results suggest that FT-NIR spectroscopy is an alternative and accurate nondestructive measurement tool for the detection of the chemical and physical properties of pharmaceutical samples.

Identification of spilled oils by NIR spectroscopy technology based on KPCA and LSSVM

Science.gov (United States)

Tan, Ailing; Bi, Weihong

2011-08-01

Oil spills on the sea surface are seen relatively often with the development of the petroleum exploitation and transportation of the sea. Oil spills are great threat to the marine environment and the ecosystem, thus the oil pollution in the ocean becomes an urgent topic in the environmental protection. To develop the oil spill accident treatment program and track the source of the spilled oils, a novel qualitative identification method combined Kernel Principal Component Analysis (KPCA) and Least Square Support Vector Machine (LSSVM) was proposed. The proposed method adapt Fourier transform NIR spectrophotometer to collect the NIR spectral data of simulated gasoline, diesel fuel and kerosene oil spills samples and do some pretreatments to the original spectrum. We use the KPCA algorithm which is an extension of Principal Component Analysis (PCA) using techniques of kernel methods to extract nonlinear features of the preprocessed spectrum. Support Vector Machines (SVM) is a powerful methodology for solving spectral classification tasks in chemometrics. LSSVM are reformulations to the standard SVMs which lead to solving a system of linear equations. So a LSSVM multiclass classification model was designed which using Error Correcting Output Code (ECOC) method borrowing the idea of error correcting codes used for correcting bit errors in transmission channels. The most common and reliable approach to parameter selection is to decide on parameter ranges, and to then do a grid search over the parameter space to find the optimal model parameters. To test the proposed method, 375 spilled oil samples of unknown type were selected to study. The optimal model has the best identification capabilities with the accuracy of 97.8%. Experimental results show that the proposed KPCA plus LSSVM qualitative analysis method of near infrared spectroscopy has good recognition result, which could work as a new method for rapid identification of spilled oils.

Determination of alcohol and extract concentration in beer samples using a combined method of near-infrared (NIR) spectroscopy and refractometry.

Science.gov (United States)

Castritius, Stefan; Kron, Alexander; Schäfer, Thomas; Rädle, Matthias; Harms, Diedrich

2010-12-22

A new approach of combination of near-infrared (NIR) spectroscopy and refractometry was developed in this work to determine the concentration of alcohol and real extract in various beer samples. A partial least-squares (PLS) regression, as multivariate calibration method, was used to evaluate the correlation between the data of spectroscopy/refractometry and alcohol/extract concentration. This multivariate combination of spectroscopy and refractometry enhanced the precision in the determination of alcohol, compared to single spectroscopy measurements, due to the effect of high extract concentration on the spectral data, especially of nonalcoholic beer samples. For NIR calibration, two mathematical pretreatments (first-order derivation and linear baseline correction) were applied to eliminate light scattering effects. A sample grouping of the refractometry data was also applied to increase the accuracy of the determined concentration. The root mean squared errors of validation (RMSEV) of the validation process concerning alcohol and extract concentration were 0.23 Mas% (method A), 0.12 Mas% (method B), and 0.19 Mas% (method C) and 0.11 Mas% (method A), 0.11 Mas% (method B), and 0.11 Mas% (method C), respectively.

Near-infrared spectroscopy for cocrystal screening

DEFF Research Database (Denmark)

Allesø, Morten; Velaga, Sitaram; Alhalaweh, Amjad

2008-01-01

Near-infrared (NIR) spectroscopy is a well-established technique for solid-state analysis, providing fast, noninvasive measurements. The use of NIR spectroscopy for polymorph screening and the associated advantages have recently been demonstrated. The objective of this work was to evaluate...... the analytical potential of NIR spectroscopy for cocrystal screening using Raman spectroscopy as a comparative method. Indomethacin was used as the parent molecule, while saccharin and l-aspartic acid were chosen as guest molecules. Molar ratios of 1:1 for each system were subjected to two types of preparative...... retained in a physical mixture with the guest molecule, while liquid-assisted cogrinding did not induce any changes in the crystal lattice. The good chemical peak selectivity of Raman spectroscopy allowed a straightforward interpretation of sample data by analyzing peak positions and comparing to those...

A brief review on the use of functional near-infrared spectroscopy (fNIRS) for language imaging studies in human newborns and adults.

Science.gov (United States)

Quaresima, Valentina; Bisconti, Silvia; Ferrari, Marco

2012-05-01

Upon stimulation, real time maps of cortical hemodynamic responses can be obtained by non-invasive functional near-infrared spectroscopy (fNIRS) which measures changes in oxygenated and deoxygenated hemoglobin after positioning multiple sources and detectors over the human scalp. The current commercially available transportable fNIRS systems have a time resolution of 1-10 Hz, a depth sensitivity of about 1.5 cm, and a spatial resolution of about 1cm. The goal of this brief review is to report infants, children and adults fNIRS language studies. Since 1998, 60 studies have been published on cortical activation in the brain's classic language areas in children/adults as well as newborns using fNIRS instrumentations of different complexity. In addition, the basic principles of fNIRS including features, strengths, advantages, and limitations are summarized in terms that can be understood even by non specialists. Future prospects of fNIRS in the field of language processing imaging are highlighted. Copyright © 2011 Elsevier Inc. All rights reserved.

[Research progress and application prospect of near infrared spectroscopy in soil nutrition analysis].

Science.gov (United States)

Ding, Hai-quan; Lu, Qi-peng

2012-01-01

"Digital agriculture" or "precision agriculture" is an important direction of modern agriculture technique. It is the combination of the modern information technique and traditional agriculture and becomes a hotspot field in international agriculture research in recent years. As a nondestructive, real-time, effective and exact analysis technique, near infrared spectroscopy, by which precision agriculture could be carried out, has vast prospect in agrology and gradually gained the recognition. The present paper intends to review the basic theory of near infrared spectroscopy and its applications in the field of agrology, pointing out that the direction of NIR in agrology should based on portable NIR spectrograph in order to acquire qualitative or quantitative information from real-time measuring in field. In addition, NIRS could be combined with space remote sensing to macroscopically control the way crop is growing and the nutrition crops need, to change the current state of our country's agriculture radically.

Near Infrared Spectroscopy (NIRS) for the determination of the milk fat fatty acid profile of goats.

Science.gov (United States)

Núñez-Sánchez, N; Martínez-Marín, A L; Polvillo, O; Fernández-Cabanás, V M; Carrizosa, J; Urrutia, B; Serradilla, J M

2016-01-01

Milk fatty acid (FA) composition is important for the goat dairy industry because of its influence on cheese properties and human health. The aim of the present work was to evaluate the feasibility of NIRS reflectance (oven-dried milk using the DESIR method) and transflectance (liquid milk) analysis to predict milk FA profile and groups of fats in milk samples from individual goats. NIRS analysis of milk samples allowed to estimate FA contents and their ratios and indexes in fat with high precision and accuracy. In general, transflectance analysis gave better or similar results than reflectance mode. Interestingly, NIRS analysis allowed direct prediction of the Atherogenicity and Thrombogenicity indexes, which are useful for the interpretation of the nutritional value of goat milk. Therefore, the calibrations obtained in the present work confirm the viability of NIRS as a fast, reliable and effective analytical method to provide nutritional information of milk samples. Copyright © 2015 Elsevier Ltd. All rights reserved.

Saphenous vein graft near-infrared spectroscopy imaging insights from the lipid core plaque association with clinical events near-infrared spectroscopy (ORACLE-NIRS) registry.

Science.gov (United States)

Danek, Barbara A; Karatasakis, Aris; Alame, Aya J; Nguyen-Trong, Phuong-Khanh J; Karacsonyi, Judit; Rangan, Bavana; Roesle, Michele; Atwell, Amy; Resendes, Erica; Martinez-Parachini, Jose Roberto; Iwnetu, Rahel; Kalsaria, Pratik; Siddiqui, Furqan; Muller, James E; Banerjee, Subhash; Brilakis, Emmanouil

2017-05-01

We sought to examine near-infrared spectroscopy (NIRS) imaging findings of aortocoronary saphenous vein grafts (SVGs). SVGs are prone to develop atherosclerosis similar to native coronary arteries. They have received little study using NIRS. We examined the clinical characteristics and imaging findings from 43 patients who underwent NIRS imaging of 45 SVGs at our institution between 2009 and 2016. The mean patient age was 67 ± 7 years and 98% were men, with high prevalence of diabetes mellitus (56%), hypertension (95%), and dyslipidemia (95%). Mean SVG age was 7 ± 7 years, mean SVG lipid core burden index (LCBI) was 53 ± 60 and mean maxLCBI 4 mm was 194 ± 234. Twelve SVGs (27%) had lipid core plaques (2 yellow blocks on the block chemogram), with a higher prevalence in SVGs older than 5 years (46% vs. 5%, P = 0.002). Older SVG age was associated with higher LCBI (r = 0.480, P < 0.001) and higher maxLCBI 4 mm (r = 0.567, P < 0.001). On univariate analysis, greater annual total cholesterol exposure was associated with higher SVG LCBI (r = 0.30, P = 0.042) and annual LDL-cholesterol and triglyceride exposure were associated with higher SVG maxLCBI 4 mm (LDL-C: r = 0.41, P = 0.020; triglycerides: r = 0.36, P = 0.043). On multivariate analysis, the only independent predictor of SVG LCBI and maxLCBI 4mm was SVG age. SVG percutaneous coronary intervention was performed in 63% of the patients. An embolic protection device was used in 96% of SVG PCIs. Periprocedural myocardial infarction occurred in one patient. Older SVG age and greater lipid exposure are associated with higher SVG lipid burden. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

[Exploration of rapidly determining quality of traditional Chinese medicines by (NIR) spectroscopy based on internet sharing mode].

Science.gov (United States)

Ni, Li-Jun; Luan, Shao-Rong; Zhang, Li-Guo

2016-10-01

Because of the numerous varieties of herbal species and active ingredients in the traditional Chinese medicine(TCM),the traditional methods employed could hardly satisfy the current determination requirements of TCM.The present work proposed an idea to realize rapid determination of the quality of TCM based on near infrared(NIR)spectroscopy and internet sharing mode. Low cost and portable multi-source composite spectrometer was invented by our group for in-site fast measurement of spectra of TCM samples. The database could be set up by sharing spectra and quality detection data of TCM samples among TCM enterprises based on the internet platform.A novel method called as keeping same relationship between X and Y space based on K nearest neighbors(KNN-KSR for short)was applied to predict the contents of effective compounds of the samples. In addition,a comparative study between KNN-KSR and partial least squares(PLS)was conducted. Two datasets were applied to validate above idea:one was about 58 Ginkgo Folium samples samples measured with four near-infrared spectroscopy instruments and two multi-source composite spectrometers,another one was about 80 corn samples available online measured with three NIR instruments. The results show that the KNN-KSR method could obtain more reliable outcomes without correcting spectrum.However transforming the PLS models to other instruments could hardly acquire better predictive results until spectral calibration is performed. Meanwhile,the similar analysis results of total flavonoids and total lactones of Ginkgo Folium samples are achieved on the multi-source composite spectrometers and near-infrared spectroscopy instruments,and the prediction results of KNN-KSR are better than PLS. The idea proposed in present study is in urgent need of more samples spectra, and then to be verified by more case studies. Copyright© by the Chinese Pharmaceutical Association.

Combined operando Raman/UV-Vis-NIR spectroscopy as a tool to study supported metal oxide catalysts at work

NARCIS (Netherlands)

Tinnemans, Stanislaus Josephus

2006-01-01

A novel set-up has been developed in which two complementary spectroscopic techniques, namely operando Raman and UV-Vis-NIR spectroscopy, are combined. With this set-up it is possible to characterize catalytic materials under reaction conditions (high temperature, normal pressure) and in this way on

Fast and Convenient NIR Spectroscopy Procedure for Determination of Metformin Hydrochloride in Tablets

Science.gov (United States)

Pyzowski, J.; Lenartowicz, M.; Sobańska, A. W.; Brzezińska, E.

2017-09-01

A rapid and convenient near-infrared (NIR) reflectance spectroscopic procedure for the determination of metformin hydrochloride in tablets is presented. Determination was based on calibration curves that were obtained using a range of standards containing different concentrations of metformin hydrochloride blended with polyvinylpyrrolidone. The raw spectra of the standards, neat PVP, metformin hydrochloride, and powdered tablets were processed using a Multiplicative Scatter Correction filter as well as by the derivative spectroscopy method to give a basis for the calibration curve construction. The results were validated by thin-layer chromatography followed by UV-densitometry.

[Real-time detection of quality of Chinese materia medica: strategy of NIR model evaluation].

Science.gov (United States)

Wu, Zhi-sheng; Shi, Xin-yuan; Xu, Bing; Dai, Xing-xing; Qiao, Yan-jiang

2015-07-01

The definition of critical quality attributes of Chinese materia medica ( CMM) was put forward based on the top-level design concept. Nowadays, coupled with the development of rapid analytical science, rapid assessment of critical quality attributes of CMM was firstly carried out, which was the secondary discipline branch of CMM. Taking near infrared (NIR) spectroscopy as an example, which is a rapid analytical technology in pharmaceutical process over the past decade, systematic review is the chemometric parameters in NIR model evaluation. According to the characteristics of complexity of CMM and trace components analysis, a multi-source information fusion strategy of NIR model was developed for assessment of critical quality attributes of CMM. The strategy has provided guideline for NIR reliable analysis in critical quality attributes of CMM.

Characterization of pigment/binder - systems in arts via FTIR and UV/Vis/NIR - spectroscopy with special consideration of nondestructive methods

International Nuclear Information System (INIS)

Vetter, W.A.

2014-01-01

The main focus of this doctoral thesis is on the non-destructive analysis of art objects by using compound specific reflection-UV/Vis/NIR and reflection-FTIR spectroscopy. Based on commercially available instruments, measuring systems have been designed and built to meet the specific requirements of material analysis in the field of art. These systems have been utilized to analyse different types of art objects (watercolour paintings, easel paintings, contemporary graphic art objects) in order to identify the materials used by the artists. Furthermore, two new procedures are presented which allow to build up adequate reference databases from only minimal sample amounts of original watercolour materials of the 19th century. This is a crucial point as both methods require references for the identification of the materials. The results obtained demonstrate that UV/Vis/NIR and FTIR spectroscopy in reflection mode enable the non-destructive identification of a variety of both, organic and inorganic materials, particularly in combination with element specific XRF (X-ray fluorescence analysis) and thus are valuable tools for the analysis of cultural heritage objects. Furthermore, the results have shown that a comparison of the complementary methods strongly facilitated the evaluation of spectra obtained by the particular analytical techniques and hence reliable results could be obtained in many cases. As expected, several frequently used pigments e.g. carbon based blacks, earth pigments and lake pigments could not be identified unambiguously due to methodical limitations. Therefore, the use of additional complementary methods such as Raman spectroscopy and X-ray diffraction (XRD) would be highly desirable. Except a few examples, the characteristics of the radiation used for the investigations did not allow to draw conclusions about the distribution of materials in multilayer structures. For this reason, it still remains necessary to analyse cross-sections of samples for a

Use of UV-vis-NIR spectroscopy to monitor label-free interaction between molecular recognition elements and erythropoietin on a gold-coated polycarbonate platform.

Science.gov (United States)

Citartan, Marimuthu; Gopinath, Subash C B; Tominaga, Junji; Chen, Yeng; Tang, Thean-Hock

2014-08-01

Label-free-based detection is pivotal for real-time monitoring of biomolecular interactions and to eliminate the need for labeling with tags that can occupy important binding sites of biomolecules. One simplest form of label-free-based detection is ultraviolet-visible-near-infrared (UV-vis-NIR) spectroscopy, which measure changes in reflectivity as a means to monitor immobilization and interaction of biomolecules with their corresponding partners. In biosensor development, the platform used for the biomolecular interaction should be suitable for different molecular recognition elements. In this study, gold (Au)-coated polycarbonate was used as a platform and as a proof-of-concept, erythropoietin (EPO), a doping substance widely abused by the athletes was used as the target. The interaction of EPO with its corresponding molecular recognition elements (anti-EPO monoclonal antibody and anti-EPO DNA aptamer) is monitored by UV-vis-NIR spectroscopy. Prior to this, to show that UV-vis-NIR spectroscopy is a suitable method for measuring biomolecular interaction, the interaction between biotin and streptavidin was demonstrated via this strategy and reflectivity of this interaction decreased by 25%. Subsequent to this, interaction of the EPO with anti-EPO monoclonal antibody and anti-EPO DNA aptamer resulted in the decrease of reflectivity by 5% and 10%, respectively. The results indicated that Au-coated polycarbonate could be an ideal biosensor platform for monitoring biomolecular interactions using UV-vis-NIR spectroscopy. A smaller version of the Au-coated polycarbonate substrates can be derived from the recent set-up, to be applied towards detecting EPO abuse among atheletes. Copyright © 2014 Elsevier B.V. All rights reserved.

Epoch making NIRS studies seen through citation trends

International Nuclear Information System (INIS)

Dan, Ippeita

2009-01-01

Near-infrared spectroscopy (NIRS) studies through citation trends are investigated of literature concerning only the brain function measurement and its methodology together with NIRS principle, technological development, present state and future view. Investigation is conducted firstly for the survey of important author name of those concerned papers in Web of Science and Google Scholar with search words of NIRS, brain and optical topography as an option. Second, >100 papers of those authors citing any of them are picked up and their papers are ranked in accordance with Web of Science citation number, of which top-nineteen are presented here. Impact and epoch making papers are reviewed with explanations of: the establishment of measuring technology of cerebral blood flow change and subsequent brain function by NIRS; development with multi-channel detection; simultaneous measurement with other imaging modalities; examination of NIRS validity; spatial analysis of NIRS; and measurement of brain function. The highest times of citation are 1,238 of the paper by F. F. Jobsis in 'Science' (1977). It should be noted that 10 of top 19 papers are those by Japanese authors. However, review articles omitted in the present literature survey are mostly described by foreign authors: an effort to systemize the concerned fields might be required in this country. (K.T.)

Wearable functional Near Infrared Spectroscopy (fNIRS and transcranial Direct Current Stimulation (tDCS: Expanding Vistas for Neurocognitive Augmentation

Directory of Open Access Journals (Sweden)

Ryan eMcKendrick

2015-03-01

Full Text Available Contemporary studies with transcranial direct current stimulation (tDCS provide a growing base of evidence for enhancing cognition through the non-invasive delivery of weak electric currents to the brain. The main effect of tDCS is to modulate cortical excitability depending on the polarity of the applied current. However, the underlying mechanism of neuromodulation is not well understood. A new generation of functional near infrared spectroscopy (fNIRS systems is described that are miniaturized, portable, and include wearable sensors. These developments provide an opportunity to couple fNIRS with tDCS, consistent with a neuroergonomics approach for joint neuroimaging and neurostimulation investigations of cognition in complex tasks and in naturalistic conditions. The effects of tDCS on complex task performance and the use of fNIRS for monitoring cognitive workload during task performance are described. Also explained is how fNIRS + tDCS can be used simultaneously for assessing spatial working memory. Mobile optical brain imaging is a promising neuroimaging tool that has the potential to complement tDCS for realistic applications in natural settings.

Using Massive Multivariate NIRS Data in Ryegrass

DEFF Research Database (Denmark)

Edriss, Vahid; Greve-Pedersen, Morten; Jensen, Christian S

2015-01-01

Near infrared spectroscopy (NIRS) analytical techniques is a simple, fast and low cost method of high dimensional phenotyping compared to usual chemical techniques. To use this method there is no need for special sample preparation. The aim of this study is to use NIRS data to predict plant traits...... (e.g. dry matter, protein content, etc.) for the next generation. In total 1984 NIRS data from 995 ryegrass families (first cut) were used. The Absorption of radiation in the region of 960 – 1690 nm in every 2 nm distance produced 366 bins to represent the NIRS spectrum. The amount of genetic...

Recent developments in fast spectroscopy for plant mineral analysis

Directory of Open Access Journals (Sweden)

Marie evan Maarschalkerweerd

2015-03-01

Full Text Available Ideal fertilizer management to optimize plant productivity and quality is more relevant than ever, as global food demands increase along with the rapidly growing world population. At the same time, sub-optimal or excessive use of fertilizers leads to severe environmental damage in areas of intensive crop production. The approaches of soil and plant mineral analysis are briefly compared and discussed here, and the new techniques using fast spectroscopy that offer cheap, rapid and easy-to-use analysis of plant nutritional status are reviewed. The majority of these methods use vibrational spectroscopy, such as Visual-Near Infrared (Vis-NIR and to a lesser extent Ultraviolet (UV and Mid-Infrared (MIR spectroscopy. Advantages of and problems with application of these techniques are thoroughly discussed. Spectroscopic techniques considered having major potential for plant mineral analysis, such as chlorophyll a fluorescence, X-ray fluorescence (XRF and Laser-Induced Breakdown Spectroscopy (LIBS are also described.

Characterisation of PDO olive oil Chianti Classico by non-selective (UV–visible, NIR and MIR spectroscopy) and selective (fatty acid composition) analytical techniques

International Nuclear Information System (INIS)

Casale, M.; Oliveri, P.; Casolino, C.; Sinelli, N.; Zunin, P.; Armanino, C.; Forina, M.; Lanteri, S.

2012-01-01

Highlights: ► Characterisation of the Italian PDO extra virgin olive oil Chianti Classico. ► Comparison between non-selective (UV–vis, NIR and MIR spectroscopy) and selective (fatty acid composition) analytical techniques. ► Synergy among spectroscopic techniques, by the fusion of the respective spectra. ► Prediction of the content of oleic and linoleic acids in the olive oils. - Abstract: An authentication study of the Italian PDO (protected designation of origin) extra virgin olive oil Chianti Classico was performed; UV–visible (UV–vis), Near-Infrared (NIR) and Mid-Infrared (MIR) spectroscopies were applied to a set of samples representative of the whole Chianti Classico production area. The non-selective signals (fingerprints) provided by the three spectroscopic techniques were utilised both individually and jointly, after fusion of the respective profile vectors, in order to build a model for the Chianti Classico PDO olive oil. Moreover, these results were compared with those obtained by the gas chromatographic determination of the fatty acids composition. In order to characterise the olive oils produced in the Chianti Classico PDO area, UNEQ (unequal class models) and SIMCA (soft independent modelling of class analogy) were employed both on the MIR, NIR and UV–vis spectra, individually and jointly, and on the fatty acid composition. Finally, PLS (partial least square) regression was applied on the UV–vis, NIR and MIR spectra, in order to predict the content of oleic and linoleic acids in the extra virgin olive oils. UNEQ, SIMCA and PLS were performed after selection of the relevant predictors, in order to increase the efficiency of both classification and regression models. The non-selective information obtained from UV–vis, NIR and MIR spectroscopy allowed to build reliable models for checking the authenticity of the Italian PDO extra virgin olive oil Chianti Classico.

Characterisation of PDO olive oil Chianti Classico by non-selective (UV-visible, NIR and MIR spectroscopy) and selective (fatty acid composition) analytical techniques

Energy Technology Data Exchange (ETDEWEB)

Casale, M., E-mail: monica@dictfa.unige.it [Universita degli Studi di Genova, Department of Chemistry and Food and Pharmaceutical Technologies, Via Brigata Salerno 13, I-16147, Genoa (Italy); Oliveri, P.; Casolino, C. [Universita degli Studi di Genova, Department of Chemistry and Food and Pharmaceutical Technologies, Via Brigata Salerno 13, I-16147, Genoa (Italy); Sinelli, N. [Universita degli Studi di Milano, Department of Food Science and Technology, Via Celoria, 2 - I-20133 Milan (Italy); Zunin, P.; Armanino, C.; Forina, M.; Lanteri, S. [Universita degli Studi di Genova, Department of Chemistry and Food and Pharmaceutical Technologies, Via Brigata Salerno 13, I-16147, Genoa (Italy)

2012-01-27

Highlights: Black-Right-Pointing-Pointer Characterisation of the Italian PDO extra virgin olive oil Chianti Classico. Black-Right-Pointing-Pointer Comparison between non-selective (UV-vis, NIR and MIR spectroscopy) and selective (fatty acid composition) analytical techniques. Black-Right-Pointing-Pointer Synergy among spectroscopic techniques, by the fusion of the respective spectra. Black-Right-Pointing-Pointer Prediction of the content of oleic and linoleic acids in the olive oils. - Abstract: An authentication study of the Italian PDO (protected designation of origin) extra virgin olive oil Chianti Classico was performed; UV-visible (UV-vis), Near-Infrared (NIR) and Mid-Infrared (MIR) spectroscopies were applied to a set of samples representative of the whole Chianti Classico production area. The non-selective signals (fingerprints) provided by the three spectroscopic techniques were utilised both individually and jointly, after fusion of the respective profile vectors, in order to build a model for the Chianti Classico PDO olive oil. Moreover, these results were compared with those obtained by the gas chromatographic determination of the fatty acids composition. In order to characterise the olive oils produced in the Chianti Classico PDO area, UNEQ (unequal class models) and SIMCA (soft independent modelling of class analogy) were employed both on the MIR, NIR and UV-vis spectra, individually and jointly, and on the fatty acid composition. Finally, PLS (partial least square) regression was applied on the UV-vis, NIR and MIR spectra, in order to predict the content of oleic and linoleic acids in the extra virgin olive oils. UNEQ, SIMCA and PLS were performed after selection of the relevant predictors, in order to increase the efficiency of both classification and regression models. The non-selective information obtained from UV-vis, NIR and MIR spectroscopy allowed to build reliable models for checking the authenticity of the Italian PDO extra virgin olive oil

Rheo-optical two-dimensional (2D) near-infrared (NIR) correlation spectroscopy for probing strain-induced molecular chain deformation of annealed and quenched Nylon 6 films

Science.gov (United States)

Shinzawa, Hideyuki; Mizukado, Junji

2018-04-01

A rheo-optical characterization technique based on the combination of a near-infrared (NIR) spectrometer and a tensile testing machine is presented here. In the rheo-optical NIR spectroscopy, tensile deformations are applied to polymers to induce displacement of ordered or disordered molecular chains. The molecular-level variation of the sample occurring on short time scales is readily captured as a form of strain-dependent NIR spectra by taking an advantage of an acousto-optic tunable filter (AOTF) equipped with the NIR spectrometer. In addition, the utilization of NIR with much less intense absorption makes it possible to measure transmittance spectra of relatively thick samples which are often required for conventional tensile testing. An illustrative example of the rheo-optical technique is given with annealed and quenched Nylon 6 samples to show how this technique can be utilized to derive more penetrating insight even from the seemingly simple polymers. The analysis of the sets of strain-dependent NIR spectra suggests the presence of polymer structures undergoing different variations during the tensile elongation. For instance, the tensile deformation of the semi-crystalline Nylon 6 involves a separate step of elongation of the rubbery amorphous chains and subsequent disintegration of the rigid crystalline structure. Excess amount of crystalline phase in Nylon 6, however, results in the retardation of the elastic deformation mainly achieved by the amorphous structure, which eventually leads to the simultaneous orientation of both amorphous and crystalline structures.

Multivariate NIR studies of seed-water interaction in Scots Pine Seeds (Pinus sylvestris L.)

OpenAIRE

Lestander, Torbjörn

2003-01-01

This thesis describes seed-water interaction using near infrared (NIR) spectroscopy, multivariate regression models and Scots pine seeds. The presented research covers classification of seed viability, prediction of seed moisture content, selection of NIR wavelengths and interpretation of seed-water interaction modelled and analysed by principal component analysis, ordinary least squares (OLS), partial least squares (PLS), bi-orthogonal least squares (BPLS) and genetic algorithms. The potenti...

A Near Infrared Spectroscopy (NIRS) and Chemometric Approach to Improve Apple Fruit Quality Management: A Case Study on the Cultivars "Cripps Pink" and "Braeburn".

Science.gov (United States)

Eisenstecken, Daniela; Panarese, Alessia; Robatscher, Peter; Huck, Christian W; Zanella, Angelo; Oberhuber, Michael

2015-07-24

The potential of near infrared spectroscopy (NIRS) in the wavelength range of 1000-2500 nm for predicting quality parameters such as total soluble solids (TSS), acidity (TA), firmness, and individual sugars (glucose, fructose, sucrose, and xylose) for two cultivars of apples ("Braeburn" and "Cripps Pink") was studied during the pre- and post-storage periods. Simultaneously, a qualitative investigation on the capability of NIRS to discriminate varieties, harvest dates, storage periods and fruit inhomogeneity was carried out. In order to generate a sample set with high variability within the most relevant apple quality traits, three different harvest time points in combination with five different storage periods were chosen, and the evolution of important quality parameters was followed both with NIRS and wet chemical methods. By applying a principal component analysis (PCA) a differentiation between the two cultivars, freshly harvested vs. long-term stored apples and, notably, between the sun-exposed vs. shaded side of apples could be found. For the determination of quality parameters effective prediction models for titratable acid (TA) and individual sugars such as fructose, glucose and sucrose by using partial least square (PLS) regression have been developed. Our results complement earlier reports, highlighting the versatility of NIRS as a fast, non-invasive method for quantitative and qualitative studies on apples.

On-chip integrated functional near infra-red spectroscopy (fNIRS) photoreceiver for portable brain imaging

Science.gov (United States)

Kamrani, Ehsan

Optical brain imaging using functional near infra-red spectroscopy (fNIRS) offers a direct and noninvasive tool for monitoring of blood oxygenation. fNIRS is a noninvasive, safe, minimally intrusive, and high temporal-resolution technique for real-time and long-term brain imaging. It allows detecting both fast-neuronal and slow-hemodynamic signals. Besides the significant advantages of fNIRS systems, they still suffer from few drawbacks including low spatial-resolution, moderately high-level noise and high-sensitivity to movement. In order to overcome the limitations of currently available non-portable fNIRS systems, we have introduced a new low-power, miniaturized on-chip photodetector front-end intended for portable fNIRS systems. It includes silicon avalanche photodiode (SiAPD), Transimpedance amplifier (TIA), and Quench- Reset circuitry implemented using standard CMOS technologies to operate in both linear and Geiger modes. So it can be applied for both continuous-wave fNIRS (CW-fNIRS) and also single-photon counting applications. Several SiAPDs have been implemented in novel structures and shapes (Rectangular, Octagonal, Dual, Nested, Netted, Quadratic and Hexadecagonal) using different premature edge breakdown prevention techniques. The main characteristics of the SiAPDs are validated and the impact of each parameter and the device simulators (TCAD, COMSOL, etc.) have been studied based on the simulation and measurement results. Proposed techniques exhibit SiAPDs with high avalanche-gain (up to 119), low breakdown-voltage (around 12V) and high photon-detection efficiency (up to 72% in NIR region) in additional to a low dark-count rate (down to 30Hz at 1V excess bias voltage). Three new high gain-bandwidth product (GBW) and low-noise TIAs are introduced and implemented based on distributed-gain concept, logarithmic-amplification and automatic noise-rejection and have been applied in linear-mode of operation. The implemented TIAs offer a power

Rapid differentiation of Ghana cocoa beans by FT-NIR spectroscopy coupled with multivariate classification

Science.gov (United States)

Teye, Ernest; Huang, Xingyi; Dai, Huang; Chen, Quansheng

2013-10-01

Quick, accurate and reliable technique for discrimination of cocoa beans according to geographical origin is essential for quality control and traceability management. This current study presents the application of Near Infrared Spectroscopy technique and multivariate classification for the differentiation of Ghana cocoa beans. A total of 194 cocoa bean samples from seven cocoa growing regions were used. Principal component analysis (PCA) was used to extract relevant information from the spectral data and this gave visible cluster trends. The performance of four multivariate classification methods: Linear discriminant analysis (LDA), K-nearest neighbors (KNN), Back propagation artificial neural network (BPANN) and Support vector machine (SVM) were compared. The performances of the models were optimized by cross validation. The results revealed that; SVM model was superior to all the mathematical methods with a discrimination rate of 100% in both the training and prediction set after preprocessing with Mean centering (MC). BPANN had a discrimination rate of 99.23% for the training set and 96.88% for prediction set. While LDA model had 96.15% and 90.63% for the training and prediction sets respectively. KNN model had 75.01% for the training set and 72.31% for prediction set. The non-linear classification methods used were superior to the linear ones. Generally, the results revealed that NIR Spectroscopy coupled with SVM model could be used successfully to discriminate cocoa beans according to their geographical origins for effective quality assurance.

[NIR and XRD analysis of drill-hole samples from Zhamuaobao iron-graphite deposit, Inner Mongolia].

Science.gov (United States)

Li, Ying-kui; Cao, Jian-jin; Wu, Zheng-quan; Dai, Dong-le; Lin, Zu-xu

2015-01-01

The author analyzed the 4202 drill-hole samples from Zhamuaobao iron-graphite deposit by using near infrared spectroscopy(NIR) and X-ray diffraction(XRD) measuring and testing techniques, and then compared and summarized the results of two kinds of testing technology. The results indicate that some difference of the mineral composition exists among different layers, the lithology from upper to deeper is the clay gravel layer of tertiary and quaternary, mudstone, mica quartz schist, quartz actinolite scarn, skarnization marble, iron ore deposits, graphite deposits and mica quartz schist. The petrogenesis in different depth also shows difference, which may indicate the geological characteristic to some extent. The samples had mainly undergone such processes as oxidization, carbonation, chloritization and skarn alteration. The research results can not only improve the geological feature of the mining area, but also have great importance in ore exploration, mining, mineral processing and so on. What's more, as XRD can provide preliminary information about the mineral composition, NIR can make further judgement on the existence of the minerals. The research integrated the advantages of both NIR and XRD measuring and testing techniques, put forward a method with two kinds of modern testing technology combined with each other, which may improve the accuracy of the mineral composition identification. In the meantime, the NIR will be more wildly used in geography on the basis of mineral spectroscopy.

Espectroscopía NIR como Técnica Exploratoria Rápida para Detección de Amarillamiento Hojas Crisantemo (Dendranthema grandiflora var. Zembla / NIR Spectroscopy as Quick Exploratory Technique for Detection of Chrysanthemum Leaf Yellowing (Dendranthema

Directory of Open Access Journals (Sweden)

Juan Carlos Pérez Naranjo

2014-03-01

. Spectral NIR data from intact leaves showing different levels of yellowing (healthy leaves, slightly deformed leaves or highly deformed leaves with advanced yellowing, used in conjunction with multivariate statistical analysis of NIR spectra, were used to build a descriptive model for chrysanthemum leaf yellowing classification. The descriptive model indicated the presence of two groups of NIR spectra belonging to asymptomatic or symptomatic leaves, with no further differentiation of NIR spectra from leaves showing mild or severe yellowing symptoms. Not without the drawbacks of a low number of NIR spectra, these results suggests that it is possible to develop a fast, accurate and nondestructive, spectroscopic based system to detect this disease on blind plant samples. Improvements to the sensitivity of this model in detecting multiple stages of this disease will depend on obtaining and adding new NIR leaf spectra obtained from clearly defined ratings of the disease. Due to its sensitivity and wide application, NIR spectroscopy appear to be a core technique to further develop new systems for the early detection of chrysanthemum leaf yellowing and other plant diseases. This in turn may result in the design of opportune and timely systems for plant disease control.

A novel in-line NIR spectroscopy application for the monitoring of tablet film coating in an industrial scale process.

Science.gov (United States)

Möltgen, C-V; Puchert, T; Menezes, J C; Lochmann, D; Reich, G

2012-04-15

Film coating of tablets is a multivariate pharmaceutical unit operation. In this study an innovative in-line Fourier-Transform Near-Infrared Spectroscopy (FT-NIRS) application is described which enables real-time monitoring of a full industrial scale pan coating process of heart-shaped tablets. The tablets were coated with a thin hydroxypropyl methylcellulose (HPMC) film of up to approx. 28 μm on the tablet face as determined by SEM, corresponding to a weight gain of 2.26%. For a better understanding of the aqueous coating process the NIR probe was positioned inside the rotating tablet bed. Five full scale experimental runs have been performed to evaluate the impact of process variables such as pan rotation, exhaust air temperature, spray rate and pan load and elaborate robust and selective quantitative calibration models for the real-time determination of both coating growth and tablet moisture content. Principal Component (PC) score plots allowed each coating step, namely preheating, spraying and drying to be distinguished and the dominating factors and their spectral effects to be identified (e.g. temperature, moisture, coating growth, change of tablet bed density, and core/coat interactions). The distinct separation of HPMC coating growth and tablet moisture in different PCs enabled a real-time in-line monitoring of both attributes. A PLS calibration model based on Karl Fischer reference values allowed the tablet moisture trajectory to be determined throughout the entire coating process. A 1-latent variable iPLS weight gain calibration model with calibration samples from process stages dominated by the coating growth (i.e. ≥ 30% of the theoretically applied amount of coating) was sufficiently selective and accurate to predict the progress of the thin HPMC coating layer. At-line NIR Chemical Imaging (NIR-CI) in combination with PLS Discriminant Analysis (PLSDA) verified the HPMC coating growth and physical changes at the core/coat interface during the initial

Brain activity underlying the recovery of meaning from degraded speech: A functional near-infrared spectroscopy (fNIRS) study.

Science.gov (United States)

Wijayasiri, Pramudi; Hartley, Douglas E H; Wiggins, Ian M

2017-08-01

The purpose of this study was to establish whether functional near-infrared spectroscopy (fNIRS), an emerging brain-imaging technique based on optical principles, is suitable for studying the brain activity that underlies effortful listening. In an event-related fNIRS experiment, normally-hearing adults listened to sentences that were either clear or degraded (noise vocoded). These sentences were presented simultaneously with a non-speech distractor, and on each trial participants were instructed to attend either to the speech or to the distractor. The primary region of interest for the fNIRS measurements was the left inferior frontal gyrus (LIFG), a cortical region involved in higher-order language processing. The fNIRS results confirmed findings previously reported in the functional magnetic resonance imaging (fMRI) literature. Firstly, the LIFG exhibited an elevated response to degraded versus clear speech, but only when attention was directed towards the speech. This attention-dependent increase in frontal brain activation may be a neural marker for effortful listening. Secondly, during attentive listening to degraded speech, the haemodynamic response peaked significantly later in the LIFG than in superior temporal cortex, possibly reflecting the engagement of working memory to help reconstruct the meaning of degraded sentences. The homologous region in the right hemisphere may play an equivalent role to the LIFG in some left-handed individuals. In conclusion, fNIRS holds promise as a flexible tool to examine the neural signature of effortful listening. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative analysis of bayberry juice acidity based on visible and near-infrared spectroscopy

International Nuclear Information System (INIS)

Shao Yongni; He Yong; Mao Jingyuan

2007-01-01

Visible and near-infrared (Vis/NIR) reflectance spectroscopy has been investigated for its ability to nondestructively detect acidity in bayberry juice. What we believe to be a new, better mathematic model is put forward, which we have named principal component analysis-stepwise regression analysis-backpropagation neural network (PCA-SRA-BPNN), to build a correlation between the spectral reflectivity data and the acidity of bayberry juice. In this model, the optimum network parameters,such as the number of input nodes, hidden nodes, learning rate, and momentum, are chosen by the value of root-mean-square (rms) error. The results show that its prediction statistical parameters are correlation coefficient (r) of 0.9451 and root-mean-square error of prediction(RMSEP) of 0.1168. Partial least-squares (PLS) regression is also established to compare with this model. Before doing this, the influences of various spectral pretreatments (standard normal variate, multiplicative scatter correction, S. Golay first derivative, and wavelet package transform) are compared. The PLS approach with wavelet package transform preprocessing spectra is found to provide the best results, and its prediction statistical parameters are correlation coefficient (r) of 0.9061 and RMSEP of 0.1564. Hence, these two models are both desirable to analyze the data from Vis/NIR spectroscopy and to solve the problem of the acidity prediction of bayberry juice. This supplies basal research to ultimately realize the online measurements of the juice's internal quality through this Vis/NIR spectroscopy technique

NIRS in Space?

Science.gov (United States)

Peterson, David L.; Condon, Estelle (Technical Monitor)

2000-01-01

Proponents of near infrared reflectance spectroscopy (NIRS) have been exceptionally successful in applying NIRS techniques to many instances of organic material analyses. While this research and development began in the 1950s, in recent years, stimulation of advancements in instrumentation is allowing NIRS to begin to find its way into the food processing systems, into food quality and safety, textiles and much more. And, imaging high spectral resolution spectrometers are now being evaluated for the rapid scanning of foodstuffs, such as the inspection of whole chicken carcasses for fecal contamination. The imaging methods are also finding their way into medical applications, such as the non-intrusive monitoring of blood oxygenation in newborns. Can these scientific insights also be taken into space and successfully used to measure the Earth's condition? Is there an analog between the organic analyses in the laboratory and clinical settings and the study of Earth's living biosphere? How are the methods comparable and how do they differ?

Possible Influences on the Interpretation of Functional Domain (FD) Near-Infrared Spectroscopy (NIRS): An Explorative Study.

Science.gov (United States)

Celie, Bert M; Boone, Jan; Dumortier, Jasmien; Derave, Wim; De Backer, Tine; Bourgois, Jan G

2016-02-01

The influence of subcutaneous adipose tissue (ATT) and oxygen (O2) delivery has been poorly defined in frequency domain (FD) near-infrared spectroscopy (NIRS). Therefore, the aim of this study was to investigate the possible influence of these variables on all FD NIRS responses using a reliable protocol. Moreover, these influences were also investigated when using relative oxy- and deoxyhemoglobin and -myoglobin (oxy[Hb + Mb] and deoxy[Hb + Mb]) values (in %). A regression analysis was carried out for ATT and maximal-minimum oxy[Hb + Mb], deoxy[Hb + Mb], oxygen saturation (SmO2), and total hemoglobin (totHb) amplitudes during an incremental cyclic contraction protocol (ICCP) in a group of 45 participants. Moreover, the same analysis was carried out between subcutaneous ATT and the relative oxy- and deoxy[Hb + Mb] values (in %). In the second part of this study, a regression analysis was performed for peak forearm blood flow (FBF) during ICCP and the absolute and relative NIRS values in a group of 37 participants. Significant exponential correlation coefficients were found between ATT and deoxy[Hb + Mb] (r = 0.53; P < 0.001), oxy[Hb + Mb] (r = 0.57; P < 0.001), and SmO2 amplitudes (r = 0.57; P < 0.001). No significant relations were found between ATT and relative oxy[Hb + Mb] (r = 0.37; P = 0.07) and deoxy[Hb + Mb] (r = 0.09; P = 0.82). Significant positive correlation coefficients were found between force at exhaustion and maximal FBF (r = 0.66; P < 0.001), maximal differences in deoxy[Hb + Mb] (r = 0.353; P = 0.032) and totHb (r = 0.512; P = 0.002) while no significant correlation coefficients were found between these maximal force values and maximal differences in oxy[Hb + Mb] (r = -0.267; P = 0.111) and SmO2 (r = -0.267; P = 0.111). Significant linear correlation coefficients were found between FBF and deoxy[Hb + Mb] (r = 0.51; P�

Advances in R&D in near-infrared spectroscopy in Japan

Science.gov (United States)

Kawano, Sumio; Iwamoto, Mutsuo

1991-02-01

More than 20 years ago when Mr. K. H. Norris firstly introduced the near infrared spectroscopy (NIRS) as a powerful technology in the field of composition analysis of cereals those who were interested in the area of classical spectroscopy would not like to recognize its potential. This tendency still remains at present however it leaves no room for doubt that from viewpoints of applied spectroscopy the NIRS has consolidated its position. From a viewpoint of NIRS application in the field of nondestructive or non invasive measuring techniques history of this technology is only the last decade in Japan. However since the technology was firstly introduced to composition analysis of agricultural commodities in the same manner as in other countries R and D have been growing more actively in diversified fields such as agriculture and industry as well as medical science. In addition the NIRS technology are becoming of general interest by combining other techniques to create various hyphenated instrumentations such as FTNIR MCFTNIR NIRCT and NIR-NMR. In this paper new trends of R D on NIR spectroscopy which are being conducted in Japan will be reviewed. 2. S1JMMARY OF PRESENT R D ON NIRS IN JAPAN NIRS applications reported in the last 3 years are summarized in Table 1. Table 1 Applications of NIRS in Japan Application for Agriculture Taste evaluation of rice and coffee Determination of chemical compositions rice for breeding Determination of chemical compositions in tea Determination of sugar contents in intact peaches Japanese pears Satsuma oranges and apples Determination of sugars and acids in intact tomatoes Determination of forage composition Application for Industry Analysis of state of water in foods Application of analyzing Maillard Reaction''s Process Pattern recognition of NIR spectra as related to process control of roasting coffee beans Quality control of tea processing Determination of moisture content of Surimi products 2 / SPIE Vol. 1379 Optics in Agriculture

Near-infrared-excited confocal Raman spectroscopy advances in vivo diagnosis of cervical precancer.

Science.gov (United States)

Duraipandian, Shiyamala; Zheng, Wei; Ng, Joseph; Low, Jeffrey J H; Ilancheran, Arunachalam; Huang, Zhiwei

2013-06-01

Raman spectroscopy is a unique optical technique that can probe the changes of vibrational modes of biomolecules associated with tissue premalignant transformation. This study evaluates the clinical utility of confocal Raman spectroscopy over near-infrared (NIR) autofluorescence (AF) spectroscopy and composite NIR AF/Raman spectroscopy for improving early diagnosis of cervical precancer in vivo at colposcopy. A rapid NIR Raman system coupled with a ball-lens fiber-optic confocal Raman probe was utilized for in vivo NIR AF/Raman spectral measurements of the cervix. A total of 1240 in vivo Raman spectra [normal (n=993), dysplasia (n=247)] were acquired from 84 cervical patients. Principal components analysis (PCA) and linear discriminant analysis (LDA) together with a leave-one-patient-out, cross-validation method were used to extract the diagnostic information associated with distinctive spectroscopic modalities. The diagnostic ability of confocal Raman spectroscopy was evaluated using the PCA-LDA model developed from the significant principal components (PCs) [i.e., PC4, 0.0023%; PC5, 0.00095%; PC8, 0.00022%, (p<0.05)], representing the primary tissue Raman features (e.g., 854, 937, 1095, 1253, 1311, 1445, and 1654 cm(-1)). Confocal Raman spectroscopy coupled with PCA-LDA modeling yielded the diagnostic accuracy of 84.1% (a sensitivity of 81.0% and a specificity of 87.1%) for in vivo discrimination of dysplastic cervix. The receiver operating characteristic curves further confirmed that the best classification was achieved using confocal Raman spectroscopy compared to the composite NIR AF/Raman spectroscopy or NIR AF spectroscopy alone. This study illustrates that confocal Raman spectroscopy has great potential to improve early diagnosis of cervical precancer in vivo during clinical colposcopy.

Decoding vigilance with NIRS.

Science.gov (United States)

Bogler, Carsten; Mehnert, Jan; Steinbrink, Jens; Haynes, John-Dylan

2014-01-01

Sustained, long-term cognitive workload is associated with variations and decrements in performance. Such fluctuations in vigilance can be a risk factor especially during dangerous attention demanding activities. Functional MRI studies have shown that attentional performance is correlated with BOLD-signals, especially in parietal and prefrontal cortical regions. An interesting question is whether these BOLD-signals could be measured in real-world scenarios, say to warn in a dangerous workplace whenever a subjects' vigilance is low. Because fMRI lacks the mobility needed for such applications, we tested whether the monitoring of vigilance might be possible using Near-Infrared Spectroscopy (NIRS). NIRS is a highly mobile technique that measures hemodynamics in the surface of the brain. We demonstrate that non-invasive NIRS signals correlate with vigilance. These signals carry enough information to decode subjects' reaction times at a single trial level.

NIR and Py-mbms coupled with multivariate data analysis as a high-throughput biomass characterization technique : a review

Directory of Open Access Journals (Sweden)

Li eXiao

2014-08-01

Full Text Available Optimizing the use of lignocellulosic biomass as the feedstock for renewable energy production is currently being developed globally. Biomass is a complex mixture of cellulose, hemicelluloses, lignins, extractives, and proteins; as well as inorganic salts. Cell wall compositional analysis for biomass characterization is laborious and time consuming. In order to characterize biomass fast and efficiently, several high through-put technologies have been successfully developed. Among them, near infrared spectroscopy (NIR and pyrolysis-molecular beam mass spectrometry (Py-mbms are complementary tools and capable of evaluating a large number of raw or modified biomass in a short period of time. NIR shows vibrations associated with specific chemical structures whereas Py-mbms depicts the full range of fragments from the decomposition of biomass. Both NIR vibrations and Py-mbms peaks are assigned to possible chemical functional groups and molecular structures. They provide complementary information of chemical insight of biomaterials. However, it is challenging to interpret the informative results because of the large amount of overlapping bands or decomposition fragments contained in the spectra. In order to improve the efficiency of data analysis, multivariate analysis tools have been adapted to define the significant correlations among data variables, so that the large number of bands/peaks could be replaced by a small number of reconstructed variables representing original variation. Reconstructed data variables are used for sample comparison (principal component analysis and for building regression models (partial least square regression between biomass chemical structures and properties of interests. In this review, the important biomass chemical structures measured by NIR and Py-mbms are summarized. The advantages and disadvantages of conventional data analysis methods and multivariate data analysis methods are introduced, compared and evaluated

[Application of near-infrared spectroscopy in golf turfgrass management].

Science.gov (United States)

Li, Shu-Ying; Han, Jian-Guo

2008-07-01

The management of golf course is different from other turfs. Its particularity lies in its higher and more precise requirement during maintenance compare with other turfs. In case something happened to turf of golf course, more effective and higher speed detecting and resolution are required. Only the data about turf growth and environment were mastered precisely in time, the friendly environmental and scientific management goal could be completed effectively and economically. The near infrared spectroscopy is a new kind of effective, convenient and non-destructive analytical method in the turfgrass management of golf course in recent years. Many factors of turf-soil system in golf course could be determined by near infrared spectroscopy at the same time. In this paper, the existing literature that use of near infrared spectroscopy to study turfgrass and soil nutrient content, soil hygroscopic moisture, feasible fertilizer application time and rate, to fix the time and volume of irrigation, turfgrass visual quality evaluation, turfgrass disease prediction and prevention were reviewed. Most researchers considered the nutrition condition of turf impacted the visual and playing quality of golf course directly and then indirectly influenced most of assistant cultivation such as fertilization, mowing and irrigation and so on. The using of NIRS can detect the nutrient content of turfgrass effectively and estimate the nutrient is excessive or deficient quickly. And then the feasible time and rate of fertilizers can be decided. Comparing with the common judgment ways based on the season fertilization and visual estimation, the using of NIRS can reduce the application of fertilizers on the base of keeping the same turf quality simultaneously. NIRS can analysis many items of soil such as moisture, elements concentration, textures on the spot by the thousands. This method can get lots of cover-all data non-destructively. What's more, NIRS can analysis soil betimes quickly

Near infrared spectroscopy in the development of solid dosage forms.

Science.gov (United States)

Räsänen, Eetu; Sandler, Niklas

2007-02-01

The use of near infrared (NIR) spectroscopy has rapidly grown partly due to demands of process analytical applications in the pharmaceutical industry. Furthermore, newest regulatory guidelines have advanced the increase of the use of NIR technologies. The non-destructive and non-invasive nature of measurements makes NIR a powerful tool in characterization of pharmaceutical solids. These benefits among others often make NIR advantageous over traditional analytical methods. However, in addition to NIR, a wide variety of other tools are naturally also available for analysis in pharmaceutical development and manufacturing, and those can often be more suitable for a given application. The versatility and rapidness of NIR will ensure its contribution to increased process understanding, better process control and improved quality of drug products. This review concentrates on the use of NIR spectroscopy from a process research perspective and highlights recent applications in the field.

On-line prediction of chemical composition of semi-frozen ground beef by non-invasive NIR spectroscopy.

Science.gov (United States)

Tøgersen, G; Arnesen, J F; Nilsen, B N; Hildrum, K I

2003-04-01

The chemical composition of industrial scale batches of frozen beef was measured on-line during grinding by near infrared (NIR) reflectance spectroscopy. The MM55E filter based non-contact NIR instrument was mounted at the outlet of a meat grinder, and the fat, moisture and protein contents determined from the average of each filter reading throughout the grinding of the batch. The filters were selected from full spectra measurements to be as insensitive to water crystallization as possible. For on-line calibration and prediction, 55 beef batches of 400-800 kg in the range of 7.66-22.91% fat, 59.36-71.48% moisture, and 17.04-20.76% protein, were ground through 4 or 13 mm hole plates. The regression results, presented as root mean square error of cross validation (RMSECV) were between 0.48 and 1.11% for fat, 0.43 and 0.97% for moisture and 0.41 and 0.47% for protein.

Decoding vigilance with NIRS.

Directory of Open Access Journals (Sweden)

Carsten Bogler

Full Text Available Sustained, long-term cognitive workload is associated with variations and decrements in performance. Such fluctuations in vigilance can be a risk factor especially during dangerous attention demanding activities. Functional MRI studies have shown that attentional performance is correlated with BOLD-signals, especially in parietal and prefrontal cortical regions. An interesting question is whether these BOLD-signals could be measured in real-world scenarios, say to warn in a dangerous workplace whenever a subjects' vigilance is low. Because fMRI lacks the mobility needed for such applications, we tested whether the monitoring of vigilance might be possible using Near-Infrared Spectroscopy (NIRS. NIRS is a highly mobile technique that measures hemodynamics in the surface of the brain. We demonstrate that non-invasive NIRS signals correlate with vigilance. These signals carry enough information to decode subjects' reaction times at a single trial level.

Hemodynamic Response to Interictal Epileptiform Discharges Addressed by Personalized EEG-fNIRS Recordings

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Pellegrino, Giovanni; Machado, Alexis; von Ellenrieder, Nicolas; Watanabe, Satsuki; Hall, Jeffery A.; Lina, Jean-Marc; Kobayashi, Eliane; Grova, Christophe

2016-01-01

Objective: We aimed at studying the hemodynamic response (HR) to Interictal Epileptic Discharges (IEDs) using patient-specific and prolonged simultaneous ElectroEncephaloGraphy (EEG) and functional Near InfraRed Spectroscopy (fNIRS) recordings. Methods: The epileptic generator was localized using Magnetoencephalography source imaging. fNIRS montage was tailored for each patient, using an algorithm to optimize the sensitivity to the epileptic generator. Optodes were glued using collodion to achieve prolonged acquisition with high quality signal. fNIRS data analysis was handled with no a priori constraint on HR time course, averaging fNIRS signals to similar IEDs. Cluster-permutation analysis was performed on 3D reconstructed fNIRS data to identify significant spatio-temporal HR clusters. Standard (GLM with fixed HRF) and cluster-permutation EEG-fMRI analyses were performed for comparison purposes. Results: fNIRS detected HR to IEDs for 8/9 patients. It mainly consisted oxy-hemoglobin increases (seven patients), followed by oxy-hemoglobin decreases (six patients). HR was lateralized in six patients and lasted from 8.5 to 30 s. Standard EEG-fMRI analysis detected an HR in 4/9 patients (4/9 without enough IEDs, 1/9 unreliable result). The cluster-permutation EEG-fMRI analysis restricted to the region investigated by fNIRS showed additional strong and non-canonical BOLD responses starting earlier than the IEDs and lasting up to 30 s. Conclusions: (i) EEG-fNIRS is suitable to detect the HR to IEDs and can outperform EEG-fMRI because of prolonged recordings and greater chance to detect IEDs; (ii) cluster-permutation analysis unveils additional HR features underestimated when imposing a canonical HR function (iii) the HR is often bilateral and lasts up to 30 s. PMID:27047325

Hemodynamic response to Interictal Epileptiform Discharges addressed by personalized EEG-fNIRS recordings

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Giovanni ePellegrino

2016-03-01

Full Text Available Objective: We aimed at studying the hemodynamic response (HR to Interictal Epileptic Discharges (IEDs using patient-specific and prolonged simultaneous ElectroEncephaloGraphy (EEG and functional Near InfraRed Spectroscopy (fNIRS recordings. Methods: The epileptic generator was localized using Magnetoencephalography source imaging. fNIRS montage was tailored for each patient, using an algorithm to optimize the sensitivity to the epileptic generator. Optodes were glued using collodion to achieve prolonged acquisition with high quality signal. fNIRS data analysis was handled with no a priori constraint on HR time course, averaging fNIRS signals to similar IEDs. Cluster-permutation analysis was performed on 3D reconstructed fNIRS data to identify significant spatio-temporal HR clusters. Standard (GLM with fixed HRF and cluster-permutation EEG-fMRI analyses were performed for comparison purposes. Results: fNIRS detected HR to IEDs for 8/9 patients. It mainly consisted oxy-hemoglobin increases (7 patients, followed by oxy-hemoglobin decreases (6 patients. HR was lateralized in 6 patients and lasted from 8.5 to 30s. Standard EEG-fMRI analysis detected an HR in 4/9 patients (4/9 without enough IEDs, 1/9 unreliable result. The cluster-permutation EEG-fMRI analysis restricted to the region investigated by fNIRS showed additional strong and non-canonical BOLD responses starting earlier than the IEDs and lasting up to 30s. Conclusions: i EEG-fNIRS is suitable to detect the HR to IEDs and can outperform EEG-fMRI because of prolonged recordings and greater chance to detect IEDs; ii cluster-permutation analysis unveils additional HR features underestimated when imposing a canonical HR function iii the HR is often bilateral and lasts up to 30s.

Probing the Behaviors of Gold Nanorods in Metastatic Breast Cancer Cells Based on UV-vis-NIR Absorption Spectroscopy

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Zhang, Weiqi; Ji, Yinglu; Meng, Jie; Wu, Xiaochun; Xu, Haiyan

2012-01-01

In this work, behaviors of positively-charged AuNRs in a highly metastatic tumor cell line MDA-MB-231 are examined based on UV-vis-NIR absorption spectroscopy in combination with inductively coupled plasma mass spectrometry (ICP-MS), transmission electron microscopy (TEM) and dark-field microscopic observation. It is found that characteristic surface plasmon resonance (SPR) peaks of AuNRs can be detected using spectroscopic method within living cells that have taken up AuNRs. The peak area of transverse SPR band is shown to be proportionally related to the amount of AuNRs in the cells determined with ICP-MS, which suggests a facile and real time quantification method for AuNRs in living cells. The shape of longitudinal SPR band in UV-vis-NIR spectrum reflects the aggregation state of AuNRs in the cells during the incubation period, which is proved by TEM and microscopic observations. Experimental results reveal that AuNRs are internalized by the cells rapidly; the accumulation, distribution and aggregation of AuNRs in the cells compartments are time and dose dependent. The established spectroscopic analysis method can not only monitor the behaviors of AuNRs in living cells but may also be helpful in choosing the optimum laser stimulation wavelength for anti-tumor thermotherapy. PMID:22384113

FT-NIR: A Tool for Process Monitoring and More.

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Martoccia, Domenico; Lutz, Holger; Cohen, Yvan; Jerphagnon, Thomas; Jenelten, Urban

2018-03-30

With ever-increasing pressure to optimize product quality, to reduce cost and to safely increase production output from existing assets, all combined with regular changes in terms of feedstock and operational targets, process monitoring with traditional instruments reaches its limits. One promising answer to these challenges is in-line, real time process analysis with spectroscopic instruments, and above all Fourier-Transform Near Infrared spectroscopy (FT-NIR). Its potential to afford decreased batch cycle times, higher yields, reduced rework and minimized batch variance is presented and application examples in the field of fine chemicals are given. We demonstrate that FT-NIR can be an efficient tool for improved process monitoring and optimization, effective process design and advanced process control.

Analyzing Brain Functions by Subject Classification of Functional Near-Infrared Spectroscopy Data Using Convolutional Neural Networks Analysis

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Satoru Hiwa

2016-01-01

Full Text Available Functional near-infrared spectroscopy (fNIRS is suitable for noninvasive mapping of relative changes in regional cortical activity but is limited for quantitative comparisons among cortical sites, subjects, and populations. We have developed a convolutional neural network (CNN analysis method that learns feature vectors for accurate identification of group differences in fNIRS responses. In this study, subject gender was classified using CNN analysis of fNIRS data. fNIRS data were acquired from male and female subjects during a visual number memory task performed in a white noise environment because previous studies had revealed that the pattern of cortical blood flow during the task differed between males and females. A learned classifier accurately distinguished males from females based on distinct fNIRS signals from regions of interest (ROI including the inferior frontal gyrus and premotor areas that were identified by the learning algorithm. These cortical regions are associated with memory storage, attention, and task motor response. The accuracy of the classifier suggests stable gender-based differences in cerebral blood flow during this task. The proposed CNN analysis method can objectively identify ROIs using fNIRS time series data for machine learning to distinguish features between groups.

Estimating Soil Organic Carbon of Cropland Soil at Different Levels of Soil Moisture Using VIS-NIR Spectroscopy

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Qinghu Jiang

2016-09-01

Full Text Available Soil organic carbon (SOC is an essential property for soil function, fertility and sustainability of agricultural systems. It can be measured with visible and near-infrared reflectance (VIS-NIR spectroscopy efficiently based on empirical equations and spectra data for air/oven-dried samples. However, the spectral signal is interfered with by soil moisture content (MC under in situ conditions, which will affect the accuracy of measurements and calibration transfer among different areas. This study aimed to (1 quantify the influences of MC on SOC prediction by VIS-NIR spectroscopy; and (2 explore the potentials of orthogonal signal correction (OSC and generalized least squares weighting (GLSW methods in the removal of moisture interference. Ninety-eight samples were collected from the Jianghan plain, China, and eight MCs were obtained for each sample by a rewetting process. The VIS-NIR spectra of the rewetted soil samples were measured in the laboratory. Partial least squares regression (PLSR was used to develop SOC prediction models. Specifically, three validation strategies, namely moisture level validation, transferability validation and mixed-moisture validation, were designed to test the potentials of OSC and GLSW in removing the MC effect. Results showed that all of the PLSR models generated at different moisture levels (e.g., 50–100, 250–300 g·kg−1 were moderately successful in SOC predictions (r2pre = 0.58–0.85, RPD = 1.55–2.55. These models, however, could not be transferred to soil samples with different moisture levels. OSC and GLSW methods are useful filter transformations improving model transferability. The GLSW-PLSR model (mean of r2pre = 0.77, root mean square error for prediction (RMSEP = 3.08 g·kg−1, and residual prediction deviations (RPD = 2.09 outperforms the OSC-PLSR model (mean of r2pre = 0.67, RMSEP = 3.67 g·kg−1, and RPD = 1.76 when the moisture-mixed protocol is used. Results demonstrated the use of OSC

An image analysis system for near-infrared (NIR) fluorescence lymph imaging

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Zhang, Jingdan; Zhou, Shaohua Kevin; Xiang, Xiaoyan; Rasmussen, John C.; Sevick-Muraca, Eva M.

2011-03-01

Quantitative analysis of lymphatic function is crucial for understanding the lymphatic system and diagnosing the associated diseases. Recently, a near-infrared (NIR) fluorescence imaging system is developed for real-time imaging lymphatic propulsion by intradermal injection of microdose of a NIR fluorophore distal to the lymphatics of interest. However, the previous analysis software3, 4 is underdeveloped, requiring extensive time and effort to analyze a NIR image sequence. In this paper, we develop a number of image processing techniques to automate the data analysis workflow, including an object tracking algorithm to stabilize the subject and remove the motion artifacts, an image representation named flow map to characterize lymphatic flow more reliably, and an automatic algorithm to compute lymph velocity and frequency of propulsion. By integrating all these techniques to a system, the analysis workflow significantly reduces the amount of required user interaction and improves the reliability of the measurement.

Comparing predictive ability of Laser-Induced Breakdown Spectroscopy to Near Infrared Spectroscopy for soil texture and organic carbon determination

DEFF Research Database (Denmark)

Knadel, Maria; Peng, Yi; Gislum, René

Soil organic carbon (SOC) and texture have a practical value for agronomy and the environment. Thus, alternative techniques to supplement or substitute for the expensive conventional analysis of soil are developed. Here the feasibility of laser-induced breakdown spectroscopy (LIBS) to determine SOC...... and texture was tested and compared with near infrared spectroscopy (NIRS) technique and traditional laboratory analysis. Calibration models were developed on 50 topsoil samples. For all properties except silt, higher predictive ability of LIBS than NIRS models was obtained. Successful calibrations indicate...... that LIBS can be used as a fast and reliable method for SOC and texture estimation....

Characterisation of PDO olive oil Chianti Classico by non-selective (UV-visible, NIR and MIR spectroscopy) and selective (fatty acid composition) analytical techniques.

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Casale, M; Oliveri, P; Casolino, C; Sinelli, N; Zunin, P; Armanino, C; Forina, M; Lanteri, S

2012-01-27

An authentication study of the Italian PDO (protected designation of origin) extra virgin olive oil Chianti Classico was performed; UV-visible (UV-vis), Near-Infrared (NIR) and Mid-Infrared (MIR) spectroscopies were applied to a set of samples representative of the whole Chianti Classico production area. The non-selective signals (fingerprints) provided by the three spectroscopic techniques were utilised both individually and jointly, after fusion of the respective profile vectors, in order to build a model for the Chianti Classico PDO olive oil. Moreover, these results were compared with those obtained by the gas chromatographic determination of the fatty acids composition. In order to characterise the olive oils produced in the Chianti Classico PDO area, UNEQ (unequal class models) and SIMCA (soft independent modelling of class analogy) were employed both on the MIR, NIR and UV-vis spectra, individually and jointly, and on the fatty acid composition. Finally, PLS (partial least square) regression was applied on the UV-vis, NIR and MIR spectra, in order to predict the content of oleic and linoleic acids in the extra virgin olive oils. UNEQ, SIMCA and PLS were performed after selection of the relevant predictors, in order to increase the efficiency of both classification and regression models. The non-selective information obtained from UV-vis, NIR and MIR spectroscopy allowed to build reliable models for checking the authenticity of the Italian PDO extra virgin olive oil Chianti Classico. Copyright © 2011 Elsevier B.V. All rights reserved.

Near-infrared spectroscopy (NIRS neurofeedback as a treatment for children with attention deficit hyperactivity disorder (ADHD – a pilot study

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Anna-Maria eMarx

2015-01-01

Full Text Available In this pilot study near-infrared spectroscopy (NIRS neurofeedback was investigated as a new method for the treatment of ADHD. Oxygenated hemoglobin in the prefrontal cortex of children with ADHD was measured and fed back. 12 sessions of NIRS-neurofeedback were compared to the intermediate outcome after 12 sessions of EEG-neurofeedback (slow cortical potentials, SCP and 12 sessions of EMG-feedback (muscular activity of left and right musculus supraspinatus. The task was either to increase or decrease hemodynamic activity in the prefrontal cortex (NIRS, to produce positive or negative shifts of SCP (EEG or to increase or decrease muscular activity (EMG. In each group nine children with ADHD, aged 7 to 10 years, took part. Changes in parents’ ratings of ADHD symptoms were assessed before and after the 12 sessions and compared within and between groups. For the NIRS-group additional teachers’ ratings of ADHD symptoms, parents’ and teachers’ ratings of associated behavioral symptoms, childrens’ self reports on quality of life and a computer based attention task were conducted before, 4 weeks and 6 months after training. As primary outcome, ADHD symptoms decreased significantly 4 weeks and 6 months after the NIRS training, according to parents’ ratings. In teachers’ ratings of ADHD symptoms there was a significant reduction 4 weeks after the training. The performance in the computer based attention test improved significantly. Within-group comparisons after 12 sessions of NIRS-, EEG- and EMG-training revealed a significant reduction in ADHD symptoms in the NIRS-group and a trend for EEG- and EMG-groups. No significant differences for symptom reduction were found between the groups. Despite the limitations of small groups and the comparison of a completed with two uncompleted interventions, the results of this pilot study are promising. NIRS-neurofeedback could be a time-effective treatment for ADHD and an interesting new option to

Near and mid infrared spectroscopy and multivariate data analysis in studies of oxidation of edible oils.

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Wójcicki, Krzysztof; Khmelinskii, Igor; Sikorski, Marek; Sikorska, Ewa

2015-11-15

Infrared spectroscopic techniques and chemometric methods were used to study oxidation of olive, sunflower and rapeseed oils. Accelerated oxidative degradation of oils at 60°C was monitored using peroxide values and FT-MIR ATR and FT-NIR transmittance spectroscopy. Principal component analysis (PCA) facilitated visualization and interpretation of spectral changes occurring during oxidation. Multivariate curve resolution (MCR) method found three spectral components in the NIR and MIR spectral matrix, corresponding to the oxidation products, and saturated and unsaturated structures. Good quantitative relation was found between peroxide value and contribution of oxidation products evaluated using MCR--based on NIR (R(2) = 0.890), MIR (R(2) = 0.707) and combined NIR and MIR (R(2) = 0.747) data. Calibration models for prediction peroxide value established using partial least squares (PLS) regression were characterized for MIR (R(2) = 0.701, RPD = 1.7), NIR (R(2) = 0.970, RPD = 5.3), and combined NIR and MIR data (R(2) = 0.954, RPD = 3.1). Copyright © 2015 Elsevier Ltd. All rights reserved.

Numerical modeling of polymorphic transformation of oleic acid via near-infrared spectroscopy and factor analysis

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Liu, Ling; Cheng, Yuliang; Sun, Xiulan; Pi, Fuwei

2018-05-01

Near-infrared (NIR) spectroscopy as a tool for direct and quantitatively screening the minute polymorphic transitions of bioactive fatty acids was assessed basing on a thermal heating process of oleic acid. Temperature-dependent NIR spectral profiles indicate that dynamical variances of COOH group dominate its γ → α phase transition, while the transition from active α to β phase mainly relates to the conformational transfer of acyl chain. Through operating multivariate curve resolution-alternating least squares with factor analysis, instantaneous contribution of each active polymorph during the transition process was illustrated for displaying the progressive evolutions of functional groups. Calculated contributions reveal that the α phase of oleic acid initially is present at around -18 °C, but sharply grows up around -2.2 °C from the transformation of γ phase and finally disappears at the melting point. On the other hand, the β phase of oleic acid is sole self-generation after melt even it embryonically appears at -2.2 °C. Such mathematical approach based on NIR spectroscopy and factor analysis calculation provides a volatile strategy in quantitatively exploring the transition processes of bioactive fatty acids; meanwhile, it maintains promising possibility for instantaneous quantifying each active polymorph of lipid materials.

A Proof of Concept Study of Function-Based Statistical Analysis of fNIRS Data: Syntax Comprehension in Children with Specific Language Impairment Compared to Typically-Developing Controls.

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Fu, Guifang; Wan, Nicholas J A; Baker, Joseph M; Montgomery, James W; Evans, Julia L; Gillam, Ronald B

2016-01-01

Functional near infrared spectroscopy (fNIRS) is a neuroimaging technology that enables investigators to indirectly monitor brain activity in vivo through relative changes in the concentration of oxygenated and deoxygenated hemoglobin. One of the key features of fNIRS is its superior temporal resolution, with dense measurements over very short periods of time (100 ms increments). Unfortunately, most statistical analysis approaches in the existing literature have not fully utilized the high temporal resolution of fNIRS. For example, many analysis procedures are based on linearity assumptions that only extract partial information, thereby neglecting the overall dynamic trends in fNIRS trajectories. The main goal of this article is to assess the ability of a functional data analysis (FDA) approach for detecting significant differences in hemodynamic responses recorded by fNIRS. Children with and without SLI wore two, 3 × 5 fNIRS caps situated over the bilateral parasylvian areas as they completed a language comprehension task. FDA was used to decompose the high dimensional hemodynamic curves into the mean function and a few eigenfunctions to represent the overall trend and variation structures over time. Compared to the most popular GLM, we did not assume any parametric structure and let the data speak for itself. This analysis identified significant differences between the case and control groups in the oxygenated hemodynamic mean trends in the bilateral inferior frontal and left inferior posterior parietal brain regions. We also detected significant group differences in the deoxygenated hemodynamic mean trends in the right inferior posterior parietal cortex and left temporal parietal junction. These findings, using dramatically different approaches, experimental designs, data sets, and foci, were consistent with several other reports, confirming group differences in the importance of these two areas for syntax comprehension. The proposed FDA was consistent with the

A Near Infrared Spectroscopy (NIRS and Chemometric Approach to Improve Apple Fruit Quality Management: A Case Study on the Cultivars “Cripps Pink” and “Braeburn”

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Daniela Eisenstecken

2015-07-01

Full Text Available The potential of near infrared spectroscopy (NIRS in the wavelength range of 1000–2500 nm for predicting quality parameters such as total soluble solids (TSS, acidity (TA, firmness, and individual sugars (glucose, fructose, sucrose, and xylose for two cultivars of apples (“Braeburn” and “Cripps Pink” was studied during the pre- and post-storage periods. Simultaneously, a qualitative investigation on the capability of NIRS to discriminate varieties, harvest dates, storage periods and fruit inhomogeneity was carried out. In order to generate a sample set with high variability within the most relevant apple quality traits, three different harvest time points in combination with five different storage periods were chosen, and the evolution of important quality parameters was followed both with NIRS and wet chemical methods. By applying a principal component analysis (PCA a differentiation between the two cultivars, freshly harvested vs. long-term stored apples and, notably, between the sun-exposed vs. shaded side of apples could be found. For the determination of quality parameters effective prediction models for titratable acid (TA and individual sugars such as fructose, glucose and sucrose by using partial least square (PLS regression have been developed. Our results complement earlier reports, highlighting the versatility of NIRS as a fast, non-invasive method for quantitative and qualitative studies on apples.

Variable selection based near infrared spectroscopy quantitative and qualitative analysis on wheat wet gluten

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Lü, Chengxu; Jiang, Xunpeng; Zhou, Xingfan; Zhang, Yinqiao; Zhang, Naiqian; Wei, Chongfeng; Mao, Wenhua

2017-10-01

Wet gluten is a useful quality indicator for wheat, and short wave near infrared spectroscopy (NIRS) is a high performance technique with the advantage of economic rapid and nondestructive test. To study the feasibility of short wave NIRS analyzing wet gluten directly from wheat seed, 54 representative wheat seed samples were collected and scanned by spectrometer. 8 spectral pretreatment method and genetic algorithm (GA) variable selection method were used to optimize analysis. Both quantitative and qualitative model of wet gluten were built by partial least squares regression and discriminate analysis. For quantitative analysis, normalization is the optimized pretreatment method, 17 wet gluten sensitive variables are selected by GA, and GA model performs a better result than that of all variable model, with R2V=0.88, and RMSEV=1.47. For qualitative analysis, automatic weighted least squares baseline is the optimized pretreatment method, all variable models perform better results than those of GA models. The correct classification rates of 3 class of 30% wet gluten content are 95.45, 84.52, and 90.00%, respectively. The short wave NIRS technique shows potential for both quantitative and qualitative analysis of wet gluten for wheat seed.

Species authentication and geographical origin discrimination of herbal medicines by near infrared spectroscopy: A review

OpenAIRE

Wang, Pei; Yu, Zhiguo

2015-01-01

Near infrared (NIR) spectroscopy as a rapid and nondestructive analytical technique, integrated with chemometrics, is a powerful process analytical tool for the pharmaceutical industry and is becoming an attractive complementary technique for herbal medicine analysis. This review mainly focuses on the recent applications of NIR spectroscopy in species authentication of herbal medicines and their geographical origin discrimination. Keywords: Near infrared spectroscopy, Herbal medicine, Species...

A Proof of Concept Study of Function-based Statistical Analysis of fNIRS Data: Syntax Comprehension in Children with Specific Language Impairment Compared To Typically-Developing Controls

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Guifang eFu

2016-06-01

Full Text Available Functional near infrared spectroscopy (fNIRS is a neuroimaging techonology that enables investigators to indirectly monitor brain activity in vivo through relative changes in the concentration of oxygenated and deoxygenated hemoglobin. One of the key features of fNIRS is its superior temporal resolution, with dense measurements over very short periods of time (100ms increments. Unfortunately, most statistical analysis approaches in the existing literature have not fully utilized the high temporal resolution of fNIRS. For example, many analysis procedures are based on linearity assumptions that only extract partial information, thereby neglecting the overall dynamic trends in fNIRS trajectories. The main goal of this article is to assess the ability of a functional data analysis approach for detecting significant differences in hemodynamic responses recorded by fNIRS. Children with and without specific language impairment wore two, 3*5 fNIRS caps situated over the bilateral parasylvian areas as they completed a language comprehension task. Functional data analysis was used to decompose the high dimensional hemodynamic curves into the mean function and a few eigenfunctions to represent the overall trend and variation structures over time. Compared to the most popular general linear model, we did not assume any parametric structure and let the data speak for itself. This analysis identified significant differences between the case and control groups in the oxygenated hemodynamic mean trends in the right inferior frontal cortex and left inferior posterior parietal cortex brain regions. We also detected significant group differences in the deoxygenated hemodynamic mean trends in the right inferior posterior parietal cortex and left temporal parietal junction brain region. These findings, using dramatically different approaches, experimental designs, data sets, and foci, were consistent with several other reports, confirming group differences in the

Prediction of purine derivatives, creatinine and total nitrogen concentrations in urine by FT-Near-lnfrared Reflectance spectroscopy (FT-NIR)

International Nuclear Information System (INIS)

Susmel, P.; Piani, B.; Toso, B.; Stefanon, B.

2004-01-01

The objective of this study was to provide an alternative method for the determination of purine derivatives (PD, which include allantoin, uric acid, hypoxanthine and xanthine), creatinine and total nitrogen (N) concentrations in urine. About 180 urine samples from cattle, buffaloes and rabbit were collected and analyzed for PD by HPLC, creatinine by spectrophotometry and N by Kjeldahl method. The urine samples were then analyzed by Fourier Transformed Near Infrared Reflectance Spectroscopy (FT-NIR) to find conformity between this technique and the HPLC and colorimetric methods. FT-NIR can predict allantoin, uric acid, hypoxanthine, xanthine, creatinine, total N and sum of N in both allantoin and uric acid with a satisfactory level of accuracy: the determination coefficient (r 2 ) of validation ranged from 0.888% for uric acid to 0.982% for total N. The coefficients of determination for allantoin, creatinine and sum of N in both allantoin and uric acid were 0.92, 0.894 and 0.90%, respectively. Hypoxanthine and xanthine in urine samples were not detectable by NIRS, probably because of their low concentrations, and therefore they were not considered for instrumental calibration. (author)

Spectroscopy: Developments in instrumentation and analysis

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Dardenne, Pierre

2002-03-01

Full Text Available This review presents the characteristics, advantages, limits and potential of three spectroscopic techniques: near-infrared spectroscopy (NIR, mid-infrared spectroscopy (MIR and Raman spectroscopy. The theoretical aspects related with these techniques, the information that can supplied and the main features of the instrumentation are presented and briefly discussed. The last part of the review concerns the application of the spectroscopy to food analysis, with special emphasis on the lipid analysis. The illustrations and examples have been chosen to demonstrate the importance of spectroscopic techniques both in process (on-line control and in laboratories for the analysis of major or minor compounds.Este artículo de revisión presenta las características, ventajas, límites y potencial de tres técnicas espectroscópicas: las espectroscopias del infrarrojo cercano, del medio infrarrojo y Raman. Se presentan, y discuten brevemente, los aspectos teóricos relacionados con estas técnicas, la información que pueden suministrar, y las principales características de la instrumentación. La última parte de la revisión esta dedicada a las aplicaciones de la espectroscopia en análisis de alimentos, con especial énfasis en análisis de lípidos. La ilustraciones y los ejemplos se han elegido para demostrar la importancia de las técnicas espectroscópicas en los procesos en-línea y en los laboratorios en el análisis de componentes mayoritarios y minoritarios.

Prediction of SOC content by Vis-NIR spectroscopy at European scale using a modified local PLS algorithm

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Nocita, M.; Stevens, A.; Toth, G.; van Wesemael, B.; Montanarella, L.

2012-12-01

In the context of global environmental change, the estimation of carbon fluxes between soils and the atmosphere has been the object of a growing number of studies. This has been motivated notably by the possibility to sequester CO2 into soils by increasing the soil organic carbon (SOC) stocks and by the role of SOC in maintaining soil quality. Spatial variability of SOC masks its slow accumulation or depletion, and the sampling density required to detect a change in SOC content is often very high and thus very expensive and labour intensive. Visible near infrared diffuse reflectance spectroscopy (Vis-NIR DRS) has been shown to be a fast, cheap and efficient tool for the prediction of SOC at fine scales. However, when applied to regional or country scales, Vis-NIR DRS did not provide sufficient accuracy as an alternative to standard laboratory soil analysis for SOC monitoring. Under the framework of Land Use/Cover Area Frame Statistical Survey (LUCAS) project of the European Commission's Joint Research Centre (JRC), about 20,000 samples were collected all over European Union. Soil samples were analyzed for several physical and chemical parameters, and scanned with a Vis-NIR spectrometer in the same laboratory. The scope of our research was to predict SOC content at European scale using LUCAS spectral library. We implemented a modified local partial least square regression (l-PLS) including, in addition to spectral distance, other potentially useful covariates (geography, texture, etc.) to select for each unknown sample a group of predicting neighbours. The dataset was split in mineral soils under cropland, mineral soils under grassland, mineral soils under woodland, and organic soils due to the extremely diverse spectral response of the four classes. Four every class training (70%) and test (30%) sets were created to calibrate and validate the SOC prediction models. The results showed very good prediction ability for mineral soils under cropland and mineral soils

Calibration sets selection strategy for the construction of robust PLS models for prediction of biodiesel/diesel blends physico-chemical properties using NIR spectroscopy

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Palou, Anna; Miró, Aira; Blanco, Marcelo; Larraz, Rafael; Gómez, José Francisco; Martínez, Teresa; González, Josep Maria; Alcalà, Manel

2017-06-01

Even when the feasibility of using near infrared (NIR) spectroscopy combined with partial least squares (PLS) regression for prediction of physico-chemical properties of biodiesel/diesel blends has been widely demonstrated, inclusion in the calibration sets of the whole variability of diesel samples from diverse production origins still remains as an important challenge when constructing the models. This work presents a useful strategy for the systematic selection of calibration sets of samples of biodiesel/diesel blends from diverse origins, based on a binary code, principal components analysis (PCA) and the Kennard-Stones algorithm. Results show that using this methodology the models can keep their robustness over time. PLS calculations have been done using a specialized chemometric software as well as the software of the NIR instrument installed in plant, and both produced RMSEP under reproducibility values of the reference methods. The models have been proved for on-line simultaneous determination of seven properties: density, cetane index, fatty acid methyl esters (FAME) content, cloud point, boiling point at 95% of recovery, flash point and sulphur.

Rapid classification of turmeric based on DNA fingerprint by near-infrared spectroscopy combined with moving window partial least squares-discrimination analysis

International Nuclear Information System (INIS)

Kasemsumran, Sumaporn; Suttiwijitpukdee, Nattaporn; Keeratinijakal, Vichein

2017-01-01

In this research, near-infrared (NIR) spectroscopy in combination with moving window partial least squares-discrimination analysis (MWPLS-DA) was utilized to discriminate the variety of turmeric based on DNA markers, which correlated to the quantity of curcuminoid. Curcuminoid was used as a marker compound in variety identification due to the most pharmacological properties of turmeric possessed from it. MWPLS-DA optimized informative NIR spectral regions for the fitting and prediction to {-1/1}-coded turmeric varieties, indicating variables in the development of latent variables in discrimination analysis. Consequently, MWPLS-DA benefited in the selection of combined informative NIR spectral regions of 1100 – 1260, 1300 – 1500 and 1880 – 2500 nm for classification modeling of turmeric variety with 148 calibration samples, and yielded the results better than that obtained from a partial least squares-discrimination analysis (PLS-DA) model built by using the whole NIR spectral region. An effective and rapid strategy of using NIR in combination with MWPLS-DA provided the best variety identification results of 100% in both specificity and total accuracy for 48 test samples. (author)

The application of near infrared spectroscopy (NIR technique for

Directory of Open Access Journals (Sweden)

Sandor Barabassy

2001-06-01

Full Text Available The production of cow’s milk in Hungary fluctuates by 15-20 % annualy. Surplus milk is dried into powder and can also be converted to modified milk powders using techniques such as ultra filtration. From approximetely 20.000 tonnes, of all milk powder types, 3.000 tonnes, is converted using ultra filtration technology. Multivariable near infrared (NIR calibration was performed on powder mixtures of whole milk, skimmed milk, whey, retenate (protein concentrate and lactose for rapid fat, protein, lactose, water and ash content determination. More than 150 samples were prepared and measured in two NIRS labs (Scottish Agriculture College – SAC – Aberdeen and University of Horticulture and Food Science - UHFS – Budapest. The results obtained from the same samples were compared. The aims of the study were: 1. Rapid quantitative and qualitative determination of mixtures of milk powder products using NIR technique. 2. Comparison of the results achieved in Aberdeen (SAC and Budapest (UHFS institutes. The mass per cent varied between 0.0-2.8% for fat, 0.0-80% for protein, 6.6-100 % for lactose, 0.0-5.0 % for water and 0.0-8.0 % for ash. High correlation coefficients (0.97-0.99 were found for all five components.

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.

On temporal connectivity of PFC via Gauss-Markov modeling of fNIRS signals.

Science.gov (United States)

Aydöre, Sergül; Mihçak, M Kivanç; Ciftçi, Koray; Akin, Ata

2010-03-01

Functional near-infrared spectroscopy (fNIRS) is an optical imaging method, which monitors the brain activation by measuring the successive changes in the concentration of oxy- and deoxyhemoglobin in real time. In this study, we present a method to investigate the functional connectivity of prefrontal cortex (PFC) Sby applying a Gauss-Markov model to fNIRS signals. The hemodynamic changes on PFC during the performance of cognitive paradigm are measured by fNIRS for 17 healthy adults. The color-word matching Stroop task is performed to activate 16 different regions of PFC. There are three different types of stimuli in this task, which can be listed as incongruent stimulus (IS), congruent stimulus (CS), and neutral stimulus (NS), respectively. We introduce a new measure, called "information transfer metric" (ITM) for each time sample. The behavior of ITMs during IS are significantly different from the ITMs during CS and NS, which is consistent with the outcome of the previous research, which concentrated on fNIRS signal analysis via color-word matching Stroop task. Our analysis shows that the functional connectivity of PFC is highly relevant with the cognitive load, i.e., functional connectivity increases with the increasing cognitive load.

Species authentication and geographical origin discrimination of herbal medicines by near infrared spectroscopy: A review.

Science.gov (United States)

Wang, Pei; Yu, Zhiguo

2015-10-01

Near infrared (NIR) spectroscopy as a rapid and nondestructive analytical technique, integrated with chemometrics, is a powerful process analytical tool for the pharmaceutical industry and is becoming an attractive complementary technique for herbal medicine analysis. This review mainly focuses on the recent applications of NIR spectroscopy in species authentication of herbal medicines and their geographical origin discrimination.

Non-invasive in situ identification and band assignments of diazepam, flunitrazepam and methadone hydrochloride with FT-near-infrared spectroscopy.

Science.gov (United States)

Ali, Hassan Refat H

2011-03-20

Near-infrared spectroscopy (NIR) has evolved into an important rapid, direct and non-invasive technique in drugs analysis. In this study, the suitability of NIR spectroscopy to identify two benzodiazepine derivatives, diazepam and flunitrazepam, and a synthetic opiate, methadone hydrochloride, inside USP vials and probe the solid-state form of diazepam presents in tablets has been explored. The results show the potential of NIR spectroscopy for rapid, in situ and non-destructive identification of drugs. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Evaluation of cerebral activity in the prefrontal cortex in mood [affective] disorders during animal-assisted therapy (AAT) by near-infrared spectroscopy (NIRS): a pilot study.

Science.gov (United States)

Aoki, Jun; Iwahashi, Kazuhiko; Ishigooka, Jun; Fukamauchi, Fumihiko; Numajiri, Maki; Ohtani, Nobuyo; Ohta, Mitsuaki

2012-09-01

Previous studies have shown the possibility that animal-assisted therapy (AAT) is useful for promoting the recovery of a patient's psychological, social, and physiological aspect. As a pilot study, we measured the effect that AAT had on cerebral activity using near-infrared spectroscopy (NIRS), and examined whether or not NIRS be used to evaluate the effect of AAT biologically and objectively. Two patients with mood [affective] disorders and a healthy subject participated in this study. We performed two AAT and the verbal fluency task (VFT). The NIRS signal during AAT showed great [oxy-Hb] increases in most of the prefrontal cortex (PFC) in the two patients. When the NIRS pattern during AAT was compared with that during VFT, greater or lesser differences were observed between them in all subjects. The present study suggested that AAT possibly causes biological and physiological changes in the PFC, and that AAT is useful for inducing the activity of the PFC in patients with depression who have generally been said to exhibit low cerebral activity in the PFC. In addition, the possibility was also suggested that the effect of AAT can be evaluated using NIRS physiologically and objectively.

Functional Connectivity Analysis of NIRS Data under Rubber Hand Illusion to Find a Biomarker of Sense of Ownership.

Science.gov (United States)

Arizono, Naoki; Ohmura, Yuji; Yano, Shiro; Kondo, Toshiyuki

2016-01-01

The self-identification, which is called sense of ownership, has been researched through methodology of rubber hand illusion (RHI) because of its simple setup. Although studies with neuroimaging technique, such as fMRI, revealed that several brain areas are associated with the sense of ownership, near-infrared spectroscopy (NIRS) has not yet been utilized. Here we introduced an automated setup to induce RHI, measured the brain activity during the RHI with NIRS, and analyzed the functional connectivity so as to understand dynamical brain relationship regarding the sense of ownership. The connectivity was evaluated by multivariate Granger causality. In this experiment, the peaks of oxy-Hb on right frontal and right motor related areas during the illusion were significantly higher compared with those during the nonillusion. Furthermore, by analyzing the NIRS recordings, we found a reliable connectivity from the frontal to the motor related areas during the illusion. This finding suggests that frontal cortex and motor related areas communicate with each other when the sense of ownership is induced. The result suggests that the sense of ownership is related to neural mechanism underlying human motor control, and it would be determining whether motor learning (i.e., neural plasticity) will occur. Thus RHI with the functional connectivity analysis will become an appropriate biomarker for neurorehabilitation.

Species authentication and geographical origin discrimination of herbal medicines by near infrared spectroscopy: A review

Directory of Open Access Journals (Sweden)

Pei Wang

2015-10-01

Full Text Available Near infrared (NIR spectroscopy as a rapid and nondestructive analytical technique, integrated with chemometrics, is a powerful process analytical tool for the pharmaceutical industry and is becoming an attractive complementary technique for herbal medicine analysis. This review mainly focuses on the recent applications of NIR spectroscopy in species authentication of herbal medicines and their geographical origin discrimination. Keywords: Near infrared spectroscopy, Herbal medicine, Species authentication, Geographical origin discrimination, Quality control

Toward Adaptation of fNIRS Instrumentation to Airborne Environments

Science.gov (United States)

Adamovsky, Grigory; Mackey, Jeffrey; Harrivel, Angela; Hearn, Tristan; Floyd, Bertram

2014-01-01

The paper reviews potential applications of functional Near-Infrared Spectroscopy (fNIRS), a well-known medical diagnostic technique, to monitoring the cognitive state of pilots with a focus on identifying ways to adopt this technique to airborne environments. We also discuss various fNIRS techniques and the direction of technology maturation of associated hardware in view of their potential for miniaturization, maximization of data collection capabilities, and user friendliness.

Adsorption of petroleum resins and asphaltenes onto reservoir rock sands studied by near infrared (NIR) spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Syunyaev, R.Z.; Balabin, R.M. [Russian State Univ. of Oil and Gas, Moscow (Russian Federation). Dept. of Physics; Akhatov, I.S. [North Dakota State Univ., Fargo, ND (United States). Dept. of Mechanical Engineering and Center for Nanoscale Science and Engineering

2008-07-01

The presence of asphaltene and resin in crude oil is known to cause well bore plugging and pipeline deposition; stabilization of water/oil emulsions; sedimentation and plugging during crude oil storage; adsorption on refining equipment and coke formation. Kinetic and thermodynamic parameters of adsorption are also known to influence wettability and the capillary number. In this study, adsorption parameters of petroleum resins and asphaltenes were evaluated by Near Infrared (NIR) spectroscopy. Fractioned quartz, dolomite, mica and kaolinite sands were used as adsorbent. The particle size distribution was evaluated using an optical microscope. Porosity and permeability of each fraction were designed and benzene was used as the solvent. Various approaches for calibrating NIR spectra-macromolecules concentration were discussed. In this study, the partial least squares (PLS) regression method was used and the Langmuir model was chosen for experimental data fitting. Kinetic and isothermic data was used to evaluate the maximal adsorbed mass density, the equilibrium constant of adsorption, and the rate constants of adsorption and desorption. The rate constants of resins adsorption and desorption depended on the concentration. A numerical algorithm was developed to estimate the diffusion coefficient and relaxation time from the experimental data.

Time-Frequency Characterization of Cerebral Hemodynamics of Migraine Sufferers as Assessed by NIRS Signals

Directory of Open Access Journals (Sweden)

Filippo Molinari

2010-01-01

Full Text Available Near-infrared spectroscopy (NIRS is a noninvasive system for the real-time monitoring of the concentration of oxygenated (O2Hb and reduced (HHb hemoglobin in the brain cortex. O2Hb and HHb concentrations vary in response to cerebral autoregulation. Sixty-eight women (14 migraineurs without aura, 49 migraineurs with aura, and 5 controls performed breath-holding and hyperventilation during NIRS recordings. Signals were processed using the Choi-Williams time-frequency transform in order to measure the power variation of the very-low frequencies (VLF: 20–40 mHz and of the low frequencies (LF: 40–140 mHz. Results showed that migraineurs without aura present different LF and VLF power levels than controls and migraineurs with aura. The accurate power measurement of the time-frequency analysis allowed for the discrimination of the subjects' hemodynamic patterns. The time-frequency analysis of NIRS signals can be used in clinical practice to assess cerebral hemodynamics.

Time-Frequency Characterization of Cerebral Hemodynamics of Migraine Sufferers as Assessed by NIRS Signals

Directory of Open Access Journals (Sweden)

Liboni William

2010-01-01

Full Text Available Abstract Near-infrared spectroscopy (NIRS is a noninvasive system for the real-time monitoring of the concentration of oxygenated ( and reduced (HHb hemoglobin in the brain cortex. and HHb concentrations vary in response to cerebral autoregulation. Sixty-eight women (14 migraineurs without aura, 49 migraineurs with aura, and 5 controls performed breath-holding and hyperventilation during NIRS recordings. Signals were processed using the Choi-Williams time-frequency transform in order to measure the power variation of the very-low frequencies (VLF: 20–40 mHz and of the low frequencies (LF: 40–140 mHz. Results showed that migraineurs without aura present different LF and VLF power levels than controls and migraineurs with aura. The accurate power measurement of the time-frequency analysis allowed for the discrimination of the subjects' hemodynamic patterns. The time-frequency analysis of NIRS signals can be used in clinical practice to assess cerebral hemodynamics.

Altered low frequency oscillations of cortical vessels in patients with cerebrovascular occlusive disease – a NIRS study

DEFF Research Database (Denmark)

Phillip, Dorte; Iversen, Helle K; Schytz, Henrik W

2013-01-01

Analysis of cerebral autoregulation by measuring spontaneous oscillations in the low frequency spectrum of cerebral cortical vessels might be a useful tool for assessing risk and investigating different treatment strategies in carotid artery disease and stroke. Near infrared spectroscopy (NIRS...

Classification of Fusarium-Infected Korean Hulled Barley Using Near-Infrared Reflectance Spectroscopy and Partial Least Squares Discriminant Analysis

Directory of Open Access Journals (Sweden)

Jongguk Lim

2017-09-01

Full Text Available The purpose of this study is to use near-infrared reflectance (NIR spectroscopy equipment to nondestructively and rapidly discriminate Fusarium-infected hulled barley. Both normal hulled barley and Fusarium-infected hulled barley were scanned by using a NIR spectrometer with a wavelength range of 1175 to 2170 nm. Multiple mathematical pretreatments were applied to the reflectance spectra obtained for Fusarium discrimination and the multivariate analysis method of partial least squares discriminant analysis (PLS-DA was used for discriminant prediction. The PLS-DA prediction model developed by applying the second-order derivative pretreatment to the reflectance spectra obtained from the side of hulled barley without crease achieved 100% accuracy in discriminating the normal hulled barley and the Fusarium-infected hulled barley. These results demonstrated the feasibility of rapid discrimination of the Fusarium-infected hulled barley by combining multivariate analysis with the NIR spectroscopic technique, which is utilized as a nondestructive detection method.

Cerebral time domain-NIRS: Reproducibility analysis, optical properties, hemoglobin species and tissue oxygen saturation in a cohort of adult subjects

OpenAIRE

Giacalone, Giacomo; Zanoletti, Marta; Contini, Davide; Rebecca, Re; Spinelli, Lorenzo; Roveri, Luisa; Torricelli, Alessandro

2017-01-01

The reproducibility of cerebral time-domain near-infrared spectroscopy (TD-NIRS) has not been investigated so far. Besides, reference intervals of cerebral optical properties, of absolute concentrations of deoxygenated-hemoglobin (HbR), oxygenated-hemoglobin (HbO), total hemoglobin (HbT) and tissue oxygen saturation (StO2) and their variability have not been reported. We have addressed these issues on a sample of 88 adult healthy subjects. TD-NIRS measurements at 690, 785, 830 nm were fitted ...

Determination of the Mechanical Properties of Rubber by FT-NIR

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Rattapol Pornprasit

2016-01-01

Full Text Available Mechanical tests, for example, tensile and hardness tests, are usually used to evaluate the properties of rubber materials. In this work, mechanical properties of selected rubber materials, that is, natural rubber (NR, styrene butadiene rubber (SBR, nitrile butadiene rubber (NBR, and ethylene propylene diene monomer (EPDM, were evaluated using a near infrared (NIR spectroscopy technique. Here, NR/NBR and NR/EPDM blends were first prepared. All of the samples were then scanned using a FT-NIR spectrometer and fitted with an integration sphere working in a diffused reflectance mode. The spectra were correlated with hardness and tensile properties. Partial least square (PLS calibration models were built from the spectra datasets with preprocessing techniques, that is, smoothing and second derivative. This indicated that reasonably accurate models, that is, with a coefficient of determination [R2] of the validation greater than 0.9, could be achieved for the hardness and tensile properties of rubber materials. This study demonstrated that FT-NIR analysis can be applied to determine hardness and tensile values in rubbers and rubber blends effectively.

Visible and Near-Infrared Spectroscopy Analysis of a Polycyclic Aromatic Hydrocarbon in Soils

Directory of Open Access Journals (Sweden)

Reuben N. Okparanma

2013-01-01

Full Text Available Visible and near-infrared (VisNIR spectroscopy is becoming recognised by soil scientists as a rapid and cost-effective measurement method for hydrocarbons in petroleum-contaminated soils. This study investigated the potential application of VisNIR spectroscopy (350–2500 nm for the prediction of phenanthrene, a polycyclic aromatic hydrocarbon (PAH, in soils. A total of 150 diesel-contaminated soil samples were used in the investigation. Partial least-squares (PLS regression analysis with full cross-validation was used to develop models to predict the PAH compound. Results showed that the PAH compound was predicted well with residual prediction deviation of 2.0–2.32, root-mean-square error of prediction of 0.21–0.25 mg kg−1, and coefficient of determination (r2 of 0.75–0.83. The mechanism of prediction was attributed to covariation of the PAH with clay and soil organic carbon. Overall, the results demonstrated that the methodology may be used for predicting phenanthrene in soils utilizing the interrelationship between clay and soil organic carbon.

Visible and Near-Infrared Spectroscopy Analysis of a Polycyclic Aromatic Hydrocarbon in Soils

Science.gov (United States)

Okparanma, Reuben N.; Mouazen, Abdul M.

2013-01-01

Visible and near-infrared (VisNIR) spectroscopy is becoming recognised by soil scientists as a rapid and cost-effective measurement method for hydrocarbons in petroleum-contaminated soils. This study investigated the potential application of VisNIR spectroscopy (350–2500 nm) for the prediction of phenanthrene, a polycyclic aromatic hydrocarbon (PAH), in soils. A total of 150 diesel-contaminated soil samples were used in the investigation. Partial least-squares (PLS) regression analysis with full cross-validation was used to develop models to predict the PAH compound. Results showed that the PAH compound was predicted well with residual prediction deviation of 2.0–2.32, root-mean-square error of prediction of 0.21–0.25 mg kg−1, and coefficient of determination (r 2) of 0.75–0.83. The mechanism of prediction was attributed to covariation of the PAH with clay and soil organic carbon. Overall, the results demonstrated that the methodology may be used for predicting phenanthrene in soils utilizing the interrelationship between clay and soil organic carbon. PMID:24453798

Development of a near-infrared spectroscopy method (NIRS) for fast analysis of total, indolic, aliphatic and individual glucosinolates in new bred open pollinating genotypes of broccoli (Brassica oleracea convar. botrytis var. italica).

Science.gov (United States)

Sahamishirazi, Samira; Zikeli, Sabine; Fleck, Michael; Claupein, Wilhelm; Graeff-Hoenninger, Simone

2017-10-01

This study describes the development of near-infrared spectroscopy (NIRS) calibration to determine individual and total glucosinolates (GSLs) content of 12 new-bred open-pollinating genotypes of broccoli (Brassica oleracea convar. botrytis var. italica). Six individual GSLs were identified using high-performance-liquid chromatography (HPLC). The NIRS calibration was established based on modified partial least squares regression with reference values of HPLC. The calibration was analyzed using coefficient of determination in prediction (R 2 ) and ratio of preference of determination (RPD). Large variation occurred in the calibrations, R 2 and RPD due to the variability of the samples. Derived calibrations for total-GSLs, aliphatic-GSLs, glucoraphanin and 4-methoxyglucobrassicin were quantitative with a high accuracy (RPD=1.36, 1.65, 1.63, 1.11) while, for indole-GSLs, glucosinigrin, glucoiberin, glucobrassicin and 1-methoxyglucobrassicin were more qualitative (RPD=0.95, 0.62, 0.67, 0.81, 0.56). Overall, the results indicated NIRS has a good potential to determine different GSLs in a large sample pool of broccoli quantitatively and qualitatively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Potable NIR spectroscopy predicting soluble solids content of pears based on LEDs

Energy Technology Data Exchange (ETDEWEB)

Liu Yande; Liu Wei; Sun Xudong; Gao Rongjie; Pan Yuanyuan; Ouyang Aiguo, E-mail: jxliuyd@163.com [School of Mechatronics Engineering, East China Jiaotong University, Changbei Open and Developing District, Nanchang, 330013 (China)

2011-01-01

A portable near-infrared (NIR) instrument was developed for predicting soluble solids content (SSC) of pears equipped with light emitting diodes (LEDs). NIR spectra were collected on the calibration and prediction sets (145:45). Relationships between spectra and SSC were developed by multivariate linear regression (MLR), partial least squares (PLS) and artificial neural networks (ANNs) in the calibration set. The 45 unknown pears were applied to evaluate the performance of them in terms of root mean square errors of prediction (RMSEP) and correlation coefficients (r). The best result was obtained by PLS with RMSEP of 0.62{sup 0}Brix and r of 0.82. The results showed that the SSC of pears could be predicted by the portable NIR instrument.

Potable NIR spectroscopy predicting soluble solids content of pears based on LEDs

International Nuclear Information System (INIS)

Liu Yande; Liu Wei; Sun Xudong; Gao Rongjie; Pan Yuanyuan; Ouyang Aiguo

2011-01-01

A portable near-infrared (NIR) instrument was developed for predicting soluble solids content (SSC) of pears equipped with light emitting diodes (LEDs). NIR spectra were collected on the calibration and prediction sets (145:45). Relationships between spectra and SSC were developed by multivariate linear regression (MLR), partial least squares (PLS) and artificial neural networks (ANNs) in the calibration set. The 45 unknown pears were applied to evaluate the performance of them in terms of root mean square errors of prediction (RMSEP) and correlation coefficients (r). The best result was obtained by PLS with RMSEP of 0.62 0 Brix and r of 0.82. The results showed that the SSC of pears could be predicted by the portable NIR instrument.

NIRS Characterization of Paper Pulps to Predict Kappa Number

Directory of Open Access Journals (Sweden)

Ana Moral

2015-01-01

Full Text Available Rice is one of the most abundant food crops in the world and its straw stands as an important source of fibres both from an economic and an environmental point of view. Pulp characterization is of special relevance in works involving alternative raw materials, since pulp properties are closely linked to the quality of the final product. One of the analytical techniques that can be used in pulp characterization is near-infrared spectroscopy (NIRS. The use of NIRS has economic and technical advantages over conventional techniques. This paper aims to discuss the convenience of using NIRS to predict Kappa number in rice straw pulps produced under different conditions. We found that the resulting Kappa number can be acceptably estimated by NIRS, as the errors obtained with that method are similar to those found for other techniques.

Towards NIRS-based hand movement recognition.

Science.gov (United States)

Paleari, Marco; Luciani, Riccardo; Ariano, Paolo

2017-07-01

This work reports on preliminary results about on hand movement recognition with Near InfraRed Spectroscopy (NIRS) and surface ElectroMyoGraphy (sEMG). Either basing on physical contact (touchscreens, data-gloves, etc.), vision techniques (Microsoft Kinect, Sony PlayStation Move, etc.), or other modalities, hand movement recognition is a pervasive function in today environment and it is at the base of many gaming, social, and medical applications. Albeit, in recent years, the use of muscle information extracted by sEMG has spread out from the medical applications to contaminate the consumer world, this technique still falls short when dealing with movements of the hand. We tested NIRS as a technique to get another point of view on the muscle phenomena and proved that, within a specific movements selection, NIRS can be used to recognize movements and return information regarding muscles at different depths. Furthermore, we propose here three different multimodal movement recognition approaches and compare their performances.

Near-Infrared Spatially Resolved Spectroscopy for Tablet Quality Determination.

Science.gov (United States)

Igne, Benoît; Talwar, Sameer; Feng, Hanzhou; Drennen, James K; Anderson, Carl A

2015-12-01

Near-infrared (NIR) spectroscopy has become a well-established tool for the characterization of solid oral dosage forms manufacturing processes and finished products. In this work, the utility of a traditional single-point NIR measurement was compared with that of a spatially resolved spectroscopic (SRS) measurement for the determination of tablet assay. Experimental designs were used to create samples that allowed for calibration models to be developed and tested on both instruments. Samples possessing a poor distribution of ingredients (highly heterogeneous) were prepared by under-blending constituents prior to compaction to compare the analytical capabilities of the two NIR methods. The results indicate that SRS can provide spatial information that is usually obtainable only through imaging experiments for the determination of local heterogeneity and detection of abnormal tablets that would not be detected with single-point spectroscopy, thus complementing traditional NIR measurement systems for in-line, and in real-time tablet analysis. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

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.

Designing and testing a wearable, wireless fNIRS patch.

Science.gov (United States)

Abtahi, Mohammadreza; Cay, Gozde; Saikia, Manob Jyoti; Mankodiya, Kunal

2016-08-01

Optical brain monitoring using near infrared (NIR) light has got a lot of attention in order to study the complexity of the brain due to several advantages as oppose to other methods such as EEG, fMRI and PET. There are a few commercially available functional NIR spectroscopy (fNIRS) brain monitoring systems, but they are still non-wearable and pose difficulties in scanning the brain while the participants are in motion. In this work, we present our endeavors to design and test a low-cost, wireless fNIRS patch using NIR light sources at wavelengths of 770 and 830nm, photodetectors and a microcontroller to trigger the light sources, read photodetector's output and transfer data wirelessly (via Bluetooth) to a smart-phone. The patch is essentially a 3-D printed wearable system, recording and displaying the brain hemodynamic responses on smartphone, also eliminates the need for complicated wiring of the electrodes. We have performed rigorous lab experiments on the presented system for its functionality. In a proof of concept experiment, the patch detected the NIR absorption on the arm. Another experiment revealed that the patch's battery could last up to several hours with continuous fNIRS recording with and without wireless data transfer.

A rapid qualitative and quantitative evaluation of grape berries at various stages of development using Fourier-transform infrared spectroscopy and multivariate data analysis.

Science.gov (United States)

Musingarabwi, Davirai M; Nieuwoudt, Hélène H; Young, Philip R; Eyéghè-Bickong, Hans A; Vivier, Melané A

2016-01-01

Fourier transform (FT) near-infrared (NIR) and attenuated total reflection (ATR) FT mid-infrared (MIR) spectroscopy were used to qualitatively and quantitatively analyse Vitis vinifera L. cv Sauvignon blanc grape berries. FT-NIR and ATR FT-MIR spectroscopy, coupled with spectral preprocessing and multivariate data analysis (MVDA), provided reliable methods to qualitatively assess berry samples at five distinct developmental stages: green, pre-véraison, véraison, post-véraison and ripe (harvest), without any prior metabolite extraction. Compared to NIR spectra, MIR spectra provided more reliable discrimination between the berry samples from the different developmental stages. Interestingly, ATR FT-MIR spectra from fresh homogenized berry samples proved more discriminatory than spectra from frozen homogenized berry samples. Different developmental stages were discriminated by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). In order to generate partial least squares (PLS) models from the MIR/NIR spectral datasets; the major sugars (glucose and fructose) and organic acids (malic acid, succinic acid and tartaric acid) were separated and quantified by high performance liquid chromatography (HPLC) and the data used as a reference dataset. PLS regression was used to develop calibration models to predict the concentration of the major sugars and organic acids in the berry samples from different developmental stages. Our data show that infrared (IR) spectroscopy could provide a rapid, reproducible and cost-effective alternative to the chromatographic analysis of the sugar and organic acid composition of grape berries at various developmental stages, using small sample volumes and requiring limited sample preparation. This provides scope and support for the possible development of hand-held devices to assess quality parameters in field-settings in real-time and non-destructively using IR technologies. Copyright �

Functional Connectivity Analysis of NIRS Data under Rubber Hand Illusion to Find a Biomarker of Sense of Ownership

Directory of Open Access Journals (Sweden)

Naoki Arizono

2016-01-01

Full Text Available The self-identification, which is called sense of ownership, has been researched through methodology of rubber hand illusion (RHI because of its simple setup. Although studies with neuroimaging technique, such as fMRI, revealed that several brain areas are associated with the sense of ownership, near-infrared spectroscopy (NIRS has not yet been utilized. Here we introduced an automated setup to induce RHI, measured the brain activity during the RHI with NIRS, and analyzed the functional connectivity so as to understand dynamical brain relationship regarding the sense of ownership. The connectivity was evaluated by multivariate Granger causality. In this experiment, the peaks of oxy-Hb on right frontal and right motor related areas during the illusion were significantly higher compared with those during the nonillusion. Furthermore, by analyzing the NIRS recordings, we found a reliable connectivity from the frontal to the motor related areas during the illusion. This finding suggests that frontal cortex and motor related areas communicate with each other when the sense of ownership is induced. The result suggests that the sense of ownership is related to neural mechanism underlying human motor control, and it would be determining whether motor learning (i.e., neural plasticity will occur. Thus RHI with the functional connectivity analysis will become an appropriate biomarker for neurorehabilitation.

A New Framework for the Assessment of Cerebral Hemodynamics Regulation in Neonates Using NIRS

NARCIS (Netherlands)

Caicedo, Alexander; Alderliesten, Thomas; Naulaers, Gunnar; Lemmers, Petra; van Bel, Frank; Van Huffel, Sabine

2016-01-01

We present a new framework for the assessment of cerebral hemodynamics regulation (CHR) in neonates using near-infrared spectroscopy (NIRS). In premature infants, NIRS measurements have been used as surrogate variables for cerebral blood flow (CBF) in the assessment of cerebral autoregulation (CA).

Near-infrared imaging spectroscopy for counterfeit drug detection

Science.gov (United States)

Arnold, Thomas; De Biasio, Martin; Leitner, Raimund

2011-06-01

Pharmaceutical counterfeiting is a significant issue in the healthcare community as well as for the pharmaceutical industry worldwide. The use of counterfeit medicines can result in treatment failure or even death. A rapid screening technique such as near infrared (NIR) spectroscopy could aid in the search for and identification of counterfeit drugs. This work presents a comparison of two laboratory NIR imaging systems and the chemometric analysis of the acquired spectroscopic image data. The first imaging system utilizes a NIR liquid crystal tuneable filter and is designed for the investigation of stationary objects. The second imaging system utilizes a NIR imaging spectrograph and is designed for the fast analysis of moving objects on a conveyor belt. Several drugs in form of tablets and capsules were analyzed. Spectral unmixing techniques were applied to the mixed reflectance spectra to identify constituent parts of the investigated drugs. The results show that NIR spectroscopic imaging can be used for contact-less detection and identification of a variety of counterfeit drugs.

Combined multi-distance frequency domain and diffuse correlation spectroscopy system with simultaneous data acquisition and real-time analysis.

Science.gov (United States)

Carp, Stefan A; Farzam, Parisa; Redes, Norin; Hueber, Dennis M; Franceschini, Maria Angela

2017-09-01

Frequency domain near infrared spectroscopy (FD-NIRS) and diffuse correlation spectroscopy (DCS) have emerged as synergistic techniques for the non-invasive assessment of tissue health. Combining FD-NIRS oximetry with DCS measures of blood flow, the tissue oxygen metabolic rate can be quantified, a parameter more closely linked to underlying physiology and pathology than either NIRS or DCS estimates alone. Here we describe the first commercially available integrated instrument, called the "MetaOx", designed to enable simultaneous FD-NIRS and DCS measurements at rates of 10 + Hz, and offering real-time data evaluation. We show simultaneously acquired characterization data demonstrating performance equivalent to individual devices and sample in vivo measurements of pulsation resolved blood flow, forearm occlusion hemodynamic changes and muscle oxygen metabolic rate monitoring during stationary bike exercise.

Is there Place for Perfectionism in the NIR Spectral Data Reduction?

Science.gov (United States)

Chilingarian, Igor

2017-09-01

"Despite the crucial importance of the near-infrared spectral domain for understanding the star formation and galaxy evolution, NIR observations and data reduction represent a significant challenge. The known complexity of NIR detectors is aggravated by the airglow emission in the upper atmosphere and the water absorption in the troposphere so that up until now, the astronomical community is divided on the issue whether ground based NIR spectroscopy has a future or should it move completely to space (JWST, Euclid, WFIRST). I will share my experience of pipeline development for low- and intermediate-resolution spectrographs operated at Magellan and MMT. The MMIRS data reduction pipeline became the first example of the sky subtraction quality approaching the limit set by the Poisson photon noise and demonstrated the feasibility of low-resolution (R=1200-3000) NIR spectroscopy from the ground even for very faint (J=24.5) continuum sources. On the other hand, the FIRE Bright Source Pipeline developed specifically for high signal-to-noise intermediate resolution stellar spectra proves that systematics in the flux calibration and telluric absorption correction can be pushed down to the (sub-)percent level. My conclusion is that even though substantial effort and time investment is needed to design and develop NIR spectroscopic pipelines for ground based instruments, it will pay off, if done properly, and open new windows of opportunity in the ELT era."

Single-trial lie detection using a combined fNIRS-polygraph system

Science.gov (United States)

Bhutta, M. Raheel; Hong, Melissa J.; Kim, Yun-Hee; Hong, Keum-Shik

2015-01-01

Deception is a human behavior that many people experience in daily life. It involves complex neuronal activities in addition to several physiological changes in the body. A polygraph, which can measure some of the physiological responses from the body, has been widely employed in lie-detection. Many researchers, however, believe that lie detection can become more precise if the neuronal changes that occur in the process of deception can be isolated and measured. In this study, we combine both measures (i.e., physiological and neuronal changes) for enhanced lie-detection. Specifically, to investigate the deception-related hemodynamic response, functional near-infrared spectroscopy (fNIRS) is applied at the prefrontal cortex besides a commercially available polygraph system. A mock crime scenario with a single-trial stimulus is set up as a deception protocol. The acquired data are classified into “true” and “lie” classes based on the fNIRS-based hemoglobin-concentration changes and polygraph-based physiological signal changes. Linear discriminant analysis is utilized as a classifier. The results indicate that the combined fNIRS-polygraph system delivers much higher classification accuracy than that of a singular system. This study demonstrates a plausible solution toward single-trial lie-detection by combining fNIRS and the polygraph. PMID:26082733

Single-trial lie detection using a combined fNIRS-polygraph system

Directory of Open Access Journals (Sweden)

M. Raheel eBhutta

2015-06-01

Full Text Available Deception is a human behavior that many people experience in daily life. It involves complex neuronal activities in addition to several physiological changes in the body. A polygraph, which can measure some of the physiological responses from the body, has been widely employed in lie-detection. Many researchers, however, believe that lie detection can become more precise if the neuronal changes that occur in the process of deception can be isolated and measured. In this study, we combine both measures (i.e., physiological and neuronal changes for enhanced lie-detection. Specifically, to investigate the deception-related hemodynamic response, functional near-infrared spectroscopy (fNIRS is applied at the prefrontal cortex besides a commercially available polygraph system. A mock crime scenario with a single-trial stimulus is set up as a deception protocol. The acquired data are classified into true and lie classes based on the fNIRS-based hemoglobin-concentration changes and polygraph-based physiological signal changes. Linear discriminant analysis is utilized as a classifier. The results indicate that the combined fNIRS-polygraph system delivers much higher classification accuracy than that of a singular system. This study demonstrates a plausible solution toward single-trial lie-detection by combining fNIRS and the polygraph.

Cytochrome cd1-containing nitrite reductase encoding gene nirS as a new functional biomarker for detection of anaerobic ammonium oxidizing (Anammox) bacteria.

Science.gov (United States)

Li, Meng; Ford, Tim; Li, Xiaoyan; Gu, Ji-Dong

2011-04-15

A newly designed primer set (AnnirS), together with a previously published primer set (ScnirS), was used to detect anammox bacterial nirS genes from sediments collected from three marine environments. Phylogenetic analysis demonstrated that all retrieved sequences were clearly different from typical denitrifiers' nirS, but do group together with the known anammox bacterial nirS. Sequences targeted by ScnirS are closely related to Scalindua nirS genes recovered from the Peruvian oxygen minimum zone (OMZ), whereas sequences targeted by AnnirS are more closely affiliated with the nirS of Candidatus 'Kuenenia stuttgartiensis' and even form a new phylogenetic nirS clade, which might be related to other genera of the anammox bacteria. Analysis demonstrated that retrieved sequences had higher sequence identities (>60%) with known anammox bacterial nirS genes than with denitrifiers' nirS, on both nucleotide and amino acid levels. Compared to the 16S rRNA and hydrazine oxidoreductase (hzo) genes, the anammox bacterial nirS not only showed consistent phylogenetic relationships but also demonstrated more reliable quantification of anammox bacteria because of the single copy of the nirS gene in the anammox bacterial genome and the specificity of PCR primers for different genera of anammox bacteria, thus providing a suitable functional biomarker for investigation of anammox bacteria.

Relative Contribution of nirK- and nirS- Bacterial Denitrifiers as Well as Fungal Denitrifiers to Nitrous Oxide Production from Dairy Manure Compost.

Science.gov (United States)

Maeda, Koki; Toyoda, Sakae; Philippot, Laurent; Hattori, Shohei; Nakajima, Keiichi; Ito, Yumi; Yoshida, Naohiro

2017-12-19

The relative contribution of fungi, bacteria, and nirS and nirK denirifiers to nitrous oxide (N 2 O) emission with unknown isotopic signature from dairy manure compost was examined by selective inhibition techniques. Chloramphenicol (CHP), cycloheximide (CYH), and diethyl dithiocarbamate (DDTC) were used to suppress the activity of bacteria, fungi, and nirK-possessing denitrifiers, respectively. Produced N 2 O were surveyed to isotopocule analysis, and its 15 N site preference (SP) and δ 18 O values were compared. Bacteria, fungi, nirS, and nirK gene abundances were compared by qPCR. The results showed that N 2 O production was strongly inhibited by CHP addition in surface pile samples (82.2%) as well as in nitrite-amended core samples (98.4%), while CYH addition did not inhibit the N 2 O production. N 2 O with unknown isotopic signature (SP = 15.3-16.2‰), accompanied by δ 18 O (19.0-26.8‰) values which were close to bacterial denitrification, was also suppressed by CHP and DDTC addition (95.3%) indicating that nirK denitrifiers were responsible for this N 2 O production despite being less abundant than nirS denitrifiers. Altogether, our results suggest that bacteria are important for N 2 O production with different SP values both from compost surface and pile core. However, further work is required to decipher whether N 2 O with unknown isotopic signature is mostly due to nirK denitrifiers that are taxonomically different from the SP-characterized strains and therefore have different SP values rather than also being interwoven with the contribution of the NO-detoxifying pathway and/or of co-denitrification.

Single seed NIR as a fast method to predict germination ability in Pak Choi

DEFF Research Database (Denmark)

Gislum, René; Deleuran, Lise Christina; Olesen, Merete Halkjær

2012-01-01

Single seed NIR has further been tested to determine the applicability for prediction of seed viability in radish (Raphanus sativus L.) seeds and spinach (Spinacia oleracea L.) seeds. The studies show the possibility of using NIR spectroscopy in a seed separating process in the future, provided...

The critical role of NIR spectroscopy and statistical process control (SPC) strategy towards captopril tablets (25 mg) manufacturing process understanding: a case study.

Science.gov (United States)

Curtivo, Cátia Panizzon Dal; Funghi, Nathália Bitencourt; Tavares, Guilherme Diniz; Barbosa, Sávio Fujita; Löbenberg, Raimar; Bou-Chacra, Nádia Araci

2015-05-01

In this work, near-infrared spectroscopy (NIRS) method was used to evaluate the uniformity of dosage units of three captopril 25 mg tablets commercial batches. The performance of the calibration method was assessed by determination of Q value (0.9986), standard error of estimation (C-set SEE = 1.956), standard error of prediction (V-set SEP = 2.076) as well as the consistency (106.1%). These results indicated the adequacy of the selected model. The method validation revealed the agreement of the reference high pressure liquid chromatography (HPLC) and NIRS methods. The process evaluation using the NIRS method showed that the variability was due to common causes and delivered predictable results consistently. Cp and Cpk values were, respectively, 2.05 and 1.80. These results revealed a non-centered process in relation to the average target (100% w/w), in the specified range (85-115%). The probability of failure was 21:100 million tablets of captopril. The NIRS in combination with the method of multivariate calibration, partial least squares (PLS) regression, allowed the development of methodology for the uniformity of dosage units evaluation of captopril tablets 25 mg. The statistical process control strategy associated with NIRS method as PAT played a critical role in understanding of the sources and degree of variation and its impact on the process. This approach led towards a better process understanding and provided the sound scientific basis for its continuous improvement.

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.

NirN Protein from Pseudomonas aeruginosa is a Novel Electron-bifurcating Dehydrogenase Catalyzing the Last Step of Heme d1 Biosynthesis*

Science.gov (United States)

Adamczack, Julia; Hoffmann, Martin; Papke, Ulrich; Haufschildt, Kristin; Nicke, Tristan; Bröring, Martin; Sezer, Murat; Weimar, Rebecca; Kuhlmann, Uwe; Hildebrandt, Peter; Layer, Gunhild

2014-01-01

Heme d1 plays an important role in denitrification as the essential cofactor of the cytochrome cd1 nitrite reductase NirS. At present, the biosynthesis of heme d1 is only partially understood. The last step of heme d1 biosynthesis requires a so far unknown enzyme that catalyzes the introduction of a double bond into one of the propionate side chains of the tetrapyrrole yielding the corresponding acrylate side chain. In this study, we show that a Pseudomonas aeruginosa PAO1 strain lacking the NirN protein does not produce heme d1. Instead, the NirS purified from this strain contains the heme d1 precursor dihydro-heme d1 lacking the acrylic double bond, as indicated by UV-visible absorption spectroscopy and resonance Raman spectroscopy. Furthermore, the dihydro-heme d1 was extracted from purified NirS and characterized by UV-visible absorption spectroscopy and finally identified by high-resolution electrospray ionization mass spectrometry. Moreover, we show that purified NirN from P. aeruginosa binds the dihydro-heme d1 and catalyzes the introduction of the acrylic double bond in vitro. Strikingly, NirN uses an electron bifurcation mechanism for the two-electron oxidation reaction, during which one electron ends up on its heme c cofactor and the second electron reduces the substrate/product from the ferric to the ferrous state. On the basis of our results, we propose novel roles for the proteins NirN and NirF during the biosynthesis of heme d1. PMID:25204657

APPLICATION OF NEAR INFRARED SPECTROSCOPY AND EXPLORATORY DATA ANALYSIS FOR THE IDENTIFICATION OF WOODS IN THE FURNITURE INDUSTRY

Directory of Open Access Journals (Sweden)

Lucas Ferreira Bastos

2012-07-01

Full Text Available The paper aimed to investigate the application of infrared spectroscopy and exploratory data analysis to distinguish the different types of natural woods, contributing to the control of the origin of the materials used in the furniture industry. The near infrared spectroscopy (NIR was used for the characterization of 44 samples of 19 different types of wood, and the principal component analysis (PCA to discriminate. The proposed methodology was efficient in the separation of some samples, but further studies should be performed for the diffusion of this methodology in the routine of the furniture industry.

Greenhouse cooling by NIR-reflection

NARCIS (Netherlands)

Hemming, S.; Kempkes, F.; Braak, van der N.; Dueck, T.A.; Marissen, A.

2007-01-01

Wageningen UR investigated the potential of several NIR-filtering methods to be applied in horticulture. In this paper the analysis of the optical properties of available NIR-filtering materials is given including a calculation method to quantify the energy reduction under these materials and to

[Identification of varieties of cashmere by Vis/NIR spectroscopy technology based on PCA-SVM].

Science.gov (United States)

Wu, Gui-Fang; He, Yong

2009-06-01

One mixed algorithm was presented to discriminate cashmere varieties with principal component analysis (PCA) and support vector machine (SVM). Cashmere fiber has such characteristics as threadlike, softness, glossiness and high tensile strength. The quality characters and economic value of each breed of cashmere are very different. In order to safeguard the consumer's rights and guarantee the quality of cashmere product, quickly, efficiently and correctly identifying cashmere has significant meaning to the production and transaction of cashmere material. The present research adopts Vis/NIRS spectroscopy diffuse techniques to collect the spectral data of cashmere. The near infrared fingerprint of cashmere was acquired by principal component analysis (PCA), and support vector machine (SVM) methods were used to further identify the cashmere material. The result of PCA indicated that the score map made by the scores of PC1, PC2 and PC3 was used, and 10 principal components (PCs) were selected as the input of support vector machine (SVM) based on the reliabilities of PCs of 99.99%. One hundred cashmere samples were used for calibration and the remaining 75 cashmere samples were used for validation. A one-against-all multi-class SVM model was built, the capabilities of SVM with different kernel function were comparatively analyzed, and the result showed that SVM possessing with the Gaussian kernel function has the best identification capabilities with the accuracy of 100%. This research indicated that the data mining method of PCA-SVM has a good identification effect, and can work as a new method for rapid identification of cashmere material varieties.

The effects of water and lipids on NIR optical breast measurements

Science.gov (United States)

Cerussi, Albert E.; Bevilacqua, Frederic; Shah, Natasha; Jakubowski, Dorota B.; Berger, Andrew J.; Lanning, Ryan M.; Tromberg, Bruce J.

2001-06-01

Near infrared diffuse optical spectroscopy and imaging may enhance existing technologies for breast cancer screening, diagnosis, and treatment. NIR spectroscopy yields quantitative functional information that cannot be obtained with other non-invasive radiological techniques. In this study we focused upon the origins of this contrast in healthy breast, especially from water and lipids.

Community Structure of Denitrifiers, Bacteria, and Archaea along Redox Gradients in Pacific Northwest Marine Sediments by Terminal Restriction Fragment Length Polymorphism Analysis of Amplified Nitrite Reductase (nirS) and 16S rRNA Genes

Science.gov (United States)

Braker, Gesche; Ayala-del-Río, Héctor L.; Devol, Allan H.; Fesefeldt, Andreas; Tiedje, James M.

2001-01-01

Steep vertical gradients of oxidants (O2 and NO3−) in Puget Sound and Washington continental margin sediments indicate that aerobic respiration and denitrification occur within the top few millimeters to centimeters. To systematically explore the underlying communities of denitrifiers, Bacteria, and Archaea along redox gradients at distant geographic locations, nitrite reductase (nirS) genes and bacterial and archaeal 16S rRNA genes (rDNAs) were PCR amplified and analyzed by terminal restriction fragment length polymorphism (T-RFLP) analysis. The suitablility of T-RFLP analysis for investigating communities of nirS-containing denitrifiers was established by the correspondence of dominant terminal restriction fragments (T-RFs) of nirS to computer-simulated T-RFs of nirS clones. These clones belonged to clusters II, III, and IV from the same cores and were analyzed in a previous study (G. Braker, J. Zhou, L. Wu, A. H. Devol, and J. M. Tiedje, Appl. Environ. Microbiol. 66:2096–2104, 2000). T-RFLP analysis of nirS and bacterial rDNA revealed a high level of functional and phylogenetic diversity, whereas the level of diversity of Archaea was lower. A comparison of T-RFLPs based on the presence or absence of T-RFs and correspondence analysis based on the frequencies and heights of T-RFs allowed us to group sediment samples according to the sampling location and thus clearly distinguish Puget Sound and the Washington margin populations. However, changes in community structure within sediment core sections during the transition from aerobic to anaerobic conditions were minor. Thus, within the top layers of marine sediments, redox gradients seem to result from the differential metabolic activities of populations of similar communities, probably through mixing by marine invertebrates rather than from the development of distinct communities. PMID:11282647

Field detection of CO and CH4 by NIR 2f modulation laser spectroscopy

Directory of Open Access Journals (Sweden)

A Khorsandi

2011-12-01

Full Text Available   A novel compact fiber-coupled NIR system based on a DFB diode laser source is employed as a portable and sensitive gas sensor for trace detection of combustion pollutant molecules. We demonstrate the performance of such an NIR gas sensor by tracing the absorption lines of CO and CH4 using 2f-WMS technique at moderate temperature of T ~ 600°C in the recuperator channel of an industrial furnace provided by Mobarakeh steel company. This measurement shows the excellent sensitivity of the applied NIR gas sensor to the on-line and in-situ monitoring of such molecular species.

Discrimination of Wild Paris Based on Near Infrared Spectroscopy and High Performance Liquid Chromatography Combined with Multivariate Analysis

Science.gov (United States)

Zhao, Yanli; Zhang, Ji; Yuan, Tianjun; Shen, Tao; Li, Wei; Yang, Shihua; Hou, Ying; Wang, Yuanzhong; Jin, Hang

2014-01-01

Different geographical origins and species of Paris obtained from southwestern China were discriminated by near infrared (NIR) spectroscopy and high performance liquid chromatography (HPLC) combined with multivariate analysis. The NIR parameter settings were scanning (64 times), resolution (4 cm−1), scanning range (10000 cm−1∼4000 cm−1) and parallel collection (3 times). NIR spectrum was optimized by TQ 8.6 software, and the ranges 7455∼6852 cm−1 and 5973∼4007 cm−1 were selected according to the spectrum standard deviation. The contents of polyphyllin I, polyphyllin II, polyphyllin VI, and polyphyllin VII and total steroid saponins were detected by HPLC. The contents of chemical components data matrix and spectrum data matrix were integrated and analyzed by partial least squares discriminant analysis (PLS-DA). From the PLS-DA model of NIR spectrum, Paris samples were separated into three groups according to the different geographical origins. The R2X and Q2Y described accumulative contribution rates were 99.50% and 94.03% of the total variance, respectively. The PLS-DA model according to 12 species of Paris described 99.62% of the variation in X and predicted 95.23% in Y. The results of the contents of chemical components described differences among collections quantitatively. A multivariate statistical model of PLS-DA showed geographical origins of Paris had a much greater influence on Paris compared with species. NIR and HPLC combined with multivariate analysis could discriminate different geographical origins and different species. The quality of Paris showed regional dependence. PMID:24558477

Near-infrared spectroscopy (NIRS) for a real time monitoring of the biogas process.

Science.gov (United States)

Stockl, Andrea; Lichti, Fabian

2018-01-01

In this research project Near-infrared spectroscopy (NIRS) was applied to monitor the content of specific process parameters in anaerobic digestion. A laboratory scaled biogas digester was constantly fed every four hours with maize- and grass silage to keep a base load with an organic loading rate (OLR) of 2.5 kg oDM/m 3  ∗ d. Daily impact loads with shredded wheat up to an OLR of 8 kg oDM/m 3  ∗ d were added in order to generate peaks at the parameters tested. The developed calibration models are capable to show changes in process parameters like volatile fatty acids (VFA), propionic acid, total inorganic carbon (TIC) and the ratio of the volatile fatty acids to the carbonate buffer (VFA/TIC). Based on the calibration of the models for VFA and TIC, the values could be predicted with an R 2 of 0.94 and 0.97, respectively. Moreover, the residual prediction deviations were 4.0 and 6.0 for VFA and TIC, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

In vivo near infrared (NIRS) sensor attachment using fibrin bioadhesive

Science.gov (United States)

Macnab, Andrew; Pagano, Roberto; Kwon, Brian; Dumont, Guy; Shadgan, Babak

2018-02-01

Background: `Tisseel' (Baxter Healthcare, Deerfield, IL) is a fibrin-based sealant that is commonly used during spine surgery to augment dural repairs. We wish to intra-operatively secure a near infrared spectroscopy (NIRS) sensor to the dura in order to monitor the tissue hemodynamics of the underlying spinal cord. To determine if `Tisseel' sealant adversely attenuates NIR photon transmission. Methods: We investigated `Tisseel' in both an in vitro and in vivo paradigm. For in vitro testing, we used a 1 mm pathlength cuvette containing either air or `Tisseel' interposed between a NIR light source (760 and 850 nm) and a photodiode detector and compared transmittance. For in vivo testing, a continuous wave (760 and 850 nm) spatiallyresolved NIRS device was placed over the triceps muscle using either conventional skin apposition (overlying adhesive bandage) or bioadhesion with `Tisseel'. Raw optical data and tissue saturation index (TSI%) collected at rest were compared. Results: In-vitro NIR light absorption by `Tisseel' was very high, with transmittance reduced by 95% compared to air. In-vivo muscle TSI% values were 80% with conventional attachment and 20% using fibrin glue. Conclusion: The optical properties of `Tisseel' significantly attenuate NIR light during in-vitro transmittance and critically compromise photon transmission in-vivo.

Characterisation of Castor (Ricinus communis L. Seed Quality Using Fourier Transform Near-Infrared Spectroscopy in Combination with Multivariate Data Analysis

Directory of Open Access Journals (Sweden)

René Gislum

2018-04-01

Full Text Available The potential of single-seed near-infrared (NIR spectroscopy was investigated to characterise castor seeds based on their seed viability and seed oil content. Distinct differences between viable and non-viable seeds were observed in the principal component analysis (PCA analysis. Furthermore, the PCA compared heavy and medium seeds with light seeds, which were comparable to the clusters of viable and non-viable seeds, respectively. Prediction accuracies of 98.7% and 99.6% were obtained with the partial least squares discriminant analysis (PLS-DA model with a classification error rate of 0.8% and 1.1% for the training set and test set, respectively. The NIR spectral regions having chemical information from the oil in castor seeds were found to be vital for determination of seed viability.

[Prediction of the side-cut product yield of atmospheric/vacuum distillation unit by NIR crude oil rapid assay].

Science.gov (United States)

Wang, Yan-Bin; Hu, Yu-Zhong; Li, Wen-Le; Zhang, Wei-Song; Zhou, Feng; Luo, Zhi

2014-10-01

In the present paper, based on the fast evaluation technique of near infrared, a method to predict the yield of atmos- pheric and vacuum line was developed, combined with H/CAMS software. Firstly, the near-infrared (NIR) spectroscopy method for rapidly determining the true boiling point of crude oil was developed. With commercially available crude oil spectroscopy da- tabase and experiments test from Guangxi Petrochemical Company, calibration model was established and a topological method was used as the calibration. The model can be employed to predict the true boiling point of crude oil. Secondly, the true boiling point based on NIR rapid assay was converted to the side-cut product yield of atmospheric/vacuum distillation unit by H/CAMS software. The predicted yield and the actual yield of distillation product for naphtha, diesel, wax and residual oil were compared in a 7-month period. The result showed that the NIR rapid crude assay can predict the side-cut product yield accurately. The near infrared analytic method for predicting yield has the advantages of fast analysis, reliable results, and being easy to online operate, and it can provide elementary data for refinery planning optimization and crude oil blending.

Dynamic Filtering Improves Attentional State Prediction with fNIRS

Science.gov (United States)

Harrivel, Angela R.; Weissman, Daniel H.; Noll, Douglas C.; Huppert, Theodore; Peltier, Scott J.

2016-01-01

Brain activity can predict a person's level of engagement in an attentional task. However, estimates of brain activity are often confounded by measurement artifacts and systemic physiological noise. The optimal method for filtering this noise - thereby increasing such state prediction accuracy - remains unclear. To investigate this, we asked study participants to perform an attentional task while we monitored their brain activity with functional near infrared spectroscopy (fNIRS). We observed higher state prediction accuracy when noise in the fNIRS hemoglobin [Hb] signals was filtered with a non-stationary (adaptive) model as compared to static regression (84% +/- 6% versus 72% +/- 15%).

Interference Tolerant Functional Near Infrared Spectrometer (fNIRS) for Cognitive State Monitoring

Data.gov (United States)

National Aeronautics and Space Administration — Measuring hemoglobin concentration changes in the brain with Functional Near Infrared Spectroscopy (fNIRS) is a promising technique for monitoring cognitive state...

Measurement of neuronal activity in a macaque monkey in response to animate images using near-infrared spectroscopy (NIRS

Directory of Open Access Journals (Sweden)

Masumi Wakita

2010-06-01

Full Text Available Near-infrared spectroscopy (NIRS has been used extensively for functional neuroimaging over the past decade, in part because it is considered a powerful tool for investigating brain function in human infants and young children, for whom other neuroimaging techniques are not suitable. In particular, several studies have measured hemodynamic responses in the occipital region in infants upon exposure to visual stimuli. In the present study, we used a multi-channel NIRS to measure neuronal activity in a macaque monkey who was trained to watch videos showing various circus animals performing acrobatic activities without fixing the head position of the monkey. Cortical activity from the occipital region was measured first by placing a probe comprising a 3x5 array of emitters and detectors (2 x 4 cm on the area (area 17, and the robustness and stability of the results were confirmed across sessions. Cortical responses were then measured from the dorsofrontal region. The oxygenated hemoglobin signals increased in area 9 and decreased in area 8b in response to viewing the videos. The results suggest that these regions are involved in cognitive processing of visually presented stimuli. The monkey showed positive responsiveness to the stimuli from the affective standpoint, but its attentional response to them was an inhibitory one.

Instrumentation and method for measuring NIR light absorbed in tissue during MR imaging in medical NIRS measurements

Science.gov (United States)

Myllylä, Teemu S.; Sorvoja, Hannu S. S.; Nikkinen, Juha; Tervonen, Osmo; Kiviniemi, Vesa; Myllylä, Risto A.

2011-07-01

Our goal is to provide a cost-effective method for examining human tissue, particularly the brain, by the simultaneous use of functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS). Due to its compatibility requirements, MRI poses a demanding challenge for NIRS measurements. This paper focuses particularly on presenting the instrumentation and a method for the non-invasive measurement of NIR light absorbed in human tissue during MR imaging. One practical method to avoid disturbances in MR imaging involves using long fibre bundles to enable conducting the measurements at some distance from the MRI scanner. This setup serves in fact a dual purpose, since also the NIRS device will be less disturbed by the MRI scanner. However, measurements based on long fibre bundles suffer from light attenuation. Furthermore, because one of our primary goals was to make the measuring method as cost-effective as possible, we used high-power light emitting diodes instead of more expensive lasers. The use of LEDs, however, limits the maximum output power which can be extracted to illuminate the tissue. To meet these requirements, we improved methods of emitting light sufficiently deep into tissue. We also show how to measure NIR light of a very small power level that scatters from the tissue in the MRI environment, which is characterized by strong electromagnetic interference. In this paper, we present the implemented instrumentation and measuring method and report on test measurements conducted during MRI scanning. These measurements were performed in MRI operating rooms housing 1.5 Tesla-strength closed MRI scanners (manufactured by GE) in the Dept. of Diagnostic Radiology at the Oulu University Hospital.

Sensitivity of fNIRS to cognitive state and load

Directory of Open Access Journals (Sweden)

Frank Anthony Fishburn

2014-02-01

Full Text Available Functional near-infrared spectroscopy (fNIRS is an emerging low-cost noninvasive neuroimaging technique that measures cortical bloodflow. While fNIRS has gained interest as a potential alternative to fMRI for use with clinical and pediatric populations, it remains unclear whether fNIRS has the necessary sensitivity to serve as a replacement for fMRI. The present study set out to examine whether fNIRS has the sensitivity to detect linear changes in activation and functional connectivity in response to cognitive load, and functional connectivity changes when transitioning from a task-free resting state to a task. Sixteen young adult subjects were scanned with a continuous-wave fNIRS system during a 10-minute resting-state scan followed by a letter n-back task with three load conditions. Five optical probes were placed over frontal and parietal cortices, covering bilateral dorsolateral PFC (dlPFC, bilateral ventrolateral PFC (vlPFC, frontopolar cortex (FP, and bilateral parietal cortex. Activation was found to scale linearly with working memory load in bilateral prefrontal cortex. Functional connectivity increased with increasing n-back loads for fronto-parietal, interhemispheric dlPFC, and local connections. Functional connectivity differed between the resting state scan and the n-back scan, with fronto-parietal connectivity greater during the n-back, and interhemispheric vlPFC connectivity greater during rest. These results demonstrate that fNIRS is sensitive to both cognitive load and state, suggesting that fNIRS is well-suited to explore the full complement of neuroimaging research questions and will serve as a viable alternative to fMRI.

Near-Infrared Spectroscopy Analysis of Heavy Fuel Oils Using a New Diffusing Support.

Science.gov (United States)

Dupuy, Nathalie; Brahem, Zeineb; Amat, Sandrine; Kister, Jacky

2015-10-01

The characterization of heavy fuel oils (HFOs), used as fuel for boats, requires the analysis of various properties that are essential for engine optimization and pollution control. For some time, near-infrared (NIR) spectroscopy combined with chemometric treatment of the spectra was used for on-line analysis. This preliminary study included 61 heavy fuels from Europe, America, and Asia with different specifications according to their geographical origin; their refining process; and their physicochemical properties, including density, flash point, viscosity, and sulfur content. We have developed a new method for sampling heavy fuels on a fiberglass cell support. This support offers the advantages of speed, easy implementation, repeatable results, and freedom from problems associated with tank cleaning. Two sample presentations, an integrating sphere and an optical fiber, were used to collect the NIR spectra. A theoretical study of the choice of the value of resolution, scan number, and spectral region was conducted. The best conditions were chosen as a function of the quality of quantitative analysis results on viscosity, sulfur content, flash point, and density. The two collecting methods were compared on the same criteria.

Brain and muscle oxygenation monitoring using near-infrared spectroscopy (NIRS) during all-night sleep

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Zhang, Zhongxing; Khatami, Ramin

2013-03-01

The hemodynamic changes during natural human sleep are still not well understood. NIRS is ideally suited for monitoring the hemodynamic changes during sleep due to the properties of local measurement, totally safe application and good tolerance to motion. Several studies have been conducted using NIRS in both normal subjects and patients with various sleep disorders during sleep to characterize the hemodynamic changing patterns during different sleep stages and during different symptoms such as obstructive apneas. Here we assessed brain and muscle oxygenation changes in 7 healthy adults during all-night sleep with combined polysomnography measurement to test the notion if hemodynamic changes in sleep are indeed brain specific. We found that muscle and brain showed similar hemodynamic changes during sleep initiation. A decrease in HbO2 and tissue oxygenation index (TOI) while an increase in HHb was observed immediately after sleep onset, and an opposite trend was found after transition with progression to deeper slow-wave sleep (SWS) stage. Spontaneous low frequency oscillations (LFO) and very low frequency oscillations (VLFO) were smaller (Levene's test, psleep (LS) and rapid-eye-movement (REM) sleep in both brain and muscle. Spectral analysis of the NIRS signals measured from brain and muscle also showed reductions in VLFO and LFO powers during SWS with respect to LS and REM sleep. These results indicate a systemic attenuation rather than local cerebral reduction of spontaneous hemodynamic activity in SWS. A systemic physiological mechanism may exist to regulate the hemodynamic changes in brain and muscle during sleep.

Non-invasive real-time monitoring of vineyard soils, berries and leaves with FT-NIR spectroscopy

Directory of Open Access Journals (Sweden)

Lopo Miguel

2015-01-01

Full Text Available Production of high quality wines requires a permanent monitoring during the entire winemaking process. A healthy production, ensured by tailor-made strategies that will lead to consumer's satisfaction is of the utmost importance. The influence of the terroir characteristics on the features of a wine has always been prone to much debate amongst the wine industry. The composition of grapes is the result of the characteristics of each individual terroir. Soil impact on growth of the vineyard, grape variety characteristics and ultimately wine quality is well known. Current strategy for analysing soils (pedology is based on wet chemistry methods, which are often laborious, expensive, time-consuming and may be of limited use. An efficient, high-throughput analytical method for estimating the impact of soil quality, tillage and thinning on the grapes quality is of paramount importance for the wine industry. Near infrared spectroscopy (NIRS is a rapid, non-destructive, inexpensive and accurate analysis technique and its use in soil evaluation for discriminating different types of soil as well as soil constituents is rapidly increasing. Results obtained from direct monitoring of four Portuguese vineyards in different locations (wine appellation regions “Alentejo”, “Dão”, “Douro” and “Vinhos Verdes” using two different portable near-infrared spectrometers are presented. In-situ measurements of soils (at different depths, plant leaves and berries were performed on different stages of the ripening period. Spectral analysis was performed with chemometric methods: PCA and PLS-DA. This monitoring approach revealed to be an excellent tool for the support of a vineyard's micro-zoning process.

Real-time monitoring of a coffee roasting process with near infrared spectroscopy using multivariate statistical analysis: A feasibility study.

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Catelani, Tiago A; Santos, João Rodrigo; Páscoa, Ricardo N M J; Pezza, Leonardo; Pezza, Helena R; Lopes, João A

2018-03-01

This work proposes the use of near infrared (NIR) spectroscopy in diffuse reflectance mode and multivariate statistical process control (MSPC) based on principal component analysis (PCA) for real-time monitoring of the coffee roasting process. The main objective was the development of a MSPC methodology able to early detect disturbances to the roasting process resourcing to real-time acquisition of NIR spectra. A total of fifteen roasting batches were defined according to an experimental design to develop the MSPC models. This methodology was tested on a set of five batches where disturbances of different nature were imposed to simulate real faulty situations. Some of these batches were used to optimize the model while the remaining was used to test the methodology. A modelling strategy based on a time sliding window provided the best results in terms of distinguishing batches with and without disturbances, resourcing to typical MSPC charts: Hotelling's T 2 and squared predicted error statistics. A PCA model encompassing a time window of four minutes with three principal components was able to efficiently detect all disturbances assayed. NIR spectroscopy combined with the MSPC approach proved to be an adequate auxiliary tool for coffee roasters to detect faults in a conventional roasting process in real-time. Copyright © 2017 Elsevier B.V. All rights reserved.

PAT: From Western solid dosage forms to Chinese materia medica preparations using NIR-CI.

Science.gov (United States)

Zhou, Luwei; Xu, Manfei; Wu, Zhisheng; Shi, Xinyuan; Qiao, Yanjiang

2016-01-01

Near-infrared chemical imaging (NIR-CI) is an emerging technology that combines traditional near-infrared spectroscopy with chemical imaging. Therefore, NIR-CI can extract spectral information from pharmaceutical products and simultaneously visualize the spatial distribution of chemical components. The rapid and non-destructive features of NIR-CI make it an attractive process analytical technology (PAT) for identifying and monitoring critical control parameters during the pharmaceutical manufacturing process. This review mainly focuses on the pharmaceutical applications of NIR-CI in each unit operation during the manufacturing processes, from the Western solid dosage forms to the Chinese materia medica preparations. Finally, future applications of chemical imaging in the pharmaceutical industry are discussed. Copyright © 2015 John Wiley & Sons, Ltd.

Simulated In Situ Determination of Soil Profile Organic and Inorganic Carbon With LIBS and VisNIR

Science.gov (United States)

Bricklemyer, R. S.; Brown, D. J.; Clegg, S. M.; Barefield, J. E.

2008-12-01

There is growing need for rapid, accurate, and inexpensive methods to measure, and verify soil organic carbon (SOC) change for national greenhouse gas accounting and the development of a soil carbon trading market. Laser Induced Breakdown Spectroscopy (LIBS) and Visible and Near Infrared Spectroscopy (VisNIR) are complementary analytical techniques that have the potential to fill that need. The LIBS method provides precise elemental analysis of soils, but generally cannot distinguish between organic C and inorganic C. VisNIR has been established as a viable technique for measuring soil properties including SOC and inorganic carbon (IC). As part of the Big Sky Carbon Sequestration Regional Partnership, 240 intact core samples (3.8 x 50 cm) have been collected from six agricultural fields in north central Montana, USA. Each of these core samples were probed concurrently with LIBS and VisNIR at 2.5, 7.5, 12.5, 17.5, 22.5, 27.5, 35 and 45 cm (+/- 1.5 cm) depths. VisNIR measurements were taken using an Analytical Spectral Devices (ASD, Boulder, CO, USA) Agrispec spectrometer to determine the partition of SOC vs. IC in the samples. The LIBS scans were collected with the LANL LIBS Core Scanner Instrument which collected the entire 200 - 900 nm plasma emission including the 247.8 nm carbon emission line. This instrument also collected the emission from the elements typically found in inorganic carbon (Ca and Mg) and organic carbon (H, O, and N). Subsamples of soil (~ 4 g) were taken from interrogation points for laboratory determination of SOC and IC. Using this analytical data, we constructed several full spectrum multivariate VisNIR/LIBS calibration models for SOC and IC. These models were then applied to independent validation cores for model evaluation.

Analysis of ecstasy tablets: comparison of reflectance and transmittance near infrared spectroscopy.

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Schneider, Ralph Carsten; Kovar, Karl-Artur

2003-07-08

Calibration models for the quantitation of commonly used ecstasy substances have been developed using near infrared spectroscopy (NIR) in diffuse reflectance and in transmission mode by applying seized ecstasy tablets for model building and validation. The samples contained amphetamine, N-methyl-3,4-methylenedioxy-amphetamine (MDMA) and N-ethyl-3,4-methylenedioxy-amphetamine (MDE) in different concentrations. All tablets were analyzed using high performance liquid chromatography (HPLC) with diode array detection as reference method. We evaluated the performance of each NIR measurement method with regard to its ability to predict the content of each tablet with a low root mean square error of prediction (RMSEP). Best calibration models could be generated by using NIR measurement in transmittance mode with wavelength selection and 1/x-transformation of the raw data. The models build in reflectance mode showed higher RMSEPs using as data pretreatment, wavelength selection, 1/x-transformation and a second order Savitzky-Golay derivative with five point smoothing was applied to obtain the best models. To estimate the influence of inhomogeneities in the illegal tablets, a calibration of the destroyed, i.e. triturated samples was build and compared to the corresponding data of the whole tablets. The calibrations using these homogenized tablets showed lower RMSEPs. We can conclude that NIR analysis of ecstasy tablets in transmission mode is more suitable than measurement in diffuse reflectance to obtain quantification models for their active ingredients with regard to low errors of prediction. Inhomogeneities in the samples are equalized when measuring the tablets as powdered samples.

Assessing Risk of Fumonisin Contamination in Maize Using Near-Infrared Spectroscopy

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Cecile Levasseur-Garcia

2015-01-01

Full Text Available Fumonisins are major mycotoxins found worldwide in maize and maize products. Because of their toxicity for both human and animals, European Union regulations were created to fix the maximal fumonisin B1 and B2 content allowed in foods and feeds. Unfortunately, directly measuring these mycotoxins by current analytical techniques is tedious and expensive and most measurement methods do not lend themselves to online control. Alternative approaches to chemical analysis have been developed and involve models that allow the mycotoxin contamination to be predicted based on environmental conditions and analysis by near-infrared (NIR spectroscopy. In the present work, we use NIR spectroscopy to determine the fumonisin and fungal contents of 117 samples of maize. The determination coefficient between fumonisin and fungal-biomass content was 0.44. We establish herein a threshold for the number of CFUs for fungal biomass beyond which the fumonisin content is likely to exceed the European regulatory level of 4000 μg/kg. In addition, we determine the fungal content by using a NIR-spectroscopy model that allows us to sort samples of maize. Upon calibration, the percentage of well-classified samples was 96%, which compares favorably to the 82% obtained by independent verification.

Potential of VIS-NIR-SWIR Spectroscopy from the Chinese Soil Spectral Library for Assessment of Nitrogen Fertilization Rates in the Paddy-Rice Region, China

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Shuo Li

2015-05-01

Full Text Available To meet growing food demand with limited land and reduced environmental impact, soil testing and formulated fertilization methods have been widely adopted around the world. However, conventional technology for investigating nitrogen fertilization rates (NFR is time consuming and expensive. Here, we evaluated the use of visible near-infrared shortwave-infrared (VIS-NIR-SWIR: 400–2500 nm spectroscopy for the assessment of NFR to provide necessary information for fast, cost-effective and precise fertilization rating. Over 2000 samples were collected from paddy-rice fields in 10 Chinese provinces; samples were added to the Chinese Soil Spectral Library (CSSL. Two kinds of modeling strategies for NFR, quantitative estimation of soil N prior to classification and qualitative by classification, were employed using partial least squares regression (PLSR, locally weighted regression (LWR, and support vector machine discriminant analogy (SVMDA. Overall, both LWR and SVMDA had moderate accuracies with Cohen’s kappa coefficients of 0.47 and 0.48, respectively, while PLSR had fair accuracy (0.37. We conclude that VIS-NIR-SWIR spectroscopy coupled with the CSSL appears to be a viable, rapid means for the assessment of NFR in paddy-rice soil. Based on qualitative classification of soil spectral data only, it is recommended that the SVMDA be adopted for rapid implementation.

Rheo-optical near-infrared (NIR) spectroscopy study of partially miscible polymer blend of polymethyl methacrylate (PMMA) and polyethylene glycol (PEG)

Science.gov (United States)

Shinzawa, Hideyuki; Mizukado, Junji

2018-03-01

Tensile deformations of a partially miscible blend of polymethyl methacrylate (PMMA) and polyethylene glycol (PEG) is studied by a rheo-optical characterization near-infrared (NIR) technique to probe deformation behavior during tensile deformation. Sets of NIR spectra of the polymer samples were collected by using an acousto-optic tunable filter (AOTF) NIR spectrometer coupled with a tensile testing machine as an excitation device. While deformations of the samples were readily captured as strain-dependent NIR spectra, the entire feature of the spectra was overwhelmed with the baseline fluctuation induced by the decrease in the sample thickness and subsequent change in the light scattering. Several pretreatment techniques, including multiplicative scatter collection (MSC) and null-space projection, are subjected to the NIR spectra prior to the determination of the sequential order of the spectral intensity changes by two-dimensional (2D) correlation analysis. The comparison of the MSC and null-space projection provided an interesting insight into the system, especially deformation-induced variation of light scattering observed during the tensile testing of the polymer sample. In addition, the sequential order determined with the 2D correlation spectra revealed that orientation of a specific part of PMMA chain occurs before that of the others because of the interaction between Cdbnd O group of PMMA and terminal sbnd OH group of PEG.

IN-VIVO DIAGNOSIS OF CHEMICALLY INDUCED MELANOMA IN AN ANIMAL MODEL USING UV-VISIBLE AND NIR ELASTIC SCATTERING SPECTROSCOPY: PRELIMINARY TESTING.

Energy Technology Data Exchange (ETDEWEB)

C. A' AMAR; R. LEY; ET AL

2001-01-01

Elastic light scattering spectroscopy (ESS) has the potential to provide spectra that contain both morphological and chromophore information from tissue. We report on a preliminary study of this technique, with the hope of developing a method for diagnosis of highly-pigmented skin lesions, commonly associated with skin cancer. Four opossums were treated with dimethylbenz(a)anthracene to induce both malignant melanoma and benign pigmented lesions. Skin lesions were examined in vivo using both UV-visible and near infrared (NIR) ESS, with wavelength ranges of 330-900 nm and 900-1700 nm, respectively. Both portable systems used identical fiber-optic probe geometry throughout all of the measurements. The core diameters for illuminating and collecting fibers were 400 and 200 {micro}m, respectively, with center-to-center separation of 350 {micro}m. The probe was placed in optical contact with the tissue under investigation. Biopsies from lesions were analyzed by two standard histopathological procedures. Taking into account only the biopsied lesions, UV-visible ESS showed distinct spectral correlation for 11/13 lesions. The NIR-ESS correlated well with 12/13 lesions correctly. The results of these experiments showed that UV-visible and NIR-ESS have the potential to classify benign and malignant skin lesions, with encouraging agreement to that provided by standard histopathological examination. These initial results show potential for ESS based diagnosis of pigmented skin lesions, but further trials are required in order to substantiate the technique.

[The NIR spectra based variety discrimination for single soybean seed].

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Zhu, Da-Zhou; Wang, Kun; Zhou, Guang-Hua; Hou, Rui-Feng; Wang, Cheng

2010-12-01

With the development of soybean producing and processing, the quality breeding becomes more and more important for soybean breeders. Traditional sampling detection methods for soybean quality need to destroy the seed, and does not satisfy the requirement of earlier generation materials sieving for breeding. Near infrared (NIR) spectroscopy has been widely used for soybean quality detection. However, all these applications were referred to mass samples, and they were not suitable for little or single seed detection in breeding procedure. In the present study, the acousto--optic tunable filter (AOTF) NIR spectroscopy was used to measure the single soybean seed. Two varieties of soybean were measured, which contained 60 KENJIANDOU43 seeds and 60 ZHONGHUANG13 seeds. The results showed that NIR spectra combined with soft independent modeling of class analogy (SIMCA) could accurately discriminate the soybean varieties. The classification accuracy for KENJIANDOU43 seeds and ZHONGHUANG13 was 100%. The spectra of single soybean seed were measured at different positions, and it showed that the seed shape has significant influence on the measurement of spectra, therefore, the key point for single seed measurement was how to accurately acquire the spectra and keep their representativeness. The spectra for soybeans with glossy surface had high repeatability, while the spectra of seeds with external defects had significant difference for several measurements. For the fast sieving of earlier generation materials in breeding, one could firstly eliminate the seeds with external defects, then apply NIR spectra for internal quality detection, and in this way the influence of seed shape and external defects could be reduced.

Agricultural applications of NIR reflectance and transmittance

DEFF Research Database (Denmark)

Gislum, René

2009-01-01

There has been a considerable increase in the use of near infrared (NIR) reflectance and transmittance spectroscopy technologies for rapid determination of quality parameters in agriculture, including applications within crop product quality, feed and food quality, manure quality, soil analyses etc....... As a result it was decided to arrange a seminar within the Nordic Association of Agricultural Scientists. This is a report of the meeting....

Detection and identification of bacteria in a juice matrix with Fourier transform-near infrared spectroscopy and multivariiate analysis.

Science.gov (United States)

Rodriguez-Saona, L E; Khambaty, F M; Fry, F S; Dubois, J; Calvey, E M

2004-11-01

The use of Fourier transform-near infrared (FT-NIR) spectroscopy combined with multivariate pattern recognition techniques was evaluated to address the need for a fast and senisitive method for the detection of bacterial contamination in liquids. The complex cellular composition of bacteria produces FT-NIR vibrational transitions (overtone and combination bands), forming the basis for identification and subtyping. A database including strains of Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis, Bacillus cereus, and Bacillus thuringiensis was built, with special care taken to optimize sample preparation. The bacterial cells were treated with 70% (vol/vol) ethanolto enhance safe handling of pathogenic strains and then concentrated on an aluminum oxide membrane to obtain a thin bacterial film. This simple membrane filtration procedure generated reproducible FT-NIR spectra that allowed for the rapid discrimination among closely related strains. Principal component analysis and soft independent modeling of class analogy of transformed spectra in the region 5,100 to 4,400 cm(-1) were able to discriminate between bacterial species. Spectroscopic analysis of apple juices inoculated with different strains of E. coli at approximately 10(5) CFU/ml showed that FT-NIR spectralfeatures are consistent with bacterial contamination and soft independent modeling of class analogy correctly predicted the identity of the contaminant as strains of E. coli. FT-NIR in conjunction with multivariate techniques can be used for the rapid and accurate evaluation of potential bacterial contamination in liquids with minimal sample manipulation, and hence limited exposure of the laboratory worker to the agents.

A systematic comparison of motion artifact correction techniques for functional near-infrared spectroscopy.

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Cooper, Robert J; Selb, Juliette; Gagnon, Louis; Phillip, Dorte; Schytz, Henrik W; Iversen, Helle K; Ashina, Messoud; Boas, David A

2012-01-01

Near-infrared spectroscopy (NIRS) is susceptible to signal artifacts caused by relative motion between NIRS optical fibers and the scalp. These artifacts can be very damaging to the utility of functional NIRS, particularly in challenging subject groups where motion can be unavoidable. A number of approaches to the removal of motion artifacts from NIRS data have been suggested. In this paper we systematically compare the utility of a variety of published NIRS motion correction techniques using a simulated functional activation signal added to 20 real NIRS datasets which contain motion artifacts. Principle component analysis, spline interpolation, wavelet analysis, and Kalman filtering approaches are compared to one another and to standard approaches using the accuracy of the recovered, simulated hemodynamic response function (HRF). Each of the four motion correction techniques we tested yields a significant reduction in the mean-squared error (MSE) and significant increase in the contrast-to-noise ratio (CNR) of the recovered HRF when compared to no correction and compared to a process of rejecting motion-contaminated trials. Spline interpolation produces the largest average reduction in MSE (55%) while wavelet analysis produces the highest average increase in CNR (39%). On the basis of this analysis, we recommend the routine application of motion correction techniques (particularly spline interpolation or wavelet analysis) to minimize the impact of motion artifacts on functional NIRS data.

Analysis of task-evoked systemic interference in fNIRS measurements: insights from fMRI.

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Erdoğan, Sinem B; Yücel, Meryem A; Akın, Ata

2014-02-15

Functional near infrared spectroscopy (fNIRS) is a promising method for monitoring cerebral hemodynamics with a wide range of clinical applications. fNIRS signals are contaminated with systemic physiological interferences from both the brain and superficial tissues, resulting in a poor estimation of the task related neuronal activation. In this study, we use the anatomical resolution of functional magnetic resonance imaging (fMRI) to extract scalp and brain vascular signals separately and construct an optically weighted spatial average of the fMRI blood oxygen level-dependent (BOLD) signal for characterizing the scalp signal contribution to fNIRS measurements. We introduce an extended superficial signal regression (ESSR) method for canceling physiology-based systemic interference where the effects of cerebral and superficial systemic interference are treated separately. We apply and validate our method on the optically weighted BOLD signals, which are obtained by projecting the fMRI image onto optical measurement space by use of the optical forward problem. The performance of ESSR method in removing physiological artifacts is compared to i) a global signal regression (GSR) method and ii) a superficial signal regression (SSR) method. The retrieved signals from each method are compared with the neural signals that represent the 'ground truth' brain activation cleaned from cerebral systemic fluctuations. We report significant improvements in the recovery of task induced neural activation with the ESSR method when compared to the other two methods as reflected in the Pearson R(2) coefficient and mean square error (MSE) metrics (two tailed paired t-tests, pnoise (CNR) improvement (60%). Our findings suggest that, during a cognitive task i) superficial scalp signal contribution to fNIRS signals varies significantly among different regions on the forehead and ii) using an average scalp measurement together with a local measure of superficial hemodynamics better accounts

Application of the near-infrared spectroscopy in the pharmaceutical technology.

Science.gov (United States)

Jamrógiewicz, Marzena

2012-07-01

Near-infrared (NIR) spectroscopy is currently the fastest-growing and the most versatile analytical method not only in the pharmaceutical sciences but also in the industry. This review focuses on recent NIR applications in the pharmaceutical technology. This article covers monitoring, by NIR, of many manufacturing processes, such as granulation, mixing or drying, in order to determine the end-point of these processes. In this paper, apart from basic theoretical information concerning the NIR spectra, there are included determinations of the quality and quantity of pharmaceutical compounds. Some examples of measurements and control of physicochemical parameters of the final medicinal products, such as hardness, porosity, thickness size, compression strength, disintegration time and potential counterfeit are included. Biotechnology and plant drug analysis using NIR is also described. Moreover, some disadvantages of this method are stressed and future perspectives are anticipated. Copyright © 2012 Elsevier B.V. All rights reserved.

Variety identification of brown sugar using short-wave near infrared spectroscopy and multivariate calibration

Science.gov (United States)

Yang, Haiqing; Wu, Di; He, Yong

2007-11-01

Near-infrared spectroscopy (NIRS) with the characteristics of high speed, non-destructiveness, high precision and reliable detection data, etc. is a pollution-free, rapid, quantitative and qualitative analysis method. A new approach for variety discrimination of brown sugars using short-wave NIR spectroscopy (800-1050nm) was developed in this work. The relationship between the absorbance spectra and brown sugar varieties was established. The spectral data were compressed by the principal component analysis (PCA). The resulting features can be visualized in principal component (PC) space, which can lead to discovery of structures correlative with the different class of spectral samples. It appears to provide a reasonable variety clustering of brown sugars. The 2-D PCs plot obtained using the first two PCs can be used for the pattern recognition. Least-squares support vector machines (LS-SVM) was applied to solve the multivariate calibration problems in a relatively fast way. The work has shown that short-wave NIR spectroscopy technique is available for the brand identification of brown sugar, and LS-SVM has the better identification ability than PLS when the calibration set is small.

Rapid analysis of adulterations in Chinese lotus root powder (LRP) by near-infrared (NIR) spectroscopy coupled with chemometric class modeling techniques.

Science.gov (United States)

Xu, Lu; Shi, Peng-Tao; Ye, Zi-Hong; Yan, Si-Min; Yu, Xiao-Ping

2013-12-01

This paper develops a rapid analysis method for adulteration identification of a popular traditional Chinese food, lotus root powder (LRP), by near-infrared spectroscopy and chemometrics. 85 pure LRP samples were collected from 7 main lotus producing areas of China to include most if not all of the significant variations likely to be encountered in unknown authentic materials. To evaluate the model specificity, 80 adulterated LRP samples prepared by blending pure LRP with different levels of four cheaper and commonly used starches were measured and predicted. For multivariate quality models, two class modeling methods, the traditional soft independent modeling of class analogy (SIMCA) and a recently proposed partial least squares class model (PLSCM) were used. Different data preprocessing techniques, including smoothing, taking derivative and standard normal variate (SNV) transformation were used to improve the classification performance. The results indicate that smoothing, taking second-order derivatives and SNV can improve the class models by enhancing signal-to-noise ratio, reducing baseline and background shifts. The most accurate and stable models were obtained with SNV spectra for both SIMCA (sensitivity 0.909 and specificity 0.938) and PLSCM (sensitivity 0.909 and specificity 0.925). Moreover, both SIMCA and PLSCM could detect LRP samples mixed with 5% (w/w) or more other cheaper starches, including cassava, sweet potato, potato and maize starches. Although it is difficult to perform an exhaustive collection of all pure LRP samples and possible adulterations, NIR spectrometry combined with class modeling techniques provides a reliable and effective method to detect most of the current LRP adulterations in Chinese market. Copyright © 2013 Elsevier Ltd. All rights reserved.

Hybrid EEG-fNIRS Asynchronous Brain-Computer Interface for Multiple Motor Tasks.

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Alessio Paolo Buccino

Full Text Available Non-invasive Brain-Computer Interfaces (BCI have demonstrated great promise for neuroprosthetics and assistive devices. Here we aim to investigate methods to combine Electroencephalography (EEG and functional Near-Infrared Spectroscopy (fNIRS in an asynchronous Sensory Motor rhythm (SMR-based BCI. We attempted to classify 4 different executed movements, namely, Right-Arm-Left-Arm-Right-Hand-Left-Hand tasks. Previous studies demonstrated the benefit of EEG-fNIRS combination. However, since normally fNIRS hemodynamic response shows a long delay, we investigated new features, involving slope indicators, in order to immediately detect changes in the signals. Moreover, Common Spatial Patterns (CSPs have been applied to both EEG and fNIRS signals. 15 healthy subjects took part in the experiments and since 25 trials per class were available, CSPs have been regularized with information from the entire population of participants and optimized using genetic algorithms. The different features have been compared in terms of performance and the dynamic accuracy over trials shows that the introduced methods diminish the fNIRS delay in the detection of changes.

Discrimination of Transgenic Rice Based on Near Infrared Reflectance Spectroscopy and Partial Least Squares Regression Discriminant Analysis

Directory of Open Access Journals (Sweden)

ZHANG Long

2015-09-01

Full Text Available Near infrared reflectance spectroscopy (NIRS, a non-destructive measurement technique, was combined with partial least squares regression discrimiant analysis (PLS-DA to discriminate the transgenic (TCTP and mi166 and wild type (Zhonghua 11 rice. Furthermore, rice lines transformed with protein gene (OsTCTP and regulation gene (Osmi166 were also discriminated by the NIRS method. The performances of PLS-DA in spectral ranges of 4 000–8 000 cm-1 and 4 000–10 000 cm-1 were compared to obtain the optimal spectral range. As a result, the transgenic and wild type rice were distinguished from each other in the range of 4 000–10 000 cm-1, and the correct classification rate was 100.0% in the validation test. The transgenic rice TCTP and mi166 were also distinguished from each other in the range of 4 000–10 000 cm-1, and the correct classification rate was also 100.0%. In conclusion, NIRS combined with PLS-DA can be used for the discrimination of transgenic rice.

Near-infrared Raman spectroscopy to detect anti-Toxoplasma gondii antibodies in blood sera of domestic cats

Science.gov (United States)

Duarte, Janaina; Pacheco, Marcos T. T.; Silveira, Landulfo, Jr.; Machado, Rosangela Z.; Martins, Rodrigo A. L.; Zangaro, Renato A.; Villaverde, Antonio G. J. B.

2001-05-01

Near-infrared (NIR) Raman spectroscopy has been studied for the last years for many biomedical applications. It is a powerful tool for biological materials analysis. Toxoplasmosis is an important zoonosis in public health, cats being the principal responsible for the transmission of the disease in Brazil. The objective of this work is to investigate a new method of diagnosis of this disease. NIR Raman spectroscopy was used to detect anti Toxoplasma gondii antibodies in blood sera from domestic cats, without sample preparation. In all, six blood serum samples were used for this study. A previous serological test was done by the Indirect Immunoenzymatic Assay (ELISA) to permit a comparative study between both techniques and it showed that three serum samples were positive and the other three were negative to toxoplasmosis. Raman spectra were taken for all the samples and analyzed by using the principal components analysis (PCA). A diagnosis parameter was defined from the analysis of the second and third principal components of the Raman spectra. It was found that this parameter can detect the infection level of the animal. The results have indicated that NIR Raman spectroscopy, associated to the PCA can be a promising technique for serological analysis, such as toxoplasmosis, allowing a fast and sensitive method of diagnosis.

Correlation between near infrared spectroscopy and electrical techniques in measuring skin moisture content

International Nuclear Information System (INIS)

Mohamad, M; Sabbri, A R M; Jafri, M Z Mat; Omar, A F

2014-01-01

Near infrared (NIR) spectroscopy technique serves as an important tool for the measurement of moisture content of skin owing to the advantages it has over the other techniques. The purpose of the study is to develop a correlation between NIR spectrometer with electrical conventional techniques for skin moisture measurement. A non-invasive measurement of moisture content of skin was performed on different part of human face and hand under control environment (temperature 21 ± 1 °C, relative humidity 45 ± 5 %). Ten healthy volunteers age between 21-25 (male and female) participated in this study. The moisture content of skin was measured using DermaLab ® USB Moisture Module, Scalar Moisture Checker and NIR spectroscopy (NIRQuest). Higher correlation was observed between NIRQuest and Dermalab moisture probe with a coefficient of determination (R 2 ) above 70 % for all the subjects. However, the value of R 2 between NIRQuest and Moisture Checker was observed to be lower with the R 2 values ranges from 51.6 to 94.4 %. The correlation of NIR spectroscopy technique successfully developed for measuring moisture content of the skin. The analysis of this correlation can help to establish novel instruments based on an optical system in clinical used especially in the dermatology field

Sleep apnea termination decreases cerebral blood volume: a near-infrared spectroscopy case study

Science.gov (United States)

Virtanen, Jaakko; Noponen, Tommi; Salmi, Tapani; Toppila, Jussi; Meriläinen, Pekka

2009-07-01

Medical near-infrared spectroscopy (NIRS) can be used to estimate cerebral haemodynamic changes non-invasively. Sleep apnea is a common sleep disorder where repetitive pauses in breathing decrease the quality of sleep and exposes the individual to various health problems. We have measured oxygenated and deoxygenated haemoglobin concentration changes during apneic events in sleep from the forehead of one subject using NIRS and used principal component analysis to extract extracerebral and cortical haemodynamic changes from NIRS signals. Comparison of NIRS signals with EEG, bioimpedance, and pulse oximetry data suggests that termination of apnea leads to decreases in cerebral blood volume and flow that may be related to neurological arousal via neurovascular coupling.

[Rapid assessment of critical quality attributes of Chinese materia medica (II): strategy of NIR assignment].

Science.gov (United States)

Pei, Yan-Ling; Wu, Zhi-Sheng; Shi, Xin-Yuan; Zhou, Lu-Wei; Qiao, Yan-Jiang

2014-09-01

The present paper firstly reviewed the research progress and main methods of NIR spectral assignment coupled with our research results. Principal component analysis was focused on characteristic signal extraction to reflect spectral differences. Partial least squares method was concerned with variable selection to discover characteristic absorption band. Two-dimensional correlation spectroscopy was mainly adopted for spectral assignment. Autocorrelation peaks were obtained from spectral changes, which were disturbed by external factors, such as concentration, temperature and pressure. Density functional theory was used to calculate energy from substance structure to establish the relationship between molecular energy and spectra change. Based on the above reviewed method, taking a NIR spectral assignment of chlorogenic acid as example, a reliable spectral assignment for critical quality attributes of Chinese materia medica (CMM) was established using deuterium technology and spectral variable selection. The result demonstrated the assignment consistency according to spectral features of different concentrations of chlorogenic acid and variable selection region of online NIR model in extract process. Although spectral assignment was initial using an active pharmaceutical ingredient, it is meaningful to look forward to the futurity of the complex components in CMM. Therefore, it provided methodology for NIR spectral assignment of critical quality attributes in CMM.

[Application of characteristic NIR variables selection in portable detection of soluble solids content of apple by near infrared spectroscopy].

Science.gov (United States)

Fan, Shu-Xiang; Huang, Wen-Qian; Li, Jiang-Bo; Guo, Zhi-Ming; Zhaq, Chun-Jiang

2014-10-01

In order to detect the soluble solids content(SSC)of apple conveniently and rapidly, a ring fiber probe and a portable spectrometer were applied to obtain the spectroscopy of apple. Different wavelength variable selection methods, including unin- formative variable elimination (UVE), competitive adaptive reweighted sampling (CARS) and genetic algorithm (GA) were pro- posed to select effective wavelength variables of the NIR spectroscopy of the SSC in apple based on PLS. The back interval LS- SVM (BiLS-SVM) and GA were used to select effective wavelength variables based on LS-SVM. Selected wavelength variables and full wavelength range were set as input variables of PLS model and LS-SVM model, respectively. The results indicated that PLS model built using GA-CARS on 50 characteristic variables selected from full-spectrum which had 1512 wavelengths achieved the optimal performance. The correlation coefficient (Rp) and root mean square error of prediction (RMSEP) for prediction sets were 0.962, 0.403°Brix respectively for SSC. The proposed method of GA-CARS could effectively simplify the portable detection model of SSC in apple based on near infrared spectroscopy and enhance the predictive precision. The study can provide a reference for the development of portable apple soluble solids content spectrometer.

[State Recognition of Solid Fermentation Process Based on Near Infrared Spectroscopy with Adaboost and Spectral Regression Discriminant Analysis].

Science.gov (United States)

Yu, Shuang; Liu, Guo-hai; Xia, Rong-sheng; Jiang, Hui

2016-01-01

In order to achieve the rapid monitoring of process state of solid state fermentation (SSF), this study attempted to qualitative identification of process state of SSF of feed protein by use of Fourier transform near infrared (FT-NIR) spectroscopy analysis technique. Even more specifically, the FT-NIR spectroscopy combined with Adaboost-SRDA-NN integrated learning algorithm as an ideal analysis tool was used to accurately and rapidly monitor chemical and physical changes in SSF of feed protein without the need for chemical analysis. Firstly, the raw spectra of all the 140 fermentation samples obtained were collected by use of Fourier transform near infrared spectrometer (Antaris II), and the raw spectra obtained were preprocessed by use of standard normal variate transformation (SNV) spectral preprocessing algorithm. Thereafter, the characteristic information of the preprocessed spectra was extracted by use of spectral regression discriminant analysis (SRDA). Finally, nearest neighbors (NN) algorithm as a basic classifier was selected and building state recognition model to identify different fermentation samples in the validation set. Experimental results showed as follows: the SRDA-NN model revealed its superior performance by compared with other two different NN models, which were developed by use of the feature information form principal component analysis (PCA) and linear discriminant analysis (LDA), and the correct recognition rate of SRDA-NN model achieved 94.28% in the validation set. In this work, in order to further improve the recognition accuracy of the final model, Adaboost-SRDA-NN ensemble learning algorithm was proposed by integrated the Adaboost and SRDA-NN methods, and the presented algorithm was used to construct the online monitoring model of process state of SSF of feed protein. Experimental results showed as follows: the prediction performance of SRDA-NN model has been further enhanced by use of Adaboost lifting algorithm, and the correct

The use of near-infrared spectroscopy in understanding skeletal muscle physiology: recent developments.

Science.gov (United States)

Ferrari, Marco; Muthalib, Makii; Quaresima, Valentina

2011-11-28

This article provides a snapshot of muscle near-infrared spectroscopy (NIRS) at the end of 2010 summarizing the recent literature, offering the present status and perspectives of the NIRS instrumentation and methods, describing the main NIRS studies on skeletal muscle physiology, posing open questions and outlining future directions. So far, different NIRS techniques (e.g. continuous-wave (CW) and spatially, time- and frequency-resolved spectroscopy) have been used for measuring muscle oxygenation during exercise. In the last four years, approximately 160 muscle NIRS articles have been published on different physiological aspects (primarily muscle oxygenation and haemodynamics) of several upper- and lower-limb muscle groups investigated by using mainly two-channel CW and spatially resolved spectroscopy commercial instruments. Unfortunately, in only 15 of these studies were the advantages of using multi-channel instruments exploited. There are still several open questions in the application of NIRS in muscle studies: (i) whether NIRS can be used in subjects with a large fat layer; (ii) the contribution of myoglobin desaturation to the NIRS signal during exercise; (iii) the effect of scattering changes during exercise; and (iv) the effect of changes in skin perfusion, particularly during prolonged exercise. Recommendations for instrumentation advancements and future muscle NIRS studies are provided.

Trends in brain oxygenation during mental and physical exercise measured using near-infrared spectroscopy (NIRS): potential for early detection of Alzheimer's disease

Science.gov (United States)

Allen, Monica S.; Allen, Jeffery W.; Mikkilineni, Shweta; Liu, Hanli

2005-04-01

Motivation: Early diagnosis of Alzheimer's disease (AD) is crucial because symptoms respond best to available treatments in the initial stages of the disease. Recent studies have shown that marked changes in brain oxygenation during mental and physical tasks can be used for noninvasive functional brain imaging to detect Alzheimer"s disease. The goal of our study is to explore the possibility of using near infrared spectroscopy (NIRS) and mapping (NIRM) as a diagnostic tool for AD before the onset of significant morphological changes in the brain. Methods: A 16-channel NIRS brain imager was used to noninvasively measure spatial and temporal changes in cerebral hemodynamics induced during verbal fluency task and physical activity. The experiments involved healthy subjects (n = 10) in the age range of 25+/-5 years. The NIRS signals were taken from the subjects' prefrontal cortex during the activities. Results and Conclusion: Trends of oxygenated and deoxygenated hemoglobin in the prefrontal cortex of the brain were observed. During the mental stimulation, the subjects showed significant increase in oxygenated hemoglobin [HbO2] with a simultaneous decrease in deoxygenated hemoglobin [Hb]. However, physical exercise caused a rise in levels of HbO2 with small variations in Hb. This study basically demonstrates that NIRM taken from the prefrontal cortex of the human brain is sensitive to both mental and physical tasks and holds potential to serve as a diagnostic means for early detection of Alzheimer's disease.

Use of in-line near-infrared spectroscopy in combination with chemometrics for improved understanding of pharmaceutical processes

DEFF Research Database (Denmark)

Rantanen, Jukka; Wikström, Håkan; Turner, Rebecca

2005-01-01

was extracted. Principal component loadings were fully interpreted to validate the conclusions drawn from scores and predictions. Thus NIR spectroscopy could be used to determine the end points of the three subphases of high shear wet granulation and, as such, provide a fast in-line quality control tool....... solid dosage form. In this study, the use of in-line near-infrared (NIR) spectroscopy as a process analytical tool for high shear granulation was investigated. In combination with principal component-based methods, process analysis of three separate phases of high shear wet granulation (mixing, spraying...

Biodiesel classification by base stock type (vegetable oil) using near infrared spectroscopy data

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)

2011-03-18

The use of biofuels, such as bioethanol or biodiesel, has rapidly increased in the last few years. Near infrared (near-IR, NIR, or NIRS) spectroscopy (>4000 cm{sup -1}) has previously been reported as a cheap and fast alternative for biodiesel quality control when compared with infrared, Raman, or nuclear magnetic resonance (NMR) methods; in addition, NIR can easily be done in real time (on-line). In this proof-of-principle paper, we attempt to find a correlation between the near infrared spectrum of a biodiesel sample and its base stock. This correlation is used to classify fuel samples into 10 groups according to their origin (vegetable oil): sunflower, coconut, palm, soy/soya, cottonseed, castor, Jatropha, etc. Principal component analysis (PCA) is used for outlier detection and dimensionality reduction of the NIR spectral data. Four different multivariate data analysis techniques are used to solve the classification problem, including regularized discriminant analysis (RDA), partial least squares method/projection on latent structures (PLS-DA), K-nearest neighbors (KNN) technique, and support vector machines (SVMs). Classifying biodiesel by feedstock (base stock) type can be successfully solved with modern machine learning techniques and NIR spectroscopy data. KNN and SVM methods were found to be highly effective for biodiesel classification by feedstock oil type. A classification error (E) of less than 5% can be reached using an SVM-based approach. If computational time is an important consideration, the KNN technique (E = 6.2%) can be recommended for practical (industrial) implementation. Comparison with gasoline and motor oil data shows the relative simplicity of this methodology for biodiesel classification.

Biodiesel classification by base stock type (vegetable oil) using near infrared spectroscopy data

International Nuclear Information System (INIS)

Balabin, Roman M.; Safieva, Ravilya Z.

2011-01-01

The use of biofuels, such as bioethanol or biodiesel, has rapidly increased in the last few years. Near infrared (near-IR, NIR, or NIRS) spectroscopy (>4000 cm -1 ) has previously been reported as a cheap and fast alternative for biodiesel quality control when compared with infrared, Raman, or nuclear magnetic resonance (NMR) methods; in addition, NIR can easily be done in real time (on-line). In this proof-of-principle paper, we attempt to find a correlation between the near infrared spectrum of a biodiesel sample and its base stock. This correlation is used to classify fuel samples into 10 groups according to their origin (vegetable oil): sunflower, coconut, palm, soy/soya, cottonseed, castor, Jatropha, etc. Principal component analysis (PCA) is used for outlier detection and dimensionality reduction of the NIR spectral data. Four different multivariate data analysis techniques are used to solve the classification problem, including regularized discriminant analysis (RDA), partial least squares method/projection on latent structures (PLS-DA), K-nearest neighbors (KNN) technique, and support vector machines (SVMs). Classifying biodiesel by feedstock (base stock) type can be successfully solved with modern machine learning techniques and NIR spectroscopy data. KNN and SVM methods were found to be highly effective for biodiesel classification by feedstock oil type. A classification error (E) of less than 5% can be reached using an SVM-based approach. If computational time is an important consideration, the KNN technique (E = 6.2%) can be recommended for practical (industrial) implementation. Comparison with gasoline and motor oil data shows the relative simplicity of this methodology for biodiesel classification.

Studying hemispheric lateralization during a Stroop task through near-infrared spectroscopy-based connectivity

Science.gov (United States)

Zhang, Lei; Sun, Jinyan; Sun, Bailei; Luo, Qingming; Gong, Hui

2014-05-01

Near-infrared spectroscopy (NIRS) is a developing and promising functional brain imaging technology. Developing data analysis methods to effectively extract meaningful information from collected data is the major bottleneck in popularizing this technology. In this study, we measured hemodynamic activity of the prefrontal cortex (PFC) during a color-word matching Stroop task using NIRS. Hemispheric lateralization was examined by employing traditional activation and novel NIRS-based connectivity analyses simultaneously. Wavelet transform coherence was used to assess intrahemispheric functional connectivity. Spearman correlation analysis was used to examine the relationship between behavioral performance and activation/functional connectivity, respectively. In agreement with activation analysis, functional connectivity analysis revealed leftward lateralization for the Stroop effect and correlation with behavioral performance. However, functional connectivity was more sensitive than activation for identifying hemispheric lateralization. Granger causality was used to evaluate the effective connectivity between hemispheres. The results showed increased information flow from the left to the right hemispheres for the incongruent versus the neutral task, indicating a leading role of the left PFC. This study demonstrates that the NIRS-based connectivity can reveal the functional architecture of the brain more comprehensively than traditional activation, helping to better utilize the advantages of NIRS.

Food Safety Evaluation Based on Near Infrared Spectroscopy and Imaging: A Review.

Science.gov (United States)

Fu, Xiaping; Ying, Yibin

2016-08-17

In recent years, due to the increasing consciousness of food safety and human health, much progress has been made in developing rapid and nondestructive techniques for the evaluation of food hazards, food authentication, and traceability. Near infrared (NIR) spectroscopy and imaging techniques have gained wide acceptance in many fields because of their advantages over other analytical techniques. Following a brief introduction of NIR spectroscopy and imaging basics, this review mainly focuses on recent NIR spectroscopy and imaging applications for food safety evaluation, including (1) chemical hazards detection; (2) microbiological hazards detection; (3) physical hazards detection; (4) new technology-induced food safety concerns; and (5) food traceability. The review shows NIR spectroscopy and imaging to be effective tools that will play indispensable roles for food safety evaluation. In addition, on-line/real-time applications of these techniques promise to be a huge growth field in the near future.

Identification of Serine Conformers by Matrix-Isolation IR Spectroscopy Aided by Near-Infrared Laser-Induced Conformational Change, 2D Correlation Analysis, and Quantum Mechanical Anharmonic Computations.

Science.gov (United States)

Najbauer, Eszter E; Bazsó, Gábor; Apóstolo, Rui; Fausto, Rui; Biczysko, Malgorzata; Barone, Vincenzo; Tarczay, György

2015-08-20

The conformers of α-serine were investigated by matrix-isolation IR spectroscopy combined with NIR laser irradiation. This method, aided by 2D correlation analysis, enabled unambiguously grouping the spectral lines to individual conformers. On the basis of comparison of at least nine experimentally observed vibrational transitions of each conformer with empirically scaled (SQM) and anharmonic (GVPT2) computed IR spectra, six conformers were identified. In addition, the presence of at least one more conformer in Ar matrix was proved, and a short-lived conformer with a half-life of (3.7 ± 0.5) × 10(3) s in N2 matrix was generated by NIR irradiation. The analysis of the NIR laser-induced conversions revealed that the excitation of the stretching overtone of both the side chain and the carboxylic OH groups can effectively promote conformational changes, but remarkably different paths were observed for the two kinds of excitations.

Hydrate formation during wet granulation studied by spectroscopic methods and multivariate analysis

DEFF Research Database (Denmark)

Jørgensen, Anna; Rantanen, Jukka; Karjalainen, Milja

2002-01-01

PURPOSE: The aim was to follow hydrate formation of two structurally related drugs, theophylline and caffeine, during wet granulation using fast and nondestructive spectroscopic methods. METHODS: Anhydrous theophylline and caffeine were granulated with purified water. Charge-coupled device (CCD......) Raman spectroscopy was compared with near-infrared spectroscopy (NIR) in following hydrate formation of drugs during wet granulation (off-line). To perform an at-line process analysis, the effect of water addition was monitored by NIR spectroscopy and principal components analysis (PCA). The changes...

Inline monitoring of adsorption of Butane Isomers with near infrared spectroscopy: Drift Correction in time based experiments

NARCIS (Netherlands)

Ferreira, A.; Boelens, H.F.M.; Westerhuis, J.A.

2005-01-01

Near-infrared (NIR) spectroscopy is used to monitor online a large variety of processes. Hydrocarbons with their strong NIR spectral signature are good candidate analytes. For this work, the sorption data are measured in a manometric setup coupled with online NIR spectroscopy, to monitor the bulk

NIR hyperspectral compressive imager based on a modified Fabry–Perot resonator

Science.gov (United States)

Oiknine, Yaniv; August, Isaac; Blumberg, Dan G.; Stern, Adrian

2018-04-01

The acquisition of hyperspectral (HS) image datacubes with available 2D sensor arrays involves a time consuming scanning process. In the last decade, several compressive sensing (CS) techniques were proposed to reduce the HS acquisition time. In this paper, we present a method for near-infrared (NIR) HS imaging which relies on our rapid CS resonator spectroscopy technique. Within the framework of CS, and by using a modified Fabry–Perot resonator, a sequence of spectrally modulated images is used to recover NIR HS datacubes. Owing to the innovative CS design, we demonstrate the ability to reconstruct NIR HS images with hundreds of spectral bands from an order of magnitude fewer measurements, i.e. with a compression ratio of about 10:1. This high compression ratio, together with the high optical throughput of the system, facilitates fast acquisition of large HS datacubes.

Anterior temporal artery tap to identify systemic interference using short-separation NIRS measurements

DEFF Research Database (Denmark)

Sood, Mehak; Jindal, Utkarsh; Chowdhury, Shubhajit Roy

2015-01-01

that are also affected by tDCS. An approach may be to use short optode separations to measure systemic hemodynamic fluctuations occurring in the superficial layers which can then be used as regressors to remove the systemic contamination. Here, we demonstrate that temporal artery tap may be used to better...... of neural activity is possible with a measure of cerebral hemoglobin oxygenation using near-infrared spectroscopy (NIRS). In principal accordance, NIRS can capture the hemodynamic response to tDCS but the challenge remains in removing the systemic interference occurring in the superficial layers of the head...... identify systemic interference using this short-separation NIRS. Moreover, NIRS-EEG joint-imaging during anodal tDCS was used to measure changes in mean cerebral haemoglobin oxygen saturation (rSO2) along with changes in the log-transformed mean-power of EEG within 0.5 Hz-11.25 Hz. We found that percent...

Spatiotemporal image correlation spectroscopy measurements of flow demonstrated in microfluidic channels

Science.gov (United States)

Rossow, Molly; Mantulin, William W.; Gratton, Enrico

2009-03-01

Accurate blood flow measurements during surgery can improve an operation's chance of success. We developed near-infrared spatio-temporal image spectroscopy (NIR-STICS), which has the potential to make blood flow measurements that are difficult to accomplish with existing methods. Specifically, we propose the technique and we show feasibility on phantom measurements. NIR-STICS has the potential of measuring the fluid velocity in small blood vessels (less than 1 mm in diameter) and of creating a map of blood flow rates over an area of approximately 1 cm2. NIR-STICS employs near-infrared spectroscopy to probe inside blood vessel walls and spatiotemporal image correlation spectroscopy to directly-without the use of a model-extract fluid velocity from the fluctuations within an image. We present computer simulations and experiments on a phantom system that demonstrate the effectiveness of NIR-STICS.

Underwater near-infrared spectroscopy can measure training adaptations in adolescent swimmers.

Science.gov (United States)

Jones, Ben; Parry, Dave; Cooper, Chris E

2018-01-01

The development of an underwater near-infrared spectroscopy (uNIRS) device has enabled previously unattainable measurements of peripheral muscle hemodynamics and oxygenation to be taken within the natural aquatic environment. The purposes of this study were (i) to trial the use of uNIRS, in a real world training study, and (ii) to monitor the effects of a swim training program upon muscle oxygenation status in short distance swimming. A total of 14 junior club level swimmers completed a repeated swim sprint test before and after an eight week endurance training program. A waterproof, portable Near-Infrared Spectroscopy device was attached to the vastus lateralis . uNIRS successfully measured changes in muscle oxygenation and blood volume in all individuals; rapid sub-second time resolution of the device was able to demonstrate muscle oxygenation changes during the characteristic swim movements. Post training heart rate recovery and swim performance time were significantly improved. uNIRS data also showed significant changes. A larger rise in deoxyhemoglobin during individual sprints suggested training induced an increase in muscle oxygen extraction; a faster recovery time for muscle oxygenation suggested positive training induced changes and significant changes in muscle blood flow also occur. As a strong correlation was seen between an increased reoxygenation rate and an improved swim performance time, these findings support the use of uNIRS as a new performance analysis tool in swimming.

Determination of fat content in chicken hamburgers using NIR spectroscopy and the Successive Projections Algorithm for interval selection in PLS regression (iSPA-PLS)

Science.gov (United States)

Krepper, Gabriela; Romeo, Florencia; Fernandes, David Douglas de Sousa; Diniz, Paulo Henrique Gonçalves Dias; de Araújo, Mário César Ugulino; Di Nezio, María Susana; Pistonesi, Marcelo Fabián; Centurión, María Eugenia

2018-01-01

Determining fat content in hamburgers is very important to minimize or control the negative effects of fat on human health, effects such as cardiovascular diseases and obesity, which are caused by the high consumption of saturated fatty acids and cholesterol. This study proposed an alternative analytical method based on Near Infrared Spectroscopy (NIR) and Successive Projections Algorithm for interval selection in Partial Least Squares regression (iSPA-PLS) for fat content determination in commercial chicken hamburgers. For this, 70 hamburger samples with a fat content ranging from 14.27 to 32.12 mg kg- 1 were prepared based on the upper limit recommended by the Argentinean Food Codex, which is 20% (w w- 1). NIR spectra were then recorded and then preprocessed by applying different approaches: base line correction, SNV, MSC, and Savitzky-Golay smoothing. For comparison, full-spectrum PLS and the Interval PLS are also used. The best performance for the prediction set was obtained for the first derivative Savitzky-Golay smoothing with a second-order polynomial and window size of 19 points, achieving a coefficient of correlation of 0.94, RMSEP of 1.59 mg kg- 1, REP of 7.69% and RPD of 3.02. The proposed methodology represents an excellent alternative to the conventional Soxhlet extraction method, since waste generation is avoided, yet without the use of either chemical reagents or solvents, which follows the primary principles of Green Chemistry. The new method was successfully applied to chicken hamburger analysis, and the results agreed with those with reference values at a 95% confidence level, making it very attractive for routine analysis.

Long-term follow-up after near-infrared spectroscopy coronary imaging: Insights from the lipid cORe plaque association with CLinical events (ORACLE-NIRS) registry.

Science.gov (United States)

Danek, Barbara Anna; Karatasakis, Aris; Karacsonyi, Judit; Alame, Aya; Resendes, Erica; Kalsaria, Pratik; Nguyen-Trong, Phuong-Khanh J; Rangan, Bavana V; Roesle, Michele; Abdullah, Shuaib; Banerjee, Subhash; Brilakis, Emmanouil S

Coronary lipid core plaque may be associated with the incidence of subsequent cardiovascular events. We analyzed outcomes of 239 patients who underwent near-infrared spectroscopy (NIRS) coronary imaging between 2009-2011. Multivariable Cox regression was used to identify variables independently associated with the incidence of major adverse cardiovascular events (MACE; cardiac mortality, acute coronary syndromes (ACS), stroke, and unplanned revascularization) during follow-up. Mean patient age was 64±9years, 99% were men, and 50% were diabetic, presenting with stable coronary artery disease (61%) or an acute coronary syndrome (ACS, 39%). Target vessel pre-stenting median lipid core burden index (LCBI) was 88 [interquartile range, IQR 50-130]. Median LCBI in non-target vessels was 57 [IQR 26-94]. Median follow-up was 5.3years. The 5-year MACE rate was 37.5% (cardiac mortality was 15.0%). On multivariable analysis the following variables were associated with MACE: diabetes mellitus, prior percutaneous coronary intervention performed at index angiography, and non-target vessel LCBI. Non-target vessel LCBI of 77 was determined using receiver-operating characteristic curve analysis to be a threshold for prediction of MACE in our cohort. The adjusted hazard ratio (HR) for non-target vessel LCBI ≥77 was 14.05 (95% confidence interval (CI) 2.47-133.51, p=0.002). The 5-year cumulative incidence of events in the above-threshold group was 58.0% vs. 13.1% in the below-threshold group. During long-term follow-up of patients who underwent NIRS imaging, high LCBI in a non-PCI target vessel was associated with increased incidence of MACE. Published by Elsevier Inc.

NIRS and IVUS for characterization of atherosclerosis in patients undergoing coronary angiography

NARCIS (Netherlands)

Brugaletta, Salvatore; Garcia-Garcia, Hector M.; Serruys, Patrick W.; de Boer, Sanneke; Ligthart, Jurgen; Gomez-Lara, Josep; Witberg, Karen; Diletti, Roberto; Wykrzykowska, Joanna; van Geuns, Robert-Jan; Schultz, Carl; Regar, Evelyn; Duckers, Henricus J.; van Mieghem, Nicolas; de Jaegere, Peter; Madden, Sean P.; Muller, James E.; van der Steen, Antonius F. W.; van der Giessen, Wim J.; Boersma, Eric

2011-01-01

The aim of this study was to compare the findings of near-infrared spectroscopy (NIRS), intravascular ultrasound (IVUS) virtual histology (VH), and grayscale IVUS obtained in matched coronary vessel segments of patients undergoing coronary angiography. Intravascular ultrasound VH has been developed

Joint attention studies in normal and autistic children using NIRS

Science.gov (United States)

Chaudhary, Ujwal; Hall, Michael; Gutierrez, Anibal; Messinger, Daniel; Rey, Gustavo; Godavarty, Anuradha

2011-03-01

Autism is a socio-communication brain development disorder. It is marked by degeneration in the ability to respond to joint attention skill task, from as early as 12 to 18 months of age. This trait is used to distinguish autistic from nonautistic. In this study Near infrared spectroscopy (NIRS) is being applied for the first time to study the difference in activation and connectivity in the frontal cortex of typically developing (TD) and autistic children between 4-8 years of age in response to joint attention task. The optical measurements are acquired in real time from frontal cortex using Imagent (ISS Inc.) - a frequency domain based NIRS system in response to video clips which engenders a feeling of joint attention experience in the subjects. A block design consisting of 5 blocks of following sequence 30 sec joint attention clip (J), 30 sec non-joint attention clip (NJ) and 30 sec rest condition is used. Preliminary results from TD child shows difference in brain activation (in terms of oxy-hemoglobin, HbO) during joint attention interaction compared to the nonjoint interaction and rest. Similar activation study did not reveal significant differences in HbO across the stimuli in, unlike in an autistic child. Extensive studies are carried out to validate the initial observations from both brain activation as well as connectivity analysis. The result has significant implication for research in neural pathways associated with autism that can be mapped using NIRS.

Challenges in the noninvasive detection of body composition using near-infrared spectroscopy

Directory of Open Access Journals (Sweden)

Wenliang Chen

2014-11-01

Full Text Available Noninvasive detection of body composition plays a significant role in the improvement of life quality and reduction in complications of the patients, and the near-infrared (NIR spectroscopy, with the advantages of painlessness and convenience, is considered as the most promising tool for the online noninvasive monitoring of body composition. However, quite different from other fields of online detection using NIR spectroscopy, such as food safety and environment monitoring, noninvasive detection of body composition demands higher precision of the instruments as well as more rigorousness of measurement conditions. Therefore, new challenges emerge when NIR spectroscopy is applied to the noninvasive detection of body composition, which, in this paper, are first concluded from the aspects of measurement methods, measurement conditions, instrument precision, multi-component influence, individual difference and novel weak-signal extraction method based on our previous research in the cutting-edge field of NIR noninvasive blood glucose detection. Moreover, novel ideas and approaches of our group to solve these problems are introduced, which may provide evidence for the future development of noninvasive blood glucose detection, and further contribute to the noninvasive detection of other body compositions using NIR spectroscopy.

Rapid and simultaneous analysis of five alkaloids in four parts of Coptidis Rhizoma by near-infrared spectroscopy

Science.gov (United States)

Jintao, Xue; Yufei, Liu; Liming, Ye; Chunyan, Li; Quanwei, Yang; Weiying, Wang; Yun, Jing; Minxiang, Zhang; Peng, Li

2018-01-01

Near-Infrared Spectroscopy (NIRS) was first used to develop a method for rapid and simultaneous determination of 5 active alkaloids (berberine, coptisine, palmatine, epiberberine and jatrorrhizine) in 4 parts (rhizome, fibrous root, stem and leaf) of Coptidis Rhizoma. A total of 100 samples from 4 main places of origin were collected and studied. With HPLC analysis values as calibration reference, the quantitative analysis of 5 marker components was performed by two different modeling methods, partial least-squares (PLS) regression as linear regression and artificial neural networks (ANN) as non-linear regression. The results indicated that the 2 types of models established were robust, accurate and repeatable for five active alkaloids, and the ANN models was more suitable for the determination of berberine, coptisine and palmatine while the PLS model was more suitable for the analysis of epiberberine and jatrorrhizine. The performance of the optimal models was achieved as follows: the correlation coefficient (R) for berberine, coptisine, palmatine, epiberberine and jatrorrhizine was 0.9958, 0.9956, 0.9959, 0.9963 and 0.9923, respectively; the root mean square error of validation (RMSEP) was 0.5093, 0.0578, 0.0443, 0.0563 and 0.0090, respectively. Furthermore, for the comprehensive exploitation and utilization of plant resource of Coptidis Rhizoma, the established NIR models were used to analysis the content of 5 active alkaloids in 4 parts of Coptidis Rhizoma and 4 main origin of places. This work demonstrated that NIRS may be a promising method as routine screening for off-line fast analysis or on-line quality assessment of traditional Chinese medicine (TCM).

Identification of geographical origin of sesame seeds by near infrared spectroscopy

International Nuclear Information System (INIS)

Kwon, Y.K.; Cho, R.K.

1998-01-01

Geographical origin of the Korean, Chinese and Japanese sesame seeds were identified very high accuracy by NIR spectroscopy. The NIR instrument of filter type showed the same accuracy of the monochromator scanning type to identify the geographical origin of the sesame seeds. in case of adulteration between the Korean and Chinese sesame seeds, the ratio of addition could be determined about 10% error level. The reason of identification of geographical origin by NIR spectroscopy, it was supposed to the difference of oil cake substance

Determination of SFC, FFA, and equivalent reaction time for enzymatically interestified oils using NIRS

DEFF Research Database (Denmark)

Houmøller, Lars P.; Kristensen, Dorthe; Rosager, Helle

2007-01-01

The use of near infrared spectroscopy (NIRS) for rapid determination of the degree of interesterification of blends of palm stearin, coconut oil, and rapeseed oil obtained using an immobilized Thermomyces lanuginosa lipase at 70 ◦C was investigated. Interesterification was carried out by applying...... that NIRS could be used to replace the traditional methods for determining FFA and SFC in vegetable oils.It was possible to monitor the activity of the immobilized enzyme for interesterification of margarine oils by predicting the equivalent reaction time in a batch reactor from NIR spectra. Root mean...... square errors of prediction for two different oil blends interesterified for 300 and 170 min were 21 and 12 min, respectively....

Spectrophotometric versus NIR-MIR assessments of cowpea pods for discriminating the impact of freezing.

Science.gov (United States)

Machado, Nelson; Domínguez-Perles, Raúl; Ramos, Ana; Rosa, Eduardo As; Barros, Ana Irna

2017-10-01

Freezing represents an important storage method for vegetal foodstuffs, such as cowpea pods, and thus the impact of this process on the chemical composition of these matrices arises as a prominent issue. In this sense, the phytochemical contents in frozen cowpea pods (i.e. at 6 and 9 months) have been compared with fresh cowpea pods material, with the samples being concomitantly assessed by Fourier-transform infrared spectroscopy (FTIR), both mid-infrared (MIR) and near infrared (NIR), aiming to evaluate the potential of these techniques as a rapid tool for the traceability of these matrices. A decrease in phytochemical contents during freezing was observed, allowing the classification of samples according to the freezing period based on such variations. Also, MIR and NIR allowed discrimination of samples: the use of the first derivative demonstrated a better performance for this purpose, whereas the use of the normalized spectra gave the best correlations between the spectra and specific contents. In both cases, NIR displayed the best performance. Freezing of cowpea pods leads to a decrease of phytochemical contents, which can be monitored by FTIR spectroscopy, both within the MIR and NIR ranges, whereas the use of this technique, in tandem with chemometrics, constitutes a suitable methodology for the traceability of these matrices. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

PREDIÇÃO DOS TEORES DE COMPOSTOS FENÓLICOS E FLAVONOIDES NA PARTE AÉREA DAS ESPÉCIES Secale cereale L., Avena strigosa L. E Raphanus sativus L. POR MEIO DE ESPECTROSCOPIA NO INFRAVERMELHO PRÓXIMO (NIR

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Monique Souza

Full Text Available Spectroscopy associated with chemometrics is a non-destructive method of the samples for the prediction of phenolic compounds. The objective of the work was to apply the near infrared spectroscopy (NIR technique for the prediction of phenolic compounds and flavonoids in aerial part samples of cover crops plants Raphanus sativus L., Secale cereale L. and Avena strigosa L. Samples were collected at 60, 80 and 100 days after sowing (DAS of the plants and, after lodging (DAA, at 15 and 30 days, in an experiment implanted in the field, in the city of Ituporanga, Santa Catarina. The samples were homogenized, identified, transported on dry ice, lyophilized, crushed, sieved and stored at -20 °C for analysis. For the calibration, 84 samples were used and for the validation 10 samples. The combination of NIR spectroscopy and multivariate analysis by partial least squares regression allowed the development of prediction models of phenolics and flavonoids with associated errors averaging 10%. NIR spectroscopy is recommended for the development of calibration models because it allows to non-destructive infer phenolic and total flavonoid contents, with high analytical frequency, without the use of reagents and other inputs required by the reference method, with results very close to those obtained in the laboratory.

[Study on predicting firmness of watermelon by Vis/NIR diffuse transmittance technique].

Science.gov (United States)

Tian, Hai-Qing; Ying, Yi-Bin; Lu, Hui-Shan; Xu, Hui-Rong; Xie, Li-Juan; Fu, Xia-Ping; Yu, Hai-Yan

2007-06-01

Watermelon is a popular fruit in the world and firmness (FM) is one of the major characteristics used for assessing watermelon quality. The objective of the present research was to study the potential of visible/near Infrared (Vis/NIR) diffuse transmittance spectroscopy as a way for the nondestructive measurement of FM of watermelon. Statistical models between the spectra and FM were developed using partial least square (PLS) and principle component regression (PCR) methods. Performance of different models was assessed in terms of correlation coefficients (r) of validation set of samples and root mean square errors of prediction (RMSEP). Models for three kinds of mathematical treatments of spectra (original, first derivative and second derivative) were established. Savitsky-Goaly filter smoothing method was used for spectra data smoothing. The PLS model of the second derivative spectra gave the best prediction of FM, with a correlation coefficient (r) of 0. 974 and root mean square errors of prediction (RMSEP) of 0. 589 N using Savitsky-Goaly filter smoothing method. The results of this study indicate that NIR diffuse transmittance spectroscopy can be used to predict the FM of watermelon. The Vis/NIR diffuse transmittance technique will be valuable for the nandestructive detection large shape and thick peel fruits'.

A hybrid NIRS-EEG system for self-paced brain computer interface with online motor imagery.

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Koo, Bonkon; Lee, Hwan-Gon; Nam, Yunjun; Kang, Hyohyeong; Koh, Chin Su; Shin, Hyung-Cheul; Choi, Seungjin

2015-04-15

For a self-paced motor imagery based brain-computer interface (BCI), the system should be able to recognize the occurrence of a motor imagery, as well as the type of the motor imagery. However, because of the difficulty of detecting the occurrence of a motor imagery, general motor imagery based BCI studies have been focusing on the cued motor imagery paradigm. In this paper, we present a novel hybrid BCI system that uses near infrared spectroscopy (NIRS) and electroencephalography (EEG) systems together to achieve online self-paced motor imagery based BCI. We designed a unique sensor frame that records NIRS and EEG simultaneously for the realization of our system. Based on this hybrid system, we proposed a novel analysis method that detects the occurrence of a motor imagery with the NIRS system, and classifies its type with the EEG system. An online experiment demonstrated that our hybrid system had a true positive rate of about 88%, a false positive rate of 7% with an average response time of 10.36 s. As far as we know, there is no report that explored hemodynamic brain switch for self-paced motor imagery based BCI with hybrid EEG and NIRS system. From our experimental results, our hybrid system showed enough reliability for using in a practical self-paced motor imagery based BCI. Copyright © 2014 Elsevier B.V. All rights reserved.

Identification of Serine Conformers by Matrix-Isolation IR Spectroscopy Aided by Near-Infrared Laser Induced Conformational Change, 2D Correlation Analysis, and Quantum Mechanical Anharmonic Computations

Science.gov (United States)

Najbauer, Eszter E.; Bazsó, Gábor; Apóstolo, Rui; Fausto, Rui; Biczysko, Malgorzata; Barone, Vincenzo; Tarczay, György

2018-01-01

The conformers of α-serine were investigated by matrix-isolation IR spectroscopy combined with NIR laser irradiation. This method, aided by 2D correlation analysis, enabled unambiguously grouping the spectral lines to individual conformers. On the basis of comparison of at least nine experimentally observed vibrational transitions of each conformer with empirically scaled (SQM) and anharmonic (GVPT2) computed IR spectra, 6 conformers were identified. In addition, the presence of at least one more conformer in Ar matrix was proved, and a short-lived conformer with a half-live of (3.7±0.5)·103 s in N2 matrix was generated by NIR irradiation. The analysis of the NIR laser induced conversions revealed that the excitation of the stretching overtone of both the side-chain and the carboxylic OH groups can effectively promote conformational changes, but remarkably different paths were observed for the two kinds of excitations. PMID:26201050

Upconverting and NIR emitting rare earth based nanostructures for NIR-bioimaging

Science.gov (United States)

Hemmer, Eva; Venkatachalam, Nallusamy; Hyodo, Hiroshi; Hattori, Akito; Ebina, Yoshie; Kishimoto, Hidehiro; Soga, Kohei

2013-11-01

In recent years, significant progress was achieved in the field of nanomedicine and bioimaging, but the development of new biomarkers for reliable detection of diseases at an early stage, molecular imaging, targeting and therapy remains crucial. The disadvantages of commonly used organic dyes include photobleaching, autofluorescence, phototoxicity and scattering when UV (ultraviolet) or visible light is used for excitation. The limited penetration depth of the excitation light and the visible emission into and from the biological tissue is a further drawback with regard to in vivo bioimaging. Lanthanide containing inorganic nanostructures emitting in the near-infrared (NIR) range under NIR excitation may overcome those problems. Due to the outstanding optical and magnetic properties of lanthanide ions (Ln3+), nanoscopic host materials doped with Ln3+, e.g. Y2O3:Er3+,Yb3+, are promising candidates for NIR-NIR bioimaging. Ln3+-doped gadolinium-based inorganic nanostructures, such as Gd2O3:Er3+,Yb3+, have a high potential as opto-magnetic markers allowing the combination of time-resolved optical imaging and magnetic resonance imaging (MRI) of high spatial resolution. Recent progress in our research on over-1000 nm NIR fluorescent nanoprobes for in vivo NIR-NIR bioimaging will be discussed in this review.In recent years, significant progress was achieved in the field of nanomedicine and bioimaging, but the development of new biomarkers for reliable detection of diseases at an early stage, molecular imaging, targeting and therapy remains crucial. The disadvantages of commonly used organic dyes include photobleaching, autofluorescence, phototoxicity and scattering when UV (ultraviolet) or visible light is used for excitation. The limited penetration depth of the excitation light and the visible emission into and from the biological tissue is a further drawback with regard to in vivo bioimaging. Lanthanide containing inorganic nanostructures emitting in the near

Effective Connectivity of Cortical Sensorimotor Networks During Finger Movement Tasks: A Simultaneous fNIRS, fMRI, EEG Study.

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Anwar, A R; Muthalib, M; Perrey, S; Galka, A; Granert, O; Wolff, S; Heute, U; Deuschl, G; Raethjen, J; Muthuraman, Muthuraman

2016-09-01

Recently, interest has been growing to understand the underlying dynamic directional relationship between simultaneously activated regions of the brain during motor task performance. Such directionality analysis (or effective connectivity analysis), based on non-invasive electrophysiological (electroencephalography-EEG) and hemodynamic (functional near infrared spectroscopy-fNIRS; and functional magnetic resonance imaging-fMRI) neuroimaging modalities can provide an estimate of the motor task-related information flow from one brain region to another. Since EEG, fNIRS and fMRI modalities achieve different spatial and temporal resolutions of motor-task related activation in the brain, the aim of this study was to determine the effective connectivity of cortico-cortical sensorimotor networks during finger movement tasks measured by each neuroimaging modality. Nine healthy subjects performed right hand finger movement tasks of different complexity (simple finger tapping-FT, simple finger sequence-SFS, and complex finger sequence-CFS). We focused our observations on three cortical regions of interest (ROIs), namely the contralateral sensorimotor cortex (SMC), the contralateral premotor cortex (PMC) and the contralateral dorsolateral prefrontal cortex (DLPFC). We estimated the effective connectivity between these ROIs using conditional Granger causality (GC) analysis determined from the time series signals measured by fMRI (blood oxygenation level-dependent-BOLD), fNIRS (oxygenated-O2Hb and deoxygenated-HHb hemoglobin), and EEG (scalp and source level analysis) neuroimaging modalities. The effective connectivity analysis showed significant bi-directional information flow between the SMC, PMC, and DLPFC as determined by the EEG (scalp and source), fMRI (BOLD) and fNIRS (O2Hb and HHb) modalities for all three motor tasks. However the source level EEG GC values were significantly greater than the other modalities. In addition, only the source level EEG showed a

Sensitivity of near-infrared spectroscopy and diffuse correlation spectroscopy to brain hemodynamics: simulations and experimental findings during hypercapnia.

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Selb, Juliette; Boas, David A; Chan, Suk-Tak; Evans, Karleyton C; Buckley, Erin M; Carp, Stefan A

2014-07-01

Near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) are two diffuse optical technologies for brain imaging that are sensitive to changes in hemoglobin concentrations and blood flow, respectively. Measurements for both modalities are acquired on the scalp, and therefore hemodynamic processes in the extracerebral vasculature confound the interpretation of cortical hemodynamic signals. The sensitivity of NIRS to the brain versus the extracerebral tissue and the contrast-to-noise ratio (CNR) of NIRS to cerebral hemodynamic responses have been well characterized, but the same has not been evaluated for DCS. This is important to assess in order to understand their relative capabilities in measuring cerebral physiological changes. We present Monte Carlo simulations on a head model that demonstrate that the relative brain-to-scalp sensitivity is about three times higher for DCS (0.3 at 3 cm) than for NIRS (0.1 at 3 cm). However, because DCS has higher levels of noise due to photon-counting detection, the CNR is similar for both modalities in response to a physiologically realistic simulation of brain activation. Even so, we also observed higher CNR of the hemodynamic response during graded hypercapnia in adult subjects with DCS than with NIRS.

On-line NIR analysis of fat, water and protein in industrial scale ground meat batches.

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Tøgersen, G; Isaksson, T; Nilsen, B N; Bakker, E A; Hildrum, K I

1999-01-01

Fat, water and protein contents in industrial scale meat batches were determined on-line by near infrared (NIR) reflectance spectroscopy. The NIR instrument was mounted at the outlet of a large meat grinder, and the measurements were performed in an industrial environment. Beef and pork samples, with chemical compositions of 7-26% fat, 58-75% water and 15-21% protein, were processed with hole diameters of 13mm in the grinder plate. Calibrations were made both for a combined set of beef and pork samples, and for separate sets of beef and pork samples. Validations were either done by full cross validation of the calibration set, or by bias corrected prediction of a test set. Prediction errors for the two sample sets, expressed as root mean square errors of cross validation or standard error of prediction, were in the ranges 0.82-1.49% fat, 0.94-1.33% water and 0.35-0.70% protein, depending of sample set and species of animal. The presented application is an improvement to the existing manual meat standardisation procedure, and has been implemented for regular use in a Norwegian meat manufacturing plant.

Principal component analysis for the forensic discrimination of black inkjet inks based on the Vis-NIR fibre optics reflection spectra.

Science.gov (United States)

Gál, Lukáš; Oravec, Michal; Gemeiner, Pavol; Čeppan, Michal

2015-12-01

Nineteen black inkjet inks of six different brands were examined by fibre optics reflection spectroscopy in Visible and Near Infrared Region (Vis-NIR FORS) directly on paper with a view to achieving good resolution between them. These different inks were tested on nineteen different inkjet printers from three brands. Samples were obtained from prints by reflection probe. Processed reflection spectra in the range 500-1000 nm were used as samples in principal component analysis. Variability between spectra of the same ink obtained from different prints, as well as between spectra of square areas and lines was examined. For both spectra obtained from square areas and lines reference, Principal Component Analysis (PCA) models were created. According to these models, the inkjet inks were divided into clusters. PCA method is able to separate inks containing carbon black as main colorant from the other inks using other colorants. Some spectra were recorded from another piece of printer and used as validation samples. Spectra of validation samples were projected onto reference PCA models. According to position of validation samples in score plots it can be concluded that PCA based on Vis-NIR FORS can reliably differentiate inkjet inks which are included in the reference database. The presented method appears to be a suitable tool for forensic examination of questioned documents containing inkjet inks. Inkjet inks spectra were obtained without extraction or cutting sample with possibility to measure out of the laboratory. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Predicting rapeseed oil content with near-infrared spectroscopy

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Roberta Rossato

2013-12-01

Full Text Available The objective of this work was to establish a calibration equation and to estimate the efficiency of near-infrared reflectance (NIR spectroscopy for evaluating rapeseed oil content in Southern Brazil. Spectral data from 124 half-sib families were correlated with oil contents determined by the chemical method. The accuracy of the equation was verified by coefficient of determination (R² of 0.92, error of calibration (SEC of 0.78, and error of performance (SEP of 1.22. The oil content of ten genotypes, which were not included in the calibration with NIR, was similar to the one obtained by the standard chemical method. NIR spectroscopy is adequate to differentiate oil content of rapeseed genotypes.

Gastric cancer differentiation using Fourier transform near-infrared spectroscopy with unsupervised pattern recognition

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Yi, Wei-song; Cui, Dian-sheng; Li, Zhi; Wu, Lan-lan; Shen, Ai-guo; Hu, Ji-ming

2013-01-01

The manuscript has investigated the application of near-infrared (NIR) spectroscopy for differentiation gastric cancer. The 90 spectra from cancerous and normal tissues were collected from a total of 30 surgical specimens using Fourier transform near-infrared spectroscopy (FT-NIR) equipped with a fiber-optic probe. Major spectral differences were observed in the CH-stretching second overtone (9000-7000 cm-1), CH-stretching first overtone (6000-5200 cm-1), and CH-stretching combination (4500-4000 cm-1) regions. By use of unsupervised pattern recognition, such as principal component analysis (PCA) and cluster analysis (CA), all spectra were classified into cancerous and normal tissue groups with accuracy up to 81.1%. The sensitivity and specificity was 100% and 68.2%, respectively. These present results indicate that CH-stretching first, combination band and second overtone regions can serve as diagnostic markers for gastric cancer.

Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS

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Jiang, Hui; Zhang, Hang; Chen, Quansheng; Mei, Congli; Liu, Guohai

2015-10-01

The use of wavelength variable selection before partial least squares discriminant analysis (PLS-DA) for qualitative identification of solid state fermentation degree by FT-NIR spectroscopy technique was investigated in this study. Two wavelength variable selection methods including competitive adaptive reweighted sampling (CARS) and stability competitive adaptive reweighted sampling (SCARS) were employed to select the important wavelengths. PLS-DA was applied to calibrate identified model using selected wavelength variables by CARS and SCARS for identification of solid state fermentation degree. Experimental results showed that the number of selected wavelength variables by CARS and SCARS were 58 and 47, respectively, from the 1557 original wavelength variables. Compared with the results of full-spectrum PLS-DA, the two wavelength variable selection methods both could enhance the performance of identified models. Meanwhile, compared with CARS-PLS-DA model, the SCARS-PLS-DA model achieved better results with the identification rate of 91.43% in the validation process. The overall results sufficiently demonstrate the PLS-DA model constructed using selected wavelength variables by a proper wavelength variable method can be more accurate identification of solid state fermentation degree.

Monitoring Industrial Food Processes Using Spectroscopy & Chemometrics

DEFF Research Database (Denmark)

Pedersen, Dorthe Kjær; Engelsen, Søren Balling

2001-01-01

In the last decade rapid spectroscopic measurements have revolutionized quality control in practically all areas of primary food and feed production. Near-infrared spectroscopy (NIR & NIT) has been implemented for monitoring the quality of millions of samples of cereals, milk and meat with unprec......In the last decade rapid spectroscopic measurements have revolutionized quality control in practically all areas of primary food and feed production. Near-infrared spectroscopy (NIR & NIT) has been implemented for monitoring the quality of millions of samples of cereals, milk and meat...

Robust and Automated Internal Quality Grading of a Chinese Green Tea (Longjing by Near-Infrared Spectroscopy and Chemometrics

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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.

Tissue oxygenation and haemodynamics measurement with spatially resolved NIRS

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Zhang, Y.; Scopesi, F.; Serra, G.; Sun, J. W.; Rolfe, P.

2010-08-01

We describe the use of Near Infrared Spectroscopy (NIRS) for the non-invasive investigation of changes in haemodynamics and oxygenation of human peripheral tissues. The goal was to measure spatial variations of tissue NIRS oxygenation variables, namely deoxy-haemoglobin (HHb), oxy-haemoglobin (HbO2), total haemoglobin (HbT), and thereby to evaluate the responses of the peripheral circulation to imposed physiological challenges. We present a skinfat- muscle heterogeneous tissue model with varying fat thickness up to 15mm and a Monte Carlo simulation of photon transport within this model. The mean partial path length and the mean photon visit depth in the muscle layer were derived for different source-detector spacing. We constructed NIRS instrumentation comprising of light-emitting diodes (LED) as light sources at four wavelengths, 735nm, 760nm, 810nm and 850nm and sensitive photodiodes (PD) as the detectors. Source-detector spacing was varied to perform measurements at different depths within forearm tissue. Changes in chromophore concentration in response to venous and arterial occlusion were calculated using the modified Lambert-Beer Law. Studies in fat and thin volunteers indicated greater sensitivity in the thinner subjects for the tissue oxygenation measurement in the muscle layer. These results were consistent with those found using Monte Carlo simulation. Overall, the results of this investigation demonstrate the usefulness of the NIRS instrument for deriving spatial information from biological tissues.

Estimation of crosstalk in LED fNIRS by photon propagation Monte Carlo simulation

Science.gov (United States)

Iwano, Takayuki; Umeyama, Shinji

2015-12-01

fNIRS (functional near-Infrared spectroscopy) can measure brain activity non-invasively and has advantages such as low cost and portability. While the conventional fNIRS has used laser light, LED light fNIRS is recently becoming common in use. Using LED for fNIRS, equipment can be more inexpensive and more portable. LED light, however, has a wider illumination spectrum than laser light, which may change crosstalk between the calculated concentration change of oxygenated and deoxygenated hemoglobins. The crosstalk is caused by difference in light path length in the head tissues depending on wavelengths used. We conducted Monte Carlo simulations of photon propagation in the tissue layers of head (scalp, skull, CSF, gray matter, and white matter) to estimate the light path length in each layers. Based on the estimated path lengths, the crosstalk in fNIRS using LED light was calculated. Our results showed that LED light more increases the crosstalk than laser light does when certain combinations of wavelengths were adopted. Even in such cases, the crosstalk increased by using LED light can be effectively suppressed by replacing the value of extinction coefficients used in the hemoglobin calculation to their weighted average over illumination spectrum.

Simultaneous FT-NIR and ESR analysis to study of the kinetics of photo induced polymerization of vinyl radical polymers

International Nuclear Information System (INIS)

Le, T.T.; Hill, D.J.T.; Pomery, P.J.

2000-01-01

Full text:The rate parameters for free vinyl radical polymerizations are difficult to determine accurately over the whole range of conversion. For systems which polymerize rapidly and for networks, this is a particular problem, because small differences in polymerization conditions, e.g., temperature, initiator concentration, photon flux, etc., can cause a large change in the time evolution of the concentration of carbon double bonds and radicals if these are monitored in separate experiments. The IUPAC Working Party on the Modeling of kinetics and processes of polymerization has the role of recommending the 'best' values for the kinetic parameters, using pulsed-laser polymerization (PLP) in conjunction with molar mass distribution (MMD) to determine k p as a function of temperature (T deg C) for bulk free-radical polymerization of methyl methacrylate at low conversions and ambient temperature. The vinyl radical polymers used in this study were methyl methacrylate and ethylene glycol dimethacrylate. In the past kinetic studies of vinyl photo-polymerization required the time dependence of the monomer and radical concentrations to be monitored separately by using FT-NIR spectroscopy and ESR spectroscopy, respectively. For the systems which polymerize rapidly, small differences in the conditions for two measurements, e.g. temperature and light intensity, can introduce significant errors. Hyphenated experiments involving in-situ ESR and FT-NIR spectroscopies using fibre optic, can overcome these problems. In this paper, the radical and monomer concentrations were measured under the same experimental conditions using the above techniques. The results obtained were used to evaluate the kinetic parameters for free radical vinyl polymerizations

Burned bones forensic investigations employing near infrared spectroscopy

OpenAIRE

Cascant, Mari Merce; Rubio, Sonia; Gallello, Gianni; Pastor, Agustin; Garrigues, Salvador; De la Guardia, Miguel

2017-01-01

The use of near infrared (NIR) spectroscopy was evaluated, by using chemometric tools, for the study of the environmental impact on burned bones. Spectra of internal and external parts of burned bones, together with sediment samples, were treated by Principal Component Analysis and cluster classification as exploratory techniques to select burned bone samples, less affected by environmental processes, to properly carry out forensic studies. Partial Least Square Discriminant Analysis was used ...

SHARK-NIR system design analysis overview

Science.gov (United States)

Viotto, Valentina; Farinato, Jacopo; Greggio, Davide; Vassallo, Daniele; Carolo, Elena; Baruffolo, Andrea; Bergomi, Maria; Carlotti, Alexis; De Pascale, Marco; D'Orazi, Valentina; Fantinel, Daniela; Magrin, Demetrio; Marafatto, Luca; Mohr, Lars; Ragazzoni, Roberto; Salasnich, Bernardo; Verinaud, Christophe

2016-08-01

In this paper, we present an overview of the System Design Analysis carried on for SHARK-NIR, the coronagraphic camera designed to take advantage of the outstanding performance that can be obtained with the FLAO facility at the LBT, in the near infrared regime. Born as a fast-track project, the system now foresees both coronagraphic direct imaging and spectroscopic observing mode, together with a first order wavefront correction tool. The analysis we here report includes several trade-offs for the selection of the baseline design, in terms of optical and mechanical engineering, and the choice of the coronagraphic techniques to be implemented, to satisfy both the main scientific drivers and the technical requirements set at the level of the telescope. Further care has been taken on the possible exploitation of the synergy with other LBT instrumentation, like LBTI. A set of system specifications is then flown down from the upper level requirements to finally ensure the fulfillment of the science drivers. The preliminary performance budgets are presented, both in terms of the main optical planes stability and of the image quality, including the contributions of the main error sources in different observing modes.

Corticospinal excitability changes to anodal tDCS elucidated with NIRS-EEG joint-imaging

DEFF Research Database (Denmark)

Jindal, Utkarsh; Sood, Mehak; Chowdhury, Shubhajit Roy

2015-01-01

Transcranial direct current stimulation (tDCS) has been shown to modulate corticospinal excitability. We used near-infrared spectroscopy (NIRS) - electroencephalography (EEG) joint-imaging during and after anodal tDCS to measure changes in mean cerebral haemoglobin oxygen saturation (rSO2) along...... with changes in the log-transformed mean-power of EEG within 0.5 Hz - 11.25 Hz. In two separate studies, we investigated local post-tDCS alterations from baseline at the site of anodal tDCS using NIRS-EEG/tDCS joint-imaging as well as local post-tDCS alterations in motor evoked potentials (MEP...... that the innovative technologies for portable NIRS-EEG neuroimaging may be leveraged to objectively quantify the progress (e.g., corticospinal excitability alterations) and dose tDCS intervention as an adjuvant treatment during neurorehabilitation....

Development of NIR calibration models to assess year-to-year variation in total non-structural carbohydrates in grasses using PLSR

DEFF Research Database (Denmark)

Shetty, Nisha; Gislum, René; Jensen, Anne Mette Dahl

2012-01-01

Near-infrared (NIR) spectroscopy was used in combination with chemometrics to quantify total nonstructural carbohydrates (TNC) in grass samples in order to overcome year-to-year variation. A total of 1103 above-ground plant and root samples were collected from different field and pot experiments...... and with various experimental designs in the period from 2001 to 2005. A calibration model was developed using partial least squares regression (PLSR). The calibration model on a large data set spanning five years demonstrated that quantification of TNC using NIR spectroscopy was possible with an acceptable low...

Underwater near-infrared spectroscopy can measure training adaptations in adolescent swimmers

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Ben Jones

2018-04-01

Full Text Available The development of an underwater near-infrared spectroscopy (uNIRS device has enabled previously unattainable measurements of peripheral muscle hemodynamics and oxygenation to be taken within the natural aquatic environment. The purposes of this study were (i to trial the use of uNIRS, in a real world training study, and (ii to monitor the effects of a swim training program upon muscle oxygenation status in short distance swimming. A total of 14 junior club level swimmers completed a repeated swim sprint test before and after an eight week endurance training program. A waterproof, portable Near-Infrared Spectroscopy device was attached to the vastus lateralis. uNIRS successfully measured changes in muscle oxygenation and blood volume in all individuals; rapid sub-second time resolution of the device was able to demonstrate muscle oxygenation changes during the characteristic swim movements. Post training heart rate recovery and swim performance time were significantly improved. uNIRS data also showed significant changes. A larger rise in deoxyhemoglobin during individual sprints suggested training induced an increase in muscle oxygen extraction; a faster recovery time for muscle oxygenation suggested positive training induced changes and significant changes in muscle blood flow also occur. As a strong correlation was seen between an increased reoxygenation rate and an improved swim performance time, these findings support the use of uNIRS as a new performance analysis tool in swimming.

fNIRS evidence of prefrontal regulation of frustration in early childhood.

Science.gov (United States)

Perlman, Susan B; Luna, Beatriz; Hein, Tyler C; Huppert, Theodore J

2014-01-15

The experience of frustration is common in early childhood, yet some children seem to possess a lower tolerance for frustration than others. Characterizing the biological mechanisms underlying a wide range of frustration tolerance observed in early childhood may inform maladaptive behavior and psychopathology that is associated with this construct. The goal of this study was to measure prefrontal correlates of frustration in 3-5-year-old children, who are not readily adaptable for typical neuroimaging approaches, using functional near infrared spectroscopy (fNIRS). fNIRS of frontal regions were measured as frustration was induced in children through a computer game where a desired and expected prize was "stolen" by an animated dog. A fNIRS general linear model (GLM) was used to quantify the correlation of brain regions with the task and identify areas that were statistically different between the winning and frustrating test conditions. A second-level voxel-based ANOVA analysis was then used to correlate the amplitude of each individual's brain activation with measure of parent-reported frustration. Experimental results indicated increased activity in the middle prefrontal cortex during winning of a desired prize, while lateral prefrontal cortex activity increased during frustration. Further, activity increase in lateral prefrontal cortex during frustration correlated positively with parent-reported frustration tolerance. These findings point to the role of the lateral prefrontal cortex as a potential region supporting the regulation of emotion during frustration. Copyright © 2013 Elsevier Inc. All rights reserved.

Light interaction with nano-structured diatom frustule, from UV-A to NIR

DEFF Research Database (Denmark)

Maibohm, Christian; Nielsen, Josefine Holm; Rottwitt, Karsten

2016-01-01

symmetry where morphological parameters vary between the different investigated species. We report how light interacts with the frustule in the wavelength range from UV-A (320-380 nm) to NIR (900 nm). High resolution spectroscopy and CCD images are used to identify photoluminescence (PL) and variations...

Spatio-Temporal Image Correlation Spectroscopy Measurements of Flow Demonstrated in Microfluidic Channels

Science.gov (United States)

Rossow, Molly; Mantulin, William W.; Gratton, Enrico

2009-01-01

Accurate blood flow measurements during surgery can improve the operations chance of success. We developed Near-infrared Spatio-Temporal Image Spectroscopy (NIR-STICS), which has the potential to make blood flow measurements that are difficult to accomplish with existing methods. Specifically, we propose the technique and we show feasibility on phantom measurements. NIR-STICS has the potential of measuring the fluid velocity in small blood vessels (less than 1mm in diameter) and of creating a map of blood flow rates over an area of approximately 1cm2. NIR-STICS employs near-infrared spectroscopy to probe inside blood vessel walls and spatio-temporal image correlation spectroscopy to directly—without the use of a model—extract fluid velocity from the fluctuations within an image. Here we present computer simulations and experiments on a phantom system that demonstrate the effectiveness of NIR-STICS. PMID:19405744

High-throughput prediction of tablet weight and trimethoprim content of compound sulfamethoxazole tablets for controlling the uniformity of dosage units by NIR.

Science.gov (United States)

Dong, Yanhong; Li, Juan; Zhong, Xiaoxiao; Cao, Liya; Luo, Yang; Fan, Qi

2016-04-15

This paper establishes a novel method to simultaneously predict the tablet weight (TW) and trimethoprim (TMP) content of compound sulfamethoxazole tablets (SMZCO) by near infrared (NIR) spectroscopy with partial least squares (PLS) regression for controlling the uniformity of dosage units (UODU). The NIR spectra for 257 samples were measured using the optimized parameter values and pretreated using the optimized chemometric techniques. After the outliers were ignored, two PLS models for predicting TW and TMP content were respectively established by using the selected spectral sub-ranges and the reference values. The TW model reaches the correlation coefficient of calibration (R(c)) 0.9543 and the TMP content model has the R(c) 0.9205. The experimental results indicate that this strategy expands the NIR application in controlling UODU, especially in the high-throughput and rapid analysis of TWs and contents of the compound pharmaceutical tablets, and may be an important complement to the common NIR on-line analytical method for pharmaceutical tablets. Copyright © 2016 Elsevier B.V. All rights reserved.

DSC, FT-IR, NIR, NIR-PCA and NIR-ANOVA for determination of chemical stability of diuretic drugs: impact of excipients

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Gumieniczek Anna

2018-03-01

Full Text Available It is well known that drugs can directly react with excipients. In addition, excipients can be a source of impurities that either directly react with drugs or catalyze their degradation. Thus, binary mixtures of three diuretics, torasemide, furosemide and amiloride with different excipients, i.e. citric acid anhydrous, povidone K25 (PVP, magnesium stearate (Mg stearate, lactose, D-mannitol, glycine, calcium hydrogen phosphate anhydrous (CaHPO4 and starch, were examined to detect interactions. High temperature and humidity or UV/VIS irradiation were applied as stressing conditions. Differential scanning calorimetry (DSC, FT-IR and NIR were used to adequately collect information. In addition, chemometric assessments of NIR signals with principal component analysis (PCA and ANOVA were applied.

Distraction decreases prefrontal oxygenation: A NIRS study.

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Ozawa, Sachiyo; Hiraki, Kazuo

2017-04-01

When near-infrared spectroscopy (NIRS) is used to measure emotion-related cerebral blood flow (CBF) changes in the prefrontal cortex regions, the functional distinction of CBF changes is often difficult because NIRS is unable to measure neural activity in deeper brain regions that play major roles in emotional processing. The CBF changes could represent cognitive control of emotion and emotional responses to emotional materials. Supposing that emotion-related CBF changes in the prefrontal cortex regions during distraction are emotional responses, we examined whether oxygenated hemoglobin (oxyHb) decreases. Attention-demanding tasks cause blood flow decreases, and we thus compared the effects of visually paced tapping with different tempos, on distraction. The results showed that the oxyHb level induced by emotional stimulation decreased with fast-tempo tapping significantly more than slow-tempo tapping in ventral medial prefrontal cortex regions. Moreover, a Global-Local task following tapping showed significantly greater local-minus-global response time (RT) difference scores in the fast- and mid-tempo condition compared with those in the slow-tempo, suggesting an increased attentional focus, and decreased negative emotion. The overall findings indicate that oxyHb changes in a relatively long distraction task, as measured by NIRS, are associated with emotional responses, and oxyHb can be decreased by successfully performing attention-demanding distraction tasks. Copyright © 2017 Elsevier Inc. All rights reserved.

CMOS integrated avalanche photodiodes and frequency-mixing optical sensor front end for portable NIR spectroscopy instruments.

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Yun, Ruida; Sthalekar, Chirag; Joyner, Valencia M

2011-01-01

This paper presents the design and measurement results of two avalanche photodiode structures (APDs) and a novel frequency-mixing transimpedance amplifier (TIA), which are key building blocks towards a monolithically integrated optical sensor front end for near-infrared (NIR) spectroscopy applications. Two different APD structures are fabricated in an unmodified 0.18 \\im CMOS process, one with a shallow trench isolation (STI) guard ring and the other with a P-well guard ring. The APDs are characterized in linear mode. The STI bounded APD demonstrates better performance and exhibits 3.78 A/W responsivity at a wavelength of 690 nm and bias voltage of 10.55 V. The frequency-mixing TIA (FM-TIA) employs a T-feedback network incorporating gate-controlled transistors for resistance modulation, enabling the simultaneous down-conversion and amplification of the high frequency modulated photodiode (PD) current. The TIA achieves 92 dS Ω conversion gain with 0.5 V modulating voltage. The measured IIP(3) is 10.6/M. The amplifier together with the 50 Ω output buffer draws 23 mA from a1.8 V power supply.

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

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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.

[Determination of acidity and vitamin C in apples using portable NIR analyzer].

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Yang, Fan; Li, Ya-Ting; Gu, Xuan; Ma, Jiang; Fan, Xing; Wang, Xiao-Xuan; Zhang, Zhuo-Yong

2011-09-01

Near infrared (NIR) spectroscopy technology based on a portable NIR analyzer, combined with kernel Isomap algorithm and generalized regression neural network (GRNN) has been applied to establishing quantitative models for prediction of acidity and vitamin C in six kinds of apple samples. The obtained results demonstrated that the fitting and the predictive accuracy of the models with kernel Isomap algorithm were satisfactory. The correlation between actual and predicted values of calibration samples (R(c)) obtained by the acidity model was 0.999 4, and for prediction samples (R(p)) was 0.979 9. The root mean square error of prediction set (RMSEP) was 0.055 8. For the vitamin C model, R(c) was 0.989 1, R(p) was 0.927 2, and RMSEP was 4.043 1. Results proved that the portable NIR analyzer can be a feasible tool for the determination of acidity and vitamin C in apples.

Practical guide to interpretive near-infrared spectroscopy

CERN Document Server

Workman, Jr, Jerry

2007-01-01

Containing focused, comprehensive coverage, Practical Guide to Interpretive Near-Infrared Spectroscopy gives you the tools necessary to interpret NIR spectra. The authors present extensive tables, charts, and figures with NIR absorption band assignments and structural information for a broad range of functional groups, organic compounds, and polymers. They include visual spectral representation of all major compound functional groupings and NIR frequency ranges. Organized by functional group type and chemical structure, based on standard compound classification, the chapters are easy to

Detection of changes in fuel quality during storage of sawdust from pine and spruce by using gas chromatography - Mass spectrometry (GC-MS) and VIS-NIR-spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Arshadi, Mehrdad; Nilsson, David; Geladi, Paul (Unit of Biomass Technology and Chemistry, Swedish Univ. of Agricultural Sciences, SE-904 03 Umeaa (Sweden)). e-mail: mehrdad.arshadi@btk.slu.se

2008-10-15

Fuel pellets made of sawdust represent a renewable energy source for heat production. The raw material comes from sawmills and sawdust is used in the pellet mills and for reasons of logistics there is a need for storage of large quantities of the raw material. Long-term storage induces changes in the sawdust and therefore processing parameters for pellets production have to be adapted. This makes knowledge of storage time or maturity necessary. Two examples of experimental studies are presented: An industrial storage of pine and spruce sawdust was carried out over a period of 16 weeks in order to monitor the changes in the quality of sawdust during storage. Samples were taken out every week and all samples were analysed by VIS-NIR spectroscopy while some samples were analysed by GC-MS for their composition of fatty- and resin acids. The resulting data were subjected to multivariate data analysis. GC-MS data showed the difference between pine and spruce sawdust and the influence of maturity. This maturity effect could be associated with the decrease in fatty- and resin acids due to auto oxidative reactions. Multivariate analysis of the VIS-NIR data showed a major effect due to maturity associated with a colour change and also weaker effects of fatty- and resin acids differences. PLS regression was used to predict the storage time with RMSEP values between 10 and 15 days. However, since weather conditions, precipitation and seasonal variation have high influence on the speed of maturing of sawdust it will be necessary to continuously determine the degree of maturity. A second similar study is used as a complementary way of corroborating the results of the first one

Fourier transform mid-infrared (MIR) and near-infrared (NIR) spectroscopy for rapid quality assessment of Chinese medicine preparation Honghua Oil.

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Wu, Yan-Wen; Sun, Su-Qin; Zhou, Qun; Leung, Hei-Wun

2008-02-13

Honghua Oil (HHO), a traditional Chinese medicine (TCM) oil preparation, is a mixture of several plant essential oils. In this text, the extended ranges of Fourier transform mid-infrared (FT-MIR) and near infrared (FT-NIR) were recorded for 48 commercially available HHOs of different batches from nine manufacturers. The qualitative and quantitative analysis of three marker components, alpha-pinene, methyl salicylate and eugenol, in different HHO products were performed rapidly by the two vibrational spectroscopic methods, i.e. MIR with horizontal attenuated total reflection (HATR) accessory and NIR with direct sampling technique, followed by partial least squares (PLS) regression treatment of the set of spectra obtained. The results indicated that it was successful to identify alpha-pinene, methyl salicylate and eugenol in all of the samples by simple inspection of the MIR-HATR spectra. Both PLS models established with MIR-HATR and NIR spectral data using gas chromatography (GC) peak areas as calibration reference showed a good linear correlation for each of all three target substances in HHO samples. The above spectroscopic techniques may be the promising methods for the rapid quality assessment/quality control (QA/QC) of TCM oil preparations.

Sensitivity of near-infrared spectroscopy and diffuse correlation spectroscopy to brain hemodynamics: simulations and experimental findings during hypercapnia

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Selb, Juliette; Boas, David A.; Chan, Suk-Tak; Evans, Karleyton C.; Buckley, Erin M.; Carp, Stefan A.

2014-01-01

Abstract. Near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) are two diffuse optical technologies for brain imaging that are sensitive to changes in hemoglobin concentrations and blood flow, respectively. Measurements for both modalities are acquired on the scalp, and therefore hemodynamic processes in the extracerebral vasculature confound the interpretation of cortical hemodynamic signals. The sensitivity of NIRS to the brain versus the extracerebral tissue and the contrast-to-noise ratio (CNR) of NIRS to cerebral hemodynamic responses have been well characterized, but the same has not been evaluated for DCS. This is important to assess in order to understand their relative capabilities in measuring cerebral physiological changes. We present Monte Carlo simulations on a head model that demonstrate that the relative brain-to-scalp sensitivity is about three times higher for DCS (0.3 at 3 cm) than for NIRS (0.1 at 3 cm). However, because DCS has higher levels of noise due to photon-counting detection, the CNR is similar for both modalities in response to a physiologically realistic simulation of brain activation. Even so, we also observed higher CNR of the hemodynamic response during graded hypercapnia in adult subjects with DCS than with NIRS. PMID:25453036

Application of near-infrared spectroscopy to preservative-treated wood

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Chi-Leung So; Stan T. Lebow; Thomas L. Eberhardt; Leslie H. Groom; Todd F. Shupe

2009-01-01

Near infrared (NIR) spectroscopy is now a widely-used technique in the field of forest products, especially for physical and mechanical property determinations. This technique is also ideal for the chemical analysis of wood. There has been a growing need to find a rapid, inexpensive and reliable method to distinguish between preservative-treated and untreated waste...

Application of FT NIR Spectroscopy in the Determination of Basic Physical and Chemical Properties of Sausages

Directory of Open Access Journals (Sweden)

Zuzana Procházková

2010-01-01

Full Text Available The objectives of this study were to develop calibration models for determination of water activity and the content of fat, dry matter, salt, non collagen muscle protein and pH in dry cooked sausages. Samples (n = 42 were scanned in FT-NIR Analyzer and simultaneously analyzed by standard methods. The spectra were measured in the reflectance mode with a compressive cell between 10 000 and 4 000 cm-1, averaging 100 scans. Calibration models were developed using the partial least squares (PLS method. These calibration models were checked later by crossvalidation. The following statistical values were obtained: R (correlation coefficient = 0.997 and SEC (standard error of calibration = 0.002 for water activity, R = 0.966 and SEC = 0.023 for pH, R = 0.995 and SEC = 0.970 for dry matter content, R = 0.995 and SEC = 0.045 for salt content, R = 0.965 and SEC = 0.652 for non collagen muscle protein, R = 0.996 and SEC = 0.559 for fat content. The results of the study showed that FT-NIR is a suitable method for rapid analysis of physical and chemical properties of sausages.

Real-Time Subject-Independent Pattern Classification of Overt and Covert Movements from fNIRS Signals.

Directory of Open Access Journals (Sweden)

Neethu Robinson

Full Text Available Recently, studies have reported the use of Near Infrared Spectroscopy (NIRS for developing Brain-Computer Interface (BCI by applying online pattern classification of brain states from subject-specific fNIRS signals. The purpose of the present study was to develop and test a real-time method for subject-specific and subject-independent classification of multi-channel fNIRS signals using support-vector machines (SVM, so as to determine its feasibility as an online neurofeedback system. Towards this goal, we used left versus right hand movement execution and movement imagery as study paradigms in a series of experiments. In the first two experiments, activations in the motor cortex during movement execution and movement imagery were used to develop subject-dependent models that obtained high classification accuracies thereby indicating the robustness of our classification method. In the third experiment, a generalized classifier-model was developed from the first two experimental data, which was then applied for subject-independent neurofeedback training. Application of this method in new participants showed mean classification accuracy of 63% for movement imagery tasks and 80% for movement execution tasks. These results, and their corresponding offline analysis reported in this study demonstrate that SVM based real-time subject-independent classification of fNIRS signals is feasible. This method has important applications in the field of hemodynamic BCIs, and neuro-rehabilitation where patients can be trained to learn spatio-temporal patterns of healthy brain activity.

Development and validation of NIR-chemometric methods for chemical and pharmaceutical characterization of meloxicam tablets.

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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.

NIR calibration of soluble stem carbohydrates for predicting drought tolerance in spring wheat

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Soluble stem carbohydrates are a component of drought response in wheat (Triticum aestivum L.) and other grasses. Near-infrared spectroscopy (NIR) can rapidly assay for soluble carbohydrates indirectly, but this requires a statistical model for calibration. The objectives of this study were: (i) to ...

Effects of Varying Gravity Levels on fNIRS Headgear Performance and Signal Recovery

Science.gov (United States)

Mackey, Jeffrey R.; Harrivel, Angela R.; Adamovsky, Grigory; Lewandowski, Beth E.; Gotti, Daniel J.; Tin, Padetha; Floyd, Bertram M.

2013-01-01

This paper reviews the effects of varying gravitational levels on functional Near-Infrared Spectroscopy (fNIRS) headgear. The fNIRS systems quantify neural activations in the cortex by measuring hemoglobin concentration changes via optical intensity. Such activation measurement allows for the detection of cognitive state, which can be important for emotional stability, human performance and vigilance optimization, and the detection of hazardous operator state. The technique depends on coupling between the fNIRS probe and users skin. Such coupling may be highly susceptible to motion if probe-containing headgear designs are not adequately tested. The lack of reliable and self-applicable headgear robust to the influence of motion artifact currently inhibits its operational use in aerospace environments. Both NASAs Aviation Safety and Human Research Programs are interested in this technology as a method of monitoring cognitive state of pilots and crew.

Linear regression models and k-means clustering for statistical analysis of fNIRS data.

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Bonomini, Viola; Zucchelli, Lucia; Re, Rebecca; Ieva, Francesca; Spinelli, Lorenzo; Contini, Davide; Paganoni, Anna; Torricelli, Alessandro

2015-02-01

We propose a new algorithm, based on a linear regression model, to statistically estimate the hemodynamic activations in fNIRS data sets. The main concern guiding the algorithm development was the minimization of assumptions and approximations made on the data set for the application of statistical tests. Further, we propose a K-means method to cluster fNIRS data (i.e. channels) as activated or not activated. The methods were validated both on simulated and in vivo fNIRS data. A time domain (TD) fNIRS technique was preferred because of its high performances in discriminating cortical activation and superficial physiological changes. However, the proposed method is also applicable to continuous wave or frequency domain fNIRS data sets.

[Determination of Chloride Salt Solution by NIR Spectroscopy].

Science.gov (United States)

Zhang, Bin; Chen, Jian-hong; Jiao, Ming-xing

2015-07-01

Determination of chloride salt solution by near infrared spectrum plays a very important role in Biomedicine. The near infrared spectrum analysis of Sodium chloride, potassium chloride, calcium chloride aqueous solution shows that the concentration change of chloride salt can affect hydrogen bond, resulting in the variation of near infrared spectrum of water. The temperature influence on NIR spectrum has been decreased by choosing reasonable wavelength range and the wavelength where the temperature effects are zero (isosbestic point). Chlorine salt prediction model was established based on partial least squares method and used for predicting the concentration of the chlorine ion. The impact on near infrared spectrum of the cation ionic radius, the number of ionic charge, the complex effect of ionic in water has also discussed in this article and the reason of every factor are analysed. Experimental results show that the temperature and concentration will affect the near-infrared spectrum of the solution, It is found that the effect of temperature plays the dominant role at low concentrations of chlorine salt; rather, the ionic dominates at high concentration. Chloride complexes are formed in aqueous solution, It has an effect on hydrogen bond of water combining with the cations in chlorine salt solution, Comparing different chloride solutions at the same concentration, the destruction effects of chloride complexes and catnions on the hydrogen bond of water increases in the sequences: CaCl2 >NaCl>KC. The modeling result shows that the determination coefficients (R2) = 99.97%, the root mean square error of cross validation (RM- SECV) = 4.51, and the residual prediction deviation (RPD) = 62.7, it meets the daily requirements of biochemical detection accuracy.

A novel GLM-based method for the Automatic IDentification of functional Events (AIDE) in fNIRS data recorded in naturalistic environments.

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Pinti, Paola; Merla, Arcangelo; Aichelburg, Clarisse; Lind, Frida; Power, Sarah; Swingler, Elizabeth; Hamilton, Antonia; Gilbert, Sam; Burgess, Paul W; Tachtsidis, Ilias

2017-07-15

Recent technological advances have allowed the development of portable functional Near-Infrared Spectroscopy (fNIRS) devices that can be used to perform neuroimaging in the real-world. However, as real-world experiments are designed to mimic everyday life situations, the identification of event onsets can be extremely challenging and time-consuming. Here, we present a novel analysis method based on the general linear model (GLM) least square fit analysis for the Automatic IDentification of functional Events (or AIDE) directly from real-world fNIRS neuroimaging data. In order to investigate the accuracy and feasibility of this method, as a proof-of-principle we applied the algorithm to (i) synthetic fNIRS data simulating both block-, event-related and mixed-design experiments and (ii) experimental fNIRS data recorded during a conventional lab-based task (involving maths). AIDE was able to recover functional events from simulated fNIRS data with an accuracy of 89%, 97% and 91% for the simulated block-, event-related and mixed-design experiments respectively. For the lab-based experiment, AIDE recovered more than the 66.7% of the functional events from the fNIRS experimental measured data. To illustrate the strength of this method, we then applied AIDE to fNIRS data recorded by a wearable system on one participant during a complex real-world prospective memory experiment conducted outside the lab. As part of the experiment, there were four and six events (actions where participants had to interact with a target) for the two different conditions respectively (condition 1: social-interact with a person; condition 2: non-social-interact with an object). AIDE managed to recover 3/4 events and 3/6 events for conditions 1 and 2 respectively. The identified functional events were then corresponded to behavioural data from the video recordings of the movements and actions of the participant. Our results suggest that "brain-first" rather than "behaviour-first" analysis is

Analysis of total oil and fatty acids composition by near infrared reflectance spectroscopy in edible nuts

Science.gov (United States)

Kandala, Chari V.; Sundaram, Jaya

2014-10-01

Near Infrared (NIR) Reflectance spectroscopy has established itself as an important tool in quantifying water and oil present in various food materials. It is rapid and nondestructive, easier to use, and does not require processing the samples with corrosive chemicals that would render them non-edible. Earlier, the samples had to be ground into powder form before making any measurements. With the development of new soft ware packages, NIR techniques could now be used in the analysis of intact grain and nuts. While most of the commercial instruments presently available work well with small grain size materials such as wheat and corn, the method present here is suitable for large kernel size products such as shelled or in-shell peanuts. Absorbance spectra were collected from 400 nm to 2500 nm using a NIR instrument. Average values of total oil contents (TOC) of peanut samples were determined by standard extraction methods, and fatty acids were determined using gas chromatography. Partial least square (PLS) analysis was performed on the calibration set of absorption spectra, and models were developed for prediction of total oil and fatty acids. The best model was selected based on the coefficient of determination (R2), Standard error of prediction (SEP) and residual percent deviation (RPD) values. Peanut samples analyzed showed RPD values greater than 5.0 for both absorbance and reflectance models and thus could be used for quality control and analysis. Ability to rapidly and nondestructively measure the TOC, and analyze the fatty acid composition, will be immensely useful in peanut varietal improvement as well as in the grading process of grain and nuts.

[Discrimination of Rice Syrup Adulterant of Acacia Honey Based Using Near-Infrared Spectroscopy].

Science.gov (United States)

Zhang, Yan-nan; Chen, Lan-zhen; Xue, Xiao-feng; Wu, Li-ming; Li, Yi; Yang, Juan

2015-09-01

At present, the rice syrup as a low price of the sweeteners was often adulterated into acacia honey and the adulterated honeys were sold in honey markets, while there is no suitable and fast method to identify honey adulterated with rice syrup. In this study, Near infrared spectroscopy (NIR) combined with chemometric methods were used to discriminate authenticity of honey. 20 unprocessed acacia honey samples from the different honey producing areas, mixed? with different proportion of rice syrup, were prepared of seven different concentration gradient? including 121 samples. The near infrared spectrum (NIR) instrument and spectrum processing software have been applied in the? spectrum? scanning and data conversion on adulterant samples, respectively. Then it was analyzed by Principal component analysis (PCA) and canonical discriminant analysis methods in order to discriminating adulterated honey. The results showed that after principal components analysis, the first two principal components accounted for 97.23% of total variation, but the regionalism of the score plot of the first two PCs was not obvious, so the canonical discriminant analysis was used to make the further discrimination, all samples had been discriminated correctly, the first two discriminant functions accounted for 91.6% among the six canonical discriminant functions, Then the different concentration of adulterant samples can be discriminated correctly, it illustrate that canonical discriminant analysis method combined with NIR spectroscopy is not only feasible but also practical for rapid and effective discriminate of the rice syrup adulterant of acacia honey.

Improving NIR snow pit stratigraphy observations by introducing a controlled NIR light source

Science.gov (United States)

Dean, J.; Marshall, H.; Rutter, N.; Karlson, A.

2013-12-01

Near-infrared (NIR) photography in a prepared snow pit measures mm-/grain-scale variations in snow structure, as reflectivity is strongly dependent on microstructure and grain size at the NIR wavelengths. We explore using a controlled NIR light source to maximize signal to noise ratio and provide uniform incident, diffuse light on the snow pit wall. NIR light fired from the flash is diffused across and reflected by an umbrella onto the snow pit; the lens filter transmits NIR light onto the spectrum-modified sensor of the DSLR camera. Lenses are designed to refract visible light properly, not NIR light, so there must be a correction applied for the subsequent NIR bright spot. To avoid interpolation and debayering algorithms automatically performed by programs like Adobe's Photoshop on the images, the raw data are analyzed directly in MATLAB. NIR image data show a doubling of the amount of light collected in the same time for flash over ambient lighting. Transitions across layer boundaries in the flash-lit image are detailed by higher camera intensity values than ambient-lit images. Curves plotted using median intensity at each depth, normalized to the average profile intensity, show a separation between flash- and ambient-lit images in the upper 10-15 cm; the ambient-lit image curve asymptotically approaches the level of the flash-lit image curve below 15cm. We hypothesize that the difference is caused by additional ambient light penetrating the upper 10-15 cm of the snowpack from above and transmitting through the wall of the snow pit. This indicates that combining NIR ambient and flash photography could be a powerful technique for studying penetration depth of radiation as a function of microstructure and grain size. The NIR flash images do not increase the relative contrast at layer boundaries; however, the flash more than doubles the amount of recorded light and controls layer noise as well as layer boundary transition noise.

Computational Pipeline for NIRS-EEG Joint Imaging of tDCS-Evoked Cerebral Responses-An Application in Ischemic Stroke.

Science.gov (United States)

Guhathakurta, Debarpan; Dutta, Anirban

2016-01-01

Transcranial direct current stimulation (tDCS) modulates cortical neural activity and hemodynamics. Electrophysiological methods (electroencephalography-EEG) measure neural activity while optical methods (near-infrared spectroscopy-NIRS) measure hemodynamics coupled through neurovascular coupling (NVC). Assessment of NVC requires development of NIRS-EEG joint-imaging sensor montages that are sensitive to the tDCS affected brain areas. In this methods paper, we present a software pipeline incorporating freely available software tools that can be used to target vascular territories with tDCS and develop a NIRS-EEG probe for joint imaging of tDCS-evoked responses. We apply this software pipeline to target primarily the outer convexity of the brain territory (superficial divisions) of the middle cerebral artery (MCA). We then present a computational method based on Empirical Mode Decomposition of NIRS and EEG time series into a set of intrinsic mode functions (IMFs), and then perform a cross-correlation analysis on those IMFs from NIRS and EEG signals to model NVC at the lesional and contralesional hemispheres of an ischemic stroke patient. For the contralesional hemisphere, a strong positive correlation between IMFs of regional cerebral hemoglobin oxygen saturation and the log-transformed mean-power time-series of IMFs for EEG with a lag of about -15 s was found after a cumulative 550 s stimulation of anodal tDCS. It is postulated that system identification, for example using a continuous-time autoregressive model, of this coupling relation under tDCS perturbation may provide spatiotemporal discriminatory features for the identification of ischemia. Furthermore, portable NIRS-EEG joint imaging can be incorporated into brain computer interfaces to monitor tDCS-facilitated neurointervention as well as cortical reorganization.

Characterizing process effects on pharmaceutical solid forms using near-infrared spectroscopy and infrared imaging.

Science.gov (United States)

Roggo, Y; Jent, N; Edmond, A; Chalus, P; Ulmschneider, M

2005-09-01

Near-infrared spectroscopy (NIRS) has become a widely used analytical technique in the pharmaceutical industry, serving for example to determine the active substance or water content of tablets. Its great advantage lies in the minimal sample preparation required and speed of measurement. In a study designed to detect the effects of process on tablet dissolution, we describe the application of NIRS to the detection and identification of changes in uncoated and coated tablets in response to pilot-scale changes in process parameters during melt granulation, compression, and coating. Beginning with a qualitative comparison between pharmaceutical batches, we show that NIRS and principal component analysis can separate batches produced with different melt granulation parameters and differentiate between cores compressed with different compaction forces. Complementary infrared imaging can also explain the difference in dissolution properties between samples produced with different melt granulation parameters. NIRS is sensitive to changes in coating formulation, the quality of a coating excipient (hydroxypropyl methylcellulose), and coating time. In a concluding quantitative analysis, we demonstrate the feasibility of NIRS in a manufacturing context for predicting coating time and detecting production cores failing to meet dissolution test specifications.

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.

Validation of brain-derived signals in near-infrared spectroscopy through multivoxel analysis of concurrent functional magnetic resonance imaging.

Science.gov (United States)

Moriguchi, Yoshiya; Noda, Takamasa; Nakayashiki, Kosei; Takata, Yohei; Setoyama, Shiori; Kawasaki, Shingo; Kunisato, Yoshihiko; Mishima, Kazuo; Nakagome, Kazuyuki; Hanakawa, Takashi

2017-10-01

Near-infrared spectroscopy (NIRS) is a convenient and safe brain-mapping tool. However, its inevitable confounding with hemodynamic responses outside the brain, especially in the frontotemporal head, has questioned its validity. Some researchers attempted to validate NIRS signals through concurrent measurements with functional magnetic resonance imaging (fMRI), but, counterintuitively, NIRS signals rarely correlate with local fMRI signals in NIRS channels, although both mapping techniques should measure the same hemoglobin concentration. Here, we tested a novel hypothesis that different voxels within the scalp and the brain tissues might have substantially different hemoglobin absorption rates of near-infrared light, which might differentially contribute to NIRS signals across channels. Therefore, we newly applied a multivariate approach, a partial least squares regression, to explain NIRS signals with multivoxel information from fMRI within the brain and soft tissues in the head. We concurrently obtained fMRI and NIRS signals in 9 healthy human subjects engaging in an n-back task. The multivariate fMRI model was quite successfully able to predict the NIRS signals by cross-validation (interclass correlation coefficient = ∼0.85). This result confirmed that fMRI and NIRS surely measure the same hemoglobin concentration. Additional application of Monte-Carlo permutation tests confirmed that the model surely reflects temporal and spatial hemodynamic information, not random noise. After this thorough validation, we calculated the ratios of the contributions of the brain and soft-tissue hemodynamics to the NIRS signals, and found that the contribution ratios were quite different across different NIRS channels in reality, presumably because of the structural complexity of the frontotemporal regions. Hum Brain Mapp 38:5274-5291, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Assessment of hyaline cartilage matrix composition using near infrared spectroscopy.

Science.gov (United States)

Palukuru, Uday P; McGoverin, Cushla M; Pleshko, Nancy

2014-09-01

Changes in the composition of the extracellular matrix (ECM) are characteristic of injury or disease in cartilage tissue. Various imaging modalities and biochemical techniques have been used to assess the changes in cartilage tissue but lack adequate sensitivity, or in the case of biochemical techniques, result in destruction of the sample. Fourier transform near infrared (FT-NIR) spectroscopy has shown promise for the study of cartilage composition. In the current study NIR spectroscopy was used to identify the contributions of individual components of cartilage in the NIR spectra by assessment of the major cartilage components, collagen and chondroitin sulfate, in pure component mixtures. The NIR spectra were obtained using homogenous pellets made by dilution with potassium bromide. A partial least squares (PLS) model was calculated to predict composition in bovine cartilage samples. Characteristic absorbance peaks between 4000 and 5000 cm(-1) could be attributed to components of cartilage, i.e. collagen and chondroitin sulfate. Prediction of the amount of collagen and chondroitin sulfate in tissues was possible within 8% (w/dw) of values obtained by gold standard biochemical assessment. These results support the use of NIR spectroscopy for in vitro and in vivo applications to assess matrix composition of cartilage tissues, especially when tissue destruction should be avoided. Copyright © 2014. Published by Elsevier B.V.

Association of Concurrent fNIRS and EEG Signatures in Response to Auditory and Visual Stimuli.

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Chen, Ling-Chia; Sandmann, Pascale; Thorne, Jeremy D; Herrmann, Christoph S; Debener, Stefan

2015-09-01

Functional near-infrared spectroscopy (fNIRS) has been proven reliable for investigation of low-level visual processing in both infants and adults. Similar investigation of fundamental auditory processes with fNIRS, however, remains only partially complete. Here we employed a systematic three-level validation approach to investigate whether fNIRS could capture fundamental aspects of bottom-up acoustic processing. We performed a simultaneous fNIRS-EEG experiment with visual and auditory stimulation in 24 participants, which allowed the relationship between changes in neural activity and hemoglobin concentrations to be studied. In the first level, the fNIRS results showed a clear distinction between visual and auditory sensory modalities. Specifically, the results demonstrated area specificity, that is, maximal fNIRS responses in visual and auditory areas for the visual and auditory stimuli respectively, and stimulus selectivity, whereby the visual and auditory areas responded mainly toward their respective stimuli. In the second level, a stimulus-dependent modulation of the fNIRS signal was observed in the visual area, as well as a loudness modulation in the auditory area. Finally in the last level, we observed significant correlations between simultaneously-recorded visual evoked potentials and deoxygenated hemoglobin (DeoxyHb) concentration, and between late auditory evoked potentials and oxygenated hemoglobin (OxyHb) concentration. In sum, these results suggest good sensitivity of fNIRS to low-level sensory processing in both the visual and the auditory domain, and provide further evidence of the neurovascular coupling between hemoglobin concentration changes and non-invasive brain electrical activity.

Diffuse Reflectance Spectroscopy of Hidden Objects, Part I: Interpretation of the Reflection-Absorption-Scattering Fractions in Near-Infrared (NIR) Spectra of Polyethylene Films.

Science.gov (United States)

Pomerantsev, Alexey L; Rodionova, Oxana Ye; Skvortsov, Alexej N

2017-08-01

Investigation of a sample covered by an interfering layer is required in many fields, e.g., for process control, biochemical analysis, and many other applications. This study is based on the analysis of spectra collected by near-infrared (NIR) diffuse reflectance spectroscopy. Each spectrum is a composition of a useful, target spectrum and a spectrum of an interfering layer. To recover the target spectrum, we suggest using a new phenomenological approach, which employs the multivariate curve resolution (MCR) method. In general terms, the problem is very complex. We start with a specific problem of analyzing a system, which consists of several layers of polyethylene (PE) film and underlayer samples with known spectral properties. To separate information originating from PE layers and the target, we modify the system versus both the number of the PE layers as well as the reflectance properties of the target sample. We consider that the interfering spectrum of the layer can be modeled using three components, which can be tentatively called transmission, absorption, and scattering contributions. The novelty of our approach is that we do not remove the reflectance and scattering effects from the spectra, but study them in detail aiming to use this information to recover the target spectrum.

Motion tracking and electromyography assist the removal of mirror hand contributions to fNIRS images acquired during a finger tapping task performed by children with cerebral palsy

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Hervey, Nathan; Khan, Bilal; Shagman, Laura; Tian, Fenghua; Delgado, Mauricio R.; Tulchin-Francis, Kirsten; Shierk, Angela; Smith, Linsley; Reid, Dahlia; Clegg, Nancy J.; Liu, Hanli; MacFarlane, Duncan; Alexandrakis, George

2013-03-01

Functional neurological imaging has been shown to be valuable in evaluating brain plasticity in children with cerebral palsy (CP). In recent studies it has been demonstrated that functional near-infrared spectroscopy (fNIRS) is a viable and sensitive method for imaging motor cortex activities in children with CP. However, during unilateral finger tapping tasks children with CP often exhibit mirror motions (unintended motions in the non-tapping hand), and current fNIRS image formation techniques do not account for this. Therefore, the resulting fNIRS images contain activation from intended and unintended motions. In this study, cortical activity was mapped with fNIRS on four children with CP and five controls during a finger tapping task. Finger motion and arm muscle activation were concurrently measured using motion tracking cameras and electromyography (EMG). Subject-specific regressors were created from motion capture and EMG data and used in a general linear model (GLM) analysis in an attempt to create fNIRS images representative of different motions. The analysis provided an fNIRS image representing activation due to motion and muscle activity for each hand. This method could prove to be valuable in monitoring brain plasticity in children with CP by providing more consistent images between measurements. Additionally, muscle effort versus cortical effort was compared between control and CP subjects. More cortical effort was required to produce similar muscle effort in children with CP. It is possible this metric could be a valuable diagnostic tool in determining response to treatment.

Hybrid EEG-fNIRS-Based Eight-Command Decoding for BCI: Application to Quadcopter Control.

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Khan, Muhammad Jawad; Hong, Keum-Shik

2017-01-01

In this paper, a hybrid electroencephalography-functional near-infrared spectroscopy (EEG-fNIRS) scheme to decode eight active brain commands from the frontal brain region for brain-computer interface is presented. A total of eight commands are decoded by fNIRS, as positioned on the prefrontal cortex, and by EEG, around the frontal, parietal, and visual cortices. Mental arithmetic, mental counting, mental rotation, and word formation tasks are decoded with fNIRS, in which the selected features for classification and command generation are the peak, minimum, and mean ΔHbO values within a 2-s moving window. In the case of EEG, two eyeblinks, three eyeblinks, and eye movement in the up/down and left/right directions are used for four-command generation. The features in this case are the number of peaks and the mean of the EEG signal during 1 s window. We tested the generated commands on a quadcopter in an open space. An average accuracy of 75.6% was achieved with fNIRS for four-command decoding and 86% with EEG for another four-command decoding. The testing results show the possibility of controlling a quadcopter online and in real-time using eight commands from the prefrontal and frontal cortices via the proposed hybrid EEG-fNIRS interface.

The application of Near-Infrared Reflectance Spectroscopy (NIRS) to detect melamine adulteration of soya bean meal.

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Haughey, Simon A; Graham, Stewart F; Cancouët, Emmanuelle; Elliott, Christopher T

2013-02-15

Soya bean products are used widely in the animal feed industry as a protein based feed ingredient and have been found to be adulterated with melamine. This was highlighted in the Chinese scandal of 2008. Dehulled soya (GM and non-GM), soya hulls and toasted soya were contaminated with melamine and spectra were generated using Near Infrared Reflectance Spectroscopy (NIRS). By applying chemometrics to the spectral data, excellent calibration models and prediction statistics were obtained. The coefficients of determination (R(2)) were found to be 0.89-0.99 depending on the mathematical algorithm used, the data pre-processing applied and the sample type used. The corresponding values for the root mean square error of calibration and prediction were found to be 0.081-0.276% and 0.134-0.368%, respectively, again depending on the chemometric treatment applied to the data and sample type. In addition, adopting a qualitative approach with the spectral data and applying PCA, it was possible to discriminate between the four samples types and also, by generation of Cooman's plots, possible to distinguish between adulterated and non-adulterated samples. Copyright © 2012 Elsevier Ltd. All rights reserved.

Cerebral time domain-NIRS: reproducibility analysis, optical properties, hemoglobin species and tissue oxygen saturation in a cohort of adult subjects.

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Giacalone, Giacomo; Zanoletti, Marta; Contini, Davide; Re, Rebecca; Spinelli, Lorenzo; Roveri, Luisa; Torricelli, Alessandro

2017-11-01

The reproducibility of cerebral time-domain near-infrared spectroscopy (TD-NIRS) has not been investigated so far. Besides, reference intervals of cerebral optical properties, of absolute concentrations of deoxygenated-hemoglobin (HbR), oxygenated-hemoglobin (HbO), total hemoglobin (HbT) and tissue oxygen saturation (StO 2 ) and their variability have not been reported. We have addressed these issues on a sample of 88 adult healthy subjects. TD-NIRS measurements at 690, 785, 830 nm were fitted with the diffusion model for semi-infinite homogenous media. Reproducibility, performed on 3 measurements at 5 minutes intervals, ranges from 1.8 to 6.9% for each of the hemoglobin species. The mean ± SD global values of HbR, HbO, HbT, StO 2 are respectively 24 ± 7 μM, 33.3 ± 9.5 μM, 57.4 ± 15.8 μM, 58 ± 4.2%. StO 2 displays the narrowest range of variability across brain regions.

Human cortical neural correlates of visual fatigue during binocular depth perception: An fNIRS study.

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Tingting Cai

Full Text Available Functional near-infrared spectroscopy (fNIRS was adopted to investigate the cortical neural correlates of visual fatigue during binocular depth perception for different disparities (from 0.1° to 1.5°. By using a slow event-related paradigm, the oxyhaemoglobin (HbO responses to fused binocular stimuli presented by the random-dot stereogram (RDS were recorded over the whole visual dorsal area. To extract from an HbO curve the characteristics that are correlated with subjective experiences of stereopsis and visual fatigue, we proposed a novel method to fit the time-course HbO curve with various response functions which could reflect various processes of binocular depth perception. Our results indicate that the parietal-occipital cortices are spatially correlated with binocular depth perception and that the process of depth perception includes two steps, associated with generating and sustaining stereovision. Visual fatigue is caused mainly by generating stereovision, while the amplitude of the haemodynamic response corresponding to sustaining stereovision is correlated with stereopsis. Combining statistical parameter analysis and the fitted time-course analysis, fNIRS could be a promising method to study visual fatigue and possibly other multi-process neural bases.

Brain plasticity and rehabilitation by using Near-Infrared Spectroscopy

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Balconi Michela

2016-04-01

Full Text Available The present review elucidated the use of optical imaging technique (Near-Infrared Spectroscopy, NIRS to better explain the brain plasticity for learning mechanisms, rehabilitation and post-traumatic brain recovery. Some recent applications were discussed, with specific focus on the usability of integrated measures (such as electroencephalography, EEG-NIRS; Transcranial Magnet Stimulation, TMS-NIRS to study plasticity and its dynamic effects. NIRS-Neurofeedback and NIRS-BCI (Brain Computer Interface were also explored as possible tools to produce a specific long-lasting learning in relationship with a specific cognitive domain. Finally a proficient domain where NIRS was found to be useful to test neuroplasticity is the interpersonal brain-to-brain coupling, termed “hyperscanning”, a new emerging paradigm in neuroscience which measures brain activity from two or more people simultaneously.

Separation of viable and non-viable tomato (Solanum lycopersicum L.) seeds using single seed near-infrared spectroscopy

DEFF Research Database (Denmark)

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

2017-01-01

Single seed near-infrared (NIR) spectroscopy is a non-destructive technology commonly used for predicting lipids, proteins, carbohydrates and water content of agricultural products. The aim of the current study is to investigate the prospects of NIR spectroscopy in classifying viable and non...... identified as important for classification of viable and non-viable tomato seeds by iPLS-DA. The sensitivity i.e. ability to correctly identify the positive samples and specificity i.e. ability to reject the negative samples of the (iPLS-DA) model on identified spectral regions for prediction of viable......-viable tomato seeds of two cultivars using chemometrics. The data exploration were performed by principal component analysis (PCA). Subsequently, viable and non-viable seeds were classified by partial least squares-discriminant analysis (PLS-DA) and interval PLS-DA (iPLS-DA). The indication of clustering...

TARGETED PRINCIPLE COMPONENT ANALYSIS: A NEW MOTION ARTIFACT CORRECTION APPROACH FOR NEAR-INFRARED SPECTROSCOPY

Science.gov (United States)

YÜCEL, MERYEM A.; SELB, JULIETTE; COOPER, ROBERT J.; BOAS, DAVID A.

2014-01-01

As near-infrared spectroscopy (NIRS) broadens its application area to different age and disease groups, motion artifacts in the NIRS signal due to subject movement is becoming an important challenge. Motion artifacts generally produce signal fluctuations that are larger than physiological NIRS signals, thus it is crucial to correct for them before obtaining an estimate of stimulus evoked hemodynamic responses. There are various methods for correction such as principle component analysis (PCA), wavelet-based filtering and spline interpolation. Here, we introduce a new approach to motion artifact correction, targeted principle component analysis (tPCA), which incorporates a PCA filter only on the segments of data identified as motion artifacts. It is expected that this will overcome the issues of filtering desired signals that plagues standard PCA filtering of entire data sets. We compared the new approach with the most effective motion artifact correction algorithms on a set of data acquired simultaneously with a collodion-fixed probe (low motion artifact content) and a standard Velcro probe (high motion artifact content). Our results show that tPCA gives statistically better results in recovering hemodynamic response function (HRF) as compared to wavelet-based filtering and spline interpolation for the Velcro probe. It results in a significant reduction in mean-squared error (MSE) and significant enhancement in Pearson’s correlation coefficient to the true HRF. The collodion-fixed fiber probe with no motion correction performed better than the Velcro probe corrected for motion artifacts in terms of MSE and Pearson’s correlation coefficient. Thus, if the experimental study permits, the use of a collodion-fixed fiber probe may be desirable. If the use of a collodion-fixed probe is not feasible, then we suggest the use of tPCA in the processing of motion artifact contaminated data. PMID:25360181

TARGETED PRINCIPLE COMPONENT ANALYSIS: A NEW MOTION ARTIFACT CORRECTION APPROACH FOR NEAR-INFRARED SPECTROSCOPY.

Science.gov (United States)

Yücel, Meryem A; Selb, Juliette; Cooper, Robert J; Boas, David A

2014-03-01

As near-infrared spectroscopy (NIRS) broadens its application area to different age and disease groups, motion artifacts in the NIRS signal due to subject movement is becoming an important challenge. Motion artifacts generally produce signal fluctuations that are larger than physiological NIRS signals, thus it is crucial to correct for them before obtaining an estimate of stimulus evoked hemodynamic responses. There are various methods for correction such as principle component analysis (PCA), wavelet-based filtering and spline interpolation. Here, we introduce a new approach to motion artifact correction, targeted principle component analysis (tPCA), which incorporates a PCA filter only on the segments of data identified as motion artifacts. It is expected that this will overcome the issues of filtering desired signals that plagues standard PCA filtering of entire data sets. We compared the new approach with the most effective motion artifact correction algorithms on a set of data acquired simultaneously with a collodion-fixed probe (low motion artifact content) and a standard Velcro probe (high motion artifact content). Our results show that tPCA gives statistically better results in recovering hemodynamic response function (HRF) as compared to wavelet-based filtering and spline interpolation for the Velcro probe. It results in a significant reduction in mean-squared error (MSE) and significant enhancement in Pearson's correlation coefficient to the true HRF. The collodion-fixed fiber probe with no motion correction performed better than the Velcro probe corrected for motion artifacts in terms of MSE and Pearson's correlation coefficient. Thus, if the experimental study permits, the use of a collodion-fixed fiber probe may be desirable. If the use of a collodion-fixed probe is not feasible, then we suggest the use of tPCA in the processing of motion artifact contaminated data.

Identifying ADHD children using hemodynamic responses during a working memory task measured by functional near-infrared spectroscopy

Science.gov (United States)

Gu, Yue; Miao, Shuo; Han, Junxia; Liang, Zhenhu; Ouyang, Gaoxiang; Yang, Jian; Li, Xiaoli

2018-06-01

Objective. Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting children and adults. Previous studies found that functional near-infrared spectroscopy (fNIRS) can reveal significant group differences in several brain regions between ADHD children and healthy controls during working memory tasks. This study aimed to use fNIRS activation patterns to identify ADHD children from healthy controls. Approach. FNIRS signals from 25 ADHD children and 25 healthy controls performing the n-back task were recorded; then, multivariate pattern analysis was used to discriminate ADHD individuals from healthy controls, and classification performance was evaluated for significance by the permutation test. Main results. The results showed that 86.0% (pADHD children from healthy controls based on fNIRS signals, which argues for the potential utility of fNIRS in future assessments.

fNIRS-based brain-computer interfaces: a review

Directory of Open Access Journals (Sweden)

Noman eNaseer

2015-01-01

Full Text Available A brain-computer interface (BCI is a communication system that allows the use of brain activity to control computers or other external devices. It can, by bypassing the peripheral nervous system, provide a means of communication for people suffering from severe motor disabilities or in a persistent vegetative state. In this paper, brain-signal generation tasks, noise removal methods, feature extraction/selection schemes, and classification techniques for fNIRS-based BCI are reviewed. The most common brain areas for fNIRS BCI are the primary motor cortex and the prefrontal cortex. In relation to the motor cortex, motor imagery tasks were preferred to motor execution tasks since possible proprioceptive feedback could be avoided. In relation to the prefrontal cortex, fNIRS showed a significant advantage due to no hair in detecting the cognitive tasks like mental arithmetic, music imagery, emotion induction, etc. In removing physiological noise in fNIRS data, band-pass filtering was mostly used. However, more advanced techniques like adaptive filtering, independent component analysis, multi optodes arrangement, etc. are being pursued to overcome the problem that a band-pass filter cannot be used when both brain and physiological signals occur within a close band. In extracting features related to the desired brain signal, the mean, variance, peak value, slope, skewness, and kurtosis of the noised-removed hemodynamic response were used. For classification, the linear discriminant analysis method provided simple but good performance among others: support vector machine, hidden Markov model, artificial neural network, etc. fNIRS will be more widely used to monitor the occurrence of neuro-plasticity after neuro-rehabilitation and neuro-stimulation. Technical breakthroughs in the future are expected via bundled-type probes, hybrid EEG-fNIRS BCI, and through the detection of initial dips.

Evaluation of portable near-infrared spectroscopy for organic milk authentication.

Science.gov (United States)

Liu, Ningjing; Parra, Hector Aya; Pustjens, Annemieke; Hettinga, Kasper; Mongondry, Philippe; van Ruth, Saskia M

2018-07-01

Organic products are vulnerable to fraud due to their premium price. Analytical methodology helps to manage the risk of fraud and due to the miniaturization of equipment, tests may nowadays even be rapidly applied on-site. The current study aimed to evaluate portable near infrared spectroscopy (NIRS) in combination with chemometrics to distinguish organic milk from other types of milk, and compare its performance with benchtop NIRS and fatty acid profiling by gas chromatography. The sample set included 37 organic retail milks and 50 non-organic retail milks (of which 36 conventional and 14 green 'pasture' milks). Partial least squares discriminant analysis was performed to build classification models and kernel density estimation (KDE) functions were calculated to generate non-parametric distributions for samples' class probabilities. These distributions showed that portable NIRS was successful to distinguish organic milks from conventional milks, and so were benchtop NIRS and fatty acid profiling procedures. However, it was less successful when 'pasture' milks were considered too, since their patterns occasionally resembled those of the organic milk group. Fatty acid profiling was capable of distinguishing organic milks from both non-organic milks though, including the 'pasture' milks. This comparative study revealed that the classification performance of the portable NIRS for this application was similar to that of the benchtop NIRS. Copyright © 2018 Elsevier B.V. All rights reserved.

On children's dyslexia with NIRS

Science.gov (United States)

Gan, Zhuo; Li, Chengjun; Gong, Hui; Luo, Qingming; Yao, Bin; Song, Ranran; Wu, Hanrong

2003-12-01

Developmental dyslexia is a kind of prevalent psychologic disease. Some functional imaging technologies, such as FMRI and PET, have been used to study the brain activities of dyslexics. NIRS is a kind of novel technology which is more and more widely being used for study of the cognitive psychology. However, there aren"t reports about the dyslexic research using NIRS to be found until now. This paper introduces a NIRS system of four measuring channels. Brain activities of dyslexic subjects and normal subjects during reading task were studied with the NIRS system. Two groups of subjects, the group of dyslexia and the group of normal, were appointed to perform two reading tasks. At the same time, their cortical activities were measured with the NIRS system. This experimental result indicates that the brain activities of the dyslexic group were significantly higher than the control group in BA 48 and that NIRS can be used for the study of human brain activity.

Study on feasibility of determination of glucosamine content of fermentation process using a micro NIR spectrometer.

Science.gov (United States)

Sun, Zhongyu; Li, Can; Li, Lian; Nie, Lei; Dong, Qin; Li, Danyang; Gao, Lingling; Zang, Hengchang

2018-08-05

N-acetyl-d-glucosamine (GlcNAc) is a microbial fermentation product, and NIR spectroscopy is an effective process analytical technology (PAT) tool in detecting the key quality attribute: the GlcNAc content. Meanwhile, the design of NIR spectrometers is under the trend of miniaturization, portability and low-cost nowadays. The aim of this study was to explore a portable micro NIR spectrometer with the fermentation process. First, FT-NIR spectrometer and Micro-NIR 1700 spectrometer were compared with simulated fermentation process solutions. The R c 2 , R p 2 , RMSECV and RMSEP of the optimal FT-NIR and Micro-NIR 1700 models were 0.999, 0.999, 3.226 g/L, 1.388 g/L and 0.999, 0.999, 1.821 g/L, 0.967 g/L. Passing-Bablok regression method and paired t-test results showed there were no significant differences between the two instruments. Then the Micro-NIR 1700 was selected for the practical fermentation process, 135 samples from 10 batches were collected. Spectral pretreatment methods and variables selection methods (BiPLS, FiPLS, MWPLS and CARS-PLS) for PLS modeling were discussed. The R c 2 , R p 2 , RMSECV and RMSEP of the optimal GlcNAc content PLS model of the practical fermentation process were 0.994, 0.995, 2.792 g/L and 1.946 g/L. The results have a positive reference for application of the Micro-NIR spectrometer. To some extent, it could provide theoretical supports in guiding the microbial fermentation or the further assessment of bioprocess. Copyright © 2018. Published by Elsevier B.V.

Analysis of ewe’s milk by FT Near Infrared spectroscopy: measurement of samples on Petri dishes in reflectance mode

Directory of Open Access Journals (Sweden)

Květoslava Šustová

2006-01-01

Full Text Available Our work deals with a possibility of determination of basic composition (dry matter, fat, protein, casein, lactose and urea nitrogen of ewe’s milk and colostrum by FT NIR spectroscopy. Samples of milk were warmed to 40 °C, agitated, cooled to 20 °C, transferred into Petri dishes and analysed by reference methods and by FT NIR in reflectance mode. The measured area was spaced by a metallic mirror. Statistically significant differences between the reference values and the calculated values of NIR were not found (p=0.05. Results of calibration for ewe’s milk determined the highest correlation coefficients: dry matter 0.983, fat 0.989, true protein 0.997, casein 0.977, lactose 0.980 and urea nitrogen 0.973. The study showed that NIRS method, when samples of milk are measured on Petri dishes, is a useful technique for the prediction of dry matter, fat, protein and casein in ewe’s milk.

Determination of the Mechanical Properties of Rubber by FT-NIR

OpenAIRE

Pornprasit, Rattapol; Pornprasit, Philaiwan; Boonma, Pruet; Natwichai, Juggapong

2016-01-01

Mechanical tests, for example, tensile and hardness tests, are usually used to evaluate the properties of rubber materials. In this work, mechanical properties of selected rubber materials, that is, natural rubber (NR), styrene butadiene rubber (SBR), nitrile butadiene rubber (NBR), and ethylene propylene diene monomer (EPDM), were evaluated using a near infrared (NIR) spectroscopy technique. Here, NR/NBR and NR/EPDM blends were first prepared. All of the samples were then scanned using a FT-...

Potential prospects in archaeological research by using optical spectroscopy through a black glass ocular

Science.gov (United States)

Cosyns, P.; Meulebroeck, W.; Thienpont, H.; Nys, K.

The aim of this paper is to draw attention to the potential usefulness of optical spectroscopy within the archaeological discourse. We therefore use the standardized color coordinates and the transmittance spectra in the region between 350- 1650 nm of nine fragmented Roman black glass artifacts from archaeological contexts in Avenches (Switzerland) and an intact piece from Tongeren (Belgium). Firstly, we demonstrate how the use of UV-Vis-NIR spectroscopy can help the archaeologist in understanding the various excavated features containing glass artifacts. The analysis of the optical spectra of Roman black glass artifacts demonstrates in the first place that an object has a very homogenous composition. The clustering of the different fragments with characteristic spectra permits to connect the pieces from various areas of an excavation to one single object or to several objects from the same batch. These results provide the archaeologist the possibility to merge recognized layers or to connect different features in the surrounding area. Secondly, we demonstrate how the use of UV-Vis-NIR spectroscopy can help improve the analysis process. This inexpensive method can facilitate a more convenient and purposive sampling by means of a preliminary inquiry, selecting the most interesting pieces out of a large group of artifacts suitable for chemical analysis.

Data Mining and NIR Spectroscopy in Viticulture: Applications for Plant Phenotyping under Field Conditions.

Science.gov (United States)

Gutiérrez, Salvador; Tardaguila, Javier; Fernández-Novales, Juan; Diago, Maria P

2016-02-16

Plant phenotyping is a very important topic in agriculture. In this context, data mining strategies may be applied to agricultural data retrieved with new non-invasive devices, with the aim of yielding useful, reliable and objective information. This work presents some applications of machine learning algorithms along with in-field acquired NIR spectral data for plant phenotyping in viticulture, specifically for grapevine variety discrimination and assessment of plant water status. Support vector machine (SVM), rotation forests and M5 trees models were built using NIR spectra acquired in the field directly on the adaxial side of grapevine leaves, with a non-invasive portable spectrophotometer working in the spectral range between 1600 and 2400 nm. The ν-SVM algorithm was used for the training of a model for varietal classification. The classifiers' performance for the 10 varieties reached, for cross- and external validations, the 88.7% and 92.5% marks, respectively. For water stress assessment, the models developed using the absorbance spectra of six varieties yielded the same determination coefficient for both cross- and external validations (R² = 0.84; RMSEs of 0.164 and 0.165 MPa, respectively). Furthermore, a variety-specific model trained only with samples of Tempranillo from two different vintages yielded R² = 0.76 and RMSE of 0.16 MPa for cross-validation and R² = 0.79, RMSE of 0.17 MPa for external validation. These results show the power of the combined use of data mining and non-invasive NIR sensing for in-field grapevine phenotyping and their usefulness for the wine industry and precision viticulture implementations.

On-line near-infrared spectroscopy optimizing and monitoring biotransformation process of γ-aminobutyric acid

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Guoyu Ding

2016-06-01

Full Text Available Near-infrared spectroscopy (NIRS with its fast and nondestructive advantages can be qualified for the real-time quantitative analysis. This paper demonstrates that NIRS combined with partial least squares (PLS regression can be used as a rapid analytical method to simultaneously quantify l-glutamic acid (l-Glu and γ-aminobutyric acid (GABA in a biotransformation process and to guide the optimization of production conditions when the merits of NIRS are combined with response surface methodology. The high performance liquid chromatography (HPLC reference analysis was performed by the o-phthaldialdehyde pre-column derivatization. NIRS measurements of two batches of 141 samples were firstly analyzed by PLS with several spectral pre-processing methods. Compared with those of the HPLC reference analysis, the resulting determination coefficients (R2, root mean square error of prediction (RMSEP and residual predictive deviation (RPD of the external validation for the l-Glu concentration were 99.5%, 1.62 g/L, and 11.3, respectively. For the GABA concentration, R2, RMSEP, and RPD were 99.8%, 4.00 g/L, and 16.4, respectively. This NIRS model was then used to optimize the biotransformation process through a Box-Behnken experimental design. Under the optimal conditions without pH adjustment, 200 g/L l-Glu could be catalyzed by 7148 U/L glutamate decarboxylase (GAD to GABA, reaching 99% conversion at the fifth hour. NIRS analysis provided timely information on the conversion from l-Glu to GABA. The results suggest that the NIRS model can not only be used for the routine profiling of enzymatic conversion, providing a simple and effective method of monitoring the biotransformation process of GABA, but also be considered to be an optimal tool to guide the optimization of production conditions.

Measuring cortical motor hemodynamics during assisted stepping - An fNIRS feasibility study of using a walker.

Science.gov (United States)

de Lima-Pardini, Andrea Cristina; Zimeo Morais, Guilherme A; Balardin, Joana Bisol; Coelho, Daniel Boari; Azzi, Nametala Maia; Teixeira, Luis Augusto; Sato, João Ricardo

2017-07-01

Walkers are commonly prescribed worldwide to individuals unable to walk independently. Walker usage leads to improved postural control and voluntary movement during step. In the present study, we aimed to provide a concept-proof on the feasibility of an event-related protocol integrating the analyses of biomechanical variables of step initiation and functional near-infrared spectroscopy (fNIRS) to measure activation of the supplementary motor area (SMA) while using a walker. Healthy young participants were tested while stepping with versus without the use of the walker. Behavioral analysis showed that anticipatory postural adjustments (APA) decreased when supporting the body weight on the walker. Delta (without-with) of activation magnitude of the muscle tibialis anterior was positively correlated to the delta of deoxyhemoglobin concentration changes in the SMA. The novelty of this study is the development of a protocol to assess brain function together with biomechanical analysis during the use of a walker. The method sheds light to the potential utility of combining fNIRS and biomechanical assessment during assistive step initiation, which can represent a new opportunity to study populations with mobility deficits. Copyright © 2017 Elsevier B.V. All rights reserved.

Fourier transform near-infrared spectroscopy application for sea salt quality evaluation.

Science.gov (United States)

Galvis-Sánchez, Andrea C; Lopes, João Almeida; Delgadillo, Ivonne; Rangel, António O S S

2011-10-26

Near-infrared (NIR) spectroscopy in diffuse reflectance mode was explored with the objective of discriminating sea salts according to their quality type (traditional salt vs "flower of salt") and geographical origin (Atlantic vs Mediterranean). Sea salts were also analyzed in terms of Ca(2+), Mg(2+), K(+), alkalinity, and sulfate concentrations to support spectroscopic results. High concentrations of Mg(2+) and K(+) characterized Atlantic samples, while a high Ca(2+) content was observed in traditional sea salts. A partial least-squares discriminant analysis model considering the 8500-7500 cm(-1) region permitted the discrimination of salts by quality types. The regions 4650-4350 and 5900-5500 cm(-1) allowed salts classification according to their geographical origin. It was possible to classify correctly 85.3 and 94.8% of the analyzed samples according to the salt type and to the geographical origin, respectively. These results demonstrated that NIR spectroscopy is a suitable and very efficient tool for sea salt quality evaluation.

A comparative study of the use of powder X-ray diffraction, Raman and near infrared spectroscopy for quantification of binary polymorphic mixtures of piracetam.

Science.gov (United States)

Croker, Denise M; Hennigan, Michelle C; Maher, Anthony; Hu, Yun; Ryder, Alan G; Hodnett, Benjamin K

2012-04-07

Diffraction and spectroscopic methods were evaluated for quantitative analysis of binary powder mixtures of FII(6.403) and FIII(6.525) piracetam. The two polymorphs of piracetam could be distinguished using powder X-ray diffraction (PXRD), Raman and near-infrared (NIR) spectroscopy. The results demonstrated that Raman and NIR spectroscopy are most suitable for quantitative analysis of this polymorphic mixture. When the spectra are treated with the combination of multiplicative scatter correction (MSC) and second derivative data pretreatments, the partial least squared (PLS) regression model gave a root mean square error of calibration (RMSEC) of 0.94 and 0.99%, respectively. FIII(6.525) demonstrated some preferred orientation in PXRD analysis, making PXRD the least preferred method of quantification. Copyright © 2012 Elsevier B.V. All rights reserved.

Gum Arabic authentication and mixture quantification by near infrared spectroscopy

DEFF Research Database (Denmark)

Dong, Yongjiang; Sørensen, Klavs Martin; He, Sailing

2017-01-01

A rapid and reliable method is developed for Gum Arabic authentication based on Near Infrared (NIR) spectroscopy and chemometric methods. On a large industrial collection of authentic gum Arabics, the two major Acacia gum species, Acacia senegal and Acacia seyal could be assigned perfectly...... by the NIR spectroscopic method. In addition, a partial least squares (PLS) regression model is calibrated to predict the blending percentage of the two pure gum types, producing an accuracy, root mean square error of cross validation (RMSECV) of 2.8%. Sampling of the Gum Arabic ‘tears’ is discussed......, and it was determined that subsamples from three ‘tears’ is required for a representative result. It is concluded that NIR spectroscopy is a very powerful and reliable method for authenticity testing of Gum Arabic species....

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.

Motor Cortex Activity During Functional Motor Skills: An fNIRS Study.

Science.gov (United States)

Nishiyori, Ryota; Bisconti, Silvia; Ulrich, Beverly

2016-01-01

Assessments of brain activity during motor task performance have been limited to fine motor movements due to technological constraints presented by traditional neuroimaging techniques, such as functional magnetic resonance imaging. Functional near-infrared spectroscopy (fNIRS) offers a promising method by which to overcome these constraints and investigate motor performance of functional motor tasks. The current study used fNIRS to quantify hemodynamic responses within the primary motor cortex in twelve healthy adults as they performed unimanual right, unimanual left, and bimanual reaching, and stepping in place. Results revealed that during both unimanual reaching tasks, the contralateral hemisphere showed significant activation in channels located approximately 3 cm medial to the C3 (for right-hand reach) and C4 (for left-hand reach) landmarks. Bimanual reaching and stepping showed activation in similar channels, which were located bilaterally across the primary motor cortex. The medial channels, surrounding Cz, showed significantly higher activations during stepping when compared to bimanual reaching. Our results extend the viability of fNIRS to study motor function and build a foundation for future investigation of motor development in infants during nascent functional behaviors and monitor how they may change with age or practice.

Hybrid EEG–fNIRS-Based Eight-Command Decoding for BCI: Application to Quadcopter Control

Science.gov (United States)

Khan, Muhammad Jawad; Hong, Keum-Shik

2017-01-01

In this paper, a hybrid electroencephalography–functional near-infrared spectroscopy (EEG–fNIRS) scheme to decode eight active brain commands from the frontal brain region for brain–computer interface is presented. A total of eight commands are decoded by fNIRS, as positioned on the prefrontal cortex, and by EEG, around the frontal, parietal, and visual cortices. Mental arithmetic, mental counting, mental rotation, and word formation tasks are decoded with fNIRS, in which the selected features for classification and command generation are the peak, minimum, and mean ΔHbO values within a 2-s moving window. In the case of EEG, two eyeblinks, three eyeblinks, and eye movement in the up/down and left/right directions are used for four-command generation. The features in this case are the number of peaks and the mean of the EEG signal during 1 s window. We tested the generated commands on a quadcopter in an open space. An average accuracy of 75.6% was achieved with fNIRS for four-command decoding and 86% with EEG for another four-command decoding. The testing results show the possibility of controlling a quadcopter online and in real-time using eight commands from the prefrontal and frontal cortices via the proposed hybrid EEG–fNIRS interface. PMID:28261084

Development of a near-infrared spectroscopy instrument for applications in urology.

Science.gov (United States)

Macnab, Andrew J; Stothers, Lynn

2008-10-01

Near infrared spectroscopy (NIRS) is an established technology using photons of light in the near infrared spectrum to monitor changes in tissue of naturally occurring chromophores, including oxygenated and deoxygenated hemoglobin. Technology and methodology have been validated for measurement of a range of physiologic parameters. NIRS has been applied successfully in urology research; however current instruments are designed principally for brain and muscle study. To describe development of a NIRS instrument specifically designed for monitoring changes in chromophore concentration in the bladder detrusor in real time, to facilitate research to establish the role of this non-invasive technology in the evaluation of patients with voiding dysfunction The portable continuous wave NIRS instrument has a 3 laser diode light source (785, 808 and 830 nanometers), fiber optic cables for light transmission, a self adhesive patient interface patch with an emitter and sensor, and software to detect the difference between the light transmitted and received by the instrument. Software incorporated auto-attenuates the optical signals and converts raw optical data into chromophore concentrations displayed graphically. The prototype was designed, tested, and iteratively developed to achieve optimal suprapubic transcutaneous monitoring of the detrusor in human subjects during bladder filling and emptying. Evaluation with simultaneous invasive urodynamic measurement in men and women indicates good specificity and sensitivity of NIRS chromophore concentration changes by receiver operator curve analysis, and correlation between NIRS data and urodynamic pressures. Urological monitoring with this NIRS instrument is feasible and generates data of potential diagnostic value.

Evanescent spectroscopy - theory and experiment

OpenAIRE

Karabchevsky, Alina

2014-01-01

Outline1 Introduction2 Literature Overview3 Photonic-Plasmonic WaveguideStructureModellingTheory4 ResultsOptical TransmittanceLoss of Fundamental Mode in a Gold RegionOptical Surface Intensity5 NIR Spectroscopy - Experiment6 Conclusions7 Acknowledgements

Cross-correlation of motor activity signals from dc-magnetoencephalography, near-infrared spectroscopy, and electromyography.

Science.gov (United States)

Sander, Tilmann H; Leistner, Stefanie; Wabnitz, Heidrun; Mackert, Bruno-Marcel; Macdonald, Rainer; Trahms, Lutz

2010-01-01

Neuronal and vascular responses due to finger movements were synchronously measured using dc-magnetoencephalography (dcMEG) and time-resolved near-infrared spectroscopy (trNIRS). The finger movements were monitored with electromyography (EMG). Cortical responses related to the finger movement sequence were extracted by independent component analysis from both the dcMEG and the trNIRS data. The temporal relations between EMG rate, dcMEG, and trNIRS responses were assessed pairwise using the cross-correlation function (CCF), which does not require epoch averaging. A positive lag on a scale of seconds was found for the maximum of the CCF between dcMEG and trNIRS. A zero lag is observed for the CCF between dcMEG and EMG. Additionally this CCF exhibits oscillations at the frequency of individual finger movements. These findings show that the dcMEG with a bandwidth up to 8 Hz records both slow and faster neuronal responses, whereas the vascular response is confirmed to change on a scale of seconds.

Identifying and quantifying main components of physiological noise in functional near infrared spectroscopy on prefrontal cortex

Directory of Open Access Journals (Sweden)

Evgeniya eKirilina

2013-12-01

Full Text Available Functional Near-Infrared Spectroscopy (fNIRS is a promising method to study functional organization of the prefrontal cortex. However, in order to realize the high potential of fNIRS, effective discrimination between physiological noise originating from forehead skin haemodynamic and cerebral signals is required. Main sources of physiological noise are global and local blood flow regulation processes on multiple time scales. The goal of the present study was to identify the main physiological noise contributions in fNIRS forehead signals and to develop a method for physiological de-noising of fNIRS data. To achieve this goal we combined concurrent time-domain fNIRS and peripheral physiology recordings with wavelet coherence analysis. Depth selectivity was achieved by analyzing moments of photon time-of-flight distributions provided by time-domain fNIRS. Simultaneously, mean arterial blood pressure (MAP, heart rate (HR, and skin blood flow (SBF on the forehead were recorded. Wavelet coherence analysis was employed to quantify the impact of physiological processes on fNIRS signals separately for different time scales. We identified three main processes contributing to physiological noise in fNIRS signals on the forehead. The first process with the period of about 3 s is induced by respiration. The second process is highly correlated with time lagged MAP and HR fluctuations with a period of about 10 s often referred as Mayer waves. The third process is local regulation of the facial skin blood flow time locked to the task-evoked fNIRS signals. All processes affect oxygenated haemoglobin concentration more strongly than that of deoxygenated haemoglobin. Based on these results we developed a set of physiological regressors, which were used for physiological de-noising of fNIRS signals. Our results demonstrate that proposed de-noising method can significantly improve the sensitivity of fNIRS to cerebral signals.

A Gaussian mixture model based adaptive classifier for fNIRS brain-computer interfaces and its testing via simulation

Science.gov (United States)

Li, Zheng; Jiang, Yi-han; Duan, Lian; Zhu, Chao-zhe

2017-08-01

Objective. Functional near infra-red spectroscopy (fNIRS) is a promising brain imaging technology for brain-computer interfaces (BCI). Future clinical uses of fNIRS will likely require operation over long time spans, during which neural activation patterns may change. However, current decoders for fNIRS signals are not designed to handle changing activation patterns. The objective of this study is to test via simulations a new adaptive decoder for fNIRS signals, the Gaussian mixture model adaptive classifier (GMMAC). Approach. GMMAC can simultaneously classify and track activation pattern changes without the need for ground-truth labels. This adaptive classifier uses computationally efficient variational Bayesian inference to label new data points and update mixture model parameters, using the previous model parameters as priors. We test GMMAC in simulations in which neural activation patterns change over time and compare to static decoders and unsupervised adaptive linear discriminant analysis classifiers. Main results. Our simulation experiments show GMMAC can accurately decode under time-varying activation patterns: shifts of activation region, expansions of activation region, and combined contractions and shifts of activation region. Furthermore, the experiments show the proposed method can track the changing shape of the activation region. Compared to prior work, GMMAC performed significantly better than the other unsupervised adaptive classifiers on a difficult activation pattern change simulation: 99% versus  brain-computer interfaces, including neurofeedback training systems, where operation over long time spans is required.

NIR studies of cholesterol-dependent structural modification of the model lipid bilayer doped with inhalation anesthetics

Science.gov (United States)

Kuć, Marta; Cieślik-Boczula, Katarzyna; Rospenk, Maria

2018-06-01

The influence of cholesterol on the structure of the model lipid bilayers treated with inhalation anesthetics (enflurane, isoflurane, sevoflurane and halothane) was investigated employing near-infrared (NIR) spectroscopy combined with the Principal Component Analysis (PCA). The conformational changes occurring in the hydrophobic area of the lipid bilayers were analyzed using the first overtones of symmetric (2νs) and antisymmetric (2νas) stretching vibrations of the CH2 groups of lipid aliphatic chains. The temperature values of chain-melting phase transition (Tm) of anesthetic-mixed dipalmitoylphosphatidylcholine (DPPC)/cholesterol and dipalmitoylphosphatidylglycerol (DPPG)/cholesterol membranes, which were obtained from the PCA analysis, were compared with cholesterol-free DPPC and DPPG bilayers mixed with inhalation anesthetics.

Qualitative and Quantitative Analysis of Heparin during Precipitation by Near-Infrared Spectroscopy

OpenAIRE

Lian Li; Jinfeng Wang; Hengchang Zang; Hui Zhang; Wei Jiang; Shang Chen; Fengshan Wang

2016-01-01

Heparin is a glycosaminoglycan (GAG) that plays an important role in the blood coagulation system. Its quality is of great importance, so it is necessary to develop a fast analytical method during the manufacture process to analyse the quality of heparin produced. In this study, the heparin contents of 80 samples collected from five batches during the precipitation process were analysed using nearinfrared (NIR) spectroscopy and a chemometrics approach. This was done in order to improve the ef...

Near-infrared Spectroscopy in the Brewing Industry.

Science.gov (United States)

Sileoni, Valeria; Marconi, Ombretta; Perretti, Giuseppe

2015-01-01

This article offers an exhaustive description of the use of Near-Infrared (NIR) Spectroscopy in the brewing industry. This technique is widely used for quality control testing of raw materials, intermediates, and finished products, as well as process monitoring during malting and brewing. In particular, most of the reviewed works focus on the assessment of barley properties, aimed at quickly selecting the best barley varieties in order to produce a high-quality malt leading to high-quality beer. Various works concerning the use of NIR in the evaluation of raw materials, such as barley, malt, hop, and yeast, are also summarized here. The implementation of NIR sensors for the control of malting and brewing processes is also highlighted, as well as the use of NIR for quality assessment of the final product.

Decorin Content and Near Infrared Spectroscopy Analysis of Dried Collagenous Biomaterial Samples

Directory of Open Access Journals (Sweden)

Suzanne Schreyer

2012-12-01

Full Text Available The efficient removal of proteoglycans, such as decorin, from the hide when processing it to leather by traditional means is generally acceptable and beneficial for leather quality, especially for softness and flexibility. A patented waterless or acetone dehydration method that can generate a product similar to leather called Dried Collagenous Biomaterial (known as BCD was developed but has no effect on decorin removal efficiency. The Alcian Blue colorimetric technique was used to assay the sulfated glycosaminoglycan (sGAG portion of decorin. The corresponding residual decorin content was correlated to the mechanical properties of the BCD samples and was comparable to the control leather made traditionally. The waterless dehydration and instantaneous chrome tanning process is a good eco-friendly alternative to transforming hides to leather because no additional effects were observed after examination using NIR spectroscopy and additional chemometric analysis.

Decorin content and near infrared spectroscopy analysis of dried collagenous biomaterial samples.

Science.gov (United States)

Aldema-Ramos, Mila L; Castell, Joan Carles; Muir, Zerlina E; Adzet, Jose Maria; Sabe, Rosa; Schreyer, Suzanne

2012-12-14

The efficient removal of proteoglycans, such as decorin, from the hide when processing it to leather by traditional means is generally acceptable and beneficial for leather quality, especially for softness and flexibility. A patented waterless or acetone dehydration method that can generate a product similar to leather called Dried Collagenous Biomaterial (known as BCD) was developed but has no effect on decorin removal efficiency. The Alcian Blue colorimetric technique was used to assay the sulfated glycosaminoglycan (sGAG) portion of decorin. The corresponding residual decorin content was correlated to the mechanical properties of the BCD samples and was comparable to the control leather made traditionally. The waterless dehydration and instantaneous chrome tanning process is a good eco-friendly alternative to transforming hides to leather because no additional effects were observed after examination using NIR spectroscopy and additional chemometric analysis.

Decorin Content and Near Infrared Spectroscopy Analysis of Dried Collagenous Biomaterial Samples

Science.gov (United States)

Aldema-Ramos, Mila L.; Castell, Joan Carles; Muir, Zerlina E.; Adzet, Jose Maria; Sabe, Rosa; Schreyer, Suzanne

2012-01-01

The efficient removal of proteoglycans, such as decorin, from the hide when processing it to leather by traditional means is generally acceptable and beneficial for leather quality, especially for softness and flexibility. A patented waterless or acetone dehydration method that can generate a product similar to leather called Dried Collagenous Biomaterial (known as BCD) was developed but has no effect on decorin removal efficiency. The Alcian Blue colorimetric technique was used to assay the sulfated glycosaminoglycan (sGAG) portion of decorin. The corresponding residual decorin content was correlated to the mechanical properties of the BCD samples and was comparable to the control leather made traditionally. The waterless dehydration and instantaneous chrome tanning process is a good eco-friendly alternative to transforming hides to leather because no additional effects were observed after examination using NIR spectroscopy and additional chemometric analysis. PMID:24970152

Tinnitus alters resting state functional connectivity (RSFC) in human auditory and non-auditory brain regions as measured by functional near-infrared spectroscopy (fNIRS).

Science.gov (United States)

San Juan, Juan; Hu, Xiao-Su; Issa, Mohamad; Bisconti, Silvia; Kovelman, Ioulia; Kileny, Paul; Basura, Gregory

2017-01-01

Tinnitus, or phantom sound perception, leads to increased spontaneous neural firing rates and enhanced synchrony in central auditory circuits in animal models. These putative physiologic correlates of tinnitus to date have not been well translated in the brain of the human tinnitus sufferer. Using functional near-infrared spectroscopy (fNIRS) we recently showed that tinnitus in humans leads to maintained hemodynamic activity in auditory and adjacent, non-auditory cortices. Here we used fNIRS technology to investigate changes in resting state functional connectivity between human auditory and non-auditory brain regions in normal-hearing, bilateral subjective tinnitus and controls before and after auditory stimulation. Hemodynamic activity was monitored over the region of interest (primary auditory cortex) and non-region of interest (adjacent non-auditory cortices) and functional brain connectivity was measured during a 60-second baseline/period of silence before and after a passive auditory challenge consisting of alternating pure tones (750 and 8000Hz), broadband noise and silence. Functional connectivity was measured between all channel-pairs. Prior to stimulation, connectivity of the region of interest to the temporal and fronto-temporal region was decreased in tinnitus participants compared to controls. Overall, connectivity in tinnitus was differentially altered as compared to controls following sound stimulation. Enhanced connectivity was seen in both auditory and non-auditory regions in the tinnitus brain, while controls showed a decrease in connectivity following sound stimulation. In tinnitus, the strength of connectivity was increased between auditory cortex and fronto-temporal, fronto-parietal, temporal, occipito-temporal and occipital cortices. Together these data suggest that central auditory and non-auditory brain regions are modified in tinnitus and that resting functional connectivity measured by fNIRS technology may contribute to conscious phantom

Tinnitus alters resting state functional connectivity (RSFC in human auditory and non-auditory brain regions as measured by functional near-infrared spectroscopy (fNIRS.

Directory of Open Access Journals (Sweden)

Juan San Juan

Full Text Available Tinnitus, or phantom sound perception, leads to increased spontaneous neural firing rates and enhanced synchrony in central auditory circuits in animal models. These putative physiologic correlates of tinnitus to date have not been well translated in the brain of the human tinnitus sufferer. Using functional near-infrared spectroscopy (fNIRS we recently showed that tinnitus in humans leads to maintained hemodynamic activity in auditory and adjacent, non-auditory cortices. Here we used fNIRS technology to investigate changes in resting state functional connectivity between human auditory and non-auditory brain regions in normal-hearing, bilateral subjective tinnitus and controls before and after auditory stimulation. Hemodynamic activity was monitored over the region of interest (primary auditory cortex and non-region of interest (adjacent non-auditory cortices and functional brain connectivity was measured during a 60-second baseline/period of silence before and after a passive auditory challenge consisting of alternating pure tones (750 and 8000Hz, broadband noise and silence. Functional connectivity was measured between all channel-pairs. Prior to stimulation, connectivity of the region of interest to the temporal and fronto-temporal region was decreased in tinnitus participants compared to controls. Overall, connectivity in tinnitus was differentially altered as compared to controls following sound stimulation. Enhanced connectivity was seen in both auditory and non-auditory regions in the tinnitus brain, while controls showed a decrease in connectivity following sound stimulation. In tinnitus, the strength of connectivity was increased between auditory cortex and fronto-temporal, fronto-parietal, temporal, occipito-temporal and occipital cortices. Together these data suggest that central auditory and non-auditory brain regions are modified in tinnitus and that resting functional connectivity measured by fNIRS technology may contribute to

[Research on modeling method to analyze Lonicerae Japonicae Flos extraction process with online MEMS-NIR based on two types of error detection theory].

Science.gov (United States)

Du, Chen-Zhao; Wu, Zhi-Sheng; Zhao, Na; Zhou, Zheng; Shi, Xin-Yuan; Qiao, Yan-Jiang

2016-10-01

To establish a rapid quantitative analysis method for online monitoring of chlorogenic acid in aqueous solution of Lonicera Japonica Flos extraction by using micro-electromechanical near infrared spectroscopy (MEMS-NIR). High performance liquid chromatography(HPLC) was used as reference method．Kennard-Stone (K-S) algorithm was used to divide sample sets, and partial least square(PLS) regression was adopted to establish the multivariate analysis model between the HPLC analysis contents and NIR spectra. The synergy interval partial least squares (SiPLS) was used to selected modeling waveband to establish PLS models. RPD was used to evaluate the prediction performance of the models. MDLs was calculated based on two types of error detection theory, on-line analytical modeling approach of Lonicera Japonica Flos extraction process was expressed scientifically by MDL. The result shows that the model established by multiplicative scatter correction(MSC) was the best, with the root mean square with cross validation(RMSECV), root mean square error of correction(RMSEC) and root mean square error of prediction(RMSEP) of chlorogenic acid as 1.707, 1.489, 2.362, respectively, the determination coefficient of the calibration model was 0.998 5, and the determination coefficient of the prediction was 0.988 1．The value of RPD is 9.468.The MDL (0.042 15 g•L⁻¹) selected by SiPLS is less than the original,which demonstrated that SiPLS was beneficial to improve the prediction performance of the model. In this study, a more accurate expression of the prediction performance of the model from the two types of error detection theory, to further illustrate MEMS-NIR spectroscopy can be used for on-line monitoring of Lonicera Japonica Flos extraction process. Copyright© by the Chinese Pharmaceutical Association.

Physiological denoising of BOLD fMRI data using Regressor Interpolation at Progressive Time Delays (RIPTiDe) processing of concurrent fMRI and near-infrared spectroscopy (NIRS).

Science.gov (United States)

Frederick, Blaise deB; Nickerson, Lisa D; Tong, Yunjie

2012-04-15

Confounding noise in BOLD fMRI data arises primarily from fluctuations in blood flow and oxygenation due to cardiac and respiratory effects, spontaneous low frequency oscillations (LFO) in arterial pressure, and non-task related neural activity. Cardiac noise is particularly problematic, as the low sampling frequency of BOLD fMRI ensures that these effects are aliased in recorded data. Various methods have been proposed to estimate the noise signal through measurement and transformation of the cardiac and respiratory waveforms (e.g. RETROICOR and respiration volume per time (RVT)) and model-free estimation of noise variance through examination of spatial and temporal patterns. We have previously demonstrated that by applying a voxel-specific time delay to concurrently acquired near infrared spectroscopy (NIRS) data, we can generate regressors that reflect systemic blood flow and oxygenation fluctuations effects. Here, we apply this method to the task of removing physiological noise from BOLD data. We compare the efficacy of noise removal using various sets of noise regressors generated from NIRS data, and also compare the noise removal to RETROICOR+RVT. We compare the results of resting state analyses using the original and noise filtered data, and we evaluate the bias for the different noise filtration methods by computing null distributions from the resting data and comparing them with the expected theoretical distributions. Using the best set of processing choices, six NIRS-generated regressors with voxel-specific time delays explain a median of 10.5% of the variance throughout the brain, with the highest reductions being seen in gray matter. By comparison, the nine RETROICOR+RVT regressors together explain a median of 6.8% of the variance in the BOLD data. Detection of resting state networks was enhanced with NIRS denoising, and there were no appreciable differences in the bias of the different techniques. Physiological noise regressors generated using

Data Mining and NIR Spectroscopy in Viticulture: Applications for Plant Phenotyping under Field Conditions

Directory of Open Access Journals (Sweden)

Salvador Gutiérrez

2016-02-01

Full Text Available Plant phenotyping is a very important topic in agriculture. In this context, data mining strategies may be applied to agricultural data retrieved with new non-invasive devices, with the aim of yielding useful, reliable and objective information. This work presents some applications of machine learning algorithms along with in-field acquired NIR spectral data for plant phenotyping in viticulture, specifically for grapevine variety discrimination and assessment of plant water status. Support vector machine (SVM, rotation forests and M5 trees models were built using NIR spectra acquired in the field directly on the adaxial side of grapevine leaves, with a non-invasive portable spectrophotometer working in the spectral range between 1600 and 2400 nm. The ν-SVM algorithm was used for the training of a model for varietal classification. The classifiers’ performance for the 10 varieties reached, for cross- and external validations, the 88.7% and 92.5% marks, respectively. For water stress assessment, the models developed using the absorbance spectra of six varieties yielded the same determination coefficient for both cross- and external validations (R2 = 0.84; RMSEs of 0.164 and 0.165 MPa, respectively. Furthermore, a variety-specific model trained only with samples of Tempranillo from two different vintages yielded R2 = 0.76 and RMSE of 0.16 MPa for cross-validation and R2 = 0.79, RMSE of 0.17 MPa for external validation. These results show the power of the combined use of data mining and non-invasive NIR sensing for in-field grapevine phenotyping and their usefulness for the wine industry and precision viticulture implementations.

Neuroimaging in autism spectrum disorders: 1H-MRS and NIRS study.

Science.gov (United States)

Mori, Kenji; Toda, Yoshihiro; Ito, Hiromichi; Mori, Tatsuo; Mori, Keiko; Goji, Aya; Hashimoto, Hiroko; Tani, Hiroe; Miyazaki, Masahito; Harada, Masafumi; Kagami, Shoji

2015-01-01

Using proton magnetic resonance spectroscopy ((1)H-MRS), we measured chemical metabolites in the left amygdala and the bilateral orbito-frontal cortex (OFC) in children with autism spectrum disorders (ASD). The concentrations of N-acetylaspartate (NAA) in these regions of ASD were significantly decreased compared to those in the control group. In the autistic patients, the NAA concentrations in these regions correlated with their social quotient. These findings suggest the presence of neuronal dysfunction in the amygdala and OFC in ASD. Dysfunction in the amygdala and OFC may contribute to the pathogenesis of ASD. We performed a near-infrared spectroscopy (NIRS) study to evaluate the mirror neuron system in children with ASD. The concentrations of oxygenated hemoglobin (oxy-Hb) were measured with frontal probes using a 34-channel NIRS machine while the subjects imitated emotional facial expressions. The increments in the concentration of oxy-Hb in the pars opercularis of the inferior frontal gyrus in autistic subjects were significantly lower than those in the controls. However, the concentrations of oxy-Hb in this area were significantly elevated in autistic subjects after they were trained to imitate emotional facial expressions. The results suggest that mirror neurons could be activated by repeated imitation in children with ASD.

Validation of interventional fiber optic spectroscopy with MR Spectroscopy, MAS-NMR spectroscopy, high-performance thin-layer chromatography, and histopathology for accurate hepatic fat quantification

NARCIS (Netherlands)

Nachabé, R.; Hoorn, J.W.A. van der; Molengraaf, R. van de; Lamerichs, R.; Pikkemaat, J.; Sio, C.F.; Hendriks, B.H.W.; Sterenborg, H.J.C.M.

2012-01-01

Objectives: To validate near-infrared (NIR)-based optical spectroscopy measurements of hepatic fat content using a minimally invasive needle-like probe with integrated optical fibers, enabling real-time feedback during percutaneous interventions. The results were compared with magnetic resonance

Fast gas spectroscopy using pulsed quantum cascade lasers

Science.gov (United States)

Beyer, T.; Braun, M.; Lambrecht, A.

2003-03-01

Laser spectroscopy has found many industrial applications, e.g., control of automotive exhaust and process monitoring. The midinfrared region is of special interest because it has stronger absorption lines compared to the near infrared (NIR). However, in the NIR high quality reliable laser sources, detectors, and passive optical components are available. A quantum cascade laser could change this situation if fundamental advantages can be exploited with compact and reliable systems. It will be shown that, using pulsed lasers and available fast detectors, lower residual sensitivity levels than in corresponding NIR systems can be achieved. The stability is sufficient for industrial applications.

Optimization of NIR Spectral Data Management for Quality Control of Grape Bunches during On-Vine Ripening

Directory of Open Access Journals (Sweden)

María-Teresa Sánchez

2011-06-01

Full Text Available NIR spectroscopy was used as a non-destructive technique for the assessment of chemical changes in the main internal quality properties of wine grapes (Vitis vinifera L. during on-vine ripening and at harvest. A total of 363 samples from 25 white and red grape varieties were used to construct quality-prediction models based on reference data and on NIR spectral data obtained using a commercially-available diode-array spectrophotometer (380–1,700 nm. The feasibility of testing bunches of intact grapes was investigated and compared with the more traditional must-based method. Two regression approaches (MPLS and LOCAL algorithms were tested for the quantification of changes in soluble solid content (SSC, reducing sugar content, pH-value, titratable acidity, tartaric acid, malic acid and potassium content. Cross-validation results indicated that NIRS technology provided excellent precision for sugar-related parameters (r2 = 0.94 for SSC and reducing sugar content and good precision for acidity-related parameters (r2 ranging between 0.73 and 0.87 for the bunch-analysis mode assayed using MPLS regression. At validation level, comparison of LOCAL and MPLS algorithms showed that the non-linear strategy improved the predictive capacity of the models for all study parameters, with particularly good results for acidity-related parameters and potassium content.

Vibrational Spectroscopies and Chemometry for Nondestructive Identification and Differentiation of Painting Binders

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Serena Carlesi

2017-01-01

Full Text Available A comprehensive dataset of vibrational spectra of different natural organic binding media is presented and discussed. The binding media were applied on a glass substrate and analyzed after three months of natural ageing. The combination of Raman and FT-NIR spectroscopies allows for an improved identification of these materials as Raman technique is more informative about the skeletal vibrations, while FT-NIR spectroscopy is more sensitive to the substituents and polar groups. The experimental results are initially discussed in the framework of current spectral assignment. Then, multivariate analysis (PCA is applied leading to differentiation among the samples. The two major principal components allow for a complete separation of the different classes of organic materials. Further differentiation within the same class is possible thanks to the secondary components. The loadings obtained from PCA are discussed on the basis of the spectral assignment leading to clear understanding of the physical basis of this differentiation process.

Classification of plum spirit drinks by synchronous fluorescence spectroscopy.

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Sádecká, J; Jakubíková, M; Májek, P; Kleinová, A

2016-04-01

Synchronous fluorescence spectroscopy was used in combination with principal component analysis (PCA) and linear discriminant analysis (LDA) for the differentiation of plum spirits according to their geographical origin. A total of 14 Czech, 12 Hungarian and 18 Slovak plum spirit samples were used. The samples were divided in two categories: colorless (22 samples) and colored (22 samples). Synchronous fluorescence spectra (SFS) obtained at a wavelength difference of 60 nm provided the best results. Considering the PCA-LDA applied to the SFS of all samples, Czech, Hungarian and Slovak colorless samples were properly classified in both the calibration and prediction sets. 100% of correct classification was also obtained for Czech and Hungarian colored samples. However, one group of Slovak colored samples was classified as belonging to the Hungarian group in the calibration set. Thus, the total correct classifications obtained were 94% and 100% for the calibration and prediction steps, respectively. The results were compared with those obtained using near-infrared (NIR) spectroscopy. Applying PCA-LDA to NIR spectra (5500-6000 cm(-1)), the total correct classifications were 91% and 92% for the calibration and prediction steps, respectively, which were slightly lower than those obtained using SFS. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

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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

Evaluation of PLS, LS-SVM, and LWR for quantitative spectroscopic analysis of soils

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Soil testing requires the analysis of large numbers of samples in laboratory that are often time consuming and expensive. Mid-infrared spectroscopy (mid-IR) and near-infrared spectroscopy (NIRS) are fast, non-destructive, and inexpensive analytical methods that have been used for soil analysis, in l...

Motor learning and modulation of prefrontal cortex: an fNIRS assessment

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Ono, Yumie; Noah, Jack Adam; Zhang, Xian; Nomoto, Yasunori; Suzuki, Tatsuya; Shimada, Sotaro; Tachibana, Atsumichi; Bronner, Shaw; Hirsch, Joy

2015-12-01

Objective. Prefrontal hemodynamic responses are observed during performance of motor tasks. Using a dance video game (DVG), a complex motor task that requires temporally accurate footsteps with given visual and auditory cues, we investigated whether 20 h of DVG training modified hemodynamic responses of the prefrontal cortex in six healthy young adults. Approach. Fronto-temporal activity during actual DVG play was measured using functional near-infrared spectroscopy (fNIRS) pre- and post-training. To evaluate the training-induced changes in the time-courses of fNIRS signals, we employed a regression analysis using the task-specific template fNIRS signals that were generated from alternate well-trained and/or novice DVG players. The HRF was also separately incorporated as a template to construct an alternate regression model. Change in coefficients for template functions at pre- and post- training were determined and compared among different models. Main results. Training significantly increased the motor performance using the number of temporally accurate steps in the DVG as criteria. The mean oxygenated hemoglobin (ΔoxyHb) waveform changed from an activation above baseline pattern to that of a below baseline pattern. Participants showed significantly decreased coefficients for regressors of the ΔoxyHb response of novice players and HRF. The model using ΔoxyHb responses from both well-trained and novice players of DVG as templates showed the best fit for the ΔoxyHb responses of the participants at both pre- and post-training when analyzed with Akaike information criteria. Significance. These results suggest that the coefficients for the template ΔoxyHb responses of the novice players are sensitive indicators of motor learning during the initial stage of training and thus clinically useful to determine the improvement in motor performance when patients are engaged in a specific rehabilitation program.

[Near-infrared reflectance spectroscopy predicts protein, moisture and ash in beans].

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Gao, Huiyu; Wang, Guodong; Men, Jianhua; Wang, Zhu

2017-05-01

To explore the potential of near-infrared reflectance( NIR)spectroscopy to determine macronutrient contents in beans. NIR spectra and analytical measurements of protein, moisture and ash were collected from 70 kinds of beans. Reference methods were used to analyze all the ground beans samples. NIR spectra on intact and ground beans samples were registered. Partial least-squares( PLS)regression models were developed with principal components analysis( PCA) to assign 49 bean accessions to a calibration data set and 21 accessions to an external validation set. For intact beans, the relative predictive determinant( RPD) values for protein and ash( 3. 67 and 3. 97, respectively) were good for screening. RPD value for moisture was only 1. 39, which was not recommended. For ground beans, the RPD values for protein, moisture and ash( 6. 63, 5. 25 and 3. 57, respectively) were good enough for screening. The protein, moisture and ash levels for intact and ground beans were all significantly correlated( P beans with no or easy sample preparation.

NIRS Study of the Effects of Computerized Brain Training Games for Cognitive Rehabilitation of Major Depressive Disorder Patients in Remission: A Pilot Study.

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Payzieva, Shaira; Maxmudova, D

2014-01-01

We used functional Near-Infrared Spectroscopy (fNIRS) to estimate brain activity in Major Depressive Disorder (MDD) patients (in remission), while they played a computerized brain training games for cognitive rehabilitation. MDD is characterized by marked deterioration in affect as well as significant impairment in cognitive function. It was found, that depressed patients showed long-lasting impaired cognitive performance on cognitive demanding tasks despite significant improvement in the depression symptoms. Previous studies have shown that video games can improve cognitive functions. But assessment was made only with cognitive tests. The main objective of this research was to study the effects of brain training games on cognitive functions of MDD patients in remission with objective instrumental NIRS method. Tissue oxygen saturation (StO2) and absolute concentrations of oxyhemoglobin ([O2Hb]), deoxyhemoglobin ([HHb]) and total hemoglobin ([tHb]) were measured by functional near-infrared spectroscopy (fNIRS) - Oxyprem (BORL, Zurich, Switzerland). Preliminary results are discussed.

In situ ESR/UV-vis-NIR and ATR-FTIR spectroelectrochemical studies on the p-doping of copolymers of 3-methylthiophene and 3-hexylthiophene.

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Cházaro-Ruiz, Luis F; Kellenberger, Andrea; Dunsch, Lothar

2009-02-26

A combined spectroelectrochemical study by ESR/UV-vis-NIR as well as FTIR spectroscopy on the influence of the copolymer composition on the stabilization of charges upon electrochemical p-doping is presented. As compared to the parent homopolymers 3-hexylthiophene (3-HeTh) and 3-methylthiophene (3-MeTh) which seems to be irregular, FTIR studies of the copolymer of both monomers (copMeHeTh) point to a regioregular structure. The in situ ESR and UV-vis-NIR spectroelectrochemistry at higher doping levels of the polymeric materials proves bipolarons and polaron pairs as stable charged states in poly(3-hexylthiophene) as well as the copolymer copMeHeTh. During the p-doping of poly(3-methylthiophene) bipolarons are the dominating species at higher doping levels. It is demonstrated that only the simultaneous use of both the ESR and the UV-vis-NIR spectroscopy enables the differentiation of polarons (paramagnetic) and polaron pairs (diamagnetic) in a conducting polymer.

Characterization and correction of the false-discovery rates in resting state connectivity using functional near-infrared spectroscopy

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Santosa, Hendrik; Aarabi, Ardalan; Perlman, Susan B.; Huppert, Theodore J.

2017-05-01

Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low levels of red to near-infrared light to measure changes in cerebral blood oxygenation. Spontaneous (resting state) functional connectivity (sFC) has become a critical tool for cognitive neuroscience for understanding task-independent neural networks, revealing pertinent details differentiating healthy from disordered brain function, and discovering fluctuations in the synchronization of interacting individuals during hyperscanning paradigms. Two of the main challenges to sFC-NIRS analysis are (i) the slow temporal structure of both systemic physiology and the response of blood vessels, which introduces false spurious correlations, and (ii) motion-related artifacts that result from movement of the fNIRS sensors on the participants' head and can introduce non-normal and heavy-tailed noise structures. In this work, we systematically examine the false-discovery rates of several time- and frequency-domain metrics of functional connectivity for characterizing sFC-NIRS. Specifically, we detail the modifications to the statistical models of these methods needed to avoid high levels of false-discovery related to these two sources of noise in fNIRS. We compare these analysis procedures using both simulated and experimental resting-state fNIRS data. Our proposed robust correlation method has better performance in terms of being more reliable to the noise outliers due to the motion artifacts.

Rapid Characterization of Fatty Acids in Oleaginous Microalgae by Near-Infrared Spectroscopy

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Bin Liu

2015-03-01

Full Text Available The key properties of microalgal biodiesel are largely determined by the composition of its fatty acid methyl esters (FAMEs. The gas chromatography (GC based techniques for fatty acid analysis involve energy-intensive and time-consuming procedures and thus are less suitable for high-throughput screening applications. In the present study, a novel quantification method for microalgal fatty acids was established based on the near-infrared spectroscopy (NIRS technique. The lyophilized cells of oleaginous Chlorella containing different contents of lipids were scanned by NIRS and their fatty acid profiles were determined by GC-MS. NIRS models were developed based on the chemometric correlation of the near-infrared spectra with fatty acid profiles in algal biomass. The optimized NIRS models showed excellent performances for predicting the contents of total fatty acids, C16:0, C18:0, C18:1 and C18:3, with the coefficient of determination (R2 being 0.998, 0.997, 0.989, 0.991 and 0.997, respectively. Taken together, the NIRS method established here bypasses the procedures of cell disruption, oil extraction and transesterification, is rapid, reliable, and of great potential for high-throughput applications, and will facilitate the screening of microalgal mutants and optimization of their growth conditions for biodiesel production.

Near-infrared spectroscopy monitoring and control of the fluidized bed granulation and coating processes-A review.

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Liu, Ronghua; Li, Lian; Yin, Wenping; Xu, Dongbo; Zang, Hengchang

2017-09-15

The fluidized bed granulation and pellets coating technologies are widely used in pharmaceutical industry, because the particles made in a fluidized bed have good flowability, compressibility, and the coating thickness of pellets are homogeneous. With the popularization of process analytical technology (PAT), real-time analysis for critical quality attributes (CQA) was getting more attention. Near-infrared (NIR) spectroscopy, as a PAT tool, could realize the real-time monitoring and control during the granulating and coating processes, which could optimize the manufacturing processes. This article reviewed the application of NIR spectroscopy in CQA (moisture content, particle size and tablet/pellet thickness) monitoring during fluidized bed granulation and coating processes. Through this review, we would like to provide references for realizing automated control and intelligent production in fluidized bed granulation and pellets coating of pharmaceutical industry. Copyright © 2017 Elsevier B.V. All rights reserved.

Altered low frequency oscillations of cortical vessels in patients with cerebrovascular occlusive disease – a NIRS study

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Dorte ePhillip

2013-12-01

Full Text Available Analysis of cerebral autoregulation by measuring spontaneous oscillations in the low frequency spectrum of cerebral cortical vessels might be a useful tool for assessing risk and investigating different treatment strategies in carotid artery disease (CAD and stroke. Near infrared spectroscopy (NIRS is a non-invasive optical method to investigate regional changes in oxygenated (oxyHb and deoxygenated hemoglobin (deoxyHb in the outermost layers of the cerebral cortex. In the present study we examined oxyHb low frequency oscillations (LFOs, believed to reflect cortical cerebral autoregulation, in 16 patients with both symptomatic carotid occlusive disease and cerebral hypoperfusion in comparison to healthy controls. Each hemisphere was examined with 2 NIRS channels using a 3 cm source detector distance. Arterial blood pressure (ABP was measured via a finger plethysmograph. Using transfer function analysis ABP-oxyHb phase shift and gain as well as inter-hemispheric phase shift and amplitude ratio were assessed. We found that inter-hemispheric amplitude ratio was significantly altered in hypoperfusion patients compared to healthy controls (P= 0.010, because of relatively lower amplitude on the hypoperfusion side. The inter-hemispheric phase shift showed a trend (P = 0.061 towards increased phase shift in hypoperfusion patients compared to controls. We found no statistical difference between hemispheres in hypoperfusion patients for phase shift or gain values. There were no differences between the hypoperfusion side and controls for phase shift or gain values. These preliminary results suggest an impairment of autoregulation in hypoperfusion patients at the cortical level using NIRS.

Noninvasive detection of change in skeletal muscle oxygenation during incremental exercise with near-infrared spectroscopy

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Liu, Fang; Luo, Qingming; Xu, Guodong; Li, Pengcheng

2003-12-01

Near infrared spectroscopy (NIRS) has been developed as a non-invasive method to assess O2 delivery, O2 consumption and blood flow, in diverse local muscle groups at rest and during exercise. The aim of this study was to investigate local O2 consumption in exercising muscle by use of near-infrared spectroscopy (NIRS). Ten elite athletes of different sport items were tested in rest and during step incremental load exercise. Local variations of quadriceps muscles were investigated with our wireless NIRS blood oxygen monitor system. The results show that the changes of blood oxygen relate on the sport items, type of muscle, kinetic capacity et al. These results indicate that NIRS is a potential useful tool to detect local muscle oxygenation and blood flow profiles; therefore it might be easily applied for evaluating the effect of athletes training.

Quantification of betaglucans, lipid and protein contents in whole oat groats (Avena sativa L.) using near infrared reflectance spectroscopy

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Whole oat has been described as an important healthy food for humans due to its beneficial nutritional components. Near infrared reflectance spectroscopy (NIRS) is a powerful, fast, accurate and non-destructive analytical tool that can be substituted for some traditional chemical analysis. A total o...

A data analysis workflow to enhance clay and organic carbon models using proximal Vis-NIR data

DEFF Research Database (Denmark)

Tabatabai, Salman; Knadel, Maria; Greve, Mogens Humlekrog

Modelling proximal sensors data is becoming a norm in soil characterization and mapping. In many cases, these models still have low predictive capabilities and lack robustness due to the large amount of noise from several environmental factors. In this study we proposed a combination of extensive...... data preprocessing (preprocessing survey) and two variable selection methods to significantly increase visible near-infrared spectroscopy (Vis-NIRS) model performance and stability. Spectra of eight agricultural fields were measured in the range of 350-2200 nm using a mobile sensor platform (Veris...... Technologies, USA) towed by a tractor. A fuzzy c-means clustering was performed based on the first 3 principal components to select 15 representative sampling locations in each field. Clay and organic carbon (OC) were determined for all calibration samples using pipette and ignition methods, respectively...

Origin of broad NIR photoluminescence in bismuthate glass and Bi-doped glasses at room temperature

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Peng, Mingying; Zollfrank, Cordt; Wondraczek, Lothar [Lehrstuhl fuer Glas und Keramik, WW3, Friedrich Alexander Universitaet Erlangen-Nuernberg, Martensstrasse 5, D-91058 Erlangen (Germany)], E-mail: mingying.peng@ww.uni-erlangen.de, E-mail: lothar.wondraczek@ww.uni-erlangen.de

2009-07-15

Bi-doped glasses with broadband photoluminescence in the near-infrared (NIR) spectral range are presently receiving significant consideration for potential applications in telecommunications, widely tunable fiber lasers and spectral converters. However, the origin of NIR emission remains disputed. Here, we report on NIR absorption and emission properties of bismuthate glass and their dependence on the melting temperature. Results clarify that NIR emission occurs from the same centers as it does in Bi-doped glasses. The dependence of absorption and NIR emission of bismuthate glasses on the melting temperature is interpreted as thermal dissociation of Bi{sub 2}O{sub 3} into elementary Bi. Darkening of bismuthate glass melted at 1300 deg. C is due to the agglomeration of Bi atoms. The presence of Bi nanoparticles is confirmed by transmission electron microscopy, high-resolution energy dispersive x-ray spectroscopy and element distribution mapping. By adding antimony oxide as an oxidation agent to the glass, NIR emission centers can be eliminated and Bi{sup 3+} is formed. By comparing with atomic spectral data, absorption bands at {approx}320 , {approx}500 , 700 , 800 and 1000 nm observed in Bi-doped glasses are assigned to Bi{sup 0} transitions {sup 4}S{sub 3/2}{yields}{sup 2}P{sub 3/2}, {sup 4}S{sub 3/2}{yields}{sup 2}P{sub 1/2}, {sup 4}S{sub 3/2}{yields}{sup 2}D{sub 5/2}, {sup 4}S{sub 3/2}{yields}{sup 2}D{sub 3/2}(2) and {sup 4}S{sub 3/2}{yields}{sup 2}D{sub 3/2}(1), respectively, and broadband NIR emission is assigned to the transition {sup 2}D{sub 3/2}(1){yields}{sup 4}S{sub 3/2}.

`VIS/NIR mapping of TOC and extent of organic soils in the Nørre Å valley

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Knadel, M.; Greve, M. H.; Thomsen, A.

2009-04-01

Organic soils represent a substantial pool of carbon in Denmark. The need for carbon stock assessment calls for more rapid and effective mapping methods to be developed. The aim of this study was to compare traditional soil mapping with maps produced from the results of a mobile VIS/NIR system and to evaluate the ability to estimate TOC and map the area of organic soils. The Veris mobile VIS/NIR spectroscopy system was compared to traditional manual sampling. The system is developed for in-situ near surface measurements of soil carbon content. It measures diffuse reflectance in the 350 nm-2200 nm region. The system consists of two spectrophotometers mounted on a toolbar and pulled by a tractor. Optical measurements are made through a sapphire window at the bottom of the shank. The shank was pulled at a depth of 5-7 cm at a speed of 4-5 km/hr. 20-25 spectra per second with 8 nm resolution were acquired by the spectrometers. Measurements were made on 10-12 m spaced transects. The system also acquired soil electrical conductivity (EC) for two soil depths: shallow EC-SH (0- 31 cm) and deep conductivity EC-DP (0- 91 cm). The conductivity was recorded together with GPS coordinates and spectral data for further construction of the calibration models. Two maps of organic soils in the Nørre Å valley (Central Jutland) were generated: (i) based on a conventional 25 m grid with 162 sampling points and laboratory analysis of TOC, (ii) based on in-situ VIS/NIR measurements supported by chemometrics. Before regression analysis, spectral information was compressed by calculating principal components. The outliers were determined by a mahalanobis distance equation and removed. Clustering using a fuzzy c- means algorithm was conducted. Within each cluster a location with the minimal spatial variability was selected. A map of 15 representative sample locations was proposed. The interpolation of the spectra into a single spectrum was performed using a Gaussian kernel weighting

Mental workload during n-back task-quantified in the prefrontal cortex using fNIRS.

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Herff, Christian; Heger, Dominic; Fortmann, Ole; Hennrich, Johannes; Putze, Felix; Schultz, Tanja

2013-01-01

When interacting with technical systems, users experience mental workload. Particularly in multitasking scenarios (e.g., interacting with the car navigation system while driving) it is desired to not distract the users from their primary task. For such purposes, human-machine interfaces (HCIs) are desirable which continuously monitor the users' workload and dynamically adapt the behavior of the interface to the measured workload. While memory tasks have been shown to elicit hemodynamic responses in the brain when averaging over multiple trials, a robust single trial classification is a crucial prerequisite for the purpose of dynamically adapting HCIs to the workload of its user. The prefrontal cortex (PFC) plays an important role in the processing of memory and the associated workload. In this study of 10 subjects, we used functional Near-Infrared Spectroscopy (fNIRS), a non-invasive imaging modality, to sample workload activity in the PFC. The results show up to 78% accuracy for single-trial discrimination of three levels of workload from each other. We use an n-back task (n ∈ {1, 2, 3}) to induce different levels of workload, forcing subjects to continuously remember the last one, two, or three of rapidly changing items. Our experimental results show that measuring hemodynamic responses in the PFC with fNIRS, can be used to robustly quantify and classify mental workload. Single trial analysis is still a young field that suffers from a general lack of standards. To increase comparability of fNIRS methods and results, the data corpus for this study is made available online.

Mental workload during n-back task - quantified in the prefrontal cortex using fNIRS

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Christian eHerff

2014-01-01

Full Text Available When interacting with technical systems, users experience mental workload. Particularly in multitasking scenarios (e.g. interacting with the car navigation system while driving it is desired to not distract the users from their primary task. For such purposes, human-machine interfaces (HCIs are desirable which continuously monitor the users' workload and dynamically adapt the behavior of the interface to the measured workload. While memory tasks have been shown to illicit hemodynamic responses in the brain when averaging over multiple trials, a robust single trial classification is a crucial prerequisite for the purpose of dynamically adapting HCIs to the workload of its user.The prefrontal cortex (PFC plays an important role in the processing of memory and the associated workload. In this study of 10 subjects, we used functional Near-Infrared Spectroscopy (fNIRS, a non-invasive imaging modality, to sample workload activity in the PFC. The results show up to 78% accuracy for single-trial discrimination of three levels of workload from each other. We use an n-back task (n ∈ {1, 2, 3} to induce different levels of workload, forcing subjects to continuously remember the last one, two or three of rapidly changing items.Our experimental results show that measuring hemodynamic responses in the PFC with fNIRS, can be used to robustly quantify and classify mental workload.Single trial analysis is still a young field that suffers from a general lack of standards. To increase comparability of fNIRS methods and results, the data corpus for this study is made available online.

Assessment of beer quality based on foamability and chemical composition using computer vision algorithms, near infrared spectroscopy and machine learning algorithms.

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Gonzalez Viejo, Claudia; Fuentes, Sigfredo; Torrico, Damir; Howell, Kate; Dunshea, Frank R

2018-01-01

Beer quality is mainly defined by its colour, foamability and foam stability, which are influenced by the chemical composition of the product such as proteins, carbohydrates, pH and alcohol. Traditional methods to assess specific chemical compounds are usually time-consuming and costly. This study used rapid methods to evaluate 15 foam and colour-related parameters using a robotic pourer (RoboBEER) and chemical fingerprinting using near infrared spectroscopy (NIR) from six replicates of 21 beers from three types of fermentation. Results from NIR were used to create partial least squares regression (PLS) and artificial neural networks (ANN) models to predict four chemometrics such as pH, alcohol, Brix and maximum volume of foam. The ANN method was able to create more accurate models (R 2  = 0.95) compared to PLS. Principal components analysis using RoboBEER parameters and NIR overtones related to protein explained 67% of total data variability. Additionally, a sub-space discriminant model using the absorbance values from NIR wavelengths resulted in the successful classification of 85% of beers according to fermentation type. The method proposed showed to be a rapid system based on NIR spectroscopy and RoboBEER outputs of foamability that can be used to infer the quality, production method and chemical parameters of beer with minimal laboratory equipment. © 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.

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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.

Using near infrared spectroscopy to classify soybean oil according to expiration date.

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da Costa, Gean Bezerra; Fernandes, David Douglas Sousa; Gomes, Adriano A; de Almeida, Valber Elias; Veras, Germano

2016-04-01

A rapid and non-destructive methodology is proposed for the screening of edible vegetable oils according to conservation state expiration date employing near infrared (NIR) spectroscopy and chemometric tools. A total of fifty samples of soybean vegetable oil, of different brands andlots, were used in this study; these included thirty expired and twenty non-expired samples. The oil oxidation was measured by peroxide index. NIR spectra were employed in raw form and preprocessed by offset baseline correction and Savitzky-Golay derivative procedure, followed by PCA exploratory analysis, which showed that NIR spectra would be suitable for the classification task of soybean oil samples. The classification models were based in SPA-LDA (Linear Discriminant Analysis coupled with Successive Projection Algorithm) and PLS-DA (Discriminant Analysis by Partial Least Squares). The set of samples (50) was partitioned into two groups of training (35 samples: 15 non-expired and 20 expired) and test samples (15 samples 5 non-expired and 10 expired) using sample-selection approaches: (i) Kennard-Stone, (ii) Duplex, and (iii) Random, in order to evaluate the robustness of the models. The obtained results for the independent test set (in terms of correct classification rate) were 96% and 98% for SPA-LDA and PLS-DA, respectively, indicating that the NIR spectra can be used as an alternative to evaluate the degree of oxidation of soybean oil samples. Copyright © 2015 Elsevier Ltd. All rights reserved.

Near-infrared Spectroscopy as a Process Analytical Technology Tool for Monitoring the Parching Process of Traditional Chinese Medicine Based on Two Kinds of Chemical Indicators.

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Li, Kaiyue; Wang, Weiying; Liu, Yanping; Jiang, Su; Huang, Guo; Ye, Liming

2017-01-01

The active ingredients and thus pharmacological efficacy of traditional Chinese medicine (TCM) at different degrees of parching process vary greatly. Near-infrared spectroscopy (NIR) was used to develop a new method for rapid online analysis of TCM parching process, using two kinds of chemical indicators (5-(hydroxymethyl) furfural [5-HMF] content and 420 nm absorbance) as reference values which were obviously observed and changed in most TCM parching process. Three representative TCMs, Areca ( Areca catechu L.), Malt ( Hordeum Vulgare L.), and Hawthorn ( Crataegus pinnatifida Bge.), were used in this study. With partial least squares regression, calibration models of NIR were generated based on two kinds of reference values, i.e. 5-HMF contents measured by high-performance liquid chromatography (HPLC) and 420 nm absorbance measured by ultraviolet-visible spectroscopy (UV/Vis), respectively. In the optimized models for 5-HMF, the root mean square errors of prediction (RMSEP) for Areca, Malt, and Hawthorn was 0.0192, 0.0301, and 0.2600 and correlation coefficients ( R cal ) were 99.86%, 99.88%, and 99.88%, respectively. Moreover, in the optimized models using 420 nm absorbance as reference values, the RMSEP for Areca, Malt, and Hawthorn was 0.0229, 0.0096, and 0.0409 and R cal were 99.69%, 99.81%, and 99.62%, respectively. NIR models with 5-HMF content and 420 nm absorbance as reference values can rapidly and effectively identify three kinds of TCM in different parching processes. This method has great promise to replace current subjective color judgment and time-consuming HPLC or UV/Vis methods and is suitable for rapid online analysis and quality control in TCM industrial manufacturing process. Near-infrared spectroscopy.(NIR) was used to develop a new method for online analysis of traditional Chinese medicine.(TCM) parching processCalibration and validation models of Areca, Malt, and Hawthorn were generated by partial least squares regression using 5

Twenty years of functional near-infrared spectroscopy: introduction for the special issue.

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Boas, David A; Elwell, Clare E; Ferrari, Marco; Taga, Gentaro

2014-01-15

Papers from four different groups were published in 1993 demonstrating the ability of functional near infrared spectroscopy (fNIRS) to non-invasively measure hemoglobin concentration responses to brain function in humans. This special issue commemorates the first 20years of fNIRS research. The 9 reviews and 49 contributed papers provide a comprehensive survey of the exciting advances driving the field forward and of the myriad of applications that will benefit from fNIRS. Copyright © 2013 Elsevier Inc. All rights reserved.

Design, construction, and testing of an automated NIR in-line analysis system for potatoes. Part I: Off-line NIR feasibility study for the characterization of potato composition

NARCIS (Netherlands)

Brunt, K.; Drost, W.C.

2010-01-01

An off-line near-infrared reflectance (NIR) feasibility study was conducted to explore the critical steps in the NIR determination of the major potato constituents (dry matter, starch, and protein) in relatively large (10 kg) potato samples. The results were important for the design of an automated

XRF and UV-Vis-NIR analyses of medieval wall paintings of al-Qarawiyyin Mosque (Morocco)

Science.gov (United States)

Fikri, I.; El Amraoui, M.; Haddad, M.; Ettahiri, A. S.; Bellot-Gurlet, L.; Falguères, C.; Lebon, M.; Nespoulet, R.; Ait Lyazidi, S.; Bejjit, L.

2018-05-01

Medieval wall painting fragments, taken at the medieval Mosque of al-Qarawiyyin in Fez, have been investigated by means of X-ray fluorescence and UV-Vis-NIR diffuse reflectance spectroscopies. The analyses permitted to determine the palette of pigments used by craftsmen of the time. Hematite or red ochre were used to obtain red brown colours, calcite for white, copper-based pigments for blue and blue-grey shades while a mixture of cinnabar, lead-based pigments and hematite was adopted to make red-orange colours. Furthermore, the analysis of mortars (external layer and plaster) on these wall painting samples revealed that they are composed mainly by calcite and sometimes by additional compounds such as quartz and gypsum.

Intact neurovascular coupling during executive function in migraine without aura: interictal near-infrared spectroscopy study

DEFF Research Database (Denmark)

Schytz, H W; Ciftçi, K; Akin, A

2010-01-01

An altered neurovascular coupling has been proposed in migraine. We aimed to investigate neurovascular coupling during a mental task interictally in patients with migraine without aura (MO) by near-infrared spectroscopy (NIRS). Twelve migraineurs and 12 healthy controls were included. Using NIRS,...

NIR detection of honey adulteration reveals differences in water spectral pattern.

Science.gov (United States)

Bázár, György; Romvári, Róbert; Szabó, András; Somogyi, Tamás; Éles, Viktória; Tsenkova, Roumiana

2016-03-01

High fructose corn syrup (HFCS) was mixed with four artisanal Robinia honeys at various ratios (0-40%) and near infrared (NIR) spectra were recorded with a fiber optic immersion probe. Levels of HFCS adulteration could be detected accurately using leave-one-honey-out cross-validation (RMSECV=1.48; R(2)CV=0.987), partial least squares regression and the 1300-1800nm spectral interval containing absorption bands related to both water and carbohydrates. Aquaphotomics-based evaluations showed that unifloral honeys contained more highly organized water than the industrial sugar syrup, supposedly because of the greater variety of molecules dissolved in the multi-component honeys. Adulteration with HFCS caused a gradual reduction of water molecular structures, especially water trimers, which facilitate interaction with other molecules. Quick, non-destructive NIR spectroscopy combined with aquaphotomics could be used to describe water molecular structures in honey and to detect a rather common form of adulteration. Copyright © 2015 Elsevier Ltd. All rights reserved.

The estimation of hemodynamic signals measured by fNIRS response to cold pressor test

Science.gov (United States)

Ansari, M. A.; Fazliazar, E.

2018-04-01

The estimation of cerebral hemodynamic signals has an important role for monitoring the stage of neurological diseases. Functional Near-Infrared Spectroscopy (fNIRS) can be used for monitoring of brain activities. fNIRS utilizes light in the near-infrared spectrum (650-1000 nm) to study the response of the brain vasculature to the changes in neural activities, called neurovascular coupling, within the cortex when cognitive activation occurs. The neurovascular coupling may be disrupted in the brain pathological condition. Therefore, we can also use fNIRS to diagnosis brain pathological conditions or to monitor the efficacy of related treatments. The Cold pressor test (CPT), followed by immersion of dominant hand or foot in the ice water, can induce cortical activities. The perception of pain induced by CPT can be related to cortical neurovascular coupling. Hence, the variation of cortical hemodynamic signals during CPT can be an indicator for studying neurovascular coupling. Here, we study the effect of pain induced by CPT on the temporal variation of concentration of oxyhemoglobin [HbO2] and deoxyhemoglobin [Hb] in the healthy brains. We use fNIRS data collected on forehead during a CPT from 11 healthy subjects, and the average data are compared with post-stimulus pain rating scores. The results show that the variation of [Hb] and [HbO2] are positively correlated with self-reported scores during the CPT. These results depict that fNIRS can be potentially applied to study the decoupling of neurovascular process in brain pathological conditions.

Characterisation of crude oil components, asphaltene aggregation and emulsion stability by means of near infrared spectroscopy and multivariate analysis

Energy Technology Data Exchange (ETDEWEB)

Aske, Narve

2002-06-01

Effective separation of water-in-crude oil emulsions is a central challenge for the oil industry on the Norwegian Continental Shelf, especially with the future increase in subsea and even down-hole processing of well fluids. The mechanisms and properties governing emulsion stability are far from fully understood but the indigenous surface active crude oil components are believed to play a major role. In this work a thorough physico-chemical characterisation of a set of crude oils originating from a variety of production fields has been performed. Crude oil properties responsible for emulsion stability were identified by use of multivariate analysis techniques like partial least squares regression (PLS) and principal component analysis (PCA). Interfacial elasticity along with both asphaltene content and asphaltene aggregation state were found to be main contributors to emulsion stability. Information on a crude oils ability to form elastic crude oil-water interfaces was found to be especially crucial when discussing emulsion stability. However, measured values of interfacial elasticity were highly dependent on asphaltene aggregation state. Several experimental techniques was utilised and partly developed for the crude oil characterisation. A high-pressure liquid chromatography (HPLC) scheme was developed for SARA-fractionation of crude oils and an oscillating pendant drop tensiometer was used for characterisation of interfacial rheological properties. For emulsion stability a cell for determining the stability as a function of applied electric fields was used. In addition, near infrared spectroscopy (NIR) was used throughout the work both for chemical and physical characterisation of crude oils and model systems. High pressure NIR was used to study the aggregation of asphaltenes by pressure depletion. A new technique for detection of asphaltene aggregation onset pressures based on NIR combined with PCA was developed. It was also found that asphaltene aggregation is

Automatic determination of moisture content in biofuels based on NIR-measurements; Automatisk fukthaltsbestaemning av biobraenslen med NIR-metoden

Energy Technology Data Exchange (ETDEWEB)

Berg, Magnus; Wiklund, Sven Erik [AaF-Process AB, Stockholm (Sweden); Karlsson, Mikael; Tryzell, Robert [Bestwood AB, Sundbyberg (Sweden)

2005-07-01

The determination of moisture content of biofuel is of large importance for the energy sector. The used methods for moisture determination are based on fuels samples taken from the bulk followed by drying and weighing. To be able to instead determine the moisture content based on a method with good accuracy and with a short response time would be a large improvement. Both for the fuel sampling and the following analysis there are Swedish standards but concerning the fuel sampling the standards are often not followed. The main reason is the difficulties to sample fuel samples from different depth from a delivery. This is one of the reasons that some plants have installed mechanical samplers but the investment cost for these is relatively high. The aim of this project was to investigate the use of the NIR-method for automatic moisture determination in biofuels. Within the project the NIR-method was used to determine the moisture content on withdrawn fuel samples, in addition the possibility to integrate the NIR-method in an automatic sampling system is also described. A large number of samples, in total over 200 samples, have been evaluated with the NIR-method and compared with the reference method, oven drying and gravimetric determination of moisture content. That the NIR-method can be used to determine moisture content in a number of well defined materials have previously been shown. In this report it has moreover been shown that the method can be used under the conditions at the fuel delivery station and for a large spectrum of biofuels. The accuracy that can be achieved with the NIR-method is in the same magnitude as the standard method, i.e. the reference method used for the measurements. Altogether this shows that the NIR-method is an interesting alternative for integration in an automatic measurement system for determination of fuel moisture content in biofuels. To be able to use the NIR-method for automatic determination of fuel moisture content at the

Semi-quantitative prediction of a multiple API solid dosage form with a combination of vibrational spectroscopy methods.

Science.gov (United States)

Hertrampf, A; Sousa, R M; Menezes, J C; Herdling, T

2016-05-30

Quality control (QC) in the pharmaceutical industry is a key activity in ensuring medicines have the required quality, safety and efficacy for their intended use. QC departments at pharmaceutical companies are responsible for all release testing of final products but also all incoming raw materials. Near-infrared spectroscopy (NIRS) and Raman spectroscopy are important techniques for fast and accurate identification and qualification of pharmaceutical samples. Tablets containing two different active pharmaceutical ingredients (API) [bisoprolol, hydrochlorothiazide] in different commercially available dosages were analysed using Raman- and NIR Spectroscopy. The goal was to define multivariate models based on each vibrational spectroscopy to discriminate between different dosages (identity) and predict their dosage (semi-quantitative). Furthermore the combination of spectroscopic techniques was investigated. Therefore, two different multiblock techniques based on PLS have been applied: multiblock PLS (MB-PLS) and sequential-orthogonalised PLS (SO-PLS). NIRS showed better results compared to Raman spectroscopy for both identification and quantitation. The multiblock techniques investigated showed that each spectroscopy contains information not present or captured with the other spectroscopic technique, thus demonstrating that there is a potential benefit in their combined use for both identification and quantitation purposes. Copyright © 2016 Elsevier B.V. All rights reserved.

Comparing predictive ability of laser-induced breakdown spectroscopy to visible near-infrared spectroscopy for soil property determination

DEFF Research Database (Denmark)

Knadel, Maria; Gislum, René; Hermansen, Cecilie

2017-01-01

Soil organic carbon (SOC) and particle size fractions have a practical value for agronomy and the environment. Thus, alternative techniques to replace the expensive conventional analyses of soil are needed. Visible near-infrared reflectance spectroscopy (viseNIRS) has already shown potential...

[Applications and prospects of on-line near infrared spectroscopy technology in manufacturing of Chinese materia medica].

Science.gov (United States)

Li, Yang; Wu, Zhi-Sheng; Pan, Xiao-Ning; Shi, Xin-Yuan; Guo, Ming-Ye; Xu, Bing; Qiao, Yan-Jiang

2014-10-01

The quality of Chinese materia medica (CMM) is affected by every process in CMM manufacturing. According to multi-unit complex features in the production of CMM, on-line near infrared spectroscopy (NIR) is used as an evaluating technology with its rapid, non-destructive and non-pollution etc. advantages. With the research in institutions, the on-line NIR applied in process analysis and control of CMM was described systematically, and the on-line NIR platform building was used as an example to clarify the feasibility of on-line NIR technology in CMM manufacturing process. Then, from the point of application by pharmaceutical companies, the current on-line NIR research on CMM and its production in pharmaceutical companies was relatively comprehensively summarized. Meanwhile, the types of CMM productions were classified in accordance with two formulations (liquid and solid dosage formulations). The different production processes (extraction, concentration and alcohol precipitation, etc. ) were used as liquid formulation diacritical points; the different types (tablets, capsules and plasters, etc.) were used as solid dosage formulation diacritical points, and the reliability of on-line NIR used in the whole process in CMM production was proved in according to the summary of literatures in recent 10 years, which could support the modernization of CMM production.

Near-infrared spectroscopy. Innovative technology summary report

International Nuclear Information System (INIS)

1999-07-01

A near-infrared (NIR) spectroscopy system with a remote fiber-optic probe was developed and demonstrated to measure the water content of high-level radioactive wastes from the underground storage tanks at the Hanford Site in richland Washington. The technology was developed as a cost-effective and safer alternative to the thermogravimetric analysis (TGA) technique in use as the baseline. This work was supported by the Tanks Focus Area (TFA) within the Department of Energy's (DOE) Office of Science and Technology (OST) in cooperation with the Hanford Tank Waste Remediation System (TWRS) Program

Neuroimaging with functional near infrared spectroscopy: From formation to interpretation

Science.gov (United States)

Herrera-Vega, Javier; Treviño-Palacios, Carlos G.; Orihuela-Espina, Felipe

2017-09-01

Functional Near Infrared Spectroscopy (fNIRS) is gaining momentum as a functional neuroimaging modality to investigate the cerebral hemodynamics subsequent to neural metabolism. As other neuroimaging modalities, it is neuroscience's tool to understand brain systems functions at behaviour and cognitive levels. To extract useful knowledge from functional neuroimages it is critical to understand the series of transformations applied during the process of the information retrieval and how they bound the interpretation. This process starts with the irradiation of the head tissues with infrared light to obtain the raw neuroimage and proceeds with computational and statistical analysis revealing hidden associations between pixels intensities and neural activity encoded to end up with the explanation of some particular aspect regarding brain function.To comprehend the overall process involved in fNIRS there is extensive literature addressing each individual step separately. This paper overviews the complete transformation sequence through image formation, reconstruction and analysis to provide an insight of the final functional interpretation.

Comparison of NIRS, laser Doppler flowmetry, photoplethysmography, and pulse oximetry during vascular occlusion challenges

International Nuclear Information System (INIS)

Abay, T Y; Kyriacou, P A

2016-01-01

Monitoring changes in blood volume, blood flow, and oxygenation in tissues is of vital importance in fields such as reconstructive surgery and trauma medicine. Near infrared spectroscopy (NIRS), laser Doppler (LDF) flowmetry, photoplethysmography (PPG), and pulse oximetry (PO) contribute to such fields due to their safe and noninvasive nature. However, the techniques have been rarely investigated simultaneously or altogether. The aim of this study was to investigate all the techniques simultaneously on healthy subjects during vascular occlusion challenges. Sensors were attached on the forearm (NIRS and LDF) and fingers (PPG and PO) of 19 healthy volunteers. Different degrees of vascular occlusion were induced by inflating a pressure cuff on the upper arm. The responses of tissue oxygenation index (NIRS), tissue haemoglobin index (NIRS), flux (LDF), perfusion index (PPG), and arterial oxygen saturation (PO) have been recorded and analyzed. Moreover, the optical densities were calculated from slow varying dc PPG, in order to distinguish changes in venous blood volumes. The indexes showed significant changes (p  <  0.05) in almost all occlusions, either venous or over-systolic occlusions. However, differentiation between venous and arterial occlusion by LDF may be challenging and the perfusion index (PI) may not be adequate to indicate venous occlusions. Optical densities may be an additional tool to detect venous occlusions by PPG. (paper)

Elucidation of the role of biological factors and device design in cerebral NIRS using an in vivo hematoma model based on high-intensity focused ultrasound

Science.gov (United States)

Wang, Jianting; Huang, Stanley; Myers, Matthew; Chen, Yu; Welle, Cristin; Pfefer, Joshua

2016-03-01

Near-Infrared Spectroscopy (NIRS) is an emerging medical countermeasure for rapid, field detection of hematomas caused by traumatic brain injury (TBI). Bench and animal tests to determine NIRS sensitivity and specificity are needed. However, current animal models involving non-invasively induced, localized neural damage are limited. We investigated an in vivo murine hematoma model in which cerebral hemorrhage was induced noninvasively by high-intensity focused ultrasound (HIFU) with calibrated positioning and parameters. To characterize the morphology of induced hematomas, we used skull-intact histological evaluation. A multi-wavelength fiber-optic NIRS system with three source-detector separation distances was used to detect hematoma A 1.1 MHz transducer produced consistent small-to-medium hematoma localized to a single hemisphere, along with bruising of the scalp, with a low mortality rate. A 220 kHz transducer produced larger, more diffuse hematomas, with higher variability in size and a correspondingly higher mortality rate. No skin bruising or blood accumulation between the skin and skull was observed following injury application with the 220 kHz transducer. Histological analysis showed higher sensitivity for larger hematomas (>4x4 mm2). NIRS optical density change after HIFU was able to detect all hematomas, with sensitivity dependent on wavelength and separation distance. While improvements in methods for validating cerebral blood distribution are needed, the HIFU hematoma model provided useful insights that will inform development of biologically relevant, performance test methods for cerebral NIRS systems.

The use of near infrared spectroscopy in the quality control laboratory of the pharmaceutical industry.

Science.gov (United States)

Plugge, W; van der Vlies, C

1992-01-01

The suitability of NIR spectroscopy as an alternative to several compendial test methods is discussed. Using ampicillin trihydrate as an example it is demonstrated that eight quality criteria are controlled by recording the NIR spectrum of a batch sample and calculating its Conformity Index.

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.

Comparison of time-gated surface-enhanced Raman spectroscopy (TG-SERS) and classical SERS based monitoring of Escherichia coli cultivation samples.

Science.gov (United States)

Kögler, Martin; Paul, Andrea; Anane, Emmanuel; Birkholz, Mario; Bunker, Alex; Viitala, Tapani; Maiwald, Michael; Junne, Stefan; Neubauer, Peter

2018-06-08

The application of Raman spectroscopy as a monitoring technique for bioprocesses is severely limited by a large background signal originating from fluorescing compounds in the culture media. Here we compare time-gated Raman (TG-Raman)-, continuous wave NIR-process Raman (NIR-Raman) and continuous wave micro-Raman (micro-Raman) approaches in combination with surface enhanced Raman spectroscopy (SERS) for their potential to overcome this limit. For that purpose, we monitored metabolite concentrations of Escherichia coli bioreactor cultivations in cell-free supernatant samples. We investigated concentration transients of glucose, acetate, AMP and cAMP at alternating substrate availability, from deficiency to excess. Raman and SERS signals were compared to off-line metabolite analysis of carbohydrates, carboxylic acids and nucleotides. Results demonstrate that SERS, in almost all cases, led to a higher number of identifiable signals and better resolved spectra. Spectra derived from the TG-Raman were comparable to those of micro-Raman resulting in well-discernable Raman peaks, which allowed for the identification of a higher number of compounds. In contrast, NIR-Raman provided a superior performance for the quantitative evaluation of analytes, both with and without SERS nanoparticles when using multivariate data analysis. This article is protected by copyright. All rights reserved. © 2018 American Institute of Chemical Engineers.

Commentary on the statistical properties of noise and its implication on general linear models in functional near-infrared spectroscopy.

Science.gov (United States)

Huppert, Theodore J

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low levels of light to measure changes in cerebral blood oxygenation levels. In the majority of NIRS functional brain studies, analysis of this data is based on a statistical comparison of hemodynamic levels between a baseline and task or between multiple task conditions by means of a linear regression model: the so-called general linear model. Although these methods are similar to their implementation in other fields, particularly for functional magnetic resonance imaging, the specific application of these methods in fNIRS research differs in several key ways related to the sources of noise and artifacts unique to fNIRS. In this brief communication, we discuss the application of linear regression models in fNIRS and the modifications needed to generalize these models in order to deal with structured (colored) noise due to systemic physiology and noise heteroscedasticity due to motion artifacts. The objective of this work is to present an overview of these noise properties in the context of the linear model as it applies to fNIRS data. This work is aimed at explaining these mathematical issues to the general fNIRS experimental researcher but is not intended to be a complete mathematical treatment of these concepts.

Decoding human mental states by whole-head EEG+fNIRS during category fluency task performance

Science.gov (United States)

Omurtag, Ahmet; Aghajani, Haleh; Onur Keles, Hasan

2017-12-01

Objective. Concurrent scalp electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), which we refer to as EEG+fNIRS, promises greater accuracy than the individual modalities while remaining nearly as convenient as EEG. We sought to quantify the hybrid system’s ability to decode mental states and compare it with its unimodal components. Approach. We recorded from healthy volunteers taking the category fluency test and applied machine learning techniques to the data. Main results. EEG+fNIRS’s decoding accuracy was greater than that of its subsystems, partly due to the new type of neurovascular features made available by hybrid data. Significance. Availability of an accurate and practical decoding method has potential implications for medical diagnosis, brain-computer interface design, and neuroergonomics.

M3BA: A Mobile, Modular, Multimodal Biosignal Acquisition Architecture for Miniaturized EEG-NIRS-Based Hybrid BCI and Monitoring.

Science.gov (United States)

von Luhmann, Alexander; Wabnitz, Heidrun; Sander, Tilmann; Muller, Klaus-Robert

2017-06-01

For the further development of the fields of telemedicine, neurotechnology, and brain-computer interfaces, advances in hybrid multimodal signal acquisition and processing technology are invaluable. Currently, there are no commonly available hybrid devices combining bioelectrical and biooptical neurophysiological measurements [here electroencephalography (EEG) and functional near-infrared spectroscopy (NIRS)]. Our objective was to design such an instrument in a miniaturized, customizable, and wireless form. We present here the design and evaluation of a mobile, modular, multimodal biosignal acquisition architecture (M3BA) based on a high-performance analog front-end optimized for biopotential acquisition, a microcontroller, and our openNIRS technology. The designed M3BA modules are very small configurable high-precision and low-noise modules (EEG input referred noise @ 500 SPS 1.39 μV pp , NIRS noise equivalent power NEP 750 nm = 5.92 pW pp , and NEP 850 nm = 4.77 pW pp ) with full input linearity, Bluetooth, 3-D accelerometer, and low power consumption. They support flexible user-specified biopotential reference setups and wireless body area/sensor network scenarios. Performance characterization and in-vivo experiments confirmed functionality and quality of the designed architecture. Telemedicine and assistive neurotechnology scenarios will increasingly include wearable multimodal sensors in the future. The M3BA architecture can significantly facilitate future designs for research in these and other fields that rely on customized mobile hybrid biosignal modal biosignal acquisition architecture (M3BA), multimodal, near-infrared spectroscopy (NIRS), wireless body area network (WBAN), wireless body sensor network (WBSN).

Chemical characteristics and mineral composition of quinoa by near-infrared spectroscopy.

Science.gov (United States)

González Martín, M Inmaculada; Wells Moncada, Guillermo; Fischer, Susana; Escuredo, Olga

2014-03-30

Quinoa (Chenopodium quinoa Willd.) has been traditionally used as a foodstuff in the Andes and it has gained increasing interest in recent years owing to its high nutritional value. The potential of near-infrared spectroscopy (NIRS) for estimating chemical compounds in quinoa was studied because of the possibility of conducting direct measurement without prior sample treatment. The use of NIRS technology with a remote reflectance fiber-optic probe for the analysis of major compounds and mineral composition of 48 quinoa samples was studied. The calibration of the NIRS instrument was conducted using modified partial least squares (MPLS) analysis. This allowed the determination of protein (16.0-20.2 g 100g⁻¹), crude fiber (1.8-3.1 g 100g⁻¹), fat (4.4-7.5 g 100g⁻¹), calcium (298.8-1164.5 mg kg⁻¹), iron (0-948.5 mg kg⁻¹) and phosphorus (2735.0-4543.3 mg kg⁻¹). The correlation coefficients (RSQ) were 0.83 for protein, 0.73 for crude fiber, 0.93 for fat; 0.60 for calcium; 0.76 for iron and 0.75 for phosphorus. The robustness of the equations obtained was verified by external validation on unknown quinoa samples. NIRS with fiber-optic probe provides an alternative for the determination of chemical compounds of quinoa, faster and at lower cost, with results comparable with chemical methods. © 2013 Society of Chemical Industry.

Multivariate Calibration Models for Sorghum Composition using Near-Infrared Spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Wolfrum, E.; Payne, C.; Stefaniak, T.; Rooney, W.; Dighe, N.; Bean, B.; Dahlberg, J.

2013-03-01

NREL developed calibration models based on near-infrared (NIR) spectroscopy coupled with multivariate statistics to predict compositional properties relevant to cellulosic biofuels production for a variety of sorghum cultivars. A robust calibration population was developed in an iterative fashion. The quality of models developed using the same sample geometry on two different types of NIR spectrometers and two different sample geometries on the same spectrometer did not vary greatly.

Challenging Near InfraRed Spectroscopy discriminating ability for counterfeit pharmaceuticals detection

Energy Technology Data Exchange (ETDEWEB)

Storme-Paris, I. [Groupe de Chimie Analytique de Paris-Sud, EA 4041, IFR 141, School of Pharmacy, Univ Paris-Sud, 5 rue Jean Baptiste Clement, 92296 Chatenay-Malabry (France); Rebiere, H. [Laboratories and Control Department, French Health Products Safety Agency (AFSSAPS), 635 rue de la Garenne, 34740 Vendargues (France); Matoga, M. [Groupe de Chimie Analytique de Paris-Sud, EA 4041, IFR 141, School of Pharmacy, Univ Paris-Sud, 5 rue Jean Baptiste Clement, 92296 Chatenay-Malabry (France); Civade, C.; Bonnet, P.-A.; Tissier, M.H. [Laboratories and Control Department, French Health Products Safety Agency (AFSSAPS), 635 rue de la Garenne, 34740 Vendargues (France); Chaminade, P., E-mail: pierre.chaminade@u-psud.fr [Groupe de Chimie Analytique de Paris-Sud, EA 4041, IFR 141, School of Pharmacy, Univ Paris-Sud, 5 rue Jean Baptiste Clement, 92296 Chatenay-Malabry (France)

2010-01-25

This study was initiated by the laboratories and control department of the French Health Products Safety Agency (AFSSAPS) as part of the fight against the public health problem of rising counterfeit and imitation medicines. To test the discriminating ability of Near InfraRed Spectroscopy (NIRS), worse cases scenarios were first considered for the discrimination of various pharmaceutical final products containing the same Active Pharmaceutical Ingredient (API) with different excipients, such as generics of proprietary medicinal products (PMP). Two generic databases were explored: low active strength hard capsules of Fluoxetine and high strength tablets of Ciprofloxacin. Then 4 other cases involving suspicious samples, counterfeits and imitations products were treated. In all these cases, spectral differences between samples were studied, giving access to API or excipient contents information, and eventually allowing manufacturing site identification. A chemometric background is developed to explain the optimisation methodology, consisting in the choices of appropriate pretreatments, algorithms for data exploratory analyses (unsupervised Principal Component Analysis), and data classification (supervised cluster analysis, and Soft Independent Modelling of Class Analogy). Results demonstrate the high performance of NIRS, highlighting slight differences in formulations, such as 2.5% (w/w) in API strength, 1.0% (w/w) in excipient and even coating variations (<1%, w/w) with identical contents, approaching the theoretical limits of NIRS sensitivity. All the different generic formulations were correctly discriminated and foreign PMP, constituted of formulations slightly different from the calibration ones, were also all discriminated. This publication addresses the ability of NIRS to detect counterfeits and imitations and presents the NIRS as an ideal tool to master the global threat of counterfeit drugs.

Challenging Near InfraRed Spectroscopy discriminating ability for counterfeit pharmaceuticals detection

International Nuclear Information System (INIS)

Storme-Paris, I.; Rebiere, H.; Matoga, M.; Civade, C.; Bonnet, P.-A.; Tissier, M.H.; Chaminade, P.

2010-01-01

This study was initiated by the laboratories and control department of the French Health Products Safety Agency (AFSSAPS) as part of the fight against the public health problem of rising counterfeit and imitation medicines. To test the discriminating ability of Near InfraRed Spectroscopy (NIRS), worse cases scenarios were first considered for the discrimination of various pharmaceutical final products containing the same Active Pharmaceutical Ingredient (API) with different excipients, such as generics of proprietary medicinal products (PMP). Two generic databases were explored: low active strength hard capsules of Fluoxetine and high strength tablets of Ciprofloxacin. Then 4 other cases involving suspicious samples, counterfeits and imitations products were treated. In all these cases, spectral differences between samples were studied, giving access to API or excipient contents information, and eventually allowing manufacturing site identification. A chemometric background is developed to explain the optimisation methodology, consisting in the choices of appropriate pretreatments, algorithms for data exploratory analyses (unsupervised Principal Component Analysis), and data classification (supervised cluster analysis, and Soft Independent Modelling of Class Analogy). Results demonstrate the high performance of NIRS, highlighting slight differences in formulations, such as 2.5% (w/w) in API strength, 1.0% (w/w) in excipient and even coating variations (<1%, w/w) with identical contents, approaching the theoretical limits of NIRS sensitivity. All the different generic formulations were correctly discriminated and foreign PMP, constituted of formulations slightly different from the calibration ones, were also all discriminated. This publication addresses the ability of NIRS to detect counterfeits and imitations and presents the NIRS as an ideal tool to master the global threat of counterfeit drugs.

Near infrared spectroscopy combined with multivariate analysis for monitoring the ethanol precipitation process of fraction I + II + III supernatant in human albumin separation

Science.gov (United States)

Li, Can; Wang, Fei; Zang, Lixuan; Zang, Hengchang; Alcalà, Manel; Nie, Lei; Wang, Mingyu; Li, Lian

2017-03-01

Nowadays, as a powerful process analytical tool, near infrared spectroscopy (NIRS) has been widely applied in process monitoring. In present work, NIRS combined with multivariate analysis was used to monitor the ethanol precipitation process of fraction I + II + III (FI + II + III) supernatant in human albumin (HA) separation to achieve qualitative and quantitative monitoring at the same time and assure the product's quality. First, a qualitative model was established by using principal component analysis (PCA) with 6 of 8 normal batches samples, and evaluated by the remaining 2 normal batches and 3 abnormal batches. The results showed that the first principal component (PC1) score chart could be successfully used for fault detection and diagnosis. Then, two quantitative models were built with 6 of 8 normal batches to determine the content of the total protein (TP) and HA separately by using partial least squares regression (PLS-R) strategy, and the models were validated by 2 remaining normal batches. The determination coefficient of validation (Rp2), root mean square error of cross validation (RMSECV), root mean square error of prediction (RMSEP) and ratio of performance deviation (RPD) were 0.975, 0.501 g/L, 0.465 g/L and 5.57 for TP, and 0.969, 0.530 g/L, 0.341 g/L and 5.47 for HA, respectively. The results showed that the established models could give a rapid and accurate measurement of the content of TP and HA. The results of this study indicated that NIRS is an effective tool and could be successfully used for qualitative and quantitative monitoring the ethanol precipitation process of FI + II + III supernatant simultaneously. This research has significant reference value for assuring the quality and improving the recovery ratio of HA in industrialization scale by using NIRS.

Near infrared spectroscopy combined with multivariate analysis for monitoring the ethanol precipitation process of fraction I+II+III supernatant in human albumin separation.

Science.gov (United States)

Li, Can; Wang, Fei; Zang, Lixuan; Zang, Hengchang; Alcalà, Manel; Nie, Lei; Wang, Mingyu; Li, Lian

2017-03-15

Nowadays, as a powerful process analytical tool, near infrared spectroscopy (NIRS) has been widely applied in process monitoring. In present work, NIRS combined with multivariate analysis was used to monitor the ethanol precipitation process of fraction I+II+III (FI+II+III) supernatant in human albumin (HA) separation to achieve qualitative and quantitative monitoring at the same time and assure the product's quality. First, a qualitative model was established by using principal component analysis (PCA) with 6 of 8 normal batches samples, and evaluated by the remaining 2 normal batches and 3 abnormal batches. The results showed that the first principal component (PC1) score chart could be successfully used for fault detection and diagnosis. Then, two quantitative models were built with 6 of 8 normal batches to determine the content of the total protein (TP) and HA separately by using partial least squares regression (PLS-R) strategy, and the models were validated by 2 remaining normal batches. The determination coefficient of validation (R p 2 ), root mean square error of cross validation (RMSECV), root mean square error of prediction (RMSEP) and ratio of performance deviation (RPD) were 0.975, 0.501g/L, 0.465g/L and 5.57 for TP, and 0.969, 0.530g/L, 0.341g/L and 5.47 for HA, respectively. The results showed that the established models could give a rapid and accurate measurement of the content of TP and HA. The results of this study indicated that NIRS is an effective tool and could be successfully used for qualitative and quantitative monitoring the ethanol precipitation process of FI+II+III supernatant simultaneously. This research has significant reference value for assuring the quality and improving the recovery ratio of HA in industrialization scale by using NIRS. Copyright © 2016 Elsevier B.V. All rights reserved.

Do radio frequencies of medical instruments common in the operating room interfere with near-infrared spectroscopy signals?

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Shadgan, Babak; Molavi, Behnam; Reid, W. D.; Dumont, Guy; Macnab, Andrew J.

2010-02-01

Background: Medical and diagnostic applications of near infrared spectroscopy (NIRS) are increasing, especially in operating rooms (OR). Since NIRS is an optical technique, radio frequency (RF) interference from other instruments is unlikely to affect the raw optical data, however, NIRS data processing and signal output could be affected. Methods: We investigated the potential for three common OR instruments: an electrical cautery, an orthopaedic drill and an imaging system, to generate electromagnetic interference (EMI) that could potentially influence NIRS signals. The time of onset and duration of every operation of each device was recorded during surgery. To remove the effects of slow changing physiological variables, we first used a lowpass filter and then selected 2 windows with variable lengths around the moment of device onset. For each instant, variances (energy) and means of the signals in the 2 windows were compared. Results: Twenty patients were studied during ankle surgery. Analysis shows no statistically significant difference in the means and variance of the NIRS signals (p < 0.01) during operation of any of the three devices for all surgeries. Conclusion: This method confirms the instruments evaluated caused no significant interference. NIRS can potentially be used without EMI in clinical environments such as the OR.

Evaluation of light detector surface area for functional Near Infrared Spectroscopy.

Science.gov (United States)

Wang, Lei; Ayaz, Hasan; Izzetoglu, Meltem; Onaral, Banu

2017-10-01

Functional Near Infrared Spectroscopy (fNIRS) is an emerging neuroimaging technique that utilizes near infrared light to detect cortical concentration changes of oxy-hemoglobin and deoxy-hemoglobin non-invasively. Using light sources and detectors over the scalp, multi-wavelength light intensities are recorded as time series and converted to concentration changes of hemoglobin via modified Beer-Lambert law. Here, we describe a potential source for systematic error in the calculation of hemoglobin changes and light intensity measurements. Previous system characterization and analysis studies looked into various fNIRS parameters such as type of light source, number and selection of wavelengths, distance between light source and detector. In this study, we have analyzed the contribution of light detector surface area to the overall outcome. Results from Monte Carlo based digital phantoms indicated that selection of detector area is a critical system parameter in minimizing the error in concentration calculations. The findings here can guide the design of future fNIRS sensors. Copyright © 2017 Elsevier Ltd. All rights reserved.

Methodology for cork plank characterization (Quercus suber L.) by near-infrared spectroscopy and image analysis

Science.gov (United States)

Prades, Cristina; García-Olmo, Juan; Romero-Prieto, Tomás; García de Ceca, José L.; López-Luque, Rafael

2010-06-01

The procedures used today to characterize cork plank for the manufacture of cork bottle stoppers continue to be based on a traditional, manual method that is highly subjective. Furthermore, there is no specific legislation regarding cork classification. The objective of this viability study is to assess the potential of near-infrared spectroscopy (NIRS) technology for characterizing cork plank according to the following variables: aspect or visual quality, porosity, moisture and geographical origin. In order to calculate the porosity coefficient, an image analysis program was specifically developed in Visual Basic language for a desktop scanner. A set comprising 170 samples from two geographical areas of Andalusia (Spain) was classified into eight quality classes by visual inspection. Spectra were obtained in the transverse and tangential sections of the cork planks using an NIRSystems 6500 SY II reflectance spectrophotometer. The quantitative calibrations showed cross-validation coefficients of determination of 0.47 for visual quality, 0.69 for porosity and 0.66 for moisture. The results obtained using NIRS technology are promising considering the heterogeneity and variability of a natural product such as cork in spite of the fact that the standard error of cross validation (SECV) in the quantitative analysis is greater than the standard error of laboratory (SEL) for the three variables. The qualitative analysis regarding geographical origin achieved very satisfactory results. Applying these methods in industry will permit quality control procedures to be automated, as well as establishing correlations between the different classification systems currently used in the sector. These methods can be implemented in the cork chain of custody certification and will also provide a certainly more objective tool for assessing the economic value of the product.

Methodology for cork plank characterization (Quercus suber L.) by near-infrared spectroscopy and image analysis