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

PubMed Central

Via, Brian K.; Fasina, Oladiran O.; Adhikari, Sushil; Billor, Nedret; Eckhardt, Lori G.

2017-01-01

The objective of this study was to investigated the use of chemometric modeling of thermogravimetric (TG) data as an alternative approach to estimate the chemical and proximate (i.e. volatile matter, fixed carbon and ash contents) composition of lignocellulosic biomass. Since these properties affect the conversion pathway, processing costs, yield and / or quality of products, a capability to rapidly determine these for biomass feedstock entering the process stream will be useful in the success and efficiency of bioconversion technologies. The 38-minute long methodology developed in this study enabled the simultaneous prediction of both the chemical and proximate properties of forest-derived biomass from the same TG data. Conventionally, two separate experiments had to be conducted to obtain such information. In addition, the chemometric models constructed with normalized TG data outperformed models developed via the traditional deconvolution of TG data. PLS and PCR models were especially robust in predicting the volatile matter (R2–0.92; RPD– 3.58) and lignin (R2–0.82; RPD– 2.40) contents of the biomass. The application of chemometrics to TG data also made it possible to predict some monomeric sugars in this study. Elucidation of PC loadings obtained from chemometric models also provided some insights into the thermal decomposition behavior of the chemical constituents of lignocellulosic biomass. For instance, similar loadings were noted for volatile matter and cellulose, and for fixed carbon and lignin. The findings indicate that common latent variables are shared between these chemical and thermal reactivity properties. Results from this study buttresses literature that have reported that the less thermally stable polysaccharides are responsible for the yield of volatiles whereas the more recalcitrant lignin with its higher percentage of elementary carbon contributes to the yield of fixed carbon. PMID:28253322

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

PubMed

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

2017-01-01

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

Tracking diffusion of conditioning water in single wheat kernels of different hardnesses by near infrared hyperspectral imaging.

PubMed

Manley, Marena; du Toit, Gerida; Geladi, Paul

2011-02-07

The combination of near infrared (NIR) hyperspectral imaging and chemometrics was used to follow the diffusion of conditioning water over time in wheat kernels of different hardnesses. Conditioning was attempted with deionised water (dH(2)O) and deuterium oxide (D(2)O). The images were recorded at different conditioning times (0-36 h) from 1000 to 2498 nm with a line scan imaging system. After multivariate cleaning and spectral pre-processing (either multiplicative scatter correction or standard normal variate and Savitzky-Golay smoothing) six principal components (PCs) were calculated. These were studied visually interactively as score images and score plots. As no clear clusters were present in the score plots, changes in the score plots were investigated by means of classification gradients made within the respective PCs. Classes were selected in the direction of a PC (from positive to negative or negative to positive score values) in almost equal segments. Subsequently loading line plots were used to provide a spectroscopic explanation of the classification gradients. It was shown that the first PC explained kernel curvature. PC3 was shown to be related to a moisture-starch contrast and could explain the progress of water uptake. The positive influence of protein was also observed. The behaviour of soft, hard and very hard kernels was different in this respect, with the uptake of water observed much earlier in the soft kernels than in the harder ones. The harder kernels also showed a stronger influence of protein in the loading line plots. Difference spectra showed interpretable changes over time for water but not for D(2)O which had a too low signal in the wavelength range used. NIR hyperspectral imaging together with exploratory chemometrics, as detailed in this paper, may have wider applications than merely conditioning studies. Copyright © 2010 Elsevier B.V. All rights reserved.

THE NIST-EPA INTERAGENCY AGREEMENT ON MEASUREMENTS AND STANDARDS IN AEROSOL CARBON: SAMPLING REGIONAL PM 2.5 FOR THE CHEMOMETRIC OPTIMIZATION OF THERMAL-OPTICAL ANALYSIS

EPA Science Inventory

Results from the NIST-EPA Interagency Agreement on Measurements and Standards in Aerosol Carbon: Sampling Regional PM2.5 for the Chemometric Optimization of Thermal-Optical Analysis Study will be presented at the American Association for Aerosol Research (AAAR) 24th Annual Confer...

Comparative Chemometric Analysis for Classification of Acids and Bases via a Colorimetric Sensor Array.

PubMed

Kangas, Michael J; Burks, Raychelle M; Atwater, Jordyn; Lukowicz, Rachel M; Garver, Billy; Holmes, Andrea E

2018-02-01

With the increasing availability of digital imaging devices, colorimetric sensor arrays are rapidly becoming a simple, yet effective tool for the identification and quantification of various analytes. Colorimetric arrays utilize colorimetric data from many colorimetric sensors, with the multidimensional nature of the resulting data necessitating the use of chemometric analysis. Herein, an 8 sensor colorimetric array was used to analyze select acid and basic samples (0.5 - 10 M) to determine which chemometric methods are best suited for classification quantification of analytes within clusters. PCA, HCA, and LDA were used to visualize the data set. All three methods showed well-separated clusters for each of the acid or base analytes and moderate separation between analyte concentrations, indicating that the sensor array can be used to identify and quantify samples. Furthermore, PCA could be used to determine which sensors showed the most effective analyte identification. LDA, KNN, and HQI were used for identification of analyte and concentration. HQI and KNN could be used to correctly identify the analytes in all cases, while LDA correctly identified 95 of 96 analytes correctly. Additional studies demonstrated that controlling for solvent and image effects was unnecessary for all chemometric methods utilized in this study.

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

PubMed

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

2007-01-01

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

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

PubMed

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

2011-03-04

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

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

PubMed

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

2006-09-15

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

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

PubMed

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

2017-01-01

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

Selection of quantum chemical descriptors by chemometric methods in the study of antioxidant activity of flavonoid compounds

NASA Astrophysics Data System (ADS)

Weber, K. C.; Honório, K. M.; da Silva, S. L.; Mercadante, R.; da Silva, A. B. F.

In the present study, the aim was to select electronic properties responsible for free radical scavenging ability of a set of 25 flavonoid compounds employing chemometric methods. Electronic parameters were calculated using the AM1 semiempirical method, and chemometric methods (principal component analysis, hierarchical cluster analysis, and k-nearest neighbor) were used with the aim to build models able to find relationships between electronic features and the antioxidant activity presented by the compounds studied. According to these models, four electronic variables can be considered important to discriminate more and less antioxidant flavonoid compounds: polarizability (α), charge at carbon 3 (QC3), total charge at substituent 5 (QS5), and total charge at substituent 3' (QS3'). The features found as being responsible for the antioxidant activity of the flavonoid compounds studied are consistent with previous results found in the literature. The results obtained can also bring improvements in the search for better antioxidant flavonoid compounds.

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

PubMed

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

2014-01-01

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

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

PubMed

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

2016-05-15

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

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

PubMed

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

2016-11-17

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

Chemometrics.

ERIC Educational Resources Information Center

Kowalski, Bruce R.

1980-01-01

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

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

Kurniawati, Endah; Rohman, Abdul; Triyana, Kuwat

2014-01-01

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

Investigation of production method, geographical origin and species authentication in commercially relevant shrimps using stable isotope ratio and/or multi-element analyses combined with chemometrics: an exploratory analysis.

PubMed

Ortea, Ignacio; Gallardo, José M

2015-03-01

Three factors defining the traceability of a food product are production method (wild or farmed), geographical origin and biological species, which have to be checked and guaranteed, not only in order to avoid mislabelling and commercial fraud, but also to address food safety issues and to comply with legal regulations. The aim of this study was to determine whether these three factors could be differentiated in shrimps using stable isotope ratio analysis of carbon and nitrogen and/or multi-element composition. Different multivariate statistics methods were applied to different data subsets in order to evaluate their performance in terms of classification or predictive ability. Although the success rates varied depending on the dataset used, the combination of both techniques allowed the correct classification of 100% of the samples according to their actual origin and method of production, and 93.5% according to biological species. Even though further studies including a larger number of samples in each group are needed in order to validate these findings, we can conclude that these methodologies should be considered for studies regarding seafood product authenticity. Copyright © 2014 Elsevier Ltd. All rights reserved.

Classification of smoke tainted wines using mid-infrared spectroscopy and chemometrics.

PubMed

Fudge, Anthea L; Wilkinson, Kerry L; Ristic, Renata; Cozzolino, Daniel

2012-01-11

In this study, the suitability of mid-infrared (MIR) spectroscopy, combined with principal component analysis (PCA) and linear discriminant analysis (LDA), was evaluated as a rapid analytical technique to identify smoke tainted wines. Control (i.e., unsmoked) and smoke-affected wines (260 in total) from experimental and commercial sources were analyzed by MIR spectroscopy and chemometrics. The concentrations of guaiacol and 4-methylguaiacol were also determined using gas chromatography-mass spectrometry (GC-MS), as markers of smoke taint. LDA models correctly classified 61% of control wines and 70% of smoke-affected wines. Classification rates were found to be influenced by the extent of smoke taint (based on GC-MS and informal sensory assessment), as well as qualitative differences in wine composition due to grape variety and oak maturation. Overall, the potential application of MIR spectroscopy combined with chemometrics as a rapid analytical technique for screening smoke-affected wines was demonstrated.

Discrimination of genetically modified sugar beets based on terahertz spectroscopy

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

Chemometrics.

ERIC Educational Resources Information Center

Delaney, Michael F.

1984-01-01

This literature review on chemometrics (covering December 1981 to December 1983) is organized under these headings: personal supermicrocomputers; education and books; statistics; modeling and parameter estimation; resolution; calibration; signal processing; image analysis; factor analysis; pattern recognition; optimization; artificial…

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

PubMed Central

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

2016-01-01

Background. Olive oils (OOs) show high chemical variability due to several factors of genetic, environmental and anthropic types. Genetic and environmental factors are responsible for natural compositions and polymorphic diversification resulting in different varietal patterns and phenotypes. Anthropic factors, however, are at the origin of different blends’ preparation leading to normative, labelled or adulterated commercial products. Control of complex OO samples requires their (i) characterization by specific markers; (ii) authentication by fingerprint patterns; and (iii) monitoring by traceability analysis. Methods. These quality control and management aims require the use of several multivariate statistical tools: specificity highlighting requires ordination methods; authentication checking calls for classification and pattern recognition methods; traceability analysis implies the use of network-based approaches able to separate or extract mixed information and memorized signals from complex matrices. Results. This chapter presents a review of different chemometrics methods applied for the control of OO variability from metabolic and physical-chemical measured characteristics. The different chemometrics methods are illustrated by different study cases on monovarietal and blended OO originated from different countries. Conclusion. Chemometrics tools offer multiple ways for quantitative evaluations and qualitative control of complex chemical variability of OO in relation to several intrinsic and extrinsic factors. PMID:28231172

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

PubMed Central

Retnaningtyas, Yuni; Nuri; Lukman, Hilmia

2016-01-01

Infrared (IR) spectroscopy combined with chemometrics has been developed for simple analysis of flavonoid in the medicinal plant extract. Flavonoid was extracted from medicinal plant leaves by ultrasonication and maceration. IR spectra of selected medicinal plant extract were correlated with flavonoid content using chemometrics. The chemometric method used for calibration analysis was Partial Last Square (PLS) and the methods used for classification analysis were Linear Discriminant Analysis (LDA), Soft Independent Modelling of Class Analogies (SIMCA), and Support Vector Machines (SVM). In this study, the calibration of NIR model that showed best calibration with R 2 and RMSEC value was 0.9916499 and 2.1521897, respectively, while the accuracy of all classification models (LDA, SIMCA, and SVM) was 100%. R 2 and RMSEC of calibration of FTIR model were 0.8653689 and 8.8958149, respectively, while the accuracy of LDA, SIMCA, and SVM was 86.0%, 91.2%, and 77.3%, respectively. PLS and LDA of NIR models were further used to predict unknown flavonoid content in commercial samples. Using these models, the significance of flavonoid content that has been measured by NIR and UV-Vis spectrophotometry was evaluated with paired samples t-test. The flavonoid content that has been measured with both methods gave no significant difference. PMID:27529051

A screening method based on UV-Visible spectroscopy and multivariate analysis to assess addition of filler juices and water to pomegranate juices.

PubMed

Boggia, Raffaella; Casolino, Maria Chiara; Hysenaj, Vilma; Oliveri, Paolo; Zunin, Paola

2013-10-15

Consumer demand for pomegranate juice has considerably grown, during the last years, for its potential health benefits. Since it is an expensive functional food, cheaper fruit juices addition (i.e., grape and apple juices) or its simple dilution, or polyphenols subtraction are deceptively used. At present, time-consuming analyses are used to control the quality of this product. Furthermore these analyses are expensive and require well-trained analysts. Thus, the purpose of this study was to propose a high-speed and easy-to-use shortcut. Based on UV-VIS spectroscopy and chemometrics, a screening method is proposed to quickly screening some common fillers of pomegranate juice that could decrease the antiradical scavenging capacity of pure products. The analytical method was applied to laboratory prepared juices, to commercial juices and to representative experimental mixtures at different levels of water and filler juices. The outcomes were evaluated by means of multivariate exploratory analysis. The results indicate that the proposed strategy can be a useful screening tool to assess addition of filler juices and water to pomegranate juices. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

PubMed

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

2015-06-01

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

Rapid detection of Listeria monocytogenes in milk using confocal micro-Raman spectroscopy and chemometric analysis.

PubMed

Wang, Junping; Xie, Xinfang; Feng, Jinsong; Chen, Jessica C; Du, Xin-jun; Luo, Jiangzhao; Lu, Xiaonan; Wang, Shuo

2015-07-02

Listeria monocytogenes is a facultatively anaerobic, Gram-positive, rod-shape foodborne bacterium causing invasive infection, listeriosis, in susceptible populations. Rapid and high-throughput detection of this pathogen in dairy products is critical as milk and other dairy products have been implicated as food vehicles in several outbreaks. Here we evaluated confocal micro-Raman spectroscopy (785 nm laser) coupled with chemometric analysis to distinguish six closely related Listeria species, including L. monocytogenes, in both liquid media and milk. Raman spectra of different Listeria species and other bacteria (i.e., Staphylococcus aureus, Salmonella enterica and Escherichia coli) were collected to create two independent databases for detection in media and milk, respectively. Unsupervised chemometric models including principal component analysis and hierarchical cluster analysis were applied to differentiate L. monocytogenes from Listeria and other bacteria. To further evaluate the performance and reliability of unsupervised chemometric analyses, supervised chemometrics were performed, including two discriminant analyses (DA) and soft independent modeling of class analogies (SIMCA). By analyzing Raman spectra via two DA-based chemometric models, average identification accuracies of 97.78% and 98.33% for L. monocytogenes in media, and 95.28% and 96.11% in milk were obtained, respectively. SIMCA analysis also resulted in satisfied average classification accuracies (over 93% in both media and milk). This Raman spectroscopic-based detection of L. monocytogenes in media and milk can be finished within a few hours and requires no extensive sample preparation. Copyright © 2015 Elsevier B.V. All rights reserved.

Fourier transform infrared spectroscopy and chemometrics for the characterization and discrimination of writing/photocopier paper types: Application in forensic document examinations

NASA Astrophysics Data System (ADS)

Kumar, Raj; Kumar, Vinay; Sharma, Vishal

2017-01-01

The aim of the present work is to explore the non-destructive application of ATR-FTIR technique for characterization and discrimination of paper samples which could be helpful to give forensic aid in resolving legal cases. Twenty-four types of paper brands were purchased from local market in and around Chandigarh, India. All the paper samples were subjected to ATR-FTIR analysis from 400 to 4000 cm- 1 wavenumber range. The qualitative feature and Chemometrics of the obtained spectral data are used for characterization and discrimination. Characterization is achieved by matching the peaks with standards of cellulose and inorganic fillers, a usual constituents of paper. Three different regions of IR, i.e. 400-2000 cm- 1, 2000-4000 cm- 1 and 400-4000 cm- 1 were selected for differentiation by Chemometrics analysis. The discrimination is achieved on the basis of three principal components, i.e. PC 1, PC 2 and PC 3. It is observed that maximum discrimination was procured in the wave number range of i.e. 2000-4000 cm- 1. Discriminating power was calculated on the basis of qualitative features as well, and it is found that the discrimination of paper samples was better achieved by Chemometrics analysis rather than qualitative features. The discriminating power by Chemometrics is 99.64% and which is larger as ever achieved by any group for present number of samples. The present result confirms that this study will be highly useful in forensic document examination work in the legal cases, where the authenticity of the document is challenged. The results are completely analytical and, therefore, overcome the problem encounter in traditional routine light/radiation scanning methods which are still in practice by various questioned document laboratories.

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

PubMed

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

2016-03-24

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

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

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

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

PubMed

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

2015-10-21

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

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

PubMed

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

2015-12-01

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

Detection of Genetically Modified Sugarcane by Using Terahertz Spectroscopy and Chemometrics

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

PubMed

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

2018-05-01

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

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

PubMed

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

2014-09-12

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

Nondestructive determination of transgenic Bacillus thuringiensis rice seeds (Oryza sativa L.) using multispectral imaging and chemometric methods.

PubMed

Liu, Changhong; Liu, Wei; Lu, Xuzhong; Chen, Wei; Yang, Jianbo; Zheng, Lei

2014-06-15

Crop-to-crop transgene flow may affect the seed purity of non-transgenic rice varieties, resulting in unwanted biosafety consequences. The feasibility of a rapid and nondestructive determination of transgenic rice seeds from its non-transgenic counterparts was examined by using multispectral imaging system combined with chemometric data analysis. Principal component analysis (PCA), partial least squares discriminant analysis (PLSDA), least squares-support vector machines (LS-SVM), and PCA-back propagation neural network (PCA-BPNN) methods were applied to classify rice seeds according to their genetic origins. The results demonstrated that clear differences between non-transgenic and transgenic rice seeds could be easily visualized with the nondestructive determination method developed through this study and an excellent classification (up to 100% with LS-SVM model) can be achieved. It is concluded that multispectral imaging together with chemometric data analysis is a promising technique to identify transgenic rice seeds with high efficiency, providing bright prospects for future applications. Copyright © 2013 Elsevier Ltd. All rights reserved.

Partial least-squares with residual bilinearization for the spectrofluorimetric determination of pesticides. A solution of the problems of inner-filter effects and matrix interferents.

PubMed

Piccirilli, Gisela N; Escandar, Graciela M

2006-09-01

This paper demonstrates for the first time the power of a chemometric second-order algorithm for predicting, in a simple way and using spectrofluorimetric data, the concentration of analytes in the presence of both the inner-filter effect and unsuspected species. The simultaneous determination of the systemic fungicides carbendazim and thiabendazole was achieved and employed for the discussion of the scopes of the applied second-order chemometric tools: parallel factor analysis (PARAFAC) and partial least-squares with residual bilinearization (PLS/RBL). The chemometric study was performed using fluorescence excitation-emission matrices obtained after the extraction of the analytes over a C18-membrane surface. The ability of PLS/RBL to recognize and overcome the significant changes produced by thiabendazole in both the excitation and emission spectra of carbendazim is demonstrated. The high performance of the selected PLS/RBL method was established with the determination of both pesticides in artificial and real samples.

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

PubMed

Tauler, Roma; Parastar, Hadi

2018-03-23

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

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

PubMed

Han, Sheng-Nan

2014-07-01

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

Rapid classification of heavy metal-exposed freshwater bacteria by infrared spectroscopy coupled with chemometrics using supervised method

NASA Astrophysics Data System (ADS)

Gurbanov, Rafig; Gozen, Ayse Gul; Severcan, Feride

2018-01-01

Rapid, cost-effective, sensitive and accurate methodologies to classify bacteria are still in the process of development. The major drawbacks of standard microbiological, molecular and immunological techniques call for the possible usage of infrared (IR) spectroscopy based supervised chemometric techniques. Previous applications of IR based chemometric methods have demonstrated outstanding findings in the classification of bacteria. Therefore, we have exploited an IR spectroscopy based chemometrics using supervised method namely Soft Independent Modeling of Class Analogy (SIMCA) technique for the first time to classify heavy metal-exposed bacteria to be used in the selection of suitable bacteria to evaluate their potential for environmental cleanup applications. Herein, we present the powerful differentiation and classification of laboratory strains (Escherichia coli and Staphylococcus aureus) and environmental isolates (Gordonia sp. and Microbacterium oxydans) of bacteria exposed to growth inhibitory concentrations of silver (Ag), cadmium (Cd) and lead (Pb). Our results demonstrated that SIMCA was able to differentiate all heavy metal-exposed and control groups from each other with 95% confidence level. Correct identification of randomly chosen test samples in their corresponding groups and high model distances between the classes were also achieved. We report, for the first time, the success of IR spectroscopy coupled with supervised chemometric technique SIMCA in classification of different bacteria under a given treatment.

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

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

PubMed

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

2018-06-15

A green, simple and cost effective chemometric UV-Vis spectrophotometric method has been developed and validated for correcting interferences that arise during conducting biowaiver studies. Chemometric manipulation has been done for enhancing the results of direct absorbance, resulting from very low concentrations (high incidence of background noise interference) of earlier points in the dissolution timing in case of dissolution profile using first and second derivative (D1 & D2) methods and their corresponding Fourier function convoluted methods (D1/FF& D2/FF). The method applied for biowaiver study of Donepezil Hydrochloride (DH) as a representative model was done by comparing two different dosage forms containing 5mg DH per tablet as an application of a developed chemometric method for correcting interferences as well as for the assay and dissolution testing in its tablet dosage form. The results showed that first derivative technique can be used for enhancement of the data in case of low concentration range of DH (1-8μgmL -1 ) in the three different pH dissolution media which were used to estimate the low drug concentrations dissolved at the early points in the biowaiver study. Furthermore, the results showed similarity in phosphate buffer pH6.8 and dissimilarity in the other 2pH media. The method was validated according to ICH guidelines and USP monograph for both assays (HCl of pH1.2) and dissolution study in 3pH media (HCl of pH1.2, acetate buffer of pH4.5 and phosphate buffer of pH6.8). Finally, the assessment of the method greenness was done using two different assessment techniques: National Environmental Method Index label and Eco scale methods. Both techniques ascertained the greenness of the proposed method. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed

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

2016-09-01

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

Fluorescence Spectroscopy for the Monitoring of Food Processes.

PubMed

Ahmad, Muhammad Haseeb; Sahar, Amna; Hitzmann, Bernd

Different analytical techniques have been used to examine the complexity of food samples. Among them, fluorescence spectroscopy cannot be ignored in developing rapid and non-invasive analytical methodologies. It is one of the most sensitive spectroscopic approaches employed in identification, classification, authentication, quantification, and optimization of different parameters during food handling, processing, and storage and uses different chemometric tools. Chemometrics helps to retrieve useful information from spectral data utilized in the characterization of food samples. This contribution discusses in detail the potential of fluorescence spectroscopy of different foods, such as dairy, meat, fish, eggs, edible oil, cereals, fruit, vegetables, etc., for qualitative and quantitative analysis with different chemometric approaches.

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

PubMed

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

2018-02-01

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

Non-destructive Measurement of Total Carotenoid Content in Processed Tomato Products: Infrared Lock-In Thermography, Near-Infrared Spectroscopy/Chemometrics, and Condensed Phase Laser-Based Photoacoustics—Pilot Study

NASA Astrophysics Data System (ADS)

Bicanic, D.; Streza, M.; Dóka, O.; Valinger, D.; Luterotti, S.; Ajtony, Zs.; Kurtanjek, Z.; Dadarlat, D.

2015-09-01

Carotenes found in a diversity of fruits and vegetables are among important natural antioxidants. In a study described in this paper, the total carotenoid content (TCC) in seven different products derived from thermally processed tomatoes was determined using laser photoacoustic spectroscopy (LPAS), infrared lock-in thermography (IRLIT), and near-infrared spectroscopy (NIRS) combined with chemometrics. Results were verified versus data obtained by traditional VIS spectrophotometry (SP) that served as a reference technique. Unlike SP, the IRLIT, NIRS, and LPAS require a minimum of sample preparation which enables practically direct quantification of the TCC.

Fourier transform infrared spectroscopy and chemometrics for the characterization and discrimination of writing/photocopier paper types: Application in forensic document examinations.

PubMed

Kumar, Raj; Kumar, Vinay; Sharma, Vishal

2017-01-05

The aim of the present work is to explore the non-destructive application of ATR-FTIR technique for characterization and discrimination of paper samples which could be helpful to give forensic aid in resolving legal cases. Twenty-four types of paper brands were purchased from local market in and around Chandigarh, India. All the paper samples were subjected to ATR-FTIR analysis from 400 to 4000cm(-1) wavenumber range. The qualitative feature and Chemometrics of the obtained spectral data are used for characterization and discrimination. Characterization is achieved by matching the peaks with standards of cellulose and inorganic fillers, a usual constituents of paper. Three different regions of IR, i.e. 400-2000cm(-1), 2000-4000cm(-1) and 400-4000cm(-1) were selected for differentiation by Chemometrics analysis. The discrimination is achieved on the basis of three principal components, i.e. PC 1, PC 2 and PC 3. It is observed that maximum discrimination was procured in the wave number range of i.e. 2000-4000cm(-1). Discriminating power was calculated on the basis of qualitative features as well, and it is found that the discrimination of paper samples was better achieved by Chemometrics analysis rather than qualitative features. The discriminating power by Chemometrics is 99.64% and which is larger as ever achieved by any group for present number of samples. The present result confirms that this study will be highly useful in forensic document examination work in the legal cases, where the authenticity of the document is challenged. The results are completely analytical and, therefore, overcome the problem encounter in traditional routine light/radiation scanning methods which are still in practice by various questioned document laboratories. Copyright © 2016 Elsevier B.V. All rights reserved.

Chemometric classification of casework arson samples based on gasoline content.

PubMed

Sinkov, Nikolai A; Sandercock, P Mark L; Harynuk, James J

2014-02-01

Detection and identification of ignitable liquids (ILs) in arson debris is a critical part of arson investigations. The challenge of this task is due to the complex and unpredictable chemical nature of arson debris, which also contains pyrolysis products from the fire. ILs, most commonly gasoline, are complex chemical mixtures containing hundreds of compounds that will be consumed or otherwise weathered by the fire to varying extents depending on factors such as temperature, air flow, the surface on which IL was placed, etc. While methods such as ASTM E-1618 are effective, data interpretation can be a costly bottleneck in the analytical process for some laboratories. In this study, we address this issue through the application of chemometric tools. Prior to the application of chemometric tools such as PLS-DA and SIMCA, issues of chromatographic alignment and variable selection need to be addressed. Here we use an alignment strategy based on a ladder consisting of perdeuterated n-alkanes. Variable selection and model optimization was automated using a hybrid backward elimination (BE) and forward selection (FS) approach guided by the cluster resolution (CR) metric. In this work, we demonstrate the automated construction, optimization, and application of chemometric tools to casework arson data. The resulting PLS-DA and SIMCA classification models, trained with 165 training set samples, have provided classification of 55 validation set samples based on gasoline content with 100% specificity and sensitivity. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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

USDA-ARS?s Scientific Manuscript database

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

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

USDA-ARS?s Scientific Manuscript database

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

Development and Validation of Chemometric Spectrophotometric Methods for Simultaneous Determination of Simvastatin and Nicotinic Acid in Binary Combinations.

PubMed

Alahmad, Shoeb; Elfatatry, Hamed M; Mabrouk, Mokhtar M; Hammad, Sherin F; Mansour, Fotouh R

2018-01-01

The development and introduction of combined therapy represent a challenge for analysis due to severe overlapping of their UV spectra in case of spectroscopy or the requirement of a long tedious and high cost separation technique in case of chromatography. Quality control laboratories have to develop and validate suitable analytical procedures in order to assay such multi component preparations. New spectrophotometric methods for the simultaneous determination of simvastatin (SIM) and nicotinic acid (NIA) in binary combinations were developed. These methods are based on chemometric treatment of data, the applied chemometric techniques are multivariate methods including classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS). In these techniques, the concentration data matrix were prepared by using the synthetic mixtures containing SIM and NIA dissolved in ethanol. The absorbance data matrix corresponding to the concentration data matrix was obtained by measuring the absorbance at 12 wavelengths in the range 216 - 240 nm at 2 nm intervals in the zero-order. The spectrophotometric procedures do not require any separation step. The accuracy, precision and the linearity ranges of the methods have been determined and validated by analyzing synthetic mixtures containing the studied drugs. Chemometric spectrophotometric methods have been developed in the present study for the simultaneous determination of simvastatin and nicotinic acid in their synthetic binary mixtures and in their mixtures with possible excipients present in tablet dosage form. The validation was performed successfully. The developed methods have been shown to be accurate, linear, precise, and so simple. The developed methods can be used routinely for the determination dosage form. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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

PubMed

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

2017-01-01

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

Rapid determination of crocins in saffron by near-infrared spectroscopy combined with chemometric techniques

NASA Astrophysics Data System (ADS)

Li, Shuailing; Shao, Qingsong; Lu, Zhonghua; Duan, Chengli; Yi, Haojun; Su, Liyang

2018-02-01

Saffron is an expensive spice. Its primary effective constituents are crocin I and II, and the contents of these compounds directly affect the quality and commercial value of saffron. In this study, near-infrared spectroscopy was combined with chemometric techniques for the determination of crocin I and II in saffron. Partial least squares regression models were built for the quantification of crocin I and II. By comparing different spectral ranges and spectral pretreatment methods (no pretreatment, vector normalization, subtract a straight line, multiplicative scatter correction, minimum-maximum normalization, eliminate the constant offset, first derivative, and second derivative), optimum models were developed. The root mean square error of cross-validation values of the best partial least squares models for crocin I and II were 1.40 and 0.30, respectively. The coefficients of determination for crocin I and II were 93.40 and 96.30, respectively. These results show that near-infrared spectroscopy can be combined with chemometric techniques to determine the contents of crocin I and II in saffron quickly and efficiently.

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

PubMed

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

2016-12-01

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

Determination of benzo[a]pyrene in cigarette mainstream smoke by using mid-infrared spectroscopy associated with a novel chemometric algorithm.

PubMed

Zhang, Yan; Zou, Hong-Yan; Shi, Pei; Yang, Qin; Tang, Li-Juan; Jiang, Jian-Hui; Wu, Hai-Long; Yu, Ru-Qin

2016-01-01

Determination of benzo[a]pyrene (BaP) in cigarette smoke can be very important for the tobacco quality control and the assessment of its harm to human health. In this study, mid-infrared spectroscopy (MIR) coupled to chemometric algorithm (DPSO-WPT-PLS), which was based on the wavelet packet transform (WPT), discrete particle swarm optimization algorithm (DPSO) and partial least squares regression (PLS), was used to quantify harmful ingredient benzo[a]pyrene in the cigarette mainstream smoke with promising result. Furthermore, the proposed method provided better performance compared to several other chemometric models, i.e., PLS, radial basis function-based PLS (RBF-PLS), PLS with stepwise regression variable selection (Stepwise-PLS) as well as WPT-PLS with informative wavelet coefficients selected by correlation coefficient test (rtest-WPT-PLS). It can be expected that the proposed strategy could become a new effective, rapid quantitative analysis technique in analyzing the harmful ingredient BaP in cigarette mainstream smoke. Copyright © 2015 Elsevier B.V. All rights reserved.

Metabolite Profiling and Classification of DNA-Authenticated Licorice Botanicals

PubMed Central

Simmler, Charlotte; Anderson, Jeffrey R.; Gauthier, Laura; Lankin, David C.; McAlpine, James B.; Chen, Shao-Nong; Pauli, Guido F.

2015-01-01

Raw licorice roots represent heterogeneous materials obtained from mainly three Glycyrrhiza species. G. glabra, G. uralensis, and G. inflata exhibit marked metabolite differences in terms of flavanones (Fs), chalcones (Cs), and other phenolic constituents. The principal objective of this work was to develop complementary chemometric models for the metabolite profiling, classification, and quality control of authenticated licorice. A total of 51 commercial and macroscopically verified samples were DNA authenticated. Principal component analysis and canonical discriminant analysis were performed on 1H NMR spectra and area under the curve values obtained from UHPLC-UV chromatograms, respectively. The developed chemometric models enable the identification and classification of Glycyrrhiza species according to their composition in major Fs, Cs, and species specific phenolic compounds. Further key outcomes demonstrated that DNA authentication combined with chemometric analyses enabled the characterization of mixtures, hybrids, and species outliers. This study provides a new foundation for the botanical and chemical authentication, classification, and metabolomic characterization of crude licorice botanicals and derived materials. Collectively, the proposed methods offer a comprehensive approach for the quality control of licorice as one of the most widely used botanical dietary supplements. PMID:26244884

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

PubMed

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.

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

PubMed

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

2016-07-01

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

Introducing Chemometrics to the Analytical Curriculum: Combining Theory and Lab Experience

ERIC Educational Resources Information Center

Gilbert, Michael K.; Luttrell, Robert D.; Stout, David; Vogt, Frank

2008-01-01

Beer's law is an ideal technique that works only in certain situations. A method for dealing with more complex conditions needs to be integrated into the analytical chemistry curriculum. For that reason, the capabilities and limitations of two common chemometric algorithms, classical least squares (CLS) and principal component regression (PCR),…

Chemometric Approach to the Calibration of Light Emitting Diode Based Optical Gas Sensors Using High-Resolution Transmission Molecular Absorption Data.

PubMed

Mahbub, Parvez; Leis, John; Macka, Mirek

2018-05-15

Modeling the propagation of light from LED sources is problematic since the emission covers a broad range of wavelengths and thus cannot be considered as monochromatic. Furthermore, the lack of directivity of such sources is also problematic. Both attributes are characteristic of LEDs. Here we propose a HITRAN ( high-resolution transmission molecular absorption database) based chemometric approach that incorporates not-perfect-monochromaticity and spatial directivity of near-infrared (NIR) LED for absorbance calculations in 1-6% methane (CH 4 ) in air, considering CH 4 as a model absorbing gas. We employed the absorbance thus calculated using HITRAN to validate the experimentally measured absorbance of CH 4 . The maximum error between the measured and calculated absorbance values were within 1%. The approach can be generalized as a chemometric calibration technique for measuring gases and gas mixtures that absorb emissions from polychromatic or not-perfect-monochromatic sources, provided the gas concentration, optical path length, as well as blank and attenuated emission spectra of the light source are incorporated into the proposed chemometric approach.

Fluorescence Spectroscopy and Chemometric Modeling for Bioprocess Monitoring

PubMed Central

Faassen, Saskia M.; Hitzmann, Bernd

2015-01-01

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

Hybrid approach combining chemometrics and likelihood ratio framework for reporting the evidential value of spectra.

PubMed

Martyna, Agnieszka; Zadora, Grzegorz; Neocleous, Tereza; Michalska, Aleksandra; Dean, Nema

2016-08-10

Many chemometric tools are invaluable and have proven effective in data mining and substantial dimensionality reduction of highly multivariate data. This becomes vital for interpreting various physicochemical data due to rapid development of advanced analytical techniques, delivering much information in a single measurement run. This concerns especially spectra, which are frequently used as the subject of comparative analysis in e.g. forensic sciences. In the presented study the microtraces collected from the scenarios of hit-and-run accidents were analysed. Plastic containers and automotive plastics (e.g. bumpers, headlamp lenses) were subjected to Fourier transform infrared spectrometry and car paints were analysed using Raman spectroscopy. In the forensic context analytical results must be interpreted and reported according to the standards of the interpretation schemes acknowledged in forensic sciences using the likelihood ratio approach. However, for proper construction of LR models for highly multivariate data, such as spectra, chemometric tools must be employed for substantial data compression. Conversion from classical feature representation to distance representation was proposed for revealing hidden data peculiarities and linear discriminant analysis was further applied for minimising the within-sample variability while maximising the between-sample variability. Both techniques enabled substantial reduction of data dimensionality. Univariate and multivariate likelihood ratio models were proposed for such data. It was shown that the combination of chemometric tools and the likelihood ratio approach is capable of solving the comparison problem of highly multivariate and correlated data after proper extraction of the most relevant features and variance information hidden in the data structure. Copyright © 2016 Elsevier B.V. All rights reserved.

Metabolic profiling of Hoodia, Chamomile, Terminalia Species and evaluation of commercial preparations using Ultra-High Performance Quadrupole Time of Flight-Mass Spectrometry

USDA-ARS?s Scientific Manuscript database

Ultra-High Performance-Quadrupole Time of Flight Mass Spectrometr(UHPLC-QToF-MS)profiling has become an impattant tool for identification of marker compounds and generation of metabolic patterns that could be interrogated using chemometric modeling software. Chemometric approaches can be used to ana...

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

USDA-ARS?s Scientific Manuscript database

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

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

PubMed Central

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

2017-01-01

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

Chemometric comparison of polychlorinated biphenyl residues and toxicologically active polychlorinated biphenyl congeners in the eggs of Forster's Terns (Sterna fosteri)

USGS Publications Warehouse

Schwartz, Ted R.; Stalling, David L.

1991-01-01

The separation and characterization of complex mixtures of polychlorinated biphenyls (PCBs) is approached from the perspective of a problem in chemometrics. A technique for quantitative determination of PCB congeners is described as well as an enrichment technique designed to isolate only those congener residues which induce mixed aryl hydrocarbon hydroxylase enzyme activity. A congener-specific procedure is utilized for the determination of PCBs in whichn-alkyl trichloroacetates are used as retention index marker compounds. Retention indices are reproducible in the range of ±0.05 to ±0.7 depending on the specific congener. A laboratory data base system developed to aid in the editing and quantitation of data generated from capillary gas chromatography was employed to quantitate chromatographic data. Data base management was provided by computer programs written in VAX-DSM (Digital Standard MUMPS) for the VAX-DEC (Digital Equipment Corp.) family of computers.In the chemometric evaluation of these complex chromatographic profiles, data are viewed from a single analysis as a point in multi-dimensional space. Principal Components Analysis was used to obtain a representation of the data in a lower dimensional space. Two-and three-dimensional proections based on sample scores from the principal components models were used to visualize the behavior of Aroclor® mixtures. These models can be used to determine if new sample profiles may be represented by Aroclor profiles. Concentrations of individual congeners of a given chlorine substitution may be summed to form homologue concentration. However, the use of homologue concentrations in classification studies with environmental samples can lead to erroneous conclusions about sample similarity. Chemometric applications are discussed for evaluation of Aroclor mixture analysis and compositional description of environmental residues of PCBs in eggs of Forster's terns (Sterna fosteri) collected from colonies near Lake Poygan and Green Bay, Wisconsin. The application of chemometrics is extended to the comparison of: a) Aroclors and PCB-containing environmental samples; to b) fractions of Aroclors and of environmental samples that have been enriched in congeners which induce mixed aryl hydrocarbon hydroxylase enzyme activity.

Experimental Design, Near-Infrared Spectroscopy, and Multivariate Calibration: An Advanced Project in a Chemometrics Course

ERIC Educational Resources Information Center

de Oliveira, Rodrigo R.; das Neves, Luiz S.; de Lima, Kassio M. G.

2012-01-01

A chemometrics course is offered to students in their fifth semester of the chemistry undergraduate program that includes an in-depth project. Students carry out the project over five weeks (three 8-h sessions per week) and conduct it in parallel to other courses or other practical work. The students conduct a literature search, carry out…

Effect of the statin therapy on biochemical laboratory tests--a chemometrics study.

PubMed

Durceková, Tatiana; Mocák, Ján; Boronová, Katarína; Balla, Ján

2011-01-05

Statins are the first-line choice for lowering total and LDL cholesterol levels and very important medicaments for reducing the risk of coronary artery disease. The aim of this study is therefore assessment of the results of biochemical tests characterizing the condition of 172 patients before and after administration of statins. For this purpose, several chemometric tools, namely principal component analysis, cluster analysis, discriminant analysis, logistic regression, KNN classification, ROC analysis, descriptive statistics and ANOVA were used. Mutual relations of 11 biochemical laboratory tests, the patient's age and gender were investigated in detail. Achieved results enable to evaluate the extent of the statin treatment in each individual case. They may also help in monitoring the dynamic progression of the disease. Copyright © 2010 Elsevier B.V. All rights reserved.

High-speed peak matching algorithm for retention time alignment of gas chromatographic data for chemometric analysis.

PubMed

Johnson, Kevin J; Wright, Bob W; Jarman, Kristin H; Synovec, Robert E

2003-05-09

A rapid retention time alignment algorithm was developed as a preprocessing utility to be used prior to chemometric analysis of large datasets of diesel fuel profiles obtained using gas chromatography (GC). Retention time variation from chromatogram-to-chromatogram has been a significant impediment against the use of chemometric techniques in the analysis of chromatographic data due to the inability of current chemometric techniques to correctly model information that shifts from variable to variable within a dataset. The alignment algorithm developed is shown to increase the efficacy of pattern recognition methods applied to diesel fuel chromatograms by retaining chemical selectivity while reducing chromatogram-to-chromatogram retention time variations and to do so on a time scale that makes analysis of large sets of chromatographic data practical. Two sets of diesel fuel gas chromatograms were studied using the novel alignment algorithm followed by principal component analysis (PCA). In the first study, retention times for corresponding chromatographic peaks in 60 chromatograms varied by as much as 300 ms between chromatograms before alignment. In the second study of 42 chromatograms, the retention time shifting exhibited was on the order of 10 s between corresponding chromatographic peaks, and required a coarse retention time correction prior to alignment with the algorithm. In both cases, an increase in retention time precision afforded by the algorithm was clearly visible in plots of overlaid chromatograms before and then after applying the retention time alignment algorithm. Using the alignment algorithm, the standard deviation for corresponding peak retention times following alignment was 17 ms throughout a given chromatogram, corresponding to a relative standard deviation of 0.003% at an average retention time of 8 min. This level of retention time precision is a 5-fold improvement over the retention time precision initially provided by a state-of-the-art GC instrument equipped with electronic pressure control and was critical to the performance of the chemometric analysis. This increase in retention time precision does not come at the expense of chemical selectivity, since the PCA results suggest that essentially all of the chemical selectivity is preserved. Cluster resolution between dissimilar groups of diesel fuel chromatograms in a two-dimensional scores space generated with PCA is shown to substantially increase after alignment. The alignment method is robust against missing or extra peaks relative to a target chromatogram used in the alignment, and operates at high speed, requiring roughly 1 s of computation time per GC chromatogram.

Chemometric Analysis of Bacterial Peptidoglycan Reveals Atypical Modifications That Empower the Cell Wall against Predatory Enzymes and Fly Innate Immunity.

PubMed

Espaillat, Akbar; Forsmo, Oskar; El Biari, Khouzaima; Björk, Rafael; Lemaitre, Bruno; Trygg, Johan; Cañada, Francisco Javier; de Pedro, Miguel A; Cava, Felipe

2016-07-27

Peptidoglycan is a fundamental structure for most bacteria. It contributes to the cell morphology and provides cell wall integrity against environmental insults. While several studies have reported a significant degree of variability in the chemical composition and organization of peptidoglycan in the domain Bacteria, the real diversity of this polymer is far from fully explored. This work exploits rapid ultraperformance liquid chromatography and multivariate data analysis to uncover peptidoglycan chemical diversity in the Class Alphaproteobacteria, a group of Gram negative bacteria that are highly heterogeneous in terms of metabolism, morphology and life-styles. Indeed, chemometric analyses revealed novel peptidoglycan structures conserved in Acetobacteria: amidation at the α-(l)-carboxyl of meso-diaminopimelic acid and the presence of muropeptides cross-linked by (1-3) l-Ala-d-(meso)-diaminopimelate cross-links. Both structures are growth-controlled modifications that influence sensitivity to Type VI secretion system peptidoglycan endopeptidases and recognition by the Drosophila innate immune system, suggesting relevant roles in the environmental adaptability of these bacteria. Collectively our findings demonstrate the discriminative power of chemometric tools on large cell wall-chromatographic data sets to discover novel peptidoglycan structural properties in bacteria.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

2014-11-01

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

Modelling spatio-temporal heterogeneities in groundwater quality in Ghana: a multivariate chemometric approach.

PubMed

Armah, Frederick Ato; Paintsil, Arnold; Yawson, David Oscar; Adu, Michael Osei; Odoi, Justice O

2017-08-01

Chemometric techniques were applied to evaluate the spatial and temporal heterogeneities in groundwater quality data for approximately 740 goldmining and agriculture-intensive locations in Ghana. The strongest linear and monotonic relationships occurred between Mn and Fe. Sixty-nine per cent of total variance in the dataset was explained by four variance factors: physicochemical properties, bacteriological quality, natural geologic attributes and anthropogenic factors (artisanal goldmining). There was evidence of significant differences in means of all trace metals and physicochemical parameters (p < 0.001) between goldmining and non-goldmining locations. Arsenic and turbidity produced very high value F's demonstrating that 'physical properties and chalcophilic elements' was the function that most discriminated between non-goldmining and goldmining locations. Variations in Escherichia coli and total coliforms were observed between the dry and wet seasons. The overall predictive accuracy of the discriminant function showed that non-goldmining locations were classified with slightly better accuracy (89%) than goldmining areas (69.6%). There were significant differences between the underlying distributions of Cd, Mn and Pb in the wet and dry seasons. This study emphasizes the practicality of chemometrics in the assessment and elucidation of complex water quality datasets to promote effective management of groundwater resources for sustaining human health.

Chemometric analysis of multisensor hyperspectral images of precipitated atmospheric particulate matter.

PubMed

Ofner, Johannes; Kamilli, Katharina A; Eitenberger, Elisabeth; Friedbacher, Gernot; Lendl, Bernhard; Held, Andreas; Lohninger, Hans

2015-09-15

The chemometric analysis of multisensor hyperspectral data allows a comprehensive image-based analysis of precipitated atmospheric particles. Atmospheric particulate matter was precipitated on aluminum foils and analyzed by Raman microspectroscopy and subsequently by electron microscopy and energy dispersive X-ray spectroscopy. All obtained images were of the same spot of an area of 100 × 100 μm(2). The two hyperspectral data sets and the high-resolution scanning electron microscope images were fused into a combined multisensor hyperspectral data set. This multisensor data cube was analyzed using principal component analysis, hierarchical cluster analysis, k-means clustering, and vertex component analysis. The detailed chemometric analysis of the multisensor data allowed an extensive chemical interpretation of the precipitated particles, and their structure and composition led to a comprehensive understanding of atmospheric particulate matter.

Mid-infrared spectroscopy combined with chemometrics to detect Sclerotinia stem rot on oilseed rape (Brassica napus L.) leaves.

PubMed

Zhang, Chu; Feng, Xuping; Wang, Jian; Liu, Fei; He, Yong; Zhou, Weijun

2017-01-01

Detection of plant diseases in a fast and simple way is crucial for timely disease control. Conventionally, plant diseases are accurately identified by DNA, RNA or serology based methods which are time consuming, complex and expensive. Mid-infrared spectroscopy is a promising technique that simplifies the detection procedure for the disease. Mid-infrared spectroscopy was used to identify the spectral differences between healthy and infected oilseed rape leaves. Two different sample sets from two experiments were used to explore and validate the feasibility of using mid-infrared spectroscopy in detecting Sclerotinia stem rot (SSR) on oilseed rape leaves. The average mid-infrared spectra showed differences between healthy and infected leaves, and the differences varied among different sample sets. Optimal wavenumbers for the 2 sample sets selected by the second derivative spectra were similar, indicating the efficacy of selecting optimal wavenumbers. Chemometric methods were further used to quantitatively detect the oilseed rape leaves infected by SSR, including the partial least squares-discriminant analysis, support vector machine and extreme learning machine. The discriminant models using the full spectra and the optimal wavenumbers of the 2 sample sets were effective for classification accuracies over 80%. The discriminant results for the 2 sample sets varied due to variations in the samples. The use of two sample sets proved and validated the feasibility of using mid-infrared spectroscopy and chemometric methods for detecting SSR on oilseed rape leaves. The similarities among the selected optimal wavenumbers in different sample sets made it feasible to simplify the models and build practical models. Mid-infrared spectroscopy is a reliable and promising technique for SSR control. This study helps in developing practical application of using mid-infrared spectroscopy combined with chemometrics to detect plant disease.

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

ERIC Educational Resources Information Center

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

2011-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2008-11-01

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

Simultaneous spectrophotometric determination of glimepiride and pioglitazone in binary mixture and combined dosage form using chemometric-assisted techniques

NASA Astrophysics Data System (ADS)

El-Zaher, Asmaa A.; Elkady, Ehab F.; Elwy, Hanan M.; Saleh, Mahmoud Abo El Makarim

2017-07-01

In the present work, pioglitazone and glimepiride, 2 widely used antidiabetics, were simultaneously determined by a chemometric-assisted UV-spectrophotometric method which was applied to a binary synthetic mixture and a pharmaceutical preparation containing both drugs. Three chemometric techniques - Concentration residual augmented classical least-squares (CRACLS), principal component regression (PCR), and partial least-squares (PLS) were implemented by using the synthetic mixtures containing the two drugs in acetonitrile. The absorbance data matrix corresponding to the concentration data matrix was obtained by the measurements of absorbencies in the range between 215 and 235 nm in the intervals with Δλ = 0.4 nm in their zero-order spectra. Then, calibration or regression was obtained by using the absorbance data matrix and concentration data matrix for the prediction of the unknown concentrations of pioglitazone and glimepiride in their mixtures. The described techniques have been validated by analyzing synthetic mixtures containing the two drugs showing good mean recovery values lying between 98 and 100%. In addition, accuracy and precision of the three methods have been assured by recovery values lying between 98 and 102% and R.S.D. % ˂0.6 for intra-day precision and ˂1.2 for inter-day precision. The proposed chemometric techniques were successfully applied to a pharmaceutical preparation containing a combination of pioglitazone and glimepiride in the ratio of 30: 4, showing good recovery values. Finally, statistical analysis was carried out to add a value to the verification of the proposed methods. It was carried out by an intrinsic comparison between the 3 chemometric techniques and by comparing values of present methods with those obtained by implementing reference pharmacopeial methods for each of pioglitazone and glimepiride.

Chemometric Methods to Quantify 1D and 2D NMR Spectral Differences Among Similar Protein Therapeutics.

PubMed

Chen, Kang; Park, Junyong; Li, Feng; Patil, Sharadrao M; Keire, David A

2018-04-01

NMR spectroscopy is an emerging analytical tool for measuring complex drug product qualities, e.g., protein higher order structure (HOS) or heparin chemical composition. Most drug NMR spectra have been visually analyzed; however, NMR spectra are inherently quantitative and multivariate and thus suitable for chemometric analysis. Therefore, quantitative measurements derived from chemometric comparisons between spectra could be a key step in establishing acceptance criteria for a new generic drug or a new batch after manufacture change. To measure the capability of chemometric methods to differentiate comparator NMR spectra, we calculated inter-spectra difference metrics on 1D/2D spectra of two insulin drugs, Humulin R® and Novolin R®, from different manufacturers. Both insulin drugs have an identical drug substance but differ in formulation. Chemometric methods (i.e., principal component analysis (PCA), 3-way Tucker3 or graph invariant (GI)) were performed to calculate Mahalanobis distance (D M ) between the two brands (inter-brand) and distance ratio (D R ) among the different lots (intra-brand). The PCA on 1D inter-brand spectral comparison yielded a D M value of 213. In comparing 2D spectra, the Tucker3 analysis yielded the highest differentiability value (D M  = 305) in the comparisons made followed by PCA (D M  = 255) then the GI method (D M  = 40). In conclusion, drug quality comparisons among different lots might benefit from PCA on 1D spectra for rapidly comparing many samples, while higher resolution but more time-consuming 2D-NMR-data-based comparisons using Tucker3 analysis or PCA provide a greater level of assurance for drug structural similarity evaluation between drug brands.

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

PubMed

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

2017-12-31

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

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

PubMed Central

Zhang, Chu; Shen, Tingting

2017-01-01

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

High-speed peak matching algorithm for retention time alignment of gas chromatographic data for chemometric analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Kevin J.; Wright, Bob W.; Jarman, Kristin H.

2003-05-09

A rapid retention time alignment algorithm was developed as a preprocessing utility to be used prior to chemometric analysis of large datasets of diesel fuel gas chromatographic profiles. Retention time variation from chromatogram-to-chromatogram has been a significant impediment against the use of chemometric techniques in the analysis of chromatographic data due to the inability of current multivariate techniques to correctly model information that shifts from variable to variable within a dataset. The algorithm developed is shown to increase the efficacy of pattern recognition methods applied to a set of diesel fuel chromatograms by retaining chemical selectivity while reducing chromatogram-to-chromatogram retentionmore » time variations and to do so on a time scale that makes analysis of large sets of chromatographic data practical.« less

Using near infrared spectroscopy to classify soybean oil according to expiration date.

PubMed

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.

Micro-Raman spectroscopy of natural and synthetic indigo samples.

PubMed

Vandenabeele, Peter; Moens, Luc

2003-02-01

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

Investigation of hydrogenation of toluene to methylcyclohexane in a trickle bed reactor by low-field nuclear magnetic resonance spectroscopy.

PubMed

Guthausen, Gisela; von Garnier, Agnes; Reimert, Rainer

2009-10-01

Low-field nuclear magnetic resonance (NMR) spectroscopy is applied to study the hydrogenation of toluene in a lab-scale reactor. A conventional benchtop NMR system was modified to achieve chemical shift resolution. After an off-line validity check of the approach, the reaction product is analyzed on-line during the process, applying chemometric data processing. The conversion of toluene to methylcyclohexane is compared with off-line gas chromatographic analysis. Both classic analytical and chemometric data processing was applied. As the results, which are obtained within a few tens of seconds, are equivalent within the experimental accuracy of both methods, low-field NMR spectroscopy was shown to provide an analytical tool for reaction characterization and immediate feedback.

Pre-selection and assessment of green organic solvents by clustering chemometric tools.

PubMed

Tobiszewski, Marek; Nedyalkova, Miroslava; Madurga, Sergio; Pena-Pereira, Francisco; Namieśnik, Jacek; Simeonov, Vasil

2018-01-01

The study presents the result of the application of chemometric tools for selection of physicochemical parameters of solvents for predicting missing variables - bioconcentration factors, water-octanol and octanol-air partitioning constants. EPI Suite software was successfully applied to predict missing values for solvents commonly considered as "green". Values for logBCF, logK OW and logK OA were modelled for 43 rather nonpolar solvents and 69 polar ones. Application of multivariate statistics was also proved to be useful in the assessment of the obtained modelling results. The presented approach can be one of the first steps and support tools in the assessment of chemicals in terms of their greenness. Copyright © 2017 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Chemometric Deconvolution of Continuous Electrokinetic Injection Micellar Electrokinetic Chromatography Data for the Quantitation of Trinitrotoluene in Mixtures of Other Nitroaromatic Compounds

DTIC Science & Technology

2014-02-24

Suite 600 Washington, DC 20036 NRL/MR/ 6110 --14-9521 Approved for public release; distribution is unlimited. 1Science & Engineering Apprenticeship...Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/ 6110 --14-9521 Chemometric Deconvolution of Continuous Electrokinetic Injection Micellar... Engineering Apprenticeship Program American Society for Engineering Education Washington, DC Kevin Johnson Navy Technology Center for Safety and

Practical aspects of chemometrics for oil spill fingerprinting.

PubMed

Christensen, Jan H; Tomasi, Giorgio

2007-10-26

Tiered approaches for oil spill fingerprinting have evolved rapidly since the 1990s. Chemometrics provides a large number of tools for pattern recognition, calibration and classification that can increase the speed and the objectivity of the analysis and allow for more extensive use of the available data in this field. However, although the chemometric literature is extensive, it does not focus on practical issues that are relevant to oil spill fingerprinting. The aim of this review is to provide a framework for the use of chemometric approaches in tiered oil spill fingerprinting and to provide clear-cut practical details and experiences that can be used by the forensic chemist. The framework is based on methods for initial screening, which include classification of samples into oil type, detection of non matches and of weathering state, and detailed oil spill fingerprinting, in which a more rigorous matching of an oil spill sample to suspected source oils is obtained. This review is intended as a tutorial, and is based on two examples of initial screening using respectively gas chromatography with flame ionization detection and fluorescence spectroscopy; and two of detailed oil spill fingerprinting where gas chromatography-mass spectrometry data are analyzed according to two approaches: The first relying on sections of processed chromatograms and the second on diagnostic ratios.

Classification and quantitation of milk powder by near-infrared spectroscopy and mutual information-based variable selection and partial least squares

NASA Astrophysics Data System (ADS)

Chen, Hui; Tan, Chao; Lin, Zan; Wu, Tong

2018-01-01

Milk is among the most popular nutrient source worldwide, which is of great interest due to its beneficial medicinal properties. The feasibility of the classification of milk powder samples with respect to their brands and the determination of protein concentration is investigated by NIR spectroscopy along with chemometrics. Two datasets were prepared for experiment. One contains 179 samples of four brands for classification and the other contains 30 samples for quantitative analysis. Principal component analysis (PCA) was used for exploratory analysis. Based on an effective model-independent variable selection method, i.e., minimal-redundancy maximal-relevance (MRMR), only 18 variables were selected to construct a partial least-square discriminant analysis (PLS-DA) model. On the test set, the PLS-DA model based on the selected variable set was compared with the full-spectrum PLS-DA model, both of which achieved 100% accuracy. In quantitative analysis, the partial least-square regression (PLSR) model constructed by the selected subset of 260 variables outperforms significantly the full-spectrum model. It seems that the combination of NIR spectroscopy, MRMR and PLS-DA or PLSR is a powerful tool for classifying different brands of milk and determining the protein content.

Determination of ambroxol hydrochloride, guaifenesin, and theophylline in ternary mixtures and in the presence of excipients in different pharmaceutical dosage forms.

PubMed

Abdelwahab, Nada S

2012-01-01

Determination of ternary mixtures of ambroxol hydrochloride, guaifenesin, and theophylline with minimum sample pretreatment and without analyte separation has been successfully achieved by using chemometric and RP-HPLC methods. The developed chemometric models are partial least squares (PLS) and genetic algorithm coupled with PLS. Data of the analyses were obtained from UV-Vis spectra of the studied drugs in different concentration ranges. These models have been successfully updated to be applied for determination of the proposed drugs in Farcosolvin syrup and in the presence of a syrup excipient (methyl paraben). In the developed RP-HPLC method, chromatographic runs were performed on an RP-C18 analytical column with the isocratic mobile phase 0.05 M phosphate buffer-methanol-acetonitrile-triethylamine (63.5 + 27.5 + 9 + 0.25, v/v/v/v, pH 5.5 adjusted with orthophosphoric acid) at a flow rate of 1.2 mL/min. The analytes were detected and quantified at 220 nm. The method was optimized in order to obtain good resolution between the studied components and to prevent interference from methyl paraben. Method validation was performed with respect to International Conference on Harmonization guidelines and the validation acceptance criteria were met in all cases. The proposed methods can be considered acceptable for QC of the studied drugs in pharmaceutical capsules and syrup. The results obtained by the suggested chemometric methods for determination of the studied mixture in different pharmaceutical preparations were statistically compared to those obtained by applying the developed RP-HPLC method, and no significant difference was found.

Quality Evaluation and Chemical Markers Screening of Salvia miltiorrhiza Bge. (Danshen) Based on HPLC Fingerprints and HPLC-MSn Coupled with Chemometrics.

PubMed

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

2017-03-17

Danshen, the dried root of Salvia miltiorrhiza Bge., is a widely used commercially available herbal drug, and unstable quality of different samples is a current issue. This study focused on a comprehensive and systematic method combining fingerprints and chemical identification with chemometrics for discrimination and quality assessment of Danshen samples. Twenty-five samples were analyzed by HPLC-PAD and HPLC-MS n . Forty-nine components were identified and characteristic fragmentation regularities were summarized for further interpretation of bioactive components. Chemometric analysis was employed to differentiate samples and clarify the quality differences of Danshen including hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis. Consistent results were that the samples were divided into three categories which reflected the difference in quality of Danshen samples. By analyzing the reasons for sample classification, it was revealed that the processing method had a more obvious impact on sample classification than the geographical origin, it induced the different content of bioactive compounds and finally lead to different qualities. Cryptotanshinone, trijuganone B, and 15,16-dihydrotanshinone I were screened out as markers to distinguish samples by different processing methods. The developed strategy could provide a reference for evaluation and discrimination of other traditional herbal medicines.

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

PubMed

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

2016-10-01

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

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

PubMed

Dinç, Erdal; Ustündağ, Ozgür; Baleanu, Dumitru

2010-08-01

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

Design and Optimization of a Chemometric-Assisted Spectrophotometric Determination of Telmisartan and Hydrochlorothiazide in Pharmaceutical Dosage Form

PubMed Central

Lakshmi, KS; Lakshmi, S

2010-01-01

Two chemometric methods were developed for the simultaneous determination of telmisartan and hydrochlorothiazide. The chemometric methods applied were principal component regression (PCR) and partial least square (PLS-1). These approaches were successfully applied to quantify the two drugs in the mixture using the information included in the UV absorption spectra of appropriate solutions in the range of 200-350 nm with the intervals Δλ = 1 nm. The calibration of PCR and PLS-1 models was evaluated by internal validation (prediction of compounds in its own designed training set of calibration) and by external validation over laboratory prepared mixtures and pharmaceutical preparations. The PCR and PLS-1 methods require neither any separation step, nor any prior graphical treatment of the overlapping spectra of the two drugs in a mixture. The results of PCR and PLS-1 methods were compared with each other and a good agreement was found. PMID:21331198

Design and optimization of a chemometric-assisted spectrophotometric determination of telmisartan and hydrochlorothiazide in pharmaceutical dosage form.

PubMed

Lakshmi, Ks; Lakshmi, S

2010-01-01

Two chemometric methods were developed for the simultaneous determination of telmisartan and hydrochlorothiazide. The chemometric methods applied were principal component regression (PCR) and partial least square (PLS-1). These approaches were successfully applied to quantify the two drugs in the mixture using the information included in the UV absorption spectra of appropriate solutions in the range of 200-350 nm with the intervals Δλ = 1 nm. The calibration of PCR and PLS-1 models was evaluated by internal validation (prediction of compounds in its own designed training set of calibration) and by external validation over laboratory prepared mixtures and pharmaceutical preparations. The PCR and PLS-1 methods require neither any separation step, nor any prior graphical treatment of the overlapping spectra of the two drugs in a mixture. The results of PCR and PLS-1 methods were compared with each other and a good agreement was found.

Circum-Arctic petroleum systems identified using decision-tree chemometrics

USGS Publications Warehouse

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

2007-01-01

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

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

PubMed

Ni, Yongnian; Wang, Lin; Kokot, Serge

2011-01-01

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

Metabolomics combined with chemometric tools (PCA, HCA, PLS-DA and SVM) for screening cassava (Manihot esculenta Crantz) roots during postharvest physiological deterioration.

PubMed

Uarrota, Virgílio Gavicho; Moresco, Rodolfo; Coelho, Bianca; Nunes, Eduardo da Costa; Peruch, Luiz Augusto Martins; Neubert, Enilto de Oliveira; Rocha, Miguel; Maraschin, Marcelo

2014-10-15

Cassava roots are an important source of dietary and industrial carbohydrates and suffer markedly from postharvest physiological deterioration (PPD). This paper deals with metabolomics combined with chemometric tools for screening the chemical and enzymatic composition in several genotypes of cassava roots during PPD. Metabolome analyses showed increases in carotenoids, flavonoids, anthocyanins, phenolics, reactive scavenging species, and enzymes (superoxide dismutase family, hydrogen peroxide, and catalase) until 3-5days postharvest. PPD correlated negatively with phenolics and carotenoids and positively with anthocyanins and flavonoids. Chemometric tools such as principal component analysis, partial least squares discriminant analysis, and support vector machines discriminated well cassava samples and enabled a good prediction of samples. Hierarchical clustering analyses grouped samples according to their levels of PPD and chemical compositions. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

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

PubMed

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

2011-06-01

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

Chemometrics-assisted spectrophotometry method for the determination of chemical oxygen demand in pulping effluent.

PubMed

Chen, Honglei; Chen, Yuancai; Zhan, Huaiyu; Fu, Shiyu

2011-04-01

A new method has been developed for the determination of chemical oxygen demand (COD) in pulping effluent using chemometrics-assisted spectrophotometry. Two calibration models were established by inducing UV-visible spectroscopy (model 1) and derivative spectroscopy (model 2), combined with the chemometrics software Smica-P. Correlation coefficients of the two models are 0.9954 (model 1) and 0.9963 (model 2) when COD of samples is in the range of 0 to 405 mg/L. Sensitivities of the two models are 0.0061 (model 1) and 0.0056 (model 2) and method detection limits are 2.02-2.45 mg/L (model 1) and 2.13-2.51 mg/L (model 2). Validation experiment showed that the average standard deviation of model 2 was 1.11 and that of model 1 was 1.54. Similarly, average relative error of model 2 (4.25%) was lower than model 1 (5.00%), which indicated that the predictability of model 2 was better than that of model 1. Chemometrics-assisted spectrophotometry method did not need chemical reagents and digestion which were required in the conventional methods, and the testing time of the new method was significantly shorter than the conventional ones. The proposed method can be used to measure COD in pulping effluent as an environmentally friendly approach with satisfactory results.

Estimation of nitrite in source-separated nitrified urine with UV spectrophotometry.

PubMed

Mašić, Alma; Santos, Ana T L; Etter, Bastian; Udert, Kai M; Villez, Kris

2015-11-15

Monitoring of nitrite is essential for an immediate response and prevention of irreversible failure of decentralized biological urine nitrification reactors. Although a few sensors are available for nitrite measurement, none of them are suitable for applications in which both nitrite and nitrate are present in very high concentrations. Such is the case in collected source-separated urine, stabilized by nitrification for long-term storage. Ultraviolet (UV) spectrophotometry in combination with chemometrics is a promising option for monitoring of nitrite. In this study, an immersible in situ UV sensor is investigated for the first time so to establish a relationship between UV absorbance spectra and nitrite concentrations in nitrified urine. The study focuses on the effects of suspended particles and saturation on the absorbance spectra and the chemometric model performance. Detailed analysis indicates that suspended particles in nitrified urine have a negligible effect on nitrite estimation, concluding that sample filtration is not necessary as pretreatment. In contrast, saturation due to very high concentrations affects the model performance severely, suggesting dilution as an essential sample preparation step. However, this can also be mitigated by simple removal of the saturated, lower end of the UV absorbance spectra, and extraction of information from the secondary, weaker nitrite absorbance peak. This approach allows for estimation of nitrite with a simple chemometric model and without sample dilution. These results are promising for a practical application of the UV sensor as an in situ nitrite measurement in a urine nitrification reactor given the exceptional quality of the nitrite estimates in comparison to previous studies. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed

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

2018-06-01

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

A manual and an automatic TERS based virus discrimination

NASA Astrophysics Data System (ADS)

Olschewski, Konstanze; Kämmer, Evelyn; Stöckel, Stephan; Bocklitz, Thomas; Deckert-Gaudig, Tanja; Zell, Roland; Cialla-May, Dana; Weber, Karina; Deckert, Volker; Popp, Jürgen

2015-02-01

Rapid techniques for virus identification are more relevant today than ever. Conventional virus detection and identification strategies generally rest upon various microbiological methods and genomic approaches, which are not suited for the analysis of single virus particles. In contrast, the highly sensitive spectroscopic technique tip-enhanced Raman spectroscopy (TERS) allows the characterisation of biological nano-structures like virions on a single-particle level. In this study, the feasibility of TERS in combination with chemometrics to discriminate two pathogenic viruses, Varicella-zoster virus (VZV) and Porcine teschovirus (PTV), was investigated. In a first step, chemometric methods transformed the spectral data in such a way that a rapid visual discrimination of the two examined viruses was enabled. In a further step, these methods were utilised to perform an automatic quality rating of the measured spectra. Spectra that passed this test were eventually used to calculate a classification model, through which a successful discrimination of the two viral species based on TERS spectra of single virus particles was also realised with a classification accuracy of 91%.Rapid techniques for virus identification are more relevant today than ever. Conventional virus detection and identification strategies generally rest upon various microbiological methods and genomic approaches, which are not suited for the analysis of single virus particles. In contrast, the highly sensitive spectroscopic technique tip-enhanced Raman spectroscopy (TERS) allows the characterisation of biological nano-structures like virions on a single-particle level. In this study, the feasibility of TERS in combination with chemometrics to discriminate two pathogenic viruses, Varicella-zoster virus (VZV) and Porcine teschovirus (PTV), was investigated. In a first step, chemometric methods transformed the spectral data in such a way that a rapid visual discrimination of the two examined viruses was enabled. In a further step, these methods were utilised to perform an automatic quality rating of the measured spectra. Spectra that passed this test were eventually used to calculate a classification model, through which a successful discrimination of the two viral species based on TERS spectra of single virus particles was also realised with a classification accuracy of 91%. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr07033j

Chemometric-assisted spectrophotometric methods and high performance liquid chromatography for simultaneous determination of seven β-blockers in their pharmaceutical products: A comparative study

NASA Astrophysics Data System (ADS)

Abdel Hameed, Eman A.; Abdel Salam, Randa A.; Hadad, Ghada M.

2015-04-01

Chemometric-assisted spectrophotometric methods and high performance liquid chromatography (HPLC) were developed for the simultaneous determination of the seven most commonly prescribed β-blockers (atenolol, sotalol, metoprolol, bisoprolol, propranolol, carvedilol and nebivolol). Principal component regression PCR, partial least square PLS and PLS with previous wavelength selection by genetic algorithm (GA-PLS) were used for chemometric analysis of spectral data of these drugs. The compositions of the mixtures used in the calibration set were varied to cover the linearity ranges 0.7-10 μg ml-1 for AT, 1-15 μg ml-1 for ST, 1-15 μg ml-1 for MT, 0.3-5 μg ml-1 for BS, 0.1-3 μg ml-1 for PR, 0.1-3 μg ml-1 for CV and 0.7-5 μg ml-1 for NB. The analytical performances of these chemometric methods were characterized by relative prediction errors and were compared with each other. GA-PLS showed superiority over the other applied multivariate methods due to the wavelength selection. A new gradient HPLC method had been developed using statistical experimental design. Optimum conditions of separation were determined with the aid of central composite design. The developed HPLC method was found to be linear in the range of 0.2-20 μg ml-1 for AT, 0.2-20 μg ml-1 for ST, 0.1-15 μg ml-1 for MT, 0.1-15 μg ml-1 for BS, 0.1-13 μg ml-1 for PR, 0.1-13 μg ml-1 for CV and 0.4-20 μg ml-1 for NB. No significant difference between the results of the proposed GA-PLS and HPLC methods with respect to accuracy and precision. The proposed analytical methods did not show any interference of the excipients when applied to pharmaceutical products.

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

PubMed

Karabagias, Ioannis K; Karabournioti, Sofia

2018-05-03

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

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

PubMed

Kalegowda, Yogesh; Harmer, Sarah L

2012-03-20

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

Enantiomeric analysis of overlapped chromatographic profiles in the presence of interferences. Determination of ibuprofen in a pharmaceutical formulation containing homatropine.

PubMed

Padró, J M; Osorio-Grisales, J; Arancibia, J A; Olivieri, A C; Castells, C B

2016-10-07

In this work, we studied the combination of chemometric methods with chromatographic separations as a strategy applied to the analysis of enantiomers when complete enantioseparation is difficult or requires long analysis times and, in addition, the target signals have interference from the matrix. We present the determination of ibuprofen enantiomers in pharmaceutical formulations containing homatropine as interference by chiral HPLC-DAD detection in combination with partial least-squares algorithms. The method has been applied to samples containing enantiomeric ratios from 95:5 to 99.5:0.5 and coelution of interferents. The results were validated using univariate calibration and without homatropine. Relative error of the method was less than 4.0%, for both enantiomers. Limits of detection (LOD) and quantification (LOQ) for (S)-(+)-ibuprofen were 4.96×10 -10 and 1.50×10 -9 mol, respectively. LOD and LOQ for the R-(-)-ibuprofen were LOD=1.60×10 -11 mol and LOQ=4.85×10 -11 mol, respectively. Finally, the chemometric method was applied to the determination of enantiomeric purity of commercial pharmaceuticals. The ultimate goal of this research was the development of rapid, reliable, and robust methods for assessing enantiomeric purity by conventional diode array detector assisted by chemometric tools. Copyright © 2016 Elsevier B.V. All rights reserved.

A comprehensive quality evaluation method by FT-NIR spectroscopy and chemometric: Fine classification and untargeted authentication against multiple frauds for Chinese Ganoderma lucidum

NASA Astrophysics Data System (ADS)

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.

Chemometric studies for the characterization and differentiation of microorganisms using in situ derivatization and thermal desorption ion mobility spectrometry.

PubMed

Ochoa, Mariela L; Harrington, Peter B

2005-02-01

Whole-cell bacteria were characterized and differentiated by thermal desorption ion mobility spectrometry and chemometric modeling. Principal component analysis was used to evaluate the differences in the ion mobility spectra of whole-cell bacteria and the fatty acid methyl esters (FAMEs) generated in situ after derivatization of the bacterial lipids. Alternating least squares served to extract bacterial peaks from the complex ion mobility spectra of intact microorganisms and, therefore, facilitated the characterization of bacterial strains, species, and Gram type. In situ thermal hydrolysis/methylation with tetramethylammonium hydroxide was necessary for the differentiation of Escherichia coli strains, which otherwise could not be distinguished by spectra acquired with the ITEMISER ion mobility spectrometer. The addition of the methylating agent had no effect on Gram-positive bacteria, and therefore, they could not be differentiated by genera. The classification of E. coli strains was possible by analysis of the IMS spectra from the FAMEs generated in situ. By using the fuzzy multivariate rule-building expert system and cross-validation, a correct classification rate of 96% (22 out of 23 spectra) was obtained. Chemometric modeling on bacterial ion mobility spectra coupled to thermal hydrolysis/methylation proved a simple, rapid (2 min/sample), inexpensive, and sensitive technique to characterize and differentiate intact microorganisms. The ITEMISER ion mobility spectrometer could detect as few as 4 x 10(6) cells/sample.

Characterization of semi-solid Self-Emulsifying Drug Delivery Systems (SEDDS) of atorvastatin calcium by Raman image spectroscopy and chemometrics.

PubMed

Breitkreitz, Márcia C; Sabin, Guilherme P; Polla, Griselda; Poppi, Ronei J

2013-01-25

A methodology based on Raman image spectroscopy and chemometrics for homogeneity evaluation of formulations containing atorvastatin calcium in Gelucire(®) 44/14 is presented. In the first part of the work, formulations with high amounts of Gelucire(®) 44/14 (80%) and solvents of different polarities (diethylene glycol monoethyl ether, propyleneglycol, propylene glycol monocaprylate and glyceryl mono/dicaprylate/caprate) were prepared for miscibility screening evaluation by classical least squares (CLS). It was observed that Gelucire(®) 44/14 presented higher affinity for the lipophilic solvents glyceryl mono/dicaprylate/caprate and propylene glycol monocaprylate, whose samples were observed to be homogeneous, and lower affinity for the hydrophilic solvents diethylene glycol monoethyl ether and propyleneglycol, whose samples were heterogeneous. In the second part of the work, the ratio of glyceryl mono/dicaprylate/caprate and Gelucire(®) 44/14 was determined based on studies in water and allowed the selection of the proportions of these two excipients in the preconcentrate that provided supersaturation of atorvastatin upon dilution. The preconcentrate was then evaluated for homogeneity by partial least squares (PLS) and an excellent miscibility was observed in this proportion as well. Therefore, it was possible to select a formulation that presented simultaneously homogeneous preconcentrate and solubility enhancement in water by Raman image spectroscopy and chemometrics. Copyright © 2012 Elsevier B.V. All rights reserved.

Quality evaluation of terpinen-4-ol-type Australian tea tree oils and commercial products: an integrated approach using conventional and chiral GC/MS combined with chemometrics.

PubMed

Wang, Mei; Zhao, Jianping; Avula, Bharathi; Wang, Yan-Hong; Chittiboyina, Amar G; Parcher, Jon F; Khan, Ikhlas A

2015-03-18

GC/MS, chiral GC/MS, and chemometric techniques were used to evaluate a large set (n=104) of tea tree oils (TTO) and commercial products purported to contain TTO. Twenty terpenoids were determined in each sample and compared with the standards specified by ISO-4730-2004. Several of the oil samples that were ISO compliant when distilled did not meet the ISO standards in this study primarily due to the presence of excessive p-cymene and/or depletion of terpinenes. Forty-nine percent of the commercial products did not meet the ISO specifications. Four terpenes, viz., α-pinene, limonene, terpinen-4-ol, and α-terpineol, present in TTOs with the (+)-isomer predominant were measured by chiral GC/MS. The results clearly indicated that 28 commercial products contained excessive (+)-isomer or contained the (+)-isomer in concentrations below the norm. Of the 28 outliers, 7 met the ISO standards. There was a substantial subset of commercial products that met ISO standards but displayed unusual enantiomeric+/-ratios. A class predictive model based on the oils that met ISO standards was constructed. The outliers identified by the class predictive model coincided with the samples that displayed an abnormal chiral ratio. Thus, chiral and chemometric analyses could be used to confirm the identification of abnormal commercial products including those that met all of the ISO standards.

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

PubMed Central

Karabournioti, Sofia

2018-01-01

Twenty-two honey samples, namely clover and citrus honeys, were collected from the greater Cairo area during the harvesting year 2014–2015. The main purpose of the present study was to characterize the aforementioned honey types and to investigate whether the use of easily assessable physicochemical parameters, including color attributes in combination with chemometrics, could differentiate honey floral origin. Parameters taken into account were: pH, electrical conductivity, ash, free acidity, lactonic acidity, total acidity, moisture content, total sugars (degrees Brix-°Bx), total dissolved solids and their ratio to total acidity, salinity, CIELAB color parameters, along with browning index values. Results showed that all honey samples analyzed met the European quality standards set for honey and had variations in the aforementioned physicochemical parameters depending on floral origin. Application of linear discriminant analysis showed that eight physicochemical parameters, including color, could classify Egyptian honeys according to floral origin (p < 0.05). Correct classification rate was 95.5% using the original method and 90.9% using the cross validation method. The discriminatory ability of the developed model was further validated using unknown honey samples. The overall correct classification rate was not affected. Specific physicochemical parameter analysis in combination with chemometrics has the potential to enhance the differences in floral honeys produced in a given geographical zone. PMID:29751543

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

PubMed

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

2015-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

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

PubMed

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

2018-02-05

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

NMR spectroscopy and chemometrics to evaluate different processing of coconut water.

PubMed

Sucupira, N R; Alves Filho, E G; Silva, L M A; de Brito, E S; Wurlitzer, N J; Sousa, P H M

2017-02-01

NMR and chemometrics was applied to understand the variations in chemical composition of coconut water under different processing. Six processing treatments were applied to coconut water and analyzed: two control (with and without sulphite), and four samples thermally processed at 110°C and 136°C (with and without sulphite). Samples processed at lower temperature and without sulphite presented pink color under storage. According to chemometrics, samples processed at higher temperature exhibited lower levels of glucose and malic acid. Samples with sulphite processed at 136°C presented lower amount of sucrose, suggesting the degradation of the carbohydrates after harshest thermal treatment. Samples with sulphite and processed at lower temperature showed higher concentration of ethanol. However, no significant changes were verified in coconut water composition as a whole. Sulphite addition and the temperature processing to 136°C were effective to prevent the pinking and to maintain the levels of main organic compounds. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

Yücel, Yasin; Sultanoğlu, Pınar

2013-09-01

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

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

PubMed

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

2018-04-09

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

New approach to the differentiation of marble samples using thermal analysis and chemometrics in order to identify provenance

PubMed Central

2014-01-01

Background The possibility of applying a novel chemometric approach which could allow the differentiation of marble samples, all from different quarries located in the Mediterranean basin and frequently used in ancient times for artistic purposes, was investigated. By suggesting tentative or allowing to rule out unlikely attributions, this kind of differentiation could, indeed, be of valuable support to restorers and other professionals in the field of cultural heritage. Experimental data were obtained only using thermal analytical techniques: Thermogravimetry (TG), Derivative Thermogravimetry (DTG) and Differential Thermal Analysis (DTA). Results The extraction of kinetic parameters from the curves obtained using these thermal analytical techniques allowed Activation Energy values to be evaluated together with the logarithm of the Arrhenius pre-exponential factor of the main TG-DTG process. The main data thus obtained after subsequent chemometric evaluation (using Principal Components Analysis) have already proved useful in the identification the original quarry of a small number of archaeological marble finds. Conclusion One of the most evident advantages of the thermoanalytical – chemometric approach adopted seems to be that it allows the certain identification of an unknown find composed of a marble known to be present among the reference samples considered, that is, contained in the reference file. On the other hand with equal certainty it prevents the occurrence of erroneous or highly uncertain identification if the find being tested does not belong to the reference file considered. PMID:24982691

Extra virgin (EV) and ordinary (ON) olive oils: distinction and detection of adulteration (EV with ON) as determined by direct infusion electrospray ionization mass spectrometry and chemometric approaches.

PubMed

Alves, Júnia de O; Neto, Waldomiro B; Mitsutake, Hery; Alves, Paulo S P; Augusti, Rodinei

2010-07-15

Extra virgin (EV), the finest and most expensive among all the olive oil grades, is often adulterated by the cheapest and lowest quality ordinary (ON) olive oil. A new methodology is described herein that provides a simple, rapid, and accurate way not only to detect such type of adulteration, but also to distinguish between these olive oil grades (EV and ON). This approach is based on the application of direct infusion electrospray ionization mass spectrometry in the positive ion mode, ESI(+)-MS, followed by the treatment of the MS data via exploratory statistical approaches, PCA (principal component analysis) and HCA (hierarchical clustering analysis). Ten distinct brands of each EV and ON olive oil, acquired at local stores, were analyzed by ESI(+)-MS and the results from HCA and PCA clearly indicated the formation of two distinct groups related to these two categories. For the adulteration study, one brand of each olive oil grade (EV and ON) was selected. The counterfeit samples (a total of 20) were then prepared by adding assorted proportions, from 1 to 20% w/w, with increments of 1% w/w, of the ON to the EV olive oil. The PCA and HCA methodologies, applied to the ESI(+)-MS data from the counterfeit (20) and authentic (10) EV samples, were able to readily detect adulteration, even at levels as low as 1% w/w. Copyright 2010 John Wiley & Sons, Ltd.

Genetic transformation of rare Verbascum eriophorum Godr. plants and metabolic alterations revealed by NMR-based metabolomics.

PubMed

Marchev, Andrey; Yordanova, Zhenya; Alipieva, Kalina; Zahmanov, Georgi; Rusinova-Videva, Snezhana; Kapchina-Toteva, Veneta; Simova, Svetlana; Popova, Milena; Georgiev, Milen I

2016-09-01

To develop a protocol to transform Verbascum eriophorum and to study the metabolic differences between mother plants and hairy root culture by applying NMR and processing the datasets with chemometric tools. Verbascum eriophorum is a rare species with restricted distribution, which is poorly studied. Agrobacterium rhizogenes-mediated genetic transformation of V. eriophorum and hairy root culture induction are reported for the first time. To determine metabolic alterations, V. eriophorum mother plants and relevant hairy root culture were subjected to comprehensive metabolomic analyses, using NMR (1D and 2D). Metabolomics data, processed using chemometric tools (and principal component analysis in particular) allowed exploration of V. eriophorum metabolome and have enabled identification of verbascoside (by means of 2D-TOCSY NMR) as the most abundant compound in hairy root culture. Metabolomics data contribute to the elucidation of metabolic alterations after T-DNA transfer to the host V. eriophorum genome and the development of hairy root culture for sustainable bioproduction of high value verbascoside.

The Influence of the Variety, Vineyard, and Vintage on the Romanian White Wines Quality

PubMed Central

Hosu, Anamaria; Floare-Avram, Veronica; Feher, Ioana; Inceu, Mihai

2016-01-01

The wine is one of the most consumed drinks over the world, being subjected to falsification or adulteration regarding the variety, vintage, and geographical region. In this study, the influence of different characteristics of wines (type, production year, and origin) on the total phenolic content, total flavonoids content, antioxidant activity, total sugars content, pH, and 18O/16O isotopic ratio was investigated. The differentiation of selected wines on the basis of tested parameters was investigated using chemometric techniques, such as analysis of variance, cluster analysis, and principal component analysis. The experimental results are in agreement with other outcomes and allow concluding that variety and vineyard have the major influence on the studied parameters, but, also, statistical interaction effect between year and vineyard and year and variety is observed in some cases. The obtained results have demonstrated that these parameters together with chemometric techniques show a significant potential to be used for discrimination of white wines. PMID:27840767

A Comparison of Raman Spectral Features of Frozen and Deparaffinized Tissues in Neuroblastoma and Ganglioneuroma

NASA Astrophysics Data System (ADS)

Devpura, Suneetha; Thakur, Jagdish S.; Poulik, Janet M.; Rabah, Raja; Naik, Vaman M.; Naik, Ratna

2012-02-01

We have investigated the cellular regions in neuroblastoma and ganglioneuroma using Raman spectroscopy and compared their spectral characteristics with those of normal adrenal gland. Thin sections from both frozen and deparaffinized tissues, obtained from the same tissue specimen, were studied in conjunction with the pathological examination of the tissues. We found a significant difference in the spectral features of frozen sections of normal adrenal gland, neuroblastoma, and ganglioneuroma when compared to deparaffinized tissues. The quantitative analysis of the Raman data using chemometric methods of principal component analysis and discriminant function analysis obtained from the frozen tissues show a sensitivity and specificity of 100% each. The biochemical identification based on the spectral differences shows that the normal adrenal gland tissues have higher levels of carotenoids, lipids, and cholesterol compared to the neuroblastoma and ganglioneuroma frozen tissues. However, deparaffinized tissues show complete removal of these biochemicals in adrenal tissues. This study demonstrates that Raman spectroscopy combined with chemometric methods can successfully distinguish neuroblastoma and ganglioneuroma at cellular level.

Chemometric dissimilarity in nutritive value of popularly consumed Nigerian brown and white common beans.

PubMed

Moyib, Oluwasayo Kehinde; Alashiri, Ganiyy Olasunkanmi; Adejoye, Oluseyi Damilola

2015-01-01

Brown beans are the preferred varieties over the white beans in Nigeria due to their assumed richer nutrients. This study was aimed at assessing and characterising some popular Nigerian common beans for their nutritive value based on seed coat colour. Three varieties, each, of Nigerian brown and white beans, and one, each, of French bean and soybean were analysed for 19 nutrients. Z-statistics test showed that Nigerian beans are nutritionally analogous to French bean and soybean. Analysis of variance showed that seed coat colour varied with proximate nutrients, Ca, Fe, and Vit C. Chemometric analysis methods revealed superior beans for macro and micro nutrients and presented clearer groupings among the beans for seed coat colour. The study estimated a moderate genetic distance (GD) that will facilitate transfer of useful genes and intercrossing among the beans. It also offers an opportunity to integrate French bean and soybean into genetic improvement programs in Nigerian common beans. Copyright © 2014 Elsevier Ltd. All rights reserved.

Chinese vinegar classification via volatiles using long-optical-path infrared spectroscopy and chemometrics.

PubMed

Dong, D; Zheng, W; Jiao, L; Lang, Y; Zhao, X

2016-03-01

Different brands of Chinese vinegar are similar in appearance, color and aroma, making their discrimination difficult. The compositions and concentrations of the volatiles released from different vinegars vary by raw material and brewing process and thus offer a means to discriminate vinegars. In this study, we enhanced the detection sensitivity of the infrared spectrometer by extending its optical path. We measured the infrared spectra of the volatiles from 5 brands of Chinese vinegar and observed the spectral characteristics corresponding to alcohols, esters, acids, furfural, etc. Different brands of Chinese vinegar had obviously different infrared spectra and could be classified through chemometrics analysis. Furthermore, we established classification models and demonstrated their effectiveness for classifying different brands of vinegar. This study demonstrates that long-optical-path infrared spectroscopy has the ability to discriminate Chinese vinegars with the advantages that it is fast and non-destructive and eliminates the need for sampling. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed

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

2016-08-15

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

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

PubMed

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

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-09-01

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

Laser-induced breakdown spectroscopy (LIBS) for rapid analysis of ash, potassium and magnesium in gluten free flours.

PubMed

Markiewicz-Keszycka, Maria; Casado-Gavalda, Maria P; Cama-Moncunill, Xavier; Cama-Moncunill, Raquel; Dixit, Yash; Cullen, Patrick J; Sullivan, Carl

2018-04-01

Gluten free (GF) diets are prone to mineral deficiency, thus effective monitoring of the elemental composition of GF products is important to ensure a balanced micronutrient diet. The objective of this study was to test the potential of laser-induced breakdown spectroscopy (LIBS) analysis combined with chemometrics for at-line monitoring of ash, potassium and magnesium content of GF flours: tapioca, potato, maize, buckwheat, brown rice and a GF flour mixture. Concentrations of ash, potassium and magnesium were determined with reference methods and LIBS. PCA analysis was performed and presented the potential for discrimination of the six GF flours. For the quantification analysis PLSR models were developed; R 2 cal were 0.99 for magnesium and potassium and 0.97 for ash. The study revealed that LIBS combined with chemometrics is a convenient method to quantify concentrations of ash, potassium and magnesium and present the potential to classify different types of flours. Copyright © 2017 Elsevier Ltd. All rights reserved.

Forensic Discrimination of Latent Fingerprints Using Laser-Induced Breakdown Spectroscopy (LIBS) and Chemometric Approaches.

PubMed

Yang, Jun-Ho; Yoh, Jack J

2018-01-01

A novel technique is reported for separating overlapping latent fingerprints using chemometric approaches that combine laser-induced breakdown spectroscopy (LIBS) and multivariate analysis. The LIBS technique provides the capability of real time analysis and high frequency scanning as well as the data regarding the chemical composition of overlapping latent fingerprints. These spectra offer valuable information for the classification and reconstruction of overlapping latent fingerprints by implementing appropriate statistical multivariate analysis. The current study employs principal component analysis and partial least square methods for the classification of latent fingerprints from the LIBS spectra. This technique was successfully demonstrated through a classification study of four distinct latent fingerprints using classification methods such as soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). The novel method yielded an accuracy of more than 85% and was proven to be sufficiently robust. Furthermore, through laser scanning analysis at a spatial interval of 125 µm, the overlapping fingerprints were reconstructed as separate two-dimensional forms.

Multivariate Classification of Original and Fake Perfumes by Ion Analysis and Ethanol Content.

PubMed

Gomes, Clêrton L; de Lima, Ari Clecius A; Loiola, Adonay R; da Silva, Abel B R; Cândido, Manuela C L; Nascimento, Ronaldo F

2016-07-01

The increased marketing of fake perfumes has encouraged us to investigate how to identify such products by their chemical characteristics and multivariate analysis. The aim of this study was to present an alternative approach to distinguish original from fake perfumes by means of the investigation of sodium, potassium, chloride ions, and ethanol contents by chemometric tools. For this, 50 perfumes were used (25 original and 25 counterfeit) for the analysis of ions (ion chromatography) and ethanol (gas chromatography). The results demonstrated that the fake perfume had low levels of ethanol and high levels of chloride compared to the original product. The data were treated by chemometric tools such as principal component analysis and linear discriminant analysis. This study proved that the analysis of ethanol is an effective method of distinguishing original from the fake products, and it may potentially be used to assist legal authorities in such cases. © 2016 American Academy of Forensic Sciences.

Exploiting the synergistic effect of concurrent data signals: Low-level fusion of liquid chromatographic with dual detection data.

PubMed

Teglia, Carla M; Azcarate, Silvana M; Alcaráz, Mirta R; Goicoechea, Héctor C; Culzoni, María J

2018-08-15

A low-level data fusion strategy was developed and implemented for data processing of second-order liquid chromatographic data with dual detection, i.e. absorbance and fluorescence monitoring. The synergistic effect of coupling individual information provided by two different detectors was evaluated by analyzing the results gathered after the application of a series of data preprocessing steps and chemometric resolution. The chemometric modeling involved data analysis by MCR-ALS, PARAFAC and N-PLS. Their ability to handle the new data block was assessed through the estimation of the analytical figures of merits achieved in the prediction of a validation set containing fifteen fluorescent and non-fluorescent veterinary active ingredients that can be found in poultry litter. Eventually, the feasibility of the application of the fusion strategy to real poultry litter samples containing the studied compounds was verified. Copyright © 2018 Elsevier B.V. All rights reserved.

Chemometric analysis of voltammetric data on metal ion binding by selenocystine.

PubMed

Gusmão, Rui; Díaz-Cruz, José Manuel; Ariño, Cristina; Esteban, Miquel

2012-06-28

The behavior of selenocystine (SeCyst) alone or in the presence of various metal ions (Bi(3+), Cd(2+), Co(2+), Cu(2+), Cr(3+), Ni(2+), Pb(2+), and Zn(2+)) was studied using differential pulse voltammetry (DPV) over a wide pH range. Voltammetric data matrices were analyzed using chemometric tools recently developed for nonlinear data: pHfit and Gaussian Peak Adjustment (GPA). Under the experimental conditions tested, no evidence was found for the formation of metal complexes with Bi(3+), Cu(2+), Cr(3+), and Pb(2+). In contrast, SeCyst formed electroinactive complexes with Co(2+) and Ni(2+) and kinetically inert but electroactive complexes with Cd(2+) and Zn(2+). Titrations with Cd(2+), Co(2+), Ni(2+), and Zn(2+) produced data that were reasonably consistent with the formation of stable 1:1 M(SeCyst) complexes.

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

PubMed

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

2014-06-05

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochloride.

PubMed

Katsarov, Plamen; Gergov, Georgi; Alin, Aylin; Pilicheva, Bissera; Al-Degs, Yahya; Simeonov, Vasil; Kassarova, Margarita

2018-03-01

The prediction power of partial least squares (PLS) and multivariate curve resolution-alternating least squares (MCR-ALS) methods have been studied for simultaneous quantitative analysis of the binary drug combination - doxylamine succinate and pyridoxine hydrochloride. Analysis of first-order UV overlapped spectra was performed using different PLS models - classical PLS1 and PLS2 as well as partial robust M-regression (PRM). These linear models were compared to MCR-ALS with equality and correlation constraints (MCR-ALS-CC). All techniques operated within the full spectral region and extracted maximum information for the drugs analysed. The developed chemometric methods were validated on external sample sets and were applied to the analyses of pharmaceutical formulations. The obtained statistical parameters were satisfactory for calibration and validation sets. All developed methods can be successfully applied for simultaneous spectrophotometric determination of doxylamine and pyridoxine both in laboratory-prepared mixtures and commercial dosage forms.

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

NASA Astrophysics Data System (ADS)

Verma, Neha; Kumar, Raj; Sharma, Vishal

2018-05-01

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

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

PubMed

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

2015-01-01

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

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

PubMed

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

2017-05-01

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

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

PubMed

Panda, Pritipadma; Dash, Priyanka; Ghosh, Goutam

2018-03-01

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

Determination of butter adulteration with margarine using Raman spectroscopy.

PubMed

Uysal, Reyhan Selin; Boyaci, Ismail Hakki; Genis, Hüseyin Efe; Tamer, Ugur

2013-12-15

In this study, adulteration of butter with margarine was analysed using Raman spectroscopy combined with chemometric methods (principal component analysis (PCA), principal component regression (PCR), partial least squares (PLS)) and artificial neural networks (ANNs). Different butter and margarine samples were mixed at various concentrations ranging from 0% to 100% w/w. PCA analysis was applied for the classification of butters, margarines and mixtures. PCR, PLS and ANN were used for the detection of adulteration ratios of butter. Models were created using a calibration data set and developed models were evaluated using a validation data set. The coefficient of determination (R(2)) values between actual and predicted values obtained for PCR, PLS and ANN for the validation data set were 0.968, 0.987 and 0.978, respectively. In conclusion, a combination of Raman spectroscopy with chemometrics and ANN methods can be applied for testing butter adulteration. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

PubMed

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

2007-04-01

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

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

PubMed

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

2013-01-01

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

Prediction of Mass Spectral Response Factors from Predicted Chemometric Data for Druglike Molecules

NASA Astrophysics Data System (ADS)

Cramer, Christopher J.; Johnson, Joshua L.; Kamel, Amin M.

2017-02-01

A method is developed for the prediction of mass spectral ion counts of drug-like molecules using in silico calculated chemometric data. Various chemometric data, including polar and molecular surface areas, aqueous solvation free energies, and gas-phase and aqueous proton affinities were computed, and a statistically significant relationship between measured mass spectral ion counts and the combination of aqueous proton affinity and total molecular surface area was identified. In particular, through multilinear regression of ion counts on predicted chemometric data, we find that log10(MS ion counts) = -4.824 + c 1•PA + c 2•SA, where PA is the aqueous proton affinity of the molecule computed at the SMD(aq)/M06-L/MIDI!//M06-L/MIDI! level of electronic structure theory, SA is the total surface area of the molecule in its conjugate base form, and c 1 and c 2 have values of -3.912 × 10-2 mol kcal-1 and 3.682 × 10-3 Å-2. On a 66-molecule training set, this regression exhibits a multiple R value of 0.791 with p values for the intercept, c 1, and c 2 of 1.4 × 10-3, 4.3 × 10-10, and 2.5 × 10-6, respectively. Application of this regression to an 11-molecule test set provides a good correlation of prediction with experiment ( R = 0.905) albeit with a systematic underestimation of about 0.2 log units. This method may prove useful for semiquantitative analysis of drug metabolites for which MS response factors or authentic standards are not readily available.

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

PubMed

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-04-15

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

Screening soy hydrolysates for the production of a recombinant therapeutic protein in commercial cell line by combined approach of near-infrared spectroscopy and chemometrics.

PubMed

Li, Guiyang; Wen, Zai-Qing

2013-03-01

Soy hydrolysates are widely used as the major nutrient sources for cell culture processes for industrial manufacturing of therapeutic recombinant proteins. The primary goal of this study was to develop a spectroscopy based chemometric method, a partial least squares (PLS), to screen soy hydrolysates for better yield of protein production (titers) in cell culture medium. Harvest titer values of 29 soy hydrolysate lots with production yield between 490 and 1,350 mg/L were obtained from shake flask models or from manufacture engineering runs. The soy hydrolysate samples were measured by near-infrared (NIR) in reflectance mode using an infrared fiber optic probe. The fiber optic probe could easily enable in situ measurement of the soy hydrolysates for convenient raw material screening. The best PLS calibration has a determination coefficient of R (2) = 0.887 utilizing no spectral preprocessing, the two spectral ranges of 10,000-5,376 cm(-1) and 4,980-4,484 cm(-1), and a rank of 6 factors. The cross-validation of the model resulted in a determination coefficient of R (2) = 0.741 between the predicted and actual titer values with an average standard deviation of 72 mg/L. Compared with the resource demanding shake flask model, the combination of NIR and chemometric modeling provides a convenient method for soy hydrolysate screening with the advantage of fast speed, low cost and non-destructive.

Improving reliability of chemometric models for authentication of species origin of heparin by switching from 1D to 2D NMR experiments.

PubMed

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

2018-05-10

Nuclear magnetic resonance (NMR) spectroscopy is regarded as one of the most powerful and versatile analytical approaches to assure the quality of heparin preparations. In particular, it was recently demonstrated that by using 1 H NMR coupled with chemometrics heparin and low molecular weight heparin (LMWH) samples derived from three major animal species (porcine, ovine and bovine) can be differentiated [Y.B. Monakhova et al. J. Pharm. Anal. 149 (2018) 114-119]. In this study, significant improvement of existing chemometric models was achieved by switching to 2D NMR experiments (heteronuclear multiple-quantum correlation (HMQC) and diffusion-ordered spectroscopy (DOSY)). Two representative data sets (sixty-nine heparin and twenty-two LMWH) belonged to different batches and distributed by different commercial companies were investigated. A trend for animal species differentiation was observed in the principal component analysis (PCA) score plot built based on the DOSY data. A superior model was constructed using HMQC experiments, where individual heparin (LMWH) clusters as well as their blends were clearly differentiated. The predictive power of different classification methods as well as unsupervised techniques (independent components analysis, ICA) clearly proved applicability of the model for routine heparin and LMWH analysis. The switch from 1D to 2D NMR techniques provides a wealth of additional information, which is beneficial for multivariate modeling of NMR spectroscopic data for heparin preparations. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed

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

2017-05-10

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

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

NASA Astrophysics Data System (ADS)

Kumar, Raj; Sharma, Vishal

2017-03-01

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%).

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

PubMed

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

2018-11-01

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

Development and validation of simple spectrophotometric and chemometric methods for simultaneous determination of empagliflozin and metformin: Applied to recently approved pharmaceutical formulation

NASA Astrophysics Data System (ADS)

Ayoub, Bassam M.

2016-11-01

New univariate spectrophotometric method and multivariate chemometric approach were developed and compared for simultaneous determination of empagliflozin and metformin manipulating their zero order absorption spectra with application on their pharmaceutical preparation. Sample enrichment technique was used to increase concentration of empagliflozin after extraction from tablets to allow its simultaneous determination with metformin without prior separation. Validation parameters according to ICH guidelines were satisfactory over the concentration range of 2-12 μg mL- 1 for both drugs using simultaneous equation with LOD values equal to 0.20 μg mL- 1 and 0.19 μg mL- 1, LOQ values equal to 0.59 μg mL- 1 and 0.58 μg mL- 1 for empagliflozin and metformin, respectively. While the optimum results for the chemometric approach using partial least squares method (PLS-2) were obtained using concentration range of 2-10 μg mL- 1. The optimized validated methods are suitable for quality control laboratories enable fast and economic determination of the recently approved pharmaceutical combination Synjardy® tablets.

Simultaneous determination of α-asarone and β-asarone in Acorus tatarinowii using excitation-emission matrix fluorescence coupled with chemometrics methods

NASA Astrophysics Data System (ADS)

Bai, Xue-Mei; Liu, Tie; Liu, De-Long; Wei, Yong-Ju

2018-02-01

A chemometrics-assisted excitation-emission matrix (EEM) fluorescence method was proposed for simultaneous determination of α-asarone and β-asarone in Acorus tatarinowii. Using the strategy of combining EEM data with chemometrics methods, the simultaneous determination of α-asarone and β-asarone in the complex Traditional Chinese medicine system was achieved successfully, even in the presence of unexpected interferents. The physical or chemical separation step was avoided due to the use of ;mathematical separation;. Six second-order calibration methods were used including parallel factor analysis (PARAFAC), alternating trilinear decomposition (ATLD), alternating penalty trilinear decomposition (APTLD), self-weighted alternating trilinear decomposition (SWATLD), the unfolded partial least-squares (U-PLS) and multidimensional partial least-squares (N-PLS) with residual bilinearization (RBL). In addition, HPLC method was developed to further validate the presented strategy. Consequently, for the validation samples, the analytical results obtained by six second-order calibration methods were almost accurate. But for the Acorus tatarinowii samples, the results indicated a slightly better predictive ability of N-PLS/RBL procedure over other methods.

An Introduction to Multivariate Curve Resolution-Alternating Least Squares: Spectrophotometric Study of the Acid-Base Equilibria of 8-Hydroxyquinoline-5-Sulfonic Acid

ERIC Educational Resources Information Center

Rodriguez-Rodriguez, Cristina; Amigo, Jose Manuel; Coello, Jordi; Maspoch, Santiago

2007-01-01

A spectrophotometric study of the acid-base equilibria of 8-hydroxyquinoline-5-sulfonic acid to describe the multivariate curve resolution-alternating least squares algorithm (MCR-ALS) is described. The algorithm provides a lot of information and hence is of great importance for the chemometrics research.

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

PubMed Central

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

2018-01-01

Background: Citri Reticulatae Pericarpium is the dried mature pericarp of Citrus reticulata Blanco which can be divided into “Chenpi” and “Guangchenpi.” “Guangchenpi” is the genuine Chinese medicinal material in Xinhui, Guangdong province; based on the greatest quality and least amount, it is most expensive among others. Hesperidin is used as the marker to identify Citri Reticulatae Pericarpium described in the Chinese Pharmacopoeia 2010. However, both “Chenpi” and “Guangchenpi” contain hesperidin so that it is impossible to differentiate them by measuring hesperidin. Objective: Our study aims to develop an efficient and accurate method to separate and identify “Guangchenpi” from other Citri Reticulatae Pericarpium. Materials and Methods: The genomic deoxyribonucleic acid (DNA) of all the materials was extracted and then the internal transcribed spacer 2 was amplified, sequenced, aligned, and analyzed. The secondary structures were created in terms of the database and website established by Jörg Schultz et al. High-performance liquid chromatography-diode array detection-electrospray Ionization/mass spectrometry (HPLC-DAD-ESI-MS)/MS coupled with chemometric analysis was applied to compare the differences in chemical profiles of the three kinds of Citri Reticulatae Pericarpium. Results: A total of 22 samples were classified into three groups. The results of DNA barcoding were in accordance with principal component analysis and hierarchical cluster analysis. Eight compounds were deduced from HPLC-DAD-ESI-MS/MS. Conclusions: This method is a reliable and effective tool to differentiate the three Citri Reticulatae Pericarpium. SUMMARY The internal transcribed spacer 2 regions and the secondary structure among three kinds of Citri Reticulatae Pericarpium varied considerablyAll the 22 samples were analyzed by high-performance liquid chromatography (HPLC) to obtain the chemical profilesPrincipal component analysis and hierarchical cluster analysis were used in the chemometric analysisdeoxyribonucleic acid barcoding and HPLC-diode array detection-electrospray ionization/mass spectrometry/MS coupled with chemometric analysis provided an accurate and strong proof to identify these three herbs. Abbreviations used: CTAB: Hexadecyltrimethylammonium bromide, DNA: Deoxyribonucleic acid, ITS2: Internal transcribed spacer 2, PCR: Polymerase chain reaction. PMID:29576703

Multivariate figures of merit (FOM) investigation on the effect of instrument parameters on a Fourier transform-near infrared spectroscopy (FT-NIRS) based content uniformity method on core tablets.

PubMed

Doddridge, Greg D; Shi, Zhenqi

2015-01-01

Since near infrared spectroscopy (NIRS) was introduced to the pharmaceutical industry, efforts have been spent to leverage the power of chemometrics to extract out the best possible signal to correlate with the analyte of the interest. In contrast, only a few studies addressed the potential impact of instrument parameters, such as resolution and co-adds (i.e., the number of averaged replicate spectra), on the method performance of error statistics. In this study, a holistic approach was used to evaluate the effect of the instrument parameters of a FT-NIR spectrometer on the performance of a content uniformity method with respect to a list of figures of merit. The figures of merit included error statistics, signal-to-noise ratio (S/N), sensitivity, analytical sensitivity, effective resolution, selectivity, limit of detection (LOD), and noise. A Bruker MPA FT-NIR spectrometer was used for the investigation of an experimental design in terms of resolution (4 cm(-1) and 32 cm(-1)) and co-adds (256 and 16) plus a center point at 8 cm(-1) and 32 co-adds. Given the balance among underlying chemistry, instrument parameters, chemometrics, and measurement time, 8 cm(-1) and 32 co-adds in combination with appropriate 2nd derivative preprocessing was found to fit best for the intended purpose as a content uniformity method. The considerations for optimizing both instrument parameters and chemometrics were proposed and discussed in order to maximize the method performance for its intended purpose for future NIRS method development in R&D. Copyright © 2014 Elsevier B.V. All rights reserved.

Conditions and chemometrics for the determination of heavy metals in natural and waste waters by stripping voltammetry with UV irradiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Volkova, V.N.; Zakharova, E.A.; Khustenko, L.A.

The number of supporting electrolytes for stripping voltammetry with photochemical oxygen deactivation was broadened. The following agents are recommended: formic, lactic, tartaric, citric, and malonic acids at pH 2-4; salts of lactic, tartaric, and citric acids at pH 6-7; and salts of lactic, tartaric, citric, and glutaric acids at pH 12-14. A rapid method was developed for simultaneously determining Zn, Cd, Pb, and Cu in a 0.5 M formic acid supporting electrolyte. The method is chemometrically sound and cost-effective.

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

PubMed

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

2016-05-15

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

Dynamic surface-enhanced Raman spectroscopy and Chemometric methods for fast detection and intelligent identification of methamphetamine and 3, 4-Methylenedioxy methamphetamine in human urine

NASA Astrophysics Data System (ADS)

Weng, Shizhuang; Dong, Ronglu; Zhu, Zede; Zhang, Dongyan; Zhao, Jinling; Huang, Linsheng; Liang, Dong

2018-01-01

Conventional Surface-Enhanced Raman Spectroscopy (SERS) for fast detection of drugs in urine on the portable Raman spectrometer remains challenges because of low sensitivity and unreliable Raman signal, and spectra process with manual intervention. Here, we develop a novel detection method of drugs in urine using chemometric methods and dynamic SERS (D-SERS) with mPEG-SH coated gold nanorods (GNRs). D-SERS combined with the uniform GNRs can obtain giant enhancement, and the signal is also of high reproducibility. On the basis of the above advantages, we obtained the spectra of urine, urine with methamphetamine (MAMP), urine with 3, 4-Methylenedioxy Methamphetamine (MDMA) using D-SERS. Simultaneously, some chemometric methods were introduced for the intelligent and automatic analysis of spectra. Firstly, the spectra at the critical state were selected through using K-means. Then, the spectra were proposed by random forest (RF) with feature selection and principal component analysis (PCA) to develop the recognition model. And the identification accuracy of model were 100%, 98.7% and 96.7%, respectively. To validate the effect in practical issue further, the drug abusers'urine samples with 0.4, 3, 30 ppm MAMP were detected using D-SERS and identified by the classification model. The high recognition accuracy of > 92.0% can meet the demand of practical application. Additionally, the parameter optimization of RF classification model was simple. Compared with the general laboratory method, the detection process of urine's spectra using D-SERS only need 2 mins and 2 μL samples volume, and the identification of spectra based on chemometric methods can be finish in seconds. It is verified that the proposed approach can provide the accurate, convenient and rapid detection of drugs in urine.

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

PubMed Central

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

2016-01-01

The capability of a phthalocyanine-based voltammetric electronic tongue to analyze strong alcoholic beverages has been evaluated and compared with the performance of spectroscopic techniques coupled to chemometrics. Nalewka Polish liqueurs prepared from five apple varieties have been used as a model of strong liqueurs. Principal Component Analysis has demonstrated that the best discrimination between liqueurs prepared from different apple varieties is achieved using the e-tongue and UV-Vis spectroscopy. Raman spectra coupled to chemometrics have not been efficient in discriminating liqueurs. The calculated Euclidean distances and the k-Nearest Neighbors algorithm (kNN) confirmed these results. The main advantage of the e-tongue is that, using PLS-1, good correlations have been found simultaneously with the phenolic content measured by the Folin–Ciocalteu method (R2 of 0.97 in calibration and R2 of 0.93 in validation) and also with the density, a marker of the alcoholic content method (R2 of 0.93 in calibration and R2 of 0.88 in validation). UV-Vis coupled with chemometrics has shown good correlations only with the phenolic content (R2 of 0.99 in calibration and R2 of 0.99 in validation) but correlations with the alcoholic content were low. Raman coupled with chemometrics has shown good correlations only with density (R2 of 0.96 in calibration and R2 of 0.85 in validation). In summary, from the three holistic methods evaluated to analyze strong alcoholic liqueurs, the voltammetric electronic tongue using phthalocyanines as sensing elements is superior to Raman or UV-Vis techniques because it shows an excellent discrimination capability and remarkable correlations with both antioxidant capacity and alcoholic content—the most important parameters to be measured in this type of liqueurs.  PMID:27735832

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

PubMed

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

2016-10-09

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

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

PubMed

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

2018-05-01

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

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

PubMed

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

2016-01-01

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

Recent advances in the use of NIR spectroscopy for qualitative control and protection of extra virgin olive oil

USDA-ARS?s Scientific Manuscript database

Recent studies on the use of near infrared (NIR) spectroscopy for the qualitative characterization of extra virgin olive oil, are reported and discussed in this paper. Research results confirms that NIR spectroscopy, combined with chemometric data analysis, allows to simultaneously evaluate all qual...

Learning Principal Component Analysis by Using Data from Air Quality Networks

ERIC Educational Resources Information Center

Perez-Arribas, Luis Vicente; Leon-González, María Eugenia; Rosales-Conrado, Noelia

2017-01-01

With the final objective of using computational and chemometrics tools in the chemistry studies, this paper shows the methodology and interpretation of the Principal Component Analysis (PCA) using pollution data from different cities. This paper describes how students can obtain data on air quality and process such data for additional information…

Chemometric correlation of shelf life, quality measurements, and visible-near infrared spectra of pasteurized eggs

USDA-ARS?s Scientific Manuscript database

A twelve week study was conducted on the egg albumen from both pasteurized and non-pasteurized shell eggs using visible-near infrared spectroscopy. Correlation of the chemical changes detected in the spectra to the measurement of Haugh units (measure of interior egg quality) was carried out using pr...

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

PubMed

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

2012-06-01

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

Discrimination of healthy and osteoarthritic articular cartilage by Fourier transform infrared imaging and Fisher’s discriminant analysis

PubMed Central

Mao, Zhi-Hua; Yin, Jian-Hua; Zhang, Xue-Xi; Wang, Xiao; Xia, Yang

2016-01-01

Fourier transform infrared spectroscopic imaging (FTIRI) technique can be used to obtain the quantitative information of content and spatial distribution of principal components in cartilage by combining with chemometrics methods. In this study, FTIRI combining with principal component analysis (PCA) and Fisher’s discriminant analysis (FDA) was applied to identify the healthy and osteoarthritic (OA) articular cartilage samples. Ten 10-μm thick sections of canine cartilages were imaged at 6.25μm/pixel in FTIRI. The infrared spectra extracted from the FTIR images were imported into SPSS software for PCA and FDA. Based on the PCA result of 2 principal components, the healthy and OA cartilage samples were effectively discriminated by the FDA with high accuracy of 94% for the initial samples (training set) and cross validation, as well as 86.67% for the prediction group. The study showed that cartilage degeneration became gradually weak with the increase of the depth. FTIRI combined with chemometrics may become an effective method for distinguishing healthy and OA cartilages in future. PMID:26977354

Chemometric studies on potential larvicidal compounds against Aedes aegypti.

PubMed

Scotti, Luciana; Scotti, Marcus Tullius; Silva, Viviane Barros; Santos, Sandra Regina Lima; Cavalcanti, Sócrates C H; Mendonça, Francisco J B

2014-03-01

The mosquito Aedes aegypti (Diptera, Culicidae) is the vector of yellow and dengue fever. In this study, chemometric tools, such as, Principal Component Analysis (PCA), Consensus PCA (CPCA), and Partial Least Squares Regression (PLS), were applied to a set of fifty five active compounds against Ae. aegypti larvae, which includes terpenes, cyclic alcohols, phenolic compounds, and their synthetic derivatives. The calculations were performed using the VolSurf+ program. CPCA analysis suggests that the higher weight blocks of descriptors were SIZE/SHAPE, DRY, and H2O. The PCA was generated with 48 descriptors selected from the previous blocks. The scores plot showed good separation between more and less potent compounds. The first two PCs accounted for over 60% of the data variance. The best model obtained in PLS, after validation leave-one-out, exhibited q(2) = 0.679 and r(2) = 0.714. External prediction model was R(2) = 0.623. The independent variables having a hydrophobic profile were strongly correlated to the biological data. The interaction maps generated with the GRID force field showed that the most active compounds exhibit more interaction with the DRY probe.

Direct analysis of six antibiotics in wastewater samples using rapid high-performance liquid chromatography coupled with diode array detector: a chemometric study towards green analytical chemistry.

PubMed

Vosough, Maryam; Rashvand, Masoumeh; Esfahani, Hadi M; Kargosha, Kazem; Salemi, Amir

2015-04-01

In this work, a rapid HPLC-DAD method has been developed for the analysis of six antibiotics (amoxicillin, metronidazole, sulfamethoxazole, ofloxacine, sulfadiazine and sulfamerazine) in the sewage treatment plant influent and effluent samples. Decreasing the chromatographic run time to less than 4 min as well as lowering the cost per analysis, were achieved through direct injection of the samples into the HPLC system followed by chemometric analysis. The problem of the complete separation of the analytes from each other and/or from the matrix ingredients was resolved as a posteriori. The performance of MCR/ALS and U-PLS/RBL, as second-order algorithms, was studied and comparable results were obtained from implication of these modeling methods. It was demonstrated that the proposed methods could be used promisingly as green analytical strategies for detection and quantification of the targeted pollutants in wastewater samples while avoiding the more complicated high cost instrumentations. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed

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

2018-10-15

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

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

PubMed

Bajoub, Aadil; Medina-Rodríguez, Santiago; Olmo-García, Lucía; Ajal, El Amine; Monasterio, Romina P; Hanine, Hafida; Fernández-Gutiérrez, Alberto; Carrasco-Pancorbo, Alegría

2016-12-28

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

A chemometric approach for optimizing protein covalent immobilization on magnetic core-shell nanoparticles in view of an alternative immunoassay.

PubMed

Teste, Bruno; Vial, Jérôme; Descroix, Stéphanie; Georgelin, Thomas; Siaugue, Jean-Michel; Petr, Jan; Varenne, Anne; Hennion, Marie-Claire

2010-06-15

A chemometric approach was developed to optimize the grafting of a bovine milk allergen: alpha-Lactalbumin (alpha-Lac) on colloidal functionalized magnetic core-shell nanoparticles (MCSNP). Such nanoparticles, functionalized with polyethyleneglycol and amino groups, exhibit a 30nm physical diameter and behave as a quasi-homogeneous system. The alpha-Lac immobilization was achieved through the covalent binding between MCSNP amino groups and alpha-Lac carboxylic moieties using the well-known tandem carbodiimide (EDC) and hydroxysulfosuccinimide (NHS). In this study, a chemometric approach was employed to highlight the parameters influencing the number of grafted proteins on the MCSNP. Three factors were evaluated: the ratio in concentration between EDC and alpha-Lac, between NHS and EDC and the concentration of alpha-Lac. After a first full factorial design to delimit the region of the space where the optimum could be located, a central composite design was then carried out to predict the best grafting conditions. It was established and experimentally confirmed that the optimum parameters are [EDC]/[alpha-Lac]=25; [NHS]/[EDC]=1.55 and alpha-Lac=24.85nmolmL(-1). In these optimal conditions, MCSNP surface was successfully saturated with alpha-Lac (34 alpha-Lac/MCSNP) with a high reproducibility (RSD=2%). The colloidal stability of MCSNP grafted with alpha-Lac as well as the immunological interactions using anti alpha-Lac antibody were then investigated in different buffers. The results emphasized that a 50mM MES buffer (pH 6) allows an efficient immune capture and a satisfying colloidal stability which provide an immunological interaction in homogeneous liquid phase.

Application of SWIR hyperspectral imaging and chemometrics for identification of aflatoxin B1 contaminated maize kernels

NASA Astrophysics Data System (ADS)

Kimuli, Daniel; Wang, Wei; Wang, Wei; Jiang, Hongzhe; Zhao, Xin; Chu, Xuan

2018-03-01

A short-wave infrared (SWIR) hyperspectral imaging system (1000-2500 nm) combined with chemometric data analysis was used to detect aflatoxin B1 (AFB1) on surfaces of 600 kernels of four yellow maize varieties from different States of the USA (Georgia, Illinois, Indiana and Nebraska). For each variety, four AFB1 solutions (10, 20, 100 and 500 ppb) were artificially deposited on kernels and a control group was generated from kernels treated with methanol solution. Principal component analysis (PCA), partial least squares discriminant analysis (PLSDA) and factorial discriminant analysis (FDA) were applied to explore and classify maize kernels according to AFB1 contamination. PCA results revealed partial separation of control kernels from AFB1 contaminated kernels for each variety while no pattern of separation was observed among pooled samples. A combination of standard normal variate and first derivative pre-treatments produced the best PLSDA classification model with accuracy of 100% and 96% in calibration and validation, respectively, from Illinois variety. The best AFB1 classification results came from FDA on raw spectra with accuracy of 100% in calibration and validation for Illinois and Nebraska varieties. However, for both PLSDA and FDA models, poor AFB1 classification results were obtained for pooled samples relative to individual varieties. SWIR spectra combined with chemometrics and spectra pre-treatments showed the possibility of detecting maize kernels of different varieties coated with AFB1. The study further suggests that increase of maize kernel constituents like water, protein, starch and lipid in a pooled sample may have influence on detection accuracy of AFB1 contamination.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Detection of Poisonous Herbs by Terahertz Time-Domain Spectroscopy

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

PubMed

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

2016-09-01

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

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

PubMed

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

2009-07-15

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

Improved Discrimination for Brassica Vegetables Treated with Agricultural Fertilizers Using a Combined Chemometric Approach.

PubMed

Yuan, Yuwei; Hu, Guixian; Chen, Tianjin; Zhao, Ming; Zhang, Yongzhi; Li, Yong; Xu, Xiahong; Shao, Shengzhi; Zhu, Jiahong; Wang, Qiang; Rogers, Karyne M

2016-07-20

Multielement and stable isotope (δ(13)C, δ(15)N, δ(2)H, δ(18)O, (207)Pb/(206)Pb, and (208)Pb/(206)Pb) analyses were combined to provide a new chemometric approach to improve the discrimination between organic and conventional Brassica vegetable production. Different combinations of organic and conventional fertilizer treatments were used to demonstrate this authentication approach using Brassica chinensis planted in experimental test pots. Stable isotope analyses (δ(15)N and δ(13)C) of B. chinensis using elemental analyzer-isotope ratio mass spectrometry easily distinguished organic and chemical fertilizer treatments. However, for low-level application fertilizer treatments, this dual isotope approach became indistinguishable over time. Using a chemometric approach (combined isotope and elemental approach), organic and chemical fertilizer mixes and low-level applications of synthetic and organic fertilizers were detectable in B. chinensis and their associated soils, improving the detection limit beyond the capacity of individual isotopes or elemental characterization. LDA shows strong promise as an improved method to discriminate genuine organic Brassica vegetables from produce treated with chemical fertilizers and could be used as a robust test for organic produce authentication.

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

PubMed

Challa, Shruthi; Potumarthi, Ravichandra

2013-01-01

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

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.

PubMed

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.

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

NASA Astrophysics Data System (ADS)

Glavanović, Siniša; Glavanović, Marija; Tomišić, Vladislav

2016-03-01

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

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

PubMed

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

2017-04-15

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

Metabolic fingerprint of Brazilian maize landraces silk (stigma/styles) using NMR spectroscopy and chemometric methods.

PubMed

Kuhnen, Shirley; Bernardi Ogliari, Juliana; Dias, Paulo Fernando; da Silva Santos, Maiara; Ferreira, Antônio Gilberto; Bonham, Connie C; Wood, Karl Vernon; Maraschin, Marcelo

2010-02-24

Aqueous extract from maize silks is used by traditional medicine for the treatment of several ailments, mainly related to the urinary system. This work focuses on the application of NMR spectroscopy and chemometric analysis for the determination of metabolic fingerprint and pattern recognition of silk extracts from seven maize landraces cultivated in southern Brazil. Principal component analysis (PCA) of the (1)H NMR data set showed clear discrimination among the maize varieties by PC1 and PC2, pointing out three distinct metabolic profiles. Target compounds analysis showed significant differences (p < 0.05) in the contents of protocatechuic acid, gallic acid, t-cinnamic acid, and anthocyanins, corroborating the discrimination of the genotypes in this study as revealed by PCA analysis. Thus the combination of (1)H NMR and PCA is a useful tool for the discrimination of maize silks in respect to their chemical composition, including rapid authentication of the raw material of current pharmacological interest.

The in vitro Antimicrobial Activity and Chemometric Modelling of 59 Commercial Essential Oils against Pathogens of Dermatological Relevance.

PubMed

Orchard, Ané; Sandasi, Maxleene; Kamatou, Guy; Viljoen, Alvaro; van Vuuren, Sandy

2017-01-01

This study reports on the inhibitory concentration of 59 commercial essential oils recommended for dermatological conditions, and identifies putative compounds responsible for antimicrobial activity. Essential oils were investigated for antimicrobial activity using minimum inhibitory concentration assays. Ten essential oils were identified as having superior antimicrobial activity. The essential oil compositions were determined using gas chromatography coupled to mass spectrometry and the data analysed with the antimicrobial activity using multivariate tools. Orthogonal projections to latent structures models were created for seven of the pathogens. Eugenol was identified as the main biomarker responsible for antimicrobial activity in the majority of the essential oils. The essential oils mostly displayed noteworthy antimicrobial activity, with five oils displaying broad-spectrum activity against the 13 tested micro-organisms. The antimicrobial efficacies of the essential oils highlight their potential in treating dermatological infections and through chemometric modelling, bioactive volatiles have been identified. © 2017 Wiley-VHCA AG, Zurich, Switzerland.

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

PubMed

Jiang, Hai; Yang, Liu; Xing, Xudong; Yan, Meiling; Guo, Xinyue; Yang, Bingyou; Wang, Qiuhong; Kuang, Haixue

2018-01-25

As a valuable herbal medicine, the fruits of Xanthium strumarium L. (Xanthii Fructus) have been widely used in raw and processed forms to achieve different therapeutic effects in practice. In this study, a comprehensive strategy was proposed for evaluating the active components in 30 batches of raw and processed Xanthii Fructus (RXF and PXF) samples, based on high-performance liquid chromatography coupled with photodiode array detection (HPLC-PDA). Twelve common peaks were detected and eight compounds of caffeoylquinic acids were simultaneously quantified in RXF and PXF. All the analytes were detected with satisfactory linearity (R² > 0.9991) over wide concentration ranges. Simultaneously, the chemically latent information was revealed by hierarchical cluster analysis (HCA) and principal component analysis (PCA). The results suggest that there were significant differences between RXF and PXF from different regions in terms of the content of eight caffeoylquinic acids. Potential chemical markers for XF were found during processing by chemometrics.

Multiple fingerprinting analyses in quality control of Cassiae Semen polysaccharides.

PubMed

Cheng, Jing; He, Siyu; Wan, Qiang; Jing, Pu

2018-03-01

Quality control issue overshadows potential health benefits of Cassiae Semen due to the analytic limitations. In this study, multiple-fingerprint analysis integrated with several chemometrics was performed to assess the polysaccharide quality of Cassiae Semen harvested from different locations. FT-IR, HPLC, and GC fingerprints of polysaccharide extracts from the authentic source were established as standard profiles, applying to assess the quality of foreign sources. Analyses of FT-IR fingerprints of polysaccharide extracts using either Pearson correlation analysis or principal component analysis (PCA), or HPLC fingerprints of partially hydrolyzed polysaccharides with PCA, distinguished the foreign sources from the authentic source. However, HPLC or GC fingerprints of completely hydrolyzed polysaccharides couldn't identify all foreign sources and the methodology using GC is quite limited in determining the monosaccharide composition. This indicates that FT-IR/HPLC fingerprints of non/partially-hydrolyzed polysaccharides, respectively, accompanied by multiple chemometrics methods, might be potentially applied in detecting and differentiating sources of Cassiae Semen. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed

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

2015-09-01

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

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

PubMed

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

2002-01-01

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

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

PubMed

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

2014-01-01

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

Application of linear discriminant analysis and Attenuated Total Reflectance Fourier Transform Infrared microspectroscopy for diagnosis of colon cancer.

PubMed

Khanmohammadi, Mohammadreza; Bagheri Garmarudi, Amir; Samani, Simin; Ghasemi, Keyvan; Ashuri, Ahmad

2011-06-01

Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) microspectroscopy was applied for detection of colon cancer according to the spectral features of colon tissues. Supervised classification models can be trained to identify the tissue type based on the spectroscopic fingerprint. A total of 78 colon tissues were used in spectroscopy studies. Major spectral differences were observed in 1,740-900 cm(-1) spectral region. Several chemometric methods such as analysis of variance (ANOVA), cluster analysis (CA) and linear discriminate analysis (LDA) were applied for classification of IR spectra. Utilizing the chemometric techniques, clear and reproducible differences were observed between the spectra of normal and cancer cases, suggesting that infrared microspectroscopy in conjunction with spectral data processing would be useful for diagnostic classification. Using LDA technique, the spectra were classified into cancer and normal tissue classes with an accuracy of 95.8%. The sensitivity and specificity was 100 and 93.1%, respectively.

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

PubMed

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

2015-04-01

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

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

PubMed

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

2017-04-15

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

Classification of inflammatory bowel diseases by means of Raman spectroscopic imaging of epithelium cells

NASA Astrophysics Data System (ADS)

Bielecki, Christiane; Bocklitz, Thomas W.; Schmitt, Michael; Krafft, Christoph; Marquardt, Claudio; Gharbi, Akram; Knösel, Thomas; Stallmach, Andreas; Popp, Juergen

2012-07-01

We report on a Raman microspectroscopic characterization of the inflammatory bowel diseases (IBD) Crohn's disease (CD) and ulcerative colitis (UC). Therefore, Raman maps of human colon tissue sections were analyzed by utilizing innovative chemometric approaches. First, support vector machines were applied to highlight the tissue morphology (=Raman spectroscopic histopathology). In a second step, the biochemical tissue composition has been studied by analyzing the epithelium Raman spectra of sections of healthy control subjects (n=11), subjects with CD (n=14), and subjects with UC (n=13). These three groups exhibit significantly different molecular specific Raman signatures, allowing establishment of a classifier (support-vector-machine). By utilizing this classifier it was possible to separate between healthy control patients, patients with CD, and patients with UC with an accuracy of 98.90%. The automatic design of both classification steps (visualization of the tissue morphology and molecular classification of IBD) paves the way for an objective clinical diagnosis of IBD by means of Raman spectroscopy in combination with chemometric approaches.

Characterization and geographical discrimination of commercial Citrus spp. honeys produced in different Mediterranean countries based on minerals, volatile compounds and physicochemical parameters, using chemometrics.

PubMed

Karabagias, Ioannis K; Louppis, Artemis P; Karabournioti, Sofia; Kontakos, Stavros; Papastephanou, Chara; Kontominas, Michael G

2017-02-15

The objective of the present study was: i) to characterize Mediterranean citrus honeys based on conventional physicochemical parameter values, volatile compounds, and mineral content ii) to investigate the potential of above parameters to differentiate citrus honeys according to geographical origin using chemometrics. Thus, 37 citrus honey samples were collected during harvesting periods 2013 and 2014 from Greece, Egypt, Morocco, and Spain. Conventional physicochemical and CIELAB colour parameters were determined using official methods of analysis and the Commission Internationale de l' Eclairage recommendations, respectively. Minerals were determined using ICP-OES and volatiles using SPME-GC/MS. Results showed that honey samples analyzed, met the standard quality criteria set by the EU and were successfully classified according to geographical origin. Correct classification rates were 97.3% using 8 physicochemical parameter values, 86.5% using 15 volatile compound data and 83.8% using 13 minerals. Copyright © 2016 Elsevier Ltd. All rights reserved.

Free variable selection QSPR study to predict 19F chemical shifts of some fluorinated organic compounds using Random Forest and RBF-PLS methods

NASA Astrophysics Data System (ADS)

Goudarzi, Nasser

2016-04-01

In this work, two new and powerful chemometrics methods are applied for the modeling and prediction of the 19F chemical shift values of some fluorinated organic compounds. The radial basis function-partial least square (RBF-PLS) and random forest (RF) are employed to construct the models to predict the 19F chemical shifts. In this study, we didn't used from any variable selection method and RF method can be used as variable selection and modeling technique. Effects of the important parameters affecting the ability of the RF prediction power such as the number of trees (nt) and the number of randomly selected variables to split each node (m) were investigated. The root-mean-square errors of prediction (RMSEP) for the training set and the prediction set for the RBF-PLS and RF models were 44.70, 23.86, 29.77, and 23.69, respectively. Also, the correlation coefficients of the prediction set for the RBF-PLS and RF models were 0.8684 and 0.9313, respectively. The results obtained reveal that the RF model can be used as a powerful chemometrics tool for the quantitative structure-property relationship (QSPR) studies.

Automatic detection and classification of EOL-concrete and resulting recovered products by hyperspectral imaging

NASA Astrophysics Data System (ADS)

Palmieri, Roberta; Bonifazi, Giuseppe; Serranti, Silvia

2014-05-01

The recovery of materials from Demolition Waste (DW) represents one of the main target of the recycling industry and the its characterization is important in order to set up efficient sorting and/or quality control systems. End-Of-Life (EOL) concrete materials identification is necessary to maximize DW conversion into useful secondary raw materials, so it is fundamental to develop strategies for the implementation of an automatic recognition system of the recovered products. In this paper, HyperSpectral Imaging (HSI) technique was applied in order to detect DW composition. Hyperspectral images were acquired by a laboratory device equipped with a HSI sensing device working in the near infrared range (1000-1700 nm): NIR Spectral Camera™, embedding an ImSpector™ N17E (SPECIM Ltd, Finland). Acquired spectral data were analyzed adopting the PLS_Toolbox (Version 7.5, Eigenvector Research, Inc.) under Matlab® environment (Version 7.11.1, The Mathworks, Inc.), applying different chemometric methods: Principal Component Analysis (PCA) for exploratory data approach and Partial Least Square- Discriminant Analysis (PLS-DA) to build classification models. Results showed that it is possible to recognize DW materials, distinguishing recycled aggregates from contaminants (e.g. bricks, gypsum, plastics, wood, foam, etc.). The developed procedure is cheap, fast and non-destructive: it could be used to make some steps of the recycling process more efficient and less expensive.

Effect of varying postmortem deboning time and sampling position on visible and near infrared spectra of broiler breast filets

USDA-ARS?s Scientific Manuscript database

Visible-Near Infrared spectroscopy (Vis-NIR) was used to characterize broiler breast filets with varied deboning times and identify how the side and position of the sampling affects the chemometric analysis and prediction capabilities. This study served to identify what differences, if any, exist wh...

Kinetics of forming aldehydes in frying oils and their distribution in French fries revealed by LC-MS-based chemometrics

USDA-ARS?s Scientific Manuscript database

Aldehydes are major secondary lipid oxidation products (LOPs) from heating vegetable oils and deep frying. The routes and reactions that generate aldehydes have been extensively investigated, but the sequences and kinetics of their formation in oils are poorly defined. In this study, a platform comb...

Binding affinity toward human prion protein of some anti-prion compounds - Assessment based on QSAR modeling, molecular docking and non-parametric ranking.

PubMed

Kovačević, Strahinja; Karadžić, Milica; Podunavac-Kuzmanović, Sanja; Jevrić, Lidija

2018-01-01

The present study is based on the quantitative structure-activity relationship (QSAR) analysis of binding affinity toward human prion protein (huPrP C ) of quinacrine, pyridine dicarbonitrile, diphenylthiazole and diphenyloxazole analogs applying different linear and non-linear chemometric regression techniques, including univariate linear regression, multiple linear regression, partial least squares regression and artificial neural networks. The QSAR analysis distinguished molecular lipophilicity as an important factor that contributes to the binding affinity. Principal component analysis was used in order to reveal similarities or dissimilarities among the studied compounds. The analysis of in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) parameters was conducted. The ranking of the studied analogs on the basis of their ADMET parameters was done applying the sum of ranking differences, as a relatively new chemometric method. The main aim of the study was to reveal the most important molecular features whose changes lead to the changes in the binding affinities of the studied compounds. Another point of view on the binding affinity of the most promising analogs was established by application of molecular docking analysis. The results of the molecular docking were proven to be in agreement with the experimental outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data.

PubMed

Tomazzoli, Maíra M; Pai Neto, Remi D; Moresco, Rodolfo; Westphal, Larissa; Zeggio, Amelia R S; Specht, Leandro; Costa, Christopher; Rocha, Miguel; Maraschin, Marcelo

2015-12-01

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plant's resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( λ= 280-400 ηm), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data.

PubMed

Tomazzoli, Maíra Maciel; Pai Neto, Remi Dal; Moresco, Rodolfo; Westphal, Larissa; Zeggio, Amélia Regina Somensi; Specht, Leandro; Costa, Christopher; Rocha, Miguel; Maraschin, Marcelo

2015-10-21

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plant's resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis' chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds (λ = 280-400ηm), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Multi-way chemometric methodologies and applications: a central summary of our research work.

PubMed

Wu, Hai-Long; Nie, Jin-Fang; Yu, Yong-Jie; Yu, Ru-Qin

2009-09-14

Multi-way data analysis and tensorial calibration are gaining widespread acceptance with the rapid development of modern analytical instruments. In recent years, our group working in State Key Laboratory of Chemo/Biosensing and Chemometrics in Hunan University has carried out exhaustive scientific research work in this area, such as building more canonical symbol systems, seeking the inner mathematical cyclic symmetry property for trilinear or multilinear decomposition, suggesting a series of multi-way calibration algorithms, exploring the rank estimation of three-way trilinear data array and analyzing different application systems. In this present paper, an overview from second-order data to third-order data covering about theories and applications in analytical chemistry has been presented.

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

PubMed

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

2015-05-01

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

Quality Evaluation of Juniperus rigida Sieb. et Zucc. Based on Phenolic Profiles, Bioactivity, and HPLC Fingerprint Combined with Chemometrics

PubMed Central

Liu, Zehua; Wang, Dongmei; Li, Dengwu; Zhang, Shuai

2017-01-01

Juniperus rigida (J. rigida) which is endemic to East Asia, has traditionally been used as an ethnomedicinal plant in China. This study was undertaken to evaluate the quality of J. rigida samples derived from 11 primary regions in China. Ten phenolic compounds were simultaneously quantified using reversed-phase high-performance liquid chromatography (RP-HPLC), and chlorogenic acid, catechin, podophyllotoxin, and amentoflavone were found to be the main compounds in J. rigida needles, with the highest contents detected for catechin and podophyllotoxin. J. rigida from Jilin (S9, S10) and Liaoning (S11) exhibited the highest contents of phenolic profiles (total phenolics, total flavonoids and 10 phenolic compounds) and the strongest antioxidant and antibacterial activities, followed by Shaanxi (S2, S3). A similarity analysis (SA) demonstrated substantial similarities in fingerprint chromatograms, from which 14 common peaks were selected. The similarity values varied from 0.85 to 0.98. Chemometrics techniques, including hierarchical cluster analysis (HCA), principal component analysis (PCA), and discriminant analysis (DA), were further applied to facilitate accurate classification and quantification of the J. rigida samples derived from the 11 regions. The results supported HPLC data showing that all J. rigida samples exhibit considerable variations in phenolic profiles, and the samples were further clustered into three major groups coincident with their geographical regions of origin. In addition, two discriminant functions with a 100% discrimination ratio were constructed to further distinguish and classify samples with unknown membership on the basis of eigenvalues to allow optimal discrimination among the groups. Our comprehensive findings on matching phenolic profiles and bioactivities along with data from fingerprint chromatograms with chemometrics provide an effective tool for screening and quality evaluation of J. rigida and related medicinal preparations. PMID:28469573

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

PubMed

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

2017-02-15

Cannabis sativa L. (cannabis, Cannabaceae), popularly called marijuana, is one of the oldest plants known to man and it is the illicit drug most used worldwide. It also has been the subject of increasing discussions from the scientific and political points of view due to its medicinal properties. In recent years in Brazil, the form of cannabis drug trafficking has been changing and the Brazilian Federal Police has exponentially increased the number of seizures of cannabis seeds sent by the mail. This new form of trafficking encouraged the study of cannabis seeds seized germinated in a greenhouse through NIR spectroscopy combined with chemometrics. The plants were cultivated in a homemade greenhouse under controlled conditions. In three different growth periods (5.5weeks, 7.5weeks and 10weeks), they were harvested, dried, ground and directly analyzed. The iPCA was used to select the best NIR spectral range (4000-4375cm -1 ) in order to develop unsupervised and supervised methods. The PCA and HCA showed a good separation between the three groups of cannabis samples at different growth stages. The PLS-DA and SVM-DA classified the samples with good results in terms of sensitivity and specificity. The sensitivity and specificity for SVM-DA classification were equal to unity. This separation may be due to the correlation of cannabinoids and volatile compounds concentration during the growth of the cannabis plant. Therefore, the growth stage of cannabis can be predicted by NIR spectroscopy and chemometric tools in the early stages of indoor cannabis cultivation. Copyright © 2016 Elsevier B.V. All rights reserved.

Short communication: Discrimination between retail bovine milks with different fat contents using chemometrics and fatty acid profiling.

PubMed

Vargas-Bello-Pérez, Einar; Toro-Mujica, Paula; Enriquez-Hidalgo, Daniel; Fellenberg, María Angélica; Gómez-Cortés, Pilar

2017-06-01

We used a multivariate chemometric approach to differentiate or associate retail bovine milks with different fat contents and non-dairy beverages, using fatty acid profiles and statistical analysis. We collected samples of bovine milk (whole, semi-skim, and skim; n = 62) and non-dairy beverages (n = 27), and we analyzed them using gas-liquid chromatography. Principal component analysis of the fatty acid data yielded 3 significant principal components, which accounted for 72% of the total variance in the data set. Principal component 1 was related to saturated fatty acids (C4:0, C6:0, C8:0, C12:0, C14:0, C17:0, and C18:0) and monounsaturated fatty acids (C14:1 cis-9, C16:1 cis-9, C17:1 cis-9, and C18:1 trans-11); whole milk samples were clearly differentiated from the rest using this principal component. Principal component 2 differentiated semi-skim milk samples by n-3 fatty acid content (C20:3n-3, C20:5n-3, and C22:6n-3). Principal component 3 was related to C18:2 trans-9,trans-12 and C20:4n-6, and its lower scores were observed in skim milk and non-dairy beverages. A cluster analysis yielded 3 groups: group 1 consisted of only whole milk samples, group 2 was represented mainly by semi-skim milks, and group 3 included skim milk and non-dairy beverages. Overall, the present study showed that a multivariate chemometric approach is a useful tool for differentiating or associating retail bovine milks and non-dairy beverages using their fatty acid profile. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Chemometric differentiation of crude oil families in the San Joaquin Basin, California

USGS Publications Warehouse

Peters, Kenneth E.; Coutrot, Delphine; Nouvelle, Xavier; Ramos, L. Scott; Rohrback, Brian G.; Magoon, Leslie B.; Zumberge, John E.

2013-01-01

Chemometric analyses of geochemical data for 165 crude oil samples from the San Joaquin Basin identify genetically distinct oil families and their inferred source rocks and provide insight into migration pathways, reservoir compartments, and filling histories. In the first part of the study, 17 source-related biomarker and stable carbon-isotope ratios were evaluated using a chemometric decision tree (CDT) to identify families. In the second part, ascendant hierarchical clustering was applied to terpane mass chromatograms for the samples to compare with the CDT results. The results from the two methods are remarkably similar despite differing data input and assumptions. Recognized source rocks for the oil families include the (1) Eocene Kreyenhagen Formation, (2) Eocene Tumey Formation, (3–4) upper and lower parts of the Miocene Monterey Formation (Buttonwillow depocenter), and (5–6) upper and lower parts of the Miocene Monterey Formation (Tejon depocenter). Ascendant hierarchical clustering identifies 22 oil families in the basin as corroborated by independent data, such as carbon-isotope ratios, sample location, reservoir unit, and thermal maturity maps from a three-dimensional basin and petroleum system model. Five families originated from the Eocene Kreyenhagen Formation source rock, and three families came from the overlying Eocene Tumey Formation. Fourteen families migrated from the upper and lower parts of the Miocene Monterey Formation source rocks within the Buttonwillow and Tejon depocenters north and south of the Bakersfield arch. The Eocene and Miocene families show little cross-stratigraphic migration because of seals within and between the source rocks. The data do not exclude the possibility that some families described as originating from the Monterey Formation actually came from source rock in the Temblor Formation.

Molecularly imprinted polymer for determination of lumefantrine in human plasma through chemometric-assisted solid-phase extraction and liquid chromatography.

PubMed

da Silva, Pedro Henrique Reis; Diniz, Melina Luiza Vieira; Pianetti, Gerson Antônio; da Costa César, Isabela; Ribeiro E Silva, Maria Elisa Scarpelli; de Souza Freitas, Roberto Fernando; de Sousa, Ricardo Geraldo; Fernandes, Christian

2018-07-01

Lumefantrine is the first-choice treatment of Falciparum uncomplicated malaria. Recent findings of resistance to lumefantrine has brought attention for the importance of therapeutic monitoring, since exposure to subtherapeutic doses of antimalarials after administration is a major cause of selection of resistant parasites. Therefore, this study focused on the development of innovative, selective, less expensive and stable molecularly imprinted polymers (MIPs) for solid-phase extraction (SPE) of lumefantrine from human plasma to be used in drug monitoring. Polymers were synthesized by precipitation polymerization and chemometric tools (Box-Behnken design and surface response methodology) were employed for rational optimization of synthetic parameters. Optimum conditions were achieved with 2-vinylpyridine as monomer, ethylene glycol dimethacrylate as crosslinker and toluene as porogen, at molar ratio of 1:6:30 of template/monomer/crosslinker and azo-bisisobutyronitrile as initiator at 65 °C. The MIP obtained was characterized and exhibited high thermal stability, adequate surface morphology and porosity characteristics and high binding properties, with high affinity (adsorption capacity of 977.83 μg g -1 ) and selectivity (imprinting factor of 2.44; and selectivity factor of 1.48 and selectivity constant of 1.44 compared with halofantrine). Doehlert matrix and fractional designs were satisfactorily used for development and optimization of a MISPE-HPLC-UV method for determination of lumefantrine. The method fulfilled all validation parameters, with recoveries ranging from 83.68% to 85.42%, and was applied for quantitation of the drug in plasma from two healthy volunteers, with results of 1407.89 and 1271.35 ng mL -1 , respectively. Therefore, the MISPE-HPLC-UV method optimized through chemometrics provided a rapid, highly selective, less expensive and reproducible approach for lumefantrine drug monitoring. Copyright © 2018 Elsevier B.V. All rights reserved.

Hyperspectral Imaging and Support Vector Machine: A Powerful Combination to Differentiate Black Cohosh (Actaea racemosa) from Other Cohosh Species.

PubMed

Tankeu, Sidonie; Vermaak, Ilze; Chen, Weiyang; Sandasi, Maxleene; Kamatou, Guy; Viljoen, Alvaro

2018-04-01

Actaea racemosa (black cohosh) has a history of traditional use in the treatment of general gynecological problems. However, the plant is known to be vulnerable to adulteration with other cohosh species. This study evaluated the use of shortwave infrared hyperspectral imaging (SWIR-HSI) in tandem with chemometric data analysis as a fast alternative method for the discrimination of four cohosh species ( Actaea racemosa, Actaea podocarpa, Actaea pachypoda, Actaea cimicifuga ) and 36 commercial products labelled as black cohosh. The raw material and commercial products were analyzed using SWIR-HSI and ultra-high-performance liquid chromatography coupled to mass spectrometry (UHPLC-MS) followed by chemometric modeling. From SWIR-HSI data (920 - 2514 nm), the range containing the discriminating information of the four species was identified as 1204 - 1480 nm using Matlab software. After reduction of the data set range, partial least squares discriminant analysis (PLS-DA) and support vector machine discriminant analysis (SVM-DA) models with coefficients of determination ( R2 ) of ≥ 0.8 were created. The novel SVM-DA model showed better predictions and was used to predict the commercial product content. Seven out of 36 commercial products were recognized by the SVM-DA model as being true black cohosh while 29 products indicated adulteration. Analysis of the UHPLC-MS data demonstrated that six commercial products could be authentic black cohosh. This was confirmed using the fragmentation patterns of three black cohosh markers (cimiracemoside C; 12- β ,21-dihydroxycimigenol-3- O -L-arabinoside; and 24- O -acetylhydroshengmanol-3- O - β -D-xylopyranoside). SWIR-HSI in conjunction with chemometric tools (SVM-DA) could identify 80% adulteration of commercial products labelled as black cohosh. Georg Thieme Verlag KG Stuttgart · New York.

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

PubMed

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

2015-08-01

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

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

PubMed Central

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

2016-01-01

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

Sequential (step-by-step) detection, identification and quantitation of extra virgin olive oil adulteration by chemometric treatment of chromatographic profiles.

PubMed

Capote, F Priego; Jiménez, J Ruiz; de Castro, M D Luque

2007-08-01

An analytical method for the sequential detection, identification and quantitation of extra virgin olive oil adulteration with four edible vegetable oils--sunflower, corn, peanut and coconut oils--is proposed. The only data required for this method are the results obtained from an analysis of the lipid fraction by gas chromatography-mass spectrometry. A total number of 566 samples (pure oils and samples of adulterated olive oil) were used to develop the chemometric models, which were designed to accomplish, step-by-step, the three aims of the method: to detect whether an olive oil sample is adulterated, to identify the type of adulterant used in the fraud, and to determine how much aldulterant is in the sample. Qualitative analysis was carried out via two chemometric approaches--soft independent modelling of class analogy (SIMCA) and K nearest neighbours (KNN)--both approaches exhibited prediction abilities that were always higher than 91% for adulterant detection and 88% for type of adulterant identification. Quantitative analysis was based on partial least squares regression (PLSR), which yielded R2 values of >0.90 for calibration and validation sets and thus made it possible to determine adulteration with excellent precision according to the Shenk criteria.

Impact of Cultivation Conditions, Ethylene Treatment, and Postharvest Storage on Selected Quality and Bioactivity Parameters of Kiwifruit "Hayward" Evaluated by Analytical and Chemometric Methods.

PubMed

Park, Yong Seo; Polovka, Martin; Ham, Kyung-Sik Ham; Park, Yang-Kyun; Vearasilp, Suchada; Namieśnik, Jacek; Toledo, Fernando; Arancibia-Avila, Patricia; Gorinstein, Shela

2016-09-01

Organic, semiorganic, and conventional "Hayward" kiwifruits, treated with ethylene for 24 h and stored during 10 days, were assessed by UV spectrometry, fluorometry, and chemometrical analysis for changes in selected characteristics of quality (firmness, dry matter and soluble solid contents, pH, and acidity) and bioactivity (concentration of polyphenols via Folin-Ciocalteu and p-hydroxybenzoic acid assays). All of the monitored qualitative parameters and characteristics related to bioactivity were affected either by cultivation practices or by ethylene treatment and storage. Results obtained, supported by statistical evaluation (Friedman two-way ANOVA) and chemometric analysis, clearly proved that the most significant impact on the majority of the evaluated parameters of quality and bioactivity of "Hayward" kiwifruit had the ethylene treatment followed by the cultivation practices and the postharvest storage. Total concentration of polyphenols expressed via p-hydroxybenzoic acid assay exhibited the most significant sensitivity to all three evaluated parameters, reaching a 16.5% increase for fresh organic compared to a conventional control sample. As a result of postharvest storage coupled with ethylene treatment, the difference increased to 26.3%. Three-dimensional fluorescence showed differences in the position of the main peaks and their fluorescence intensity for conventional, semiorganic, and organic kiwifruits in comparison with ethylene nontreated samples.

Using fluorescence spectroscopy coupled with chemometric analysis to investigate the origin, composition, and dynamics of dissolved organic matter in leachate-polluted groundwater.

PubMed

He, Xiao-Song; Xi, Bei-Dou; Gao, Ru-Tai; Wang, Lei; Ma, Yan; Cui, Dong-Yu; Tan, Wen-Bing

2015-06-01

Groundwater was collected in 2011 and 2012, and fluorescence spectroscopy coupled with chemometric analysis was employed to investigate the composition, origin, and dynamics of dissolved organic matter (DOM) in the groundwater. The results showed that the groundwater DOM comprised protein-, fulvic-, and humic-like substances, and the protein-like component originated predominantly from microbial production. The groundwater pollution by landfill leachate enhanced microbial activity and thereby increased microbial by-product-like material such as protein-like component in the groundwater. Excitation-emission matrix fluorescence spectra combined with parallel factor analysis showed that the protein-like matter content increased from 2011 to 2012 in the groundwater, whereas the fulvic- and humic-like matter concentration exhibited no significant changes. In addition, synchronous-scan fluorescence spectra coupled with two-dimensional correlation analysis showed that the change of the fulvic- and humic-like matter was faster than that of the protein-like substances, as the groundwater flowed from upstream to downstream in 2011, but slower than that of the protein-like substance in 2012 due to the enhancement of microbial activity. Fluorescence spectroscopy combined with chemometric analysis can investigate groundwater pollution characteristics and monitor DOM dynamics in groundwater.

Rapid detection of talcum powder in tea using FT-IR spectroscopy coupled with chemometrics

PubMed Central

Li, Xiaoli; Zhang, Yuying; He, Yong

2016-01-01

This paper investigated the feasibility of Fourier transform infrared transmission (FT-IR) spectroscopy to detect talcum powder illegally added in tea based on chemometric methods. Firstly, 210 samples of tea powder with 13 dose levels of talcum powder were prepared for FT-IR spectra acquirement. In order to highlight the slight variations in FT-IR spectra, smoothing, normalize and standard normal variate (SNV) were employed to preprocess the raw spectra. Among them, SNV preprocessing had the best performance with high correlation of prediction (RP = 0.948) and low root mean square error of prediction (RMSEP = 0.108) of partial least squares (PLS) model. Then 18 characteristic wavenumbers were selected based on a hybrid of backward interval partial least squares (biPLS) regression, competitive adaptive reweighted sampling (CARS) algorithm and successive projections algorithm (SPA). These characteristic wavenumbers only accounted for 0.64% of the full wavenumbers. Following that, 18 characteristic wavenumbers were used to build linear and nonlinear determination models by PLS regression and extreme learning machine (ELM), respectively. The optimal model with RP = 0.963 and RMSEP = 0.137 was achieved by ELM algorithm. These results demonstrated that FT-IR spectroscopy with chemometrics could be used successfully to detect talcum powder in tea. PMID:27468701

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

NASA Astrophysics Data System (ADS)

Tewari, Jagdish; Strong, Richard; Boulas, Pierre

2017-02-01

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

Authenticity identification and classification of Rhodiola species in traditional Tibetan medicine based on Fourier transform near-infrared spectroscopy and chemometrics analysis.

PubMed

Li, Tao; Su, Chen

2018-06-02

Rhodiola is an increasingly widely used traditional Tibetan medicine and traditional Chinese medicine in China. The composition profiles of bioactive compounds are somewhat jagged according to different species, which makes it crucial to identify authentic Rhodiola species accurately so as to ensure clinical application of Rhodiola. In this paper, a nondestructive, rapid, and efficient method in classification of Rhodiola was developed by Fourier transform near-infrared (FT-NIR) spectroscopy combined with chemometrics analysis. A total of 160 batches of raw spectra were obtained from four different species of Rhodiola by FT-NIR, such as Rhodiola crenulata, Rhodiola fastigiata, Rhodiola kirilowii, and Rhodiola brevipetiolata. After excluding the outliers, different performances of 3 sample dividing methods, 12 spectral preprocessing methods, 2 wavelength selection methods, and 2 modeling evaluation methods were compared. The results indicated that this combination was superior than others in the authenticity identification analysis, which was FT-NIR combined with sample set partitioning based on joint x-y distances (SPXY), standard normal variate transformation (SNV) + Norris-Williams (NW) + 2nd derivative, competitive adaptive reweighted sampling (CARS), and kernel extreme learning machine (KELM). The accuracy (ACCU), sensitivity (SENS), and specificity (SPEC) of the optimal model were all 1, which showed that this combination of FT-NIR and chemometrics methods had the optimal authenticity identification performance. The classification performance of the partial least squares discriminant analysis (PLS-DA) model was slightly lower than KELM model, and PLS-DA model results were ACCU = 0.97, SENS = 0.93, and SPEC = 0.98, respectively. It can be concluded that FT-NIR combined with chemometrics analysis has great potential in authenticity identification and classification of Rhodiola, which can provide a valuable reference for the safety and effectiveness of clinical application of Rhodiola. Copyright © 2018 Elsevier B.V. All rights reserved.

Chemomic and chemometric approach based on ultra-fast liquid chromatography with ion trap time-of-flight mass spectrometry to reveal the difference in the chemical composition between Da-Cheng-Qi decoction and its three constitutional herbal medicines.

PubMed

Wang, Mengru; Li, Yuanyuan; Huang, Yin; Tian, Yuan; Xu, Fengguo; Zhang, Zunjian

2014-05-01

Da-Cheng-Qi decoction (DCQT) is a traditional purgative Chinese decoction with a history of 2000 years. To study the effect of interactions between the ingredients on the overall chemical composition of DCQT, a chemomic and chemometric approach based on ultra-fast liquid chromatography with ion trap time-of-flight mass spectrometry was developed and validated. After mixing and decocting all four ingredients to make the DCQT, the concentrations of some chemicals are significantly different from those in single herb decoction and 24 of them were identified and tentatively characterized by comparing their data with those of standard compounds or literature data. No new chemicals were formed during mixing and decoction. Our findings indicated that there are interactions between these natural medicines during the mixing and preparation process. The 24 identified chemicals could be used as chemical markers for optimizing prescription and evaluation of consistent quality, and the strategy in the present study could be applied for other multiherb formulae. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed Central

Bajoub, Aadil; Medina-Rodríguez, Santiago; Olmo-García, Lucía; Ajal, El Amine; Monasterio, Romina P.; Hanine, Hafida; Fernández-Gutiérrez, Alberto; Carrasco-Pancorbo, Alegría

2016-01-01

Olive oil phenolic fraction considerably contributes to the sensory quality and nutritional value of this foodstuff. Herein, the phenolic fraction of 203 olive oil samples extracted from fruits of four autochthonous Moroccan cultivars (“Picholine Marocaine”, “Dahbia”, “Haouzia” and “Menara”), and nine Mediterranean varieties recently introduced in Morocco (“Arbequina”, “Arbosana”, “Cornicabra”, “Frantoio”, “Hojiblanca”, “Koroneiki”, “Manzanilla”, “Picholine de Languedoc” and “Picual”), were explored over two consecutive crop seasons (2012/2013 and 2013/2014) by using liquid chromatography-mass spectrometry. A total of 32 phenolic compounds (and quinic acid), belonging to five chemical classes (secoiridoids, simple phenols, flavonoids, lignans and phenolic acids) were identified and quantified. Phenolic profiling revealed that the determined phenolic compounds showed variety-dependent levels, being, at the same time, significantly affected by the crop season. Moreover, based on the obtained phenolic composition and chemometric linear discriminant analysis, statistical models were obtained allowing a very satisfactory classification and prediction of the varietal origin of the studied oils. PMID:28036024

Resolving anthropogenic aerosol pollution types - deconvolution and exploratory classification of pollution events

NASA Astrophysics Data System (ADS)

Äijälä, Mikko; Heikkinen, Liine; Fröhlich, Roman; Canonaco, Francesco; Prévôt, André S. H.; Junninen, Heikki; Petäjä, Tuukka; Kulmala, Markku; Worsnop, Douglas; Ehn, Mikael

2017-03-01

Mass spectrometric measurements commonly yield data on hundreds of variables over thousands of points in time. Refining and synthesizing this raw data into chemical information necessitates the use of advanced, statistics-based data analytical techniques. In the field of analytical aerosol chemistry, statistical, dimensionality reductive methods have become widespread in the last decade, yet comparable advanced chemometric techniques for data classification and identification remain marginal. Here we present an example of combining data dimensionality reduction (factorization) with exploratory classification (clustering), and show that the results cannot only reproduce and corroborate earlier findings, but also complement and broaden our current perspectives on aerosol chemical classification. We find that applying positive matrix factorization to extract spectral characteristics of the organic component of air pollution plumes, together with an unsupervised clustering algorithm, k-means+ + , for classification, reproduces classical organic aerosol speciation schemes. Applying appropriately chosen metrics for spectral dissimilarity along with optimized data weighting, the source-specific pollution characteristics can be statistically resolved even for spectrally very similar aerosol types, such as different combustion-related anthropogenic aerosol species and atmospheric aerosols with similar degree of oxidation. In addition to the typical oxidation level and source-driven aerosol classification, we were also able to classify and characterize outlier groups that would likely be disregarded in a more conventional analysis. Evaluating solution quality for the classification also provides means to assess the performance of mass spectral similarity metrics and optimize weighting for mass spectral variables. This facilitates algorithm-based evaluation of aerosol spectra, which may prove invaluable for future development of automatic methods for spectra identification and classification. Robust, statistics-based results and data visualizations also provide important clues to a human analyst on the existence and chemical interpretation of data structures. Applying these methods to a test set of data, aerosol mass spectrometric data of organic aerosol from a boreal forest site, yielded five to seven different recurring pollution types from various sources, including traffic, cooking, biomass burning and nearby sawmills. Additionally, three distinct, minor pollution types were discovered and identified as amine-dominated aerosols.

Cartilage analysis by reflection spectroscopy

NASA Astrophysics Data System (ADS)

Laun, T.; Muenzer, M.; Wenzel, U.; Princz, S.; Hessling, M.

2015-07-01

A cartilage bioreactor with analytical functions for cartilage quality monitoring is being developed. For determining cartilage composition, reflection spectroscopy in the visible (VIS) and near infrared (NIR) spectral region is evaluated. Main goal is the determination of the most abundant cartilage compounds water, collagen I and collagen II. Therefore VIS and NIR reflection spectra of different cartilage samples of cow, pig and lamb are recorded. Due to missing analytical instrumentation for identifying the cartilage composition of these samples, typical literature concentration values are used for the development of chemometric models. In spite of these limitations the chemometric models provide good cross correlation results for the prediction of collagen I and II and water concentration based on the visible and the NIR reflection spectra.

Modelling of Hydrophilic Interaction Liquid Chromatography Stationary Phases Using Chemometric Approaches

PubMed Central

Ortiz-Villanueva, Elena; Tauler, Romà

2017-01-01

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

Qualitative and quantitative control of pediatric syrups using Nuclear Magnetic Resonance and chemometrics.

PubMed

Alves Filho, Elenilson G; Silva, Lorena Mara A; Araújo, Nathália V P; Alves, Elenilson G; Lião, Luciano M; Alcantara, Glaucia B

2018-05-10

Several flavoring and sweetening agents added to excipient of pediatric syrups are not declared in the package leaflet. Therefore, the aim of this study was to develop a non-target, simple, and precise method for qualitative and quantitative evaluation of pediatric syrups using NMR spectroscopy combined with chemometrics. This approach allowed the identification of several added compounds as citric acid, cyclamate, ethanol, glycerol, propylene glycol, saccharin, sorbitol, fructose, glucose, and sucrose. Among the sugared syrups, sucrose was the main carbohydrate with approximately 59.1%, and for sweetened syrups, glycerol with 25.5%. The ethanol was found with highest concentration of 4.0%, approximately. In addition, some syrups presented both sugar and sweetener, which is inconsistent according to the purpose of the addition. Consequently, institutional structures of countries as Brazil that are in charge of public health should put additional compliance pressure on pharmaceutical companies to clearly declare in package leaflet the presence and exact amount of the main compounds (at least) existent in the pediatric excipients. Copyright © 2018 Elsevier B.V. All rights reserved.

Chemometric evaluation of the volatile profile of probiotic melon and probiotic cashew juice.

PubMed

de Godoy Alves Filho, Elenilson; Rodrigues, Tigressa Helena Soares; Fernandes, Fabiano André Narciso; Pereira, Ana Lucia Fernandes; Narain, Narendra; de Brito, Edy Sousa; Rodrigues, Sueli

2017-09-01

The aim of this study was to evaluate the influence of the lactic acid fermentation on volatile compounds of melon and cashew apple juices. The effect of the fermentation processing on the volatile profile of probiotic juices was assessed by HS-SPME/GC-MS coupled to chemometrics with 67.9% and 81.0% of the variance in the first principal component for melon and cashew juices, respectively. The Lactobacillus casei fermentation imparted a reduction of ethyl butanoate, ethyl-2-methylbutirate, and ethyl hexanoate for melon juice; and of ethyl acetate, ethyl-2-methyl butanoate, ethyl crotonate, ethyl isovalerate, benzaldehyde, and ethyl hexanoate for cashew juice. Measurements of the stability of these compounds and the formation of the component 3-methyl-2-butenyl in melon juice may be used as a volatile marker to follow the juice fermentation. These findings suggested that even though it is not a dairy product the lactic acid fermentation of fruits developed a volatile profile combining the fruit and lactic acid fermentation volatiles with mildly formation or degradation of aroma compounds. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Chemometrics Approach for Nuclear Magnetic Resonance Data to Characterize the Partial Metabolome Banana Peels from Southern Brazil.

PubMed

Cardoso, Sara; Maraschin, Marcelo; Peruch, Luiz Augusto Martins; Rocha, Miguel; Pereira, Aline

2017-12-13

Banana peels are well recognized as a source of important bioactive compounds, such as phenolics, carotenoids, biogenic amines, among others. As such, they have recently started to be used for industrial purposes. However, its composition seems to be strongly affected by biotic or abiotic ecological factors. Thus, this study aimed to investigate banana peels chemical composition, not only to get insights on eventual metabolic changes caused by the seasons, in southern Brazil, but also to identify the most relevant metabolites for these processes. To achieve this, a Nuclear magnetic resonance (NMR)-based metabolic profiling strategy was adopted, followed by chemometrics analysis, using the specmine package for the R environment, and metabolite identification. The results showed that the metabolomic approach adopted allowed identifying a series of primary and secondary metabolites in the aqueous extracts investigated. Besides, over the seasons the metabolic profiles of the banana peels showed to contain biologically active compounds relevant to the skin wound healing process, indicating the biotechnological potential of that raw material.

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

PubMed

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

2014-12-01

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

Rapid discrimination of the causal agents of urinary tract infection using ToF-SIMS with chemometric cluster analysis

NASA Astrophysics Data System (ADS)

Fletcher, John S.; Henderson, Alexander; Jarvis, Roger M.; Lockyer, Nicholas P.; Vickerman, John C.; Goodacre, Royston

2006-07-01

Advances in time of flight secondary ion mass spectrometry (ToF-SIMS) have enabled this technique to become a powerful tool for the analysis of biological samples. Such samples are often very complex and as a result full interpretation of the acquired data can be extremely difficult. To simplify the interpretation of these information rich data, the use of chemometric techniques is becoming widespread in the ToF-SIMS community. Here we discuss the application of principal components-discriminant function analysis (PC-DFA) to the separation and classification of a number of bacterial samples that are known to be major causal agents of urinary tract infection. A large data set has been generated using three biological replicates of each isolate and three machine replicates were acquired from each biological replicate. Ordination plots generated using the PC-DFA are presented demonstrating strain level discrimination of the bacteria. The results are discussed in terms of biological differences between certain species and with reference to FT-IR, Raman spectroscopy and pyrolysis mass spectrometric studies of similar samples.

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

PubMed

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

2016-01-01

Analysis of phenolic profile and tocopherol fractions in conjunction with chemometrics techniques were used for the accurate characterization of extra virgin argan oil and eight other edible vegetable virgin oils (olive, soybean, wheat germ, walnut, almond, sesame, avocado, and linseed) and to establish similarities among them. Phenolic profile and tocopherols were determined by HPLC coupled with diode-array and fluorescence detectors, respectively. Multivariate factor analysis (MFA) and linear correlations were applied. Significant negative correlations were found between tocopherols and some of the polyphenols identified, but more intensely (P < 0.001) between the γ-tocopherol and oleuropein, pinoresinol, and luteolin. MFA revealed that tocopherols, especially γ-fraction, most strongly influenced the oil characterization. Among the phenolic compounds, syringic acid, dihydroxybenzoic acid, oleuropein, pinoresinol, and luteolin also contributed to the discrimination of the oils. According to the variables analyzed in the present study, argan oil presented the greatest similarity with walnut oil, followed by sesame and linseed oils. Olive, avocado, and almond oils showed close similarities.

Discrimination of geographical origin of lentils (Lens culinaris Medik.) using isotope ratio mass spectrometry combined with chemometrics.

PubMed

Longobardi, F; Casiello, G; Cortese, M; Perini, M; Camin, F; Catucci, L; Agostiano, A

2015-12-01

The aim of this study was to predict the geographic origin of lentils by using isotope ratio mass spectrometry (IRMS) in combination with chemometrics. Lentil samples from two origins, i.e. Italy and Canada, were analysed obtaining the stable isotope ratios of δ(13)C, δ(15)N, δ(2)H, δ(18)O, and δ(34)S. A comparison between median values (U-test) highlighted statistically significant differences (p<0.05) for all isotopic parameters between the lentils produced in these two different geographic areas, except for δ(15)N. Applying principal component analysis, grouping of samples was observed on the basis of origin but with overlapping zones; consequently, two supervised discriminant techniques, i.e. partial least squares discriminant analysis and k-nearest neighbours algorithm were used. Both models showed good performances with external prediction abilities of about 93% demonstrating the suitability of the methods developed. Subsequently, isotopic determinations were also performed on the protein and starch fractions and the relevant results are reported. Copyright © 2015 Elsevier Ltd. All rights reserved.

Photocatalytic degradation using design of experiments: a review and example of the Congo red degradation.

PubMed

Sakkas, Vasilios A; Islam, Md Azharul; Stalikas, Constantine; Albanis, Triantafyllos A

2010-03-15

The use of chemometric methods such as response surface methodology (RSM) based on statistical design of experiments (DOEs) is becoming increasingly widespread in several sciences such as analytical chemistry, engineering and environmental chemistry. Applied catalysis, is certainly not the exception. It is clear that photocatalytic processes mated with chemometric experimental design play a crucial role in the ability of reaching the optimum of the catalytic reactions. The present article reviews the major applications of RSM in modern experimental design combined with photocatalytic degradation processes. Moreover, the theoretical principles and designs that enable to obtain a polynomial regression equation, which expresses the influence of process parameters on the response are thoroughly discussed. An original experimental work, the photocatalytic degradation of the dye Congo red (CR) using TiO(2) suspensions and H(2)O(2), in natural surface water (river water) is comprehensively described as a case study, in order to provide sufficient guidelines to deal with this subject, in a rational and integrated way. (c) 2009 Elsevier B.V. All rights reserved.

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

PubMed

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

2014-03-01

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

Determination of the botanical origin of honey by front-face synchronous fluorescence spectroscopy.

PubMed

Lenhardt, Lea; Zeković, Ivana; Dramićanin, Tatjana; Dramićanin, Miroslav D; Bro, Rasmus

2014-01-01

Front-face synchronous fluorescence spectroscopy combined with chemometrics is used to classify honey samples according to their botanical origin. Synchronous fluorescence spectra of three monofloral (linden, sunflower, and acacia), polyfloral (meadow mix), and fake (fake acacia and linden) honey types (109 samples) were collected in an excitation range of 240-500 nm for synchronous wavelength intervals of 30-300 nm. Chemometric analysis of the gathered data included principal component analysis and partial least squares discriminant analysis. Mean cross-validated classification errors of 0.2 and 4.8% were found for a model that accounts only for monofloral samples and for a model that includes both the monofloral and polyfloral groups, respectively. The results demonstrate that single synchronous fluorescence spectra of different honeys differ significantly because of their distinct physical and chemical characteristics and provide sufficient data for the clear differentiation among honey groups. The spectra of fake honey samples showed pronounced differences from those of genuine honey, and these samples are easily recognized on the basis of their synchronous fluorescence spectra. The study demonstrated that this method is a valuable and promising technique for honey authentication.

Monitoring multiple components in vinegar fermentation using Raman spectroscopy.

PubMed

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

2013-12-15

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

Combinatorially-generated library of 6-fluoroquinolone analogs as potential novel antitubercular agents: a chemometric and molecular modeling assessment.

PubMed

Minovski, Nikola; Perdih, Andrej; Solmajer, Tom

2012-05-01

The virtual combinatorial chemistry approach as a methodology for generating chemical libraries of structurally-similar analogs in a virtual environment was employed for building a general mixed virtual combinatorial library with a total of 53.871 6-FQ structural analogs, introducing the real synthetic pathways of three well known 6-FQ inhibitors. The druggability properties of the generated combinatorial 6-FQs were assessed using an in-house developed drug-likeness filter integrating the Lipinski/Veber rule-sets. The compounds recognized as drug-like were used as an external set for prediction of the biological activity values using a neural-networks (NN) model based on an experimentally-determined set of active 6-FQs. Furthermore, a subset of compounds was extracted from the pool of drug-like 6-FQs, with predicted biological activity, and subsequently used in virtual screening (VS) campaign combining pharmacophore modeling and molecular docking studies. This complex scheme, a powerful combination of chemometric and molecular modeling approaches provided novel QSAR guidelines that could aid in the further lead development of 6-FQs agents.

Binding assessment of two arachidonic-based synthetic derivatives of adrenalin with β-lactoglobulin: Molecular modeling and chemometrics approach.

PubMed

Gholami, S; Bordbar, A K; Akvan, N; Parastar, H; Fani, N; Gretskaya, N M; Bezuglov, V V; Haertlé, T

2015-12-01

A computational approach to predict the main binding modes of two adrenalin derivatives, arachidonoyl adrenalin (AA-AD) and arachidonoyl noradrenalin (AA-NOR) with the β-lactoglubuline (BLG) as a nano-milk protein carrier is presented and assessed by comparison to the UV-Vis absorption spectroscopic data using chemometric analysis. Analysis of the spectral data matrices by using the multivariate curve resolution-alternating least squares (MCR-ALS) algorithm led to the pure concentration calculation and spectral profiles resolution of the chemical constituents and the apparent equilibrium constants computation. The negative values of entropy and enthalpy changes for both compound indicated the essential role of hydrogen bonding and van der Waals interactions as main driving forces in stabilizing protein-ligand complex. Computational studies predicted that both derivatives are situated in the calyx pose and remained in that pose during the whole time of simulation with no any significant protein structural changes which pointed that the BLG could be considered as a suitable carrier for these catecholamine compounds. Copyright © 2015 Elsevier B.V. All rights reserved.

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

PubMed

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

2013-11-15

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

Detection of l-Cysteine in wheat flour by Raman microspectroscopy combined chemometrics of HCA and PCA.

PubMed

Cebi, Nur; Dogan, Canan Ekinci; Develioglu, Ayşen; Yayla, Mediha Esra Altuntop; Sagdic, Osman

2017-08-01

l-Cysteine is deliberately added to various flour types since l-Cysteine has enabled favorable baking conditions such as low viscosity, increased elasticity and rise during baking. In Turkey, usage of l-Cysteine as a food additive isn't allowed in wheat flour according to the Turkish Food Codex Regulation on food additives. There is an urgent need for effective methods to detect l-Cysteine in wheat flour. In this study, for the first time, a new, rapid, effective, non-destructive and cost-effective method was developed for detection of l-Cysteine in wheat flour using Raman microscopy. Detection of l-Cysteine in wheat flour was accomplished successfully using Raman microscopy combined chemometrics of PCA (Principal Component Analysis) and HCA (Hierarchical Cluster Analysis). In this work, 500-2000cm -1 spectral range (fingerprint region) was determined to perform PCA and HCA analysis. l-Cysteine and l-Cystine were determined with detection limit of 0.125% (w/w) in different wheat flour samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

Chemometric investigation of light-shade effects on essential oil yield and morphology of Moroccan Myrtus communis L.

PubMed

Fadil, Mouhcine; Farah, Abdellah; Ihssane, Bouchaib; Haloui, Taoufik; Lebrazi, Sara; Zghari, Badreddine; Rachiq, Saâd

2016-01-01

To investigate the effect of environmental factors such as light and shade on essential oil yield and morphological traits of Moroccan Myrtus communis, a chemometric study was conducted on 20 individuals growing under two contrasting light environments. The study of individual's parameters by principal component analysis has shown that essential oil yield, altitude, and leaves thickness were positively correlated between them and negatively correlated with plants height, leaves length and leaves width. Principal component analysis and hierarchical cluster analysis have also shown that the individuals of each sampling site were grouped separately. The one-way ANOVA test has confirmed the effect of light and shade on essential oil yield and morphological parameters by showing a statistically significant difference between them from the shaded side to the sunny one. Finally, the multiple linear model containing main, interaction and quadratic terms was chosen for the modeling of essential oil yield in terms of morphological parameters. Sun plants have a small height, small leaves length and width, but they are thicker and richer in essential oil than shade plants which have shown almost the opposite. The highlighted multiple linear model can be used to predict essential oil yield in the studied area.

¹H and ¹³C NMR-based sugar profiling with chemometric analysis and antioxidant activity of herbhoneys and honeys.

PubMed

Jamróz, Marta K; Paradowska, Katarzyna; Zawada, Katarzyna; Makarova, Katerina; Kaźmierski, Sławomir; Wawer, Iwona

2014-01-30

Herbhoneys, relatively new bee products, are expected to have interesting medicinal properties. However, there is still a lack of data concerning their composition and antioxidant properties. ¹H and ¹³C NMR spectroscopy coupled with chemometric analysis (PCA and PLS-DA) and antioxidant assays (DPPH-ESR and ORAC-FL) were used to study 25 samples of Polish herbhoneys and honeys. Antioxidant activity varied among the samples. The best properties were exhibited by cocoa and instant coffee herbhoneys. The contents of total polyphenols and total carotenoids in the studied samples were found to be 70-1340 mg GAE kg⁻¹ and 0-28.05 mg kg⁻¹ respectively. No significant differences between herbhoney and honey samples were found in their sugar profiles. The PCA of ¹³C NMR spectra of the samples in DMSO-d6 resulted in sample clustering due to sucrose content. Herbhoneys have similar antioxidant properties to traditional honeys, being therefore of equal nutritional value. There was a noticeable influence of the extract concentration on the observed antioxidant effect. For samples with high antioxidant activity, polyphenols were responsible for the observed effect. Sample clustering due to sucrose content in the NMR-PCA study allowed effortless detection of adulteration. © 2013 Society of Chemical Industry.

The Emergence of Inclusive Exploratory Talk in Primary Students' Peer Interaction

ERIC Educational Resources Information Center

Rajala, Antti; Hilppo, Jaakko; Lipponen, Lasse

2012-01-01

In this study, we examine a prominent type of classroom talk, exploratory talk, in primary school peer interactions. Exploratory talk has been shown to be productive in facilitating problem solving and fostering school achievement. However, within the growing body of research concerning exploratory talk, the relation between exploratory talk and…

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

PubMed

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

2017-04-01

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

Chemometric techniques in oil classification from oil spill fingerprinting.

PubMed

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

2016-10-15

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

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

PubMed

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

2015-10-01

Tulsi, Banyan, and Jamun are popular Indian medicinal plants with notable hypoglycemic potentials. Now the work reports chemo-profiling of the three species with in-vitro screening approach for natural enzyme inhibitors (NEIs) against enzymes pathogenic for type 2 diabetes. Further along with the chemometrics optimized extraction process technology, phyto-synergistic studies of the composite polyherbal blends have also been reported. Chemometrically optimized extraction procedures, ratios of polyherbal composites to achieve phyto-synergistic actions, and in-vitro screening of NEIs amongst leaves of Tulsi, Banyan, and Jamun. The extraction process parameters of the leaves of three plant species (Ficus benghalensis, Syzigium cumini and Ocimum sanctum) were optimized by rotatable central composite design of chemometrics so as to get maximal yield of bio-actives. Phyto-blends of three species were prepared so as to achieve synergistic antidiabetic and antioxidant potentials and the ratios were optimized by chemometrics. Next, for in vitro screening of natural enzyme inhibitors the individual leaf extracts as well as composite blends were subjected to assay procedures to see their inhibitory potentials against the enzymes pathogenic in type 2 diabetes. The antioxidant potentials were also estimated by DPPH radical scavenging, ABTS, FRAP and Dot Blot assay. Considering response surface methodology studies and from the solutions obtained using desirability function, it was found that hydro-ethanolic or methanolic solvent ratio of 52.46 ± 1.6 and at a temperature of 20.17 ± 0.6 gave an optimum yield of polyphenols with minimal chlorophyll leaching. The species also showed the presence of glycosides, alkaloids, and saponins. Composites in the ratios of 1:1:1 and 1:1:2 gave synergistic effects in terms of polyphenol yield and anti-oxidant potentials. All composites (1:1:1, 1:2:1, 2:1:1, 1:1:2) showed synergistic anti-oxidant actions. Inhibitory activities against the targeted enzymes expressed in terms of IC50 values have shown that hydro-ethanolic extracts in all cases whether individual species or composites in varying ratios gave higher IC50 values thus showing greater effectivity. Current research provides the state-of-the-art of search of NEIs amongst three species by in-vitro assays which can be further utilized for bioactivity-guided isolations of such enzyme inhibitors. Further, it reports the optimized phyto-blend ratios so as to achieve synergistic anti-oxidative actions. The current research work focuses on the optimization of the extraction process parameters and the ratios of phyto-synergistic blends of the leaves of three common medicinal plants viz. banyan, jamun and tulsi by chemometrics. Qualitative and quantitative chemo profiling of the extracts were done by different phytochemical tests and UV spectrophotometric methods. Enzymes like alpha amylase, alpha glucosidase, aldose reductase, dipeptidyl peptidase 4, angiotensin converting enzymes are found to be pathogenic in type 2 diabetes. In vitro screening of natural enzyme inhibitors amongst individual extracts and composite blends were carried out by different assay procedures and the potency expressed in terms of IC50 values. Antioxidant potentials were estimated by DPPH radical scavenging, ABTS, FRAP and Dot Blot assay. Hydroalcoholic solvent (50:50) gave maximal yield of bio-actives with minimal chlorophyll leaching. Hydroethanolic extract of tulsi showed maximal antioxidant effect. Though all composites showed synergism, maximal effects were shown by the composite (1:1:2) in terms of polyphenol yield, antioxidant effect and inhibitory actions against the targeted enzymes. Abbreviations used: DPP4- dipeptidyl peptidase 4; AR- aldose reductase; ACE- angiotensin converting enzyme; PPAR-γ- peroxisome proliferator activated receptor-γ; NEIs- natural enzyme inhibitors; BE- binding energy; GLP-1- Glucagon like peptide -1; ROS- Reactive oxygen species; CAT- catalase; GSH-Px- glutathione per-oxidase; SOD- superoxide dismutase; pNPG- para-nitro phenyl-α-D-gluco-pyranoside solution; DPPH- 1,1-diphenyl-2-picrylhydrazyl; RSM- Response surface methodology; CCD- central composite design; DMSO- dimethyl sulfoxide; HHL- hippuryl-L-histidyl-L-leucine; GPN-Tos- Gly-Pro p-nitroanilide toluenesulfonate salt; ESC- experimental scavenging capacity; TSC- theoretical scavenging capacity; FRAP- Ferric Reducing Assay Procedure; ABTS- 2, 2'- azinobis (3-ethylbenzothiazoline-6 - sulfonic acid.

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

PubMed Central

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

2015-01-01

Background: Tulsi, Banyan, and Jamun are popular Indian medicinal plants with notable hypoglycemic potentials. Now the work reports chemo-profiling of the three species with in-vitro screening approach for natural enzyme inhibitors (NEIs) against enzymes pathogenic for type 2 diabetes. Further along with the chemometrics optimized extraction process technology, phyto-synergistic studies of the composite polyherbal blends have also been reported. Objective: Chemometrically optimized extraction procedures, ratios of polyherbal composites to achieve phyto-synergistic actions, and in-vitro screening of NEIs amongst leaves of Tulsi, Banyan, and Jamun. Materials and Methods: The extraction process parameters of the leaves of three plant species (Ficus benghalensis, Syzigium cumini and Ocimum sanctum) were optimized by rotatable central composite design of chemometrics so as to get maximal yield of bio-actives. Phyto-blends of three species were prepared so as to achieve synergistic antidiabetic and antioxidant potentials and the ratios were optimized by chemometrics. Next, for in vitro screening of natural enzyme inhibitors the individual leaf extracts as well as composite blends were subjected to assay procedures to see their inhibitory potentials against the enzymes pathogenic in type 2 diabetes. The antioxidant potentials were also estimated by DPPH radical scavenging, ABTS, FRAP and Dot Blot assay. Results: Considering response surface methodology studies and from the solutions obtained using desirability function, it was found that hydro-ethanolic or methanolic solvent ratio of 52.46 ± 1.6 and at a temperature of 20.17 ± 0.6 gave an optimum yield of polyphenols with minimal chlorophyll leaching. The species also showed the presence of glycosides, alkaloids, and saponins. Composites in the ratios of 1:1:1 and 1:1:2 gave synergistic effects in terms of polyphenol yield and anti-oxidant potentials. All composites (1:1:1, 1:2:1, 2:1:1, 1:1:2) showed synergistic anti-oxidant actions. Inhibitory activities against the targeted enzymes expressed in terms of IC50 values have shown that hydro-ethanolic extracts in all cases whether individual species or composites in varying ratios gave higher IC50 values thus showing greater effectivity. Conclusion: Current research provides the state-of-the-art of search of NEIs amongst three species by in-vitro assays which can be further utilized for bioactivity-guided isolations of such enzyme inhibitors. Further, it reports the optimized phyto-blend ratios so as to achieve synergistic anti-oxidative actions. SUMMARY The current research work focuses on the optimization of the extraction process parameters and the ratios of phyto-synergistic blends of the leaves of three common medicinal plants viz. banyan, jamun and tulsi by chemometrics. Qualitative and quantitative chemo profiling of the extracts were done by different phytochemical tests and UV spectrophotometric methods. Enzymes like alpha amylase, alpha glucosidase, aldose reductase, dipeptidyl peptidase 4, angiotensin converting enzymes are found to be pathogenic in type 2 diabetes. In vitro screening of natural enzyme inhibitors amongst individual extracts and composite blends were carried out by different assay procedures and the potency expressed in terms of IC50 values. Antioxidant potentials were estimated by DPPH radical scavenging, ABTS, FRAP and Dot Blot assay. Hydroalcoholic solvent (50:50) gave maximal yield of bio-actives with minimal chlorophyll leaching. Hydroethanolic extract of tulsi showed maximal antioxidant effect. Though all composites showed synergism, maximal effects were shown by the composite (1:1:2) in terms of polyphenol yield, antioxidant effect and inhibitory actions against the targeted enzymes. Abbreviations used: DPP4- dipeptidyl peptidase 4; AR- aldose reductase; ACE- angiotensin converting enzyme; PPAR-γ- peroxisome proliferator activated receptor-γ; NEIs- natural enzyme inhibitors; BE- binding energy; GLP-1- Glucagon like peptide -1; ROS- Reactive oxygen species; CAT- catalase; GSH-Px- glutathione per-oxidase; SOD- superoxide dismutase; pNPG- para-nitro phenyl-α-D-gluco-pyranoside solution; DPPH- 1,1-diphenyl-2-picrylhydrazyl; RSM- Response surface methodology; CCD- central composite design; DMSO- dimethyl sulfoxide; HHL- hippuryl-L-histidyl-L-leucine; GPN-Tos- Gly-Pro p-nitroanilide toluenesulfonate salt; ESC- experimental scavenging capacity; TSC- theoretical scavenging capacity; FRAP- Ferric Reducing Assay Procedure; ABTS- 2, 2’- azinobis (3-ethylbenzothiazoline-6 – sulfonic acid. PMID:27013789

Characterization of a new fertilizer during field trials by hyperspectral imaging

NASA Astrophysics Data System (ADS)

Bonifazi, Giuseppe; Serranti, Silvia; Trella, Agata; Garcia Izquierdo, Carlos

2016-05-01

This work was carried out in the framework of the LIFE RESAFE Project (LIFE12 ENV/IT/000356) "Innovative fertilizer from urban waste, bio-char and farm residues as substitute of chemical fertilizers". The aim of RESAFE project is the production of a new fertilizer from waste for agricultural practices. The new fertilizer was tested on 5 different crops during field trials carried out in Spain: barley, corn, tomato, potato and melon. For each crop six different treatments were applied and compared to verify the quality of RESAFE fertilizer. Soil samples were collected at the beginning and at the end of the experiment. The possibility to apply hyperspectral imaging (HSI) to perform soil evolution monitoring and characterization in respect to the fertilizer utilization and quality of the resulting crops was investigated. Soil samples were acquired by HSI in the near infrared field (1000-1700 nm) and on the same samples classical chemical analyses were carried out with reference to total nitrogen, total organic carbon, C/N ratio, total organic matter. Hyperspectral data were analyzed adopting a chemometric approach through application of Principal Component Analysis (PCA) for exploratory purposes and Partial Least Squares Analysis (PLS) for estimation of chemical parameters. The results showed as the proposed hardware and software integrated architecture allows to implement low cost and easy to use analytical procedures able to quantitatively assess soil chemical-physical attributes according to different fertilization strategies, in respect of different environmental conditions and selected crops.

Report: Scientific Software.

ERIC Educational Resources Information Center

Borman, Stuart A.

1985-01-01

Discusses various aspects of scientific software, including evaluation and selection of commercial software products; program exchanges, catalogs, and other information sources; major data analysis packages; statistics and chemometrics software; and artificial intelligence. (JN)

Fatty acid composition of wild mushroom species of order Agaricales--examination by gas chromatography-mass spectrometry and chemometrics.

PubMed

Marekov, Ilko; Momchilova, Svetlana; Grung, Bjørn; Nikolova-Damyanova, Boryana

2012-12-01

Applying gas chromatography-mass spectrometry of 4,4-dimethyloxazoline fatty acid derivatives, the fatty acid composition of 15 mushroom species belonging to 9 genera and 5 families of order Agaricales growing in Bulgaria is determined. The structure of 31 fatty acids (not all present in each species) is unambiguously elucidated, with linoleic, oleic and palmitic acids being the main components (ranging between 70.9% (Marasmius oreades) and 91.2% (Endoptychum agaricoides)). A group of three hexadecenoic positionally isomeric fatty acids, 6-, 9- and 11-16:1, appeared to be characteristic components of the examined species. By applying chemometrics it was possible to show that the fatty acid composition closely reflects the classification of the species. Copyright © 2012 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

Differentiation of Aurantii Fructus Immaturus from Poniciri Trifoliatae Fructus Immaturus using Flow- injection Mass spectrometric (FIMS) Metabolic Fingerprinting Method Combined with Chemometrics

PubMed Central

Zhao, Yang; Chang, Yuan-Shiun; Chen, Pei

2015-01-01

A flow-injection mass spectrometric metabolic fingerprinting method in combination with chemometrics was used to differentiate Aurantii Fructus Immaturus from its counterfeit Poniciri Trifoliatae Fructus Immaturus. Flow-injection mass spectrometric (FIMS) fingerprints of 9 Aurantii Fructus Immaturus samples and 12 Poniciri Trifoliatae Fructus Immaturus samples were acquired and analyzed using principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA). The authentic herbs were differentiated from their counterfeits easily. Eight characteristic components which were responsible for the difference between the samples were tentatively identified. Furthermore, three out of the eight components, naringin, hesperidin, and neohesperidin, were quantified. The results are useful to help identify the authenticity of Aurantii Fructus Immaturus. PMID:25622204

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

NASA Astrophysics Data System (ADS)

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

2011-01-01

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

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

PubMed

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

2011-07-27

Our main goal was to investigate if robust chemical fingerprints could be developed for three Argentinean red wines based on organic, inorganic, and isotopic patterns, in relation to the regional soil composition. Soils and wines from three regions (Mendoza, San Juan, and Córdoba) and three varieties (Cabernet Sauvignon, Malbec, and Syrah) were collected. The phenolic profile was determined by HPLC-MS/MS and multielemental composition by ICP-MS; (87)Sr/(86)Sr and δ(13)C were determined by TIMS and IRMS, respectively. Chemometrics allowed robust differentiation between regions, wine varieties, and the same variety from different regions. Among phenolic compounds, resveratrol concentration was the most useful marker for wine differentiation, whereas Mg, K/Rb, Ca/Sr, and (87)Sr/(86)Sr were the main inorganic and isotopic parameters selected. Generalized Procrustes analysis (GPA) using two studied matrices (wine and soil) shows consensus between them and clear differences between studied areas. Finally, we applied a canonical correlation analysis, demonstrating significant correlation (r = 0.99; p < 0.001) between soil and wine composition. To our knowledge this is the first report combining independent variables, constructing a fingerprint including elemental composition, isotopic, and polyphenol patterns to differentiate wines, matching part of this fingerprint with the soil provenance.

Chemometric assessment of enhanced bioremediation of oil contaminated soils.

PubMed

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

2013-06-15

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

LC-MS based metabolomics and chemometrics study of the toxic effects of copper on Saccharomyces cerevisiae.

PubMed

Farrés, Mireia; Piña, Benjamí; Tauler, Romà

2016-08-01

Copper containing fungicides are used to protect vineyards from fungal infections. Higher residues of copper in grapes at toxic concentrations are potentially toxic and affect the microorganisms living in vineyards, such as Saccharomyces cerevisiae. In this study, the response of the metabolic profiles of S. cerevisiae at different concentrations of copper sulphate (control, 1 mM, 3 mM and 6 mM) was analysed by liquid chromatography coupled to mass spectrometry (LC-MS) and multivariate curve resolution-alternating least squares (MCR-ALS) using an untargeted metabolomics approach. Peak areas of the MCR-ALS resolved elution profiles in control and in Cu(ii)-treated samples were compared using partial least squares regression (PLSR) and PLS-discriminant analysis (PLS-DA), and the intracellular metabolites best contributing to sample discrimination were selected and identified. Fourteen metabolites showed significant concentration changes upon Cu(ii) exposure, following a dose-response effect. The observed changes were consistent with the expected effects of Cu(ii) toxicity, including oxidative stress and DNA damage. This research confirmed that LC-MS based metabolomics coupled to chemometric methods are a powerful approach for discerning metabolomics changes in S. cerevisiae and for elucidating modes of toxicity of environmental stressors, including heavy metals like Cu(ii).

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

PubMed

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

2017-04-06

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

[Quality evaluation of Artemisiae Argyi Folium based on fingerprint analysis and quantitative analysis of multicomponents].

PubMed

Guo, Long; Jiao, Qian; Zhang, Dan; Liu, Ai-Peng; Wang, Qian; Zheng, Yu-Guang

2018-03-01

Artemisiae Argyi Folium, the dried leaves of Artemisia argyi, has been widely used in traditional Chinese and folk medicines for treatment of hemorrhage, pain, and skin itch. Phytochemical studies indicated that volatile oil, organic acid and flavonoids were the main bioactive components in Artemisiae Argyi Folium. Compared to the volatile compounds, the research of nonvolatile compounds in Artemisiae Argyi Folium are limited. In the present study, an accurate and reliable fingerprint approach was developed using HPLC for quality control of Artemisiae Argyi Folium. A total of 10 common peaks were marked，and the similarity of all the Artemisiae Argyi Folium samples was above 0.940. The established fingerprint method could be used for quality control of Artemisiae Argyi Folium. Furthermore, an HPLC method was applied for simultaneous determination of seven bioactive compounds including five organic acids and two flavonoids in Artemisiae Argyi Folium and Artemisiae Lavandulaefoliae Folium samples. Moreover, chemometrics methods such as hierarchical clustering analysis and principal component analysis were performed to compare and discriminate the Artemisiae Argyi Folium and Artemisiae Lavandulaefoliae Folium based on the quantitative data of analytes. The results indicated that simultaneous quantification of multicomponents coupled with chemometrics analysis could be a well-acceptable strategy to identify and evaluate the quality of Artemisiae Argyi Folium. Copyright© by the Chinese Pharmaceutical Association.

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

PubMed

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

2018-01-15

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

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

PubMed Central

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

2018-01-01

Origin traceability is an important step to control the nutritional and pharmacological quality of food products. Boletus edulis mushroom is a well-known food resource in the world. Its nutritional and medicinal properties are drastically varied depending on geographical origins. In this study, three sensor systems (inductively coupled plasma atomic emission spectrophotometer (ICP-AES), ultraviolet-visible (UV-Vis) and Fourier transform mid-infrared spectroscopy (FT-MIR)) were applied for the origin traceability of 184 mushroom samples (caps and stipes) in combination with chemometrics. The difference between cap and stipe was clearly illustrated based on a single sensor technique, respectively. Feature variables from three instruments were used for origin traceability. Two supervised classification methods, partial least square discriminant analysis (FLS-DA) and grid search support vector machine (GS-SVM), were applied to develop mathematical models. Two steps (internal cross-validation and external prediction for unknown samples) were used to evaluate the performance of a classification model. The result is satisfactory with high accuracies ranging from 90.625% to 100%. These models also have an excellent generalization ability with the optimal parameters. Based on the combination of three sensory systems, our study provides a multi-sensory and comprehensive origin traceability of B. edulis mushrooms. PMID:29342969

Least-Squares Regression and Spectral Residual Augmented Classical Least-Squares Chemometric Models for Stability-Indicating Analysis of Agomelatine and Its Degradation Products: A Comparative Study.

PubMed

Naguib, Ibrahim A; Abdelrahman, Maha M; El Ghobashy, Mohamed R; Ali, Nesma A

2016-01-01

Two accurate, sensitive, and selective stability-indicating methods are developed and validated for simultaneous quantitative determination of agomelatine (AGM) and its forced degradation products (Deg I and Deg II), whether in pure forms or in pharmaceutical formulations. Partial least-squares regression (PLSR) and spectral residual augmented classical least-squares (SRACLS) are two chemometric models that are being subjected to a comparative study through handling UV spectral data in range (215-350 nm). For proper analysis, a three-factor, four-level experimental design was established, resulting in a training set consisting of 16 mixtures containing different ratios of interfering species. An independent test set consisting of eight mixtures was used to validate the prediction ability of the suggested models. The results presented indicate the ability of mentioned multivariate calibration models to analyze AGM, Deg I, and Deg II with high selectivity and accuracy. The analysis results of the pharmaceutical formulations were statistically compared to the reference HPLC method, with no significant differences observed regarding accuracy and precision. The SRACLS model gives comparable results to the PLSR model; however, it keeps the qualitative spectral information of the classical least-squares algorithm for analyzed components.

Applying Fourier Transform Mid Infrared Spectroscopy to Detect the Adulteration of Salmo salar with Oncorhynchus mykiss

PubMed Central

Moreira, Maria João

2018-01-01

The aim of this study was to evaluate the potential of Fourier transform infrared (FTIR) spectroscopy coupled with chemometric methods to detect fish adulteration. Muscles of Atlantic salmon (Salmo salar) (SS) and Salmon trout (Onconrhynchus mykiss) (OM) muscles were mixed in different percentages and transformed into mini-burgers. These were stored at 3 °C, then examined at 0, 72, 160, and 240 h for deteriorative microorganisms. Mini-burgers was submitted to Soxhlet extraction, following which lipid extracts were analyzed by FTIR. The principal component analysis (PCA) described the studied adulteration using four principal components with an explained variance of 95.60%. PCA showed that the absorbance in the spectral region from 721, 1097, 1370, 1464, 1655, 2805, to 2935, 3009 cm−1 may be attributed to biochemical fingerprints related to differences between SS and OM. The partial least squares regression (PLS-R) predicted the presence/absence of adulteration in fish samples of an external set with high accuracy. The proposed methods have the advantage of allowing quick measurements, despite the storage time of the adulterated fish. FTIR combined with chemometrics showed that a methodology to identify the adulteration of SS with OM can be established, even when stored for different periods of time. PMID:29621135

Formative Qualitative Evaluation for "Exploratory" ITS Research.

ERIC Educational Resources Information Center

Murray, Tom

1993-01-01

Discusses evaluation methods applicable to exploratory research areas, provides an overview of qualitative and formative methods for exploratory research on intelligent tutoring systems (ITS) and describes an exploratory study in ITS knowledge acquisition which involved working with three educators to build an ITS for high school physics.…

Chemical Sensing in Process Analysis.

ERIC Educational Resources Information Center

Hirschfeld, T.; And Others

1984-01-01

Discusses: (1) rationale for chemical sensors in process analysis; (2) existing types of process chemical sensors; (3) sensor limitations, considering lessons of chemometrics; (4) trends in process control sensors; and (5) future prospects. (JN)

Effects of Type of Exploratory Strategy and Prior Knowledge on Middle School Students' Learning of Chemical Formulas from a 3D Role-Playing Game

ERIC Educational Resources Information Center

Chen, Ming-Puu; Wong, Yu-Ting; Wang, Li-Chun

2014-01-01

The purpose of this study was to examine the effects of the type of exploratory strategy and level of prior knowledge on middle school students' performance and motivation in learning chemical formulas via a 3D role-playing game (RPG). Two types of exploratory strategies-RPG exploratory with worked-example and RPG exploratory without…

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

PubMed

Sun, Li-Li; Wang, Meng; Zhang, Hui-Jie; Liu, Ya-Nan; Ren, Xiao-Liang; Deng, Yan-Ru; Qi, Ai-Di

2018-01-01

Polygoni Multiflori Radix (PMR) is increasingly being used not just as a traditional herbal medicine but also as a popular functional food. In this study, multivariate chemometric methods and mass spectrometry were combined to analyze the ultra-high-performance liquid chromatograph (UPLC) fingerprints of PMR from six different geographical origins. A chemometric strategy based on multivariate curve resolution-alternating least squares (MCR-ALS) and three classification methods is proposed to analyze the UPLC fingerprints obtained. Common chromatographic problems, including the background contribution, baseline contribution, and peak overlap, were handled by the established MCR-ALS model. A total of 22 components were resolved. Moreover, relative species concentrations were obtained from the MCR-ALS model, which was used for multivariate classification analysis. Principal component analysis (PCA) and Ward's method have been applied to classify 72 PMR samples from six different geographical regions. The PCA score plot showed that the PMR samples fell into four clusters, which related to the geographical location and climate of the source areas. The results were then corroborated by Ward's method. In addition, according to the variance-weighted distance between cluster centers obtained from Ward's method, five components were identified as the most significant variables (chemical markers) for cluster discrimination. A counter-propagation artificial neural network has been applied to confirm and predict the effects of chemical markers on different samples. Finally, the five chemical markers were identified by UPLC-quadrupole time-of-flight mass spectrometer. Components 3, 12, 16, 18, and 19 were identified as 2,3,5,4'-tetrahydroxy-stilbene-2-O-β-d-glucoside, emodin-8-O-β-d-glucopyranoside, emodin-8-O-(6'-O-acetyl)-β-d-glucopyranoside, emodin, and physcion, respectively. In conclusion, the proposed method can be applied for the comprehensive analysis of natural samples. Copyright © 2016. Published by Elsevier B.V.

Chemometric Profile of Root Extracts of Rhodiola imbricata Edgew. with Hyphenated Gas Chromatography Mass Spectrometric Technique

PubMed Central

Tayade, Amol B.; Dhar, Priyanka; Kumar, Jatinder; Sharma, Manu; Chauhan, Rajinder S.; Chaurasia, Om P.; Srivastava, Ravi B.

2013-01-01

Rhodiola imbricata Edgew. (Rose root or Arctic root or Golden root or Shrolo), belonging to the family Crassulaceae, is an important food crop and medicinal plant in the Indian trans-Himalayan cold desert. Chemometric profile of the n-hexane, chloroform, dichloroethane, ethyl acetate, methanol, and 60% ethanol root extracts of R. imbricata were performed by hyphenated gas chromatography mass spectrometry (GC/MS) technique. GC/MS analysis was carried out using Thermo Finnigan PolarisQ Ion Trap GC/MS MS system comprising of an AS2000 liquid autosampler. Interpretation on mass spectrum of GC/MS was done using the NIST/EPA/NIH Mass Spectral Database, with NIST MS search program v.2.0g. Chemometric profile of root extracts revealed the presence of 63 phyto-chemotypes, among them, 1-pentacosanol; stigmast-5-en-3-ol, (3β,24S); 1-teracosanol; 1-henteracontanol; 17-pentatriacontene; 13-tetradecen-1-ol acetate; methyl tri-butyl ammonium chloride; bis(2-ethylhexyl) phthalate; 7,8-dimethylbenzocyclooctene; ethyl linoleate; 3-methoxy-5-methylphenol; hexadecanoic acid; camphor; 1,3-dimethoxybenzene; thujone; 1,3-benzenediol, 5-pentadecyl; benzenemethanol, 3-hydroxy, 5-methoxy; cholest-4-ene-3,6-dione; dodecanoic acid, 3-hydroxy; octadecane, 1-chloro; ethanone, 1-(4-hydroxyphenyl); α-tocopherol; ascaridole; campesterol; 1-dotriacontane; heptadecane, 9-hexyl were found to be present in major amount. Eventually, in the present study we have found phytosterols, terpenoids, fatty acids, fatty acid esters, alkyl halides, phenols, alcohols, ethers, alkanes, and alkenes as the major group of phyto-chemotypes in the different root extracts of R. imbricata. All these compounds identified by GC/MS analysis were further investigated for their biological activities and it was found that they possess a diverse range of positive pharmacological actions. In future, isolation of individual phyto-chemotypes and subjecting them to biological activity will definitely prove fruitful results in designing a novel drug. PMID:23326358

1H-NMR, 1H-NMR T2-edited, and 2D-NMR in bipolar disorder metabolic profiling.

PubMed

Sethi, Sumit; Pedrini, Mariana; Rizzo, Lucas B; Zeni-Graiff, Maiara; Mas, Caroline Dal; Cassinelli, Ana Cláudia; Noto, Mariane N; Asevedo, Elson; Cordeiro, Quirino; Pontes, João G M; Brasil, Antonio J M; Lacerda, Acioly; Hayashi, Mirian A F; Poppi, Ronei; Tasic, Ljubica; Brietzke, Elisa

2017-12-01

The objective of this study was to identify molecular alterations in the human blood serum related to bipolar disorder, using nuclear magnetic resonance (NMR) spectroscopy and chemometrics. Metabolomic profiling, employing 1 H-NMR, 1 H-NMR T 2 -edited, and 2D-NMR spectroscopy and chemometrics of human blood serum samples from patients with bipolar disorder (n = 26) compared with healthy volunteers (n = 50) was performed. The investigated groups presented distinct metabolic profiles, in which the main differential metabolites found in the serum sample of bipolar disorder patients compared with those from controls were lipids, lipid metabolism-related molecules (choline, myo-inositol), and some amino acids (N-acetyl-L-phenyl alanine, N-acetyl-L-aspartyl-L-glutamic acid, L-glutamine). In addition, amygdalin, α-ketoglutaric acid, and lipoamide, among other compounds, were also present or were significantly altered in the serum of bipolar disorder patients. The data presented herein suggest that some of these metabolites differentially distributed between the groups studied may be directly related to the bipolar disorder pathophysiology. The strategy employed here showed significant potential for exploring pathophysiological features and molecular pathways involved in bipolar disorder. Thus, our findings may contribute to pave the way for future studies aiming at identifying important potential biomarkers for bipolar disorder diagnosis or progression follow-up.

STATISTICAL SAMPLING AND DATA ANALYSIS

EPA Science Inventory

Research is being conducted to develop approaches to improve soil and sediment sampling techniques, measurement design and geostatistics, and data analysis via chemometric, environmetric, and robust statistical methods. Improvements in sampling contaminated soil and other hetero...

Raman Spectroscopy and Chemometrics for Identification and Strain Discrimination of the Wine Spoilage Yeasts Saccharomyces cerevisiae, Zygosaccharomyces bailii, and Brettanomyces bruxellensis

PubMed Central

Thornton, Mark A.; Thornton, Roy J.

2013-01-01

The yeasts Zygosaccharomyces bailii, Dekkera bruxellensis (anamorph, Brettanomyces bruxellensis), and Saccharomyces cerevisiae are the major spoilage agents of finished wine. A novel method using Raman spectroscopy in combination with a chemometric classification tool has been developed for the identification of these yeast species and for strain discrimination of these yeasts. Raman spectra were collected for six strains of each of the yeasts Z. bailii, B. bruxellensis, and S. cerevisiae. The yeasts were classified with high sensitivity at the species level: 93.8% for Z. bailii, 92.3% for B. bruxellensis, and 98.6% for S. cerevisiae. Furthermore, we have demonstrated that it is possible to discriminate between strains of these species. These yeasts were classified at the strain level with an overall accuracy of 81.8%. PMID:23913433

Raman spectroscopy and chemometrics for identification and strain discrimination of the wine spoilage yeasts Saccharomyces cerevisiae, Zygosaccharomyces bailii, and Brettanomyces bruxellensis.

PubMed

Rodriguez, Susan B; Thornton, Mark A; Thornton, Roy J

2013-10-01

The yeasts Zygosaccharomyces bailii, Dekkera bruxellensis (anamorph, Brettanomyces bruxellensis), and Saccharomyces cerevisiae are the major spoilage agents of finished wine. A novel method using Raman spectroscopy in combination with a chemometric classification tool has been developed for the identification of these yeast species and for strain discrimination of these yeasts. Raman spectra were collected for six strains of each of the yeasts Z. bailii, B. bruxellensis, and S. cerevisiae. The yeasts were classified with high sensitivity at the species level: 93.8% for Z. bailii, 92.3% for B. bruxellensis, and 98.6% for S. cerevisiae. Furthermore, we have demonstrated that it is possible to discriminate between strains of these species. These yeasts were classified at the strain level with an overall accuracy of 81.8%.

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

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

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

PubMed

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

2012-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

Chemical Fingerprint and Quantitative Analysis for the Quality Evaluation of Docynia dcne Leaves by High-Performance Liquid Chromatography Coupled with Chemometrics Analysis.

PubMed

Zhang, Xiaoyu; Mei, Xueran; Wang, Zhanguo; Wu, Jing; Liu, Gang; Hu, Huiling; Li, Qijuan

2018-05-24

Docynia dcne leaf from the genus of Docynia Dcne (including three species of Docynia delavayi, Docynia indica and Docynia longiunguis.) is an important raw material of local ethnic minority tea, ethnomedicines and food supplements in southwestern areas of China. However, D. dcne leaves from these three species are usually used confusingly, which could influence the therapeutic effect of it. A rapid and effective method for the chemical fingerprint and quantitative analysis to evaluate the quality of D. dcne leaves was established. The chemometric methods, including similarity analysis, hierarchical cluster analysis and partial least-squares discrimination analysis, were applied to distinguish 30 batches of D. dcne leaf samples from these three species. The above results could validate each other and successfully group these samples into three categories which were closely related to the species of D. dcne leaves. Moreover, isoquercitrin and phlorizin were screened as the chemical markers to evaluate the quality of D. dcne leaves from different species. And the contents of isoquercitrin and phlorizin varied remarkably in these samples, with ranges of 6.41-38.84 and 95.73-217.76 mg/g, respectively. All the results indicated that an integration method of chemical fingerprint couple with chemometrics analysis and quantitative assessment was a powerful and beneficial tool for quality control of D. dcne leaves, and could be applied also for differentiation and quality control of other herbal preparations.

Signature-Discovery Approach for Sample Matching of a Nerve-Agent Precursor using Liquid Chromatography–Mass Spectrometry, XCMS, and Chemometrics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fraga, Carlos G.; Clowers, Brian H.; Moore, Ronald J.

2010-05-15

This report demonstrates the use of bioinformatic and chemometric tools on liquid chromatography mass spectrometry (LC-MS) data for the discovery of ultra-trace forensic signatures for sample matching of various stocks of the nerve-agent precursor known as methylphosphonic dichloride (dichlor). The use of the bioinformatic tool known as XCMS was used to comprehensively search and find candidate LC-MS peaks in a known set of dichlor samples. These candidate peaks were down selected to a group of 34 impurity peaks. Hierarchal cluster analysis and factor analysis demonstrated the potential of these 34 impurities peaks for matching samples based on their stock source.more » Only one pair of dichlor stocks was not differentiated from one another. An acceptable chemometric approach for sample matching was determined to be variance scaling and signal averaging of normalized duplicate impurity profiles prior to classification by k-nearest neighbors. Using this approach, a test set of dichlor samples were all correctly matched to their source stock. The sample preparation and LC-MS method permitted the detection of dichlor impurities presumably in the parts-per-trillion (w/w). The detection of a common impurity in all dichlor stocks that were synthesized over a 14-year period and by different manufacturers was an unexpected discovery. Our described signature-discovery approach should be useful in the development of a forensic capability to help in criminal investigations following chemical attacks.« less

Use of Vis/NIRS for the determination of sugar content of cola soft drinks based on chemometric methods

NASA Astrophysics Data System (ADS)

Liu, Fei; He, Yong

2008-03-01

Three different chemometric methods were performed for the determination of sugar content of cola soft drinks using visible and near infrared spectroscopy (Vis/NIRS). Four varieties of colas were prepared and 180 samples (45 samples for each variety) were selected for the calibration set, while 60 samples (15 samples for each variety) for the validation set. The smoothing way of Savitzky-Golay, standard normal variate (SNV) and Savitzky-Golay first derivative transformation were applied for the pre-processing of spectral data. The first eleven principal components (PCs) extracted by partial least squares (PLS) analysis were employed as the inputs of BP neural network (BPNN) and least squares-support vector machine (LS-SVM) model. Then the BPNN model with the optimal structural parameters and LS-SVM model with radial basis function (RBF) kernel were applied to build the regression model with a comparison of PLS regression. The correlation coefficient (r), root mean square error of prediction (RMSEP) and bias for prediction were 0.971, 1.259 and -0.335 for PLS, 0.986, 0.763, and -0.042 for BPNN, while 0.978, 0.995 and -0.227 for LS-SVM, respectively. All the three methods supplied a high and satisfying precision. The results indicated that Vis/NIR spectroscopy combined with chemometric methods could be utilized as a high precision way for the determination of sugar content of cola soft drinks.

Chemometric evaluation of concentrations of trace elements in intervertebral disc tissue in patient with degenerative disc disease.

PubMed

Kubaszewski, Łukasz; Zioła-Frankowska, Anetta; Gasik, Zuzanna; Frankowski, Marcin; Dąbrowski, Mikołaj; Molisak, Bartłomiej; Kaczmarczyk, Jacek; Gasik, Robert

2017-12-23

The work is designed to uncover the pattern of mutual relation among trace elements and epidemiological data in the degenerated intervertebral disk tissue in humans. Hitherto the reason of the degenerative process is not fully understood. Trace elements are the basic components of the biological compound related both its metabolism as well as environmental exposure. The relation pattern among elements occurs gives new perspective in solving the cause of the disease. We have analysed trace elements content in the 30 intervertebral disc from 22 patients with degenerative disc disease. The concentrations of Al, Cu, Cd, Mo, Ni and Pb were determined with Atomic Absorption Spectrometry. To analyse the multidimentional relation between trace element concentration and epidemiological data the chemometric analysis was applied. The similarity have been shown in occurrence of following pairs: Cd-Mo as well as Mg-Zn. The second pair was correlated with Pb concentration. Pb levels are observed to be competitive to Cu concentration. Cd concentration was related to Zn and Mg deficiency. No single but rather cluster of epidemiological data show observable influence on the TE tissue variance. Zn and Cu was related to the male sex. Operation with orthopedic implants were related to combined Al, Mo and Zn concentration. This is the first chemometric analysis of trace elements in disk tissue. It shows multidimentional relations that are missed by the classical statistic. The analysis shows significant relation. The nature of the relations is the basis for further metabolic and environmental research.

Pattern recognition and genetic algorithms for discrimination of orange juices and reduction of significant components from headspace solid-phase microextraction.

PubMed

Rinaldi, Maurizio; Gindro, Roberto; Barbeni, Massimo; Allegrone, Gianna

2009-01-01

Orange (Citrus sinensis L.) juice comprises a complex mixture of volatile components that are difficult to identify and quantify. Classification and discrimination of the varieties on the basis of the volatile composition could help to guarantee the quality of a juice and to detect possible adulteration of the product. To provide information on the amounts of volatile constituents in fresh-squeezed juices from four orange cultivars and to establish suitable discrimination rules to differentiate orange juices using new chemometric approaches. Fresh juices of four orange cultivars were analysed by headspace solid-phase microextraction (HS-SPME) coupled with GC-MS. Principal component analysis, linear discriminant analysis and heuristic methods, such as neural networks, allowed clustering of the data from HS-SPME analysis while genetic algorithms addressed the problem of data reduction. To check the quality of the results the chemometric techniques were also evaluated on a sample. Thirty volatile compounds were identified by HS-SPME and GC-MS analyses and their relative amounts calculated. Differences in composition of orange juice volatile components were observed. The chosen orange cultivars could be discriminated using neural networks, genetic relocation algorithms and linear discriminant analysis. Genetic algorithms applied to the data were also able to detect the most significant compounds. SPME is a useful technique to investigate orange juice volatile composition and a flexible chemometric approach is able to correctly separate the juices.

A metabolic fingerprinting approach based on selected ion flow tube mass spectrometry (SIFT-MS) and chemometrics: A reliable tool for Mediterranean origin-labeled olive oils authentication.

PubMed

Bajoub, Aadil; Medina-Rodríguez, Santiago; Ajal, El Amine; Cuadros-Rodríguez, Luis; Monasterio, Romina Paula; Vercammen, Joeri; Fernández-Gutiérrez, Alberto; Carrasco-Pancorbo, Alegría

2018-04-01

Selected Ion flow tube mass spectrometry (SIFT-MS) in combination with chemometrics was used to authenticate the geographical origin of Mediterranean virgin olive oils (VOOs) produced under geographical origin labels. In particular, 130 oil samples from six different Mediterranean regions (Kalamata (Greece); Toscana (Italy); Meknès and Tyout (Morocco); and Priego de Córdoba and Baena (Spain)) were considered. The headspace volatile fingerprints were measured by SIFT-MS in full scan with H 3 O + , NO + and O 2 + as precursor ions and the results were subjected to chemometric treatments. Principal Component Analysis (PCA) was used for preliminary multivariate data analysis and Partial Least Squares-Discriminant Analysis (PLS-DA) was applied to build different models (considering the three reagent ions) to classify samples according to the country of origin and regions (within the same country). The multi-class PLS-DA models showed very good performance in terms of fitting accuracy (98.90-100%) and prediction accuracy (96.70-100% accuracy for cross validation and 97.30-100% accuracy for external validation (test set)). Considering the two-class PLS-DA models, the one for the Spanish samples showed 100% sensitivity, specificity and accuracy in calibration, cross validation and external validation; the model for Moroccan oils also showed very satisfactory results (with perfect scores for almost every parameter in all the cases). Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

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

2017-09-05

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

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

PubMed

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

2009-07-01

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

Laser-induced breakdown spectroscopy (LIBS) combined with hyperspectral imaging for the evaluation of printed circuit board composition.

PubMed

Carvalho, Rodrigo R V; Coelho, Jomarc A O; Santos, Jozemir M; Aquino, Francisco W B; Carneiro, Renato L; Pereira-Filho, Edenir R

2015-03-01

In this study, laser-induced breakdown spectroscopy (LIBS) was combined with chemometric strategies (PCA, Principal Component Analysis) and scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS) to investigate the metal composition of a printed circuit board (PCB) sample from a mobile phone. Scanning electron microscopy-EDS was used for two main reasons: it was possible at the same time to visualize the sample surface, craters (made by the laser pulses) and also the chemical composition of the samples. A 30 mm×40 mm area of the mobile phone PCB sample, which was manufactured in 2011, was investigated. In this case, a matrix with 30 rows and 40 columns (1200 points) was analyzed, and 10 pulses were performed at each point. A total of 12,000 emission spectra were recorded in the wavelength range from 186 to 1040 nm. After an initial exploratory investigation using PCA, 18 emission lines were selected (representing the elements Al, Au, Ba, Ca, Co, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Sb, Si, Sn, Ti and Zn) and then normalized by the relative intensities, and a new PCA was calculated with the autoscaled data. For example, Au and Si were mainly observed in the superficial electrical contacts and in the bulk of the PCB, respectively. A second sample (a mouse PCB) was also analyzed and Pb (emission lines 357.273, 363.956, 368.346, 373.994 and 405.780 nm) was identified in the solders. In addition, this element was determined using FAAS (flame atomic absorption spectrometry) and the Pb concentration was around 25% (w/w). This study opens the possibility for improved recycling processes and the chemical investigation of solid samples measuring a few millimeters in dimension without sample preparation. Copyright © 2014 Elsevier B.V. All rights reserved.

Classification of edible oils and modeling of their physico-chemical properties by chemometric methods using mid-IR spectroscopy

NASA Astrophysics Data System (ADS)

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

This research work describes two studies for the classification and characterization of edible oils and its quality parameters through Fourier transform mid infrared spectroscopy (FT-mid-IR) together with chemometric methods. The discrimination of canola, sunflower, corn and soybean oils was investigated using SVM-DA, SIMCA and PLS-DA. Using FT-mid-IR, DPLS was able to classify 100% of the samples from the validation set, but SIMCA and SVM-DA were not. The quality parameters: refraction index and relative density of edible oils were obtained from reference methods. Prediction models for FT-mid-IR spectra were calculated for these quality parameters using partial least squares (PLS) and support vector machines (SVM). Several preprocessing alternatives (first derivative, multiplicative scatter correction, mean centering, and standard normal variate) were investigated. The best result for the refraction index was achieved with SVM as well as for the relative density except when the preprocessing combination of mean centering and first derivative was used. For both of quality parameters, the best results obtained for the figures of merit expressed by the root mean square error of cross validation (RMSECV) and prediction (RMSEP) were equal to 0.0001.

Discrimination and Measurements of Three Flavonols with Similar Structure Using Terahertz Spectroscopy and Chemometrics

NASA Astrophysics Data System (ADS)

Yan, Ling; Liu, Changhong; Qu, Hao; Liu, Wei; Zhang, Yan; Yang, Jianbo; Zheng, Lei

2018-03-01

Terahertz (THz) technique, a recently developed spectral method, has been researched and used for the rapid discrimination and measurements of food compositions due to its low-energy and non-ionizing characteristics. In this study, THz spectroscopy combined with chemometrics has been utilized for qualitative and quantitative analysis of myricetin, quercetin, and kaempferol with concentrations of 0.025, 0.05, and 0.1 mg/mL. The qualitative discrimination was achieved by KNN, ELM, and RF models with the spectra pre-treatments. An excellent discrimination (100% CCR in the prediction set) could be achieved using the RF model. Furthermore, the quantitative analyses were performed by partial least square regression (PLSR) and least squares support vector machine (LS-SVM). Comparing to the PLSR models, the LS-SVM yielded better results with low RMSEP (0.0044, 0.0039, and 0.0048), higher Rp (0.9601, 0.9688, and 0.9359), and higher RPD (8.6272, 9.6333, and 7.9083) for myricetin, quercetin, and kaempferol, respectively. Our results demonstrate that THz spectroscopy technique is a powerful tool for identification of three flavonols with similar chemical structures and quantitative determination of their concentrations.

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

PubMed

Gallotta, Fabiana D C; Christensen, Jan H

2012-04-27

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

Optimisation of the formulation of a bubble bath by a chemometric approach market segmentation and optimisation.

PubMed

Marengo, Emilio; Robotti, Elisa; Gennaro, Maria Carla; Bertetto, Mariella

2003-03-01

The optimisation of the formulation of a commercial bubble bath was performed by chemometric analysis of Panel Tests results. A first Panel Test was performed to choose the best essence, among four proposed to the consumers; the best essence chosen was used in the revised commercial bubble bath. Afterwards, the effect of changing the amount of four components (the amount of primary surfactant, the essence, the hydratant and the colouring agent) of the bubble bath was studied by a fractional factorial design. The segmentation of the bubble bath market was performed by a second Panel Test, in which the consumers were requested to evaluate the samples coming from the experimental design. The results were then treated by Principal Component Analysis. The market had two segments: people preferring a product with a rich formulation and people preferring a poor product. The final target, i.e. the optimisation of the formulation for each segment, was obtained by the calculation of regression models relating the subjective evaluations given by the Panel and the compositions of the samples. The regression models allowed to identify the best formulations for the two segments ofthe market.

Advances in high-resolution mass spectrometry based on metabolomics studies for food--a review.

PubMed

Rubert, Josep; Zachariasova, Milena; Hajslova, Jana

2015-01-01

Food authenticity becomes a necessity for global food policies, since food placed in the market without fail has to be authentic. It has always been a challenge, since in the past minor components, called also markers, have been mainly monitored by chromatographic methods in order to authenticate the food. Nevertheless, nowadays, advanced analytical methods have allowed food fingerprints to be achieved. At the same time they have been also combined with chemometrics, which uses statistical methods in order to verify food and to provide maximum information by analysing chemical data. These sophisticated methods based on different separation techniques or stand alone have been recently coupled to high-resolution mass spectrometry (HRMS) in order to verify the authenticity of food. The new generation of HRMS detectors have experienced significant advances in resolving power, sensitivity, robustness, extended dynamic range, easier mass calibration and tandem mass capabilities, making HRMS more attractive and useful to the food metabolomics community, therefore becoming a reliable tool for food authenticity. The purpose of this review is to summarise and describe the most recent metabolomics approaches in the area of food metabolomics, and to discuss the strengths and drawbacks of the HRMS analytical platforms combined with chemometrics.

Traceability of Opuntia ficus-indica L. Miller by ICP-MS multi-element profile and chemometric approach.

PubMed

Mottese, Antonio Francesco; Naccari, Clara; Vadalà, Rossella; Bua, Giuseppe Daniel; Bartolomeo, Giovanni; Rando, Rossana; Cicero, Nicola; Dugo, Giacomo

2018-01-01

Opuntia ficus-indica L. Miller fruits, particularly 'Ficodindia dell'Etna' of Biancavilla (POD), 'Fico d'india tradizionale di Roccapalumba' with protected brand and samples from an experimental field in Pezzolo (Sicily) were analyzed by inductively coupled plasma mass spectrometry in order to determine the multi-element profile. A multivariate chemometric approach, specifically principal component analysis (PCA), was applied to individuate how mineral elements may represent a marker of geographic origin, which would be useful for traceability. PCA has allowed us to verify that the geographical origin of prickly pear fruits is significantly influenced by trace element content, and the results found in Biancavilla PDO samples were linked to the geological composition of this volcanic areas. It was observed that two principal components accounted for 72.03% of the total variance in the data and, in more detail, PC1 explains 45.51% and PC2 26.52%, respectively. This study demonstrated that PCA is an integrated tool for the traceability of food products and, at the same time, a useful method of authentication of typical local fruits such as prickly pear. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Compositional variations for alpha-galactosides in different species of leguminosae, brassicaceae, and barley: a chemotaxonomic study based on chemometrics and high-performance capillary electrophoresis.

PubMed

Andersen, Keld Ejdrup; Bjergegaard, Charlotte; Møller, Peter; Sørensen, Jens Christian; Sørensen, Hilmer

2005-07-13

The contents of raffinose family oligosaccharides (RFO) and sucrose in Brassica, Lupinus, Pisum, and Hordeum species were investigated by chemometric principal component analysis (PCA). Hordeum samples contained sucrose and raffinose, and Brassica samples all contained sucrose, raffinose, and stachyose. In addition to these, the Pisum samples contained verbascose and the Lupinus samples also contained ajugose. High stachyose and low ajugose contents were found in Lupinus albus in contrast to Lupinus angustifolius, having low stachyose and high ajugose contents. Lupinus luteus had average stachyose and ajugose contents, whereas large amounts of verbascose were accumulated in these seeds. Lupinus mutabilis had high stachyose and low ajugose contents, similar to the composition in L. albus but showing higher raffinose content. The Brassica samples also showed compositional RFO variations within the species, and subgroup formations were discovered within the investigated Brassica napus varieties. PCA results indicated compositional variations between the investigated genera and within the various species of value as chemotaxonomic defined parameters and as tools in evaluations of authenticity/falsifications when RFO-containing plants are used as, for example, feed and food additives.

Propellant's differentiation using FTIR-photoacoustic detection for forensic studies of improvised explosive devices.

PubMed

Álvarez, Ángela; Yáñez, Jorge; Contreras, David; Saavedra, Renato; Sáez, Pedro; Amarasiriwardena, Dulasiri

2017-11-01

The use of propellant for making improvised explosive devices (IED) is an incipient criminal practice. Propellant can be used as initiator in explosive mixtures along with other components such as coal, ammonium nitrate, sulfur, etc. The identification of the propellant's brand used in homemade explosives can provide additional forensic information of this evidence. In this work, four of the most common propellant brands were characterized by Fourier-transform infrared photoacoustic spectroscopy (FTIR-PAS) which is a non-destructive micro-analytical technique. Spectra shows characteristic signals of typical compounds in the propellants, such as nitrocellulose, nitroglycerin, guanidine, diphenylamine, etc. The differentiation of propellant components was achieved by using FTIR-PAS combined with chemometric methods of classification. Principal component analysis (PCA) and soft independent modelling of class analogy (SIMCA) were used to achieve an effective differentiation and classification (100%) of propellant brands. Furthermore, propellant brand differentiation was also assessed using partial least squares discriminant analyses (PLS-DA) by leave one out cross (∼97%) and external (∼100%) validation method. Our results show the ability of FTIR-PAS combined with chemometric analysis to identify and differentiate propellant brands in different explosive formulations of IED. Copyright © 2017 Elsevier B.V. All rights reserved.

Chemometric optimization of the robustness of the near infrared spectroscopic method in wheat quality control.

PubMed

Pojić, Milica; Rakić, Dušan; Lazić, Zivorad

2015-01-01

A chemometric approach was applied for the optimization of the robustness of the NIRS method for wheat quality control. Due to the high number of experimental (n=6) and response variables to be studied (n=7) the optimization experiment was divided into two stages: screening stage in order to evaluate which of the considered variables were significant, and optimization stage to optimize the identified factors in the previously selected experimental domain. The significant variables were identified by using fractional factorial experimental design, whilst Box-Wilson rotatable central composite design (CCRD) was run to obtain the optimal values for the significant variables. The measured responses included: moisture, protein and wet gluten content, Zeleny sedimentation value and deformation energy. In order to achieve the minimal variation in responses, the optimal factor settings were found by minimizing the propagation of error (POE). The simultaneous optimization of factors was conducted by desirability function. The highest desirability of 87.63% was accomplished by setting up experimental conditions as follows: 19.9°C for sample temperature, 19.3°C for ambient temperature and 240V for instrument voltage. Copyright © 2014 Elsevier B.V. All rights reserved.

Botanical discrimination of Greek unifloral honeys with physico-chemical and chemometric analyses.

PubMed

Karabagias, Ioannis K; Badeka, Anastasia V; Kontakos, Stavros; Karabournioti, Sofia; Kontominas, Michael G

2014-12-15

The aim of the present study was to investigate the possibility of characterisation and classification of Greek unifloral honeys (pine, thyme, fir and orange blossom) according to botanical origin using volatile compounds, conventional physico-chemical parameters and chemometric analyses (MANOVA and Linear Discriminant Analysis). For this purpose, 119 honey samples were collected during the harvesting period 2011 from 14 different regions in Greece known to produce unifloral honey of good quality. Physico-chemical analysis included the identification and semi quantification of fifty five volatile compounds performed by Headspace Solid Phase Microextraction coupled to gas chromatography/mass spectroscopy and the determination of conventional quality parameters such as pH, free, lactonic, total acidity, electrical conductivity, moisture, ash, lactonic/free acidity ratio and colour parameters L, a, b. Results showed that using 40 diverse variables (30 volatile compounds of different classes and 10 physico-chemical parameters) the honey samples were satisfactorily classified according to botanical origin using volatile compounds (84.0% correct prediction), physicochemical parameters (97.5% correct prediction), and the combination of both (95.8% correct prediction) indicating that multi element analysis comprises a powerful tool for honey discrimination purposes. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed

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

2015-03-05

Forty ampholytic compounds of biological and pharmaceutical relevance were subjected to chemometric analysis based on unsupervised and supervised learning algorithms. This enabled relations to be found between empirical spectral characteristics derived from electronic absorption data and structural and physicochemical parameters predicted by quantum chemistry methods or phenomenological relationships based on additivity rules. It was found that the energies of long wavelength absorption bands are correlated through multiparametric linear relationships with parameters reflecting the bulkiness features of the absorbing molecules as well as their nucleophilicity and electrophilicity. These dependences enable the quantitative analysis of spectral features of the compounds, as well as a comparison of their similarities and certain pharmaceutical and biological features. Three QSPR models to predict the energies of long-wavelength absorption in buffers with pH=2.5 and pH=7.0, as well as in methanol, were developed and validated in this study. These models can be further used to predict the long-wavelength absorption energies of untested substances (if they are structurally similar to the training compounds). Copyright © 2014 Elsevier B.V. All rights reserved.

Detection of goat body fat adulteration in pure ghee using ATR-FTIR spectroscopy coupled with chemometric strategy.

PubMed

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

2016-10-01

Ghee forms an important component of the diet of human beings due to its rich flavor and high nutritive value. This high priced fat is prone to adulteration with cheaper fats. ATR-FTIR spectroscopy coupled with chemometrics was applied for determining the presence of goat body fat in ghee (@1, 3, 5, 10, 15 and 20% level in the laboratory made/spiked samples). The spectra of pure (ghee and goat body fat) and spiked samples were taken in the wavenumber range of 4000-500 cm -1 . Separated clusters of pure ghee and spiked samples were obtained on applying principal component analysis at 5% level of significance in the selected wavenumber range (1786-1680, 1490-919 and 1260-1040 cm -1 ). SIMCA was applied for classification of samples and pure ghee showed 100% classification efficiency. The value of R 2 was found to be >0.99 for calibration and validation sets using partial least square method at all the selected wavenumber range which indicate that the model was well developed. The study revealed that the spiked samples of goat body fat could be detected even at 1% level in ghee.

Fingerprint profiles of flavonoid compounds from different Psidium guajava leaves and their antioxidant activities.

PubMed

Wang, Lu; Wu, Yanan; Bei, Qi; Shi, Kan; Wu, Zhenqiang

2017-10-01

Flavonoids are the main active components in Psidium guajava leaves and have many multi-physiological functions. In this study, the flavonoid compositions were identified in the Psidium guajava leaves samples using a high-performance liquid chromatography with time-of-flight electrospray ionization mass spectrometry method. A high-performance liquid chromatography fingerprint method, combined with chemometrics, was used to perform a quality assessment of the Psidium guajava leaves samples. The eight identified flavonoid compounds including rutin, isoquercitrin, quercetin-3-O-β-d-xylopyranoside, quercetin-3-O-α-l-arabinopyranoside, avicularin, quercitrin, quercetin, and kaempferol were used as the chemical markers. The antioxidant activity of 15 batches of samples was examined using three different methods, and the results revealed the Psidium guajava leaves samples that had higher contents of the flavonoid compounds, glycoside and aglycone, possessed the highest antioxidant capacities. Consequently, a combination of chromatographic fingerprints and chemometric analyses was used for a quality assessment of Psidium guajava leaf tea and its derived products, which can lay the foundation for the development of plant tea resources or other herbs. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Combination of near infrared spectroscopy and chemometrics for authentication of taro flour from wheat and sago flour

NASA Astrophysics Data System (ADS)

Rachmawati; Rohaeti, E.; Rafi, M.

2017-05-01

Taro flour on the market is usually sold at higher price than wheat and sago flour. This situation could be a cause for adulteration of taro flour from wheat and sago flour. For this reason, we will need an identification and authentication. Combination of near infrared (NIR) spectrum with multivariate analysis was used in this study to identify and authenticate taro flour from wheat and sago flour. The authentication model of taro flour was developed by using a mixture of 5%, 25%, and 50% of adulterated taro flour from wheat and sago flour. Before subjected to multivariate analysis, an initial preprocessing signal was used namely normalization and standard normal variate to the NIR spectrum. We used principal component analysis followed by discriminant analysis to make an identification and authentication model of taro flour. From the result obtained, about 90.48% of the taro flour mixed with wheat flour and 85% of taro flour mixed with sago flour were successfully classified into their groups. So the combination of NIR spectrum with chemometrics could be used for identification and authentication of taro flour from wheat and sago flour.

Testing the performance of pure spectrum resolution from Raman hyperspectral images of differently manufactured pharmaceutical tablets.

PubMed

Vajna, Balázs; Farkas, Attila; Pataki, Hajnalka; Zsigmond, Zsolt; Igricz, Tamás; Marosi, György

2012-01-27

Chemical imaging is a rapidly emerging analytical method in pharmaceutical technology. Due to the numerous chemometric solutions available, characterization of pharmaceutical samples with unknown components present has also become possible. This study compares the performance of current state-of-the-art curve resolution methods (multivariate curve resolution-alternating least squares, positive matrix factorization, simplex identification via split augmented Lagrangian and self-modelling mixture analysis) in the estimation of pure component spectra from Raman maps of differently manufactured pharmaceutical tablets. The batches of different technologies differ in the homogeneity level of the active ingredient, thus, the curve resolution methods are tested under different conditions. An empirical approach is shown to determine the number of components present in a sample. The chemometric algorithms are compared regarding the number of detected components, the quality of the resolved spectra and the accuracy of scores (spectral concentrations) compared to those calculated with classical least squares, using the true pure component (reference) spectra. It is demonstrated that using appropriate multivariate methods, Raman chemical imaging can be a useful tool in the non-invasive characterization of unknown (e.g. illegal or counterfeit) pharmaceutical products. Copyright © 2011 Elsevier B.V. All rights reserved.

Enhancing prediction power of chemometric models through manipulation of the fed spectrophotometric data: A comparative study

NASA Astrophysics Data System (ADS)

Saad, Ahmed S.; Hamdy, Abdallah M.; Salama, Fathy M.; Abdelkawy, Mohamed

2016-10-01

Effect of data manipulation in preprocessing step proceeding construction of chemometric models was assessed. The same set of UV spectral data was used for construction of PLS and PCR models directly and after mathematically manipulation as per well known first and second derivatives of the absorption spectra, ratio spectra and first and second derivatives of the ratio spectra spectrophotometric methods, meanwhile the optimal working wavelength ranges were carefully selected for each model and the models were constructed. Unexpectedly, number of latent variables used for models' construction varied among the different methods. The prediction power of the different models was compared using a validation set of 8 mixtures prepared as per the multilevel multifactor design and results were statistically compared using two-way ANOVA test. Root mean squares error of prediction (RMSEP) was used for further comparison of the predictability among different constructed models. Although no significant difference was found between results obtained using Partial Least Squares (PLS) and Principal Component Regression (PCR) models, however, discrepancies among results was found to be attributed to the variation in the discrimination power of adopted spectrophotometric methods on spectral data.

Speciation of adsorbates on surface of solids by infrared spectroscopy and chemometrics.

PubMed

Vilmin, Franck; Bazin, Philippe; Thibault-Starzyk, Frédéric; Travert, Arnaud

2015-09-03

Speciation, i.e. identification and quantification, of surface species on heterogeneous surfaces by infrared spectroscopy is important in many fields but remains a challenging task when facing strongly overlapped spectra of multiple adspecies. Here, we propose a new methodology, combining state of the art instrumental developments for quantitative infrared spectroscopy of adspecies and chemometrics tools, mainly a novel data processing algorithm, called SORB-MCR (SOft modeling by Recursive Based-Multivariate Curve Resolution) and multivariate calibration. After formal transposition of the general linear mixture model to adsorption spectral data, the main issues, i.e. validity of Beer-Lambert law and rank deficiency problems, are theoretically discussed. Then, the methodology is exposed through application to two case studies, each of them characterized by a specific type of rank deficiency: (i) speciation of physisorbed water species over a hydrated silica surface, and (ii) speciation (chemisorption and physisorption) of a silane probe molecule over a dehydrated silica surface. In both cases, we demonstrate the relevance of this approach which leads to a thorough surface speciation based on comprehensive and fully interpretable multivariate quantitative models. Limitations and drawbacks of the methodology are also underlined. Copyright © 2015 Elsevier B.V. All rights reserved.

Soft and Robust Identification of Body Fluid Using Fourier Transform Infrared Spectroscopy and Chemometric Strategies for Forensic Analysis.

PubMed

Takamura, Ayari; Watanabe, Ken; Akutsu, Tomoko; Ozawa, Takeaki

2018-05-31

Body fluid (BF) identification is a critical part of a criminal investigation because of its ability to suggest how the crime was committed and to provide reliable origins of DNA. In contrast to current methods using serological and biochemical techniques, vibrational spectroscopic approaches provide alternative advantages for forensic BF identification, such as non-destructivity and versatility for various BF types and analytical interests. However, unexplored issues remain for its practical application to forensics; for example, a specific BF needs to be discriminated from all other suspicious materials as well as other BFs, and the method should be applicable even to aged BF samples. Herein, we describe an innovative modeling method for discriminating the ATR FT-IR spectra of various BFs, including peripheral blood, saliva, semen, urine and sweat, to meet the practical demands described above. Spectra from unexpected non-BF samples were efficiently excluded as outliers by adopting the Q-statistics technique. The robustness of the models against aged BFs was significantly improved by using the discrimination scheme of a dichotomous classification tree with hierarchical clustering. The present study advances the use of vibrational spectroscopy and a chemometric strategy for forensic BF identification.

Kinetics of Forming Aldehydes in Frying Oils and Their Distribution in French Fries Revealed by LC-MS-Based Chemometrics.

PubMed

Wang, Lei; Csallany, A Saari; Kerr, Brian J; Shurson, Gerald C; Chen, Chi

2016-05-18

In this study, the kinetics of aldehyde formation in heated frying oils was characterized by 2-hydrazinoquinoline derivatization, liquid chromatography-mass spectrometry (LC-MS) analysis, principal component analysis (PCA), and hierarchical cluster analysis (HCA). The aldehydes contributing to time-dependent separation of heated soybean oil (HSO) in a PCA model were grouped by the HCA into three clusters (A1, A2, and B) on the basis of their kinetics and fatty acid precursors. The increases of 4-hydroxynonenal (4-HNE) and the A2-to-B ratio in HSO were well-correlated with the duration of thermal stress. Chemometric and quantitative analysis of three frying oils (soybean, corn, and canola oils) and French fry extracts further supported the associations between aldehyde profiles and fatty acid precursors and also revealed that the concentrations of pentanal, hexanal, acrolein, and the A2-to-B ratio in French fry extracts were more comparable to their values in the frying oils than other unsaturated aldehydes. All of these results suggest the roles of specific aldehydes or aldehyde clusters as novel markers of the lipid oxidation status for frying oils or fried foods.

Acid-Base Properties of Azo Dyes in Solution Studied Using Spectrophotometry and Colorimetry

NASA Astrophysics Data System (ADS)

Snigur, D. V.; Chebotarev, A. N.; Bevziuk, K. V.

2018-03-01

Colorimetry and spectrophotometry with chemometric data processing were used to study the acid-base properties of azo dyes in aqueous solution. The capabilities of both methods were compared. Ionization constants of all the functional groups of the azo compounds studied could be determined relative to the change in the specific color difference depending on the acidity of the medium. The colorimetric functions of ion-molecular forms of azo compounds used as an analytical signal allow us to obtain complete information on the acid-base equilibrium in a wide acidity range.

Exploratory studies to decide whether and how to proceed with full-scale evaluations of public health interventions: a systematic review of guidance.

PubMed

Hallingberg, Britt; Turley, Ruth; Segrott, Jeremy; Wight, Daniel; Craig, Peter; Moore, Laurence; Murphy, Simon; Robling, Michael; Simpson, Sharon Anne; Moore, Graham

2018-01-01

Evaluations of complex interventions in public health are frequently undermined by problems that can be identified before the effectiveness study stage. Exploratory studies, often termed pilot and feasibility studies, are a key step in assessing the feasibility and value of progressing to an effectiveness study. Such studies can provide vital information to support more robust evaluations, thereby reducing costs and minimising potential harms of the intervention. This systematic review forms the first phase of a wider project to address the need for stand-alone guidance for public health researchers on designing and conducting exploratory studies. The review objectives were to identify and examine existing recommendations concerning when such studies should be undertaken, questions they should answer, suitable methods, criteria for deciding whether to progress to an effectiveness study and appropriate reporting. We searched for published and unpublished guidance reported between January 2000 and November 2016 via bibliographic databases, websites, citation tracking and expert recommendations. Included papers were thematically synthesized. The search retrieved 4095 unique records. Thirty papers were included, representing 25 unique sources of guidance/recommendations. Eight themes were identified: pre-requisites for conducting an exploratory study, nomenclature, guidance for intervention assessment, guidance surrounding any future evaluation study design, flexible versus fixed design, progression criteria to a future evaluation study, stakeholder involvement and reporting of exploratory studies. Exploratory studies were described as being concerned with the intervention content, the future evaluation design or both. However, the nomenclature and endorsed methods underpinning these aims were inconsistent across papers. There was little guidance on what should precede or follow an exploratory study and decision-making surrounding this. Existing recommendations are inconsistent concerning the aims, designs and conduct of exploratory studies, and guidance is lacking on the evidence needed to inform when to proceed to an effectiveness study. PROSPERO 2016, CRD42016047843.

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

PubMed

Spanos, Thomas; Ene, Antoaneta; Simeonova, Pavlina

2015-01-01

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

Reappraisal of soil C storage processes. The controversy on structural diversity of humic substances as biogeochemical driver for soil C fluxes

NASA Astrophysics Data System (ADS)

Almendros, Gonzalo; Gonzalez-Vila, Francisco J.; Gonzalez-Perez, Jose Antonio; Knicker, Heike

2016-04-01

The functional relationships between the macromolecular structure of the humic substances (HS) and a series of biogeochemical processes related with the C sequestration performance in soils have been recently questioned. In this communication we collect recent data from a wide array of different ecosystems where the C storage in soils has been studied and explained as a possible cause-to-effect relationship or has been found significantly correlated (multivariate statistical models) with a series of structural characteristics of humic materials. The study of humic materials has methodological analytical limitations that are derived from its complex, chaotic and not completely understood structure, that reflects its manifold precursors as well as the local impact of environmental/depositional factors. In this work we attempt to design an exploratory, multiomic approach based on the information provided by the molecular characterization of the soil organic matter (SOM). Massive data harvesting was carried out of statistical variables, to infer biogeochemical proxies (spectroscopic, chromatographic, mass spectrometric quantitative descriptors). The experimental data were acquired from advanced instrumental methodologies, viz, analytical pyrolysis, compound-specific stable isotope analysis (CSIA), derivative infrared (FTIR) spectroscopy, solid-state C-13 and N-15 nuclear magnetic resonance (NMR) and mass spectrometry (MS) data after direct injection (thermoevaporation), previous pyrolysis, or ion averaging of specific m/z ranges from classical GC/MS chromatograms. In the transversal exploratory analysis of the multianalytical information, the data were coded for on-line processing in a stage in which there is no need for interpretation, in molecular or structural terms, of the quantitative data consisting of e.g., peak intensities, signal areas, chromatographic (GC) total abundances, etc. A series of forecasting chemometric approaches (aiming to express SOM biodegradability, or soil C resilience as a function of intrinsic molecular characteristics of the SOM) were especially successful in the case of: a) linear multiple regression models (LMR) with automatic backward variable selection, b) supervised removal of internal redundancy of the variables based on multidimensional scaling (MDS), and c) partial least squares (PLS) regression to obtain the variable importance for projection (VIP) which is useful to identify new environmental proxies. At least the results obtained from differing continental Mediterranean soils showed that a large influence of local (soil-dependant) abiotic factors in the final variance (of the total soil C quality and quantity) was explained by the SOM molecular structure. This conclusion is relevant as regards the recent (in our opinion hermeneutic and speculative) controversy disregarding the importance of the structural features of HS in biogeochemical and environmental processes controlling C sequestration in soils.

Best conditions for biodegradation of diesel oil by chemometric tools.

PubMed

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

2014-01-01

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

Determination and discrimination of biodiesel fuels by gas chromatographic and chemometric methods

NASA Astrophysics Data System (ADS)

Milina, R.; Mustafa, Z.; Bojilov, D.; Dagnon, S.; Moskovkina, M.

2016-03-01

Pattern recognition method (PRM) was applied to gas chromatographic (GC) data for a fatty acid methyl esters (FAME) composition of commercial and laboratory synthesized biodiesel fuels from vegetable oils including sunflower, rapeseed, corn and palm oils. Two GC quantitative methods to calculate individual fames were compared: Area % and internal standard. The both methods were applied for analysis of two certified reference materials. The statistical processing of the obtained results demonstrates the accuracy and precision of the two methods and allows them to be compared. For further chemometric investigations of biodiesel fuels by their FAME-profiles any of those methods can be used. PRM results of FAME profiles of samples from different vegetable oils show a successful recognition of biodiesels according to the feedstock. The information obtained can be used for selection of feedstock to produce biodiesels with certain properties, for assessing their interchangeability, for fuel spillage and remedial actions in the environment.

Towards the identification of plant and animal binders on Australian stone knives.

PubMed

Blee, Alisa J; Walshe, Keryn; Pring, Allan; Quinton, Jamie S; Lenehan, Claire E

2010-07-15

There is limited information regarding the nature of plant and animal residues used as adhesives, fixatives and pigments found on Australian Aboriginal artefacts. This paper reports the use of FTIR in combination with the chemometric tools principal component analysis (PCA) and hierarchical clustering (HC) for the analysis and identification of Australian plant and animal fixatives on Australian stone artefacts. Ten different plant and animal residues were able to be discriminated from each other at a species level by combining FTIR spectroscopy with the chemometric data analysis methods, principal component analysis (PCA) and hierarchical clustering (HC). Application of this method to residues from three broken stone knives from the collections of the South Australian Museum indicated that two of the handles of knives were likely to have contained beeswax as the fixative whilst Spinifex resin was the probable binder on the third. Copyright 2010 Elsevier B.V. All rights reserved.

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

PubMed

Insausti, Matías; Fernández Band, Beatriz S

2015-04-05

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

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

PubMed

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

2015-10-01

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

A chemometric approach to the characterisation of historical mortars

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rampazzi, L.; Pozzi, A.; Sansonetti, A.

2006-06-15

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

Authentication of monofloral Yemeni Sidr honey using ultraviolet spectroscopy and chemometric analysis.

PubMed

Roshan, Abdul-Rahman A; Gad, Haidy A; El-Ahmady, Sherweit H; Khanbash, Mohamed S; Abou-Shoer, Mohamed I; Al-Azizi, Mohamed M

2013-08-14

This work describes a simple model developed for the authentication of monofloral Yemeni Sidr honey using UV spectroscopy together with chemometric techniques of hierarchical cluster analysis (HCA), principal component analysis (PCA), and soft independent modeling of class analogy (SIMCA). The model was constructed using 13 genuine Sidr honey samples and challenged with 25 honey samples of different botanical origins. HCA and PCA were successfully able to present a preliminary clustering pattern to segregate the genuine Sidr samples from the lower priced local polyfloral and non-Sidr samples. The SIMCA model presented a clear demarcation of the samples and was used to identify genuine Sidr honey samples as well as detect admixture with lower priced polyfloral honey by detection limits >10%. The constructed model presents a simple and efficient method of analysis and may serve as a basis for the authentication of other honey types worldwide.

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

PubMed

Darwish, Hany W; Bakheit, Ahmed H; Abdelhameed, Ali S

2016-03-01

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

A new simplex chemometric approach to identify olive oil blends with potentially high traceability.

PubMed

Semmar, N; Laroussi-Mezghani, S; Grati-Kamoun, N; Hammami, M; Artaud, J

2016-10-01

Olive oil blends (OOBs) are complex matrices combining different cultivars at variable proportions. Although qualitative determinations of OOBs have been subjected to several chemometric works, quantitative evaluations of their contents remain poorly developed because of traceability difficulties concerning co-occurring cultivars. Around this question, we recently published an original simplex approach helping to develop predictive models of the proportions of co-occurring cultivars from chemical profiles of resulting blends (Semmar & Artaud, 2015). Beyond predictive model construction and validation, this paper presents an extension based on prediction errors' analysis to statistically define the blends with the highest predictability among all the possible ones that can be made by mixing cultivars at different proportions. This provides an interesting way to identify a priori labeled commercial products with potentially high traceability taking into account the natural chemical variability of different constitutive cultivars. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quality assessment of Penthorum chinense Pursh through multicomponent qualification and fingerprint, chemometric, and antihepatocarcinoma analyses.

PubMed

Sun, Zong-Liang; Zhang, Yu-Zhen; Zhang, Feng; Zhang, Jia-Wei; Zheng, Guo-Can; Tan, Ling; Wang, Chong-Zhi; Zhou, Lian-Di; Zhang, Qi-Hui; Yuan, Chun-Su

2018-06-22

An efficient method combined with fingerprint and chemometric analyses was developed to evaluate the quality of the traditional Chinese medicine plant Penthorum chinense Pursh. Nine samples were collected from different regions during different harvest periods, and 17 components in the form of extracts were simultaneously examined to assess quality by using high-performance liquid chromatography. The hepatoprotective effects of components were investigated by assessing the inhibition of SMMC-7721 cell growth. The results indicated that the quality control method was accurate, stable, and reliable, and the hierarchical heat-map cluster and the principle component analyses confirmed that the classification of all nine samples was consistent. Quercetin and ellagitannins including pinocembrin-7-O-[3''-O-galloyl-4'',6''-hexahydroxydiphenoyl]-β-glucose (PGHG), thonningianin A, thonningianin B, and other flavonoids were abundant in the extracts, and significantly contributed to the hepatoprotective effects.

Discrimination of transgenic soybean seeds by terahertz spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Wei; Liu, Changhong; Chen, Feng; Yang, Jianbo; Zheng, Lei

2016-10-01

Discrimination of genetically modified organisms is increasingly demanded by legislation and consumers worldwide. The feasibility of a non-destructive discrimination of glyphosate-resistant and conventional soybean seeds and their hybrid descendants was examined by terahertz time-domain spectroscopy system combined with chemometrics. Principal component analysis (PCA), least squares-support vector machines (LS-SVM) and PCA-back propagation neural network (PCA-BPNN) models with the first and second derivative and standard normal variate (SNV) transformation pre-treatments were applied to classify soybean seeds based on genotype. Results demonstrated clear differences among glyphosate-resistant, hybrid descendants and conventional non-transformed soybean seeds could easily be visualized with an excellent classification (accuracy was 88.33% in validation set) using the LS-SVM and the spectra with SNV pre-treatment. The results indicated that THz spectroscopy techniques together with chemometrics would be a promising technique to distinguish transgenic soybean seeds from non-transformed seeds with high efficiency and without any major sample preparation.

How Information Affects Intrinsic Motivation: Two Exploratory Pilot Studies.

ERIC Educational Resources Information Center

Small, Ruth V.; Samijo

Research on the motivational aspects of multimedia games may provide ways to design more engaging user information systems which increase users' exploratory and information-seeking behaviors. Two small-scale exploratory studies examined the effects of introducing information on the intrinsic motivation of users of a CD-ROM game. Results of the…

Evaluation Study of the Exploratory Visit: An Innovative Outreach Activity of the ILGWU's Friendly Visiting Program

ERIC Educational Resources Information Center

Wright, Holly; And Others

1977-01-01

The exploratory visit to recent retirees, an outreach component of the International Ladies Garment Workers Union Friendly Visiting Program, was evaluated. A post-test only control group effect study revealed exploratory visits were effective in establishing a link between the program and the retiree. (Author)

Rapidly differentiating grape seeds from different sources based on characteristic fingerprints using direct analysis in real time coupled with time-of-flight mass spectrometry combined with chemometrics.

PubMed

Song, Yuqiao; Liao, Jie; Dong, Junxing; Chen, Li

2015-09-01

The seeds of grapevine (Vitis vinifera) are a byproduct of wine production. To examine the potential value of grape seeds, grape seeds from seven sources were subjected to fingerprinting using direct analysis in real time coupled with time-of-flight mass spectrometry combined with chemometrics. Firstly, we listed all reported components (56 components) from grape seeds and calculated the precise m/z values of the deprotonated ions [M-H](-) . Secondly, the experimental conditions were systematically optimized based on the peak areas of total ion chromatograms of the samples. Thirdly, the seven grape seed samples were examined using the optimized method. Information about 20 grape seed components was utilized to represent characteristic fingerprints. Finally, hierarchical clustering analysis and principal component analysis were performed to analyze the data. Grape seeds from seven different sources were classified into two clusters; hierarchical clustering analysis and principal component analysis yielded similar results. The results of this study lay the foundation for appropriate utilization and exploitation of grape seed samples. Due to the absence of complicated sample preparation methods and chromatographic separation, the method developed in this study represents one of the simplest and least time-consuming methods for grape seed fingerprinting. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2018-01-31

β-Thalassemia is one of the most common inherited disorders and is widely distributed throughout the world. Owing to severe deficiencies in red blood cell production, blood transfusion is required to correct anemia for normal growth and development but causes additional complications owing to iron overload. The aim of this study is to quantify the biometal dysregulations in β-thalassemia patients as compared with healthy controls. A total of 17 elements were analyzed in serum samples of β-thalassemia patients and healthy controls using ICP-MS followed by chemometric analyses. Out of these analyzed elements, 14 showed a significant difference between healthy and disease groups at p < 0.05 and fold change >3. A PLS-DA model revealed an excellent separation with 89.8% sensitivity and 97.2% specificity and the overall accuracy of the model was 92.2%. This metallomic study revealed that there is major difference in metallomic profiling of β-thalassemia patients specifically in Co, Mn, Ni, V and Ba, whereas the fold changes in Co, Mn, V and Ba were found to be greater than that in Fe, providing evidence that, in addition to Fe, other metals are also altered significantly and therefore chelation therapy for other metals may also needed in β-thalassemia patients. Copyright © 2018 John Wiley & Sons, Ltd.

Thermodynamics study of the dimerization equilibria of rhodamine B and 6G in different ionic strengths by photometric titration and chemometrics method

NASA Astrophysics Data System (ADS)

Ghasemi, Jahanbakhsh; Niazi, Ali; Kubista, Mikael

2005-11-01

The dimerization constants of rhodamine B and 6G have been determined by studying the dependence of their absorption spectra on the temperature in the range 20-80 °C at different total concentrations of rhodamine B (5.89 × 10 -6 to 2.36 × 10 -4 M) and rhodamine 6G (2.34 × 10 -5 to 5.89 × 10 -4 M) and in different concentrations of LiCl, NaCl and KCl salts as supporting electrolytes. The monomer-dimer equilibrium of rhodamine B and 6G have been determined by chemometrics refinement of the absorption spectra obtained by thermometric titrations performed at different ionic strengths. The quantitative analysis of the data of undefined mixtures, was carried out by simultaneous resolution of the overlapping spectral bands in the whole set of absorption spectra. The dimerization constants are varied by changing the ionic strength and the degree of dimerization are decreased by increasing of the ionic strength of the medium. The enthalpy and entropy of the dimerization reactions were determined from the dependence of the equilibrium constants on the temperature (van't Hoff equation). From the thermodynamic results the TΔ S°-Δ H° plot was sketched. It shows a fairly good positive correlation which indicates the enthalpy-entropy compensation in the dimerization reactions (compensation effect).

Thermodynamics study of the dimerization equilibria of rhodamine B and 6G in different ionic strengths by photometric titration and chemometrics method.

PubMed

Ghasemi, Jahanbakhsh; Niazi, Ali; Kubista, Mikael

2005-11-01

The dimerization constants of rhodamine B and 6G have been determined by studying the dependence of their absorption spectra on the temperature in the range 20-80 degrees C at different total concentrations of rhodamine B (5.89 x 10(-6) to 2.36 x 10(-4)M) and rhodamine 6G (2.34 x 10(-5) to 5.89 x 10(-4)M) and in different concentrations of LiCl, NaCl and KCl salts as supporting electrolytes. The monomer-dimer equilibrium of rhodamine B and 6G have been determined by chemometrics refinement of the absorption spectra obtained by thermometric titrations performed at different ionic strengths. The quantitative analysis of the data of undefined mixtures, was carried out by simultaneous resolution of the overlapping spectral bands in the whole set of absorption spectra. The dimerization constants are varied by changing the ionic strength and the degree of dimerization are decreased by increasing of the ionic strength of the medium. The enthalpy and entropy of the dimerization reactions were determined from the dependence of the equilibrium constants on the temperature (van't Hoff equation). From the thermodynamic results the TDeltaS degrees -DeltaH degrees plot was sketched. It shows a fairly good positive correlation which indicates the enthalpy-entropy compensation in the dimerization reactions (compensation effect).

The biocompatibility of carbon hydroxyapatite/β-glucan composite for bone tissue engineering studied with Raman and FTIR spectroscopic imaging.

PubMed

Sroka-Bartnicka, Anna; Kimber, James A; Borkowski, Leszek; Pawlowska, Marta; Polkowska, Izabela; Kalisz, Grzegorz; Belcarz, Anna; Jozwiak, Krzysztof; Ginalska, Grazyna; Kazarian, Sergei G

2015-10-01

The spectroscopic approaches of FTIR imaging and Raman mapping were applied to the characterisation of a new carbon hydroxyapatite/β-glucan composite developed for bone tissue engineering. The composite is an artificial bone material with an apatite-forming ability for the bone repair process. Rabbit bone samples were tested with an implanted bioactive material for a period of several months. Using spectroscopic and chemometric methods, we were able to determine the presence of amides and phosphates and the distribution of lipid-rich domains in the bone tissue, providing an assessment of the composite's bioactivity. Samples were also imaged in transmission using an infrared microscope combined with a focal plane array detector. CaF2 lenses were also used on the infrared microscope to improve spectral quality by reducing scattering artefacts, improving chemometric analysis. The presence of collagen and lipids at the bone/composite interface confirmed biocompatibility and demonstrate the suitability of FTIR microscopic imaging with lenses in studying these samples. It confirmed that the composite is a very good background for collagen growth and increases collagen maturity with the time of the bone growth process. The results indicate the bioactive and biocompatible properties of this composite and demonstrate how Raman and FTIR spectroscopic imaging have been used as an effective tool for tissue characterisation.

High-Throughput Metabolic Fingerprinting of Legume Silage Fermentations via Fourier Transform Infrared Spectroscopy and Chemometrics

PubMed Central

Johnson, Helen E.; Broadhurst, David; Kell, Douglas B.; Theodorou, Michael K.; Merry, Roger J.; Griffith, Gareth W.

2004-01-01

Silage quality is typically assessed by the measurement of several individual parameters, including pH, lactic acid, acetic acid, bacterial numbers, and protein content. The objective of this study was to use a holistic metabolic fingerprinting approach, combining a high-throughput microtiter plate-based fermentation system with Fourier transform infrared (FT-IR) spectroscopy, to obtain a snapshot of the sample metabolome (typically low-molecular-weight compounds) at a given time. The aim was to study the dynamics of red clover or grass silage fermentations in response to various inoculants incorporating lactic acid bacteria (LAB). The hyperspectral multivariate datasets generated by FT-IR spectroscopy are difficult to interpret visually, so chemometrics methods were used to deconvolute the data. Two-phase principal component-discriminant function analysis allowed discrimination between herbage types and different LAB inoculants and modeling of fermentation dynamics over time. Further analysis of FT-IR spectra by the use of genetic algorithms to identify the underlying biochemical differences between treatments revealed that the amide I and amide II regions (wavenumbers of 1,550 to 1,750 cm−1) of the spectra were most frequently selected (reflecting changes in proteins and free amino acids) in comparisons between control and inoculant-treated fermentations. This corresponds to the known importance of rapid fermentation for the efficient conservation of forage proteins. PMID:15006782

Screening and analysis of potential anti-tumor components from the stipe of Ganoderma sinense using high-performance liquid chromatography/time-of-flight mass spectrometry with multivariate statistical tool.

PubMed

Chan, Kar-Man; Yue, Grace Gar-Lee; Li, Ping; Wong, Eric Chun-Wai; Lee, Julia Kin-Ming; Kennelly, Edward J; Lau, Clara Bik-San

2017-03-03

According to Chinese Pharmacopoeia 2015 edition, Ganoderma (Lingzhi) is a species complex that comprise of Ganoderma lucidum and Ganoderma sinense. The bioactivity and chemical composition of G. lucidium had been studied extensively, and it was shown to possess antitumor activities in pharmacological studies. In contrast, G. sinense has not been studied in great detail. Our previous studies found that the stipe of G. sinense exhibited more potent antitumor activity than the pileus. To identify the antitumor compounds in the stipe of G. sinense, we studied its chemical components by merging the bioactivity results with liquid chromatography-mass spectrometry-based chemometrics. The stipe of G. sinense was extracted with water, followed by ethanol precipitation and liquid-liquid partition. The resulting residue was fractionated using column chromatography. The antitumor activity of these fractions were analysed using MTT assay in murine breast tumor 4T1 cells, and their chemical components were studied using the LC-QTOF-MS with multivariate statistical tools. The chemometric and MS/MS analysis correlated bioactivity with five known cytotoxic compounds, 4-hyroxyphenylacetate, 9-oxo-(10E,12E)-octadecadienoic acid, 3-phenyl-2-propenoic acid, 13-oxo-(9E,11E)-octadecadienoic acid and lingzhine C, from the stipe of G. sinense. To the best of our knowledge, 4-hyroxyphenylacetate, 3-phenyl-2-propenoic acid and lingzhine C are firstly reported to be found in G. sinense. These five compounds will be investigated for their antitumor activities in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

High-throughput NIR spectroscopic (NIRS) detection of microplastics in soil.

PubMed

Paul, Andrea; Wander, Lukas; Becker, Roland; Goedecke, Caroline; Braun, Ulrike

2018-05-12

The increasing pollution of terrestrial and aquatic ecosystems with plastic debris leads to the accumulation of microscopic plastic particles of still unknown amount. To monitor the degree of contamination, analytical methods are urgently needed, which help to quantify microplastics (MP). Currently, time-costly purified materials enriched on filters are investigated both by micro-infrared spectroscopy and/or micro-Raman. Although yielding precise results, these techniques are time consuming, and are restricted to the analysis of a small part of the sample in the order of few micrograms. To overcome these problems, we tested a macroscopic dimensioned near-infrared (NIR) process-spectroscopic method in combination with chemometrics. For calibration, artificial MP/ soil mixtures containing defined ratios of polyethylene, polyethylene terephthalate, polypropylene, and polystyrene with diameters < 125 μm were prepared and measured by a process FT-NIR spectrometer equipped with a fiber-optic reflection probe. The resulting spectra were processed by chemometric models including support vector machine regression (SVR), and partial least squares discriminant analysis (PLS-DA). Validation of models by MP mixtures, MP-free soils, and real-world samples, e.g., fermenter residue, suggests a reliable detection and a possible classification of MP at levels above 0.5 to 1.0 mass% depending on the polymer. The benefit of the combined NIRS chemometric approach lies in the rapid assessment whether soil contains MP, without any chemical pretreatment. The method can be used with larger sample volumes and even allows for an online prediction and thus meets the demand of a high-throughput method.

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

PubMed

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

2012-06-04

Precision agriculture depends on the knowledge and management of soil quality (SQ), which calls for affordable, simple and rapid but accurate analysis of bioavailable soil nutrients. Conventional SQ analysis methods are tedious and expensive. We demonstrate the utility of a new chemometrics-assisted energy dispersive X-ray fluorescence and scattering (EDXRFS) spectroscopy method we have developed for direct rapid analysis of trace 'bioavailable' macronutrients (i.e. C, N, Na, Mg, P) in soils. The method exploits, in addition to X-ray fluorescence, the scatter peaks detected from soil pellets to develop a model for SQ analysis. Spectra were acquired from soil samples held in a Teflon holder analyzed using (109)Cd isotope source EDXRF spectrometer for 200 s. Chemometric techniques namely principal component analysis (PCA), partial least squares (PLS) and artificial neural networks (ANNs) were utilized for pattern recognition based on fluorescence and Compton scatter peaks regions, and to develop multivariate quantitative calibration models based on Compton scatter peak respectively. SQ analyses were realized with high CMD (R(2)>0.9) and low SEP (0.01% for N and Na, 0.05% for C, 0.08% for Mg and 1.98 μg g(-1) for P). Comparison of predicted macronutrients with reference standards using a one-way ANOVA test showed no statistical difference at 95% confidence level. To the best of the authors' knowledge, this is the first time that an XRF method has demonstrated utility in trace analysis of macronutrients in soil or related matrices. Copyright © 2012 Elsevier B.V. All rights reserved.

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

PubMed

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

2012-01-01

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

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

PubMed

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

2018-04-19

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

Healthy Eating Exploratory Program for the Elderly: Low Salt Intake in Congregate Meal Service.

PubMed

Seo, S; Kim, O Y; Ahn, J

2016-03-01

This study reported on an exploratory program to help the low income elderly improve healthy eating behavior, specifically by reducing salt intake. We conducted an exploratory program for 4 weeks for this study. The exploratory program involved offering menus with reduced salt and providing education on healthy eating. After the exploratory program, a survey of the elderly and in-depth interviews allowed us to evaluate the program for foodservice providers (dietitian, social workers, and volunteer workers). This study included both foodservice workers and elderly who actually used the foodservice in a congregate meal service system. This is a unique approach. A congregate meal service center in Seoul, Korea. Seventy four elderly in a congregate meal service center. Demographics were collected, and the healthy eating program and healthy eating education for elderly respondents were evaluated. The elderly showed high satisfaction with the exploratory program for healthy eating. We found no significant differences in satisfaction with the program between the elderly who attended education sessions and those who did not, but more of the elderly from the education sessions showed positive behavioral change intentions. The exploratory program influenced to reduce the salt intake of the elderly in congregate meal service. This study suggests cooperation of foodservice providers and the support of administrators is critical to the success of such programs.

Rapid analysis of sugars in honey by processing Raman spectrum using chemometric methods and artificial neural networks.

PubMed

Özbalci, Beril; Boyaci, İsmail Hakkı; Topcu, Ali; Kadılar, Cem; Tamer, Uğur

2013-02-15

The aim of this study was to quantify glucose, fructose, sucrose and maltose contents of honey samples using Raman spectroscopy as a rapid method. By performing a single measurement, quantifications of sugar contents have been said to be unaffordable according to the molecular similarities between sugar molecules in honey matrix. This bottleneck was overcome by coupling Raman spectroscopy with chemometric methods (principal component analysis (PCA) and partial least squares (PLS)) and an artificial neural network (ANN). Model solutions of four sugars were processed with PCA and significant separation was observed. This operation, done with the spectral features by using PLS and ANN methods, led to the discriminant analysis of sugar contents. Models/trained networks were created using a calibration data set and evaluated using a validation data set. The correlation coefficient values between actual and predicted values of glucose, fructose, sucrose and maltose were determined as 0.964, 0.965, 0.968 and 0.949 for PLS and 0.965, 0.965, 0.978 and 0.956 for ANN, respectively. The requirement of rapid analysis of sugar contents of commercial honeys has been met by the data processed within this article. Copyright © 2012 Elsevier Ltd. All rights reserved.

Time-Domain Nuclear Magnetic Resonance (TD-NMR) and Chemometrics for Determination of Fat Content in Commercial Products of Milk Powder.

PubMed

Nascimento, Paloma Andrade Martins; Barsanelli, Paulo Lopes; Rebellato, Ana Paula; Pallone, Juliana Azevedo Lima; Colnago, Luiz Alberto; Pereira, Fabíola Manhas Verbi

2017-03-01

This study shows the use of time-domain (TD)-NMR transverse relaxation (T2) data and chemometrics in the nondestructive determination of fat content for powdered food samples such as commercial dried milk products. Most proposed NMR spectroscopy methods for measuring fat content correlate free induction decay or echo intensities with the sample's mass. The need for the sample's mass limits the analytical frequency of NMR determination, because weighing the samples is an additional step in this procedure. Therefore, the method proposed here is based on a multivariate model of T2 decay, measured with Carr-Purcell-Meiboom-Gill pulse sequence and reference values of fat content. The TD-NMR spectroscopy method shows high correlation (r = 0.95) with the lipid content, determined by the standard extraction method of Bligh and Dyer. For comparison, fat content determination was also performed using a multivariate model with near-IR (NIR) spectroscopy, which is also a nondestructive method. The advantages of the proposed TD-NMR method are that it (1) minimizes toxic residue generation, (2) performs measurements with high analytical frequency (a few seconds per analysis), and (3) does not require sample preparation (such as pelleting, needed for NIR spectroscopy analyses) or weighing the samples.

Rapid authentication of edible bird's nest by FTIR spectroscopy combined with chemometrics.

PubMed

Guo, Lili; Wu, Yajun; Liu, Mingchang; Ge, Yiqiang; Chen, Ying

2018-06-01

Edible bird's nests (EBNs) have been traditionally regarded as a kind of medicinal and healthy food in China. For economic reasons, they are frequently subjected to adulteration with some cheaper substitutes, such as Tremella fungus, agar, fried pigskin, and egg white. As a kind of precious and functional product, it is necessary to establish a robust method for the rapid authentication of EBNs with small amounts of samples by simple processes. In this study, the Fourier transform infrared spectroscopy (FTIR) system was utilized and its feasibility for identification of EBNs was verified. FTIR spectra data of authentic and adulterated EBNs were analyzed by chemometrics analyses including principal component analysis, linear discriminant analysis (LDA), support vector machine (SVM) and one-class partial least squares (OCPLS). The results showed that the established LDA and SVM models performed well and had satisfactory classification ability, with the former 94.12% and the latter 100%. The OCPLS model was developed with prediction sensitivity of 0.937 and specificity of 0.886. Further detection of commercial EBN samples confirmed these results. FTIR is applicable in the scene of rapid authentication of EBNs, especially for quality supervision departments, entry-exit inspection and quarantine, and customs administration. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

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

PubMed

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

2016-12-01

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

Quality assessment of crude and processed Arecae semen based on colorimeter and HPLC combined with chemometrics methods.

PubMed

Sun, Meng; Yan, Donghui; Yang, Xiaolu; Xue, Xingyang; Zhou, Sujuan; Liang, Shengwang; Wang, Shumei; Meng, Jiang

2017-05-01

Raw Arecae Semen, the seed of Areca catechu L., as well as Arecae Semen Tostum and Arecae semen carbonisata are traditionally processed by stir-baking for subsequent use in a variety of clinical applications. These three Arecae semen types, important Chinese herbal drugs, have been used in China and other Asian countries for thousands of years. In this study, the sensory technologies of a colorimeter and sensitive validated high-performance liquid chromatography with diode array detection were employed to discriminate raw Arecae semen and its processed drugs. The color parameters of the samples were determined by a colorimeter instrument CR-410. Moreover, the fingerprints of the four alkaloids of arecaidine, guvacine, arecoline and guvacoline were surveyed by high-performance liquid chromatography. Subsequently, Student's t test, the analysis of variance, fingerprint similarity analysis, hierarchical cluster analysis, principal component analysis, factor analysis and Pearson's correlation test were performed for final data analysis. The results obtained demonstrated a significant color change characteristic for components in raw Arecae semen and its processed drugs. Crude and processed Arecae semen could be determined based on colorimetry and high-performance liquid chromatography with a diode array detector coupled with chemometrics methods for a comprehensive quality evaluation. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2014-03-01

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

A catheter-based near-infrared scanning spectroscopy system for imaging lipid-rich plaques in human coronary arteries in vivo

NASA Astrophysics Data System (ADS)

Gardner, Craig M.; Lisauskas, Jennifer; Hull, Edward L.; Tan, Huwei; Sum, Stephen; Meese, Thomas; Jiang, Chunsheng; Madden, Sean; Caplan, Jay; Muller, James E.

2007-09-01

Although heart disease remains the leading cause of death in the industrialized world, there is still no method, even under cardiac catheterization, to reliably identify those atherosclerotic lesions most likely to lead to heart attack and death. These lesions, which are often non-stenotic, are frequently comprised of a necrotic, lipid-rich core overlaid with a thin fibrous cap infiltrated with inflammatory cells. InfraReDx has developed a scanning, near-infrared, optical-fiber-based, spectroscopic cardiac catheter system capable of acquiring NIR reflectance spectra from coronary arteries through flowing blood under automated pullback and rotation in order to identify lipid-rich plaques (LRP). The scanning laser source and associated detection electronics produce a spectrum in 5 ms at a collection rate of 40 Hz, yielding thousands of spectra in a single pullback. The system console analyzes the spectral data with a chemometric model, producing a hyperspectral image (a Chemogram, see figure below) that identifies LRP encountered in the region interrogated by the system. We describe the system architecture and components, explain the experimental procedure by which the chemometric model was constructed from spectral data and histology-based reference information collected from autopsy hearts, and provide representative data from ongoing ex vivo and clinical studies.

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

PubMed

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

2018-04-01

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

Transmission near-infrared (NIR) and photon time-of-flight (PTOF) spectroscopy in a comparative analysis of pharmaceuticals.

PubMed

Kamran, Faisal; Abildgaard, Otto H A; Sparén, Anders; Svensson, Olof; Johansson, Jonas; Andersson-Engels, Stefan; Andersen, Peter E; Khoptyar, Dmitry

2015-03-01

We present a comprehensive study of the application of photon time-of-flight spectroscopy (PTOFS) in the wavelength range 1050-1350 nm as a spectroscopic technique for the evaluation of the chemical composition and structural properties of pharmaceutical tablets. PTOFS is compared to transmission near-infrared spectroscopy (NIRS). In contrast to transmission NIRS, PTOFS is capable of directly and independently determining the absorption and reduced scattering coefficients of the medium. Chemometric models were built on the evaluated absorption spectra for predicting tablet drug concentration. Results are compared to corresponding predictions built on transmission NIRS measurements. The predictive ability of PTOFS and transmission NIRS is comparable when models are based on uniformly distributed tablet sets. For non-uniform distribution of tablets based on particle sizes, the prediction ability of PTOFS is better than that of transmission NIRS. Analysis of reduced scattering spectra shows that PTOFS is able to characterize tablet microstructure and manufacturing process parameters. In contrast to the chemometric pseudo-variables provided by transmission NIRS, PTOFS provides physically meaningful quantities such as scattering strength and slope of particle size. The ability of PTOFS to quantify the reduced scattering spectra, together with its robustness in predicting drug content, makes it suitable for such evaluations in the pharmaceutical industry.

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

PubMed

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

2011-04-01

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

Multivariate Analysis of Combined Fourier Transform Near-Infrared Spectrometry (FT-NIR) and Raman Datasets for Improved Discrimination of Drying Oils.

PubMed

Carlesi, Serena; Ricci, Marilena; Cucci, Costanza; La Nasa, Jacopo; Lofrumento, Cristiana; Picollo, Marcello; Becucci, Maurizio

2015-07-01

This work explores the application of chemometric techniques to the analysis of lipidic paint binders (i.e., drying oils) by means of Raman and near-infrared spectroscopy. These binders have been widely used by artists throughout history, both individually and in mixtures. We prepared various model samples of the pure binders (linseed, poppy seed, and walnut oils) obtained from different manufacturers. These model samples were left to dry and then characterized by Raman and reflectance near-infrared spectroscopy. Multivariate analysis was performed by applying principal component analysis (PCA) on the first derivative of the corresponding Raman spectra (1800-750 cm(-1)), near-infrared spectra (6000-3900 cm(-1)), and their combination to test whether spectral differences could enable samples to be distinguished on the basis of their composition. The vibrational bands we found most useful to discriminate between the different products we studied are the fundamental ν(C=C) stretching and methylenic stretching and bending combination bands. The results of the multivariate analysis demonstrated the potential of chemometric approaches for characterizing and identifying drying oils, and also for gaining a deeper insight into the aging process. Comparison with high-performance liquid chromatography data was conducted to check the PCA results.

Simultaneous determination of penicillin G salts by infrared spectroscopy: Evaluation of combining orthogonal signal correction with radial basis function-partial least squares regression

NASA Astrophysics Data System (ADS)

Talebpour, Zahra; Tavallaie, Roya; Ahmadi, Seyyed Hamid; Abdollahpour, Assem

2010-09-01

In this study, a new method for the simultaneous determination of penicillin G salts in pharmaceutical mixture via FT-IR spectroscopy combined with chemometrics was investigated. The mixture of penicillin G salts is a complex system due to similar analytical characteristics of components. Partial least squares (PLS) and radial basis function-partial least squares (RBF-PLS) were used to develop the linear and nonlinear relation between spectra and components, respectively. The orthogonal signal correction (OSC) preprocessing method was used to correct unexpected information, such as spectral overlapping and scattering effects. In order to compare the influence of OSC on PLS and RBF-PLS models, the optimal linear (PLS) and nonlinear (RBF-PLS) models based on conventional and OSC preprocessed spectra were established and compared. The obtained results demonstrated that OSC clearly enhanced the performance of both RBF-PLS and PLS calibration models. Also in the case of some nonlinear relation between spectra and component, OSC-RBF-PLS gave satisfactory results than OSC-PLS model which indicated that the OSC was helpful to remove extrinsic deviations from linearity without elimination of nonlinear information related to component. The chemometric models were tested on an external dataset and finally applied to the analysis commercialized injection product of penicillin G salts.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Rapid detection of bacterial pathogens using flourescence spectroscopy and chemometrics

USDA-ARS?s Scientific Manuscript database

This work presents the development of a method for rapid bacterial identification based on the fluorescence spectroscopy combined with multivariate analysis. Fluorescence spectra of pure three different genera of bacteria (Escherichia coli, Salmonella, and Campylobacter) were collected from 200...

Optimization and Development of a Human Scent Collection Method

DTIC Science & Technology

2007-06-04

19. Schoon, G. A. A., Scent Identification Lineups by Dogs (Canis familiaris): Experimental Design and Forensic Application. Applied Animal...Parker, Lloyd R., Morgan, Stephen L., Deming, Stanley N., Sequential Simplex Optimization. Chemometrics Series, ed. S.D. Brown. 1991, Boca Raton

Cross-species assessments of motor and exploratory behavior related to bipolar disorder.

PubMed

Henry, Brook L; Minassian, Arpi; Young, Jared W; Paulus, Martin P; Geyer, Mark A; Perry, William

2010-07-01

Alterations in exploratory behavior are a fundamental feature of bipolar mania, typically characterized as motor hyperactivity and increased goal-directed behavior in response to environmental cues. In contrast, abnormal exploration associated with schizophrenia and depression can manifest as prominent withdrawal, limited motor activity, and inattention to the environment. While motor abnormalities are cited frequently as clinical manifestations of these disorders, relatively few empirical studies have quantified human exploratory behavior. This article reviews the literature characterizing motor and exploratory behavior associated with bipolar disorder and genetic and pharmacological animal models of the illness. Despite sophisticated assessment of exploratory behavior in rodents, objective quantification of human motor activity has been limited primarily to actigraphy studies with poor cross-species translational value. Furthermore, symptoms that reflect the cardinal features of bipolar disorder have proven difficult to establish in putative animal models of this illness. Recently, however, novel tools such as the human behavioral pattern monitor provide multivariate translational measures of motor and exploratory activity, enabling improved understanding of the neurobiology underlying psychiatric disorders.

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

PubMed

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

2017-10-01

Genus Ficus (Moraceae) constitutes more than 850 species and about 2000 varieties and it acts as a golden mine that could afford effective and safe remedies combating many health disorders. Discrimination of Ficus cordata , Ficus ingens , and Ficus palmata using chemometric analysis and assessment of their role in combating oxidative stress. Phytochemical profiling of the methanol extracts of the three Ficus species and their successive fractions was performed using high-performance liquid chromatography/electrospray ionization mass spectrometry. Their discrimination was carried out using the obtained spectral data applying chemometric unsupervised pattern-recognition techniques, namely, principal component analysis and hierarchical cluster analysis. In vitro hepatoprotective and antioxidant evaluation of the samples was performed using human hepatocellular carcinoma cells challenged by carbon tetrachloride (CCl 4 ). Altogether, 22 compounds belonging to polyphenolics, flavonoids, and furanocoumarins were identified in the three Ficus species. Aviprin is the most abundant compound in F. cordata while chlorogenic acid and psoralen were present in high percentages in F. ingens and F. palmata , respectively. Chemometric analyses showed that F. palmata and F. cordata are more closely related chemically to each other rather than F. ingens . The ethyl acetate fractions of all the examined species showed a marked hepatoprotective efficacy accounting for 54.78%, 55.46%, and 56.42% reduction in serum level of alanine transaminase and 56.82%, 54.16%, and 57.06% suppression in serum level of aspartate transaminase, respectively, at 100 μg/mL comparable to CCl 4 -treated cells. Ficus species exhibited a no table antioxidant and hepatoprotective activity owing to their richness in polyphenolics and furanocoumarins. Ficus cordata , Ficus ingens , and Ficus palmata were analyzed using high-performance liquid chromatography/electrospray ionization mass spectrometry that revealed their richness with polyphenolics and furanocoumarinsDiscrimination of the three species was performed using spectral data coupled with chemometrics that showed that F. palmata and F. cordata are chemically related to each other rather than F. ingens In vitro hepatoprotective and antioxidant evaluation was performed using human hepatocellular carcinoma cells. The ethyl acetate fractions of all the examined species showed a marked hepatoprotective efficacy Ficus species exhibited notable activities due to polyphenolics and furanocoumarins. Abbreviations used: ALT: Alanine transaminase, AST: Aspartate transaminase, CCl 4: Carbon tetrachloride, DMEM: Dulbecco's Modified Eagle's medium, DMSO: Dimethyl sulfoxide, EDTA: Ethylenediaminetetraacetic acid, FBS: Fetal bovine serum, FCA: Ficus cordata remaining aqueous fraction, FCB: Ficus cordata n -butanol fraction, FCE: Ficus cordata ethyl acetate fraction, FCP: Ficus cordata petroleum ether fraction, FCT: Ficus cordata total methanol extract, FIA: Ficus ingens remaining aqueous fraction, FIB: Ficus ingens n -butanol fraction, FIE: Ficus ingens ethyl acetate fraction, FIP: Ficus ingens petroleum ether fraction, FIT: Ficus ingens total methanol extract, FPA: Ficus palmata remaining aqueous fraction, FPB: Ficus palmata n -butanol fraction, FPE: Ficus palmata ethyl acetate fraction, FPP: Ficus palmata petroleum ether fraction, FPT: Ficus palmata total methanol extract, GSH: Reduced glutathione, HepG2 cells: Human hepatocellular carcinoma, HPLC-ESI-MS: High-performance liquid chromatography/electrospray ionization mass spectrometry, and SOD: Superoxide dismutase.

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

PubMed

Mohammadi, Saeedeh; Parastar, Hadi

2018-05-15

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

Botanical supplements: detecting the transition from ingredients to supplements

USDA-ARS?s Scientific Manuscript database

Methods were developed using flow injection mass spectrometry (FIMS) and chemometrics for the comparison of spectral similarities and differences of 3 botanical ingredients and their supplements: Echinacea purpurea aerial samples and solid and liquid supplements, E. purpurea root samples and solid s...

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

USDA-ARS?s Scientific Manuscript database

Techniques including ultraviolet-visible spectra (UV), high performance size-exclusion chromatography (HPSEC), fourier-transform infrared spectroscopy (FT-IR) and pre-column derivatization high-performance liquid chromatography (PCD-HPLC) were used in the fingerprinting analysis of Lycium barbarum p...

Characterization of Uranium Ore Concentrate Chemical Composition via Raman Spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Su, Yin-Fong; Tonkyn, Russell G.; Sweet, Lucas E.

Uranium Ore Concentrate (UOC, often called yellowcake) is a generic term that describes the initial product resulting from the mining and subsequent milling of uranium ores en route to production of the U-compounds used in the fuel cycle. Depending on the mine, the ore, the chemical process, and the treatment parameters, UOC composition can vary greatly. With the recent advent of handheld spectrometers, we have chosen to investigate whether either commercial off-the-shelf (COTS) handheld devices or laboratory-grade Raman instruments might be able to i) identify UOC materials, and ii) differentiate UOC samples based on chemical composition and thus suggest themore » mining or milling process. Twenty-eight UOC samples were analyzed via FT-Raman spectroscopy using both 1064 nm and 785 nm excitation wavelengths. These data were also compared with results from a newly developed handheld COTS Raman spectrometer using a technique that lowers background fluorescence signal. Initial chemometric analysis was able to differentiate UOC samples based on mine location. Additional compositional information was obtained from the samples by performing XRD analysis on a subset of samples. The compositional information was integrated with chemometric analysis of the spectroscopic dataset allowing confirmation that class identification is possible based on compositional differences between the UOC samples, typically involving species such as U3O8, α-UO2(OH)2, UO4•2H2O (metastudtite), K(UO2)2O3, etc. While there are clearly excitation λ sensitivities, especially for dark samples, Raman analysis coupled with chemometric data treatment can nicely differentiate UOC samples based on composition and even mine origin.« less

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

PubMed

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

2015-12-01

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

Ion mobility based on column leaching of South African gold tailings dam with chemometric evaluation.

PubMed

Cukrowska, Ewa M; Govender, Koovila; Viljoen, Morris

2004-07-01

New column leaching experiments were designed and used as an alternative rapid screening approach to element mobility assessment. In these experiments, field-moist material was treated with an extracting solution to assess the effects of acidification on element mobility in mine tailings. The main advantage of this version of column leaching experiments with partitioned segments is that they give quick information on current element mobility in conditions closely simulating field conditions to compare with common unrepresentative air-dried, sieved samples used for column leaching experiments. Layers from the tailings dump material were sampled and packed into columns. The design of columns allows extracting leachates from each layer. The extracting solutions used were natural (pH 6.8) and acidified (pH 4.2) rainwater. Metals and anions were determined in the leachates. The concentrations of metals (Ca, Mg, Fe, Mn, Al, Cr, Ni, Co, Zn, and Cu) in sample leachates were determined using ICP OES. The most important anions (NO3-, Cl-, and SO4(2)-) were determined using the closed system izotacophoresis ITP analyser. The chemical analytical data from tailings leaching and physico-chemical data from field measurements (including pH, conductivity, redox potential, temperature) were used for chemometric evaluation of element mobility. Principal factor analysis (PFA) was used to evaluate ions mobility from different layers of tailings dump arising from varied pH and redox conditions. It was found that the results from the partitioned column leaching illustrate much better complex processes of metals mobility from tailings dump than the total column. The chemometric data analysis (PFA) proofed the differences in the various layers leachability that are arising from physico-chemical processes due to chemical composition of tailings dump deposit. Copyright 2004 Elsevier Ltd.

Adult Response to Children's Exploratory Behaviours: An Exploratory Study

ERIC Educational Resources Information Center

Chak, Amy

2010-01-01

Children's interest in exploration is the hallmark of their curiosity. As people who are significant in organising children's environment, how teachers and parents respond to children's exploratory behaviours may promote or hinder the child's desire for further investigation. With reference to Kurt Lewin's concept of "total situation",…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lupoi, Jason

This dissertation focuses on techniques for (1) increasing ethanol yields from saccharification and fermentation of cellulose using immobilized cellulase, and (2) the characterization and classification of lignocellulosic feedstocks, and quantification of useful parameters such as the syringyl/guaiacyl (S/G) lignin monomer content using 1064 nm dispersive multichannel Raman spectroscopy and chemometrics.

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

PubMed

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

2016-06-22

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

Tracking thermal degradation on passion fruit juice through Nuclear Magnetic Resonance and chemometrics.

PubMed

Soares, Marcia Valeria L; Alves Filho, Elenilson G; Silva, Lorena Mara A; Novotny, Etelvino Henrique; Canuto, Kirley Marques; Wurlitzer, Nedio Jair; Narain, Narendra; de Brito, Edy Sousa

2017-03-15

Thermal food processing mainly aims to control microorganism in order to extend its shelf life. However, it may induce chemical and nutritional changes in foodstuff. The Nuclear Magnetic Resonance (NMR) coupled to multivariate analysis was used to evaluate the effect of different thermal processing conditions (85 and 140°C for 4; 15; 30; and 60s) on the passion fruit juice using an Armfield pasteurizer. Through this approach it was possible to identify the changes in the juice composition. The temperature and the time lead to a hydrolysis of the sucrose to glucose and fructose. Additionally, juice submitted to 140°C for 60s results in the degradation of the sucrose and the formation of 5-(hydroxymethyl)-2-furfural (HMF). Despite no novel chemical marker has been identified, the 1 H NMR chemometrics approach may contribute in the choice of the temperature and time to be employed in the juice processing. Copyright © 2016 Elsevier Ltd. All rights reserved.

A new technique for spectrophotometric determination of pseudoephedrine and guaifenesin in syrup and synthetic mixture.

PubMed

Riahi, Siavash; Hadiloo, Farshad; Milani, Seyed Mohammad R; Davarkhah, Nazila; Ganjali, Mohammad R; Norouzi, Parviz; Seyfi, Payam

2011-05-01

The accuracy in predicting different chemometric methods was compared when applied on ordinary UV spectra and first order derivative spectra. Principal component regression (PCR) and partial least squares with one dependent variable (PLS1) and two dependent variables (PLS2) were applied on spectral data of pharmaceutical formula containing pseudoephedrine (PDP) and guaifenesin (GFN). The ability to derivative in resolved overlapping spectra chloropheniramine maleate was evaluated when multivariate methods are adopted for analysis of two component mixtures without using any chemical pretreatment. The chemometrics models were tested on an external validation dataset and finally applied to the analysis of pharmaceuticals. Significant advantages were found in analysis of the real samples when the calibration models from derivative spectra were used. It should also be mentioned that the proposed method is a simple and rapid way requiring no preliminary separation steps and can be used easily for the analysis of these compounds, especially in quality control laboratories. Copyright © 2011 John Wiley & Sons, Ltd.

Detection of counterfeit electronic components through ambient mass spectrometry and chemometrics.

PubMed

Pfeuffer, Kevin P; Caldwell, Jack; Shelley, Jake T; Ray, Steven J; Hieftje, Gary M

2014-09-21

In the last several years, illicit electronic components have been discovered in the inventories of several distributors and even installed in commercial and military products. Illicit or counterfeit electronic components include a broad category of devices that can range from the correct unit with a more recent date code to lower-specification or non-working systems with altered names, manufacturers and date codes. Current methodologies for identification of counterfeit electronics rely on visual microscopy by expert users and, while effective, are very time-consuming. Here, a plasma-based ambient desorption/ionization source, the flowing atmospheric pressure afterglow (FAPA) is used to generate a mass-spectral fingerprint from the surface of a variety of discrete electronic integrated circuits (ICs). Chemometric methods, specifically principal component analysis (PCA) and the bootstrapped error-adjusted single-sample technique (BEAST), are used successfully to differentiate between genuine and counterfeit ICs. In addition, chemical and physical surface-removal techniques are explored and suggest which surface-altering techniques were utilized by counterfeiters.

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

PubMed

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

2015-01-01

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

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

PubMed

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

2018-03-01

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

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

PubMed

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

2013-07-17

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

The discrimination of honey origin using melissopalynology and Raman spectroscopy techniques coupled with multivariate analysis.

PubMed

Corvucci, Francesca; Nobili, Lara; Melucci, Dora; Grillenzoni, Francesca-Vittoria

2015-02-15

Honey traceability to food quality is required by consumers and food control institutions. Melissopalynologists traditionally use percentages of nectariferous pollens to discriminate the botanical origin and the entire pollen spectrum (presence/absence, type and quantities and association of some pollen types) to determinate the geographical origin of honeys. To improve melissopalynological routine analysis, principal components analysis (PCA) was used. A remarkable and innovative result was that the most significant pollens for the traditional discrimination of the botanical and geographical origin of honeys were the same as those individuated with the chemometric model. The reliability of assignments of samples to honey classes was estimated through explained variance (85%). This confirms that the chemometric model properly describes the melissopalynological data. With the aim to improve honey discrimination, FT-microRaman spectrography and multivariate analysis were also applied. Well performing PCA models and good agreement with known classes were achieved. Encouraging results were obtained for botanical discrimination. Copyright © 2014 Elsevier Ltd. All rights reserved.

Best conditions for biodegradation of diesel oil by chemometric tools

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-12-19

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

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

PubMed

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

2018-01-01

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

A chemometrics as a powerful tool in the elucidation of the role of metals in the biosynthesis of volatile organic compounds in Hungarian thyme samples.

PubMed

Arsenijević, Jelena; Marković, Jelena; Soštarić, Ivan; Ražić, Slavica

2013-10-01

The volatile fraction of the leaves of Thymus pannonicus All. (Lamiaceae) was analyzed by headspace extraction followed by GC-FID and GC-MS analysis. The different headspace profiles were recognized, with citral and with monoterpene hydrocarbons as dominant compounds. In addition, the determination of Cr, Co, Ni, Mo, Cu, Zn, Mn, Fe, Mg, Ca, K and Na was conducted by spectroscopic techniques (FAAS, GFAAS and ICP-OES). In order to evaluate the relationship between volatile organic compounds and metals, a chemometrics approach was applied. The data obtained by analysis of the headspace and elemental content were subjected to correlation analysis, factor analysis, principal component analysis and cluster analysis. A number of significant correlations of metals with plant volatiles were found. Correlation of Zn with citral, Mn with oxygenated monoterpenes and Mg with β-bourbonene, could be explained by involvement of metals in the biosynthesis of volatile organic compounds. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Vibrational biospectroscopy: from plants to animals to humans. A historical perspective

NASA Astrophysics Data System (ADS)

Shaw, R. Anthony; Mantsch, Henry H.

1999-05-01

Today, more than ever, vibrational spectroscopy means different things to different people. From their roots as molecular fingerprinting techniques, both infrared and Raman spectroscopy have evolved to the point where they play roles in a staggering variety of scientific endeavors. This survey focuses upon biological and medical applications. The past 40 years have witnessed enormous advances in our understanding of the building blocks of life, and vibrational spectroscopy has played an important role. That role is reviewed briefly here. In parallel with these efforts, the near-IR community developed powerful 'chemometric' methods to extract a wealth of information from spectra that appeared superficially featureless. As vibrational spectroscopy is finding new niches in the medical and clinical realms, these chemometric methods are proving to be a valuable (but not infallible!) adjunct to conventional spectral interpretation. This survey includes a brief outline of biomedical vibrational spectroscopy and imaging, including several representative examples to illustrate the strengths and pitfalls of a growing reliance upon multivariate quantitation and classification methods.

Advanced stability indicating chemometric methods for quantitation of amlodipine and atorvastatin in their quinary mixture with acidic degradation products

NASA Astrophysics Data System (ADS)

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

2016-02-01

Two advanced, accurate and precise chemometric methods are developed for the simultaneous determination of amlodipine besylate (AML) and atorvastatin calcium (ATV) in the presence of their acidic degradation products in tablet dosage forms. The first method was Partial Least Squares (PLS-1) and the second was Artificial Neural Networks (ANN). PLS was compared to ANN models with and without variable selection procedure (genetic algorithm (GA)). For proper analysis, a 5-factor 5-level experimental design was established resulting in 25 mixtures containing different ratios of the interfering species. Fifteen mixtures were used as calibration set and the other ten mixtures were used as validation set to validate the prediction ability of the suggested models. The proposed methods were successfully applied to the analysis of pharmaceutical tablets containing AML and ATV. The methods indicated the ability of the mentioned models to solve the highly overlapped spectra of the quinary mixture, yet using inexpensive and easy to handle instruments like the UV-VIS spectrophotometer.

Quality assessment of the saffron samples using second-order spectrophotometric data assisted by three-way chemometric methods via quantitative analysis of synthetic colorants in adulterated saffron

NASA Astrophysics Data System (ADS)

Masoum, Saeed; Gholami, Ali; Hemmesi, Marjan; Abbasi, Saleheh

2015-09-01

Saffron is a valuable culinary spice that can be used not only for dyes and cooking, but also for many medical purposes. Due to its high price and restriction of its production, various fraud manners in its production have been growing. Addition of synthetic colorants to saffron is the most common way for adulteration. In this work, chemometric methods are proposed to resolve the three-dimensional absorbance spectra-pH data for simultaneous determination of the two colorants Tartrazin and Sunset yellow, in adulterated saffron. The rank deficiency in the concentration mode impaired the system. Therefore, to extirpate the ambiguity, which results from rank deficiency, three-way variation array V was generated by subtracting the first pH spectrum from each spectrum at each pH. This allows the extraction of extent reaction profile and mixture reaction spectral profiles, as well as the relative concentrations of the analytes.

Central composite design with the help of multivariate curve resolution in loadability optimization of RP-HPLC to scale-up a binary mixture.

PubMed

Taheri, Mohammadreza; Moazeni-Pourasil, Roudabeh Sadat; Sheikh-Olia-Lavasani, Majid; Karami, Ahmad; Ghassempour, Alireza

2016-03-01

Chromatographic method development for preparative targets is a time-consuming and subjective process. This can be particularly problematic because of the use of valuable samples for isolation and the large consumption of solvents in preparative scale. These processes could be improved by using statistical computations to save time, solvent and experimental efforts. Thus, contributed by ESI-MS, after applying DryLab software to gain an overview of the most effective parameters in separation of synthesized celecoxib and its co-eluted compounds, design of experiment software that relies on multivariate modeling as a chemometric approach was used to predict the optimized touching-band overloading conditions by objective functions according to the relationship between selectivity and stationary phase properties. The loadability of the method was investigated on the analytical and semi-preparative scales, and the performance of this chemometric approach was approved by peak shapes beside recovery and purity of products. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Prediction models for Arabica coffee beverage quality based on aroma analyses and chemometrics.

PubMed

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

2012-11-15

In this work, soft modeling based on chemometric analyses of coffee beverage sensory data and the chromatographic profiles of volatile roasted coffee compounds is proposed to predict the scores of acidity, bitterness, flavor, cleanliness, body, and overall quality of the coffee beverage. A partial least squares (PLS) regression method was used to construct the models. The ordered predictor selection (OPS) algorithm was applied to select the compounds for the regression model of each sensory attribute in order to take only significant chromatographic peaks into account. The prediction errors of these models, using 4 or 5 latent variables, were equal to 0.28, 0.33, 0.35, 0.33, 0.34 and 0.41, for each of the attributes and compatible with the errors of the mean scores of the experts. Thus, the results proved the feasibility of using a similar methodology in on-line or routine applications to predict the sensory quality of Brazilian Arabica coffee. Copyright © 2012 Elsevier B.V. All rights reserved.

Chemometric analysis for extraction of individual fluorescence spectrum and lifetimes from a target mixture

NASA Technical Reports Server (NTRS)

Hallidy, William H. (Inventor); Chin, Robert C. (Inventor)

1999-01-01

The present invention is a system for chemometric analysis for the extraction of the individual component fluorescence spectra and fluorescence lifetimes from a target mixture. The present invention combines a processor with an apparatus for generating an excitation signal to transmit at a target mixture and an apparatus for detecting the emitted signal from the target mixture. The present invention extracts the individual fluorescence spectrum and fluorescence lifetime measurements from the frequency and wavelength data acquired from the emitted signal. The present invention uses an iterative solution that first requires the initialization of several decision variables and the initial approximation determinations of intermediate matrices. The iterative solution compares the decision variables for convergence to see if further approximation determinations are necessary. If the solution converges, the present invention then determines the reduced best fit error for the analysis of the individual fluorescence lifetime and the fluorescence spectrum before extracting the individual fluorescence lifetime and fluorescence spectrum from the emitted signal of the target mixture.

Authenticity of rice (Oryza sativa L.) geographical origin based on analysis of C, N, O and S stable isotope ratios: a preliminary case report in Korea, China and Philippine.

PubMed

Chung, Ill-Min; Kim, Jae-Kwang; Prabakaran, Mayakrishnan; Yang, Jin-Hee; Kim, Seung-Hyun

2016-05-01

Although rice (Oryza sativa L.) is the third largest food crop, relatively fewer studies have been reported on rice geographical origin based on light element isotope ratios in comparison with other foods such as wine, beef, juice, oil and milk. Therefore this study tries to discriminate the geographical origin of the same rice cultivars grown in different Asian countries using the analysis of C, N, O and S stable isotope ratios and chemometrics. The δ(15) NAIR , δ(18) OVSMOW and δ(34) SVCDT values of brown rice were more markedly influenced by geographical origin than was the δ(13) CVPDB value. In particular, the combination of δ(18) OVSMOW and δ(34) SVCDT more efficiently discriminated rice geographical origin than did the remaining combinations. Principal component analysis (PCA) revealed a clear discrimination between different rice geographical origins but not between rice genotypes. In particular, the first components of PCA discriminated rice cultivated in the Philippines from rice cultivated in China and Korea. The present findings suggest that analysis of the light element isotope composition combined with chemometrics can be potentially applicable to discriminate rice geographical origin and also may provide a valuable insight into the control of improper or fraudulent labeling regarding the geographical origin of rice worldwide. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

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

PubMed

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

2011-10-10

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

Elemental profiling of Noah's Ark shell (Arca noae, Linnaeus, 1758) by plasma optical spectrometry and chemometric tools.

PubMed

Kobelja, Kristina; Nemet, Ivan; Župan, Ivan; Čulin, Jelena; Rončević, Sanda

2016-12-01

Determination of metal content in biominerals provides essential information with respect to relations between biomineralization processes and environmental status. Mussels are species that have a great potential as bio-marker species and therefore, they are in the focus of numerous biomineralization and ecological studies. In this study, elemental profile of mussel shell of Noah's Ark (Arca noe, Linnaeus, 1758), which inhabit eastern Adriatic Sea was obtained by determination of seventeen elements content using inductively coupled plasma optical emission spectrometry (ICP-OES). Shell samples were collected from marine protected area and from marine shipping route in eastern Adriatic Sea. The accuracy of applied analytical procedure based on microwave decomposition of shell samples was tested by use of reference materials of limestone and by matrix-matched standards. By aid of chemometric methods, the elemental profile along with variability of elements content of shell was obtained. The impact of different environment on elements content was established by use of multivariate statistical PCA method. Discernment between two groups of samples was manifested. Among results of main, minor and trace elements content, the last one which denoted to Cd, Co, Cu, Pb, and Mn was expressed as principal distinctive feature of shell samples collected from different sampling sites. Elemental profiling of mussel shell Noah's Ark provides novel insight in species status as well as in environmental status on the observed locations. Copyright © 2016 Elsevier GmbH. All rights reserved.

Isotope ratio mass spectrometry in combination with chemometrics for characterization of geographical origin and agronomic practices of table grape.

PubMed

Longobardi, Francesco; Casiello, Grazia; Centonze, Valentina; Catucci, Lucia; Agostiano, Angela

2017-08-01

Although table grape is one of the most cultivated and consumed fruits worldwide, no study has been reported on its geographical origin or agronomic practice based on stable isotope ratios. This study aimed to evaluate the usefulness of isotopic ratios (i.e. 2 H/ 1 H, 13 C/ 12 C, 15 N/ 14 N and 18 O/ 16 O) as possible markers to discriminate the agronomic practice (conventional versus organic farming) and provenance of table grape. In order to quantitatively evaluate which of the isotopic variables were more discriminating, a t test was carried out, in light of which only δ 13 C and δ 18 O provided statistically significant differences (P ≤ 0.05) for the discrimination of geographical origin and farming method. Principal component analysis (PCA) showed no good separation of samples differing in geographical area and agronomic practice; thus, for classification purposes, supervised approaches were carried out. In particular, general discriminant analysis (GDA) was used, resulting in prediction abilities of 75.0 and 92.2% for the discrimination of farming method and origin respectively. The present findings suggest that stable isotopes (i.e. δ 18 O, δ 2 H and δ 13 C) combined with chemometrics can be successfully applied to discriminate the provenance of table grape. However, the use of bulk nitrogen isotopes was not effective for farming method discrimination. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

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

PubMed

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

2014-10-01

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

Simulated aging of lubricant oils by chemometric treatment of infrared spectra: potential antioxidant properties of sulfur structures.

PubMed

Amat, Sandrine; Braham, Zeineb; Le Dréau, Yveline; Kister, Jacky; Dupuy, Nathalie

2013-03-30

Lubricant oils are complex mixtures of base oils and additives. The evolution of their performance over time strongly depends on its resistance to thermal oxidation. Sulfur compounds revealed interesting antioxidant properties. This study presents a method to evaluate the lubricant oil oxidation. Two samples, a synthetic and a paraffinic base oils, were tested pure and supplemented with seven different sulfur compounds. An aging cell adapted to a Fourier Transform InfraRed (FT-IR) spectrometer allows the continuous and direct analysis of the oxidative aging of base oils. Two approaches were applied to study the oxidation/anti-oxidation phenomena. The first one leads to define a new oxidative spectroscopic index based on a reduced spectral range where the modifications have been noticed (from 3050 to 2750 cm(-1)). The second method is based on chemometric treatments of whole spectra (from 4000 to 400 cm(-1)) to extract underlying information. A SIMPLe-to-use Interactive Self Modeling Analysis (SIMPLISMA) method has been used to identify more precisely the chemical species produced or degraded during the thermal treatment and to follow their evolution. Pure spectra of different species present in oil were obtained without prior information of their existence. The interest of this tool is to supply relative quantitative information reflecting evolution of the relative abundance of the different products over thermal aging. Results obtained by these two ways have been compared to estimate their concordance. Copyright © 2013 Elsevier B.V. All rights reserved.

Chemometrics and Intelligent Laboratory Systems, Volume 10, Numbers 1-2, February 1991. Proceedings of the Mathematics in Chemistry Conference Held in College Station, Texas on 8-10 November 1989

DTIC Science & Technology

1991-02-01

from a small group of speak- Four quite different subjects were tors, were well described. As these ers. This arrangement meant that discussed: local...ACKNOWLEDGEMENTS 6 M Gerloch and RG Woolley. The functional group m igand-field studies the empircal and theoretical status of It is a pleasure to thank...Al) Babes 26 3 43 add about three or four observable c.,mponents. Learning 26 0 44 0 In this study we applied SIMCA. nearest machine neighbor, Bayes

Exploratory Programing in Georgia's Middle Schools.

ERIC Educational Resources Information Center

Warren, Louis L.; Allen, Michael G.

This study surveyed the nature and extent of exploratory programming in intermediate schools. A 22-item questionnaire was sent to all 285 of the state's middle and junior high schools. Of the 163 respondents, 160 indicated that they had some form of exploratory programming. The latter number included: (1) 155 schools with traditional exploratory…

The Effects of Feedback during Exploratory Mathematics Problem Solving: Prior Knowledge Matters

ERIC Educational Resources Information Center

Fyfe, Emily R.; Rittle-Johnson, Bethany; DeCaro, Marci S.

2012-01-01

Providing exploratory activities prior to explicit instruction can facilitate learning. However, the level of guidance provided during the exploration has largely gone unstudied. In this study, we examined the effects of 1 form of guidance, feedback, during exploratory mathematics problem solving for children with varying levels of prior domain…

Cross-species assessments of Motor and Exploratory Behavior related to Bipolar Disorder

PubMed Central

Henry, Brook L.; Minassian, Arpi; Young, Jared W.; Paulus, Martin P.; Geyer, Mark A.; Perry, William

2010-01-01

Alterations in exploratory behavior are a fundamental feature of bipolar mania, typically characterized as motor hyperactivity and increased goal-directed behavior in response to environmental cues. In contrast, abnormal exploration associated with schizophrenia and depression can manifest as prominent withdrawal, limited motor activity, and inattention to the environment. While motor abnormalities are cited frequently as clinical manifestations of these disorders, relatively few empirical studies have quantified human exploratory behavior. This article reviews the literature characterizing motor and exploratory behavior associated with bipolar disorder and genetic and pharmacological animal models of the illness. Despite sophisticated assessment of exploratory behavior in rodents, objective quantification of human motor activity has been limited primarily to actigraphy studies with poor cross-species translational value. Furthermore, symptoms that reflect the cardinal features of bipolar disorder have proven difficult to establish in putative animal models of this illness. Recently, however, novel tools such as the Human Behavioral Pattern Monitor provide multivariate translational measures of motor and exploratory activity, enabling improved understanding of the neurobiology underlying psychiatric disorders. PMID:20398694

Quality-by-design III: application of near-infrared spectroscopy to monitor roller compaction in-process and product quality attributes of immediate release tablets.

PubMed

Kona, Ravikanth; Fahmy, Raafat M; Claycamp, Gregg; Polli, James E; Martinez, Marilyn; Hoag, Stephen W

2015-02-01

The objective of this study is to use near-infrared spectroscopy (NIRS) coupled with multivariate chemometric models to monitor granule and tablet quality attributes in the formulation development and manufacturing of ciprofloxacin hydrochloride (CIP) immediate release tablets. Critical roller compaction process parameters, compression force (CFt), and formulation variables identified from our earlier studies were evaluated in more detail. Multivariate principal component analysis (PCA) and partial least square (PLS) models were developed during the development stage and used as a control tool to predict the quality of granules and tablets. Validated models were used to monitor and control batches manufactured at different sites to assess their robustness to change. The results showed that roll pressure (RP) and CFt played a critical role in the quality of the granules and the finished product within the range tested. Replacing binder source did not statistically influence the quality attributes of the granules and tablets. However, lubricant type has significantly impacted the granule size. Blend uniformity, crushing force, disintegration time during the manufacturing was predicted using validated PLS regression models with acceptable standard error of prediction (SEP) values, whereas the models resulted in higher SEP for batches obtained from different manufacturing site. From this study, we were able to identify critical factors which could impact the quality attributes of the CIP IR tablets. In summary, we demonstrated the ability of near-infrared spectroscopy coupled with chemometrics as a powerful tool to monitor critical quality attributes (CQA) identified during formulation development.

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

PubMed

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

2007-08-01

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

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

PubMed

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

2005-07-01

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

Application of chemometric methods for assessment and modelling of microbiological quality data concerning coastal bathing water in Greece.

PubMed

Papaioannou, Agelos; Rigas, George; Papastergiou, Panagiotis; Hadjichristodoulou, Christos

2014-12-02

Worldwide, the aim of managing water is to safeguard human health whilst maintaining sustainable aquatic and associated terrestrial, ecosystems. Because human enteric viruses are the most likely pathogens responsible for waterborne diseases from recreational water use, but detection methods are complex and costly for routine monitoring, it is of great interest to determine the quality of coastal bathing water with a minimum cost and maximum safety. This study handles the assessment and modelling of the microbiological quality data of 2149 seawater bathing areas in Greece over 10-year period (1997-2006) by chemometric methods. Cluster analysis results indicated that the studied bathing beaches are classified in accordance with the seasonality in three groups. Factor analysis was applied to investigate possible determining factors in the groups resulted from the cluster analysis, and also two new parameters were created in each group; VF1 includes E. coli, faecal coliforms and total coliforms and VF2 includes faecal streptococci/enterococci. By applying the cluster analysis in each seasonal group, three new groups of coasts were generated, group A (ultraclean), group B (clean) and group C (contaminated). The above analysis is confirmed by the application of discriminant analysis, and proves that chemometric methods are useful tools for assessment and modeling microbiological quality data of coastal bathing water on a large scale, and thus could attribute to effective and economical monitoring of the quality of coastal bathing water in a country with a big number of bathing coasts, like Greece. Significance for public healthThe microbiological protection of coastal bathing water quality is of great interest for the public health authorities as well as for the economy. The present study proves that this protection can be achieved by monitoring only two microbiological parameters, E. coli and faecal streptococci/enterococci instead four microbiological parameters (the two mentioned above plus Total coliforms and Faecal coliforms) that are usually monitored today. As a consequence, countries, especially those with large quantities of coastal bathing sites, can perform microbiological monitoring of their bathing waters by checking only the mentioned two parameters, thus ensuring economies of scale. Thus, funds can be used in other actions to preserve the quality of coastal water and human health. This in turn, would aid in the assessment of the quality of coastal bathing waters and provide a more timely indication of bathing water quality, hence contributing to the immediate health protection of bathers.

Diffuse Reflectance Spectroscopy for Total Carbon Analysis of Hawaiian Soils

NASA Astrophysics Data System (ADS)

McDowell, M. L.; Bruland, G. L.; Deenik, J. L.; Grunwald, S.; Uchida, R.

2010-12-01

Accurate assessment of total carbon (Ct) content is important for fertility and nutrient management of soils, as well as for carbon sequestration studies. The non-destructive analysis of soils by diffuse reflectance spectroscopy (DRS) is a potential supplement or alternative to the traditional time-consuming and costly combustion method of Ct analysis, especially in spatial or temporal studies where sample numbers are large. We investigate the use of the visible to near-infrared (VNIR) and mid-infrared (MIR) spectra of soils coupled with chemometric analysis to determine their Ct content. Our specific focus is on Hawaiian soils of agricultural importance. Though this technique has been introduced to the soil community, it has yet to be fully tested and used in practical applications for all soil types, and this is especially true for Hawaii. In short, DRS characterizes and differentiates materials based on the variation of the light reflected by a material at certain wavelengths. This spectrum is dependent on the material’s composition, structure, and physical state. Multivariate chemometric analysis unravels the information in a set of spectra that can help predict a property such as Ct. This study benefits from the remarkably diverse soils of Hawaii. Our sample set includes 216 soil samples from 145 pedons from the main Hawaiian Islands archived at the National Soil Survey Center in Lincoln, NE, along with more than 50 newly-collected samples from Kauai, Oahu, Molokai, and Maui. In total, over 90 series from 10 of the 12 soil orders are represented. The Ct values of these samples range from < 1% - 55%. We anticipate that the diverse nature of our sample set will ensure a model with applicability to a wide variety of soils, both in Hawaii and globally. We have measured the VNIR and MIR spectra of these samples and obtained their Ct values by dry combustion. Our initial analyses are conducted using only samples obtained from the Lincoln archive. In this preliminary case, we use Partial Least Squares (PLS) regression with cross validation to develop a prediction model for soils of unknown carbon content given only their spectral signature. We find R2 values of greater than 0.93 for the MIR spectra and 0.87 for the VNIR spectra, indicating a strong ability to correlate a soil’s spectrum with its Ct content. We build on these encouraging results by continuing chemometric analyses using the full data set, different data subsets, separate model calibration and validation groups, combined VNIR and MIR spectra, and exploring different data pretreatment options and variations to the PLS parameters.

Applying Fingerprint Fourier Transformed Infrared Spectroscopy and Chemometrics to Assess Soil Ecosystem Disturbance and Recovery

USDA-ARS?s Scientific Manuscript database

The assessment and monitoring of soil ecosystem function has been hindered due to the shortcomings of many traditional analytical techniques (e.g., soil enzyme activities, microbial incubations), including: high cost, long time investment and difficulties with data interpretation. Consequently, ther...

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

NASA Astrophysics Data System (ADS)

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

2015-07-01

Highly non-linear dynamical systems, such as those found in atmospheric chemistry, necessitate hierarchical approaches to both experiment and modelling in order to ultimately identify and achieve fundamental process-understanding in the full open system. Atmospheric simulation chambers comprise an intermediate in complexity, between a classical laboratory experiment and the full, ambient system. As such, they can generate large volumes of difficult-to-interpret data. Here we describe and implement a chemometric dimension reduction methodology for the deconvolution and interpretation of complex gas- and particle-phase composition spectra. The methodology comprises principal component analysis (PCA), hierarchical cluster analysis (HCA) and positive least-squares discriminant analysis (PLS-DA). These methods are, for the first time, applied to simultaneous gas- and particle-phase composition data obtained from a comprehensive series of environmental simulation chamber experiments focused on biogenic volatile organic compound (BVOC) photooxidation and associated secondary organic aerosol (SOA) formation. We primarily investigated the biogenic SOA precursors isoprene, α-pinene, limonene, myrcene, linalool and β-caryophyllene. The chemometric analysis is used to classify the oxidation systems and resultant SOA according to the controlling chemistry and the products formed. Results show that "model" biogenic oxidative systems can be successfully separated and classified according to their oxidation products. Furthermore, a holistic view of results obtained across both the gas- and particle-phases shows the different SOA formation chemistry, initiating in the gas-phase, proceeding to govern the differences between the various BVOC SOA compositions. The results obtained are used to describe the particle composition in the context of the oxidised gas-phase matrix. An extension of the technique, which incorporates into the statistical models data from anthropogenic (i.e. toluene) oxidation and "more realistic" plant mesocosm systems, demonstrates that such an ensemble of chemometric mapping has the potential to be used for the classification of more complex spectra of unknown origin. More specifically, the addition of mesocosm data from fig and birch tree experiments shows that isoprene and monoterpene emitting sources, respectively, can be mapped onto the statistical model structure and their positional vectors can provide insight into their biological sources and controlling oxidative chemistry. The potential to extend the methodology to the analysis of ambient air is discussed using results obtained from a zero-dimensional box model incorporating mechanistic data obtained from the Master Chemical Mechanism (MCMv3.2). Such an extension to analysing ambient air would prove a powerful asset in assisting with the identification of SOA sources and the elucidation of the underlying chemical mechanisms involved.

Middle School Exploratory Foreign Language Programs: A Position Paper.

ERIC Educational Resources Information Center

National Council of State Supervisors of Foreign Language.

Four types of exploratory foreign language programs are described: (1) the language overview course, (2) the trial-study course, (3) the Level I offering, and (4) the course for the non-college bound. It is largely in the middle schools (grades 6-8) and junior high schools (grades 7-9) that exploratory programs are being used. The language…

Envisioning Competence: Learning, Problem Solving, and Children at Work in the Exploratory Bicycle Shop

ERIC Educational Resources Information Center

Hammond, Charles Florian

2010-01-01

This study examines the conceptual learning and cognitive development processes of schoolchildren engaged in problem solving activities in a non-school, workplace setting known as the exploratory bicycle shop. The exploratory bike shop is a commercial bicycle shop: a) that has been adapted for combined retail and educational purposes and b) where…

Automated software-guided identification of new buspirone metabolites using capillary LC coupled to ion trap and TOF mass spectrometry.

PubMed

Fandiño, Anabel S; Nägele, Edgar; Perkins, Patrick D

2006-02-01

The identification and structure elucidation of drug metabolites is one of the main objectives in in vitro ADME studies. Typical modern methodologies involve incubation of the drug with subcellular fractions to simulate metabolism followed by LC-MS/MS or LC-MS(n) analysis and chemometric approaches for the extraction of the metabolites. The objective of this work was the software-guided identification and structure elucidation of major and minor buspirone metabolites using capillary LC as a separation technique and ion trap MS(n) as well as electrospray ionization orthogonal acceleration time-of-flight (ESI oaTOF) mass spectrometry as detection techniques. Buspirone mainly underwent hydroxylation, dihydroxylation and N-oxidation in S9 fractions in the presence of phase I co-factors and the corresponding glucuronides were detected in the presence of phase II co-factors. The use of automated ion trap MS/MS data-dependent acquisition combined with a chemometric tool allowed the detection of five small chromatographic peaks of unexpected metabolites that co-eluted with the larger chromatographic peaks of expected metabolites. Using automatic assignment of ion trap MS/MS fragments as well as accurate mass measurements from an ESI oaTOF mass spectrometer, possible structures were postulated for these metabolites that were previously not reported in the literature. Copyright 2006 John Wiley & Sons, Ltd.

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

PubMed

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

2016-11-01

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

Multi-capillary column-ion mobility spectrometry: a potential screening system to differentiate virgin olive oils.

PubMed

Garrido-Delgado, Rocío; Arce, Lourdes; Valcárcel, Miguel

2012-01-01

The potential of a headspace device coupled to multi-capillary column-ion mobility spectrometry has been studied as a screening system to differentiate virgin olive oils ("lampante," "virgin," and "extra virgin" olive oil). The last two types are virgin olive oil samples of very similar characteristics, which were very difficult to distinguish with the existing analytical method. The procedure involves the direct introduction of the virgin olive oil sample into a vial, headspace generation, and automatic injection of the volatiles into a gas chromatograph-ion mobility spectrometer. The data obtained after the analysis by duplicate of 98 samples of three different categories of virgin olive oils, were preprocessed and submitted to a detailed chemometric treatment to classify the virgin olive oil samples according to their sensory quality. The same virgin olive oil samples were also analyzed by an expert's panel to establish their category and use these data as reference values to check the potential of this new screening system. This comparison confirms the potential of the results presented here. The model was able to classify 97% of virgin olive oil samples in their corresponding group. Finally, the chemometric method was validated obtaining a percentage of prediction of 87%. These results provide promising perspectives for the use of ion mobility spectrometry to differentiate virgin olive oil samples according to their quality instead of using the classical analytical procedure.

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

NASA Astrophysics Data System (ADS)

Rasouli, Zolaikha; Ghavami, Raouf

2018-02-01

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

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

PubMed

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

2017-10-01

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

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

PubMed

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

2016-02-01

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

Chemometric techniques on the analysis of Raman spectra of serum blood samples of breast cancer patients

NASA Astrophysics Data System (ADS)

Rocha-Osornio, L. N.; Pichardo-Molina, J. L.; Barbosa-Garcia, O.; Frausto-Reyes, C.; Araujo-Andrade, C.; Huerta-Franco, R.; Gutiérrez-Juárez, G.

2008-02-01

Raman spectroscopy and Multivariate methods were used to study serum blood samples of control and breast cancer patients. Blood samples were obtained from 11 patients and 12 controls from the central region of Mexico. Our results show that principal component analysis is able to discriminate serum sample of breast cancer patients from those of control group, also the loading vectors of PCA plotted as a function of Raman shift shown which bands permitted to make the maximum discrimination between both groups of samples.

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

PubMed

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

2006-12-01

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

An integrated approach utilizing chemometrics and GC/MS for classification of chamomile flowers, essential oils and commerical products

USDA-ARS?s Scientific Manuscript database

As part of an ongoing research program on authentication, safety and biological evaluation of phytochemicals and dietary supplements, an in-depth chemical investigation of different types of chamomile was performed. A collection of chamomile samples including authenticated plants, commercial product...

Authentication of organically and conventionally grown basils by gas chromatograpy/mass spectrometry chemical profiles

USDA-ARS?s Scientific Manuscript database

Basil plants cultivated by organic and conventional farming practices were differentiated using gas chromatography/mass spectrometry (GC/MS) and chemometric methods. The two-way GC/MS data sets were baseline-corrected and retention time-aligned prior to data processing. Two self-devised fuzzy clas...

Online high-speed NIR diffuse-reflectance imaging spectroscopy in food quality monitoring

NASA Astrophysics Data System (ADS)

Driver, Richard D.; Didona, Kevin

2009-05-01

The use of hyperspectral technology in the NIR for food quality monitoring is discussed. An example of the use of hyperspectral diffuse reflectance scanning and post-processing with a chemometric model shows discrimination between four pharmaceutical samples comprising Aspirin, Acetaminophen, Vitamin C and Vitamin D.

Characterizing the EEG correlates of exploratory behavior.

PubMed

Bourdaud, Nicolas; Chavarriaga, Ricardo; Galan, Ferran; Millan, José Del R

2008-12-01

This study aims to characterize the electroencephalography (EEG) correlates of exploratory behavior. Decision making in an uncertain environment raises a conflict between two opposing needs: gathering information about the environment and exploiting this knowledge in order to optimize the decision. Exploratory behavior has already been studied using functional magnetic resonance imaging (fMRI). Based on a usual paradigm in reinforcement learning, this study has shown bilateral activation in the frontal and parietal cortex. To our knowledge, no previous study has been done on it using EEG. The study of the exploratory behavior using EEG signals raises two difficulties. First, the labels of trial as exploitation or exploration cannot be directly derived from the subject action. In order to access this information, a model of how the subject makes his decision must be built. The exploration related information can be then derived from it. Second, because of the complexity of the task, its EEG correlates are not necessarily time locked with the action. So the EEG processing methods used should be designed in order to handle signals that shift in time across trials. Using the same experimental protocol as the fMRI study, results show that the bilateral frontal and parietal areas are also the most discriminant. This strongly suggests that the EEG signal also conveys information about the exploratory behavior.

Empowered to Play: A Case Study Describing the Impact of Powered Mobility on the Exploratory Play of Disabled Children.

PubMed

Sonday, Amshuda; Gretschel, Pam

2016-03-01

Exploratory play is one of the most vital ways in which children learn about their environment and develop. It is well documented that limited mobility restricts a child's ability to engage in their environment through exploratory play. In this study, a qualitative, collective case study design explored the impact of powered mobility on the exploratory play of two children with physical disabilities. Data were collected from the children, their parents and their siblings through participant observation and in-depth, informal interviews. This paper focuses on two themes: Opportunity to Play revealed how powered mobility increased opportunities for the children to become more actively engaged in exploratory play with others across a wider array of contexts, and My Child was Transformed highlighted significant changes in the affect and motivation of each child, which seemed to be linked to their increased internal control over their play choices. The findings suggest that the provision of powered mobility is a key contributor promoting the participation of physically disabled children in exploratory play. Because of undergraduate curricular constraints, a limitation of this study was that data were only confined to 2 months; affecting the depth of data gained that prolonged engagement would have offered. The study recommends for occupational therapy practice that occupational therapists advocate for easier access to powered mobility through governmental and policy means. The study also recommends further research be conducted on the experiences of the caregivers on how these powered mobility devices have influenced their day-to-day occupations. Copyright © 2015 John Wiley & Sons, Ltd.

Changes in the pattern of exploratory behavior are associated with the emergence of social dominance relationships in male rats.

PubMed

Arakawa, Hiroyuki

2006-01-01

This study examined the effect of the establishment of dominance relationships and subordination on exploratory behavior for both postpubertal and adult male rats. Prior to an open field test, subjects were housed either in isolation (IS) or in littermate pairs (PS) with mild dominance relationships without overt victory or defeat, or in pairs with clear hierarchical relationships as dominants (DOM) or subordinates (SUB). Stretch-attend postures and entries into the center area of the open-field were measured as an index of passive and active exploratory behavior, respectively, and crossings in the peripheral area were counted as activity. SUB rats, both postpubertal and adult, displayed less activity and lower levels of active exploratory behavior, whereas adult IS rats showed higher levels of active exploratory behavior compared to the other groups. Furthermore, both DOM and PS rats exhibited a more passive pattern of exploratory behavior in adulthood than in postpuberty. Thus the results show that an increase in the active exploratory pattern is inhibited by the establishment of social relationships among adult rats, while a decrease in activity is a primarily effect of subordination. The capacity to change exploratory patterns following subordination is found even in the postpubertal stage when adultlike social relationships have not yet appeared. Copyright 2005 Wiley Periodicals, Inc.

[Studies of pattern recognition of fingerprint profile of cattle bile powder and determination of multi-component in it].

PubMed

Shi, Yan; Zheng, Tian-Jiao; Wei, Feng; Lin, Rui-Chao; Ma, Shuang-Cheng

2016-07-01

An HPLC-ELSD method with good specificity and good accuracy was used for the studies of fingerprint and quantification of multi-components for cattle bile powder. The chromatographic analysis was carried out on a Phenomenex Gemini C₁₈ column (4.6 mm×250 mm, 5 μm) with a column temperature of 40 ℃ and a liquid flow-rate of 1.0 mL•min⁻¹ using 10 mmol ammonium acetate solution and acetonitrile as the mobile phase with a linear gradient. An ELSD was used with a nitrogen flow-rate of 2.8 L•h⁻¹, at a drift tube temperature of 110 ℃. The average contents of glycocholic acid, glycodeoxycholic acid, taurocholic acid, taurodeoxycholic acid were (25.2±17.0)%, (4.1±3.4)%, (24.5±20.0)% and (5.2±3.8)% respectively, and the total content of the four bile acids was (59.0±26.0)%. Beyond that, the preprocessing and pattern recognition analysis of the chromatographic fingerprints of samples were applied with chemometric method. The results of this chemometric analysis indicated that the samples from market and self-made samples were different signally, and four regions were noteworthy due to their great impact with poor chromatographic signal. All in one, because this HPLC-ELSD method was simple and accurate, it was suitable for the quality assessment and quality control of cattle bile powder and could be the technological base for its standard perfection. Copyright© by the Chinese Pharmaceutical Association.

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

PubMed

Wang, Yong; Ni, Yongnian

2014-01-21

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

Investigation of different spectrophotometric and chemometric methods for determination of entacapone, levodopa and carbidopa in ternary mixture

NASA Astrophysics Data System (ADS)

Abdel-Ghany, Maha F.; Hussein, Lobna A.; Ayad, Miriam F.; Youssef, Menatallah M.

2017-01-01

New, simple, accurate and sensitive UV spectrophotometric and chemometric methods have been developed and validated for determination of Entacapone (ENT), Levodopa (LD) and Carbidopa (CD) in ternary mixture. Method A is a derivative ratio spectra zero-crossing spectrophotometric method which allows the determination of ENT in the presence of both LD and CD by measuring the peak amplitude at 249.9 nm in the range of 1-20 μg mL- 1. Method B is a double divisor-first derivative of ratio spectra method, used for determination of ENT, LD and CD at 245, 239 and 293 nm, respectively. Method C is a mean centering of ratio spectra which allows their determination at 241, 241.6 and 257.1 nm, respectively. Methods B and C could successfully determine the studied drugs in concentration ranges of 1-20 μg mL- 1 for ENT and 10-90 μg mL- 1 for both LD and CD. Methods D and E are principal component regression and partial least-squares, respectively, used for the simultaneous determination of the studied drugs by using seventeen mixtures as calibration set and eight mixtures as validation set. The developed methods have the advantage of simultaneous determination of the cited components without any pre-treatment. All the results were statistically compared with the reported methods, where no significant difference was observed. The developed methods were satisfactorily applied to the analysis of the investigated drugs in their pure form and in pharmaceutical dosage forms.

Connectivism in Postsecondary Online Courses: An Exploratory Factor Analysis

ERIC Educational Resources Information Center

Hogg, Nanette; Lomicky, Carol S.

2012-01-01

This study explores 465 postsecondary students' experiences in online classes through the lens of connectivism. Downes' 4 properties of connectivism (diversity, autonomy, interactivity, and openness) were used as the study design. An exploratory factor analysis was performed. This study found a 4-factor solution. Subjects indicated that autonomy…

An Exploratory Study of the Implementation of Computer Technology in an American Islamic Private School

ERIC Educational Resources Information Center

Saleem, Mohammed M.

2009-01-01

This exploratory study of the implementation of computer technology in an American Islamic private school leveraged the case study methodology and ethnographic methods informed by symbolic interactionism and the framework of the Muslim Diaspora. The study focused on describing the implementation of computer technology and identifying the…

Rapid assessment of corn seed viability using short wave infrared line-scan hyperspectral imaging and chemometrics

USDA-ARS?s Scientific Manuscript database

Knowledge of the viability status of seeds before sowing is important to farmers and seed suppliers. However, a myriad of factors can reduce viability of seeds or completely render seeds non-viable during pre- and post-harvest operations. Spectral imaging has shown potential for determining seed via...

Classification of cultivation locations of Panax quinquefolius L samples using high performance liquid chromatography-electrospray ionization mass spectrometry and chemometric analysis

USDA-ARS?s Scientific Manuscript database

Panax quinquefolius L (P. quinquefolius L) samples grown in the United States and China were analyzed with high performance liquid chromatography-mass spectrometry (HPLC—MS). Prior to classification, the two-way datasets were subjected to pretreatment including baseline correction and retention tim...

Classification of cultivation locations of panax quinquefolius L samples using high performance liquid chromatography-electrospray ionization mass spectrometry and chemometric analysis

USDA-ARS?s Scientific Manuscript database

Panax quinquefolius L (P. quinquefolius L) samples grown in the United States and China were analyzed with high performance liquid chromatography-mass spectrometry (HPLC—MS). Prior to classification, the two-way datasets were subjected to pretreatment including baseline correction and retention ti...

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

USDA-ARS?s Scientific Manuscript database

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

Progress Toward Quality Assurance Standards for Advanced Hydrocarbon Fuels Based on Thermal Performance Testing and Chemometric Modeling

DTIC Science & Technology

2015-12-15

axial direction; v – fluid velocity; Twc – wall temperature; Tb – fuel bulk temperature; q″ – heat flux ; ρ – fluid density. INTRODUCTION In...and cyclic paraffins ] and distribution are not. Chromatograms demonstrating RP compositional variability are shown in Fig. 2 alongside aviation

Advanced stability indicating chemometric methods for quantitation of amlodipine and atorvastatin in their quinary mixture with acidic degradation products.

PubMed

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

2016-02-05

Two advanced, accurate and precise chemometric methods are developed for the simultaneous determination of amlodipine besylate (AML) and atorvastatin calcium (ATV) in the presence of their acidic degradation products in tablet dosage forms. The first method was Partial Least Squares (PLS-1) and the second was Artificial Neural Networks (ANN). PLS was compared to ANN models with and without variable selection procedure (genetic algorithm (GA)). For proper analysis, a 5-factor 5-level experimental design was established resulting in 25 mixtures containing different ratios of the interfering species. Fifteen mixtures were used as calibration set and the other ten mixtures were used as validation set to validate the prediction ability of the suggested models. The proposed methods were successfully applied to the analysis of pharmaceutical tablets containing AML and ATV. The methods indicated the ability of the mentioned models to solve the highly overlapped spectra of the quinary mixture, yet using inexpensive and easy to handle instruments like the UV-VIS spectrophotometer. Copyright © 2015 Elsevier B.V. All rights reserved.

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

PubMed

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

2017-07-01

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

Assessment of repeatability of composition of perfumed waters by high-performance liquid chromatography combined with numerical data analysis based on cluster analysis (HPLC UV/VIS - CA).

PubMed

Ruzik, L; Obarski, N; Papierz, A; Mojski, M

2015-06-01

High-performance liquid chromatography (HPLC) with UV/VIS spectrophotometric detection combined with the chemometric method of cluster analysis (CA) was used for the assessment of repeatability of composition of nine types of perfumed waters. In addition, the chromatographic method of separating components of the perfume waters under analysis was subjected to an optimization procedure. The chromatograms thus obtained were used as sources of data for the chemometric method of cluster analysis (CA). The result was a classification of a set comprising 39 perfumed water samples with a similar composition at a specified level of probability (level of agglomeration). A comparison of the classification with the manufacturer's declarations reveals a good degree of consistency and demonstrates similarity between samples in different classes. A combination of the chromatographic method with cluster analysis (HPLC UV/VIS - CA) makes it possible to quickly assess the repeatability of composition of perfumed waters at selected levels of probability. © 2014 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Main differences between volatiles of sparkling and base wines accessed through comprehensive two dimensional gas chromatography with time-of-flight mass spectrometric detection and chemometric tools.

PubMed

Welke, Juliane Elisa; Zanus, Mauro; Lazzarotto, Marcelo; Pulgati, Fernando Hepp; Zini, Cláudia Alcaraz

2014-12-01

The main changes in the volatile profile of base wines and their corresponding sparkling wines produced by traditional method were evaluated and investigated for the first time using headspace solid-phase microextraction combined with comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry detection (GC×GC/TOFMS) and chemometric tools. Fisher ratios helped to find the 119 analytes that were responsible for the main differences between base and sparkling wines and principal component analysis explained 93.1% of the total variance related to the selected 78 compounds. It was also possible to observe five subclusters in base wines and four subclusters in sparkling wines samples through hierarchical cluster analysis, which seemed to have an organised distribution according to the regions where the wines came from. Twenty of the most important volatile compounds co-eluted with other components and separation of some of them was possible due to GC×GC/TOFMS performance. Copyright © 2014. Published by Elsevier Ltd.

Rapid discrimination of pork in Halal and non-Halal Chinese ham sausages by Fourier transform infrared (FTIR) spectroscopy and chemometrics.

PubMed

Xu, L; Cai, C B; Cui, H F; Ye, Z H; Yu, X P

2012-12-01

Rapid discrimination of pork in Halal and non-Halal Chinese ham sausages was developed by Fourier transform infrared (FTIR) spectrometry combined with chemometrics. Transmittance spectra ranging from 400 to 4000 cm⁻¹ of 73 Halal and 78 non-Halal Chinese ham sausages were measured. Sample preparation involved finely grinding of samples and formation of KBr disks (under 10 MPa for 5 min). The influence of data preprocessing methods including smoothing, taking derivatives and standard normal variate (SNV) on partial least squares discriminant analysis (PLSDA) and least squares support vector machine (LS-SVM) was investigated. The results indicate removal of spectral background and baseline plays an important role in discrimination. Taking derivatives, SNV can improve classification accuracy and reduce the complexity of PLSDA. Possibly due to the loss of detailed high-frequency spectral information, smoothing degrades the model performance. For the best models, the sensitivity and specificity was 0.913 and 0.929 for PLSDA with SNV spectra, 0.957 and 0.929 for LS-SVM with second derivative spectra, respectively. Copyright © 2012 Elsevier Ltd. All rights reserved.

Application of neural networks with novel independent component analysis methodologies to a Prussian blue modified glassy carbon electrode array.

PubMed

Wang, Liang; Yang, Die; Fang, Cheng; Chen, Zuliang; Lesniewski, Peter J; Mallavarapu, Megharaj; Naidu, Ravendra

2015-01-01

Sodium potassium absorption ratio (SPAR) is an important measure of agricultural water quality, wherein four exchangeable cations (K(+), Na(+), Ca(2+) and Mg(2+)) should be simultaneously determined. An ISE-array is suitable for this application because its simplicity, rapid response characteristics and lower cost. However, cross-interferences caused by the poor selectivity of ISEs need to be overcome using multivariate chemometric methods. In this paper, a solid contact ISE array, based on a Prussian blue modified glassy carbon electrode (PB-GCE), was applied with a novel chemometric strategy. One of the most popular independent component analysis (ICA) methods, the fast fixed-point algorithm for ICA (fastICA), was implemented by the genetic algorithm (geneticICA) to avoid the local maxima problem commonly observed with fastICA. This geneticICA can be implemented as a data preprocessing method to improve the prediction accuracy of the Back-propagation neural network (BPNN). The ISE array system was validated using 20 real irrigation water samples from South Australia, and acceptable prediction accuracies were obtained. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed

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

2013-11-01

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

Indonesian palm civet coffee discrimination using UV-visible spectroscopy and several chemometrics methods

NASA Astrophysics Data System (ADS)

Yulia, M.; Suhandy, D.

2017-05-01

Indonesian palm civet coffee or kopi luwak (Indonesian words for coffee and palm civet) is well known as the world’s priciest and rarest coffee. To protect the authenticity of luwak coffee and protect consumer from luwak coffee adulteration, it is very important to develop a simple and inexpensive method to discriminate between civet and non-civet coffee. The discrimination between civet and non-civet coffee in ground roasted (powder) samples is very challenging since it is very difficult to distinguish between the two by using conventional method. In this research, the use of UV-Visible spectra combined with two chemometric methods, SIMCA and PLS-DA, was evaluated to discriminate civet and non-civet ground coffee samples. The spectral data of civet and non-civet coffee were acquired using UV-Vis spectrometer (Genesys™ 10S UV-Vis, Thermo Scientific, USA). The result shows that using both supervised discrimination methods: SIMCA and PLS-DA, all samples were correctly classified into their corresponding classes with 100% rate for accuracy, sensitivity and specificity, respectively.

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

PubMed

Liao, Lifu; Yang, Jing; Yuan, Jintao

2007-05-15

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

Rapid indentification of organic contaminants in pretreated waste water using AOTF near-IR spectometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eilert, A.J.; Danley, W.J.; Wang, Xiaolu

1995-12-31

A near-infrared analyzer utilizing state-of-the-art acousto-optic tunable filter (AOTF) spectrometry with digital wavelength control and high D* extended-range INGaAs TE-cooled detector provides excellent wavelength repeatability (better than 0.02 nm) and very high signal-to-noise ration. Because the AOTF dispersive element is completely solid-state (no-moving parts), as is the entire spectrometer, the instrument is small, rugged and very reliable. Using this spectrometer, methods employing chemometrics have been developed and applied to measure organic contaminants such as gasoline and a variety of jet fuels in water. Qualitative identification of contaminants was achieved with discriminant analysis software developed specifically for this task. Both themore » technique of grouping sample spectra into specific clusters based of Mahalanobis distances and that of matching each spectrum with the most representative member of the appropriate group of calibration spectra were used to identify contaminants. After initial classification, appropriate qualitative chemometric calibrations may be applied to more accurately assess the level of contamination. The instrument will be used to evaluate ground water supplies.« less

Portable visible and near-infrared spectrophotometer for triglyceride measurements.

PubMed

Kobayashi, Takanori; Kato, Yukiko Hakariya; Tsukamoto, Megumi; Ikuta, Kazuyoshi; Sakudo, Akikazu

2009-01-01

An affordable and portable machine is required for the practical use of visible and near-infrared (Vis-NIR) spectroscopy. A portable fruit tester comprising a Vis-NIR spectrophotometer was modified for use in the transmittance mode and employed to quantify triglyceride levels in serum in combination with a chemometric analysis. Transmittance spectra collected in the 600- to 1100-nm region were subjected to a partial least-squares regression analysis and leave-out cross-validation to develop a chemometrics model for predicting triglyceride concentrations in serum. The model yielded a coefficient of determination in cross-validation (R2VAL) of 0.7831 with a standard error of cross-validation (SECV) of 43.68 mg/dl. The detection limit of the model was 148.79 mg/dl. Furthermore, masked samples predicted by the model yielded a coefficient of determination in prediction (R2PRED) of 0.6856 with a standard error of prediction (SEP) and detection limit of 61.54 and 159.38 mg/dl, respectively. The portable Vis-NIR spectrophotometer may prove convenient for the measurement of triglyceride concentrations in serum, although before practical use there remain obstacles, which are discussed.

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

PubMed

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

2017-01-15

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

Classification and identification of Rhodobryum roseum Limpr. and its adulterants based on fourier-transform infrared spectroscopy (FTIR) and chemometrics.

PubMed

Cao, Zhen; Wang, Zhenjie; Shang, Zhonglin; Zhao, Jiancheng

2017-01-01

Fourier-transform infrared spectroscopy (FTIR) with the attenuated total reflectance technique was used to identify Rhodobryum roseum from its four adulterants. The FTIR spectra of six samples in the range from 4000 cm-1 to 600 cm-1 were obtained. The second-derivative transformation test was used to identify the small and nearby absorption peaks. A cluster analysis was performed to classify the spectra in a dendrogram based on the spectral similarity. Principal component analysis (PCA) was used to classify the species of six moss samples. A cluster analysis with PCA was used to identify different genera. However, some species of the same genus exhibited highly similar chemical components and FTIR spectra. Fourier self-deconvolution and discrete wavelet transform (DWT) were used to enhance the differences among the species with similar chemical components and FTIR spectra. Three scales were selected as the feature-extracting space in the DWT domain. The results show that FTIR spectroscopy with chemometrics is suitable for identifying Rhodobryum roseum and its adulterants.

Preparation and Physical Characterization of a Diclofenac-Ranitidine Co-precipitate for Improving the Dissolution of Diclofenac.

PubMed

Gaitano, Robertino O; Calvo, Natalia L; Narda, Griselda E; Kaufman, Teodoro S; Maggio, Rubén M; Brusau, Elena V

2016-03-01

Mixing aqueous solutions of sodium diclofenac (DIC-Na) and ranitidine hydrochloride (RAN·HCl) afforded an off-white solid (DIC-RAN) that was investigated from the microscopic, thermal, diffractometric, spectroscopic, and functional (chemometrics-assisted dissolution) points of view. The solid has a 2:1 (DIC:RAN) molar ratio according to (1)H nuclear magnetic resonance spectroscopy. It is thermally stable, displaying a broad endothermic signal centered at 105°C in the thermogram, and its characteristic reflections in the powder X-ray diffractogram remained unchanged after a 3-month aging period. Scanning electron microscopy micrographs uncovered its morphology, whereas the spectral data suggested an interaction between the carboxylic acid of DIC and the alkyldimethylamino moiety of RAN. The dissolution of DIC-RAN was monitored at different pH values by an ultraviolet/chemometrics procedure, being complete within 5 min at pH 6.8. This compares favorably with the dissolution of a DIC-Na sample of the same particle size. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Discrimination of lymphoma using laser-induced breakdown spectroscopy conducted on whole blood samples

PubMed Central

Chen, Xue; Li, Xiaohui; Yang, Sibo; Yu, Xin; Liu, Aichun

2018-01-01

Lymphoma is a significant cancer that affects the human lymphatic and hematopoietic systems. In this work, discrimination of lymphoma using laser-induced breakdown spectroscopy (LIBS) conducted on whole blood samples is presented. The whole blood samples collected from lymphoma patients and healthy controls are deposited onto standard quantitative filter papers and ablated with a 1064 nm Q-switched Nd:YAG laser. 16 atomic and ionic emission lines of calcium (Ca), iron (Fe), magnesium (Mg), potassium (K) and sodium (Na) are selected to discriminate the cancer disease. Chemometric methods, including principal component analysis (PCA), linear discriminant analysis (LDA) classification, and k nearest neighbor (kNN) classification are used to build the discrimination models. Both LDA and kNN models have achieved very good discrimination performances for lymphoma, with an accuracy of over 99.7%, a sensitivity of over 0.996, and a specificity of over 0.997. These results demonstrate that the whole-blood-based LIBS technique in combination with chemometric methods can serve as a fast, less invasive, and accurate method for detection and discrimination of human malignancies. PMID:29541503

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

NASA Astrophysics Data System (ADS)

Zimányi, László; Khoroshyy, Petro; Mair, Thomas

2010-06-01

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

Exploratory Study of Basement Moisture During Operation of Active Soil Depressurization Radon Control Systems

EPA Pesticide Factsheets

As part of an exploratory study, three houses were monitored for moisture indicators, radon levels, building operations, and other environmental parameters while ASD systems were cycled on and off. December 6, 2007, Revised 3/10/08.

A Restorative Justice Approach to Empathy Development in Sex Offenders: An Exploratory Study

ERIC Educational Resources Information Center

Roseman, Christopher P.; Ritchie, Martin; Laux, John M.

2009-01-01

The authors describe an exploratory study in sex offender treatment using a restorative justice approach to examine the shame, guilt, and empathy development of convicted sexual offenders. Implications for clinical practice and future research are highlighted. (Contains 3 tables.)

Simultaneous determination of hydrocarbon renewable diesel, biodiesel and petroleum diesel contents in diesel fuel blends using near infrared (NIR) spectroscopy and chemometrics.

PubMed

Alves, Julio Cesar Laurentino; Poppi, Ronei Jesus

2013-11-07

Highly polluting fuels based on non-renewable resources such as fossil fuels need to be replaced with potentially less polluting renewable fuels derived from vegetable or animal biomass, these so-called biofuels, are a reality nowadays and many countries have started the challenge of increasing the use of different types of biofuels, such as ethanol and biodiesel (fatty acid alkyl esters), often mixed with petroleum derivatives, such as gasoline and diesel, respectively. The quantitative determination of these fuel blends using simple, fast and low cost methods based on near infrared (NIR) spectroscopy combined with chemometric methods has been reported. However, advanced biofuels based on a mixture of hydrocarbons or a single hydrocarbon molecule, such as farnesane (2,6,10-trimethyldodecane), a hydrocarbon renewable diesel, can also be used in mixtures with biodiesel and petroleum diesel fuel and the use of NIR spectroscopy for the quantitative determination of a ternary fuel blend of these two hydrocarbon-based fuels and biodiesel can be a useful tool for quality control. This work presents a development of an analytical method for the quantitative determination of hydrocarbon renewable diesel (farnesane), biodiesel and petroleum diesel fuel blends using NIR spectroscopy combined with chemometric methods, such as partial least squares (PLS) and support vector machines (SVM). This development leads to a more accurate, simpler, faster and cheaper method when compared to the standard reference method ASTM D6866 and with the main advantage of providing the individual quantification of two different biofuels in a mixture with petroleum diesel fuel. Using the developed PLS model the three fuel blend components were determined simultaneously with values of root mean square error of prediction (RMSEP) of 0.25%, 0.19% and 0.38% for hydrocarbon renewable diesel, biodiesel and petroleum diesel, respectively, the values obtained were in agreement with those suggested by reference methods for the determination of renewable fuels.

Exploratory Study of the HOPE Foundation[C] Courageous Leadership Academy: Summary of Findings

ERIC Educational Resources Information Center

Brown, Seth; Choi, KC; Herman, Becki

2011-01-01

The HOPE Foundation (HOPE) commissioned the American Institutes for Research (AIR) to conduct an exploratory study of the implementation and impact of the Courageous Leadership Academy (CLA). In this report, the authors introduce the school reform model, describe the study methodology, present findings for each of the three research questions…

An Exploratory Study of Listening Practice Relative to Memory Testing and Lecture in Business Administration Courses

ERIC Educational Resources Information Center

Peterson, Robin T.

2007-01-01

This study investigates the combined impact of a memory test and subsequent listening practice in enhancing student listening abilities in collegiate business administration courses. The article reviews relevant literature and describes an exploratory study that was undertaken to compare the effectiveness of this technique with traditional…

Application of Exploratory Structural Equation Modeling to Evaluate the Academic Motivation Scale

ERIC Educational Resources Information Center

Guay, Frédéric; Morin, Alexandre J. S.; Litalien, David; Valois, Pierre; Vallerand, Robert J.

2015-01-01

In this research, the authors examined the construct validity of scores of the Academic Motivation Scale using exploratory structural equation modeling. Study 1 and Study 2 involved 1,416 college students and 4,498 high school students, respectively. First, results of both studies indicated that the factor structure tested with exploratory…

An Exploratory Study of Intrinsic & Extrinsic Motivators and Student Performance in an Auditing Course

ERIC Educational Resources Information Center

Mo, Songtao

2011-01-01

The objective of this study is to investigate the association of intrinsic and extrinsic motivators and student performance. This study performs an exploratory analysis and presents evidence to demonstrate that intrinsic motivators affect the connection between external motivators and student performance. The empirical tests follow the framework…

An Exploratory Multiple Case Study about Using Game-Based Learning in STEM Classrooms

ERIC Educational Resources Information Center

Vu, Phu; Feinstein, Sheryl

2017-01-01

This exploratory multiple case study attempted to examine whether game-based learning activities had any impacts on students' academic performances and behaviors, and what perceptions the teachers had toward implementing games into their classrooms. Data used in this study included 101 students' pre and post-test scores, and four structured…

Technical Communications in Aeronautics: Results of an Exploratory Study. NASA Technical Memorandum 101534, Parts 1 and 2.

ERIC Educational Resources Information Center

Pinelli, Thomas E.; And Others

An exploratory study investigated technical communications in aeronautics by surveying aeronautical engineers and scientists. The study had five specific objectives: to solicit the opinions of aeronautical engineers and scientists regarding the importance of technical communications to their profession; to determine their use and production of…

Situated Analysis of Team Handball Players' Decisions: An Exploratory Study

ERIC Educational Resources Information Center

Lenzen, Benoit; Theunissen, Catherine; Cloes, Marc

2009-01-01

This exploratory study aimed to investigate elements involved in decision making in team handball live situations and to provide coaches and educators with teaching recommendations. The study was positioned within the framework of the situated-action paradigm of which two aspects were of particular interest for this project: (a) the relationship…

Giving Voice to Reluctant Learners: An Exploratory Study

ERIC Educational Resources Information Center

Pringle, Mark T.

2010-01-01

The purpose of this exploratory study is to hear from reluctant learners about their perceptions of their experiences in middle school and the meanings they make from these. This study will give voice to students, a stakeholder group that has been traditionally silent in the literature on K-12 learning and achievement. Capturing the perceptions…

Authentic Reading, Writing, and Discussion: An Exploratory Study of a Pen Pal Project

ERIC Educational Resources Information Center

Gambrell, Linda B.; Hughes, Elizabeth M.; Calvert, Leah; Malloy, Jacquelynn A.; Igo, Brent

2011-01-01

In this exploratory study, reading, writing, and discussion were examined within the context of a pen pal intervention focusing on authentic literacy tasks. The study employed a mixed-method design with a triangulation-convergence model to explore the relationship between authentic literacy tasks and the literacy motivation of elementary students…

Consumer Rights and Accountability in Postsecondary Vocational-Technical Education: An Exploratory Study.

ERIC Educational Resources Information Center

Fitzgerald, Brian; Harmon, Lisa

Beginning in October 1987, Pelavin Associates conducted an exploratory study of consumer rights and accountability in postsecondary vocational-technical (PVT) programs for the U.S. Department of Education. The study focused on how effectively the governance structure--accreditation and federal and state regulation--ensures that consumer rights are…

Comprehension and Recall of Television's Computerized Image: An Exploratory Study.

ERIC Educational Resources Information Center

Metallinos, Nikos; Chartrand, Sylvie

This exploratory study of the effects of the new visual communications media imagery (e.g., video games, digital television, and computer graphics) on the visual perception process is designed to provide a theoretical framework for research, introduce appropriate research instruments for such study, and experiment with the application of biometric…

Linkage between Free Exploratory Movements and Subjective Tactile Ratings.

PubMed

Yokosaka, Takumi; Kuroki, Scinob; Watanabe, Junji; Nishida, Shinya

2017-01-01

We actively move our hands and eyes when exploring the external world and gaining information about object's attributes. Previous studies showing that how we touch might be related to how we felt led us to consider whether we could decode observers' subjective tactile experiences only by analyzing their exploratory movements without explicitly asking how they perceived. However, in those studies, explicit judgment tasks were performed about specific tactile attributes that were prearranged by experimenters. Here, we systematically investigated whether exploratory movements can explain tactile ratings even when participants do not need to judge any tactile attributes. While measuring both hand and eye movements, we asked participants to touch materials freely without judging any specific tactile attributes (free-touch task) or to evaluate one of four tactile attributes (roughness, hardness, slipperiness, and temperature). We found that tactile ratings in the judgment tasks correlated with exploratory movements even in the free-touch task and that eye movements as well as hand movements correlated with tactile ratings. These results might open up the possibility of decoding tactile experiences by exploratory movements.

Impairment of exploratory behavior and spatial memory in adolescent rats in lithium-pilocarpine model of temporal lobe epilepsy.

PubMed

Kalemenev, S V; Zubareva, O E; Frolova, E V; Sizov, V V; Lavrentyeva, V V; Lukomskaya, N Ya; Kim, K Kh; Zaitsev, A V; Magazanik, L G

2015-01-01

Cognitive impairment in six-week -old rats has been studied in the lithium-pilocarpine model of adolescent temporal lobe epilepsy in humans. The pilocarpine-treated rats (n =21) exhibited (a) a decreased exploratory activity in comparison with control rats (n = 20) in the open field (OP) test and (b) a slower extinction of exploratory behavior in repeated OP tests. The Morris Water Maze (MWM) test showed that the effect of training was less pronounced in the pilocarpine-treated rats, which demonstrated disruption of predominantly short-term memory. Therefore, our study has shown that lithium-pilocarpine seizures induce substantial changes in exploratory behavior and spatial memory in adolescent rats. OP and MWM tests can be used in the search of drugs reducing cognitive impairments associated with temporal lobe epilepsy.

Nettle sting of Urtica dioica for joint pain--an exploratory study of this complementary therapy.

PubMed

Randall, C; Meethan, K; Randall, H; Dobbs, F

1999-09-01

This exploratory study aims to explore the present use of the common stinging nettle to treat joint pain. Eighteen self-selected patients using the nettle sting of Urtica dioica were interviewed. Information regarding patients' use of nettle therapy was elicited, in particular mode of application, dosage and effects. All except one respondent were sure that netles had been very helpful and several considered themselves cured. No observed side effects were reported, except a transient urticarial rash. This exploratory study suggests nettle sting is a useful, safe and cheap therapy which needs further study. A randomized controlled trial is planned in collaboration with a rheumatology specialist.

At-Risk Learner Preference in Engineering/Technical Graphics: An Exploratory Study

ERIC Educational Resources Information Center

Ernst, Jeremy V.

2011-01-01

This exploratory study investigated learner preferences of secondary Career and Technical Education (CTE) Engineering/Technical Graphics students using the VARK Questionnaire. The VARK Questionnaire is an instrument that assists in determining students' dominant preferred learning styles, whether visual, aural, reading, or kinesthetic. This study…

Predicting the ethanol potential of wheat straw using near-infrared spectroscopy and chemometrics: The challenge of inherently intercorrelated response functions

DOE PAGES

Rinnan, Asmund; Bruun, Sander; Lindedam, Jane; ...

2017-02-07

Here, the combination of NIR spectroscopy and chemometrics is a powerful correlation method for predicting the chemical constituents in biological matrices, such as the glucose and xylose content of straw. However, difficulties arise when it comes to predicting enzymatic glucose and xylose release potential, which is matrix dependent. Further complications are caused by xylose and glucose release potential being highly intercorrelated. This study emphasizes the importance of understanding the causal relationship between the model and the constituent of interest. It investigates the possibility of using near-infrared spectroscopy to evaluate the ethanol potential of wheat straw by analyzing more than 1000more » samples from different wheat varieties and growth conditions. During the calibration model development, the prime emphasis was to investigate the correlation structure between the two major quality traits for saccharification of wheat straw: glucose and xylose release. The large sample set enabled a versatile and robust calibration model to be developed, showing that the prediction model for xylose release is based on a causal relationship with the NIR spectral data. In contrast, the prediction of glucose release was found to be highly dependent on the intercorrelation with xylose release. If this correlation is broken, the model performance breaks down. A simple method was devised for avoiding this breakdown and can be applied to any large dataset for investigating the causality or lack of causality of a prediction model.« less

Predicting the ethanol potential of wheat straw using near-infrared spectroscopy and chemometrics: The challenge of inherently intercorrelated response functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rinnan, Asmund; Bruun, Sander; Lindedam, Jane

Here, the combination of NIR spectroscopy and chemometrics is a powerful correlation method for predicting the chemical constituents in biological matrices, such as the glucose and xylose content of straw. However, difficulties arise when it comes to predicting enzymatic glucose and xylose release potential, which is matrix dependent. Further complications are caused by xylose and glucose release potential being highly intercorrelated. This study emphasizes the importance of understanding the causal relationship between the model and the constituent of interest. It investigates the possibility of using near-infrared spectroscopy to evaluate the ethanol potential of wheat straw by analyzing more than 1000more » samples from different wheat varieties and growth conditions. During the calibration model development, the prime emphasis was to investigate the correlation structure between the two major quality traits for saccharification of wheat straw: glucose and xylose release. The large sample set enabled a versatile and robust calibration model to be developed, showing that the prediction model for xylose release is based on a causal relationship with the NIR spectral data. In contrast, the prediction of glucose release was found to be highly dependent on the intercorrelation with xylose release. If this correlation is broken, the model performance breaks down. A simple method was devised for avoiding this breakdown and can be applied to any large dataset for investigating the causality or lack of causality of a prediction model.« less

Chemometric analysis of soil pollution data using the Tucker N-way method.

PubMed

Stanimirova, I; Zehl, K; Massart, D L; Vander Heyden, Y; Einax, J W

2006-06-01

N-way methods, particularly the Tucker method, are often the methods of choice when analyzing data sets arranged in three- (or higher) way arrays, which is the case for most environmental data sets. In the future, applying N-way methods will become an increasingly popular way to uncover hidden information in complex data sets. The reason for this is that classical two-way approaches such as principal component analysis are not as good at revealing the complex relationships present in data sets. This study describes in detail the application of a chemometric N-way approach, namely the Tucker method, in order to evaluate the level of pollution in soil from a contaminated site. The analyzed soil data set was five-way in nature. The samples were collected at different depths (way 1) from two locations (way 2) and the levels of thirteen metals (way 3) were analyzed using a four-step-sequential extraction procedure (way 4), allowing detailed information to be obtained about the bioavailability and activity of the different binding forms of the metals. Furthermore, the measurements were performed under two conditions (way 5), inert and non-inert. The preferred Tucker model of definite complexity showed that there was no significant difference in measurements analyzed under inert or non-inert conditions. It also allowed two depth horizons, characterized by different accumulation pathways, to be distinguished, and it allowed the relationships between chemical elements and their biological activities and mobilities in the soil to be described in detail.

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

PubMed

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

2014-12-01

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

An Exploratory Study of Thai University Students' Understanding of World Englishes

ERIC Educational Resources Information Center

Saengboon, Saksit

2015-01-01

This exploratory study investigated the perceptions of Thai university students towards World Englishes (WEs). One hundred and ninety-eight students from three universities in Bangkok were administered a questionnaire inquiring about definitions of WEs, the Kachruvian concentric circles, the concepts of standard and ownership of English, Thai…

Parent Involvement in Children's Education: An Exploratory Study of Urban, Chinese Immigrant Families

ERIC Educational Resources Information Center

Ji, Cheng Shuang; Koblinsky, Sally A.

2009-01-01

This exploratory study examined the involvement of Chinese immigrant parents in children's elementary and secondary education. Participants were 29 low-income, urban parents of public school children working primarily in the hospitality sector. Parents were interviewed about their academic expectations, knowledge of school performance, parent…

Competent Communication in the First College Year: An Exploratory Study

ERIC Educational Resources Information Center

Morreale, Sherwyn; Staley, Constance; Campbell, Tajshen

2015-01-01

First-year students' communication abilities are critical to succeeding in college and interacting professionally with faculty, student affairs staff, and administrators. The purpose of this exploratory study is to better understand how introductory-level college students, particularly those born since 1990, define competent communication in the…

An Exploratory Study: Assessment of Modeled Dioxin Exposure in Ceramic Art Studios (Final Report, 2008)

EPA Science Inventory

EPA announced the availability of the final report, An Exploratory Study: Assessment of Modeled Dioxin Exposure in Ceramic Art Studios. This report investigates the potential dioxin exposure to artists/hobbyists who use ball clay to make pottery and related products. Derm...

Existential Measurement: A Factor Analytic Study of Some Current Psychometric Instruments.

ERIC Educational Resources Information Center

Thauberger, Patrick C.; And Others

1982-01-01

Research in existentialism and ontology has given rise to several psychometric instruments. Used both exploratory and confirmatory principal-factor analyses to study relationships among 16 existential scales. Exploratory factor analysis provided some support of the theory that the avoidance of existential confrontation is a central function of…

Investigating Crickets: Observing Animal Exploratory Behavior

ERIC Educational Resources Information Center

Bowen, G. M.

2008-01-01

For curriculum content-related reasons, inquiry activities can be difficult in classrooms unless the activities are approached in a manner that makes variations among student group findings understandable in the context of the study. Studies of individual animals and plant reactions to stimuli, such as insect exploratory behavior, allow the…

Sustaining Latina Student Organizations: An Exploratory Instrumental Case Study

ERIC Educational Resources Information Center

Castellanos, Michelle

2016-01-01

Utilizing the exploratory case study methodology, the author examines the conditions that support and limit a Latina-based student organization at a predominately White institution of higher education. Seven organizational structures were found to influence the organization's ability to advance its aims, from interviews, documents, observations,…

Disaster Preparedness Information Needs of Individuals Attending an Adult Literacy Center: An Exploratory Study

ERIC Educational Resources Information Center

Friedman, Daniela; Tanwar, Manju; Yoho, Deborah W.; Richter, Jane V. E.

2009-01-01

Being prepared with accurate, credible, and timely information during a disaster can help individuals make informed decisions about taking appropriate actions. Unfortunately, many people have difficulty understanding health and risk-related resources. This exploratory, mixed methods study assessed disaster information seeking behaviors and…

Brief Report: An Exploratory Study of the Diagnostic Reliability for Autism Spectrum Disorder

ERIC Educational Resources Information Center

Taylor, Lauren J.; Eapen, Valsamma; Maybery, Murray; Midford, Sue; Paynter, Jessica; Quarmby, Lyndsay; Smith, Timothy; Williams, Katrina; Whitehouse, Andrew J.

2017-01-01

Previous research shows inconsistency in clinician-assigned diagnoses of Autism Spectrum Disorder (ASD). We conducted an exploratory study that examined the concordance of diagnoses between a multidisciplinary assessment team and a range of independent clinicians throughout Australia. Nine video-taped Autism Diagnostic Observation Schedule (ADOS)…

An Exploratory Study of Student Satisfaction with University Web Page Design

ERIC Educational Resources Information Center

Gundersen, David E.; Ballenger, Joe K.; Crocker, Robert M.; Scifres, Elton L.; Strader, Robert

2013-01-01

This exploratory study evaluates the satisfaction of students with a web-based information system at a medium-sized regional university. The analysis provides a process for simplifying data interpretation in captured student user feedback. Findings indicate that student classifications, as measured by demographic and other factors, determine…

Organic Chemistry Educators' Perspectives on Fundamental Concepts and Misconceptions: An Exploratory Study

ERIC Educational Resources Information Center

Duis, Jennifer M.

2011-01-01

An exploratory study was conducted with 23 organic chemistry educators to discover what general chemistry concepts they typically review, the concepts they believe are fundamental to introductory organic chemistry, the topics students find most difficult in the subject, and the misconceptions they observe in undergraduate organic chemistry…

Emotional Reactions of Students in Field Education: An Exploratory Study

ERIC Educational Resources Information Center

Litvack, Andrea; Mishna, Faye; Bogo, Marion

2010-01-01

An exploratory study using qualitative methodology was undertaken with recent MSW graduates (N=12) from 2 graduate social work programs to identify and describe the students' emotional reactions to experiences in field education. Significant and interrelated themes emerged including the subjective and unique definitions of emotionally charged…

District Capacity and the Implementation of Positive Behavior Interventions and Supports: An Exploratory Study

ERIC Educational Resources Information Center

Blakely, Allison Wright

2017-01-01

The purpose of this study was to examine the relation between "district capacity" as measured by the District Capacity Assessment (DCA) and the "initial, depth, scale," and "sustained" implementation of an evidence-based practice (EBP), Positive Behavior Interventions and Supports (PBIS). This exploratory analysis…

The Temporal Properties of E-Learning: An Exploratory Study of Academics' Conceptions

ERIC Educational Resources Information Center

Martins, Jorge; Nunes, Miguel Baptista

2016-01-01

Purpose: The purpose of this paper is to present the results of an exploratory study that investigates Portuguese academics' conceptions concerning the temporal properties of e-learning, in the context of traditional Higher Education Institutions. Design/methodology/approach: Grounded Theory methodology was used to systematically analyse data…

Vowel Intelligibility in Children with and without Dysarthria: An Exploratory Study

ERIC Educational Resources Information Center

Levy, Erika S.; Leone, Dorothy; Moya-Gale, Gemma; Hsu, Sih-Chiao; Chen, Wenli; Ramig, Lorraine O.

2016-01-01

Children with dysarthria due to cerebral palsy (CP) present with decreased vowel space area and reduced word intelligibility. Although a robust relationship exists between vowel space and word intelligibility, little is known about the intelligibility of vowels in this population. This exploratory study investigated the intelligibility of American…

Teaching Social Skills in a Virtual Environment: An Exploratory Study

ERIC Educational Resources Information Center

Baker, Jason; Parks-Savage, Agatha; Rehfuss, Mark

2009-01-01

This article reports on an exploratory study which examines the use of virtual environment technology as a tool to teach elementary school children social skills. Small group interventions were assessed to determine how the participants were measurably different on 7 different dependent variables: problem behaviors, academic competence,…

An Exploratory Study: Assessment of Modeled Dioxin Exposure in Ceramic Art Studios (External Review Draft)

EPA Science Inventory

EPA has released an external review draft entitled, An Exploratory Study: Assessment of Modeled Dioxin Exposure in Ceramic Art Studios(External Review Draft). The public comment period and the external peer-review workshop are separate processes that provide opportunities ...

The Effectiveness of Course Web Sites in Higher Education: An Exploratory Study.

ERIC Educational Resources Information Center

Comunale, Christie L.; Sexton, Thomas R.; Voss, Diana J. Pedagano

2002-01-01

Describes an exploratory study of the educational effectiveness of course Web sites among undergraduate accounting students and graduate students in business statistics. Measured Web site visit frequency, usefulness of each site feature, and the impacts of Web sites on perceived learning and course performance. (Author/LRW)

An Exploratory Comparative Case Study of Employee Engagement in Christian Higher Education

ERIC Educational Resources Information Center

Daniels, Jessica R.

2016-01-01

Numerous studies have identified a positive correlation between employee engagement and overall organizational performance. However, research on employee engagement specifically within higher education is limited, and even less attention has been focused on engagement within the context of Christian higher education. An exploratory comparative…

Teaching Writing in the Shadow of Standardized Writing Assessment: An Exploratory Study

ERIC Educational Resources Information Center

Brimi, Hunter

2012-01-01

This exploratory study results from interviews with five high school English teachers regarding their writing instruction. The researcher sought to answer these questions: (1) How had the Tennessee Comprehensive Assessment Program's (TCAP) Writing Assessment affected their teaching as gauged by the teachers' statements regarding the assessment,…

Improved chemometric methodologies for the assessment of soil carbon sequestration mechanisms

NASA Astrophysics Data System (ADS)

Jiménez-González, Marco A.; Almendros, Gonzalo; Álvarez, Ana M.; González-Vila, Francisco J.

2016-04-01

The factors involved soil C sequestration, which is reflected in the highly variable content of organic matter in the soils, are not yet well defined. Therefore, their identification is crucial for understanding Earth's biogeochemical cycle and global change. The main objective of this work is to contribute to a better qualitative and quantitative assessment of the mechanisms of organic C sequestration in the soil, using omic approaches not requiring the detailed knowledge of the structure of the material under study. With this purpose, we have carried out a series of chemometric approaches on a set of widely differing soils (35 representative ecosystems). In an exploratory phase, we used multivariate statistical models (e.g., multidimensional scaling, discriminant analysis with automatic backward variable selection…) to analyze arrays of more than 200 independent soil variables (physicochemical, spectroscopic, pyrolytic...) in order to select those factors (descriptors or proxies) that explain most of the total system variance (content and stability of the different C forms). These models showed that the factors determining the stabilization of organic material are greatly dependent on the soil type. In some cases, the molecular structure of organic matter seemed strongly correlated with their resilience, while in other soil types the organo-mineral interactions played a significant bearing on the accumulation of selectively preserved C forms. In any case, it was clear that the factors driving the resilience of organic matter are manifold and not exclusive. Consequently, in a second stage, prediction models of the soil C content and their biodegradability (laboratory incubation experiments) were carried out by massive data processing by partial least squares (PLS) regression of data from Py-GC-MS and Py-MS. In some models, PLS was applied to a matrix of 150 independent variables corresponding to major pyrolysis compounds (peak areas) from the 35 samples of whole soils. The variable importance in the projection (VIP) histogram obtained from this treatment (total C and total mineralization coefficients as dependent variables) illustrated the contribution of the individual compounds to the total inertia of the models (e.g., carbohydrate-derived compounds, methoxyphenols, or specific alkylbenzenes were relevant in explaining the total quality and the biodegradation rates of the organic matter). Further simplified models consisting of direct PLS analysis of the debugged ion matrix calculated by averaging all ions (45 - 250 amu) in the whole chromatographic area in the 5-60 min range (here referred to as 'rebuilt MS spectra' or 'Py-MS spectra' when obtained connecting directly the pyrolyser to the MS detector through suitable interfaces) were carried out. The above three approaches coincided in pointing out that C sequestration behave as an emergent soil property depending on the complexity of its progressive molecular levels. Most of the total variance is explained by specific assemblages of variables, strongly depending on the soil types. On the other hand, chemical biodiversity (e.g., Shannon indices or coefficients from multivariate data models) behaved as a common background in the prediction models including very different soil types. In fact, assessment of chemodiversity of the pyrolytic compound assemblages (or the Py-MS ion data) would represent a valid clue for the assessment of the extent to which the original biomass has been diagenetically reworked into chaotic structures with non-repeatable units, providing a useful proxy to forecast at least a portion of the total variance in the soil organic matter biodegradability.

Vibrational spectroscopy-based chemometrics to map host resistance to sudden oak death

Treesearch

Pierluigi (Enrico) Bonello; Anna O. Conrad; Luis Rodriguez Saona; Brice A. McPherson; David L. Wood

2017-01-01

A strong focus on tree germplasm that can resist threats such as non-native insects and pathogens, or a changing climate, is fundamental for successful conservation efforts. This project is predicated on the fact that genetic resistance is the cornerstone for protecting plants against pathogens and insects in environments conducive to the attacking organisms, a...

Elimination of interference from water in KBr disk FT-IR spectra of solid biomaterials by chemometrics solved with kinetic modeling

USDA-ARS?s Scientific Manuscript database

Infrared analysis of proteins and polysaccharides by the well known KBr disk technique is notoriously frustrated and defeated by absorbed water interference in the important amide and hydroxyl regions of spectra. This interference has too often been overlooked or ignored even when the resulting dist...

Tensor Toolbox for MATLAB v. 3.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kola, Tamara; Bader, Brett W.; Acar Ataman, Evrim NMN

Tensors (also known as multidimensional arrays or N-way arrays) are used in a variety of applications ranging from chemometrics to network analysis. The Tensor Toolbox provides classes for manipulating dense, sparse, and structured tensors using MATLAB's object-oriented features. It also provides algorithms for tensor decomposition and factorization, algorithms for computing tensor eigenvalues, and methods for visualization of results.

THE OPTIMIZATION OF THERMAL OPTICAL ANALYSIS FOR THE MEASUREMENT OF BLACK CARBON IN REGIONAL PM2.5: A CHEMOMETRIC APPROACH REPORT

EPA Science Inventory

In thermal-optical analysis (TOA), particulate organic carbon (OC) as well as black carbon (BC) must be quantified. Both the BC that is native to the filter and instrument-produced OC char are products of incomplete combustion and have similar optical as well as chemical properti...