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Sample records for chemometric analysis discriminacao

  1. 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…

  2. 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…

  3. Chemometric Analysis of Nuclear Magnetic Resonance Spectroscopy Data

    SciTech Connect

    ALAM,TODD M.; ALAM,M. KATHLEEN

    2000-07-20

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

  4. Chemometrics in pharmaceutical analysis: an introduction, review, and future perspectives.

    PubMed

    El-Gindy, Alaa; Hadad, Ghada M

    2012-01-01

    Chemometrics is the application of statistical and mathematical methods to analytical data to permit maximum collection and extraction of useful information. The utility of chemometric techniques as tools enabling multidimensional calibration of selected spectroscopic, electrochemical, and chromatographic methods is demonstrated. Application of this approach mainly for interpretation of UV-Vis and near-IR (NIR) spectra, as well as for data obtained by other instrumental methods, makes identification and quantitative analysis of active substances in complex mixtures possible, especially in the analysis of pharmaceutical preparations present in the market. Such analytical work is carried out by the use of advanced chemical instruments and data processing, which has led to a need for advanced methods to design experiments, calibrate instruments, and analyze the resulting data. The purpose of this review is to describe various chemometric methods in combination with UV-Vis spectrophotometry, NIR spectroscopy, fluorescence spectroscopy, electroanalysis, chromatographic separation, and flow-injection analysis for the analysis of drugs in pharmaceutical preparations. Theoretical and practical aspects are described with pharmaceutical examples of chemometric applications. This review will concentrate on gaining an understanding of how chemometrics can be useful in the modern analytical laboratory. A selection of the most challenging problems faced in pharmaceutical analysis is presented, the potential for chemometrics is considered, and some consequent implications for utilization are discussed. The reader can refer to the citations wherever appropriate.

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

    PubMed

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

    2017-08-03

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

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

    PubMed

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

    2014-10-01

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

  7. Chemometric analysis of Ragusano cheese flavor.

    PubMed

    Carpino, S; Acree, T E; Barbano, D M; Licitra, G; Siebert, K J

    2002-02-27

    Ragusano cheeses were produced in duplicate from milk collected from pasture-fed and total mixed ration (TMR)-fed cattle at four time intervals. The cheeses were subjected to chemical analysis, conventional sensory testing, and gas chromatography-olfactometry (GCO). Data from each type of analysis were examined by principal component and factor analysis and by pattern recognition (SIMCA) to see if sufficient information for classification into pasture-fed and TMR-fed groups was contained therein. The results clearly indicate that there are significant differences in sensory panel and chemical analysis results between the two cheeses. The data were also examined to see if models of sensory responses as a function of analytical or GCO results or both could be constructed with the modeling technique partial least-squares regression (PLS). Strong PLS models of some sensory responses (green and toasted odor; salt, pungent, bitter, and butyric sensations; and smooth consistency) were obtained.

  8. 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

  9. Qualitative analysis using Raman spectroscopy and chemometrics: a comprehensive model system for narcotics analysis.

    PubMed

    O'Connell, Marie-Louise; Ryder, Alan G; Leger, Marc N; Howley, Tom

    2010-10-01

    The rapid, on-site identification of illicit narcotics, such as cocaine, is hindered by the diverse nature of the samples, which can contain a large variety of materials in a wide concentration range. This sample variance has a very strong influence on the analytical methodologies that can be utilized and in general prevents the widespread use of quantitative analysis of illicit narcotics on a routine basis. Raman spectroscopy, coupled with chemometric methods, can be used for in situ qualitative and quantitative analysis of illicit narcotics; however, careful consideration must be given to dealing with the extensive variety of sample types. To assess the efficacy of combining Raman spectroscopy and chemometrics for the identification of a target analyte under real-world conditions, a large-scale model sample system (633 samples) using a target (acetaminophen) mixed with a wide variety of excipients was created. Materials that exhibit problematic factors such as fluorescence, variable Raman scattering intensities, and extensive peak overlap were included to challenge the efficacy of chemometric data preprocessing and classification methods. In contrast to spectral matching analyte identification approaches, we have taken a chemometric classification model-based approach to account for the wide variances in spectral data. The first derivative of the Raman spectra from the fingerprint region (750-1900 cm(-1)) yielded the best classifications. Using a robust segmented cross-validation method, correct classification rates of better than ∼90% could be attained with regression-based classification, compared to ∼35% for SIMCA. This study demonstrates that even with very high degrees of sample variance, as evidenced by dramatic changes in Raman spectra, it is possible to obtain reasonably reliable identification using a combination of Raman spectroscopy and chemometrics. The model sample set can now be used to validate more advanced chemometric or machine learning

  10. Chemometric analysis of the water purification process data.

    PubMed

    Stanimirova, I; Połowniak, M; Skorek, R; Kita, A; John, E; Buhl, F; Walczak, B

    2007-11-15

    The aim of this work was to show usefulness of chemometric analysis in processing of the data describing production of drinking water in the Silesian region of Poland. Water samples have been collected within the period of 1 year and the quality of water was characterized by a number of physical, chemical and microbiological parameters. Principal component analysis (PCA) and STATIS (Structuration des Tableaux A Trois Indices de la Statistique) were employed to obtain the knowledge about the complete water treatment process. PCA makes it possible to uncover seasonal changes influencing the water treatment process. In particular, it was found out that the salt content, hardness and conductivity of water tend to obtain higher levels in winter rather than in summer, and the relatively lower acidity is also to be expected in winter. The sensory quality of water is considerably improved over the consecutive purification steps. Complementary information about the individual technological units of the process is gained with the STATIS approach. The obtained results show that the water produced by the two independent filtering branches of the water plant is of similar quality and the prescribed quality characteristics of drinking water are fulfilled.

  11. 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.

  12. Review of chemometric analysis techniques for comprehensive two dimensional separations data.

    PubMed

    Pierce, Karisa M; Kehimkar, Benjamin; Marney, Luke C; Hoggard, Jamin C; Synovec, Robert E

    2012-09-14

    Comprehensive two-dimensional (2D) separations, such as comprehensive 2D gas chromatography (GC×GC), liquid chromatography (LC×LC), and related instrumental techniques, provide very large and complex data sets. It is often up to the software to assist the analyst in transforming these complex data sets into useful information, and that is precisely where the field of chemometric data analysis plays a pivotal role. Chemometric tools for comprehensive 2D separations are continually being developed and applied as researchers make significant advances in novel state-of-the-art algorithms and software, and as the commercial sector continues to provide user friendly chemometric software. In this review, we build upon previous reviews of this topic, by focusing primarily on advances that have been reported in the past five years. Most of the reports focus on instrumental platforms using GC×GC with either flame ionization detection (FID) or time-of-flight mass spectrometry (TOFMS) detection, or LC×LC with diode array absorbance detection (DAD). The review covers the following general topics: data preprocessing techniques, target analyte techniques, comprehensive nontarget analysis techniques, and software for chemometrics in multidimensional separations.

  13. 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.

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

    PubMed

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

    2017-11-01

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

  15. Detection of cow milk in donkey milk by chemometric procedures on triacylglycerol stereospecific analysis results.

    PubMed

    Cossignani, Lina; Blasi, Francesca; Bosi, Ancilla; D'Arco, Gilda; Maurelli, Silvia; Simonetti, Maria Stella; Damiani, Pietro

    2011-08-01

    Stereospecific analysis is an important tool for the characterization of lipid fraction of food matrices, and also of milk samples. The results of a chemical-enzymatic-chromatographic analytical method were elaborated by chemometric procedures such as linear discriminant analysis (LDA) and artificial neural network (ANN). According to the total composition and intrapositional fatty acid distribution in the triacylglycerol (TAG) backbone, the obtained results were able to characterize pure milk samples and milk mixtures with 1, 3, 5% cow milk added to donkey milk. The resulting score was very satisfactory. Totally correct classified samples were obtained when the TAG stereospecific results of all the considered milk mixtures (donkey-cow) were elaborated by LDA and ANN chemometric procedures.

  16. 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 R2 and RMSEC value was 0.9916499 and 2.1521897, respectively, while the accuracy of all classification models (LDA, SIMCA, and SVM) was 100%. R2 and RMSEC of calibration of FTIR model were 0.8653689 and 8.8958149, respectively, while the accuracy of LDA, SIMCA, and SVM was 86.0%, 91.2%, and 77.3%, respectively. PLS and LDA of NIR models were further used to predict unknown flavonoid content in commercial samples. Using these models, the significance of flavonoid content that has been measured by NIR and UV-Vis spectrophotometry was evaluated with paired samples t-test. The flavonoid content that has been measured with both methods gave no significant difference. PMID:27529051

  17. 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

  18. 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.

  19. Overview of chemometrics

    NASA Astrophysics Data System (ADS)

    Schlager, Kenneth J.; Ruchti, Timothy L.

    1995-04-01

    Chemometrics is a broad field concerned with the application of mathematical and statistical methods to problems in chemistry. Biotronics Technologies has applied chemometrics to demanding chemical applications involving noninvasive medical diagnostic measurement instrumentation using advanced signal processing and calibration techniques. The chemometrics methods have also been extended to quantitative analysis in microbiology. Signal processing transforms data measurements to enhance the extraction of physically significant information. Examples include the Fourier Transform, first and second derivatives, and digital and adaptive filtering. Calibration is the process of relating data measurements to a chemical concentration for the purpose of estimation. Standard methods of calibration include linear regression, multiple-linear regression, partial linear regression, and principal components regression. For more demanding applications, novel techniques involving artificial neural networks, genetic algorithms, and rotated principal components have been developed. This paper summarizes the chemometric experience of Biotronics Technologies including relevant theoretical background.

  20. Bioaerosols chemometric characterization by laser-induced fluorescence: air sample analysis.

    PubMed

    Cabredo, Susana; Parra, Alejandro; Sáenz, Cecilia; Anzano, Jesús

    2009-03-15

    A laser-induced fluorescence (LIF) system was optimized using a solution of Micrococcus luteus in ethanol/water 50% (v/v) to obtain spectra in the gas phase of 46 bioaerosols. Experimental designs such as Plackett-Burman and factorial design were applied. The fluorescence spectra were treated chemometrically by principal component analysis, linear discriminant analysis and hierarchical cluster analysis to classify the microorganisms according to family, morphology and gram. The best results were obtained using LDA. The method was applied to air samples and the LIF results allowed to characterize bioaerosols reliability. The robustness of the technique was demonstrated by the identification of many bacteria.

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

    PubMed

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

    2011-01-01

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

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

    PubMed

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

    2015-04-22

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

  3. 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.

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

    PubMed

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

    2014-07-01

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

  5. Liquid chromatography-mass spectrometry and chemometric analysis of Ricinus communis extracts for cultivar identification.

    PubMed

    Ovenden, Simon P B; Pigott, Eloise J; Rochfort, Simone; Bourne, David J

    2014-01-01

    Seeds of Ricinus communis contain the toxic protein ricin, a 64 kD heterodimeric type II ribosome-inactivating protein that has been used in several high-profile poisoning incidents. The ability to determine which cultivar the toxin was isolated from via an LC-MS method would be of significant use to law enforcement and forensic agencies. To analyse via LC-MS and chemometrics (principal components analysis (PCA), orthogonal partial-least-squares discriminant analysis (OPLS-DA)) extracts of R. communis to identify compounds specific to a particular cultivar. Seeds from eight specimens of six cultivars of R. communis ('carmencita', 'dehradun', 'gibsonii', 'impala', 'sanguineus' and 'zanzibariensis') were extracted using a standard methodology. These extracts were analysed by LC-MS then subjected to chemometric analysis (PCA and OPLS-DA). Identified compounds of importance were subjected to high-resolution Fourier transform (HRFT) MS and MS/MS to elucidate their structures. This analysis identified 17 ions as potential cultivar determinators. Through accurate mass measurement and MS/MS, molecular formulae for 13 ions were determined, including two known and 11 new peptides. Unique ions in extracts of 'carmencita', 'dehradun', 'gibsonii', 'impala' and 'zanzibariensis' were identified that would allow an individual cultivar to be distinguished from other cultivars in this study. Although 'sanguineus' extracts contained no unique compounds, a unique LC-MS profile would allow for cultivar assignment. Copyright © 2014 John Wiley & Sons, Ltd.

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

    PubMed

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

    2015-01-01

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

  7. 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.

  8. Micro-analysis by near-infrared diffuse reflectance spectroscopy with chemometric methods.

    PubMed

    Liu, Yan; Ning, Yu; Cai, Wensheng; Shao, Xueguang

    2013-11-07

    Great attention has been paid to near-infrared diffuse reflectance spectroscopy (NIRDRS) due to its practicability in analyzing real complex samples. However, the application of the technique in micro-analysis is badly restricted by its low sensitivity or high detection limit. In this study, the possibility of achieving the sensitive detection of micro-components using NIRDRS with the help of chemometric methods is studied with two experimental datasets. The results show that a very high sensitivity can be obtained when the noise and the variant background are minimized. Quantitative determination of low concentrations of pesticides and trace Cr(3+) in solutions is achieved by using preconcentration and chemometric approaches to minimize the noise and background. The absolute prediction error of the method can be as low as 7.6 μg for the pesticide and 28.6 μg for Cr(3+). These quantities are equivalent to 76 ng mL(-1) and 286 ng mL(-1) if 100 mL of solution are used for the analysis.

  9. 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.

  10. 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 ...

  11. Maize authentication: quality control methods and multivariate analysis (chemometrics).

    PubMed

    Arvanitoyannis, Ioannis S; Vlachos, Antonios

    2009-06-01

    Maize is one of the most important cereals because of its numerous applications in processed foods where it is the major or minor component. Apart from maize authenticity issues related to cultivar and geographical origin (national and/or international level), there is another important issue related to genetically modified maize. Various objective parameters such as fatty acids, phenolic compounds, pigments, heavy metals were determined in conjunction with subjective (sensory analysis) in order to identify the maize authenticity. However, the implementation of multivariate analysis (principal component analysis, cluster analysis, discriminant analysis, canonical analysis) is of great importance toward reaching valid conclusions on authenticity issues. This review summarized the most important finding of both objective and subjective evaluations of maize in five comprehensive tables in conjunction with the discussion.

  12. 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.

  13. A Fast and Reliable UPLC-PAD Fingerprint Analysis of Chimonanthus salicifolius Combined with Chemometrics Methods.

    PubMed

    Liang, Xianrui; Zhao, Cui; Su, Weike

    2016-08-01

    A novel fingerprinting approach was developed by means of ultra-high-performance liquid chromatography with photodiode array detector (UPLC-PAD) for the quality control of Chimonanthus salicifolius (C. salicifolius). All UPLC analyses were carried out on a Waters Acquity BEH Phenyl column (2.1 × 50 mm, 1.7 μm particle size) at 48°C, with a gradient mobile phase composed of 0.1% aqueous phosphoric acid and acetonitrile at a flow rate of 0.2 mL/min. The method validation results demonstrated the developed method possessing desirable precision [<0.88% relative standard deviation (RSD)], reproducibility (<1.87% RSD), stability (<1.42% RSD) and allowing fingerprint analysis in one chromatographic run within 21 min. The quality assessment was achieved by using chemometrics methods including similarity analysis, hierarchical clustering analysis and principal component analysis. The developed method can be used for further quality control of C. salicifolius.

  14. 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.

  15. Chemometric approach for fast analysis of prometryn in human hair by GC-MS.

    PubMed

    Yu, Weiwei; Cai, Wensheng; Shao, Xueguang

    2013-07-01

    A method for the fast analysis of a specific component in complex samples by GC-MS was developed and used for the quantitative determination of prometryn in hair samples. In this method, the tedious and time-consuming sample pretreatment for purification was avoided, and a short capillary column and fast temperature program were employed to speed up the analysis. Although the measured total ion chromatogram is composed of overlapping peaks with interference and background noise, the signal of prometryn can be extracted by chemometric methods. Window-independent component analysis was used to extract the mass spectrum and a non-negative immune algorithm was employed to obtain the chromatographic profile of the interesting component from the measured data. Due to the complexity of the matrix, a standard addition method was adopted for the quantification. The applicability of the method was validated with spiked samples, and the recoveries were in the range of 99-105%.

  16. Analysis of spreadable cheese by Raman spectroscopy and chemometric tools.

    PubMed

    Oliveira, Kamila de Sá; Callegaro, Layce de Souza; Stephani, Rodrigo; Almeida, Mariana Ramos; de Oliveira, Luiz Fernando Cappa

    2016-03-01

    In this work, FT-Raman spectroscopy was explored to evaluate spreadable cheese samples. A partial least squares discriminant analysis was employed to identify the spreadable cheese samples containing starch. To build the models, two types of samples were used: commercial samples and samples manufactured in local industries. The method of supervised classification PLS-DA was employed to classify the samples as adulterated or without starch. Multivariate regression was performed using the partial least squares method to quantify the starch in the spreadable cheese. The limit of detection obtained for the model was 0.34% (w/w) and the limit of quantification was 1.14% (w/w). The reliability of the models was evaluated by determining the confidence interval, which was calculated using the bootstrap re-sampling technique. The results show that the classification models can be used to complement classical analysis and as screening methods. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Rapid analysis of polysaccharides contents in Glycyrrhiza by near infrared spectroscopy and chemometrics.

    PubMed

    Zhang, Ci-Hai; Yun, Yong-Huan; Fan, Wei; Liang, Yi-Zeng; Yu, Yue; Tang, Wen-Xian

    2015-08-01

    A method for quantitative analysis of the polysaccharides contents in Glycyrrhiza was developed based on near infrared (NIR) spectroscopy, and by adopting the phenol-sulphuric acid method as the reference method. This is the first time to use this method for predicting polysaccharides contents in Glycyrrhiza. To improve the predictive ability (or robustness) of the model, the competitive adaptive reweighted sampling (CARS) mathematical strategy was used for selecting relevance wavelengths. By using the restricted relevance wavelengths, the PLS model was more efficient and parsimonious. The coefficient of determination of prediction (Rp(2)) and the root mean square error of prediction (RMSEP) of the obtained optimum models were 0.9119 and 0.4350 for polysaccharides. The selected relevance wavelengths were also interpreted. It proved that all the wavelengths selected by CARS were related to functional groups of polysaccharide. The overall results show that NIR spectroscopy combined with chemometrics can be efficiently utilised for analysis of polysaccharides contents in Glycyrrhiza.

  18. Chemometrics-based Approach in Analysis of Arnicae flos

    PubMed Central

    Zheleva-Dimitrova, Dimitrina Zh.; Balabanova, Vessela; Gevrenova, Reneta; Doichinova, Irini; Vitkova, Antonina

    2015-01-01

    Introduction: Arnica montana flowers have a long history as herbal medicines for external use on injuries and rheumatic complaints. Objective: To investigate Arnicae flos of cultivated accessions from Bulgaria, Poland, Germany, Finland, and Pharmacy store for phenolic derivatives and sesquiterpene lactones (STLs). Materials and Methods: Samples of Arnica from nine origins were prepared by ultrasound-assisted extraction with 80% methanol for phenolic compounds analysis. Subsequent reverse-phase high-performance liquid chromatography (HPLC) separation of the analytes was performed using gradient elution and ultraviolet detection at 280 and 310 nm (phenolic acids), and 360 nm (flavonoids). Total STLs were determined in chloroform extracts by solid-phase extraction-HPLC at 225 nm. The HPLC generated chromatographic data were analyzed using principal component analysis (PCA) and hierarchical clustering (HC). Results: The highest total amount of phenolic acids was found in the sample from Botanical Garden at Joensuu University, Finland (2.36 mg/g dw). Astragalin, isoquercitrin, and isorhamnetin 3-glucoside were the main flavonol glycosides being present up to 3.37 mg/g (astragalin). Three well-defined clusters were distinguished by PCA and HC. Cluster C1 comprised of the German and Finnish accessions characterized by the highest content of flavonols. Cluster C2 included the Bulgarian and Polish samples presenting a low content of flavonoids. Cluster C3 consisted only of one sample from a pharmacy store. Conclusion: A validated HPLC method for simultaneous determination of phenolic acids, flavonoid glycosides, and aglycones in A. montana flowers was developed. The PCA loading plot showed that quercetin, kaempferol, and isorhamnetin can be used to distinguish different Arnica accessions. SUMMARY A principal component analysis (PCA) on 13 phenolic compounds and total amount of sesquiterpene lactones in Arnicae flos collection tended to cluster the studied 9 accessions into

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

    PubMed

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

    2016-10-01

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

  20. 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.

  1. [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.

  2. Quality Assessment of Ojeok-San, a Traditional Herbal Formula, Using High-Performance Liquid Chromatography Combined with Chemometric Analysis.

    PubMed

    Kim, Jung-Hoon; Seo, Chang-Seob; Kim, Seong-Sil; Shin, Hyeun-Kyoo

    2015-01-01

    Ojeok-san (OJS) is a traditional herbal formula consisting of 17 herbal medicines that has been used to treat various disorders. In this study, quantitative analytical methods were developed using high-performance liquid chromatography equipped with a photodiode array detector to determine 19 marker compounds in OJS preparations, which was then combined with chemometric analysis. The method developed was validated in terms of its precision and accuracy. The intra- and interday precision of the marker compounds were <3.0% of the relative standard deviation (RSD) and the recovery of the marker compounds was 92.74%-104.16% with RSD values <3.0%. The results of our quantitative analysis show that the quantities of the 19 marker compounds varied between a laboratory water extract and commercial OJS granules. The chemometric analysis used, principal component analysis (PCA) and hierarchical clustering analysis (HCA), also showed that the OJS water extract produced using a laboratory method clearly differed from the commercial OJS granules; therefore, an equalized production process is required for quality control of OJS preparations. Our results suggest that the HPLC analytical methods developed are suitable for the quantification and quality assessment of OJS preparations when combined with chemometric analysis involving PCA and HCA.

  3. Quality Assessment of Ojeok-San, a Traditional Herbal Formula, Using High-Performance Liquid Chromatography Combined with Chemometric Analysis

    PubMed Central

    Seo, Chang-Seob; Kim, Seong-Sil; Shin, Hyeun-Kyoo

    2015-01-01

    Ojeok-san (OJS) is a traditional herbal formula consisting of 17 herbal medicines that has been used to treat various disorders. In this study, quantitative analytical methods were developed using high-performance liquid chromatography equipped with a photodiode array detector to determine 19 marker compounds in OJS preparations, which was then combined with chemometric analysis. The method developed was validated in terms of its precision and accuracy. The intra- and interday precision of the marker compounds were <3.0% of the relative standard deviation (RSD) and the recovery of the marker compounds was 92.74%–104.16% with RSD values <3.0%. The results of our quantitative analysis show that the quantities of the 19 marker compounds varied between a laboratory water extract and commercial OJS granules. The chemometric analysis used, principal component analysis (PCA) and hierarchical clustering analysis (HCA), also showed that the OJS water extract produced using a laboratory method clearly differed from the commercial OJS granules; therefore, an equalized production process is required for quality control of OJS preparations. Our results suggest that the HPLC analytical methods developed are suitable for the quantification and quality assessment of OJS preparations when combined with chemometric analysis involving PCA and HCA. PMID:26539304

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

    PubMed

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

    2016-10-21

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

  5. A combined chemometric and quantitative NMR analysis of HIV/AIDS serum discloses metabolic alterations associated with disease status.

    PubMed

    McKnight, Tracy R; Yoshihara, Hikari A I; Sitole, Lungile J; Martin, Jeffery N; Steffens, Francois; Meyer, Debra

    2014-11-01

    Individuals infected with the human immunodeficiency virus (HIV) often suffer from concomitant metabolic complications. Treatment with antiretroviral therapy has also been shown to alter the metabolism of patients. Although chemometric analysis of nuclear magnetic resonance (NMR) spectra of human sera can distinguish normal sera (HIVneg) from HIV-infected sera (HIVpos) and sera from HIV-infected patients on antiretroviral therapy (ART), quantitative analysis of the discriminating metabolites and their relationship to disease status has yet to be determined. The objectives of the study were to analyze NMR spectra of HIVneg, HIVpos, and ART serum samples with a combination of chemometric and quantitative methods and to compare the NMR data with disease status as measured by viral load and CD4 count. High-resolution magic angle spinning (HRMAS) NMR spectroscopy was performed on HIVneg (N = 10), HIVpos (N = 10), and ART (N = 10) serum samples. Chemometric linear discriminant analysis classified the three groups of spectra with 100% accuracy. Concentrations of 12 metabolites were determined with a semi-parametric metabolite quantification method named high-resolution quantum estimation (HR-QUEST). CD4 count was directly associated with alanine (p = 0.008), and inversely correlated with both glutamine (p = 0.017) and glucose (p = 0.022) concentrations. A multivariate linear model using alanine, glutamine and glucose as covariates demonstrated an association with CD4 count (p = 0.038). The combined chemometric and quantitative analysis of the data disclosed previously unknown associations between specific metabolites and disease status. The observed associations with CD4 count are consistent with metabolic disorders that are commonly seen in HIV-infected patients.

  6. 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.

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

    PubMed

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

    2012-01-01

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

  8. [Fingerprint analysis of Resina Draconis from different manufactuers by UPLC coupled with chemometrics].

    PubMed

    Qin, Jian-ping; Li, Jia-chun; Wu, Jian-xiong; Wu, Su-su; Huang, Wen-zhe; Wang, Zhen-zhong; Xiao, Wei

    2015-03-01

    This study is to establish an UPLC fingerprint of Resina Draconis from different manufacturers, which can provide a comprehensive evaluation for its quality control. The analysis was performed on a Phenomenex Kinetex 2.6 μ C18 100A column by agradientelution program with acetonitrile-water as mobile phase at a flow rate of 1.7 mL x min(-1). The column temperature was 40 degrees C and the detection wavelengthwas 280 nm. The fingerprints of 18 batches of Draconis Resina were further evaluated by chemometrics methods including similarity analysis (SA), hierarchical clustering analysis (HCA) and principal component analysis (PCA). As a result, there were 15 common peaks, 13 of which had been identified by LC-Q-TOF MS, and the similarity degrees of 15 batches of the samples was more than 0.9, and the samples were divided into 4 clusters by their quality difference. The method is reproducible, simple and reliablethat it can be used for quality control and evaluation of Resina Draconis from different manufacturers.

  9. 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.

  10. 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

  11. Quantitative and fingerprinting analysis of Pogostemon cablin based on GC-FID combined with chemometrics.

    PubMed

    Yang, Yinhui; Kong, Weijun; Feng, Huanhuan; Dou, Xiaowen; Zhao, Lianhua; Xiao, Qiang; Yang, Meihua

    2016-03-20

    In this study, a simple, sensitive and reliable gas chromatography-flame ionization detection (GC-FID) method is established for quantitative chemical fingerprinting of essential oils from Pogostemon cablin. Oil samples are prepared by hydrodistillation, with yields ranging from 0.73% to 2.02%. The two main components of the oil, patchouli alcohol and pogostone, were detected simultaneously in 36 samples and were found to have average contents of 43.07% and 7.84%, respectively. The method was validated in terms of linearity, sensitivity, precision, stability, and accuracy. All calibration curves showed excellent linearity (r(2)>0.9992) within the test ranges, and the relative standard deviation (RSD) values for intra- and inter-day precision were less than 1.5%, indicating a high degree of precision. The GC-FID chemical fingerprints of the 36 samples were established using 12 common peaks which account for over 90% of the total peak area. Chemometric techniques, including similarity analysis and hierarchical cluster analysis, were also employed to explore the similarities and outstanding consistencies among different P. cablin oil samples. The results demonstrate that chromatographic fingerprinting and quantitative analysis can be achieved simultaneously when evaluating quality and authenticating samples of P. cablin.

  12. 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.

  13. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  16. 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.

  17. 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.

  18. Chemometric analysis of cow dung ash as an adsorbent for purifying biodiesel from waste cooking oil.

    PubMed

    Avinash, A; Murugesan, A

    2017-08-25

    Taraditionally, the water-soluble contaminants of biodiesel are treated by water wash method. However, water wash method ends up in an aqueous effluent, which might then cause a harmful environmental impact. As a consequence, waterless purification of biodiesel has triggered primary interest in biodiesel manufacturing process. To address this issue, an endeavour has been made in this work to investigate the waterless purification of biodiesel from waste cooking oil using cow dung ash at different concentration of 1, 2, 3 and 4 wt/wt %. The optimum concentration of cow dung ash for biodiesel purification was found through chemometric analysis by comparing the Fourier transform infrared transmission (FTIR) spectral characteristics of cow dung ash with the water treated FTIR. It was observed from the experimental study that 1 wt/wt % of cow dung ash exhibited similar structural characteristics as that of traditional water treated method of biodiesel purification. Therefore, bio-waste cow dung ash is an effective adsorbent in purifying biodiesel analogous to traditional water washing technology.

  19. Chemometric analysis of femtosecond transient absorption spectroscopy data: Study of the photochromism of anils

    NASA Astrophysics Data System (ADS)

    Ruckebusch, Cyril; Mouton, Nicolas; Gladytz, Thomas; Rendelmann, Anika; Buntinx, Guy; Sliwa, Michel

    2010-06-01

    Chemometric methods are applied for the purpose of extracting relevant information from transient absorption spectroscopy data probing the photochromism of molecules from the family of salicylidene aniline. The process consists of an ultrafast excited state intramolecular proton transfer occurring from an enol form which is then followed by a cis-trans isomerization to finally reach a trans-keto photo-product. This work focuses on the potential of combining multivariate curve resolution for modeling pure profiles and two dimensional correlation spectroscopy data analysis for providing information on the dynamics of spectral features. The results obtained for one derivative of salicylidene aniline provide information regarding the number of species created after the proton transfer and characterization of their absorption spectra and their kinetics in the picosecond time scale. The spectral resolution of two cis-keto* forms is proposed for the first time. It is also found that both cis-keto* species are involved in the formation of the trans-keto photo-product. The main precursor of the trans-keto photo-product is the cis-keto* form which has the shortest characteristic time.

  20. ATR-FTIR spectroscopy coupled with chemometric analysis discriminates normal, borderline and malignant ovarian tissue: classifying subtypes of human cancer.

    PubMed

    Theophilou, Georgios; Lima, Kássio M G; Martin-Hirsch, Pierre L; Stringfellow, Helen F; Martin, Francis L

    2016-01-21

    Surgical management of ovarian tumours largely depends on their histo-pathological diagnosis. Currently, screening for ovarian malignancy with tumour markers in conjunction with radiological investigations has a low specificity for discriminating benign from malignant tumours. Also, pre-operative biopsy of ovarian masses increases the risk of intra-peritoneal dissemination of malignancy. Intra-operative frozen section, although sufficiently accurate in differentiating tumours according to their histological type, increases operation times. This results in increased surgery-related risks to the patient and additional burden to resource allocation. We set out to determine whether attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy, combined with chemometric analysis can be applied to discriminate between normal, borderline and malignant ovarian tumours and classify ovarian carcinoma subtypes according to the unique spectral signatures of their molecular composition. Formalin-fixed, paraffin-embedded ovarian tissue blocks were de-waxed, mounted on Low-E slides and desiccated before being analysed using ATR-FTIR spectroscopy. Chemometric analysis in the form of principal component analysis (PCA), successive projection algorithm (SPA) and genetic algorithm (GA), followed by linear discriminant analysis (LDA) of the obtained spectra revealed clear segregation between benign versus borderline versus malignant tumours as well as segregation between different histological tumour subtypes, when these approaches are used in combination. ATR-FTIR spectroscopy coupled with chemometric analysis has the potential to provide a novel diagnostic approach in the accurate diagnosis of ovarian tumours assisting surgical decision making to avoid under-treatment or over-treatment, with minimal impact to the patient.

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

    PubMed

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

    2016-09-01

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

  2. Chemometric Analysis of Some Biologically Active Groups of Drugs on the Basis Chromatographic and Molecular Modeling Data.

    PubMed

    Stasiak, Jolanta; Koba, Marcin; Baczek, Tomasz; Bucinski, Adam

    2015-01-01

    In this work, three different groups of drugs such as 12 analgesic drugs, 11 cardiovascular system drugs and 36 "other" compounds, respectively, were analyzed with cluster analysis (CA), principal component analysis (PCA) and factor analysis (FA) methods. All chemometric analysis were based on the chromatographic parameters (logk and logk(w)) determined by means of high-performance liquid chromatography (HPLC) and also by molecular modeling descriptors calculated using various computer programs (HyperChem, Dragon, and the VCCLAB). The clustering of compounds were obtained by CA (using various algorithm as e.g. Ward method or unweighted pair-group method using arithmetic averages as well as Euclidean or Manhattan distance), and allowed to build dendrograms linked drugs with similar physicochemical and pharmacological properties were discussed. Moreover, the analysis performed for analyzed groups of compounds with the use of FA or PCA methods indicated that almost all information reached in input chromatographic parameters as well as in molecular modeling descriptors can be explained by first two factors. Additionally, all analyzed drugs were clustered according to their chemical structure and pharmacological activity. Summarized, the performed classification analysis of studied drugs was focused on similarities and differences in methods being used for chemometric analysis as well as focused abilities to drugs classification (clustering) according to their molecular structures and pharmacological activity performed on the basis of chromatographic experimental and molecular modeling data. Thus, the most important application of statistically important molecular descriptors taken from QSRR models to classification analysis allow detailed biological (pharmacological) classification of analyzed drugs.

  3. Untargeted detection and quantitative analysis of poplar balata (PB) in Chinese propolis by FT-NIR spectroscopy and chemometrics.

    PubMed

    Xu, Lu; Yan, Si-Min; Cai, Chen-Bo; Yu, Xiao-Ping

    2013-12-15

    This paper investigates the feasibility of using FT-NIR spectroscopy and chemometrics for rapid analysis of poplar balata (PB) in Chinese propolis. Because practical adulterations usually involve addition of certain known active components, together with commercial PB, the commonly targeted analysis methods are insufficient to identify PB-adulterated propolis. Untargeted analysis of PB was performed by developing class models of pure propolis using one-class partial least squares (OCPLS). Quantitative analysis of PB was performed using partial least squares regression (PLSR). For untargeted analysis, the most accurate OCPLS model was obtained with SNV spectra with sensitivity 0.960 and specificity 0.941. OCPLS could detect adulterations with 2% (w/w) or more PB. For quantitative analysis, the root mean squared error of prediction (RMSEP) value of PB was 0.902 (w/w, %) with SNV-PLS. FT-NIR spectrometry and chemometrics demonstrate potential for rapid analysis of PB adulterations in Chinese propolis. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. Analysis of Volatile Compounds by Advanced Analytical Techniques and Multivariate Chemometrics.

    PubMed

    Lubes, Giuseppe; Goodarzi, Mohammad

    2017-05-10

    Smelling is one of the five senses, which plays an important role in our everyday lives. Volatile compounds are, for example, characteristics of food where some of them can be perceivable by humans because of their aroma. They have a great influence on the decision making of consumers when they choose to use a product or not. In the case where a product has an offensive and strong aroma, many consumers might not appreciate it. On the contrary, soft and fresh natural aromas definitely increase the acceptance of a given product. These properties can drastically influence the economy; thus, it has been of great importance to manufacturers that the aroma of their food product is characterized by analytical means to provide a basis for further optimization processes. A lot of research has been devoted to this domain in order to link the quality of, e.g., a food to its aroma. By knowing the aromatic profile of a food, one can understand the nature of a given product leading to developing new products, which are more acceptable by consumers. There are two ways to analyze volatiles: one is to use human senses and/or sensory instruments, and the other is based on advanced analytical techniques. This work focuses on the latter. Although requirements are simple, low-cost technology is an attractive research target in this domain; most of the data are generated with very high-resolution analytical instruments. Such data gathered based on different analytical instruments normally have broad, overlapping sensitivity profiles and require substantial data analysis. In this review, we have addressed not only the question of the application of chemometrics for aroma analysis but also of the use of different analytical instruments in this field, highlighting the research needed for future focus.

  5. 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...

  6. Combined cluster and discriminant analysis: An efficient chemometric approach in diesel fuel characterization.

    PubMed

    Novák, Márton; Palya, Dóra; Bodai, Zsolt; Nyiri, Zoltán; Magyar, Norbert; Kovács, József; Eke, Zsuzsanna

    2017-01-01

    Combined cluster and discriminant analysis (CCDA) as a chemometric tool in compound specific isotope analysis of diesel fuels was studied. The stable carbon isotope ratios (δ(13)C) of n-alkanes in diesel fuel can be used to characterize or differentiate diesels originating from different sources. We investigated 25 diesel fuel samples representing 20 different brands. The samples were collected from 25 different service stations in 11 European countries over a 2 year period. The n-alkane fraction of diesel fuels was separated using solid-state urea clathrate formation combined with silica gel fractionation. The stable carbon isotope ratios of C10-C24 n-alkanes were measured with gas chromatography-isotope ratio mass spectrometry (GC-IRMS) using perdeuterated n-alkanes as internal standards. Beside the 25 samples one additional diesel fuel was prepared and measured three times to get totally homogenous samples in order to test the performance of our analytical and statistical routine. Stable isotope ratio data were evaluated with hierarchical cluster analysis (HCA), principal component analysis (PCA) and CCDA. CCDA combines two multivariate data analysis methods hierarchical cluster analysis with linear discriminant analysis (LDA). The main idea behind CCDA is to compare the goodness of preconceived (based on the sample origins) and random groupings. In CCDA all the samples were compared pairwise. The results for the parallel sample preparations showed that the analytical procedure does not have any significant effect on the δ(13)C values of n-alkanes. The three parallels proved to be totally homogenous with CCDA. HCA and PCA can be useful tools when the examining of the relationship among several samples is in question. However, these two techniques cannot be always decisive on the origin of similar samples. The initial hypothesis that all diesel fuel samples are considered chemically unique was verified by CCDA. The main advantage of CCDA is that it gives an

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

    PubMed

    Ni, Yongnian; Wang, Yong; Kokot, Serge

    2009-04-30

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

  8. Study of the evolution of organic matter during composting of winery and distillery residues by classical and chemometric analysis.

    PubMed

    Martínez-Sabater, Encarnación; Bustamante, María A; Marhuenda-Egea, Frutos C; El-Khattabi, Mounir; Moral, Raúl; Lorenzo, Emilio; Paredes, Concepción; Gálvez, Luis N; Jordá, Juana D

    2009-10-28

    The aim of the present paper is to evaluate the changes of organic matter during the composting process of fresh winery and distillery residues (WDR) by means of classical and chemometric analysis of (13)C cross-polarization magic angle spinning (CPMAS) NMR and Fourier transform infrared (FT-IR) spectra. (13)C NMR spectroscopy displayed a preferential biodegradation of carbohydrates as well as an accumulation of aliphatic chains (cutin- and suberin-like substances). This preferential biodegradation of the organic fractions reduces the landfill emission potential. Although the composition of the input mixture strongly affects the shape of the infrared (IR) spectra, typical bands of components can be selected and used to follow the composting process; that is, changes in the relative absorbances of the band of nitrate (at 1384 cm(-1)) and in the band of carbohydrates (at 1037 cm(-1)) have been observed. In addition, different chemometric tools, such as partial least-squares (PLS), interval PLS (iPLS), backward iPLS (biPLS), and genetic algorithm (GA), have been used to find the most relevant spectral region during the composting process. Chemometric analysis based on the combined and sequential use of iPLS and GA has been revealed as a very powerful tool for the detection in samples of the most relevant spectral region related to the composting process. From the obtained results, it can be concluded that CPMAS (13)C NMR supported by FT-IR could provide information about the evolution and characteristics of the organic matter during the composting process in order to avoid contamination problems after its use as amendment in agriculture or after landfilling.

  9. Screening Brazilian commercial gasoline quality by hydrogen nuclear magnetic resonance spectroscopic fingerprintings and pattern-recognition multivariate chemometric analysis.

    PubMed

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

    2010-06-30

    The identification of gasoline adulteration by organic solvents is not an easy task, because compounds that constitute the solvents are already in gasoline composition. In this work, the combination of Hydrogen Nuclear Magnetic Resonance ((1)H NMR) spectroscopic fingerprintings with pattern-recognition multivariate Soft Independent Modeling of Class Analogy (SIMCA) chemometric analysis provides an original and alternative approach to screening Brazilian commercial gasoline quality in a Monitoring Program for Quality Control of Automotive Fuels. SIMCA was performed on spectroscopic fingerprints to classify the quality of representative commercial gasoline samples selected by Hierarchical Cluster Analysis (HCA) and collected over a 6-month period from different gas stations in the São Paulo state, Brazil. Following optimized the (1)H NMR-SIMCA algorithm, it was possible to correctly classify 92.0% of commercial gasoline samples, which is considered acceptable. The chemometric method is recommended for routine applications in Quality-Control Monitoring Programs, since its measurements are fast and can be easily automated. Also, police laboratories could employ this method for rapid screening analysis to discourage adulteration practices. Copyright 2010 Elsevier B.V. All rights reserved.

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

    PubMed

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

    2015-10-01

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

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

    PubMed

    Carneiro, Renato Lajarim; Poppi, Ronei Jesus

    2014-01-24

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

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

    PubMed

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

    2014-11-28

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

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

    NASA Astrophysics Data System (ADS)

    Carneiro, Renato Lajarim; Poppi, Ronei Jesus

    2014-01-01

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

  14. 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

  15. 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...

  16. Objective data alignment and chemometric analysis of comprehensive two-dimensional separations with run-to-run peak shifting on both dimensions.

    PubMed

    Fraga, C G; Prazen, B J; Synovec, R E

    2001-12-15

    Data from comprehensive two-dimensional (2-D) separation techniques, such as comprehensive 2-D gas chromatography (GC x GC), liquid chromatography/liquid chromatography (LC x LC) and liquid chromatography/ capillary electrophoresis (LC x CE) can be readily analyzed by various chemometric methods to increase chemical analysis capabilities. A retention time alignment, preprocessing method is presented that objectively corrects for run-to-run retention time variations on both separation dimensions of comprehensive 2-D separations prior to application of chemometric data analysis algorithms. The 2-D alignment method corrects for run-to-run shifting of a sample data matrix relative to a standard data matrix on both separation time axes in an independent, stepwise fashion. After 2-D alignment, the generalized rank annihilation method (GRAM) is successfully applied, substantiating the performance of the alignment method. The alignment method should have important implications, because most 2-D separation techniques exhibit, in the context of chemometric data analysis, considerable run-to-run retention time shifting on both dimensions. Even when there are only three to four points/peak, that is, with three to four separations on the second dimension (column 2) per peak width from the first dimension (column 1), the 2-D alignment coupled with GRAM provides dependable analyte peak identification capabilities and adequate quantitative precision for unresolved analyte peaks. Thus, the 2-D alignment algorithm is applicable to lower data density conditions, which broadens the scope of chemometric analysis to high-speed 2-D separations.

  17. Classification of 7 monofloral honey varieties by PTR-ToF-MS direct headspace analysis and chemometrics.

    PubMed

    Schuhfried, Erna; Sánchez del Pulgar, José; Bobba, Marco; Piro, Roberto; Cappellin, Luca; Märk, Tilmann D; Biasioli, Franco

    2016-01-15

    Honey, in particular monofloral varieties, is a valuable commodity. Here, we present proton transfer reaction-time of flight-mass spectrometry, PTR-ToF-MS, coupled to chemometrics as a successful tool in the classification of monofloral honeys, which should serve in fraud protection against mispresentation of the floral origin of honey. We analyzed 7 different honey varieties from citrus, chestnut, sunflower, honeydew, robinia, rhododendron and linden tree, in total 70 different honey samples and a total of 206 measurements. Only subtle differences in the profiles of the volatile organic compounds (VOCs) in the headspace of the different honeys could be found. Nevertheless, it was possible to successfully apply 6 different classification methods with a total correct assignment of 81-99% in the internal validation sets. The most successful methods were stepwise linear discriminant analysis (LDA) and probabilistic neural network (PNN), giving total correct assignments in the external validation sets of 100 and 90%, respectively. Clearly, PTR-ToF-MS/chemometrics is a powerful tool in honey classification.

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

    PubMed

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

    2010-02-10

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

  19. Differentiation and classification of bacteria using vancomycin functionalized silver nanorods array based surface-enhanced Raman spectroscopy and chemometric analysis.

    PubMed

    Wu, Xiaomeng; Huang, Yao-Wen; Park, Bosoon; Tripp, Ralph A; Zhao, Yiping

    2015-07-01

    Twenty seven different bacteria isolates from 12 species were analyzed using intrinsic surface-enhanced Raman scattering (SERS) spectra with recently developed vancomycin coated silver nanorod (VAN AgNR) substrates. The VAN AgNR substrates could generate reproducible SERS spectra of the bacteria with little to no interference from the environment or bacterial by-products as compared to the pristine substrates. By taking advantage of the structural composition of the cellular wall which varies from species to species, the differentiation of bacterial species is demonstrated by using chemometric analyses on those spectra. A second chemometric analysis step within the species cluster is able to differentiate serotypes and strains. The spectral features used for serotype differentiation arises from the surface proteins, while Raman peaks from adenine dominate the differentiation of strains. In addition, due to the intrinsic structural differences in the cell walls, the SERS spectra can distinguish Gram-positive from Gram-negative bacteria with high sensitivity and specificity, as well as 100% accuracy on predicting test samples. Our results provide important insights for using SERS as a bacterial diagnostic tool and further guide the design of a SERS-based detection platform.

  20. 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.

  1. 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.

  2. Chemometric evaluation of the column classification system during the pharmaceutical analysis of lamotrigine and its related substances.

    PubMed

    Szulfer, Jarosław; Plenis, Alina; Bączek, Tomasz

    2013-08-01

    This paper investigates the performance of a column classification system developed at the Katholieke Universiteit Leuven applied to pharmaceutical chromatographic analyses. The liquid chromatography assay of lamotrigine and related compounds was carried out according to the method prescribed in the European Pharmacopoeia monograph, using 28 brands of stationary phases. A ranking was built based on the F KUL value calculated against the selected reference column, then compared with the column test performance established for the stationary phases studied. Therefore, the system suitability test prescribed by the European Pharmacopoeia in order to distinguish between suitable or unsuitable columns for this analysis was evaluated. Moreover, it was examined whether the classes of the stationary phases, determined using test parameter results, contain either suitable or unsuitable supports for the lamotrigine separation. This assay was performed using chemometric a technique, namely factor analysis.

  3. Feasibility of discrimination of dairy creams and cream-like analogues using Raman spectroscopy and chemometric analysis.

    PubMed

    Nedeljkovic, Aleksandar; Tomasevic, Igor; Miocinovic, Jelena; Pudja, Predrag

    2017-10-01

    Dairy cream and its analogues with sunflower oil, coconut oil and palm oil in different milk fat/vegetable fat ratios were prepared and analysed using Raman spectroscopy. The linear discriminant analysis was conducted in order to classify the samples. Samples were well separated and displayed distinguishing linear arrangement along the principal component that expressed the variation in lipid unsaturation. Good separation of sunflower oil and milk fat samples was obtained in contrast to the samples with coconut and palm oil, where the substantial overlapping occurred. The method permitted classifying of the samples in terms of the type of fat used. Calibrated model was extremely sensitive (100%) for dairy cream. The results indicated that it is possible to consider the Raman spectroscopy coupled with chemometric analysis as a rapid way for the detection of dairy cream adulteration with sunflower, coconut and palm oils. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. 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.

  5. Quantitative and chemical fingerprint analysis for the quality evaluation of Isatis indigotica based on ultra-performance liquid chromatography with photodiode array detector combined with chemometric methods.

    PubMed

    Shi, Yan-Hong; Xie, Zhi-Yong; Wang, Rui; Huang, Shan-Jun; Li, Yi-Ming; Wang, Zheng-Tao

    2012-01-01

    A simple and reliable method of ultra-performance liquid chromatography with photodiode array detector (UPLC-PDA) was developed to control the quality of Radix Isatidis (dried root of Isatis indigotica) for chemical fingerprint analysis and quantitative analysis of eight bioactive constituents, including R,S-goitrin, progoitrin, epiprogoitrin, gluconapin, adenosine, uridine, guanosine, and hypoxanthine. In quantitative analysis, the eight components showed good regression (R > 0.9997) within test ranges, and the recovery method ranged from 99.5% to 103.0%. The UPLC fingerprints of the Radix Isatidis samples were compared by performing chemometric procedures, including similarity analysis, hierarchical clustering analysis, and principal component analysis. The chemometric procedures classified Radix Isatidis and its finished products such that all samples could be successfully grouped according to crude herbs, prepared slices, and adulterant Baphicacanthis cusiae Rhizoma et Radix. The combination of quantitative and chromatographic fingerprint analysis can be used for the quality assessment of Radix Isatidis and its finished products.

  6. Chemometric Analysis of Multiple Species of Bacillus Bacterial Endospores Using Infrared Spectroscopy: Discrimination to the Strain Level

    SciTech Connect

    Forrester, Joel B.; Valentine, Nancy B.; Su, Yin-Fong; Johnson, Timothy J.

    2009-09-28

    Previous work using infrared spectroscopy has shown potential for rapid discrimination between bacteria in either their sporulated or vegetative states, as well as between bacteria and other common interferents. For species within one physiological state, however, distinction is far more challenging, and requires chemometrics. In the current study, we have narrowed the field of study by eliminating the confounding issues of vegetative cells as well as growth media and focused on using IR spectra to distinguish between different species all in the sporulated state. Using principal component analysis (PCA) and a classification method based upon similarity measurements, we demonstrate a successful identification rate to the species level of 85% for Bacillus spores grown and sporulated in a glucose broth medium.

  7. Application of terahertz time-domain spectroscopy combined with chemometrics to quantitative analysis of imidacloprid in rice samples

    NASA Astrophysics Data System (ADS)

    Chen, Zewei; Zhang, Zhuoyong; Zhu, Ruohua; Xiang, Yuhong; Yang, Yuping; Harrington, Peter B.

    2015-12-01

    Terahertz time-domain spectroscopy (THz-TDS) has been utilized as an effective tool for quantitative analysis of imidacloprid in rice powder samples. Unlike previous studies, our method for sample preparation was mixing imidacloprid with rice powder instead of polyethylene. Then, terahertz time domain transmission spectra of these mixed samples were measured and the absorption coefficient spectra of the samples with frequency range extending from 0.3 to 1.7 THz were obtained. Asymmetric least square (AsLS) method was utilized to correct the slope baselines that are presented in THz absorption coefficient spectra and improve signal-to-noise ratio of THz spectra. Chemometrics methods, including partial least squares (PLS), support vector regression (SVR), interval partial least squares (iPLS), and backward interval partial least squares (biPLS), were used for quantitative model building and prediction. To achieve a reliable and unbiased estimation, bootstrapped Latin partition was chosen as an approach for statistical cross-validation. Results showed that the mean value of root mean square error of prediction (RMSEP) for PLS (0.5%) is smaller than SVR (0.7%), these two methods were based on the whole absorption coefficient spectra. In addition, PLS performed a better performance with a lower RMSEP (0.3%) based on the THz absorption coefficient spectra after AsLS baseline correction. Alternatively, two methods for variable selection, namely iPLS and biPLS, yielded models with improved predictions. Comparing with conventional PLS and SVR, the mean values of RMSEP were 0.4% (iPLS) and 0.3% (biPLS) by selecting the informative frequency ranges. The results demonstrated that an accurate quantitative analysis of imidacloprid in rice powder samples could be achieved by terahertz time-domain transmission spectroscopy combined with chemometrics. Furthermore, these results demonstrate that THz time-domain spectroscopy can be used for quantitative determinations of other

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

    PubMed

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

    2017-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-09-01

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

  10. Quantitative and chemical fingerprint analysis for quality control of rhizoma Coptidischinensis based on UPLC-PAD combined with chemometrics methods.

    PubMed

    Kong, Wei-Jun; Zhao, Yan-Ling; Xiao, Xiao-He; Jin, Cheng; Li, Zu-Lun

    2009-10-01

    To control the quality of rhizoma Coptidis, a method based on ultra performance liquid chromatography with photodiode array detector (UPLC-PAD) was developed for quantitative analysis of five active alkaloids and chemical fingerprint analysis. In quantitative analysis, the five alkaloids showed good regression (R > 0.9992) within test ranges and the recovery of the method was in the range of 98.4-100.8%. The limit of detections and quantifications for five alkaloids in PAD were less than 0.07 and 0.22 microg/ml, respectively. In order to compare the UPLC fingerprints between rhizoma Coptidis from different origins, the chemometrics procedures, including similarity analysis (SA), hierarchical clustering analysis (HCA), principal component analysis (PCA) were applied to classify the rhizoma Coptidis samples according to their cultivated origins. Consistent results were obtained to show that rhizoma Coptidis samples could be successfully grouped in accordance with the province of origin. Furthermore, five marker constituents were screened out to be the main chemical marker, which could be applied to accurate discrimination and quality control for rhizoma Coptidis by quantitative analysis. This study revealed that UPLC-PAD method was simple, sensitive and reliable for quantitative and chemical fingerprint analysis, moreover, for the quality evaluation and control of rhizoma Coptidis.

  11. Mining in chemometrics.

    PubMed

    Mutihac, Lucia; Mutihac, Radu

    2008-03-31

    Some of the increasingly spread data mining methods in chemometrics like exploratory data analysis, artificial neural networks, pattern recognition, and digital image processing with their highs and lows along with some of their representative applications are discussed. The development of more complex analytical instruments and the need to cope with larger experimental data sets have demanded for new approaches in data analysis, which have led to advanced methods in experimental design and data processing. Hypothesis-driven methods typified by inferential statistics have been gradually complemented or even replaced by data-driven model-free methods that seek for structure in data without reference to the experimental protocol or prior hypotheses. The emphasis is put on the ability of data mining methods to solve multivariate-multiresponse problems on the basis of experimental data and minimal statistical assumptions only, in contrast to classical methods, which require predefined priors to be tested against some null-hypothesis.

  12. Simultaneous Quantitative and Chemical Fingerprint Analysis of Receptaculum Nelumbinis Based on HPLC-DAD-MS Combined with Chemometrics.

    PubMed

    Liu, Haitao; Liu, Jiushi; Zhang, Jin; Qi, Yaodong; Jia, Xiaoguang; Zhang, Bengang; Xiao, Peigen

    2016-04-01

    A rapid and sensitive method based on HPLC-DAD-MS was developed for quantitative analysis of two flavonoids and chemical fingerprint analysis to evaluate the quality of Receptaculum Nelumbinis. The analysis was conducted on a Poroshell 120 C18 column (100 × 4.6 mm, 2.7 μm) with 0.2% formic acid buffer solution and methanol as mobile phases with gradient elution. This method displayed good linearity with R(2) at >0.9999 and limits of quantity <0.37 μg mL(-1). Relative standard deviation values for intra- and interday precision were <0.82 and 1.03%, respectively. The mean recovery of hyperoside was 95.54% and of isoquercitrin was 92.10%. Hyperoside and isoquercitrin were determined simultaneously, and 12 peaks in the chemical fingerprint were identified. The chemometric methods, including similarity analysis, hierarchical clustering analysis and principal component analysis, were applied to distinguish 11 batches of Receptaculum Nelumbinis samples. The above results could validate each other and successfully divide these samples into two groups. Moreover, hyperoside and isoquercitrin could be selected as chemical markers to evaluate the quality of Receptaculum Nelumbinis from different localities. This study demonstrated that the developed method was a powerful and beneficial tool to carry out the quality control of Receptaculum Nelumbinis.

  13. Simultaneous Quantitative and Chemical Fingerprint Analysis of Receptaculum Nelumbinis Based on HPLC–DAD-MS Combined with Chemometrics

    PubMed Central

    Liu, Haitao; Liu, Jiushi; Zhang, Jin; Qi, Yaodong; Jia, Xiaoguang; Zhang, Bengang; Xiao, Peigen

    2016-01-01

    A rapid and sensitive method based on HPLC–DAD-MS was developed for quantitative analysis of two flavonoids and chemical fingerprint analysis to evaluate the quality of Receptaculum Nelumbinis. The analysis was conducted on a Poroshell 120 C18 column (100 × 4.6 mm, 2.7 μm) with 0.2% formic acid buffer solution and methanol as mobile phases with gradient elution. This method displayed good linearity with R2 at >0.9999 and limits of quantity <0.37 μg mL−1. Relative standard deviation values for intra- and interday precision were <0.82 and 1.03%, respectively. The mean recovery of hyperoside was 95.54% and of isoquercitrin was 92.10%. Hyperoside and isoquercitrin were determined simultaneously, and 12 peaks in the chemical fingerprint were identified. The chemometric methods, including similarity analysis, hierarchical clustering analysis and principal component analysis, were applied to distinguish 11 batches of Receptaculum Nelumbinis samples. The above results could validate each other and successfully divide these samples into two groups. Moreover, hyperoside and isoquercitrin could be selected as chemical markers to evaluate the quality of Receptaculum Nelumbinis from different localities. This study demonstrated that the developed method was a powerful and beneficial tool to carry out the quality control of Receptaculum Nelumbinis. PMID:26921895

  14. Nondestructive Total Excitation-Emission Fluorescence Microscopy Combined with Multi-Way Chemometric Analysis for Visually Indistinguishable Single Fiber Discrimination.

    PubMed

    Muñoz de la Peña, Arsenio; Mujumdar, Nirvani; Heider, Emily C; Goicoechea, Hector C; Muñoz de la Peña, David; Campiglia, Andres D

    2016-03-01

    The potential of total excitation-emission fluorescence microscopy combined with multiway chemometric analysis was investigated for the nondestructive forensic analysis of textile fibers. The four pairs of visually indistinguishable fibers consisted of nylon 361 dyed with acid yellow 17 and acid yellow 23, acetate satin 105B dyed with disperse blue 3 and disperse blue 14, polyester 777 dyed with disperse red 1 and disperse red 19, and acrylic 864 dyed with basic green 1 and basic green 4. Excitation emission matrices were recorded with the aid of an inverted microscope and a commercial spectrofluorimeter. The full information content of excitation-emission matrices was processed with the aid of unsupervised parallel factor analysis (PARAFAC), PARAFAC supervised by linear discriminant analysis (LDA), and discriminant unfolded partial least-squares (DU-PLS). The ability of the latter algorithm to classify the four pairs of fibers demonstrates the advantage of using the multidimensionality of fluorescence data formats for the nondestructive analysis of forensic fiber evidence.

  15. 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.

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

    Yang, Yuangui

    2016-01-01

    A fast method was developed by ultra high performance liquid chromatography (UHPLC) for simultaneous determination of polyphyllin I and polyphyllin II. Chemometric analyses including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) based on UHPLC chromatography were used to evaluate 38 batches from six species of Paris. Variable importance of projection was applied to select important peaks. Meanwhile, similarity analysis of UHPLC fingerprint was used to evaluate the sample of Paris polyphylla yunnanensis (PPY) and P. axialis (PA). The results indicated that the total content of saponins in PPY and PA collected from Baoshan City of Yunnan Province above 8.07 mg/g was stronger than that from other areas of the rest of species. PLS-DA showed better performance than PCA with regard to classifying the samples. Retention time during 20–27 minutes of UHPLC was screened as significant peak for distinguishing Paris of different species and original geography. All of PPY and PA with similarity value were more than 0.80. It indicated that quantitative analysis combined with chemometric and similarity analyses could evaluate the different species of Paris effectively and comprehensively. PMID:28097038

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

    PubMed

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

    2011-02-15

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

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

    PubMed

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

    2017-03-14

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

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

    PubMed Central

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

    2017-01-01

    Fragrant agarwood, arguably the costliest wood in the world, is formed by plant-fungal interactions in Aquilaria spp. However, very little is known about this fragrant outcome of interaction. Therefore, mimicking the ancient traditions of agarwood production in Assam (Northeast India), a chemometric assessment of the agarwood-fungus interaction was made by chemical profiling (GC-MS) coupled with statistical analysis (principal component, correlation network analysis) across three platforms, viz. callus, juvenile plants and resinous wood-chips with an associated Fusarium. In the study of callus-fungus interaction, increased accumulation of key aroma compounds such as pentatriacontane {fold change (log2FC) = 3.47)}, 17-pentatriacontene (log2FC = 2.95), tetradecane, 2-methyl- (log2FC = 1.10) over callus and activation of pathways related to defense and secondary metabolism indicated links to aroma production. Study on fungal interactions in juvenile plants and resinous wood-chips indicated formation of terpenoid precursors (e.g. farnesol, geranylgeraniol acetate) and agarwood sesquiterpenes (e.g. agarospirol, γ-eudesmol). Correlation network analysis revealed the possible regulation of sesquiterpene biosynthesis involving squalene. Also a direct role of fungus in aroma (e.g. dodecane, 4-methyl-, tetracosane) was highlighted. Appearance of fragrant molecules unknown to agarwood during interaction featured as a new possibility for future research. PMID:28290512

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

    PubMed

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

    2012-01-11

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

  2. Perfluoroalkylated Substance Effects in Xenopus laevis A6 Kidney Epithelial Cells Determined by ATR-FTIR Spectroscopy and Chemometric Analysis

    PubMed Central

    2016-01-01

    The effects of four perfluoroalkylated substances (PFASs), namely, perfluorobutanesulfonate (PFBS), perfluorooctanoic acid (PFOA), perfluorooctanesulfonate (PFOS), and perfluorononanoic acid (PFNA) were assessed in Xenopus laevis A6 kidney epithelial cells by attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy and chemometric analysis. Principal component analysis–linear discriminant analysis (PCA-LDA) was used to visualize wavenumber-related alterations and ANOVA-simultaneous component analysis (ASCA) allowed data processing considering the underlying experimental design. Both analyses evidenced a higher impact of low-dose PFAS-treatments (10–9 M) on A6 cells forming monolayers, while there was a larger influence of high-dose PFAS-treatments (10–5 M) on A6 cells differentiated into dome structures. The observed dose–response PFAS-induced effects were to some extent related to their cytotoxicity: the EC50-values of most influential PFAS-treatments increased (PFOS < PFNA < PFOA ≪ PFBS), and higher-doses of these chemicals induced a larger impact. Major spectral alterations were mainly attributed to DNA/RNA, secondary protein structure, lipids, and fatty acids. Finally, PFOS and PFOA caused a decrease in A6 cell numbers compared to controls, whereas PFBS and PFNA did not significantly change cell population levels. Overall, this work highlights the ability of PFASs to alter A6 cells, whether forming monolayers or differentiated into dome structures, and the potential of PFOS and PFOA to induce cell death. PMID:27078751

  3. 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.

  4. Chemometric data analysis application to Sparus aurata samples from two offshore farming plants along the Apulian (Italy) coastline.

    PubMed

    Miniero, Roberto; Brambilla, Gianfranco; Chiaravalle, Eugenio; Mangiacotti, Michele; Brizzi, Giulio; Ingelido, Anna Maria; Abate, Vittorio; Cascone, Valeria; Ferri, Fabiola; Iacovella, Nicola; di Domenico, Alessandro

    2011-10-01

    The levels of polychlorodibenzo-p-dioxins (PCDDs), polychlorodibenzofurans (PCDFs), dioxin-like polychlorobiphenyls (DL-PCBs), non-dioxin-like polychlorobiphenyls (NDL-PCBs), and polybromodiphenyl ethers (PBDEs) in fish collected from two marine offshore farming plants were determined. Each sample was constituted by specimens of the same size collected at the same time in four different seasons along the farming year. The feeds given were of industrial origin and the plants were positioned in two different sites respectively exposed to different environmental characteristics. A chemometric approach was applied to interpret the subtle differences observed in fish body burdens across the three chemical groups taken into consideration. The approach consisted in a stepwise multivariate process including a hierarchical cluster analysis (CA) and a linear discriminant analysis (DA). The two main clusters determined by CA were subjected to the canonical DA, backward and forward selection procedures to select the best discriminative functions. A clear temporal and spatial discrimination was found among the samples. Across the three chemical groups, the monthly separation seemed to depend on the growth process and the main exposure was due to the feed. In addition, the two plants differed significantly from the environmental point of view and the most important discriminating group of chemicals were the NDL-PCBs. The approach resulted really effective in discriminating the subtle differences and in individuating suggestions to improve the quality of culturing conditions.

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

    NASA Astrophysics Data System (ADS)

    Kotwa, Ewelina; Lacorte, Silvia; Duarte, Carlos; Tauler, Roma

    2014-09-01

    In this paper we examine 2- and 3-way chemometric methods for analysis of Arctic and Antarctic water samples. Standard CTD (conductivity-temperature-depth) sensor devices were used during two oceanographic expeditions (July 2007 in the Arctic; February 2009 in the Antarctic) covering a total of 174 locations. The output from these devices can be arranged in a 3-way data structure (according to sea water depth, measured variables, and geographical location). We used and compared 2- and 3-way statistical tools including PCA, PARAFAC, PLS, and N-PLS for exploratory analysis, spatial patterns discovery and calibration. Particular importance was given to the correlation and possible prediction of fluorescence from other physical variables. MATLAB's mapping toolbox was used for geo-referencing and visualization of the results. We conclude that: 1) PCA and PARAFAC models were able to describe data in a satisfactory way, but PARAFAC results were easier to interpret; 2) applying a 2-way model to 3-way data raises the risk of flattening the covariance structure of the data and losing information; 3) the distinction between Arctic and Antarctic seas was revealed mostly by PC1, relating to the physico-chemical properties of the water samples; and 4) we confirm the ability to predict fluorescence values from physical measurements when the 3-way data structure is used in N-way PLS regression.

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

    PubMed

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

    2014-05-15

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

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

    PubMed Central

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

    2016-01-01

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

  8. Quantitative analysis of 17 amino acids in tobacco leaves using an amino acid analyzer and chemometric resolution.

    PubMed

    Zeng, Yihang; Cai, Wensheng; Shao, Xueguang

    2015-06-01

    A method was developed for quantifying 17 amino acids in tobacco leaves by using an A300 amino acid analyzer and chemometric resolution. In the method, amino acids were eluted by the buffer solution on an ion-exchange column. After reacting with ninhydrin, the derivatives of amino acids were detected by ultraviolet detection. Most amino acids are separated by the elution program. However, five peaks of the derivatives are still overlapping. A non-negative immune algorithm was employed to extract the profiles of the derivatives from the overlapping signals, and then peak areas were adopted for quantitative analysis of the amino acids. The method was validated by the determination of amino acids in tobacco leaves. The relative standard deviations (n = 5) are all less than 2.54% and the recoveries of the spiked samples are in a range of 94.62-108.21%. The feasibility of the method was proved by analyzing the 17 amino acids in 30 tobacco leaf samples.

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

    PubMed

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

    2014-01-01

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

  10. Chromatographic fingerprint analysis of metabolites in natural and artificial agarwood using gas chromatography-mass spectrometry combined with chemometric methods.

    PubMed

    Gao, Xiaoxia; Xie, Mingrong; Liu, Shaofeng; Guo, Xiaoling; Chen, Xiaoying; Zhong, Zhaojian; Wang, Lei; Zhang, Weimin

    2014-09-15

    Agarwood is a resinous material formed in wounded Aquilaria sinensis in China, which is widely used as an effective traditional Chinese medicine (TCM). This study is aimed to use gas chromatography-mass spectrometry combined with chemometric methods to create reliable criteria for accurate identification of natural agarwood and artificial agarwood, as well as for quality evaluation of artificial agarwood. Natural agarwood and artificial agarwood (stimulated by formic acid or formic acid plus fungal inoculation) were used as standards and controls for the gas chromatography-mass spectrometry (GC-MS) and multivariate analysis. The identification criteria developed were applied to commercial agarwood. A reliable criteria including correlation coefficient of GC-MS fingerprint of natural agarwood and 22 markers of metabolism in natural and artificial agarwood was constructed. Compared with chemically stimulated agarwood (formic acid) and in terms of the 22 markers, artificial agarwood obtained by formic acid stimulation and fungal inoculation were much closer to natural agarwood. The study demonstrates that the chemical components of artificial agarwood obtained by comprehensive stimulated method (formic acid plus fungal inoculation) are much closer to the natural agarwood than those obtained by chemically stimulated method (formic acid), as times goes by. A reliable criteria containing correlation coefficient of GC-MS fingerprint of natural agarwood and 22 metabolism markers can be used to evaluate the quality of the agarwood. As an application case, three samples were identified as natural agarwood from the 25 commercial agarwood by using the evaluation method.

  11. Laser-induced breakdown spectroscopy-based investigation and classification of pharmaceutical tablets using multivariate chemometric analysis.

    PubMed

    Myakalwar, Ashwin Kumar; Sreedhar, S; Barman, Ishan; Dingari, Narahara Chari; Venugopal Rao, S; Prem Kiran, P; Tewari, Surya P; Manoj Kumar, G

    2011-12-15

    We report the effectiveness of laser-induced breakdown spectroscopy (LIBS) in probing the content of pharmaceutical tablets and also investigate its feasibility for routine classification. This method is particularly beneficial in applications where its exquisite chemical specificity and suitability for remote and on site characterization significantly improves the speed and accuracy of quality control and assurance process. Our experiments reveal that in addition to the presence of carbon, hydrogen, nitrogen and oxygen, which can be primarily attributed to the active pharmaceutical ingredients, specific inorganic atoms were also present in all the tablets. Initial attempts at classification by a ratiometric approach using oxygen (∼777 nm) to nitrogen (742.36 nm, 744.23 nm and 746.83 nm) compositional values yielded an optimal value at 746.83 nm with the least relative standard deviation but nevertheless failed to provide an acceptable classification. To overcome this bottleneck in the detection process, two chemometric algorithms, i.e. principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA), were implemented to exploit the multivariate nature of the LIBS data demonstrating that LIBS has the potential to differentiate and discriminate among pharmaceutical tablets. We report excellent prospective classification accuracy using supervised classification via the SIMCA algorithm, demonstrating its potential for future applications in process analytical technology, especially for fast on-line process control monitoring applications in the pharmaceutical industry. Copyright © 2011 Elsevier B.V. All rights reserved.

  12. Laser-induced breakdown spectroscopy-based investigation and classification of pharmaceutical tablets using multivariate chemometric analysis

    PubMed Central

    Myakalwar, Ashwin Kumar; Sreedhar, S.; Barman, Ishan; Dingari, Narahara Chari; Rao, S. Venugopal; Kiran, P. Prem; Tewari, Surya P.; Kumar, G. Manoj

    2012-01-01

    We report the effectiveness of laser-induced breakdown spectroscopy (LIBS) in probing the content of pharmaceutical tablets and also investigate its feasibility for routine classification. This method is particularly beneficial in applications where its exquisite chemical specificity and suitability for remote and on site characterization significantly improves the speed and accuracy of quality control and assurance process. Our experiments reveal that in addition to the presence of carbon, hydrogen, nitrogen and oxygen, which can be primarily attributed to the active pharmaceutical ingredients, specific inorganic atoms were also present in all the tablets. Initial attempts at classification by a ratiometric approach using oxygen to nitrogen compositional values yielded an optimal value (at 746.83 nm) with the least relative standard deviation but nevertheless failed to provide an acceptable classification. To overcome this bottleneck in the detection process, two chemometric algorithms, i.e. principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA), were implemented to exploit the multivariate nature of the LIBS data demonstrating that LIBS has the potential to differentiate and discriminate among pharmaceutical tablets. We report excellent prospective classification accuracy using supervised classification via the SIMCA algorithm, demonstrating its potential for future applications in process analytical technology, especially for fast on-line process control monitoring applications in the pharmaceutical industry. PMID:22099648

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

    PubMed

    Yao, Shuai; Zhang, Jingxian; Wang, Dandan; Hou, Jinjun; Yang, Wenzhi; Da, Juan; Cai, Luying; Yang, Min; Jiang, Baohong; Liu, Xuan; Guo, De-an; Wu, Wanying

    2015-01-01

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

  14. Discriminatory Components Retracing Strategy for Monitoring the Preparation Procedure of Chinese Patent Medicines by Fingerprint and Chemometric Analysis

    PubMed Central

    Wang, Dandan; Hou, Jinjun; Yang, Wenzhi; Da, Juan; Cai, Luying; Yang, Min; Jiang, Baohong; Liu, Xuan; Guo, De-an; Wu, Wanying

    2015-01-01

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

  15. 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.

  16. 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.

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

    PubMed Central

    2013-01-01

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

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

    PubMed

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

    2013-08-30

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

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

    PubMed

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

    2016-11-01

    The essential oil compositions of the leaves of three related Myrtaceae species, namely Syzygium aqueum, Syzygium samarangense and Eugenia uniflora, were investigated using GLC/MS and GLC/FID. Altogether, 125 compounds were identified: α-Selinene (13.85%), β-caryophyllene (12.72%) and β-selinene constitute the most abundant constituents in S. aqueum. Germacrene D (21.62%) represents the major compound in S. samarangense whereas in E. uniflora, spathulenol (15.80%) represents the predominant component. Multivariate chemometric analyses were used to discriminate the essential oils using hierarchical cluster analysis (HCA) and principal component analysis (PCA) based on the chromatographic results. The antimicrobial activity of the popularly used E. uniflora essential oil was assessed using broth microdilution method against six Gram-positive, three Gram-negative bacteria and two fungi. The oil showed moderate antimicrobial activity against Bacillus licheniformis exhibiting MIC and MMC of 0.63 mg/ml. The cytotoxic activity of E. uniflora essential oil was investigated against Trypanosoma brucei brucei (T. b. brucei) and MCF-7 cancer cell line using MTT assay. It showed moderate activity against MCF-7 cells with an IC50 value of 76.40 μg/ml. On the other hand, T. brucei was highly susceptible to E. uniflora essential oil with IC50 of 11.20 μg/ml, and a selectivity index of 6.82. © 2016 Wiley-VHCA AG, Zurich, Switzerland.

  20. Comparative analysis of two species of Asari Radix et Rhizoma by electronic nose, headspace GC-MS and chemometrics.

    PubMed

    Li, Chen; Xu, Feng; Cao, Chen; Shang, Ming-Ying; Zhang, Cui-Ying; Yu, Jie; Liu, Guang-Xue; Wang, Xuan; Cai, Shao-Qing

    2013-11-01

    Traditional Chinese medicines (TCM) can be identified by experts according to their odors. However, the identification of these medicines is subjective and requires long-term experience. In this paper, electronic nose, headspace gas chromatography-mass spectrometry (GC-MS) and chemometrics methods were applied to differentiate two species of Asari Radix et Rhizoma by their odors. The samples used were the dried roots and rhizomes of Asarum heterotropoides var. mandshuricum (AH) and Asarum sieboldii (AS). The electronic nose was used to determine the odors of the samples and enabled rapid differentiation of AH and AS when coupled with principal component analysis. Headspace GC-MS was utilized to reveal the differences between the volatile constituents of AH and AS. In all, 54 volatile constituents were identified, and 9 major constituents (eucalyptol, eucarvone, 3,5-dimethoxytoluene, 3,4,5-trimethoxytoluene, methyleugenol, 2,3,5-trimethoxytoluene, croweacin, pentadecane and asaricin) could be used as chemical markers to distinguish these two species. AH contained higher relative contents of eucarvone (1.79-16.76%), 3,5-dimethoxytoluene (6.64-26.52%), 3,4,5-trimethoxytoluene/methyleugenol (6.43-31.67%) and 2,3,5-trimethoxytoluene (1.64-6.66%), whereas AS had higher relative contents of eucalyptol (14.06-24.95%), croweacin (5.64-13.55%), pentadecane (8.44-20.82%) and asaricin (7.03-13.45%). Moreover, AH and AS could be distinguished according to the contents of either all 54 identified volatile constituents or only the 9 major constituents by employing cluster analysis. The proposed method is rapid, simple, eco-friendly and can successfully differentiate these two species of Asari Radix et Rhizoma by their odors.

  1. Libraries, classifiers, and quantifiers: a comparison of chemometric methods for the analysis of Raman spectra of contaminated pharmaceutical materials.

    PubMed

    Gryniewicz-Ruzicka, Connie M; Rodriguez, Jason D; Arzhantsev, Sergey; Buhse, Lucinda F; Kauffman, John F

    2012-03-05

    In this study, pharmaceutical grade sorbitol was used as a model system for comparison of Raman based library spectral correlation methods with more sophisticated methods of chemometric data analysis. Both crystallizing sorbitol (CS) and non-crystallizing sorbitol (NCS) from several manufacturers were examined. The Raman spectrum of each sample was collected and identified by correlation with a spectral library that included the CS spectrum but not the NCS spectrum. The average hit quality index (HQI) for the measured NCS spectra and the library CS spectrum was 0.966 whereas the average HQI for the measured CS spectra was 0.991. Both HQIs exceeded the 0.950 threshold that is commonly used for material verification. To enhance the discrimination between CS and NCS, a CS/NCS classification model was constructed using soft independent modeling of class analogies (SIMCA). SIMCA was able to positively identify CS and NCS solutions with no misclassifications. When CS was adulterated with low levels (0-5%) of ethylene glycol (EG) and diethylene glycol (DEG), the HQI values of the measured spectra and the CS library spectrum were still above 0.950. When the CS SIMCA model was applied to adulterated CS spectra, it determined that CS samples with adulterant levels as low as 2% were outside of the CS class. A quantitative PLS model was also applied to EG adulterated CS and resulted in a detection limit of 0.9% for EG. The results obtained from these studies highlight the importance of selecting an appropriate data analysis process for the detection of low level adulterants in pharmaceutical raw materials using Raman spectroscopic screening methods.

  2. Combined Use of Post-Ion Mobility/Collision-Induced Dissociation and Chemometrics for b Fragment Ion Analysis

    NASA Astrophysics Data System (ADS)

    Zekavat, Behrooz; Miladi, Mahsan; Becker, Christopher; Munisamy, Sharon M.; Solouki, Touradj

    2013-09-01

    Although structural isomers may yield indistinguishable ion mobility (IM) arrival times and similar fragment ions in tandem mass spectrometry (MS), it is demonstrated that post-IM/collision-induced dissociation MS (post-IM/CID MS) combined with chemometrics can enable independent study of the IM-overlapped isomers. The new approach allowed us to investigate the propensity of selected b type fragment ions from AlaAlaAlaHisAlaAlaAla-NH2 (AAA(His)AAA) heptapeptide to form different isomers. Principle component analysis (PCA) of the unresolved post-IM/CID profiles indicated the presence of two different isomer types for b4 +, b5 +, and b6 + and a single isomer type for b7 + fragments of AAA(His)AAA. We employed a simple-to-use interactive self-modeling mixture analysis (SIMPLISMA) to calculate the total IM profiles and CID mass spectra of b fragment isomers. The deconvoluted CID mass spectra showed discernible fragmentation patterns for the two isomers of b4 +, b5 +, and b6 + fragments. Under our experimental conditions, calculated percentages of the "cyclic" isomers (at the 95 % confidence level for n = 3) for b4 +, b5 +, and b6 + were 61 (± 5) %, 36 (± 5) %, and 48 (± 2) %, respectively. Results from the SIMPLISMA deconvolution of b5 + species resembled the CID MS patterns of fully resolved IM profiles for the two b5 + isomers. The "cyclic" isomers for each of the two-component b fragment ions were less susceptible to ion fragmentation than their "linear" counterparts.

  3. A novel near-infrared spectroscopy and chemometrics method for rapid analysis of several chemical components and antioxidant activity of mint (Mentha haplocalyx Briq.) samples.

    PubMed

    Dong, Wenjiang; Ni, Yongnian; Kokot, Serge

    2014-01-01

    A novel near-infrared spectroscopy (NIRS) method has been researched and developed for the simultaneous analyses of the chemical components and associated properties of mint (Mentha haplocalyx Briq.) tea samples. The common analytes were: total polysaccharide content, total flavonoid content, total phenolic content, and total antioxidant activity. To resolve the NIRS data matrix for such analyses, least squares support vector machines was found to be the best chemometrics method for prediction, although it was closely followed by the radial basis function/partial least squares model. Interestingly, the commonly used partial least squares was unsatisfactory in this case. Additionally, principal component analysis and hierarchical cluster analysis were able to distinguish the mint samples according to their four geographical provinces of origin, and this was further facilitated with the use of the chemometrics classification methods-K-nearest neighbors, linear discriminant analysis, and partial least squares discriminant analysis. In general, given the potential savings with sampling and analysis time as well as with the costs of special analytical reagents required for the standard individual methods, NIRS offered a very attractive alternative for the simultaneous analysis of mint samples.

  4. 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.

  5. 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

    2017-02-14

    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.

  6. 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.

  7. Use of fuzzy chromatography mass spectrometric (FCMS) fingerprinting and chemometric analysis for differentiation of whole-grain and refined wheat (T. aestivum) flour.

    PubMed

    Geng, Ping; Zhang, Mengliang; Harnly, James M; Luthria, Devanand L; Chen, Pei

    2015-10-01

    A fuzzy chromatography mass spectrometric (FCMS) fingerprinting method combined with chemometric analysis has been established for rapid discrimination of whole-grain flour (WF) from refined wheat flour (RF). Bran, germ, endosperm, and WF from three local cultivars or purchased from a grocery store were studied. The state of refinement (whole vs. refined) of wheat flour was differentiated successfully by use of principal-components analysis (PCA) and soft independent modeling of class analogy (SIMCA), despite potential confounding introduced by wheat class (red vs. white; hard vs. soft) or resources (different brands). Twelve discriminatory variables were putatively identified. Among these, dihexoside, trihexoside, apigenin glycosides, and citric acid had the highest peak intensity for germ. Variable line plots indicated phospholipids were more abundant in endosperm. Samples of RF and WF from three cultivars (Hard Red, Hard White, and Soft White) were physically mixed to furnish 20, 40, 60, and 80 % WF of each cultivar. SIMCA was able to discriminate between 100 %, 80 %, 60 %, 40 %, and 20 % WF and 100 % RF. Partial least-squares (PLS) regression was used for prediction of RF-to-WF ratios in the mixed samples. When PLS models were used the relative prediction errors for RF-to-WF ratios were less than 6 %. Graphical Abstract Workflow of targeting discriminatory compounds by use of FCMS and chemometric analysis.

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

    PubMed

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

    2016-07-01

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

  9. Unique ion filter: a data reduction tool for GC/MS data preprocessing prior to chemometric analysis.

    PubMed

    Adutwum, L A; Harynuk, J J

    2014-08-05

    Using raw GC/MS data as the X-block for chemometric modeling has the potential to provide better classification models for complex samples when compared to using the total ion current (TIC), extracted ion chromatograms/profiles (EIC/EIP), or integrated peak tables. However, the abundance of raw GC/MS data necessitates some form of data reduction/feature selection to remove the variables containing primarily noise from the data set. Several algorithms for feature selection exist; however, due to the extreme number of variables (10(6)-10(8) variables per chromatogram), the feature selection time can be prolonged and computationally expensive. Herein, we present a new prefilter for automated data reduction of GC/MS data prior to feature selection. This tool, termed unique ion filter (UIF), is a module that can be added after chromatographic alignment and prior to any subsequent feature selection algorithm. The UIF objectively reduces the number of irrelevant or redundant variables in raw GC/MS data, while preserving potentially relevant analytical information. In the m/z dimension, data are reduced from a full spectrum to a handful of unique ions for each chromatographic peak. In the time dimension, data are reduced to only a handful of scans around each peak apex. UIF was applied to a data set of GC/MS data for a variety of gasoline samples to be classified using partial least-squares discriminant analysis (PLS-DA) according to octane rating. It was also applied to a series of chromatograms from casework fire debris analysis to be classified on the basis of whether or not signatures of gasoline were detected. By reducing the overall population of candidate variables subjected to subsequent variable selection, the UIF reduced the total feature selection time for which a perfect classification of all validation data was achieved from 373 to 9 min (98% reduction in computing time). Additionally, the significant reduction in included variables resulted in a concomitant

  10. A Comprehensive Two-Dimensional Retention Time Alignment Algorithm To Enhance Chemometric Analysis of Comprehensive Two-Dimensional Separation Data

    SciTech Connect

    Pierce, Karisa M.; Wood, Lianna F.; Wright, Bob W.; Synovec, Robert E.

    2005-12-01

    trilinearity to the data, since trilinearity benefits chemometric analysis. By applying comprehensive 2D retention time alignment to all three data sets (control mixtures, gasoline samples, and diesel samples), classification by principal component analysis (PCA) substantially improved, resulting in 100% accurate scores clustering.

  11. A comprehensive two-dimensional retention time alignment algorithm to enhance chemometric analysis of comprehensive two-dimensional separation data.

    PubMed

    Pierce, Karisa M; Wood, Lianna F; Wright, Bob W; Synovec, Robert E

    2005-12-01

    trilinearity to the data, since trilinearity benefits chemometric analysis. By applying comprehensive 2D retention time alignment to all three data sets (control mixtures, gasoline samples, and diesel samples), classification by principal component analysis (PCA) substantially improved, resulting in 100% accurate scores clustering.

  12. A review on tomato authenticity: quality control methods in conjunction with multivariate analysis (chemometrics).

    PubMed

    Arvanitoyannis, Ioannis S; Vaitsi, Olga B

    2007-01-01

    Authenticity and traceability have been two of the most important issues in the food chain. Authenticity in particular, is closely related with both food quality and safety issues. Vegetables stand for a category of foods heavily affected by adulteration either in terms of geographic origin (national or international level) or production methods (organic or conventional production, fertilizers, pesticides, genetically modified vegetables). This review aims at addressing most of the currently applied methods for ensuring quality control of vegetables; a) instrumental: ion chromatography, high pressure liquid chromatography, atomic absorption spectrophotometry, electronic nose and mass spectroscopy and b) sensory analysis. The results of all the above mentioned methods were analyzed by means of multivariate analysis (principal component analysis, discriminant analysis, cluster analysis, canonical analysis, and factor analysis). All ensuing results and conclusions are summarized in eight comprehensive tables.

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

    PubMed

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

    2016-02-26

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

  14. High-performance liquid chromatography based chemical fingerprint analysis and chemometric approaches for the identification and distinction of three endangered Panax plants in Southeast Asia.

    PubMed

    Xia, Pengguo; Bai, Zhenqing; Liang, Tongyao; Yang, Dongfeng; Liang, Zongsuo; Yan, Xijun; Liu, Yan

    2016-10-01

    Among Panax genus, only three endangered species Panax notoginseng, P. vietnamensis, and P. stipuleanatus that have a similar morphology are mainly distributed in Southeast Asia. These three plants are usually misidentified or adulterated. To identify them well, their chemical chromatographic fingerprints were established by an effective high-performance liquid chromatography method. By comparing the chromatograms, the three Panax species could be distinguished easily using the 22 characteristic peaks. Besides, the data of the chromatographic fingerprints aided by chemometric approaches were applied for the identification and investigation the relationship of different samples and species. Using similarity analysis, the chemical components revealed higher similarity between P. vietnamensis and P. stipuleanatus. The results of hierarchical clustering analysis indicated that samples belonging to the same species could be clustered together. The result of principal component analysis was similar with hierarchical clustering analysis and the three principal components accounted for >80.5% of total variability.

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

    USDA-ARS?s Scientific Manuscript database

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

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

    PubMed

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

    2016-11-01

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

  17. 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.

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

    PubMed

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

    2017-08-08

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

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

    PubMed

    Ni, Yongnian; Lai, Yanhua; Kokot, Serge

    2012-07-01

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

  20. 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.

  1. Chemometric analysis with near-infrared spectroscopy for chemically pretreated Erianthus toward efficient bioethanol production.

    PubMed

    Horikawa, Yoshiki; Imai, Tomoya; Takada, Rie; Watanabe, Takashi; Takabe, Keiji; Kobayashi, Yoshinori; Sugiyama, Junji

    2012-02-01

    In this paper, we report the combination of a near-infrared (NIR) spectroscopic method with multivariate analysis in order to develop a calibration model of the saccharification ratio of chemically pretreated Erianthus. The regression models clearly depend on the NIR spectral regions, and the information of CH and aromatic framework vibrations contributed most effectively to the alkaline dataset. From interpretations of the regression coefficient, lignin and cellulose were negatively and positively correlated with the saccharification ratio, respectively, and this result was supported by the data from wet chemical analysis. A more complex dataset was obtained from varied chemical pretreatments; here, the saccharification ratio was either small or had no linear correlation with each structural monocomponent. These results enabled the successful construction of the PLS regression model. NIR spectroscopy can be a rapid screening method for the saccharification ratio, and furthermore, can provide information of the key factors influencing the realization of more efficient enzymatic accessibility.

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

    PubMed Central

    2013-01-01

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

  3. Combined online spectroscopic, calorimetric, and chemometric analysis: reaction enthalpy determinations in single and parallel reactions.

    PubMed

    Tjahjono, Martin; Widjaja, Effendi; Garland, Marc

    2009-06-02

    Calorimetry and signal processing: Vibrational spectroscopies, heat-flow microcalorimetry, and multivariate analysis are combined to decouple the reaction enthalpies of parallel reactions [picture: see text]. This methodology allows the evaluation of reaction enthalpy from complex systems without recourse to conventional kinetic modeling. Simultaneous in situ/online spectroscopy and heat-flow measurements as well as multivariate analyses are performed, apparently for the first time, to determine heats of reaction for single and parallel reactions. Two different vibrational spectroscopy techniques, namely Raman and FTIR spectroscopy, are used in conjunction with flow-through TAM III microcalorimetry. With respect to the spectroscopic analysis, the reaction spectra are first analyzed to determine the pure-component spectra and the corresponding concentrations without recourse to external calibration. With respect to the calorimetric analysis, a soft modeling approach is employed to determine the heats of reaction without recourse to any conventional kinetic models. This combined approach is implemented to determine the extents of reaction as well as the corresponding heats of reaction at 298.15 K and 0.1 MPa for a) the hydrolysis of acetic anhydride (single reaction) and b) the hydrolysis of methyl paraben and ethyl paraben in alkaline solution (both single and parallel reactions). In the latter case, the heat-flow contributions from the two simultaneous reactions are successfully decoupled. Taken together, these results demonstrate proof of concept for the present approach. The newly developed methodology appears to be quite general and particularly useful for investigating complex reaction systems. This is particularly true for multiple simultaneous reactions and reactions where the detailed kinetic expressions are not available, or cannot be easily determined. The use of extents of reaction is also very helpful where there is high variability in reaction rates

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

    PubMed

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

    2016-02-02

    Chemical attribution signatures (CAS) for chemical threat agents (CTAs), such as cyanides, are being investigated to provide an evidentiary link between CTAs and specific sources to support criminal investigations and prosecutions. Herein, stocks of KCN and NaCN were analyzed for trace anions by high performance ion chromatography (HPIC), carbon stable isotope ratio (δ(13)C) by isotope ratio mass spectrometry (IRMS), and trace elements by inductively coupled plasma optical emission spectroscopy (ICP-OES). The collected analytical data were evaluated using hierarchical cluster analysis (HCA), Fisher-ratio (F-ratio), interval partial least-squares (iPLS), genetic algorithm-based partial least-squares (GAPLS), partial least-squares discriminant analysis (PLSDA), K nearest neighbors (KNN), and support vector machines discriminant analysis (SVMDA). HCA of anion impurity profiles from multiple cyanide stocks from six reported countries of origin resulted in cyanide samples clustering into three groups, independent of the associated alkali metal (K or Na). The three groups were independently corroborated by HCA of cyanide elemental profiles and corresponded to countries each having one known solid cyanide factory: Czech Republic, Germany, and United States. Carbon stable isotope measurements resulted in two clusters: Germany and United States (the single Czech stock grouped with United States stocks). Classification errors for two validation studies using anion impurity profiles collected over five years on different instruments were as low as zero for KNN and SVMDA, demonstrating the excellent reliability associated with using anion impurities for matching a cyanide sample to its factory using our current cyanide stocks. Variable selection methods reduced errors for those classification methods having errors greater than zero; iPLS-forward selection and F-ratio typically provided the lowest errors. Finally, using anion profiles to classify cyanides to a specific stock

  5. Applying and comparing two chemometric methods in absorption spectral analysis of photopigments from Arctic microalgae.

    PubMed

    Zhang, Fang; He, Jianfeng; Xia, Lihua; Cai, Minghong; Lin, Ling; Guang, Yingzhi

    2010-11-01

    Pigment absorption property of two arctic microalgae species (Skeletonema marinoi and Chlorella sp.) cultured at three temperatures (0, 4 and 8°C) was analyzed. Carotenoids and chlorophyll (Chl) c were positive factors to the high cell activities and primary productivities of S. marinoi at 4°C and 0°C, respectively; whereas Chl a had a positive effect on Chlorella sp. at all three temperatures, and carotenoids had a relatively high effect at 0°C. The absorption locations of photopigments were analyzed in detail using both fourth derivative and Symlet-6 wavelet analysis. Both methods precisely detected pigments with a relative large content; the fourth derivative analysis specifically detected the existence of a Chl a peak at about 410 nm and showed better differentiation of diatoxanthin, whereas the wavelet analysis distinctively indicated the existence of chlorophyllide a, β-carotene, and Chl c. The separation limit to pigment peaks of the fourth derivative spectra (4 nm) was 1 nm higher than that of the wavelet high-frequency spectra (3 nm). The wavelet high-frequency spectra were more stable in detecting pigment locations and were more effective in discriminating microalgae. Small algebraic difference of 10(-16) between the reconstructed absorption spectra obtained by the inverse wavelet transform and their corresponding original spectra also showed the validity of Symlet-6 wavelet in the detection of pigments. Another specific discovery of this research is the existence of a Chl a allomer in Chlorella sp., which was detected by both methods.

  6. Hyperspectral imaging coupled with chemometric analysis for non-invasive differentiation of black pens

    NASA Astrophysics Data System (ADS)

    Chlebda, Damian K.; Majda, Alicja; Łojewski, Tomasz; Łojewska, Joanna

    2016-11-01

    Differentiation of the written text can be performed with a non-invasive and non-contact tool that connects conventional imaging methods with spectroscopy. Hyperspectral imaging (HSI) is a relatively new and rapid analytical technique that can be applied in forensic science disciplines. It allows an image of the sample to be acquired, with full spectral information within every pixel. For this paper, HSI and three statistical methods (hierarchical cluster analysis, principal component analysis, and spectral angle mapper) were used to distinguish between traces of modern black gel pen inks. Non-invasiveness and high efficiency are among the unquestionable advantages of ink differentiation using HSI. It is also less time-consuming than traditional methods such as chromatography. In this study, a set of 45 modern gel pen ink marks deposited on a paper sheet were registered. The spectral characteristics embodied in every pixel were extracted from an image and analysed using statistical methods, externally and directly on the hypercube. As a result, different black gel inks deposited on paper can be distinguished and classified into several groups, in a non-invasive manner.

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

    PubMed

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

    2014-12-31

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

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

    PubMed

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

    2008-07-15

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

  9. Comprehensive chemical analysis of Schisandra chinensis by HPLC-DAD-MS combined with chemometrics.

    PubMed

    Liu, Haitao; Lai, Hongwu; Jia, Xinyue; Liu, Jiushi; Zhang, Zhao; Qi, Yaodong; Zhang, Jin; Song, Junbin; Wu, Chongming; Zhang, Bengang; Xiao, Peigen

    2013-09-15

    The fruit of Schisandra chinensis, namely "Wuweizi" in China, is a well-known herbal medicine and health food. In this paper, an accurate and reliable high performance liquid chromatography coupled with diode array detection and mass spectrometry was developed for quality evaluation of Wuweizi. Nine lignans, including schisandrol A, schisandrol B, angeloylgomisin H, gomisin G, schisantherin A, schisanhenol, schisandrin A, schisandrin B, and schisandrin C were determined simultaneously in forty-three batches of Wuweizi samples collected from different localities. Thirty-six common peaks were unequivocally identified or tentatively assigned by comparing their mass spectrometric data with reference compounds, self-established compound library and published literatures. And the thirty-six common peaks were selected as characteristic peaks to assess the similarity of chromatographic fingerprinting of these Wuweizi samples. Moreover, hierarchical clustering analysis and principal components analysis were successfully applied to demonstrate the variability of these Wuweizi samples. The results indicated the content of nine investigated lignans varied greatly among the samples, and samples collected from different localities could be discriminated. Furthermore, schisandrol A, schisandrol B, schisandrin B, and schisandrin C were found to chemical marker for evaluating the quality of Wuweizi.

  10. 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.

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

    SciTech Connect

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

    2016-01-08

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

  12. Chemometric differentiation of raw and commercial milk by trace elements using principal component analysis.

    PubMed

    Vojnovic, D; Procida, G; Gabrielli Favretto, L

    1991-01-01

    Nine trace elements (Cr, Mn, Fe, Ni, Cu, Zn, Mo, Cd, and Pb) were determined in the dissolved ash of 36 samples of raw milk. The distribution of the concentration of each element was first investigated by means of a test of normality. The matrix of the correlation between the concentrations of the elements was then used as a starting matrix for principal component analysis. Nine variables were reduced to four principal components, accounting for 75% of the total variance. The biophilic elements Mn-Fe and Cu-Mo were positively associated with the first two principal components, while Cr was correlated to the third and Ni and Cd with the fourth principal component. Pb and Zn are both negatively correlated to the first principal component. Comparison with 42 samples of a commercial milk, by using a two-dimensional plot of the principal component scores, rendered possible the differentiation between raw and commercial milk.

  13. Analysis of Iranian rosemary essential oil: application of gas chromatography-mass spectrometry combined with chemometrics.

    PubMed

    Jalali-Heravi, Mehdi; Moazeni, Rudabeh Sadat; Sereshti, Hassan

    2011-05-06

    This paper focuses on characterization of the components of Iranian rosemary essential oil using gas chromatography-mass spectrometry (GC-MS). Multivariate curve resolution (MCR) approach was used to overcome the problem of background, baseline offset and overlapping/embedded peaks in GC-MS. The analysis of GC-MS data revealed that sixty eight components exist in the rosemary essential oil. However, with the help of MCR this number was extended to ninety nine components with concentrations higher than 0.01%, which accounts for 98.23% of the total relative content of the rosemary essential oil. The most important constituents of the Iranian rosemary are 1,8-cineole (23.47%), α-pinene (21.74%), berbonone (7.57%), camphor (7.21%) and eucalyptol (4.49%).

  14. Nondestructive analysis and dating of historical paper based on IR spectroscopy and chemometric data evaluation.

    PubMed

    Trafela, Tanja; Strlic, Matija; Kolar, Jana; Lichtblau, Dirk A; Anders, Manfred; Mencigar, Danijela Pucko; Pihlar, Boris

    2007-08-15

    Sampling restrictions in analysis of cultural heritage materials narrow the choice of appropriate analytical methods considerably. In this work, near- and mid-FT-IR reflectance data were related to paper properties determined with classical analytical methods using partial least-squares. Nondestructive determination of properties, which are of importance for evaluation of the long-term stability of historical paper, i.e., ash content, lignin content, degree of polymerization of cellulose, pH, and aluminum content, is possible. With the use of a considerable sample set, satisfactory reliability was achieved for all properties but aluminum content. Considering that with age, chemical properties of paper change, dating of historical documents was attempted for the first time, also with success.

  15. Quantification of simvastatin in mice plasma by near-infrared and chemometric analysis of spectral data.

    PubMed

    Fahmy, Usama A

    2016-01-01

    Time and cost saving is an essential requirement in pharmacokinetics and bioequivalence studies. The aim of this study is to use a simple, fast, and nondestructive near-infrared transmission spectroscopic method to quantify simvastatin (SMV) concentrations in mice plasma and also to improve SMV bioavailability by using alpha-lipoic acid as a carrier. Calibration curve was built at a concentration range of 10-250 ng/mL, and HPLC method was considered as a reference method. A partial least squares regression analysis model was used for method development, which gave less root mean square error cross-validation. Comparison of SMV concentrations obtained from both instruments showed no statistically significant differences between all the data. Near-infrared spectroscopy was utilized as a rapid, simple accurate method to quantify drug-plasma concentrations without need for any extraction protocols, and the significant effect of alpha-lipoic acid as a novel carrier to enhance SMV bioavailability is also addressed.

  16. Molecular Fingerprint Comparison of Closely Related Rose Varieties based on UHPLC-HRMS Analysis and Chemometrics.

    PubMed

    Riffault-Valois, Ludivine; Blanchot, Lucille; Colas, Cyril; Destandau, Emilie; Pasquier, Laure; André, Patrice; Elfakir, Claire

    2017-01-01

    The "Jardin de Granville" modern rose variety not only combines the morphological properties of its two parental cultivars, but also possesses better agronomic characteristics (abundant blooms, strong growth and vitality, high resistance to common rose diseases). In addition, it shows remarkable biological properties such as a high ability to decrease inflammatory and oxidative stress on skin cells. That is why Parfums Christian Dior selected this rose variety to be an active ingredient in luxury cosmetics. To identify the characteristic molecular signature of "Jardin de Granville" compared with its parents "Annapurna" and "John Clare", by the mean of a non-targeted metabolomic comparison. Wood, flower and leaf hydro-alcoholic extracts were analysed by UHPLC-ESI-HRMS. The fingerprints were then submitted to unsupervised multivariate analyses involving principal component analysis (PCA) and hierarchical ascendant classification (HAC). Analysis of variance (ANOVA) was finally performed to highlight the significant differences in each group of organs. The extracts were composed of phenolic compounds such as hydrolysable and condensed tannins and flavonol derivatives. Three groups of extracts were clustered as a function of the variety. The compounds overexpressed in "Jardin de Granville" variety were highlighted thanks to ANOVA test. Flower was the most discriminative organ with 15 overexpressed molecules. Auto MS/MS analyses led to their tentative identifications. The non-targeted metabolomic approach revealed the importance of tannins to discriminate close rose varieties. The overexpressed hydrolysable tannins characteristic of "Jardin de Granville" can be responsible for the antioxidant and anti-inflammatory properties of the rose cosmetic ingredients. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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

    PubMed

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

    2015-02-05

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

  19. Rapid detection and quantification of milk adulteration using infrared microspectroscopy and chemometrics analysis.

    PubMed

    Santos, P M; Pereira-Filho, E R; Rodriguez-Saona, L E

    2013-05-01

    The application of attenuated total reflectance mid-infrared microspectroscopy (MIR-microspectroscopy) was evaluated as a rapid method for detection and quantification of milk adulteration. Milk samples were purchased from local grocery stores (Columbus, OH, USA) and spiked at different concentrations of whey, hydrogen peroxide, synthetic urine, urea and synthetic milk. Samples were place on a 192-well microarray slide, air-dried and spectra were collected by using MIR-microspectroscopy. Pattern recognition analysis by Soft Independent Modeling of Class Analogy (SIMCA) showed tight and well-separated clusters allowing discrimination of control samples from adulterated milk. Partial Least Squares Regression (PLSR) showed standard error of prediction (SEP) ~2.33, 0.06, 0.41, 0.30 and 0.014 g/L for estimation of levels of adulteration with whey, synthetic milk, synthetic urine, urea and hydrogen peroxide, respectively. Results showed that MIR-microspectroscopy can provide an alternative methodology to the dairy industry for screening potential fraudulent practice for economic adulteration of cow's milk. Copyright © 2012 Elsevier Ltd. All rights reserved.

  20. Assessing evidentiary value in fire debris analysis by chemometric and likelihood ratio approaches.

    PubMed

    Sigman, Michael E; Williams, Mary R

    2016-07-01

    Results are presented from support vector machine (SVM), linear and quadratic discriminant analysis (LDA and QDA) and k-nearest neighbors (kNN) methods of binary classification of fire debris samples as positive or negative for ignitable liquid residue. Training samples were prepared by computationally mixing data from ignitable liquid and substrate pyrolysis databases. Validation was performed on an unseen set of computationally mixed (in silico) data and on fire debris from large-scale research burns. The probabilities of class membership were calculated using an uninformative (equal) prior and a likelihood ratio was calculated from the resulting class membership probabilities. The SVM method demonstrated a high discrimination, low error rate and good calibration for the in silico validation data; however, the performance decreased significantly for the fire debris validation data, as indicated by a significant increase in the error rate and decrease in the calibration. The QDA and kNN methods showed similar performance trends. The LDA method gave poorer discrimination, higher error rates and slightly poorer calibration for the in silico validation data; however the performance did not deteriorate for the fire debris validation data.

  1. Quantification of simvastatin in mice plasma by near-infrared and chemometric analysis of spectral data

    PubMed Central

    Fahmy, Usama A

    2016-01-01

    Time and cost saving is an essential requirement in pharmacokinetics and bioequivalence studies. The aim of this study is to use a simple, fast, and nondestructive near-infrared transmission spectroscopic method to quantify simvastatin (SMV) concentrations in mice plasma and also to improve SMV bioavailability by using alpha-lipoic acid as a carrier. Calibration curve was built at a concentration range of 10–250 ng/mL, and HPLC method was considered as a reference method. A partial least squares regression analysis model was used for method development, which gave less root mean square error cross-validation. Comparison of SMV concentrations obtained from both instruments showed no statistically significant differences between all the data. Near-infrared spectroscopy was utilized as a rapid, simple accurate method to quantify drug–plasma concentrations without need for any extraction protocols, and the significant effect of alpha-lipoic acid as a novel carrier to enhance SMV bioavailability is also addressed. PMID:27540278

  2. 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.

  3. Chemometric Analysis of Lavender Essential Oils Using Targeted and Untargeted GC-MS Acquired Data for the Rapid Identification and Characterization of Oil Quality.

    PubMed

    Beale, David J; Morrison, Paul D; Karpe, Avinash V; Dunn, Michael S

    2017-08-11

    Standard raw material test methods such as the ISO Standard 11024 are focused on the identification of lavender oil and not the actual class/quality of the oil. However, the quality of the oil has a significant effect on its price at market. As such, there is a need for raw material tests to identify not only the type of oil but its quality. This paper describes two approaches to rapidly identifying and classifying lavender oil. First, the ISO Standard 11024 test method was evaluated in order to determine its suitability to assess lavender oil quality but due to its targeted and simplistic approach, it has the potential to miss classify oil quality. Second, utilizing the data generated by the ISO Standard 11024 test methodology, an untargeted chemometric predicative model was developed in order to rapidly assess and characterize lavender oils (Lavandulaangustifolia L.) for geographical/environmental adulteration that impact quality. Of the 170 compounds identified as per the ISO Standard 11024 test method utilizing GC-MS analyses, 15 unique compounds that greatly differentiate between the two classes of lavender were identified. Using these 15 compounds, a predicative multivariate chemometric model was developed that enabled lavender oil samples to be reliably differentiated based on quality. A misclassification analysis was performed and it was found that the predictions were sound (100% matching rate). Such an approach will enable producers, distributers, suppliers and manufactures to rapidly screen lavender essential oil. The authors concede that the validation and implementation of such an approach is more difficult than a conventional chromatographic assay. However, the rapid, reliable and less problematic screening is vastly superior and easily justifies any early implementation validation difficulties and costs.

  4. Comparative study of machine-learning and chemometric tools for analysis of in-vivo high-throughput screening data.

    PubMed

    Simmons, Kirk; Kinney, John; Owens, Aaron; Kleier, Dan; Bloch, Karen; Argentar, Dave; Walsh, Alicia; Vaidyanathan, Ganesh

    2008-08-01

    High-throughput screening (HTS) has become a central tool of many pharmaceutical and crop-protection discovery operations. If HTS screening is carried out at the level of the intact organism, as is commonly done in crop protection, this strategy has the potential of uncovering a completely new mechanism of actions. The challenge in running a cost-effective HTS operation is to identify ways in which to improve the overall success rate in discovering new biologically active compounds. To this end, we describe our efforts directed at making full use of the data stream arising from HTS. This paper describes a comparative study in which several machine learning and chemometric methodologies were used to develop classifiers on the same data sets derived from in vivo HTS campaigns and their predictive performances compared in terms of false negative and false positive error profiles.

  5. 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.

  6. Selection of background electrolyte for CZE analysis by a chemometric approach. Part I. Separation of a mixture of acidic non-steroidal anti-inflammatory drugs.

    PubMed

    Furlanetto, Sandra; Lanteri, Silvia; Orlandini, Serena; Gotti, Roberto; Giannini, Iacopo; Pinzauti, Sergio

    2007-03-12

    This paper is the first part of the presentation of a chemometric approach for the rapid selection of a suitable background electrolyte (BGE) in CZE analysis of small drug molecules. The strategy is based on principal component analysis and experimental design. In this first section, the approach is applied to the analysis of a mixture of six arylpropionic anti-inflammatory drugs. Initially, 222 possible aqueous background electrolytes (objects) were characterized using as descriptors pH, conductivity, ionic strength and relative viscosity. In order to allow the dissociation of the acidic analytes, this original data set was reduced to 154 background electrolytes with pH values higher than or equal to 5. Principal component analysis made it possible to graphically represent the new set of objects, described by the four variables, in a two-dimensional space. Among these electrolytes, Kennard-Stone algorithm selected ten objects to be tested by CZE, covering homogeneously principal component space. CZE analyses were carried out with the selected electrolytes, and 0.1 M borax was identified as the most suitable one for the specified application. Finally, the characteristics of the analysis were finely tuned by means of a response surface study, which allowed the best conditions to be determined: borax concentration, 0.09 M; methanol, 6% (v/v); temperature, 24 degrees C, voltage, 20 kV. Applying these conditions, a baseline resolution among the six compounds was obtained in less than 10 min.

  7. Chemometric analysis of multi-sensor hyperspectral images of coarse mode aerosol particles for the image-based investigation on aerosol particles

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Multi-sensor hyperspectral imaging is a novel technique, which allows the determination of composition, chemical structure and pure components of laterally resolved samples by chemometric analysis of different hyperspectral datasets. These hyperspectral datasets are obtained by different imaging methods, analysing the same sample spot and superimposing the hyperspectral data to create a single multi-sensor dataset. Within this study, scanning electron microscopy (SEM), Raman and energy-dispersive X-ray spectroscopy (EDX) images were obtained from size-segregated aerosol particles, sampled above Western Australian salt lakes. The particles were collected on aluminum foils inside a 2350 L Teflon chamber using a Sioutas impactor, sampling aerosol particles of sizes between 250 nm and 10 µm. The complex composition of the coarse-mode particles can be linked to primary emissions of inorganic species as well as to oxidized volatile organic carbon (VOC) emissions. The oxidation products of VOC emissions are supposed to form an ultra-fine nucleation mode, which was observed during several field campaigns between 2006 and 2013. The aluminum foils were analysed using chemical imaging and electron microscopy. A Horiba LabRam 800HR Raman microscope was used for vibrational mapping of an area of about 100 µm x 100 µm of the foils at a resolution of about 1 µm. The same area was analysed using a Quanta FEI 200 electron microscope (about 250 nm resolution). In addition to the high-resolution image, the elemental composition could be investigated using energy-dispersive X-ray spectroscopy. The obtained hyperspectral images were combined into a multi-sensor dataset using the software package Imagelab (Epina Software Labs, www.imagelab.at). After pre-processing of the images, the multi-sensor hyperspectral dataset was analysed using several chemometric methods such as principal component analysis (PCA), hierarchical cluster analysis (HCA) and other multivariate methods. Vertex

  8. GC-MS combined with chemometric techniques for the quality control and original discrimination of Curcumae longae rhizome: analysis of essential oils.

    PubMed

    Hu, Yichen; Kong, Weijun; Yang, Xihui; Xie, Liwei; Wen, Jing; Yang, Meihua

    2014-02-01

    Curcumae longae rhizome is a widely used traditional herb in many countries. Various geographical origins of this herb might lead to diversity or instability of the herbal quality. The objective of this work was to establish the chemical fingerprints for quality control and find the chemical markers for discriminating these herbs from different origins. First, chemical fingerprints of essential oil of 24 C. longae rhizome from four different geographical origins in China were determined by GC-MS. Then, pattern recognition techniques were introduced to analyze these abundant chemical data in depth; hierarchical cluster analysis was used to sort samples into groups by measuring their similarities, and principal component analysis and partial least-squares discriminate analysis were applied to find the main chemical markers for discriminating these samples. Curcumae longae rhizome from Guangxi province had the highest essential oil yield (4.32 ± 1.45%). A total of 46 volatile compounds were identified in total. Consistent results were obtained to show that C. longae rhizome samples could be successfully grouped according to their origins, and turmerone, ar-turmerone, and zingiberene were the characteristic components for discriminating these samples of various geographical origins and for quality control. This finding revealed that fingerprinting analysis based on GC-MS coupled with chemometric techniques could provide a reliable platform to discriminate herbs from different origins, which is a benefit for quality control.

  9. Inorganic elemental determinations of marine traditional Chinese Medicine Meretricis concha from Jiaozhou Bay: The construction of inorganic elemental fingerprint based on chemometric analysis

    NASA Astrophysics Data System (ADS)

    Shao, Mingying; Li, Xuejie; Zheng, Kang; Jiang, Man; Yan, Cuiwei; Li, Yantuan

    2016-04-01

    The goal of this paper is to explore the relationship between the inorganic elemental fingerprint and the geographical origin identification of Meretricis concha, which is a commonly used marine traditional Chinese medicine (TCM) for the treatment of asthma and scald burns. For that, the inorganic elemental contents of Meretricis concha from five sampling points in Jiaozhou Bay have been determined by means of inductively coupled plasma optical emission spectrometry, and the comparative investigations based on the contents of 14 inorganic elements (Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Mo, Ni, Pb, Se and Zn) of the samples from Jiaozhou Bay and the previous reported Rushan Bay were performed. It has been found that the samples from the two bays are approximately classified into two kinds using hierarchical cluster analysis, and a four-factor model based on principle component analysis could explain approximately 75% of the detection data, also linear discriminant analysis can be used to develop a prediction model to distinguish the samples from Jiaozhou Bay and Rushan Bay with accuracy of about 93%. The results of the present investigation suggested that the inorganic elemental fingerprint based on the combination of the measured elemental content and chemometric analysis is a promising approach for verifying the geographical origin of Meretricis concha, and this strategy should be valuable for the authenticity discrimination of some marine TCM.

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

    SciTech Connect

    1994-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-09-01

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

  12. Screening and Analysis of the Marker Components in Ganoderma lucidum by HPLC and HPLC-MS(n) 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.

  13. Screening and Analysis of the Potential Bioactive Components of Poria cocos (Schw.) Wolf by HPLC and HPLC-MS(n) with the Aid of Chemometrics.

    PubMed

    Wu, Ling-Fang; Wang, Kun-Feng; Mao, Xin; Liang, Wen-Yi; Chen, Wen-Jing; Li, Shi; Qi, Qi; Cui, Ya-Ping; Zhang, Lan-Zhen

    2016-02-18

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

  14. Characterization of the Authenticity of Pasta di Gragnano Protected Geographical Indication Through Flavor Component Analysis by Gas Chromatography-Mass Spectrometry and Chemometric Tools.

    PubMed

    Giannetti, Vanessa; Boccacci Mariani, Maurizio; Mannino, Paola

    2016-09-01

    An authentication study based on headspace solid-phase microextraction/GC-MS was performed with a set of 60 samples representative of traditional "Pasta di Gragnano protected geographical indication (PGI)" and the most common Italian pasta brands. Multivariate chemometric tools were used to classify the samples based on the chemical information provided from 20 target flavor compounds, including Maillard reaction and lipid oxidation products. Pattern recognition by principal component analysis and linear discriminant analysis showed a natural grouping of samples according to the drying process adopted for their production (i.e., the traditional Cirillo method versus a high-temperature approach). Subsequently, soft independent modeling by class analogy (SIMCA) and unequal dispersed classes (UNEQ) were used to build class models at 95% confidence and 100% sensitivity levels (forced models) for predictive classification purposes. The good performance obtained from the models in terms of cross-validation efficiency (SIMCA, 57.01%; UNEQ, 86.60%; 100% for both forced models) highlighted that targeted analysis of flavor profiles could be used to assess the authenticity of Pasta di Gragnano PGI samples. Hence, the proposed method may help to protect Pasta di Gragnano PGI from label frauds by verifying whether samples comply with statements concerning drying process conditions as stated in the product specification.

  15. Non-destructive analysis of the two subspecies of African elephants, mammoth, hippopotamus, and sperm whale ivories by visible and short-wave near infrared spectroscopy and chemometrics.

    PubMed

    Shimoyama, Masahiko; Morimoto, Susumu; Ozaki, Yukihiro

    2004-06-01

    Visible (VIS) and short-wave near infrared (SW-NIR) spectroscopy was used for non-destructive analysis of ivories. VIS-SW-NIR (500-1000 nm) spectra were measured in situ for five kinds of ivories, that is two subspecies of African elephants, mammoth, hippopotamus, and sperm whale. Chemometrics analyses were carried out for the spectral data from 500 to 1000 nm region. The five kinds of ivories were clearly discriminated from each other on the scores plot of two principal components (PCs) obtained by principal component analysis (PCA). It was noteworthy that the ivories of the two subspecies of African elephants were discriminated by the scores of PC 1. The loadings plot for PC 1 showed that the discrimination relies on the intensity changes in bands due to collagenous proteins and water interacting with proteins. It was found that the scores plot of PC 2 is useful to distinguish between the ivories of the two subspecies of African elephants and the other ivories. We also developed a calibration model that predicted the specific gravity of five kinds of ivories from their VIS-SW-NIR spectral data using partial least squares (PLS)-1 regression. The correlation coefficient and root mean square error of cross validation (RMSECV) of this model were 0.960 and 0.037, respectively.

  16. Chemometric analysis of the interactions among different parameters describing health conditions, breast cancer risk and fatty acids profile in serum of rats supplemented with conjugated linoleic acids.

    PubMed

    Białek, Agnieszka; Zagrodzki, Paweł; Tokarz, Andrzej

    2016-03-01

    We investigated how different doses of conjugated linoleic acids applied for various periods of time influence breast cancer risk and fatty acids profile in serum of rats treated or not with 7,12-dimethylbenz[a]anthracene (DMBA). We also search for interactions among parameters describing health conditions and cancer risk. Animals were divided into 18 groups with different diet modifications (vegetable oil, 1.0%, 2.0% additions of CLA) and different periods of supplementation. In groups treated with DMBA mammary adenocarcinomas appeared. Due to the complexity of experiment apart from statistical analysis a chemometric tool-Partial Least Square method was applied. Analysis of pairs of correlated parameters allowed to identify some regularities concerning the relationships between fatty acid profiles and clinical features of animals. Fatty acids profile was the result of prolonged exposure to high dose of CLA and DMBA administration. These two factors underlined the differences in fatty acids profiles among clusters of animals. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

    PubMed

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

    2017-02-20

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

  18. Molecular determinants for nuclear receptors selectivity: chemometric analysis, dockings and site-directed mutagenesis of dual peroxisome proliferator-activated receptors α/γ agonists.

    PubMed

    Carrieri, Antonio; Giudici, Marco; Parente, Mariagiovanna; De Rosas, Mario; Piemontese, Luca; Fracchiolla, Giuseppe; Laghezza, Antonio; Tortorella, Paolo; Carbonara, Giuseppe; Lavecchia, Antonio; Gilardi, Federica; Crestani, Maurizio; Loiodice, Fulvio

    2013-05-01

    A series of previously synthesized chiral derivatives of clofibric and phenylacetic acids, acting as dual agonists towards the peroxisome proliferator-activated receptors (PPARs) α and γ, was taken into account, and the efficacy of these compounds was analyzed by means of 2D-, 3D-QSAR and docking studies with the goal to gain deeper insights into the three-dimensional determinants governing ligands selectivity for PPARs. By multiregressional analysis a correlation between the lipophilicity and PPARα activity was found, whereas for PPARγ the correlation was achieved once efficacy was related to the presence of polar groups on agonists scaffold. Docking of these compounds further corroborated this hypothesis, and then provided a valid support for subsequent chemometric analysis and pharmacophore models development for both receptors subtypes. Computational results suggested site directed mutagenesis experiments which confirmed the importance of amino acid residues in PPAR activity, allowing the identification of critical hotspots most likely taking over PPARs selectivity. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

  19. 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.

  20. Comparative analysis of essential oils from eight herbal medicines with pungent flavor and cool nature by GC-MS and chemometric resolution methods.

    PubMed

    Zhao, Chenxi; Zeng, Yingxu; Wan, Mingzhu; Li, Rongxi; Liang, Yizeng; Li, Chengyong; Zeng, Zhongda; Chau, Foo-Tim

    2009-02-01

    Systematic comparative research was conducted on essential oils from eight traditional Chinese medicines (TCM) of pungent flavor and cool nature because the essential oils are the main active ingredients of herbs of this kind. The work was based on their component analysis by gas chromatography-mass spectrometry (GC-MS), on their retention indices, as well as on chemometric resolution methods. A total of 144 compounds were tentatively identified, accounting for 69.0% to 91.8% of the total essential oils. It is worth noting that there are 67 compounds in at least three of these eight essential oils. Moreover, many biologically active compounds, such as hexanal, alpha-pinene, camphene, beta-pinene, p-cymene, limonene, eucalyptol, (Z)-ocimene, gamma-terpinene, camphor, p-menthone, 4-terpineol, alpha-terpineol, carvone, eugenol, caryophyllene, beta-farnesene, alpha-curcumene, beta-selinene, delta-cadinene, caryophyllene oxide, cedrol, n-hexadecanoic acid, benzaldehyde, benzeneacetaldehyde, phthalic acid diisobutyl ester, linoleic acid, tetradecanoic acid, (Z,Z,Z)-9,12,15-octadecatrienoic acid, eucalyptol, pentadecanoic acid, hexadecanoic acid methyl ester, linoleic acid methyl ester, exist in at least four of the eight essential oils. These results might help us to understand why the eight herbs are all of pungent flavor and cool nature according to the theory of TCM, and may provide a useful chemical basis for future research on herbs of this kind.

  1. 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.

  2. PCA-CR analysis of dissolution profiles. A chemometric approach to probe the polymorphic form of the active pharmaceutical ingredient in a drug product.

    PubMed

    Maggio, Rubén M; Castellano, Patricia M; Kaufman, Teodoro S

    2009-08-13

    A simple chemometric approach to differentiate among the three crystalline polymorphs of the model drug Furosemide (FUR) in a pharmaceutical dosage form is presented. The proposed method is based on the principal component analysis with confidence regions (PCA-CR) comparison of the dissolution profiles of the test pharmaceutical formulation, and formulations containing the different polymorphs, employed as the corresponding references. For the elaboration of the references, FUR polymorphs I, II and III were prepared, characterized and compounded with the excipients found in the test commercial formulation. The dissolutions were carried out in a discriminating HCl-KCl dissolution medium (pH 2.2), and the corresponding profiles were constructed from the absorbances (274 nm) of the dissolution samples. PCA-CR was able to differentiate among the three crystalline polymorphs of FUR and to confirm the presence of polymorph I in the test sample, with 99% statistical confidence. The PCA-CR results were compared with those obtained by a bootstrap-mediated implementation of Moore and Flanner's difference factor (f(2)). The same conclusion was reached employing an f(2)-based comparison, despite its inability to differentiate between polymorphs II and III. Therefore, PCA-CR may be considered a complementary and useful tool for probing the polymorphic form present in a pharmaceutical formulation.

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

    PubMed

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

    2014-01-01

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

  4. Analysis of volatile organic compounds in exhaled breath by gas chromatography-mass spectrometry combined with chemometric analysis.

    PubMed

    Dallinga, Jan W; Smolinska, Agnieszka; van Schooten, Frederik-Jan

    2014-01-01

    Analysis of exhaled breath samples reveals the presence of many volatile organic compounds (VOCs). The VOC composition of the breath, the so-called breath profile, contains a variety of information including the health status and condition of the organism that produced the sample. Therefore, breath profiling can be used in diagnosing and monitoring disease and other characteristics of the organism, such as phenotype, diet, and exercise. Among various techniques available for breath analysis, GC-MS provides the most extensive information with regard to the qualitative and quantitative presence of VOCs in breath.

  5. Chemometrics applied to vibrational spectroscopy: overview, challenges and pitfalls

    SciTech Connect

    Haaland, D.M.

    1996-10-01

    Chemometric multivariate calibration methods are rapidly impacting quantitative infrared spectroscopy in many positive ways. The combination of vibrational spectroscopy and chemometrics has been used by industry for quality control and process monitoring. The growth of these methods has been phenomenal in the past decade. Yet, as with any new technology, there are growing pains. The methods are so powerful at finding correlations in the data, that when used without great care they can readily yield results that are not valid for the analysis of future unknown samples. In this paper, the power of the multivariate calibration methods is discussed while pointing out common pitfalls and some remaining challenges that may slow the implementation of chemometrics in research and industry.

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

    PubMed

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

    2015-01-01

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

  7. Integrated plasma and urine metabolomics coupled with HPLC/QTOF-MS and chemometric analysis on potential biomarkers in liver injury and hepatoprotective effects of Er-Zhi-Wan.

    PubMed

    Yao, Weifeng; Gu, Haiwei; Zhu, Jiangjiang; Barding, Gregory; Cheng, Haibo; Bao, Beihua; Zhang, Li; Ding, Anwei; Li, Wei

    2014-11-01

    Metabolomics techniques are the comprehensive assessment of endogenous metabolites in a biological system and may provide additional insight into the molecular mechanisms. Er-Zhi-Wan (EZW) is a traditional Chinese medicine formula, which contains Fructus Ligustri Lucidi (FLL) and Herba Ecliptae (HE). EZW is widely used to prevent and treat various liver injuries through the nourishment of the liver. However, the precise molecular mechanism of hepatoprotective effects has not been comprehensively explored. Here, an integrated metabolomics strategy was designed to assess the effects and possible mechanisms of EZW against carbon tetrachloride-induced liver injury, a commonly used model of both acute and chronic liver intoxication. High-performance chromatography/quadrupole time-of-flight mass spectrometry (HPLC/QTOF-MS) combined with chemometric approaches including principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used to discover differentiating metabolites in metabolomics data of rat plasma and urine. Results indicate six differentiating metabolites, tryptophan, sphinganine, tetrahydrocorticosterone, pipecolic acid, L-2-amino-3-oxobutanoic acid and phosphoribosyl pyrophosphate, in the positive mode. Functional pathway analysis revealed that the alterations in these metabolites were associated with tryptophan metabolism, sphingolipid metabolism, steroid hormone biosynthesis, lysine degradation, glycine, serine and threonine metabolism, and pentose phosphate pathway. Of note, EZW has a potential pharmacological effect, which might be through regulating multiple perturbed pathways to the normal state. Our findings also showed that the robust integrated metabolomics techniques are promising for identifying more biomarkers and pathways and helping to clarify the function mechanisms of traditional Chinese medicine.

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

    PubMed

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

    2016-09-02

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

  9. Investigation of the acid-base properties of mononitro-calix[4]arene with chemometric methods.

    PubMed

    Wang, Li; Shi, Xian-Fa; Zhu, Zhong-Liang

    2007-07-01

    The acid-base properties of mononitro-calix[4]arene was studied with chemometric methods by measurement of its UV absorbance under different pH. The chemometric method-iterative target transformation factor (ITTFA) was employed to resolve the acid-base fraction curves. Combining with other chemometric methods-principal component analysis (PCA) and evolving factor analysis (EFA), the proton dissociation behavior of the derivative was investigated in detail. The pK(a) values of the derivative were determined and the fraction curves and pure absorbing spectra of each absorbing component were obtained.

  10. Prediction of source rock origin by chemometric analysis of fourier transform infrared-attenuated total reflectance spectra of oil petroleum: evaluation of aliphatic and aromatic fractions by self-modeling mixture analysis.

    PubMed

    Abbas, Ouissam; Dupuy, Nathalie; Rebufa, Catherine; Vrielynck, Laurence; Kister, Jacky; Permanyer, Albert

    2006-03-01

    This study describes a new methodology for the interpretation of Fourier transform infrared (FT-IR) attenuated total reflectance (ATR) spectra of Algerian, Brazilian, and Venezuelan crude oils. It is based on a comparative study between a chemometric treatment and the classical one, which refers to indices calculation. In fact, the combined use of FT-IR indices and principal component analysis (PCA) has led to the classification of the studied samples in terms of geographic distribution. Quantitative analysis has been successfully realized by the supervised method partial least squares (PLS), which has permitted the prediction of the locations of oils. We have also applied another mathematical processing method, simple-to-use interactive self-modeling mixture analysis (SIMPLISMA), to evaluate the aromatic and aliphatic composition of the oils by extracting pure spectra representative of the different fractions.

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

    PubMed

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

    2016-11-01

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

  12. Chemometric evaluation of brompheniramine-tannate complexes.

    PubMed

    Zidan, Ahmed S; Rahman, Ziyaur; Khan, Mansoor A

    2012-04-01

    The objective of the current study was to evaluate the performance of Raman and near-infrared (NIR) techniques combined with chemometrics in characterizing the critical quality attributes of brompheniramine (BP)-tannate complexes. Seven complexes were prepared and evaluated for chemical interactions, solubilities, dissolutions, and spatial distributions by NIR chemical imaging (CI). Principal component analysis (PCA) was applied before either partial least squares regression (PLSR) or principal component regression (PCR) models were developed. Complexation was confirmed by Fourier transform IR analysis to yield complexes of lower drug solubilities and sustained-release characteristics in alkaline media. PCA results showed better discrimination ability by NIR than by Raman spectroscopy. Compared with PCR, the PLSR predictions errors, calculated from the Raman and NIR data with second-derivative pretreatment, showed lesser values of 2.68, 0.37, 1.79, and 5.60 and 0.58, 0.25, 0.93, and 0.58 for complex solubilities in acidic and alkaline media and percentages dissolved after 1 and 20 h, respectively. In addition, good correlation (>0.95) was obtained for predicting the drug concentration using PLSR score images explaining the validity of the NIR-CI model for spatial quantitation of BP within its tannate complexes. In conclusion, the chemometric analysis of NIR and/or Raman spectra represented an innovative approach to determine the tannate complexation variability. Copyright © 2011 Wiley Periodicals, Inc.

  13. (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.

  14. Recent advancements in comprehensive two-dimensional separations with chemometrics.

    PubMed

    Pierce, Karisa M; Hoggard, Jamin C; Mohler, Rachel E; Synovec, Robert E

    2008-03-14

    Comprehensive two-dimensional (2D) separations provide the analyst with a tremendous amount of complex data. In order to glean useful information from this complex data, advancements in commercially available software that implement chemometrics are currently available and continue to evolve. Future advancements will no doubt involve commercializing (or adapting) specialized, in-house chemometric techniques that are currently found only in the hands of technical experts and researchers in industry, government, and academia. In order to make timely advancements, future commercialization of novel chemometric techniques should involve collaborations among instrument software manufacturers, professional programmers, technical experts, and researchers. During the last decade, this field has seen a steady advancement from single analyte target analysis to comprehensive non-target analysis of entire multidimensional sample profiles (involving sample classification and/or data mining for discovery-based sample comparisons). The advancements in instrumentation and chemometric software tools have a tremendous impact in various applications: fuels, food, environmental, pharmaceuticals, metabolomics, etc. Most of the development has been for software to apply with gas chromatography-based instrumentation, such as comprehensive two-dimensional gas chromatography (GC x GC) and comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC x GC-TOF-MS). More recently there have been notable advancements in liquid-phase instrumentation as well.

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

    PubMed

    Jiang, Pin; Lu, Yan; Chen, Daofeng

    2017-02-01

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

  16. Chemometric experimental design based optimization techniques in capillary electrophoresis: a critical review of modern applications.

    PubMed

    Hanrahan, Grady; Montes, Ruthy; Gomez, Frank A

    2008-01-01

    A critical review of recent developments in the use of chemometric experimental design based optimization techniques in capillary electrophoresis applications is presented. Current advances have led to enhanced separation capabilities of a wide range of analytes in such areas as biological, environmental, food technology, pharmaceutical, and medical analysis. Significant developments in design, detection methodology and applications from the last 5 years (2002-2007) are reported. Furthermore, future perspectives in the use of chemometric methodology in capillary electrophoresis are considered.

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

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

  18. OPTIMIZATION OF THERMAL OPTICAL ANALYSIS FOR THE MEASUREMENT OF BLACK CARBON IN REGIONAL PM2.5: A CHEMOMETRIC APPROACH

    EPA Science Inventory

    Thermal-optical analysis (TOA) is the principal method of the U.S. EPA's National Air Monitoring System for determining refractory carbon from combustion, or elemental carbon (EC), in particulate matter <2.5 µm (PM2.5). To isolate and quantify EC from organic carbon (...

  19. OPTIMIZATION OF THERMAL OPTICAL ANALYSIS FOR THE MEASUREMENT OF BLACK CARBON IN REGIONAL PM2.5: A CHEMOMETRIC APPROACH

    EPA Science Inventory

    Thermal-optical analysis (TOA) is the principal method of the U.S. EPA's National Air Monitoring System for determining refractory carbon from combustion, or elemental carbon (EC), in particulate matter <2.5 µm (PM2.5). To isolate and quantify EC from organic carbon (...

  20. Migration from printing inks in multilayer food packaging materials by GC-MS analysis and pattern recognition with chemometrics.

    PubMed

    Clemente, Isabel; Aznar, Margarita; Nerín, Cristina; Bosetti, Osvaldo

    2016-01-01

    Inks and varnishes used in food packaging multilayer materials can contain different substances that are potential migrants when packaging is in contact with food. Although printing inks are applied on the external layer, they can migrate due to set-off phenomena. In order to assess food safety, migration tests were performed from two materials sets: set A based on paper and set B based on PET; both contained inks. Migration was performed to four food simulants (EtOH 50%, isooctane, EtOH 95% and Tenax(®)) and the volatile compounds profile was analysed by GC-MS. The effect of presence/absence of inks and varnishes and also their position in the material was studied. A total of 149 volatile compounds were found in migration from set A and 156 from set B materials, some of them came from inks. Quantitative analysis and a principal component analysis were performed in order to identify patterns among sample groups.

  1. Floral classification of honey using liquid chromatography-diode array detection-tandem mass spectrometry and chemometric analysis.

    PubMed

    Zhou, Jinhui; Yao, Lihu; Li, Yi; Chen, Lanzhen; Wu, Liming; Zhao, Jing

    2014-02-15

    A high performance liquid chromatography-diode array detection-tandem mass spectrometry (HPLC-DAD-MS/MS) method for the floral origin traceability of chaste honey and rape honey samples was firstly presented in this study. Kaempferol, morin and ferulic acid were used as floral markers to distinguish chaste honey from rape honey. Chromatographic fingerprinting at 270 nm and 360 nm could be used to characterise chaste honey and rape honey according to the analytical profiles. Principal component analysis (PCA), partial least squares (PLS), partial least squares-discrimination analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA) were applied to classify the honey samples according to their floral origins. The results showed that chaste honey and rape honey could be successfully classified by their floral sources with the analytical methods developed through this study and could be considered encouraging and promising for the honey traceability from unifloral or multifloral nectariferous sources.

  2. Metabolomics driven analysis of artichoke leaf and its commercial products via UHPLC-q-TOF-MS and chemometrics.

    PubMed

    Farag, Mohamed A; El-Ahmady, Sherweit H; Elian, Fatma S; Wessjohann, Ludger A

    2013-11-01

    The demand to develop efficient and reliable analytical methods for the quality control of herbal medicines and nutraceuticals is on the rise, together with an increase in the legal requirements for safe and consistent levels of active principles. Here, we describe an ultra-high performance liquid chromatography method (UHPLC) coupled with quadrupole high resolution time of flight mass spectrometry (qTOF-MS) analysis for the comprehensive measurement of metabolites from three Cynara scolymus (artichoke) cultivars: American Green Globe, French Hyrious, and Egyptian Baladi. Under optimized conditions, 50 metabolites were simultaneously quantified and identified including: eight caffeic acid derivatives, six saponins, 12 flavonoids and 10 fatty acids. Principal component analysis (PCA) was used to define both similarities and differences among the three artichoke leaf cultivars. In addition, batches from seven commercially available artichoke market products were analysed and showed variable quality, particularly in caffeic acid derivatives, flavonoid and fatty acid contents. PCA analysis was able to discriminate between various preparations, including differentiation between various batches from the same supplier. To the best of our knowledge, this study provides the first approach utilizing UHPLC-MS based metabolite fingerprinting to reveal secondary metabolite compositional differences in artichoke leaf extracts.

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

    PubMed

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

    2015-05-01

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

  4. Analysis of human tissues by total reflection X-ray fluorescence. Application of chemometrics for diagnostic cancer recognition

    NASA Astrophysics Data System (ADS)

    Benninghoff, L.; von Czarnowski, D.; Denkhaus, E.; Lemke, K.

    1997-07-01

    For the determination of trace element distributions of more than 20 elements in malignant and normal tissues of the human colon, tissue samples (approx. 400 mg wet weight) were digested with 3 ml of nitric acid (sub-boiled quality) by use of an autoclave system. The accuracy of measurements has been investigated by using certified materials. The analytical results were evaluated by using a spreadsheet program to give an overview of the element distribution in cancerous samples and in normal colon tissues. A further application, cluster analysis of the analytical results, was introduced to demonstrate the possibility of classification for cancer diagnosis. To confirm the results of cluster analysis, multivariate three-way principal component analysis was performed. Additionally, microtome frozen sections (10 μm) were prepared from the same tissue samples to compare the analytical results, i.e. the mass fractions of elements, according to the preparation method and to exclude systematic errors depending on the inhomogeneity of the tissues.

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

    PubMed

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

    2015-10-09

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

  6. Application of two-dimensional correlation spectroscopy to chemometrics: self-modeling curve resolution analysis of spectral data sets.

    PubMed

    Jung Mee, Young; Kim Bin, Seung; Noda, Isao

    2003-11-01

    This paper demonstrates the use of two-dimensional (2D) correlation spectroscopy in conjunction with alternating least squares (ALS) based self-modeling curve resolution (SMCR) analysis of spectral data sets. This iterative regression technique utilizes the non-negativity constraints for spectral intensity and concentration. ALS-based SMCR analysis assisted with 2D correlation was applied to Fourier transform infrared (FT-IR) spectra of a polystyrene/methyl ethyl ketone/deuterated toluene (PS/MEK/d-toluene) solution mixture during the solvent evaporation process to obtain the pure component spectra and then the time-dependent concentration profiles of these three components during the evaporation process. We focus the use of asynchronous 2D correlation peaks for the identification of pure variables needed for the initial estimates of the ALS process. Choosing the most distinct bands via the positions of asynchronous 2D peaks is a viable starting point for ALS iteration. Once the pure variables are selected, ALS regression can be used to obtain the concentration profiles and pure component spectra. The obtained pure component spectra of MEK, d-toluene, and PS matched well with known spectra. The concentration profiles for components looked reasonable.

  7. Chemometric analysis of gas chromatography with flame ionisation detection chromatograms: a novel method for classification of petroleum products.

    PubMed

    Nielsen, N J; Ballabio, D; Tomasi, G; Todeschini, R; Christensen, J H

    2012-05-18

    Most oil characterisation procedures are time consuming, labour intensive and utilise only part of the acquired chemical information. Oil spill fingerprinting with multivariate data processing represents a fast and objective evaluation procedure, where the entire chromatographic profile is used. Methods for oil classification should be robust towards changes imposed on the spill fingerprint by short-term weathering, i.e. dissolution and evaporation processes in the hours following a spill. We propose a methodology for the classification of petroleum products. The method consists of: chemical analysis; data clean-up by baseline removal, retention time alignment and normalisation; recognition of oil type by classification followed by initial source characterisation. A classification model based on principal components and quadratic discrimination robust towards the effect of short-term weathering was established. The method was tested successfully on real spill and source samples. Copyright © 2012 Elsevier B.V. All rights reserved.

  8. Chemometric analysis for the evaluation of phenolic patterns in olive leaves from six cultivars at different growth stages.

    PubMed

    Talhaoui, Nassima; Gómez-Caravaca, Ana María; Roldán, Cristina; León, Lorenzo; De la Rosa, Raúl; Fernández-Gutiérrez, Alberto; Segura-Carretero, Antonio

    2015-02-18

    Leaves from six important olive cultivars grown under the same agronomic conditions were collected at four different times from June to December and analyzed by high performance liquid chromatography-diode array detector-time-of-flight-mass spectrometry (HPLC-DAD-TOF-MS). Twenty-eight phenolic compounds were identified and quantified. No qualitative differences were detected among leaves. However, for all cultivars, total concentrations of phenolic compounds decreased from June to August, then increased from October on, and reached higher levels again in December. Principal component analysis provided a clear separation of the phenolic content in leaves for different sampling times and cultivars. Hence, the availability of phenolic compounds depends on both the season and the cultivar. June and December seem to be good times to collect leaves as a source of phenolic compounds. December coincides with the harvest period of olives in the Andalusian region. Thus, in December olive leaves could be valorized efficiently as olive byproducts.

  9. Comparison of two officinal Chinese pharmacopoeia species of Ganoderma based on chemical research with multiple technologies and chemometrics analysis.

    PubMed

    Da, Juan; Wu, Wan-Ying; Hou, Jin-Jun; Long, Hua-Li; Yao, Shuai; Yang, Zhou; Cai, Lu-Ying; Yang, Min; Jiang, Bao-Hong; Liu, Xuan; Cheng, Chun-Ru; Li, Yi-Feng; Guo, De-An

    2012-01-27

    To investigate the chemical differences between Ganoderma lucidum (G. lucidum, Chizhi) and Ganoderma sinense (G. sinense, Zizhi). Thirty two batches of commercial Ganoderma samples were collected, including 20 batches of G. lucidum and 12 batches of G. sinense cultivated in different geographical regions. Chemical substances in aqueous extract and alcoholic extract, mainly polysaccharides and triterpenes respectively, were investigated. Determination of polysaccharides was carried out with a high performance liquid chromatography with an variable wavelength detector. Meanwhile, analysis of triterpenes were performed on an ultraviolet spectrophotometer, an ultra performance liquid chromatography and a rapid resolution liquid chromatograph combined with an electrospray ionization mass spectrometer. Chromatograms and spectra for all batches and reference standards of main components were obtained and used for direct comparison. Further discussion was made on the basis of the result of principal component analysis (PCA). Significant difference of triterpenes was shown between G. lucidum and G. sinense. In 20 batches of G. lucidum, 12 main components, including eight ganoderic acids and four ganoderenic acids were identified and ten of them were quantitatively determined, with the total content from 0.249% to 0.690%. However, none of those triterpenes was found in either batch of G. sinense. As for constituents of polysaccharides, seven monosaccharides were identified and four main components among them were quantitatively determined. Difference of polysaccharides was not directly observed, but latent information was revealed by PCA and the discrimination became feasible. G. lucidum and G. sinense were chemically different, which might result in pharmacological distinction. Preparations of traditional Chinese medicine (TCM) from Ganoderma should make accurate specification on the origin of species. Copyright © 2011 Elsevier B.V. All rights reserved.

  10. Analysis of trace metal concentrations in raw cow's milk from three dairy farms in North Gondar, Ethiopia: chemometric approach.

    PubMed

    Akele, M L; Abebe, D Z; Alemu, A K; Assefa, A G; Madhusudhan, A; de Oliveira, R R

    2017-09-11

    Concentrations of essential (Cu, Mn, and Zn) and toxic (Cr, Cd, and Pb) trace metals in 30 raw cow's milk samples were quantified using flame atomic absorption spectrometry. The samples were collected from the Nara-Awudarda, Tana-Abo, and Kosoye Amba-Rass sites in North Gondar, Ethiopia, preserved in a deep freezer (-20 °C), and then digested by Kjeldahl apparatus with HNO3/H2O2 (5:2; v/v) at 300 °C for 2.5 h. The data were subject to principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA). Overall hazard quotient (HQ) and carcinogenic risk (CR) values were also estimated to assess metal-related health risks. The mean concentrations of Cr, Mn, Cu, Zn, Cd, and Pb in the milk samples ranged 0.468-0.828, 1.614-2.806, 0.840-1.532, 1.208-5.267, ND-0.330, and ND-0.186 mg/kg, respectively. The lowest values were obtained for Kosoye Amba-Rass milk samples, while the highest were found for those collected from Nara-Awudarda milk samples, probably due to high mineral enrichment and metal leaching (especially Cd and Pb) from coal deposits. PCA revealed clustering of samples with respect to their geographic origin. Validation of PLS-DA model showed 100% classification efficiency using external validation samples and detected Cd and Cu as trace metal markers. The HQ and CR values were within the safe level; however, the former is close to the alert threshold level for Nara-Awudarda milk samples. Thus, further studies on common foodstuffs, constituting a higher proportion in the local diet, are required in this area to provide a complete risk assessment.

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

    PubMed

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

    2017-01-27

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

  12. Classification of natural resins by liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry using chemometric analysis.

    PubMed

    Rhourrhi-Frih, B; West, C; Pasquier, L; André, P; Chaimbault, P; Lafosse, M

    2012-09-21

    Twenty-six resins from six botanical sources belonging to the class Magnoliopsida were compared based on gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry data. The extracts were analysed by GC after silylation and by reversed phase LC combined with atmospheric pressure photoionisation (APPI) mass spectrometry. The chromatograms were re-organized in data matrices, where each sample was represented by a single column comprising 2755 observations (intensity, time, m/z) in GC-MS and 360 observations in LC-MS. A simple comparison of resin fingerprints was attempted by organizing data according to a three dimensional bubble chart (retention time against m/z where each point was a bubble which size represented the ion intensity) where it is possible to easily superimpose the fingerprints. Thus the common and different species can be easily observed enabling to classify the resins. Hierarchical cluster analysis based on characteristics of GC-MS and LC-MS profiles affords a complete description of the classes of the resins and shows that 26 resins are divided into five main clusters Commiphora mukul, Daniella oliveri, Gardenia gummifera, Canarium madagascariensis, Boswellia dalzielii and Boswellia serrata, respectively. In conclusion, the proposed method has been applied to three other resinous samples from the Burseraceae family to evaluate their alteration state.

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  14. Near-infrared spectroscopy (NIRS) and chemometric analysis of Malaysian and UK paracetamol tablets: a spectral database study.

    PubMed

    Said, Mazlina M; Gibbons, Simon; Moffat, Anthony C; Zloh, Mire

    2011-08-30

    The influx of medicines from different sources into healthcare systems of developing countries presents a challenge to monitor their origin and quality. The absence of a repository of reference samples or spectra prevents the analysis of tablets by direct comparison. A set of paracetamol tablets purchased in Malaysian pharmacies were compared to a similar set of sample purchased in the UK using near-infrared spectroscopy (NIRS). Additional samples of products containing ibuprofen or paracetamol in combination with other actives were added to the study as negative controls. NIR spectra of the samples were acquired and compared by using multivariate modeling and classification algorithms (PCA/SIMCA) and stored in a spectral database. All analysed paracetamol samples contained the purported active ingredient with only 1 out of 20 batches excluded from the 95% confidence interval, while the negative controls were clearly classified as outliers of the set. Although the substandard products were not detected in the purchased sample set, our results indicated variability in the quality of the Malaysian tablets. A database of spectra was created and search methods were evaluated for correct identification of tablets. The approach presented here can be further developed as a method for identifying substandard pharmaceutical products. Copyright © 2011 Elsevier B.V. All rights reserved.

  15. 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.

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

    PubMed

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

    2017-07-15

    The present work evaluated the effect of the acid treatment conditions of natural kaolinite (NK) regarding its efficiency in removing etheramine. The treatment was conducted using sulfuric acid at the concentrations of 1 mol L(-1) (KA-01), 2 mol L(-1) (KA-02) and 5 mol L(-1) (KA-05) at 85 °C. The obtained adsorbents were characterized by X-ray fluorescence, X-ray diffraction, N2 adsorption/desorption isotherms, zeta potential analysis and infrared spectroscopy. The Response Surface Method was used to optimize adsorption parameters (initial concentration of etheramine, adsorbent mass and pH of the solution). The results, described by means of a central composite design, were adjusted to the quadratic model. Results revealed that the adsorption was more efficient at the etheramine concentration of 400 mg L(-1), pH 10 and adsorbent mass of 0.1 g for NK and 0.2 g for KA-01, KA-02 and KA-05. The sample KA-02 presented a significant increase of etheramine removal compared to the NK sample. The adsorption kinetics conducted under optimized conditions showed that the system reached the equilibrium in approximately 30 min. The kinetic data were better adjusted to the pseudo-second order model. The isotherm data revealed that the Sips model was the most adequate one. The calculation of Eads allowed to infer that the mechanism for etheramine removal in all the evaluated samples was chemisorption. The reuse tests showed that, after four uses, the efficiency of adsorbents in removing etheramine did not suffer significant modifications, which makes the use of kaolinite to treat effluents from the reverse flotation of iron ore feasible. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. A dynamic thermal ATR-FTIR/chemometric approach to the analysis of polymorphic interconversions. Cimetidine as a model drug.

    PubMed

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

    2014-04-01

    Crystal polymorphism of active ingredients is relevant to the pharmaceutical industry, since polymorphic changes taking place during manufacture or storage of pharmaceutical formulations can affect critical properties of the products. Cimetidine (CIM) has several relevant solid state forms, including four polymorphs (A, B, C and D), an amorphous form (AM) and a monohydrate (M1). Dehydration of M1 has been reported to yield mixtures of polymorphs A, B and C or just a single form. Standards of the solid forms of CIM were prepared and unequivocally characterized by FTIR spectroscopy, digital microscopy, differential scanning calorimetry and solid state (13)C NMR spectroscopy. Multivariate curve resolution with alternating least squares (MCR-ALS) was coupled to variable temperature attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) to dynamically characterize the behavior of form M1 of CIM over a temperature range from ambient to 160°C, without sample pretreatment. MCR-ALS analysis of ATR-FTIR spectra obtained from the tested solid under variable temperature conditions unveiled the pure spectra of the species involved in the polymorphic transitions. This allowed the simultaneous observation of thermochemical and thermophysical events associated to the changes involved in the solid forms, enabling their unequivocal identification and improving the understanding of their thermal behavior. It was demonstrated that under the experimental conditions, dehydration of M1 initially results in the formation of polymorph B; after melting and upon cooling, the latter yields an amorphous solid (AM). It was concluded that the ATR-FTIR/MCR association is a promising and useful technique for monitoring solid-state phase transformations. Copyright © 2014 Elsevier B.V. All rights reserved.

  18. Chemometric analysis of the consumption of oral rinse chlorite (ClO2-) by human salivary biomolecules.

    PubMed

    Chang, Hubert; Blackburn, John; Grootveld, Martin

    2013-12-01

    Oral rinse formulations containing chlorite anion (ClO(2)(-)) as an active agent exert a range of valuable oral healthcare activities. However, salivary biomolecules which chemically react with this oxidant can, at least in principle, serve as potentially significant barriers to these therapeutic properties in the oral environment. Therefore, in this investigation, we have explored the extent of ClO(2)(-) consumption by biomolecules which scavenge this agent in human salivary supernatants (HSSs) in vitro. HSS samples were equilibrated with oral rinse formulations containing this active agent (30 s at 35 °C in order to mimic oral rinsing episodes). Differential spectrophotometric and ion-pair reversed-phase high-performance liquid chromatographic analyses were employed to determine residual ClO(2)(-) in these admixtures. Bioanalytical data acquired revealed the rapid consumption of ClO(2)(-) by biomolecular electron donors and/or antioxidants present in HSS samples. Mean ± 95 % confidence interval (CI) consumption levels of 7.14 ± 0.69 and 5.34 ± 0.69 % of the total ClO(2)(-) available were found for oral rinse products containing 0.10 and 0.40 % (w/v) ClO(2)(-), respectively. A mixed model analysis-of-variance performed on experimental data acquired demonstrated highly-significant differences between oral rinse ClO(2)(-) contents (p < 0.0001), trial participants (p < 0.001) and sampling days-within-participants (p < 0.001), and also revealed non-additive ClO(2)(-)-scavenging responses of participants' HSSs to increases in the oral rinse content of this oxidant (p < 0.0001). A slower, second phase of the reaction process (t (1/2) = 1.7-2.8 h) involved the oxidative consumption of salivary urate. These data clearly demonstrate that for recommended 30 s oral rinsing episodes performed at physiological temperature, <10 % of the total oral rinse ClO(2)(-) available is chemically and/or reductively consumed by HSS biomolecules for both

  19. Exploration of anthropological specimens by GC-MS and chemometrics.

    PubMed

    Varmuza, Kurt; Makristathis, Athanasios; Schwarzmeier, Josef; Seidler, Horst; Mader, Robert M

    2005-01-01

    Anthropological specimens combine a variety of unfavorable characteristics, rendering their evaluation an analytical challenge. Their remarkable status is primarily based on two characteristics: (i) these very rare samples of human origin are testimonies of human history and are, therefore, available only in minute amounts for analytical purposes, and (ii) the analysis of these samples is extremely limited by the decomposition of molecules, which are easily detected in living organisms, such as nucleic acids and proteins, but are subject to rapid post-mortem decay. In this article, we review the methods and results of archaeometry, emphasizing the role of MS combined with chemometrics. Focusing on experimental results for fatty acid profiles, specimens from mummies from different civilizations were compared. Considering in particular the Tyrolean Iceman, the application of chemometric methods to GC-MS data recovers essential information about the preservation and the storage conditions of mummies.

  20. 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.

    PubMed

    Masoum, Saeed; Gholami, Ali; Hemmesi, Marjan; Abbasi, Saleheh

    2015-09-05

    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.

  1. 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.

  2. 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

  3. Evaluation of traditional Chinese herbal medicine: Chaihu (Bupleuri Radix) by both high-performance liquid chromatographic and high-performance thin-layer chromatographic fingerprint and chemometric analysis.

    PubMed

    Tian, Run-tao; Xie, Pei-shan; Liu, He-ping

    2009-03-13

    Chaihu (Bupleuri Radix), roots of Bupleurum chinense and B. scorzonerifolium, is an authentic Chinese Materia Medica in the Chinese Pharmacopoeia. Some other species such as the roots of B. falcatum, B.bicaule and B. marginatum var. stenophyllum similar to Chaihu can also be occasionally found in local raw herb markets. The quality of 33 lots of authenticated Chaihu samples vs. 31 lots of commercial samples was evaluated by both high-performance liquid chromatography-evaporative light scattering detector (HPLC-ELSD) and high-performance thin-layer chromatography (HPTLC) analyses of its principal bioactive components (saikosaponins). The pre-treated data acquired from both HPLC fingerprints and HPTLC fluorescent images were processed by chemometrics for similarity and pattern recognition, including Artificial Neural Networks (ANNs), k-nearest neighbor (k-NN) and an expert's panel. It was apparent that k-NN classifier exhibited good performance with sufficient flexibility for processing HPTLC fingerprint images which were otherwise not easily dealt with by other algorithms due to the shift of R(f) values and varying hue/saturation of the band colours between different TLC plates. These two chromatographic fingerprint methods can be considered complementary measure of quality control. The roots of Chaihu from different species of the genus Bupleurum could readily be distinguished from each other so that commercial samples can easily be classified. Chaihu collected from several major herbal distribution centers was found to belong to B. chinense with great variation in the content of its major saikosaponins.

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

    PubMed

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

    2016-10-01

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

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

    PubMed

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

    2015-10-01

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

  6. Chemometrics applications in biotech processes: a review.

    PubMed

    Rathore, Anurag S; Bhushan, Nitish; Hadpe, Sandip

    2011-01-01

    Biotech unit operations are often characterized by a large number of inputs (operational parameters) and outputs (performance parameters) along with complex correlations amongst them. A typical biotech process starts with the vial of the cell bank, ends with the final product, and has anywhere from 15 to 30 such unit operations in series. The aforementioned parameters can impact process performance and product quality and also interact amongst each other. Chemometrics presents one effective approach to gather process understanding from such complex data sets. The increasing use of chemometrics is fuelled by the gradual acceptance of quality by design and process analytical technology amongst the regulators and the biotech industry, which require enhanced process and product understanding. In this article, we review the topic of chemometrics applications in biotech processes with a special focus on recent major developments. Case studies have been used to highlight some of the significant applications.

  7. [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.

  8. Solvent effect modelling of isocyanuric products synthesis by chemometric methods

    PubMed Central

    Havet, Jean-Louis; Billiau-Loreau, Myriam; Delacroix, Alain

    2002-01-01

    Chemometric tools were used to generate the modelling of solvent e¡ects on the N-alkylation of an isocyanuric acid salt. The method proceeded from a central composite design applied on the Carlson solvent classification using principal components analysis. The selectivity of the reaction was studied from the production of different substituted isocyanuric derivatives. Response graphs were obtained for each compound and used to devise a strategy for solvent selection. The prediction models were validated and used to search for the best selectivity for the reaction system. The solvent most often selected as the best for the reaction is the N,N-dimethylformamide. PMID:18924731

  9. Analysis of the interactions of mixtures of two beta-agonists steroids with bovine serum albumin: a fluorescence spectroscopy and chemometrics investigation.

    PubMed

    Ni, Yongnian; Zhang, Qiulan; Kokot, Serge

    2010-08-01

    Beta-agonists such as ractopamine (RAC) and clenbuterol (CLEN), have similar effects as anabolic steroids i.e. they promote growth of muscular tissue and reduce body fat. They have been used successfully with animals and humans but have also been banned in many countries principally, because of their serious side effects. However, their illegal use persists. Thus, their interaction with biomolecules such as bovine serum albumin (BSA) is of significance, especially the co-operative reaction of mixed ligands with the protein. Fluorescence and UV-vis spectra of complex mixtures of individual ligands, binary and ternary complexes with BSA resulted in significantly overlapping spectral profiles. Qualitative and quantitative information about the various complex ligand-protein species formed, was obtained with the resolution of the excitation-emission fluorescence three-way data matrices by chemometrics methods-MCR-ALS and PARAFAC. Individual spectra of the ligands, their binary complexes with BSA and their ternary complexes were extracted, and quantitative concentration profiles for each species in a particular interaction were constructed. Such analyses made it possible to interpret the role and behaviour of each reaction component. It was found that both ligands, RAC and CLEN, bound co-operatively in site I of the BSA. This was confirmed with the use of site markers such as warfarin (site I) and ibuprofen (site II). However, CLEN formed a 1:1 CLEN-BSA complex, while RAC formed a 2:1 RAC(2)-BSA binary species. Interestingly, when CLEN or RAC was added to RAC(2)-BSA or CLEN-BSA, respectively, ternary complexes were produced such as RAC(2)-BSA-CLEN. Significantly, the presence of the second ligand in such an interaction in excess, appeared to increase the affinity of the added ligand for BSA. This may have consequences on the amount of steroid required to achieve a desired tissue growth effect.

  10. Prediction of class membership of biodiesels using chemometrics.

    PubMed

    Mustafa, Zylia; Milina, Rumyana; Simeonova, Pavlina A; Tsakovski, Stefan L; Simeonov, Vasil D

    2015-01-01

    Recently, serious scientific and technological attention is paid to creation of alternative energy sources, including biofuels. The assessment of the quality of the biofuels produced and of the raw materials needed for the production technology is an important scientific challenge. One of the major sources for biodiesel production is plant oils material (sunflower, rapeseed, palm, soya etc.). Since plants are complex system from the biota it is not easy to find specific chemical components responsible for their ability to serve as biodiesels. The characterization and classification of plant sources as biofuel material could be reliably estimated only by the use of multivariate statistical approaches (chemometrics). The chemometric expertise makes it possible not only to classify different biofuel sources into similarity classes but also to predict the membership of unknown by origin chemically analyzed samples to already existing classes. The present study deals with the prediction of the class membership of several unknown by origin samples, which are included in a large data set with FAME profiles of biodiesel plant sources. Using a data set from chromatographic analysis of fatty acid methyl esters profiles (FAME) of different plant biodiesel sources and applying the chemometric technique know as partial least squares-discriminant analysis (PLS - DA) a pattern recognition procedure is developed to: I. Model classes of similarity of biodiesel plant sources using their FAME profiles not taking into account the samples with unknown origin; II. Classify correctly the samples with unknown origin to the previously defined classes of biodiesel sources (palm oil, soybean oil, peanut oil, rapeseed oil, sunflower oil and maize oil). The prediction is successfully achieved for all samples with previously unknown origin. This pattern recognition approach is applied for the first time in the field of biodiesel classification and modeling tasks.

  11. 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.

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

    ERIC Educational Resources Information Center

    Wanke, Randall; Stauffer, Jennifer

    2007-01-01

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

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

    ERIC Educational Resources Information Center

    Wanke, Randall; Stauffer, Jennifer

    2007-01-01

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

  14. Chemometric Methods for Biomedical Raman Spectroscopy and Imaging

    NASA Astrophysics Data System (ADS)

    Reddy, Rohith K.; Bhargava, Rohit

    The vibrational spectrum is a quantitative measure of a sample's molecular composition. Hence, classical chemometric methods, especially regression-based, have focused on exact mapping between identity and sample composition. While this approach works well for molecular identifications and scientific investigations, problems of biomedical interest often involve complex mixtures of stochastically varying compositions and complex spatial distributions of molecules contributing to the recorded signals. Hence, the challenge often is not to predict the identity of materials but to determine chemical markers that help rapidly detect species (e.g. impurities, conformations, strains of bacteria) in large areas or indicate changes in function in complex tissue (e.g. cancer or tissue engineering). Hence, the rate of data analysis has to be rapid, has to be robust with respect to stochastic variance and the provided information is usually related to biomedical context and not to molecular compositions. The emergence of imaging techniques and clinical applications are spurring growth in this area. In this chapter, we discuss chemometric methods that are useful in this milieu. We first review methods for data pre-processing with a focus on the key challenges facing a spectroscopist. Next, we survey some of the well known, widely used pattern classification techniques under the framework of supervised and unsupervised classification. We discuss the applicability, advantages and drawbacks of each of these techniques and help the reader not only gain useful insights into the techniques themselves but also acquire an understating of the underlying ideas and principles. We conclude by providing examples of the coupled use of chemometric and statistical tools to develop robust classification protocols for prostate and breast tissue pathology. We specifically focus on the critical factors and pitfalls at each step in converting spectral data sets into hi-fidelity images useful for

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

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

    PubMed

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

    2017-04-15

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

  17. 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.

  18. Chemometric characterization of river water quality.

    PubMed

    Kumari, Menka; Tripathi, Smriti; Pathak, Vinita; Tripathi, B D

    2013-04-01

    Various industrial facilities in the city of Varanasi discharge their effluent mixed with municipal sewage into the River Ganges at different discharge points. In this study, chemometric tools such as cluster analysis and box-whisker plots were applied to interpret data obtained during examination of River Ganges water quality. Specifically, we investigated the temperature (T), pH, total alkalinity, total acidity, electrical conductivity (EC), biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), nitrate nitrogen (N), phosphate (PO 4(2-) ), copper (Cu), cadmium (Cd), chromium (Cr), nickel (Ni), iron (Fe), lead (Pb), and zinc (Zn) in water samples collected from six sampling stations. Hierarchical agglomerative cluster analysis was conducted using Ward's method. Proximity distance between EC and Cr was the smallest revealing a relationship between these parameters, which was confirmed by Pearson's correlation. Based on proximity distances, EC, Cr, Ni, Fe, N, COD, temperature, BOD, and total acidity comprised one group; Zn, Pb, Cd, total alkalinity, Cu, and phosphate (PO 4(2-) ) were in another group; and DO and pH formed a separate group. These groups were confirmed by Pearson's correlation (r) values that indicated significant and positive correlation between variables in the same group. Box-whisker plots revealed that as we go downstream, the pollutant concentration increases and maximum at the downstream station Raj Ghat and minimum at the upstream station Samane Ghat. Seasonal variations in water quality parameters signified that total alkalinity, total acidity, DO, BOD, COD, N, phosphate (PO 4(2-) ), Cu, Cd, Cr, Ni, Fe, Pb, and Zn were the highest in summer (March-June) and the lowest during monsoon season (July-October). Temperature was the highest in summer and the lowest in winter (November-February). DO was the highest in winter and the lowest in summer season. pH was observed to be the highest in monsoon and the lowest in

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

    NASA Astrophysics Data System (ADS)

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

    2008-08-01

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

  20. 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.

  1. A Comparison of Blood-lead Level (BLL) in Opium-dependant Addicts With Healthy Control Group Using the Graphite Furnace/atomic Absorption Spectroscopy (GF-AAS) Followed by Chemometric Analysis.

    PubMed

    Amiri, Mojtaba; Amini, Ramin

    2012-08-01

    A comparison of oral/inhaled opium addicts with a healthy control group was investigated. Using the graphite furnace atomic absorption spectroscopy (GF-AAS) followed by chemometric analysis, sub-to-low µg L-1 concentrations of blood lead level (BLL) was detected in both the addict and the control groups. In this study, BLL of 78 subjects (Iranian volunteers) in two opium-addicted (patient group) and healthy control groups was evaluated. All the volunteers were men. The patient group was comprised of 39 patients who used opium orally or by inhalation with a mean age of 48.6 ± 7.3 years. The patient group was selected through systematic incidental sampling from 150 orally or by inhalation opium-addicted patients referred to Shariati Hospital located in Tehran .The control group (39 subjects) was matched with the patient group with regard to age and sex and with a mean age of 44.8 ± 5.6 years. The mean concentration of lead was found to be significantly lower (P = 0.0001) in control group (16.70 ± 12.51 μg/dL) compared to addicts (57.04 ± 46.03 μg/dL). When the addicts were divided into various age groups, there appeared to be a significant difference (p= 0.0451) in blood lead concentration as a function of age, however when the control group was considered, no difference was observed (P = 0.51). Also, a tendency (P = 0.048) towards increasing BLL with respect to BMI was observed due to drug consumption, but there was no significant variation between BLL concentration and BMI when the control group was considered (P = 0.35). It was observed that the BLL in opium-addicts was significantly higher than that of the healthy control group. The mean difference of both groups was statistically significant.

  2. Chemometrics: an important tool for monitoring interactions of vitamin B7 with bovine serum albumin with the aim of developing an efficient biosensing system for the analysis of protein.

    PubMed

    Gholivand, Mohammad-Bagher; Jalalvand, Ali R; Goicoechea, Hector C; Gargallo, Raimundo; Skov, Thomas

    2015-01-01

    For the first time, interaction of vitamin B7 (VB7) with bovine serum albumin (BSA) was investigated with the aim of developing a method for the analysis of BSA. The interaction of VB7 with BSA was investigated by cyclic voltammetry (CV), linear sweep voltammetry (LSV), and differential pulse voltammetry (DPV) at a multi-walled carbon nanotubes-modified glassy carbon electrode (MWCNTs/GCE). The recorded electrochemical data was combined with UVvis and fluorescence (F) spectroscopic data into a row- and column-wise augmented matrix and resolved by multivariate curve resolution-alternating least squares (MCR-ALS) as an efficient chemometric tool, and this assisted in the further elucidation of the above interaction. Also, with aid of MCR-BANDS method, the absence of rotational ambiguity was verified in the obtained results and we confirmed that the obtained results were unambiguous and reliable. The binding of VB7 to BSA was also modeled by molecular docking methods. Excellent agreement was found between the experimental and computational results. The differences of DPV responses of VB7 in the absence and presence of BSA (ΔI) were found to be linearly related to BSA concentration between 0.5×10(-9) mol L(-1) and 35.0×10(-9) mol L(-1), and a limit of detection (LOD, 3Sb/b) of 0.22×10(-9) mol L(-1) was calculated. Finally, the DPV method was further applied to the determination of serum albumin (SA) in serum samples obtained from Holstein cows and the results were in good agreement with those obtained by a medical diagnostic laboratory whose method was based on traditional cellulose acetate electrophoresis. The MWCNTs/GCE showed enhanced electron transfer kinetics, large electroactive surface area, and was highly sensitive, selective, and stable towards SA determination. The satisfactory analytical performance of the proposed method would make it potentially advantageous for a broad range of biosensing and clinical applications.

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

    PubMed

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

    2014-01-01

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

  4. Determination of antioxidant content and antioxidant activity in foods using infrared spectroscopy and chemometrics: a review.

    PubMed

    Lu, Xiaonan; Rasco, Barbara A

    2012-01-01

    Developing rapid analytical methods for bioactive components and predicting both the concentration and biological availability of nutraceutical components in foods is a topic of growing interest. Here, analysis of bioactive components and total antioxidant activity in food matrices using infrared spectroscopy coupled with chemometric predictive models is described. Infrared spectroscopy offers an alternative to wet chemistry, chromatographic determination of antioxidants, and in vitro biochemical assays for assessment of antioxidant activity. Spectroscopic methods provide a technique that can be used with biological tissues without extraction, which can often lead to degradation of the antioxidant components. Sample preparation time greatly decreases and analysis time is very short once a predictive model has been developed. Spectroscopic methods can have a high degree of precision when applied to analysis of nutraceutical compound concentration and antioxidant activity in foods. This article summarizes recent advances in vibrational spectroscopy and chemometrics and applications of these methods for antioxidant detection in foods.

  5. Iron-induced oxidative stress in a macrophyte: a chemometric approach.

    PubMed

    Sinha, Sarita; Basant, Ankita; Malik, Amrita; Singh, Kunwar P

    2009-02-01

    Iron-induced oxidative stress in plants of Bacopa monnieri L., a macrophyte with medicinal value, was investigated using the chemometric approach. Cluster analysis (CA) rendered two distinct clusters of roots and shoots. Discriminant analysis (DA) identified discriminating variables (NP-SH and APX) between the root and shoot tissues. Principal component analysis (PCA) results suggested that protein, superoxide dismutase (SOD), ascorbic acid, proline, and Fe uptake are dominant in root tissues, whereas malondialdehyde (MDA), guaiacol peroxidase (POD), cysteine, and non-protein thiol (NP-SH) in shoot of the stress plant. Discriminant partial-least squares (DPLS) results further confirmed that SOD and ascorbic acid contents dominated in root tissues, while NP-SH, cysteine, POD, ascorbate peroxidase (APX), and MDA in shoot. MDA and NP-SH were identified as most pronounced variables in plant during the highest exposure time. The chemometric approach allowed for the interpretation of the induced biochemical changes in plant tissues exposed to iron.

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

    PubMed

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

    2016-07-01

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

  7. Quality evaluation of Salvia miltiorrhiza Bge. by ultra high performance liquid chromatography with photodiode array detection and chemical fingerprinting coupled with chemometric analysis.

    PubMed

    Luo, Hongli; Kong, Weijun; Hu, Yichen; Chen, Ping; Wu, Xiaoru; Wan, Li; Yang, Meihua

    2015-05-01

    An ultra high performance liquid chromatography with photodiode array detection method is developed for the simultaneous quantitative determination of five water-soluble compounds including danshensu, protocatechualdehyde, rosmarinic acid, salvianolic acid B, and salvianolic acid A in Salvia miltiorrhiza Bge. Through method optimization, the five compounds all expressed good linearity (R(2) > 0.9990) in a wide concentration range together with satisfactory accuracy, precision, and stability. Moreover, through qualitative analysis of the chemical fingerprint combined with similarity analysis, hierarchical cluster analysis, principle component analysis, and partial least-squares discriminate analysis, we determined that the 13 batches of Salvia miltiorrhiza Bge. were similar in internal quality and the differences resulted from various cultivation environments, recovery elements, and others. Seen from the results of hierarchical cluster analysis and principle component analysis, the classification of 13 batches was in accordance, and partial least-squares discriminate analysis technique was more suitable than the principle component analysis model to provide a distinct classification of test samples on the basis of their different components. Moreover, a permutation test verified the rationality of partial least-squares discriminate analysis and variable importance plot showed that peaks 37 and 38 were the most significant variables in distinguishing the Salvia miltiorrhiza Bge. The idea of the quantitative and qualitative analysis of Salvia miltiorrhiza Bge. was convenient, sensitive, and comprehensive, which could be applied to evaluate the quality of more traditional Chinese medicines. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. 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

  9. A chemometric approach to the characterisation of historical mortars

    SciTech Connect

    Rampazzi, L. . E-mail: laura.rampazzi@uninsubria.it; Pozzi, A.; Sansonetti, A.; Toniolo, L.; Giussani, B.

    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 features of specimens and samples. A Partial Least Square (PLS1) regression was done in order to predict the binder/aggregate ratio. The model was applied to historical mortars from the churches of St. Lorenzo (Milan) and St. Abbondio (Como). The accordance between the predictive model and the real samples is discussed.

  10. Application of fluorescence spectroscopy and chemometrics in the evaluation of processed cheese during storage.

    PubMed

    Christensen, J; Povlsen, V T; Sørensen, J

    2003-04-01

    Front face fluorescence spectroscopy is applied for an evaluation of the stability of processed cheese during storage. Fluorescence landscapes with excitation from 240 to 360 nm and emission in the range of 275 to 475 nm were obtained from cheese samples stored in darkness and light in up to 259 d, at 5, 20 and 37 degrees C, respectively. Parallel factor (PARAFAC) analysis of the fluorescence landscapes exhibits four fluorophores present in the cheese, all related to the storage conditions. The chemometric analysis resolves the fluorescence signal into excitation and emission profiles of the pure fluorescent compounds, which are suggested to be tryptophan, vitamin A and a compound derived from oxidation. Thus, it is concluded that fluorescence spectroscopy in combination with chemometrics has a potential as a fast method for monitoring the stability of processed cheese.

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

    PubMed

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

    2016-08-01

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

  12. 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…

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

    USDA-ARS?s Scientific Manuscript database

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

  14. 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…

  15. Characteristic fingerprint based on gingerol derivative analysis for discrimination of ginger (Zingiber officinale) according to geographical origin using HPLC-DAD combined with chemometrics.

    PubMed

    Yudthavorasit, Soparat; Wongravee, Kanet; Leepipatpiboon, Natchanun

    2014-09-01

    Chromatographic fingerprints of gingers from five different ginger-producing countries (China, India, Malaysia, Thailand and Vietnam) were newly established to discriminate the origin of ginger. The pungent bioactive principles of ginger, gingerols and six other gingerol-related compounds were determined and identified. Their variations in HPLC profiles create the characteristic pattern of each origin by employing similarity analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA) and linear discriminant analysis (LDA). As results, the ginger profiles tended to be grouped and separated on the basis of the geographical closeness of the countries of origin. An effective mathematical model with high predictive ability was obtained and chemical markers for each origin were also identified as the characteristic active compounds to differentiate the ginger origin. The proposed method is useful for quality control of ginger in case of origin labelling and to assess food authenticity issues. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Assessment of heavy metal contamination in Hindon River sediments: a chemometric and geochemical approach.

    PubMed

    Chabukdhara, Mayuri; Nema, Arvind K

    2012-05-01

    The aim of this study was to assess the level of heavy metals (Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) in the surface sediments of the Hindon River, India that receives both treated and untreated municipal and industrial discharges generated in and around Ghaziabad, India. Mean metals concentrations (mg kg(-1)) were in the range of; Cu: 21.70-280.33, Cd: 0.29-6.29, Fe: 4151.75-17318.75, Zn: 22.22.50-288.29, Ni: 13.90-57.66, Mn: 49.55-516.97, Cr: 17.48-33.70 and Pb: 27.56-313.57 respectively. Chemometric analysis was applied to identify contribution sources by heavy metals while geochemical approaches (enrichment factor and geo-accumulation index) were exploited for the assessment of the enrichment and contamination level of heavy metals in the river sediments. Chemometric analysis suggested anthropic origin of Cu, Cd, Pb, Zn, and Ni while Fe showed lithogenic origin. Mn and Cr was associated and controlled by mixed origin. Geochemical approach confirms the anthropogenic influence of heavy metal pollution in the river sediments. The study suggests that a complementary approach that integrates chemometric analysis, sediment quality criteria, and geochemical investigation should be considered in order to provide a more accurate appraisal of the heavy metal pollution in river sediments. Consequently, it may serve to undertake and design effective strategies and remedial measures to prevent further deterioration of the river ecosystem in future.

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

    NASA Astrophysics Data System (ADS)

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

    2017-05-01

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

  18. Characterization and classification of pseudo-stationary phases in micellar electrokinetic chromatography using chemometric methods.

    PubMed

    Fu, Cexiong; Khaledi, Morteza G

    2014-03-04

    Two types of chemometric methods, principal component analysis (PCA) and cluster analysis, are employed to characterize and classify a total of 70 pseudostationary phases (54 distinct systems and 16 decoy systems) in micellar electrokinetic chromatography (MEKC). PCA excels at removing redundant information for micellar phase characterization and retaining principal determinants for phase classification. While PCA is useful in the characterization of micelle selectivities, it is ineffective in defining the grouping of micellar phases. Hierarchical clustering yields a complete dendrogram of cluster structures but provides only limited cluster characterizations. The combination of these two chemometric methods leads to a comprehensive interpretation of the micellar phase classification. Moreover, the k-means analysis can further discern subtle differences among those closely located micellar phases. All three chemometric methods result in similar classifications with respect to the similarities and differences of the 70 micelle systems investigated. These systems are categorized into 3 major clusters: fluoro-surfactants represent cluster I, identified as strong hydrogen bond donors and dipolar but weak hydrogen bond acceptors. Cluster II includes sulfonated acrylamide/acrylate copolymers and surfactants with trimethylammonium head groups, characterized by strong hydrophobicity (v) and weak hydrogen bond acidity (b). The last cluster consists of two subclusters: clusters III and IV. Cluster III includes siloxane-based polymeric micelles, exhibiting weak hydrophobicity and medium hydrogen bond acidity and basicity (a), and the cluster IV micellar systems are characterized by their strong hydrophobicity and medium hydrogen bond acidity and basicity but rather weak dipolarity. Cluster III differs from cluster IV by its slightly weaker hydrophobicity and hydrogen bond donating capability. The classification by chemometric methods is in good agreement with the

  19. Comparative analysis of the volatile components in cut tobacco from different locations with gas chromatography-mass spectrometry (GC-MS) and combined chemometric methods.

    PubMed

    Huang, Lan-Fang; Zhong, Ke-Jun; Sun, Xian-Jun; Wu, Ming-Jian; Huang, Ke-Long; Liang, Yi-Zeng; Guo, Fang-Qiu; Li, Ya-Wen

    2006-08-11

    A combined approach of subwindow factor analysis and orthogonal projection resolution was used to analyze the volatile components of cut tobacco samples from different sources. After extracted with simultaneous distillation and extraction method, the volatile components in cut tobacco from five different locations were detected by GC-MS. Then, the qualitative and quantitative analysis of the volatile components of cut tobacco from Changde area was completed with the help of subwindow factor analysis resolving two-dimensional original data into pure mass spectra and chromatograms. One hundred and two volatile components among 138 separated peaks were identified and quantified, accounting for about 88.90% of the total content. Finally, orthogonal projection method was used to extract the common peaks from different locations. Among the identified components, there were 74 components coexisting in five studied samples although the relative content of each component showed difference to some extent. The results showed a fair consistency in their GC-MS fingerprints. It was the first time to apply orthogonal projection method to compare different cut tobacco samples, and it reduced the burden of qualitative analysis as well as the subjectivity. The obtained results proved the combined approach powerful for the analysis of complex cut tobacco samples. The developed method can be used to compare the sameness and differences of cut tobacco from different sources and for quality control of cigarette production and materials.

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

    PubMed

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

    2015-07-01

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

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

    PubMed

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

    2016-11-01

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

  2. 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.

  3. Tea classification and quality assessment using laser-induced fluorescence and chemometric evaluation.

    PubMed

    Mei, Liang; Lundin, Patrik; Brydegaard, Mikkel; Gong, Shuying; Tang, Desong; Somesfalean, Gabriel; He, Sailing; Svanberg, Sune

    2012-03-01

    Laser-induced fluorescence was used to evaluate the classification and quality of Chinese oolong teas and jasmine teas. The fluorescence of four different types of Chinese oolong teas-Guangdong oolong, North Fujian oolong, South Fujian oolong, and Taiwan oolong was recorded and singular value decomposition was used to describe the autofluoresence of the tea samples. Linear discriminant analysis was used to train a predictive chemometric model and a leave-one-out methodology was used to classify the types and evaluate the quality of the tea samples. The predicted classification of the oolong teas and the grade of the jasmine teas were estimated using this method. The agreement between the grades evaluated by the tea experts and by the chemometric model shows the potential of this technique to be used for practical assessment of tea grades.

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

    USDA-ARS?s Scientific Manuscript database

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

  5. 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...

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

    PubMed

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

    2017-08-15

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

  7. PIXE analysis of PM2.5 and PM(2.5-10) for air quality assessment of Islamabad, Pakistan: application of chemometrics for source identification.

    PubMed

    Waheed, Shahida; Jaafar, Muhammad Z; Siddique, Naila; Markwitz, Andreas; Brereton, Richard G

    2012-01-01

    A Gent sampler was used to collect 379 pairs of filters from Nilore, a suburban area of Islamabad city. The study was designed to assess the concentration variations of trace elements in fine and coarse particulate matter due to anthropogenic activities and naturally occurring events. Source identification was performed by applying MATLAB software for principal component analysis (PCA), and cluster analysis (CA). The average fine and coarse particulate masses during the study period were 15.1 ± 11.9 and 37.3 ± 28.0 μg/m(3) respectively which complies with the 24-h air quality limits set by the government of Pakistan. The application of PCA to PM(2.5) data suggests the PM contribution from sources such as soil, automobile exhaust and coal combustion, road dust and wearing of tyres, wood combustion, biomass burning and fertilizers and fungicides whereas for the PM(2.5-10) data shows signatures of suspended soil, automobile exhaust, road dust and wearing of tyres, wood and biomass burning, refuse incineration, Ni smelter, fertilizers and fungicides are obtained. Cluster analysis of PM(2.5) and PM(2.5-10) datasets reveals that there are mainly three contributory pollution sources and these are suspended soil particles, automobile related sources and wood and coal combustion.

  8. Evolving window zone selection method followed by independent component analysis as useful chemometric tools to discriminate between grapefruit juice, orange juice and blends.

    PubMed

    Cuny, M; Le Gall, G; Colquhoun, I J; Lees, M; Rutledge, D N

    2007-08-06

    This study investigates the use of high resolution 1H NMR as a suitable alternative to the standard chromatographic method for the determination of adulteration of orange juice (Citrus sinensis) with grapefruit juice (Citrus paradisi) based on flavonoid glycoside content. Fifty-nine orange juices (OJ), 23 grapefruit juices (GJ) and 10 blends (OG), obtained from local retail outlets were used to assess the performance of the 1H NMR method. The work presented here introduces the Evolving Window Zone Selection (EWZS) function that holds promise for the automatic detection of spectral regions tailored to discriminate predefined groups. This technique was applied on the pre-processed 1H NMR spectra of the 92 juices. Independent Component Analysis (ICA) is a good alternative to Principal Component Analysis (PCA) for recovering linearly-mixed unobserved multidimensional independent signals and has been used in this study to build supervised models that classify the samples into three categories, OJ, GJ, OG. The regions containing the known flavonoid glycoside markers were selected as well as another zone containing the signals of sucrose, alpha-glucose and other components that were tentatively attributed. ICA was applied on three different groups of selected variables and showed good results for both discrimination and interpretation of the signals. Up to 97.8% of the juices were correctly attributed. This method gave better results than the commonly used PCA method. In addition, the time required to carry out the 1H NMR analysis was less than half the time of the standard chromatographic method.

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

    PubMed

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

    2014-01-08

    The analysis of the effect of cultivar and olive leaves addition before the extraction on the different analytical values revealed significant differences (p < 0.05) in some parameters, mainly in peroxide value, phenols and tocopherol contents, and oxidative stability. Aroma profiles were also influenced by the different varieties and the addition of different amounts (0% and 3%) of olive leaves. Twenty-three compounds were characterized, representing 86.1-99.2% of the total volatiles. Chétoui cultivar has the highest amount of (E)-2-hexenal, followed by Chemlali cultivar, whereas (E)-2-hexen-1-ol was the major constituent of Zalmati and crossbreeding Chemlali by Zalmati cultivars. Sensory analysis showed that Chemlali and Chétoui Zarzis possessed a high fruity, bitter, and pungent taste, whereas the Zalmati and crossbreeding Chemlali by Zalmati had a 'green' taste among its attributes. Indeed, the taste panel found an improvement of the oil quality when an amount of olive leaves (3%) added to the olives fruits.

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

    PubMed Central

    Śliwińska, Magdalena; Namieśnik, Jacek; Wardencki, Waldemar; Dymerski, Tomasz

    2016-01-01

    Spirit beverages are a diverse group of foodstuffs. They are very often counterfeited which cause the appearance of low quality products or wrongly labelled products on the market. It is important to find a proper quality control and botanical origin method enabling the same time preliminary check of the composition of investigated samples, which was the main goal of this work. For this purpose, the usefulness of electronic nose based on ultra-fast gas chromatography (fast GC e-nose) was verified. A set of 24 samples of raw spirits, 33 samples of vodkas, and 8 samples of whisky were analysed by fast GC e-nose. Four data analysis methods were used. The PCA was applied for the visualization of dataset, observation of the variation inside groups of samples, and selection of variables for the other three statistical methods. The SQC method was utilized to compare the quality of the samples. Both the DFA and SIMCA data analysis methods were used for discrimination of vodka, whisky, and spirits samples. The fast GC e-nose combined with four statistical methods can be used for rapid discrimination of raw spirits, vodkas, and whisky and in the same for preliminary determination of the composition of investigated samples. PMID:27446633

  11. Virtually nonexistent correlation between the OH stretching frequency and the instantaneous geometry in the short hydrogen bond of sodium hydrogen bis(sulfate): advanced chemometrics analysis.

    PubMed

    Pirc, Gordana; Mavri, Janez; Novič, Marjana; Stare, Jernej

    2012-06-21

    We examined the correlation between the dynamically sampled anharmonic frequency of the OH stretching motion and the corresponding instantaneous geometric parameters associated with the structure of crystalline sodium hydrogen bis(sulfate), which is a benchmark system with an extremely short hydrogen bond. We analyzed the trajectory obtained by a conventional Car-Parrinello molecular dynamics simulation, followed by an a posteriori quantization of the proton motion. For statistical analysis we applied the established methodologies of multiple linear regression, principal component analysis, principal component regression, and Kohonen neural networks. No simple correlation scheme between the OH stretching frequency and any particular geometry parameter (or their combination) was found. In comparison to the established correlation schemes (e.g., Mikenda and Novak) that consider a series of systems, our study provides a complementary insight into the nature of hydrogen bonding of a single system, in the sense that it considers the important aspects of fluctuations of the environment and the resulting broadening of the OH stretching band, which cannot be adequately assessed by experiment. The absence of appreciable correlations gives strong evidence of the extreme complexity of short hydrogen bonding.

  12. High-performance liquid chromatography with photodiode array detection and chemometrics method for the analysis of multiple components in the traditional Chinese medicine Shuanghuanglian oral liquid.

    PubMed

    Li, Bao Qiong; Chen, Jing; Li, Jiao Jiao; Wang, Xue; Zhai, Hong Lin; Zhang, Xiao Yun

    2015-12-01

    Shuanghuanlian oral liquid, a traditional Chinese medicine preparation, is a mixture of three herbs (Flos Lonicerae, Radix Scutellariae and Fructus Forsythiae). In this study, the quantitative analysis of three main active compounds, chlorogenic acid, forsythin and baicalin in samples from different manufacturers was performed rapidly by high-performance liquid chromatography coupled with photodiode array detection followed by Contour Projection coupled to stepwise regression treatment of the obtained three-dimensional spectra in which the partial overlap between adjacent target components existed. The method was validated for linearity (R>0.9940), precision (RSD<1.25%), recovery (92.20-102.50%), limit of detection (0.01-0.02 μg/mL) and limit of quantification (0.03-0.07 μg/mL). The results indicated that the combination of the three-dimensional spectra of traditional Chinese medicine and Contour Projection-stepwise regression offered an accurate, simple, low-cost and eco-friendly way for the rapid quantitative analysis of Shuanghuanlian oral liquid samples.

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

    PubMed

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

    2016-01-01

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

  14. 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.

  15. Chemometric characterization of sunflower seeds.

    PubMed

    Monferrere, Gastón Lancelle; Azcarate, Silvana Mariela; Cantarelli, Miguel Ángel; Funes, Israel German; Camiña, José Manuel

    2012-09-01

    The spectroscopic characterization of different varieties of sunflower seeds based on their oleic acid content is proposed. One hundred fifty samples of sunflower seeds from different places of Argentina were analyzed by near-infrared diffuse reflectance spectroscopy (NIRDRS). Seed samples were grounded and sieved without chemical treatment previous to the analysis. For the characterization, the used multivariate methods were: principal component analysis (PCA), cluster analysis (CA), linear discriminant analysis (LDA), and partial least square discriminant analysis (PLS-DA). By using PCA, CA, and LDA, and from the point of view of varieties of sunflower seeds, 2 groups were differentiated, based on the concentration of oleic acid: a low oleic group, which ranged from 15% to 25% w/w oleic acid; and the other one (mid-high oleic varieties) which ranged from 26% to 90% w/w oleic acid. However, by using the PLS-DA, 3 groups were correctly differentiated based on the concentration of oleic acid: low oleic (from 15% to 25% w/w oleic acid); mid oleic (26% to 76% w/w oleic acid); and high oleic (≥ than 77% w/w oleic acid), demonstrating the high classification ability of this method. This multivariate characterization of sunflower seed varieties did not require chromatographic analysis to generate the matrix of concentrations, and only direct measures of NIRDRS spectra were required. This characterization can be useful to quickly know the variety of sunflower seed in the grain market. Practical Applications: This manuscript describes a method to determine 3 varieties of sunflower seeds (high, mid, and low oleic) The advantage of this method is to avoid the use of techniques that require long-time analysis. © 2012 Institute of Food Technologists®

  16. Merging a sensitive capillary electrophoresis-ultraviolet detection method with chemometric exploratory data analysis for the determination of phenolic acids and subsequent characterization of avocado fruit.

    PubMed

    Hurtado-Fernández, Elena; Contreras-Gutiérrez, Paulina K; Cuadros-Rodríguez, Luis; Carrasco-Pancorbo, Alegría; Fernández-Gutiérrez, Alberto

    2013-12-15

    Herein we present the development of a powerful CE-UV method able to detect and quantify an important number of phenolic acids in 13 varieties of avocado fruits at 2 ripening stages. All the variables involved in CE separation were exhaustively optimized and the best results were obtained with a capillary of 50 μm i.d. × 50 cm effective length, sodium tetraborate 40 mM at a pH of 9.4, 30 kV, 25 °C, 10s of hydrodynamic injection (0.5 psi) and UV detection at 254 nm. This optimal methodology was fully validated and then applied to different avocado samples. The number of phenolic acids determined varied from 8 to 14 compounds; in general, they were in concentrations ranging from 0.13 ppm to 3.82 ppm, except p-coumaric, benzoic and protocatechuic acids, which were found at higher concentrations. Principal component analysis (PCA) was applied to highlight the differences between varieties and ripening degrees, looking for the most influential analytes.

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

    PubMed

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

    2014-05-15

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

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

    PubMed

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

    2016-05-15

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

  1. Chemometrics applied to the analysis of induced phytochelatins in Hordeum vulgare plants stressed with various toxic non-essential metals and metalloids.

    PubMed

    Dago, Àngela; González, Inmaculada; Ariño, Cristina; Díaz-Cruz, José Manuel; Esteban, Miquel

    2014-01-01

    Hordeum vulgare plants were stressed with Hg, Cd and As and their phytotoxicity was evaluated in terms of growth inhibition and total metal uptake by the plant. The synthesised phytochelatins ((γ-Glu-Cys)n-Gly, n=2-5; PCs) were determined by HPLC with amperometric detection at a glassy carbon electrode. The results indicate that H. vulgare is a good phytostabilisation plant due to its capacity to accumulate heavy metals in roots. Cd and Hg are the most uptake toxic elements, being Cd the most potent inducer of PCs. The data obtained on the different PCs and related peptides induced by each heavy metal were used to perform a Principal Component Analysis (PCA) of the results as a function of the contaminating toxic element or its concentration level. The nature of the stressor element could be predicted from the pattern of PCs and related peptides identified by PCA. PCs were the most strongly induced peptides under Cd and Hg stress, whereas As only tended to synthesise small thiols such as glutathione and γ-glutamylcysteine, both precursors of PCs synthesis. This finding indicates that PCs are induced at different rates depending on the metal stressor used. © 2013 Elsevier B.V. All rights reserved.

  2. A feasibility study on quantitative analysis of glucose and fructose in lotus root powder by FT-NIR spectroscopy and chemometrics.

    PubMed

    Niu, Xiaoying; Zhao, Zhilei; Jia, Kejun; Li, Xiaoting

    2012-07-15

    The feasibility of rapid analysis of glucose and fructose in lotus root powder by Fourier transform near-infrared (FT-NIR) spectroscopy was studied. Diffuse reflectance spectra were collected between 4000 and 12,432cm(-1). Calibration models established by partial least-squares regression (PLSR), interval PLS of forward (FiPLS) and backward (BiPLS), back propagation-artificial neural networks (BP-ANN) and least squares-support vector machine (LS-SVM) were compared. The optimal models for glucose and fructose were obtained by LS-SVM with the first 10 latent variables (LVs) as input. For fructose the correlation coefficients of calibration (rc) and prediction (rp), the root-mean-square errors of calibration (RMSEC) and prediction (RMSEP), and the residual predictive deviation (RPD) were 0.9827, 0.9765, 0.107%, 0.115% and 4.599, respectively. For glucose the indexes were 0.9243, 0.8286, 0.543%, 0.812% and 1.785. The results indicate that NIR spectroscopy technique with LS-SVM offers effective quantitative capability for glucose and fructose in lotus root powder. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

    PubMed

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

    2015-03-01

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

  4. Chemometric Analysis of Gas Chromatography – Mass Spectrometry Data using Fast Retention Time Alignment via a Total Ion Current Shift Function

    SciTech Connect

    Nadeau, Jeremy S.; Wright, Bob W.; Synovec, Robert E.

    2010-04-15

    A critical comparison of methods for correcting severely retention time shifted gas chromatography-mass spectrometry (GC-MS) data is presented. The method reported herein is an adaptation to the Piecewise Alignment Algorithm to quickly align severely shifted one-dimensional (1D) total ion current (TIC) data, then applying these shifts to broadly align all mass channels throughout the separation, referred to as a TIC shift function (SF). The maximum shift varied from (-) 5 s in the beginning of the chromatographic separation to (+) 20 s toward the end of the separation, equivalent to a maximum shift of over 5 peak widths. Implementing the TIC shift function (TIC SF) prior to Fisher Ratio (F-Ratio) feature selection and then principal component analysis (PCA) was found to be a viable approach to classify complex chromatograms, that in this study were obtained from GC-MS separations of three gasoline samples serving as complex test mixtures, referred to as types C, M and S. The reported alignment algorithm via the TIC SF approach corrects for large dynamic shifting in the data as well as subtle peak-to-peak shifts. The benefits of the overall TIC SF alignment and feature selection approach were quantified using the degree-of-class separation (DCS) metric of the PCA scores plots using the type C and M samples, since they were the most similar, and thus the most challenging samples to properly classify. The DCS values showed an increase from an initial value of essentially zero for the unaligned GC-TIC data to a value of 7.9 following alignment; however, the DCS was unchanged by feature selection using F-Ratios for the GC-TIC data. The full mass spectral data provided an increase to a final DCS of 13.7 after alignment and two-dimensional (2D) F-Ratio feature selection.

  5. Three-dimensional voltammetry: a chemometrical analysis of electrochemical data for determination of dopamine in the presence of unexpected interference by a biosensor based on gold nanoparticles.

    PubMed

    Khoobi, Asma; Ghoreishi, Sayed Mehdi; Behpour, Mohsen; Masoum, Saeed

    2014-09-16

    Multivariate curve resolution by alternating least-squares (MCR-ALS) was used for voltammetric determination of dopamine (DA) in the presence of epinephrine (EP) at a gold nanoparticles chemically modified carbon paste electrode (AuNPs/CPE). Scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), and cyclic voltammetry (CV) techniques were applied for characterization of the nanostructure modified electrode. Central composite rotatable design (CCRD) was employed to generate an experimental program to offer data to model the effects of different parameters on voltammetric responses. Response surface methodology (RSM) was applied to show the individual and interactive effects of chemical and instrumental variables at five levels, combined according to CCRD. For determination of DA in the presence of unexpected interference, three-way data were achieved from various pulse heights in differential pulse voltammetry (DPV) technique. This type of data construction, analyzed by MCR-ALS, makes it possible to exploit the so-called "second-order advantage". The second-order advantage provided unbiased results even in the presence of electroactive interferences with highly overlapped peaks. Also, an algorithm was applied to correct the detected potential shift in the voltammetric data. The voltammograms of the samples were then deposited in an augmented data matrix (column-wise) and subsequently analyzed by MCR-ALS. The effect of rotational ambiguity associated with a particular MCR-ALS solution under a set of constraints was also studied. The proposed method could be applied for the determination of DA and EP in the presence of each other in a wide concentration range of 0.1-205.0 μM, and the detection limit of DA has been found to be 35.5 nM. Finally, the technique has been used for the reliable analysis of DA in real samples.

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

    PubMed

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

    2014-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-09-01

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

  8. Bioreactor monitoring with spectroscopy and chemometrics: a review.

    PubMed

    Lourenço, N D; Lopes, J A; Almeida, C F; Sarraguça, M C; Pinheiro, H M

    2012-09-01

    Biotechnological processes are crucial to the development of any economy striving to ensure a relevant position in future markets. The cultivation of microorganisms in bioreactors is one of the most important unit operations of biotechnological processes, and real-time monitoring of bioreactors is essential for effective bioprocess control. In this review, published material on the potential application of different spectroscopic techniques for bioreactor monitoring is critically discussed, with particular emphasis on optical fiber technology, reported for in situ bioprocess monitoring. Application examples are presented by spectroscopy type, specifically focusing on ultraviolet-visible, near-infrared, mid-infrared, Raman, and fluorescence spectroscopy. The spectra acquisition devices available and the major advantages and disadvantages of each spectroscopy are discussed. The type of information contained in the spectra and the available chemometric methods for extracting that information are also addressed, including wavelength selection, spectra pre-processing, principal component analysis, and partial least-squares. Sample handling techniques (flow and sequential injection analysis) that include transport to spectroscopic sensors for ex-situ on-line monitoring are not covered in this review.

  9. Raman Spectroscopy and Chemometrics Applied to Recycled Polyethylene Terephthalate

    NASA Astrophysics Data System (ADS)

    Silva, Edmir Augusto

    For decades, polyester polymer has maintained its position as the polymer of choice for multiple applications. Recently, recycling of polyester has become very popular. Given the challenge of process control, this dissertation suggests Raman spectroscopy as a viable soft, non-destructive analysis tool for discrimination and potential characterization of the melt stream. This research found that Raman can be applied to recycled Polyethylene Terephthalate (PET) to ameliorate the production off-quality materials by predicting melt viscosity and detecting polymer contaminants. It was found that melt temperature and melt pressure could be predicted using Chemometrics tools, such as OPLS, when spectra were collected from a Raman probe facing the melt in a polyester extruder. This work opens the door to the usage of spectrometer in the extrusion field more often than it is today; most of the Raman work published in polyester is regarding crystallinity. This thesis will list some of those, but none of the existing literature spends time showing how to predict melt viscosity, for example. This dissertation will show how to calculate it from the melt pressure. In the future a lot more important information can be extracted from the same system described here due to the system proposed: spectrometer, probe, statistical method for pre and post processing the data and predictive model.

  10. 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.

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

    PubMed

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

    2015-04-01

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

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

    PubMed

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

    2015-08-10

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

  13. 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

  14. 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.

  15. 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.

  16. Chemometric tools for identification of volatile aroma-active compounds in oregano.

    PubMed

    Bansleben, Anne-Christin; Schellenberg, Ingo; Einax, Jürgen W; Schaefer, Kristin; Ulrich, Detlef; Bansleben, David

    2009-11-01

    One of the purposes of chemical analysis is to find quick and efficient methods to answer complex analytical questions in the life sciences. New analytical methods, in particular, produce a flood of data which are often very badly arranged. An effective way to overcome this problem is to apply chemometric methods. As part of the following investigations, three brands of oregano were analysed to identify their volatile aroma-active compounds. Two techniques were applied--gas chromatograpy-olfactometry (GC-O) and human sensory evaluation. Aroma-impact compounds could be identified in the main brands of oregano with the aid of chemometric methods (principal-components analysis, hierarchical cluster analysis, linear discriminant analysis, partial least-squares regression). Therefore, it is possible to reduce the analysis of sensory and olfactometry to relevant attributes. This makes classifying new species easier, much faster, and less expensive and is the premise for quick and more economic identification of new potential genotypes for oregano plant breeding. A comprehensive list of oregano key odourants, determined by GC-O and human sensory evaluation using different methods of supervised and unsupervised pattern cognition, has not previously been published.

  17. 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.

  18. 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...

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

    NASA Astrophysics Data System (ADS)

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

    2017-05-01

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

  20. [Discrimination of donkey meat by NIR and chemometrics].

    PubMed

    Niu, Xiao-Ying; Shao, Li-Min; Dong, Fang; Zhao, Zhi-Lei; Zhu, Yan

    2014-10-01

    Donkey meat samples (n = 167) from different parts of donkey body (neck, costalia, rump, and tendon), beef (n = 47), pork (n = 51) and mutton (n = 32) samples were used to establish near-infrared reflectance spectroscopy (NIR) classification models in the spectra range of 4,000~12,500 cm(-1). The accuracies of classification models constructed by Mahalanobis distances analysis, soft independent modeling of class analogy (SIMCA) and least squares-support vector machine (LS-SVM), respectively combined with pretreatment of Savitzky-Golay smooth (5, 15 and 25 points) and derivative (first and second), multiplicative scatter correction and standard normal variate, were compared. The optimal models for intact samples were obtained by Mahalanobis distances analysis with the first 11 principal components (PCs) from original spectra as inputs and by LS-SVM with the first 6 PCs as inputs, and correctly classified 100% of calibration set and 98. 96% of prediction set. For minced samples of 7 mm diameter the optimal result was attained by LS-SVM with the first 5 PCs from original spectra as inputs, which gained an accuracy of 100% for calibration and 97.53% for prediction. For minced diameter of 5 mm SIMCA model with the first 8 PCs from original spectra as inputs correctly classified 100% of calibration and prediction. And for minced diameter of 3 mm Mahalanobis distances analysis and SIMCA models both achieved 100% accuracy for calibration and prediction respectively with the first 7 and 9 PCs from original spectra as inputs. And in these models, donkey meat samples were all correctly classified with 100% either in calibration or prediction. The results show that it is feasible that NIR with chemometrics methods is used to discriminate donkey meat from the else meat.

  1. 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.

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

    PubMed

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

    2012-10-01

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

  3. Rapid characterization and quality control of complex cell culture media solutions using raman spectroscopy and chemometrics.

    PubMed

    Li, Boyan; Ryan, Paul W; Ray, Bryan H; Leister, Kirk J; Sirimuthu, Narayana M S; Ryder, Alan G

    2010-10-01

    The use of Raman spectroscopy coupled with chemometrics for the rapid identification, characterization, and quality assessment of complex cell culture media components used for industrial mammalian cell culture was investigated. Raman spectroscopy offers significant advantages for the analysis of complex, aqueous-based materials used in biotechnology because there is no need for sample preparation and water is a weak Raman scatterer. We demonstrate the efficacy of the method for the routine analysis of dilute aqueous solution of five different chemically defined (CD) commercial media components used in a Chinese Hamster Ovary (CHO) cell manufacturing process for recombinant proteins.The chemometric processing of the Raman spectral data is the key factor in developing robust methods. Here, we discuss the optimum methods for eliminating baseline drift, background fluctuations, and other instrumentation artifacts to generate reproducible spectral data. Principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA) were then employed in the development of a robust routine for both identification and quality evaluation of the five different media components. These methods have the potential to be extremely useful in an industrial context for "in-house" sample handling, tracking, and quality control.

  4. Chemometric tools to highlight non-intentionally added substances (NIAS) in polyethylene terephthalate (PET).

    PubMed

    Kassouf, Amine; Maalouly, Jacqueline; Chebib, Hanna; Rutledge, Douglas N; Ducruet, Violette

    2013-10-15

    In an effort to identify non-intentionally added substances (NIAS), which is still a challenging task for analytical chemists, PET pellets, preforms and bottles were analyzed by an optimized headspace solid phase microextraction coupled to gas chromatography-mass spectrometry (HS-SPME/GC-MS). Fingerprints obtained by the proposed method were analyzed by three chemometric tools: Principal Components Analysis (PCA), Independent Components Analysis (ICA) and a multi-block method (Common Components and Specific Weights Analysis CCSWA) in order to extract pertinent variations in NIAS concentrations. Total ion current (TIC) chromatograms were used for PCA and ICA while extracted ion chromatograms (EIC) were used for CCSWA, each ion corresponding to a block. PCA managed to discriminate pellets and preforms from bottles due to several NIAS. Volatiles like 2-methyl-1,3-dioxolane, ethylene glycol, ethylbenzene and xylene were responsible for the discrimination of pellets and preforms. Less volatile compounds like linear aldehydes and phthalates were responsible for the discrimination of bottles. ICA showed more specific discriminations especially for bottles and pellets while CCSWA managed to discriminate preforms. The proposed methodology, combining HS-SPME/GC-MS with chemometric tools proved its efficiency in highlighting NIAS in PET samples in a relatively simple and fast approach compared to classical techniques.

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

    PubMed

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

    2017-06-15

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

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  8. Classification of washing powder brands using near-infrared spectroscopy combined with chemometric calibrations.

    PubMed

    Zhang, Hongguang; Yang, Qinmin; Lu, Jiangang

    2014-01-01

    In this study, near-infrared (NIR) spectroscopy is applied for rapid and objective classification of 5 different brands of washing powder. Chemometric calibrations including partial least square discriminant analysis (PLS-DA), back propagation neural network (BP-NN) and least square support vector machine (LS-SVM) are investigated and compared to achieve an optimal result. Firstly, principal component analysis (PCA) is conducted to visualize the difference among washing powder samples of different brands and principal components (PCs) are extracted as inputs of BP-NN and LS-SVM models. The number of PCs and parameters of such models are optimized via cross validation. In experimental studies, a total of 225 spectra of washing powder samples (45 samples for each brand) were used to build models and 75 spectra of washing powder samples (15 samples for each brand) were used as the validation set to evaluate the performance of developed models. As for the comparison of the three investigated models, both BP-NN model and LS-SVM model successfully classified all samples in validation set according to their brands. However, the PLS-DA model failed to achieve 100% of classification accuracy. The results obtained in this investigation demonstrate that NIR spectroscopy combined with chemometric calibrations including BP-NN and LS-SVM can be successfully utilized to classify the brands of washing powder.

  9. 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.

  10. Chemometrics for the classification and calibration of seawater using the H+ affinity spectrum.

    PubMed

    Kortazar, L; Sáez, J; Astigarraga, E; Goienaga, N; Fernández, L

    2013-11-15

    In 1819 Alexander Marcet proposed that seawater contains small amounts of all soluble substances and that the relative abundances of some of them were constant. This hypothesis is nowadays known as Marcet's Principle or the principle of constancy of the composition of seawater. Based on this principle, the present research tried to prove that it is possible to detect polluted seawater samples using the seawater H(+) affinity spectrum by the application of the possibilities provided by chemometric tools. Seawater samples were classified using the principal component analysis (PCA) of the HBound spectra of the samples. It was concluded that the sampling points location does not have any influence in the cluster formation, while the season in which they were collected is significant. On the other hand, the seawater composition was calibrated using estuary water samples of different salinities. Once the major constituents were measured, the data analysis concluded that it is possible to make a calibration of the HBound spectrum vs. any of these constituents by means of partial least square (PLS) regression. Thus, the experimental evidence collected in this work confirms that it is possible to detect polluted sea or estuary water samples using these chemometric tools and the H(+) affinity spectrum because with polluted samples these multivariate methods lead to incoherent results. So, suspect polluted zones may be monitored in a simple way with a low cost method and spending much less time. © 2013 Elsevier B.V. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

  12. 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

  13. 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.

  14. Chemometric study on the TiO2-photocatalytic degradation of nitrilotriacetic acid.

    PubMed

    Emilio, Carina A; Magallanes, Jorge F; Litter, Marta I

    2007-07-09

    A chemometric study on the TiO2-photocatalytic degradation of nitrilotriacetic acid (NTA) in aqueous media under UV radiation has been carried out taking into account the multiple variables that take part in the system. To save redundant number of experiments, the system has been managed under chemometric techniques for several variables as NTA and TiO2 concentrations, pH and irradiation time. Multiple-way analysis of the variance (MANOVA) has been applied to find the statistically significant variables. An artificial neural network (ANN) has been used to build an empirical model of the system. All measurements have been driven under experimental designs: a full-factorial design (FFD) was used to analyze significant factors through MANOVA, and a Doehlert design, which was modified by spatial rotation, was applied in order to have a satisfactory number of levels for the factor time to be able to train the ANN. The study allows the knowledge and prediction of the behavior of the system as well as to work out kinetic parameters and to optimize their variables. The results of kinetic parameters obtained with the neural network agreed with independent experimental results, confirming a Langmuir-Hinshelwood kinetic regime. The difference between NTA and ethylenediaminetetraacetic acid (EDTA), which has been previously studied, is also established.

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

    PubMed

    Glavanović, Siniša; Glavanović, Marija; Tomišić, Vladislav

    2016-03-15

    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%). Copyright © 2015. Published by Elsevier B.V.

  16. Raman spectroscopy and chemometrics for on-line control of glucose fermentation by Saccharomyces cerevisiae.

    PubMed

    Avila, Thiago C; Poppi, Ronei J; Lunardi, Inês; Tizei, Pedro A G; Pereira, Gonçalo A G

    2012-01-01

    This work presents the use of Raman spectroscopy and chemometrics for on-line control of the fermentation process of glucose by Saccharomyces cerevisiae. In a first approach, an on-line determination of glucose, ethanol, glycerol, and cells was accomplished using multivariate calibration based on partial least squares (PLS). The PLS models presented values of root mean square error of prediction (RMSEP) of 0.53, 0.25, and 0.02% for glucose, ethanol and glycerol, respectively, and RMSEP of 1.02 g L(-1) for cells. In a second approach, multivariate control charts based on multiway principal component analysis (MPCA) were developed for detection of fermentation fault-batch. Two multivariate control charts were developed, based on the squared prediction error (Q) and Hotelling's T(2) . The use of the Q control chart in on-line monitoring was efficient for detection of the faults caused by temperature, type of substrate and contamination, but the T(2) control chart was not able to monitor these faults. On-line monitoring by Raman spectroscopy in conjunction with chemometric procedures allows control of the fermentative process with advantages in relation to reference methods, which require pretreatment, manipulation of samples and are time consuming. Also, the use of multivariate control charts made possible the detection of faults in a simple way, based only on the spectra of the system.

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

    NASA Astrophysics Data System (ADS)

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

    2006-09-01

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

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

    PubMed

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

    2017-02-01

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

  19. 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%).

  20. Chemometrics optimization of six antihistamines separations by capillary electrophoresis with electrochemiluminescence detection.

    PubMed

    Zhu, Derong; Li, Xia; Sun, Jinying; You, Tianyan

    2012-01-15

    This work expanded the knowledge of the use of chemometric experimental design in optimizing of six antihistamines separations by capillary electrophoresis with electrochemiluminescence detection. Specially, central composite design was employed for optimizing the three critical electrophoretic variables (Tris-H(3)PO(4) buffer concentration, buffer pH value and separation voltage) using the chromatography resolution statistic function (CRS function) as the response variable. The optimum conditions were established from empirical model: 24.2mM Tris-H(3)PO(4) buffer (pH 2.7) with separation voltage of 15.9 kV. Applying theses conditions, the six antihistamines (carbinoxamine, chlorpheniramine, cyproheptadine, doxylamine, diphenhydramine and ephedrine) could be simultaneous separated in less than 22 min. Our results indicate that the chemometrics optimization method can greatly simplify the optimization procedure for multi-component analysis. The proposed method was also validated for linearity, repeatability and sensitivity, and was successfully applied to determine these antihistamine drugs in urine.

  1. 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.

  2. Discrimination of planting area of white peach based near-infrared spectra and chemometrics methods

    NASA Astrophysics Data System (ADS)

    Fu, Xiaping; Ying, Yibin; Zhou, Ying; Xu, Huirong; Xie, Lijuan; Jiang, Xuesong

    2007-09-01

    White peach is a famous peach variety for its super-quality and high economic benefit. It is originally planted in Yuandong Villiage, Jinhua County, Zhejiang province. By now, it has been planted in many other places in southeast of China. However, peaches from different planting areas have dissimilar quality and taste, which result in different selling price. The objective of this research was to discriminate peaches from different planting areas by using near-infrared (NIR) spectra and chemometrics methods. Diffuse reflectance spectra were collected by a fiber spectrometer in the range of 800-2500 nm. Discriminant analysis (DA), soft independent modeling of class analogy (SIMCA), and discriminant partial least square regression (DPLS) methods were employed to classify the peaches from three planting areas 'Jinhua', 'Wuyi', and 'Yongkang' of Zhejiang province. 360 samples were used in this study, 120 samples per planting area. The classifying correctness were above 92% for both DA and SIMCA mdoels. And the result of DPLS model was slightly better. By using DPLS method, two 'Jinhua' peaches, three 'Wuyi' peaches, and three 'Yongkang' peaches were misclassified, the accruacy was above 95%. The results of this study indicate that the three chemometrics methods DA, SIMCA, and DPLS are effective for discriminating peaches from different planting areas based on NIR spectroscopy.

  3. Chemometric tools to highlight possible migration of compounds from packaging to sunflower oils.

    PubMed

    Maalouly, Jacqueline; Hayeck, Nathalie; Kassouf, Amine; Rutledge, Douglas N; Ducruet, Violette

    2013-11-06

    Polyethylene terephthalate (PET) could be considered for the packaging of vegetable oils taking into account the impact of its oxygen permeability on the oxidation of the oil and the migration of volatile organic compounds (VOC) from the polymer matrix. After accelerated aging tests at 40 °C for 10, 20, and 30 days, the headspace of three sunflower oils packed in PET with high density polyethylene caps was carried out using solid phase microextraction. VOCs such as benzene hydrocarbons, ethylbenzene, xylene isomers and diethyl phthalate were identified in vegetable oils by gas chromatography coupled to mass spectrometry. Chemometric tools such as principal components analysis (PCA), independent components analysis (ICA), and a multiblocks analysis, common components and specific weight analysis (CCSWA) applied to analytical data were revealed to be very efficient to discriminate between samples according to oil oxidation products (hexanal, heptanal, 2-pentenal) and to the migration of packaging contaminants (xylene).

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

    SciTech Connect

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

    2007-10-24

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

  5. Excitation-emission matrix fluorescence coupled to chemometrics for the exploration of essential oils.

    PubMed

    Mbogning Feudjio, William; Ghalila, Hassen; Nsangou, Mama; Mbesse Kongbonga, Yvon G; Majdi, Youssef

    2014-12-01

    Excitation-emission matrix fluorescence (EEMF) coupled to chemometrics was used to explore essential oils (EOs). The spectrofluorometer was designed with basic and inexpensive materials and was accompanied by appropriate tools for data pre-treatment. Excitation wavelengths varied between 320 nm and 600 nm while emission wavelengths were from 340 nm to 700 nm. Excitation-emission matrix (EEM) spectra of EOs presented different features, revealing the presence of varying fluorophores. EOs from the same species but from different origins presented almost the same spectra, showing the possibility that EEM spectra could be used as additional parameters in the standardisation of EOs. With the aid of unfold principal component analysis (UPCA), resemblances obtained by spectral analysis of EOs were confirmed. A five components parallel factor analysis (PARAFAC) model was used to find the profiles of fluorophores in EOs. One of those components was associated to chlorophyll a. Copyright © 2014 Elsevier B.V. All rights reserved.

  6. 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.

  7. 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.

  8. Chemometric evaluation of the heavy metals distribution in waters from the Dilovasi region in Kocaeli, Turkey.

    PubMed

    Bingöl, Deniz; Ay, Umit; Karayünlü Bozbaş, Seda; Uzgören, Nevin

    2013-03-15

    The main objective of this study was to test water samples collected from 10 locations in the Dilovası area (a town in the Kocaeli region of Turkey) for heavy metal contamination and to classify the heavy metal (Cr, Mn, Co, Ni, Cu, Zn, As, Cd, Pb and Hg) contents in water samples using chemometric methods. The heavy metals in the water samples were identified using inductively coupled plasma-mass spectrometry (ICP-MS). To ascertain the relationship among the water samples and their possible sources, the correlation analysis, principal component analysis (PCA), and cluster analysis (CA) were used as classification techniques. About 10 water samples were classified into five groups using PCA. A very similar grouping was obtained using CA.

  9. Chemometric interpretation of heavy metal patterns in soils worldwide.

    PubMed

    Skrbić, Biljana; Durisić-Mladenović, Natasa

    2010-09-01

    Principal component analysis (PCA) was applied on data sets containing levels of six heavy metals (Pb, Cu, Zn, Cd, Ni, Cr) in soils from different parts of the world in order to investigate the information captured in the global heavy metal patterns. Data used in this study consisted of the heavy metal contents determined in 23 soil samples from and around the Novi Sad city area in the Vojvodina Province, northern part of Serbia, together with those from the city of Banja Luka, the second largest city in Bosnia and Herzegovina, and the ones reported previously in the relevant literature in order to evaluate heavy metal distribution pattern in soils of different land-use types, as well as spatial and temporal differences in the patterns. The chemometric analysis was applied on the following input data sets: the overall set with all data gathered in this study containing 264 samples, and two sub sets obtained after dividing the overall set in accordance to the soil metal index, SMI, calculated here, i.e. the set of unpolluted soils having SMIs<100%, and the set of polluted soils with SMIs>100%. Additionally, univariate descriptive statistics and the Spearman's non-parametric rank correlation coefficients were calculated for these three sets. A Box-Cox transformation was used as a data pretreatment before the statistical methods applied. According to the results, it was seen that anthropogenic and background sources had different impact on the data variability in the case of polluted and unpolluted soils. The sample discrimination regarding the land-use types was more evident for the unpolluted soils than for the polluted ones. Using linear discriminant analysis, content of Cu was determined as a variable with a major discriminant capacity. The correct classification of 73.3% was achieved for predefined land-use types. Classification of the samples in accordance to the pollution level expressed as SMI was necessary in order to avoid the "masking" effect of the

  10. IUPAC project: a glossary of concepts and terms in chemometrics.

    PubMed

    Hibbert, D Brynn; Minkkinen, Pentti; Faber, N M; Wise, Barry M

    2009-05-29

    A project has been initiated by the International Union of Pure and Applied Chemistry (IUPAC) to create a glossary of concepts and terms in chemometrics. This will be accomplished by consultation with the community through the means of a wiki--a web site that can be modified by users (see http://www.iupacterms.eigenvector.com/index.php?title=Main_Page). Over time new terms can be added, and consensus definitions arrived at. The definitions will be published as IUPAC recommendations.

  11. A novel storage method for near infrared spectroscopy chemometric models.

    PubMed

    Zhang, Zhi-Min; Chen, Shan; Liang, Yi-Zeng

    2010-06-04

    Chemometric Modeling Markup Language (CMML) is developed by us for containing chemometrics models within one document through converting binary data into strings by base64 encode/decode algorithms to solve the interoperability issue in sharing chemometrics models. It provides a base functionality for storage of sampling, variable selection, pretreating, outlier and modeling parameters and data. With the help of base64 algorithm, the usability of CMML is in equilibrium with size by transforming the binary data into base64 encoded string. Due to the advantages of Extensible Markup Language (XML), models stored in CMML can be easily reused in various other software and programming languages as long as the programming language has XML parsing library. One can also use the XML Path Language (XPath) query language to select desired data from the CMML file effectively. The application of this language in near infrared spectroscopy model storage is implemented as a class in C++ language and available as open source software (http://code.google.com/p/cmml), and the implementations in other languages, such as MATLAB and R are in progress.

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

    PubMed

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

    2014-06-23

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

  13. 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.

  14. Detection of apple juice concentrate in the manufacture of natural and sparkling cider by means of HPLC chemometric sugar analyses.

    PubMed

    Blanco Gomis, Domingo; Muro Tamayo, Daysi; Suárez Valles, Belén; Mangas Alonso, Juan J

    2004-01-28

    An HPLC method for sugar analyses in cider was used in order to detect the presence of apple juice concentrate. Sugars, previously derivatized with p-aminobenzoic ethyl ester, were analyzed by reversed-phase liquid chromatography using a C(8) column and a mobile phase of citrate buffer pH 5.5/tetrahydrofuran/acetonitrile, operated in gradient mode. The use of this analytical procedure together with chemometric techniques, such as principal component analysis and Bayesean analysis, allowed the authors to establish the minimum concentration of apple juice concentrate obtained by liquefaction or press technology that can be detected in natural cider.

  15. Chemometrics and visible-near infrared spectroscopic monitoring of red wine fermentation in a pilot scale.

    PubMed

    Cozzolino, Daniel; Parker, Mango; Dambergs, Robert G; Herderich, Markus; Gishen, Mark

    2006-12-20

    The modern wine industry needs tools for process control and quality assessment in order to better manage fermentation or bottling processes. During wine fermentation it is important to measure both substrate and product concentrations (e.g. sugars, phenolic compounds), however, the analysis of these compounds by traditional means requires sample preparation and in some cases several steps of purification are needed. The combination of visible/near-infrared (Vis/NIR) spectroscopy and chemometrics potentially provides an ideal solution to accurately and rapidly monitor physical or chemical changes in wine during processing without the need for chemical analysis. The aim of this study was to assess the possibility of combining spectral and multivariate techniques, such as principal component analysis (PCA), discriminant partial least squares (DPLS), or linear discriminant analysis (LDA), to monitor time-related changes that occur during red wine fermentation. Samples (n = 652) were collected at various times from several pilot scale fermentations with grapes from either Cabernet Sauvignon or Shiraz varieties, over three vintages (2001-2003) and scanned using a monochromator instrument (Foss-NIRSystems 6500, Silver Spring, MD) in transmission mode (400-2,500 nm). PCA was used to demonstrate consistent progressive spectral changes that occur through the time course of the fermentation. LDA using PCA scores showed that regardless of variety or vintage, samples belonging to a particular time point in fermentation could be correctly classified. This study demonstrates the potential of Vis/NIR spectroscopy combined with chemometrics, as a tool for the rapid monitoring of red wine fermentation.

  16. Description and comparison of chromatographic tests and chemometric methods for packed column classification.

    PubMed

    Lesellier, E; West, C

    2007-07-27

    The main tests developed in last 20 years to investigate the chromatographic behaviour and the stationary phase properties are described in this paper. These properties are the hydrophobicity, depending on the surface area and the bonding density, the number of accessible residual silanol groups having sometimes different acidity, which can interact with neutral solutes by hydrogen bonds or with the ionic form of basic compounds and the shape or steric selectivity, depending on both the functionality of the silanising agent and the bonding density. Two types of tests are performed, either based on key solutes having well defined properties such as phenol, caffeine, amitriptyline, benzylamine, acenaphtene, o-terphenyl, triphenylene, p-ethylaniline, carotenoid pigments, or on retention models (solvation parameter, hydrophobic subtraction) obtained from the analyses of numerous and varied compounds. Thus, the chromatographic properties are either related to selectivities or retention factors calculated from key solutes, or they are described by interaction coefficients provided by multilinear regression from retention models. Three types of comparison methods are used based on these data. First, simple plots allow the study of differences between the columns as regards to one or two properties. Columns located in the same area of the plot display close properties. Second, chemometric methods such as principal component analysis (PCA) or hierarchical cluster analysis (HCA) can be performed to compare columns. In this case, all the studied properties are included in the comparison, done either by data projection to reduce the space in which the information is located (PCA) or by distance calculation and comparison for drawing a classification (HCA). Neighbouring columns are expected to provide identical chromatographic performances. These two chemometric methods can be used together, PCA before HCA. The third way is to calculate a discrimination factor from a reference

  17. Chemometrics-enhanced high performance liquid chromatography-ultraviolet detection of bioactive metabolites from phytochemically unknown plants.

    PubMed

    Alvarez-Zapata, Radamés; Sánchez-Medina, Alberto; Chan-Bacab, Manuel; García-Sosa, Karlina; Escalante-Erosa, Fabiola; García-Rodríguez, Rosa Virginia; Peña-Rodríguez, Luis Manuel

    2015-11-27

    This work describes the use of Colubrina greggii as a model to investigate the use of chemometric analysis combined with data from a leishmanicidal bioassay, using Principal Component Analysis (PCA) and Orthogonal Projections to Latent Structures (O-PLS), to detect biologically active natural products in crude extracts from plants having little or no phytochemical information. A first analysis of the HPLC-UV profiles of the extract and its semi-purified fractions using both Principal Component Analysis (PCA) and Orthogonal Partial Least Squares (O-PLS) indicated that the components at tR 48.2, 48.7, 51.8min correlated with the variation in bioactivity. However, a further O-PLS analysis of the HPLC-UV profiles of fractions obtained through a final semi-preparative HPLC purification showed two components at tR 48.7 and 49.5min which correlated with the variation of the bioactivity in a high performance predictive model, with high determination coefficient, high correlation coefficient values (R(2) and Q(2)=0.99) and a low root mean square error (RMSE=0.018). This study demonstrates that the association of chemometric analysis with bioassay results can be an excellent strategy for the detection and isolation of bioactive metabolites from phytochemically unknown plant crude extracts.

  18. 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.

  19. Discriminant analyzing system for wood wastes using a visible-near-infrared chemometric imaging technique.

    PubMed

    Kobori, Hikaru; Yonenobu, Hitoshi; Noma, Junichi; Tsuchikawa, Satoru

    2008-08-01

    A new optical system was developed and applied to automated separation of wood wastes, using a combined technique of visible-near-infrared (Vis-NIR) imaging analysis and chemometrics. Three kinds of typical wood wastes were used, i.e., non-treated, impregnated, and plastic-film overlaid wood. The classification model based on soft independent modeling of class analogy (SIMCA) was examined using the difference luminance brightness of a sample. Our newly developed system showed a good/promising performance in separation of wood wastes, with an average rate of correct separation of 89%. Hence, it is concluded that the system is efficiently feasible for online monitoring and separation of wood wastes in recycling mills.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Identification and quantitation of petroleum substances in environmental samples using Friedel-Crafts/Hanby spectrophotometry with chemometrics

    SciTech Connect

    Hanby, J.D.

    1997-12-31

    Hanby method extraction/colorimetric field test kits have been successfully utilized in the past decade for the detection and quantitation of petroleum compounds in water and soil samples employing visual comparison of test results with photograph standards. The past several years have seen a number of investigations into the development of various visible-region spectrometric instruments to be used as read-out devices for these test results. Very recent developments in Charge-Transfer Device (CTD) technology coupled with advances in fiber-optics, microprocessors, and software innovations in chemometrics are preparing the way for expansion of this portable technology into visible molecular spectroscopic analysis.

  6. Diffuse reflectance near infrared-chemometric methods development and validation of amoxicillin capsule formulations

    PubMed Central

    Khan, Ahmed Nawaz; Khar, Roop Krishen; Ajayakumar, P. V.

    2016-01-01

    Objective: The aim of present study was to establish near infrared-chemometric methods that could be effectively used for quality profiling through identification and quantification of amoxicillin (AMOX) in formulated capsule which were similar to commercial products. In order to evaluate a large number of market products easily and quickly, these methods were modeled. Materials and Methods: Thermo Scientific Antaris II near infrared analyzer with TQ Analyst Chemometric Software were used for the development and validation of the identification and quantification models. Several AMOX formulations were composed with four excipients microcrystalline cellulose, magnesium stearate, croscarmellose sodium and colloidal silicon dioxide. Development includes quadratic mixture formulation design, near infrared spectrum acquisition, spectral pretreatment and outlier detection. According to prescribed guidelines by International Conference on Harmonization (ICH) and European Medicine Agency (EMA) developed methods were validated in terms of specificity, accuracy, precision, linearity, and robustness. Results: On diffuse reflectance mode, an identification model based on discriminant analysis was successfully processed with 76 formulations; and same samples were also used for quantitative analysis using partial least square algorithm with four latent variables and 0.9937 correlation of coefficient followed by 2.17% root mean square error of calibration (RMSEC), 2.38% root mean square error of prediction (RMSEP), 2.43% root mean square error of cross-validation (RMSECV). Conclusion: Proposed model established a good relationship between the spectral information and AMOX identity as well as content. Resulted values show the performance of the proposed models which offers alternate choice for AMOX capsule evaluation, relative to that of well-established high-performance liquid chromatography method. Ultimately three commercial products were successfully evaluated using developed

  7. 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.

  8. Test of the relationships between the content of heavy metals in sewage sludge and source of their pollution by chemometric methods.

    PubMed

    Hanć, Anetta; Komorowicz, Izabela; Sek, Karol; Baralkiewicz, Danuta

    2009-11-01

    The content of various metals (Cd, Cr, Cu, Ni, Pb and Zn) in sewage sludge was analysed by ICP-OES technique. The study was performed on 14 samples from the Wielkopolska region and 4 from the neighbouring provinces. The results were used to perform chemometric analysis. Two chemometric methods were used to test the relationships between the content of heavy metals in sewage sludge and the sources of their pollution. The application of cluster analysis displayed important information about the identification of similar locations of sewage sludge sampling stations. This chemometric method showed that all the monitoring locations are grouped into three main clusters. Separated clusters present similarities between locations of the sewage treatment plants, which have the same kind of industrial plants in their catchment area. Principal component analysis enabled interpretation of the complex relationships between determined elements. Application of principal component analysis to the whole data set helped to distinguish only two sewage sludge stations (Ostrow Wlkp. and Poznan-Kozieglowy) that could be interpreted, each in different principal component thereby suggesting that element's concentration differ considerably. The interpretation of relationships between the rest of the stations was possible by performing PCA for the second time, but on the reduced data set (two above-mentioned stations were excluded). It distinguished two groups: (1) Gniezno, Srem, Kalisz, Inowrocław and Sroda Wlkp, and (2) Gostyn, Gniezno and Kalisz, which differ with regard to element's concentration.

  9. 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

  10. 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.

  11. Spatial distribution of heavy metals in Hong Kong's marine sediments and their human impacts: a GIS-based chemometric approach.

    PubMed

    Zhou, Feng; Guo, Huaicheng; Hao, Zejia

    2007-09-01

    A geographic information system (GIS)-based chemometric approach was applied to investigate the spatial distribution patterns of heavy metals in marine sediments and to identify spatial human impacts on global and local scales. Twelve metals (Zn, V, Ni, Mn, Pb, Cu, Cd, Ba, Hg, Fe, Cr and Al) were surveyed twice annually at 59 sites in Hong Kong from 1998 to 2004. Cluster analysis classified the entire coastal area into three areas on a global scale, representing different pollution levels. Backward discriminant analysis, with 84.5% correct assignments, identified Zn, Pb, Cu, Cd, V, and Fe as significant variables affecting spatial variation on a local scale. Enrichment factors indicated that Cu, Cr, and Zn were derived from human impacts while Al, Ba, Mn, V and Fe originated from rock weathering. Principal component analysis further subdivided human impacts and their affected areas in each area, explaining 87%, 84% and 87% of the total variances, respectively. The primary anthropogenic sources in the three areas were (i) anti-fouling paint and domestic sewage; (ii) surface runoff, wastewater, vehicle emissions and marine transportation; and (iii) ship repainting, dental clinics, electronic/chemical industries and leaded fuel, respectively. Moreover, GIS-based spatial analysis facilitated chemometric methods.

  12. 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.

  13. 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).

  14. Chemometric evaluation of pharmaceutical properties of antipyrine granules by near-infrared spectroscopy.

    PubMed

    Otsuka, Makoto; Mouri, Yoshifumi; Matsuda, Yoshihisa

    2003-01-01

    The purpose of this research was to apply near-infrared (NIR) spectroscopy with chemometrics to predict the change of pharmaceutical properties of antipyrine granules during granulation by regulation of the amount of water added. The various kinds of granules (mean particle size, 70-750 microm) were obtained from the powder mixture (1 g of antipyrine, 6 g of hydroxypropylcellulose, 140 g of lactose, and 60 g of potato starch) by regulation of the added water amount (11-19 wt/wt%) in a high-speed mixer. The granules were characterized by mean particle size, angle of repose, compressibility, tablet porosity, and tablet hardness as parameters of pharmaceutical properties. To predict the pharmaceutical properties, NIR spectra of the granules were measured and analyzed by principal component regression (PCR) analysis. The mean particle size of the granules increased from 81 micro m to 650 micro m with an increase in the amount of water, and it was possible to make larger spherical granules with narrow particle size distribution using a high-speed mixer. Angle of repose, compressibility, and porosity of the tablets decreased with an increase of added water, but tablet hardness increased. The independent calibration models to evaluate particle size, angle of repose, and tablet porosity and hardness were established by using PCR based on NIR spectra of granules, respectively. The correlation coefficient constants of calibration curves for prediction of mean particle size, angle of repose, tablet porosity, and tablet hardness were 0.9109, 0.8912, 0.7437, and 0.8064, respectively. It is possible that the pharmaceutical properties of the granule, such as mean particle size, angle of repose, tablet porosity, and tablet hardness, could be predicted by an NIR-chemometric method.

  15. Chemometric determination of naproxen sodium and pseudoephedrine hydrochloride in tablets by HPLC.

    PubMed

    Dinç, Erdal; Ozdemir, Abdil; Aksoy, Halil; Ustündağ, Ozgür; Baleanu, Dumitru

    2006-04-01

    A new chemometric determination by high-performance liquid chromatography (HPLC) with photodiode array (PDA) detection was implemented for the simultaneous determination of naproxen sodium and pseudoephedrine hydrochloride in tablets. Three chemometric calibration techniques, classical least squares (CLS), principle component regression (PCR) and partial least squares (PLS) were applied to the peak area at multiwavelength PDA detector responses. The combinations of HPLC with chemometric calibration techniques were called HPLC-CLS, HPLC-PCR and HPLC-PLS. For comparison purposes the HPLC method called the classic HPLC method was used to confirm the results obtained from combined HPLC-chemometric calibration techniques. A good chromatographic separation between two drugs with losartan potassium as an internal standard was achieved using a Waters Symmetry C18 Column 5 microm 4.6+/-250 mm and a mobile phase containing 0.2 M acetate buffer and acetonitrile (v/v, 40:60). The multiwavelength PDA detection was measured at five different wavelengths. The chromatograms were recorded as a training set in the mobile phase. Three HPLC-chemometric calibrations and the classic-HPLC method were used to test the synthetic mixtures of naproxen sodium and pseudoephedrine hydrochloride in the presence of the internal standard. The HPLC-chemometric approaches were applied to real samples containing drugs of interest. The experimental results obtained from HPLC-chemometric calibrations were compared with those obtained by a classic HPLC method.

  16. Evaluation of the effects of Candidatus Liberibacter asiaticus on inoculated citrus plants using laser-induced breakdown spectroscopy (LIBS) and chemometrics tools.

    PubMed

    Pereira, Fabíola Manhas Verbi; Milori, Débora Marcondes Bastos Pereira; Venâncio, André Leonardo; Russo, Mariana de Sá Tavares; Martins, Polyana Kelly; Freitas-Astúa, Juliana

    2010-12-15

    This study investigated the organic and inorganic constituents of healthy leaves and Candidatus Liberibacter asiaticus (CLas)-inoculated leaves of citrus plants. The bacteria CLas are one of the causal agents of citrus greening (or Huanglongbing) and its effect on citrus leaves was investigated using laser-induced breakdown spectroscopy (LIBS) combined with chemometrics. The information obtained from the LIBS spectra profiles with chemometrics analysis was promising for the construction of predictive models to identify healthy and infected plants. The major, macro- and microconstituents were relevant for differentiation of the sample conditions. The models were then applied to different inoculation times (from 1 to 8 months). The models were effective in the classification of 82-97% of the diseased samples with a 95% significance level. The novelty of this method was in the fingerprinting of healthy and diseased plants based on their organic and inorganic contents. Copyright © 2010 Elsevier B.V. All rights reserved.

  17. 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.

  18. Feasibility study on chemometric discrimination of roasted Arabica coffees by solvent extraction and Fourier transform infrared spectroscopy.

    PubMed

    Wang, Niya; Fu, Yucheng; Lim, Loong-Tak

    2011-04-13

    In this feasibility study, Fourier transform infrared (FTIR) spectroscopy and chemometric analysis were adopted to discriminate coffees from different geographical origins and of different roasting degrees. Roasted coffee grounds were extracted using two methods: (1) solvent alone (dichloromethane, ethyl acetate, hexane, acetone, ethanol, or acetic acid) and (2) coextraction using a mixture of equal volume of the solvent and water. Experiment results showed that the coextraction method resulted in cleaner extract and provided a greater amount of spectral information, which was important for sample discrimination. Principal component analysis of infrared spectra of ethyl acetate extracts for dark and medium roast coffees showed separated clusters according to their geographical origins and roast degrees. Classification models based on soft independent modeling of class analogy analysis were used to classify different coffee samples. Coffees from four different countries, which were roasted to dark, were 100% correctly classified when ethyl acetate was used as a solvent. The FTIR-chemometric technique developed here may serve as a rapid tool for discriminating geographical origin of roasted coffees. Future studies involving green coffee beans and the use of larger sample size are needed to further validate the robustness of this technique.

  19. Determination of phenolic compounds and authentication of PDO Lambrusco wines by HPLC-DAD and chemometric techniques.

    PubMed

    Salvatore, Elisa; Cocchi, Marina; Marchetti, Andrea; Marini, Federico; de Juan, Anna

    2013-01-25

    This work proposes a fast and simple method for detection and quantification of phenolic compounds in PDO Lambrusco wines using HPLC-DAD and chemometric techniques. Samples belonging to three different varieties of Lambrusco (Grasparossa, Salamino and Sorbara) were analyzed to provide a methodology appropriate for routine analysis. Given the high complexity of the sample and the coelution among chromatographic peaks, the use of chemometric techniques to extract the information of the individual eluting compounds was needed. Multivariate curve resolution-alternating least squares (MCR-ALS) allowed the resolution of the chromatographic peaks obtained and the use of this information for the quantification of the phenolic analytes in the presence of interferences. Use of multiset analysis and local rank/selectivity information was proven to be crucial for the correct resolution and quantification of compounds. The quantitative data provided by MCR-ALS about the phenolic targets and additional compounds present in the samples analyzed provided wine composition profiles, which were afterwards used to distinguish among wine varieties. Principal component analysis applied to the wine profiles allowed characterizing the wines according to their varieties.

  20. Ultra-Performance Liquid Chromatography for the Simultaneous Quantification of Rutin and Chlorogenic Acid in Leaves of Ribes L. Species by Conventional and Chemometric Calibration Approaches.

    PubMed

    Kendir, Gülsen; Dinç, Erdal; Güvenç, Ayşegül Köroǧlu

    2015-10-01

    A new ultra-performance liquid chromatography (UPLC) using conventional and chemometric calibrations was improved for the simultaneous estimation of chlorogenic acid (CA) and rutin (RUT) in leaves of Ribes L. species (R. rubrum, R. biebersteinii, R. nigrum, R. uva-crispa, R. alpinum, R. orientale, R. multiflorum and R. anatolica). The UPLC separation for CA and RUT in samples were performed on a Waters UPLC BEH phenyl column (100 mm × 1.0 mm i.d., 1.7 μm) and mobile phase consisting of acetonitrile and 0.1 M formic acid buffer, pH = 3.77 (15:85, v/v) containing 1.0 mL triethylamine in 1,000 mL mobile phase. Multi-wavelength UPLC chromatograms of CA and RUT in calibration and plant samples were obtained by the photodiode array (PDA) detection at the wavelength set from 290 to 360 nm with the interval of Δλ = 10 nm. Conventional UPLC-single and chemometric calibrations were subjected to the analysis of the related compounds. By using UPLC data, conventional and chemometric calibrations in the linear concentration range between 2.5 and 40.0 μg/mL for all compounds were applied for the simultaneous quantitative analysis of CA and RUT in plant samples of seven different Ribes species.

  1. Simultaneous spectrophotometric determination of atrazine and cyanazine by chemometric methods

    NASA Astrophysics Data System (ADS)

    Zhang, Guowen; Pan, Junhui

    2011-01-01

    A spectrophotometric method for the simultaneous determination of two herbicides, atrazine and cyanazine, is described for the first time based on their reaction with p-aminoacetophenone in the presence of pyridine in hydrochloric acid medium. The absorption spectra were measured in the wavelength range of 400-600 nm. The optimized method indicated that individual analytes followed Beer's law in the concentration ranges for atrazine and cyanazine were 0.2-3.5 mg L -1 and 0.3-5.0 mg L -1, and the limits of detection for atrazine and cyanazine were 0.099 and 0.15 mg L -1, respectively. The original and first-derivative absorption spectra of the binary mixtures were performed as a pre-treatment on the calibration matrices prior to the application of chemometric models such as classical least squares (CLS), principal component regression (PCR), partial least squares (PLS). The analytical results obtained by using these chemometric methods were evaluated on the basis of percent relative prediction error and recovery. It was found that the application of PCR and PLS models for first-derivative absorbance data gave the satisfactory results. The proposed methods were successfully applied for the simultaneous determination of the two herbicides in several food samples.

  2. Liquid Chromatographic-Chemometric Techniques for the Simultaneous HPLC Determination of Lansoprazole, Amoxicillin and Clarithromycin in Commercial Preparation.

    PubMed

    Aktas, A Hakan; Saridag, Ayse Mine

    2017-09-01

    Two multivariate calibration-prediction techniques, principal component regression (PCR) and partial least-squares regression (PLSR) were applied to the chromatographic multicomponent analysis of the drug containing lansoprazole (LAN), clarithromycin (CLA) and amoxicillin (AMO). Optimum chromatographic separation of LAN, CLA and AMO with atorvastatin as the internal standard (IS) was obtained by using Xterra® RP18 column 5 μm 4.6 × 250 mm2, and 25 mM ammonium chloride buffer prepared ammonium chloride, acetonitrile and bidistilled water (45:45:10 v/v) as the mobile phase at flow rate 1.0 mL/min. The high pressure liquid chromatography data sets consisting of the ratios of analyte peak areas to the IS peak area were obtained by using diode array detector detection at five wavelengths (205, 210, 215, 220 and 225 nm). LC-chemometric calibration for LAN, CLA and AMO were separately constructed by using the relationship between the peak-area ratio and training sets for each analyte. A series of synthetic solutions containing different concentrations of LAN, CLA and AMO were used to check the prediction ability of the PCR and PLS. Both of the two-chemometric methods in this study can be satisfactorily used for the quantitative analysis and for dissolutions tests of multicomponent commercial drug. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  3. Nondestructive discrimination of ivories and prediction of their specific gravity by Fourier-transform Raman spectroscopy and chemometrics.

    PubMed

    Shimoyama, Masahiko; Ninomiya, Toshio; Ozaki, Yukihiro

    2003-07-01

    Fourier-transform (FF) Raman spectroscopy and chemometrics were used for nondestructive analysis of ivories. The discrimination of five kinds of ivories, two subspecies of African elephant, mammoth, hippopotamus, and sperm whale, was investigated, and a calibration model for predicting their specific gravity was developed. FT-Raman spectra were measured in situ for them and chemometrics analyses were carried out for the 3050-350 cm(-1) region. The five kinds of ivories were clearly discriminated from each other on the scores plots of two or three principal components (PCs) obtained by principal component analysis (PCA). The loadings plot for PC 1 shows that the discrimination relies on the content ratio of organic collagenous protein and inorganic hydroxyapatite of ivories. The loadings plot for PC 2 shows that bands due to the CH3 and CH2 stretching modes of the protein also play a role in the discrimination. Using partial least squares regression (PLSR), we developed a calibration model that predicts the specific gravity of the ivories from the FT-Raman spectra. The correlation coefficient and root mean square error of cross validation (RMSECV) of this model were 0.980 and 0.024, respectively.

  4. Chemometric quality control of chromatographic purity.

    PubMed

    Laursen, Kristoffer; Frederiksen, Søren Søndergaard; Leuenhagen, Casper; Bro, Rasmus

    2010-10-15

    It is common practice in chromatographic purity analysis of pharmaceutical manufacturing processes to assess the quality of peak integration combined by visual investigation of the chromatogram. This traditional method of visual chromatographic comparison is simple, but is very subjective, laborious and seldom very quantitative. For high-purity drugs it would be particularly difficult to detect the occurrence of an unknown impurity co-eluting with the target compound, which is present in excess compared to any impurity. We hypothesize that this can be achieved through Multivariate Statistical Process Control (MSPC) based on principal component analysis (PCA) modeling. In order to obtain the lowest detection limit, different chromatographic data preprocessing methods such as time alignment, baseline correction and scaling are applied. Historical high performance liquid chromatography (HPLC) chromatograms from a biopharmaceutical in-process analysis are used to build a normal operation condition (NOC) PCA model. Chromatograms added simulated 0.1% impurities with varied resolutions are exposed to the NOC model and monitored with MSPC charts. This study demonstrates that MSPC based on PCA applied on chromatographic purity analysis is a powerful tool for monitoring subtle changes in the chromatographic pattern, providing clear diagnostics of subtly deviating chromatograms. The procedure described in this study can be implemented and operated as the HPLC analysis runs according to the process analytical technology (PAT) concept aiming for real-time release. Copyright © 2010 Elsevier B.V. All rights reserved.

  5. Chemometric studies of several minerals in milks.

    PubMed

    Rodríguez Rodríguez, E M; Sanz Alaejos, M; Díaz Romero, C

    1999-04-01

    A statistical study of correlation, factorial, and discriminant analysis on the metal composition (Se, Fe, Cu, Zn, Na, K, Ca, Mg) of different types of milks (human, cow, goat, pasteurized, and powdered infant formula) was carried out to establish the relationships between the metal concentrations and, therefore, differentiate the samples according to the type of milk. A large number of significant intermetallic correlations were found in all samples, which could be due to biological relationships between the metals studied. After the factorial analysis, the dimension space was reduced from eight variables to two factors, accounting for approximately 71.4% of the total variance. After an orthogonal rotation, the first factor was positively correlated with Ca and the second factor with Fe. The representation of the scores makes it possible to separate not only human milk from powdered infant formula but also to separate both of these from the other milks. In the discriminant analysis, four discriminant functions were obtained, which are linear combinations of the quantitative variables that best explain the differences among the different milks analyzed. These functions make it possible to classify 98% of the samples analyzed within each type of milk correctly. Therefore, discriminant functions obtained here can be used to identify the origin of any milk sample.

  6. Chemometric classification techniques as a tool for solving problems in analytical chemistry.

    PubMed

    Bevilacqua, Marta; Nescatelli, Riccardo; Bucci, Remo; Magrì, Andrea D; Magrì, Antonio L; Marini, Federico

    2014-01-01

    Supervised pattern recognition (classification) techniques, i.e., the family of chemometric methods whose aim is the prediction of a qualitative response on a set of samples, represent a very important assortment of tools for solving problems in several areas of applied analytical chemistry. This paper describes the theory behind the chemometric classification techniques most frequently used in analytical chemistry together with some examples of their application to real-world problems.

  7. Fingerprint developing of coffee flavor by gas chromatography-mass spectrometry and combined chemometrics methods.

    PubMed

    Huang, Lan-Fang; Wu, Ming-Jian; Zhong, Ke-Jun; Sun, Xian-Jun; Liang, Yi-Zeng; Dai, Yun-Hui; Huang, Ke-Long; Guo, Fang-Qiu

    2007-04-11

    In this paper, chromatographic fingerprint was firstly used for quality control of tobacco flavors. Based on gas chromatography-mass spectrometry (GC-MS) and combined chemometrics methods, a simple, reliable and reproducible method for developing chromatographic fingerprint of coffee flavor, one of tobacco flavors, was described. Six coffee flavor samples obtained from different locations were used to establish the fingerprint. The qualitative and quantitative analysis of coffee flavor sample from Shenzhen was completed with the help of subwindow factor analysis (SFA). Fifty-two components of 68 separated constituents in coffee flavor sample from Shenzhen, accounting for 88.42% of the total content, were identified and quantified. Then, spectral correlative chromatography (SCC) was used to extract the common peaks from other five studied coffee flavor samples. Thirty-eight components were found to exist in all six samples. Finally, the method validation of fingerprint analysis was performed based on the relative retention time and the relative peak area of common peaks, sample stability and similarity analysis. The similarities of six coffee flavor samples were more than 0.9104 and showed that samples from different locations were consistent to some extent. The developed chromatographic fingerprint was successfully used to differentiate coffee flavor from cocoa flavor and some little difference sample prepared with coffee flavor and cocoa flavor by both similarity comparison and principal component projection analysis. The developed method can be used for quality control of coffee flavor.

  8. Nondestructive prediction of oren extract powder, a herbal medicine, in suppositories by chemometric near-infrared spectroscopy.

    PubMed

    Teraoka, Ryutaro; Abe, Hiroyuki; Sugama, Tadaaki; Ito, Kiyomi; Aburada, Masaki; Otsuka, Makoto

    2012-04-01

    Near-infrared (NIR) spectroscopy combined with chemometrics has been utilized in predictions of natural medicine content without destroying samples. Suppositories (oren powdered extract content 0, 0.5, 1.0, 2.5, 10, 12.5, and 15%) were produced by mixing oren powdered extract with macrogol mixture consisting of 1 part macrogol 1500 and 2.5 parts macrogol 4000 at 54°C, and pouring the melt mixture into a plastic container. NIR spectra of the 10 prepared samples were recorded 10 times, and a total of 100 spectra were randomly divided into two data sets, one for calibration and the other for validation. The calibration model for the oren content of the suppository was calculated based on NIR spectra using a partial least-squares regression analysis after pre-treatment (smoothing and the multiplicative scatter correction). The relationship between the actual and predicted values for calibration and validation models had a straight line with correlation coefficients of 0.9936 and 0.9898, respectively. The regression vector result of the calibration model indicates that the peaks at 6945, 5747, and 5160 cm(-1) in the regression vector were consistent with those in oren powder extracts. NIR spectroscopy combined with chemometrics offers promise as a method of predicting the oren powder content in suppositories without destroying the samples.

  9. Neurochemostat: A Neural Interface SoC with Integrated Chemometrics for Closed-Loop Regulation of Brain Dopamine

    PubMed Central

    Bozorgzadeh, Bardia; Schuweiler, Douglas R.; Bobak, Martin J.; Garris, Paul A.; Mohseni, Pedram

    2016-01-01

    This paper presents a 3.3 × 3.2mm2 system-on-chip (SoC) fabricated in AMS 0.35µm 2P/4M CMOS for closed-loop regulation of brain dopamine. The SoC uniquely integrates neurochemical sensing, on-the-fly chemometrics, and feedback-controlled electrical stimulation to realize a “neurochemostat” by maintaining brain levels of electrically evoked dopamine between two user-set thresholds. The SoC incorporates a 90µW, custom-designed, digital signal processing (DSP) unit for real-time processing of neurochemical data obtained by 400V/s fast-scan cyclic voltammetry (FSCV) with a carbon-fiber microelectrode (CFM). Specifically, the DSP unit executes a chemometrics algorithm based upon principal component regression (PCR) to resolve in real time electrically evoked brain dopamine levels from pH change and CFM background-current drift, two common interferents encountered using FSCV with a CFM in vivo. Further, the DSP unit directly links the chemically resolved dopamine levels to the activation of the electrical microstimulator in on-off-keying (OOK) fashion. Measured results from benchtop testing, flow injection analysis (FIA), and biological experiments with an anesthetized rat are presented. PMID:26390501

  10. 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.

  11. Neurochemostat: A Neural Interface SoC With Integrated Chemometrics for Closed-Loop Regulation of Brain Dopamine.

    PubMed

    Bozorgzadeh, Bardia; Schuweiler, Douglas R; Bobak, Martin J; Garris, Paul A; Mohseni, Pedram

    2016-06-01

    This paper presents a 3.3×3.2 mm(2) system-on-chip (SoC) fabricated in AMS 0.35 μm 2P/4M CMOS for closed-loop regulation of brain dopamine. The SoC uniquely integrates neurochemical sensing, on-the-fly chemometrics, and feedback-controlled electrical stimulation to realize a "neurochemostat" by maintaining brain levels of electrically evoked dopamine between two user-set thresholds. The SoC incorporates a 90 μW, custom-designed, digital signal processing (DSP) unit for real-time processing of neurochemical data obtained by 400 V/s fast-scan cyclic voltammetry (FSCV) with a carbon-fiber microelectrode (CFM). Specifically, the DSP unit executes a chemometrics algorithm based upon principal component regression (PCR) to resolve in real time electrically evoked brain dopamine levels from pH change and CFM background-current drift, two common interferents encountered using FSCV with a CFM in vivo. Further, the DSP unit directly links the chemically resolved dopamine levels to the activation of the electrical microstimulator in on-off-keying (OOK) fashion. Measured results from benchtop testing, flow injection analysis (FIA), and biological experiments with an anesthetized rat are presented.

  12. Manufacturer identification and storage time determination of "Dong'e Ejiao" using near infrared spectroscopy and chemometrics.

    PubMed

    Li, Wen-Long; Han, Hai-Fan; Zhang, Lu; Zhang, Yan; Qu, Hai-Bin

    2016-05-01

    We have developed a set of chemometric methods to address two critical issues in quality control of a precious traditional Chinese medicine (TCM), Dong'e Ejiao (DEEJ). Based on near infrared (NIR) spectra of multiple samples, the genuine manufacturer of DEEJ, e.g. Dong'e Ejiao Co., Ltd., was accurately identified among 21 suppliers by the fingerprint method using Hotelling T(2), distance to Model X (DModX), and similarity match value (SMV) as discriminate criteria. Soft independent modeling of the class analogy algorithm led to a misjudgment ratio of 6.2%, suggesting that the fingerprint method is more suitable for manufacturer identification. For another important feature related to clinical efficacy of DEEJ, storage time, the partial least squares-discriminant analysis (PLS-DA) method was applied with a satisfactory misjudgment ratio (15.6%) and individual prediction error around 1 year. Our results demonstrate that NIR spectra comprehensively reflect the essential quality information of DEEJ, and with the aid of proper chemometric algorithms, it is able to identify genuine manufacturer and determine accurate storage time. The overall results indicate the promising potential of NIR spectroscopy as an effective quality control tool for DEEJ and other precious TCM products.

  13. Manufacturer identification and storage time determination of “Dong’e Ejiao” using near infrared spectroscopy and chemometrics*

    PubMed Central

    Li, Wen-long; Han, Hai-fan; Zhang, Lu; Zhang, Yan; Qu, Hai-bin

    2016-01-01

    We have developed a set of chemometric methods to address two critical issues in quality control of a precious traditional Chinese medicine (TCM), Dong’e Ejiao (DEEJ). Based on near infrared (NIR) spectra of multiple samples, the genuine manufacturer of DEEJ, e.g. Dong’e Ejiao Co., Ltd., was accurately identified among 21 suppliers by the fingerprint method using Hotelling T2, distance to Model X (DModX), and similarity match value (SMV) as discriminate criteria. Soft independent modeling of the class analogy algorithm led to a misjudgment ratio of 6.2%, suggesting that the fingerprint method is more suitable for manufacturer identification. For another important feature related to clinical efficacy of DEEJ, storage time, the partial least squares-discriminant analysis (PLS-DA) method was applied with a satisfactory misjudgment ratio (15.6%) and individual prediction error around 1 year. Our results demonstrate that NIR spectra comprehensively reflect the essential quality information of DEEJ, and with the aid of proper chemometric algorithms, it is able to identify genuine manufacturer and determine accurate storage time. The overall results indicate the promising potential of NIR spectroscopy as an effective quality control tool for DEEJ and other precious TCM products. PMID:27143266

  14. 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 C18 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.

  15. A comparative chemometric study for water quality expertise of the Athenian water reservoirs.

    PubMed

    Farmaki, Eleni G; Thomaidis, Nikolaos S; Simeonov, Vasil; Efstathiou, Constantinos E

    2012-12-01

    The aim of the present study is to compare the application of unsupervised and supervised pattern recognition techniques for the quality assessment and classification of the reservoirs used as the source for the domestic and industrial water supply of the city of Athens, Greece. A new optimization strategy for sampling, monitoring, and water management is proposed. During the period of October 2006 to April 2007, 89 samples were collected from the three water reservoirs (Iliki, Mornos, and Marathon), and 13 parameters (metals and metalloids) were analytically determined. Generally, all the elements were found to fluctuate at very low levels, especially for Mornos that comprises the main water reservoir of Athens. Iliki and Marathon showed relatively elevated values, compared to Mornos, but below the legislative limits. Multivariate unsupervised statistical techniques, such as factor analysis/principal components analysis, and cluster analysis and supervised ones, like discriminant analysis and classification trees, were applied to the data set, and their classification abilities were compared. All the chemometric techniques successfully revealed the critical variables and described the similarities and dissimilarities among the sampling points, emphasizing the individual characteristics in every sample and revealing the sources of elements in the region. New data from posterior samplings (November and December 2007) were used for the validation of the supervised techniques. Finally, water management strategies were proposed concerning the sampling points and representative parameters.

  16. 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)

  17. Chemometric model for describing Greek traditional sausages.

    PubMed

    Papadima, S N; Arvanitoyannis, I; Bloukas, J G; Fournitzis, G C

    1999-03-01

    Chemical, physical, microbiological and sensory analyses were performed on 31 samples of Greek traditional sausages. The following attributes were recorded: fat 15.49-56.86%, moisture 21.92-65.40%, protein 14.73-26.74%, sodium chloride 2.36-4.13%, nitrites 0.0-3.26 ppm, mean nitrates 38.19 ppm, TBA value 0.42-5.33 mg malonaldehyde/kg, pH 4.74-6.74, water activity (a(w)) 0.88-0.97, firmness 0-64 Zwick units, lightness (L(*)) 25.03-35.37, redness (a(*)) 2.55-11.42, yellowness 4.42-12.96, aerobic plate count 5.48-9.32 cfu/g, lactic acid bacteria (LAB) 5.26-9.08 cfu/g, micrococci/staphylococci 4.11-6.91 cfu/g and Gram (-) bacteria 1.78-6.15 cfu/g. Mean sensory scores ranged from 3.14 to 3.54 on a 5-point hedonic scale. Two statistical analysis programmes (Praxitele and SPSS) were used for characterising and assessing the properties of sausages. The first two principal components (PC1-2) derived by SPSS (50.5% variance) describe more satisfactorily the variance than the corresponding PC1-2, PC1-3 obtained by Praxitele (40.4% variance). High consumer preference was strongly related to satisfactory appearance and strong taste, high LAB count, medium fat content, medium firmness and lightness (L(*)(surface)). Extreme attribute values (high or low) for firmness, moisture and fat content, low salt content and low taste were related to low consumer preference.

  18. Chemometric characterization of fruit juices from Spanish cultivars according to their phenolic compound contents: I. Citrus fruits.

    PubMed

    Abad-García, Beatriz; Berrueta, Luis A; Garmón-Lobato, Sergio; Urkaregi, Arantza; Gallo, Blanca; Vicente, Francisca

    2012-04-11

    The data set composed by phenolic compound profiles of 83 Citrus juices (determined by HPLC-DAD-MS/MS) was evaluated by chemometrics to differentiate them according to Citrus species (sweet orange, tangerine, lemon, and grapefruit). Cluster analysis (CA) and principal component analysis (PCA) showed natural sample grouping among Citrus species and even the Citrus subclass. Most of the information contained in the full data set can be captured if only 15 phenolic compounds (concentration ≥10 mg/L), which can be quantified with fast and accurate methods in real samples, are introduced in the models; a good classification which allows the confirmation of the authenticity of juices is achieved by linear discriminant analysis. Using this reduced data set, fast and routine methods have been developed for predicting the percentage of grapefruit in adulterated sweet orange juices using principal component regression (PCR) and partial least-squares regression (PLS). The PLS model has provided suitable estimation errors.

  19. A chemometric approach to characterization of ionic liquids for gas chromatography.

    PubMed

    González-Álvarez, Jaime; Mangas-Alonso, Juan José; Arias-Abrodo, Pilar; Gutiérrez-Álvarez, María Dolores

    2014-05-01

    A chemometric study was carried out to characterize three ionic liquid types (ILs) with hexacationic imidazolium, polymeric imidazolium, and phosphonium cationic cores, using a range of contra-anions such as halogens, thiocyanate, boron anions, triflate, and bistriflimide. The solvation parameter model developed by Abraham et al., unsupervised techniques as cluster analysis (CA), and supervised techniques as linear discriminant analysis (LDA), step-LDA, quadratic discriminant analysis (QDA), and multivariate regression techniques as discriminant partial least squares (D-PLS), or multiple linear regression (MLR) were used to characterize the functionalized ILs above. CA established two main groups of phases, those with an acidic H-bond and those with basic ones. Once detected, the two natural groups, a linear and quadratic delimiters with good classification (>96 %) and prediction (>92 %) capacities were computed. The use of step-LDA technique allowed us to establish that a, b, and s solvation parameters were the most discriminant variables. These variables were used for modeling purposes, and a D-PLS and MLR models were constructed using a binary response. The explained variance of categorical variable by the model validated by cross-validation was 65 %, and 94.5 % of ILs were correctly predicted. IL characterization carried out would allow the appropriate selection of phases for gas chromatography (GC).

  20. Rapid detection of peanut oil adulteration using low-field nuclear magnetic resonance and chemometrics.

    PubMed

    Zhu, Wenran; Wang, Xin; Chen, Lihua

    2017-02-01

    (1)H low-field nuclear magnetic resonance (LF-NMR) and chemometrics were employed to screen the quality changes of peanut oil (PEO) adulterated with soybean oil (SO), rapeseed oil (RO), or palm oil (PAO) in ratios ranging from 0% to 100%. Significant differences in the LF-NMR parameters, single component relaxation time (T2W), and peak area proportion (S21 and S22), were detected between pure and adulterated peanut oil samples. As the ratio of adulteration increased, the T2W, S21, and S22 changed linearly; however, the multicomponent relaxation times (T21 and T22) changed slightly. The established principal component analysis or discriminant analysis models can correctly differentiate authentic PEO from fake and adulterated samples with at least 10% of SO, RO, or PAO. The binary blends of oils can be clearly classified by discriminant analysis when the adulteration ratio is above 30%, illustrating possible applications in screening the oil species in peanut oil blends. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Investigation of Size and Morphology of Chitosan Nanoparticles Used in Drug Delivery System Employing Chemometric Technique

    PubMed Central

    Khanmohammadi, Mohammadreza; Elmizadeh, Hamideh; Ghasemi, Keyvan

    2015-01-01

    The polymeric nanoparticles are prepared from biocompatible polymers in size between 10-1000 nm. Chitosan is a biocompatible polymer that - can be utilized as drug delivery systems. In this study, chitosan nanoparticles were synthesized using an optimized spontaneous emulsification method. Determining particle size and morphology are two critical parameters in nanotechnology. The aim of this study is to introduce methodology based on relation between particle size and diffuse reflectance infrared fourier transform (DRIFT) spectroscopy technique. Partial least squares (PLS) technique was used to estimate the average particle size based on DRIFT spectra. Forty two different chitosan nanoparticle samples with different particle sizes were analyzed using DRIFT spectrometry and the obtained data were processed by PLS. Results obtained from the real samples were compared to those obtained using field emission scanning electron microscope(FE-SEM) as a reference method. It was observed that PLS could correctly predict the average particle size of synthesized sample. Nanoparticles and their morphological state were determined by FE-SEM. Based on morphological characteristics analyzing with proposed method the samples were separated into two groups of "appropriate" and "inappropriate". Chemometrics methods such as principal component analysis, cluster analysis (CA) and linear discriminate analysis (LDA) were used to classify chitosan nanoparticles in terms of morphology. The percent of correctly classified samples using LDA were 100 %and 90% for training and test sets, respectively. PMID:26330855

  2. Investigation of Size and Morphology of Chitosan Nanoparticles Used in Drug Delivery System Employing Chemometric Technique.

    PubMed

    Khanmohammadi, Mohammadreza; Elmizadeh, Hamideh; Ghasemi, Keyvan

    2015-01-01

    The polymeric nanoparticles are prepared from biocompatible polymers in size between 10-1000 nm. Chitosan is a biocompatible polymer that - can be utilized as drug delivery systems. In this study, chitosan nanoparticles were synthesized using an optimized spontaneous emulsification method. Determining particle size and morphology are two critical parameters in nanotechnology. The aim of this study is to introduce methodology based on relation between particle size and diffuse reflectance infrared fourier transform (DRIFT) spectroscopy technique. Partial least squares (PLS) technique was used to estimate the average particle size based on DRIFT spectra. Forty two different chitosan nanoparticle samples with different particle sizes were analyzed using DRIFT spectrometry and the obtained data were processed by PLS. Results obtained from the real samples were compared to those obtained using field emission scanning electron microscope(FE-SEM) as a reference method. It was observed that PLS could correctly predict the average particle size of synthesized sample. Nanoparticles and their morphological state were determined by FE-SEM. Based on morphological characteristics analyzing with proposed method the samples were separated into two groups of "appropriate" and "inappropriate". Chemometrics methods such as principal component analysis, cluster analysis (CA) and linear discriminate analysis (LDA) were used to classify chitosan nanoparticles in terms of morphology. The percent of correctly classified samples using LDA were 100 %and 90% for training and test sets, respectively.

  3. Differentiation of Crataegus spp. guided by nuclear magnetic resonance spectrometry with chemometric analyses.

    PubMed

    Lund, Jensen A; Brown, Paula N; Shipley, Paul R

    2017-09-01

    For compliance with US Current Good Manufacturing Practice regulations for dietary supplements, manufacturers must provide identity of source plant material. Despite the popularity of hawthorn as a dietary supplement, relatively little is known about the comparative phytochemistry of different hawthorn species, and in particular North American hawthorns. The combination of NMR spectrometry with chemometric analyses offers an innovative approach to differentiating hawthorn species and exploring the phytochemistry. Two European and two North American species, harvested from a farm trial in late summer 2008, were analyzed by standard 1D (1)H and J-resolved (JRES) experiments. The data were preprocessed and modelled by principal component analysis (PCA). A supervised model was then generated by partial least squares-discriminant analysis (PLS-DA) for classification and evaluated by cross validation. Supervised random forests models were constructed from the dataset to explore the potential of machine learning for identification of unique patterns across species. 1D (1)H NMR data yielded increased differentiation over the JRES data. The random forests results correlated with PLS-DA results and outperformed PLS-DA in classification accuracy. In all of these analyses differentiation of the Crataegus spp. was best achieved by focusing on the NMR spectral region that contains signals unique to plant phenolic compounds. Identification of potentially significant metabolites for differentiation between species was approached using univariate techniques including significance analysis of microarrays and Kruskall-Wallis tests. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    PubMed

    Ríos-Reina, Rocío; Elcoroaristizabal, Saioa; Ocaña-González, Juan A; García-González, Diego L; Amigo, José M; Callejón, Raquel M

    2017-09-01

    This work assesses the potential of multidimensional fluorescence spectroscopy combined with chemometrics for characterization and authentication of Spanish Protected Designation of Origin (PDO) wine vinegars. Seventy-nine vinegars of different categories (aged and sweet) belonging to the Spanish PDOs "Vinagre de Jerez", "Vinagre de Montilla-Moriles" and "Vinagre de Condado de Huelva", were analyzed by excitation-emission fluorescence spectroscopy. A visual assessment of fluorescence landscapes pointed out different trends with vinegar categories. PARAllel FACtor analysis (PARAFAC) extracted the potential fluorophores and their values in the PDO vinegars. This information, coupled with different classification methods (Partial Least Square Discrimination Analysis "PLS-DA" and Support Vectors Machines "SVM"), was able to discriminate the wine vinegar category within each PDO, for which SVM models obtained better results (>92% of classification). In each category, SVM also allows the differentiation between PDOs. The proposed methodology could be used as an analysis method for the authentication of Spanish PDO wine vinegars. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Diagnosis of early-stage esophageal cancer by Raman spectroscopy and chemometric techniques.

    PubMed

    Ishigaki, Mika; Maeda, Yasuhiro; Taketani, Akinori; Andriana, Bibin B; Ishihara, Ryu; Wongravee, Kanet; Ozaki, Yukihiro; Sato, Hidetoshi

    2016-02-07

    Esophageal cancer is a disease with high mortality. In order to improve the 5 year survival rate after cancer treatment, it is important to develop a method for early detection of the cancer and for therapy support. There is increasing evidence that Raman spectroscopy, in combination with chemometric analysis, is a powerful technique for discriminating pre-cancerous and cancerous biochemical changes. In the present study, we used Raman spectroscopy to examine early-stage (stages 0 and I) esophageal cancer samples ex vivo. Comparison between the Raman spectra of cancerous and normal samples using a t-test showed decreased concentrations of glycogen, collagen, and tryptophan in cancerous tissue. Partial least squares regression (PLSR) analysis and self-organization maps (SOMs) discriminated the datasets of cancerous and normal samples into two groups, but there was a relatively large overlap between them. Linear discriminant analysis (LDA) based on Raman bands found in the t-test was able to predict the tissue types with 81.0% sensitivity and 94.0% specificity.

  6. Multivariate Chemometrics with Regression and Classification Analyses in Heroin Profiling Based on the Chromatographic Data.

    PubMed

    B Gadžurić, Slobodan; O Podunavac Kuzmanović, Sanja; B Vraneš, Milan; Petrin, Marija; Bugarski, Tatjana; Kovačević, Strahinja Z

    2016-01-01

    The purpose of this work is to promote and facilitate forensic profiling and chemical analysis of illicit drug samples in order to determine their origin, methods of production and transfer through the country. The article is based on the gas chromatography analysis of heroin samples seized from three different locations in Serbia. Chemometric approach with appropriate statistical tools (multiple-linear regression (MLR), hierarchical cluster analysis (HCA) and Wald-Wolfowitz run (WWR) test) were applied on chromatographic data of heroin samples in order to correlate and examine the geographic origin of seized heroin samples. The best MLR models were further validated by leave-one-out technique as well as by the calculation of basic statistical parameters for the established models. To confirm the predictive power of the models, external set of heroin samples was used. High agreement between experimental and predicted values of acetyl thebaol and diacetyl morphine peak ratio, obtained in the validation procedure, indicated the good quality of derived MLR models. WWR test showed which examined heroin samples come from the same population, and HCA was applied in order to overview the similarities among the studied heroine samples.

  7. Targeted and non-targeted detection of lemon juice adulteration by LC-MS and chemometrics.

    PubMed

    Wang, Zhengfang; Jablonski, Joseph E

    2016-01-01

    Economically motivated adulteration (EMA) of lemon juice was detected by LC-MS and principal component analysis (PCA). Twenty-two batches of freshly squeezed lemon juice were adulterated by adding an aqueous solution containing 5% citric acid and 6% sucrose to pure lemon juice to obtain 30%, 60% and 100% lemon juice samples. Their total titratable acidities, °Brix and pH values were measured, and then all the lemon juice samples were subject to LC-MS analysis. Concentrations of hesperidin and eriocitrin, major phenolic components of lemon juice, were quantified. The PCA score plots for LC-MS datasets were used to preview the classification of pure and adulterated lemon juice samples. Results showed a large inherent variability in the chemical properties among 22 batches of 100% lemon juice samples. Measurement or quantitation of one or several chemical properties (targeted detection) was not effective in detecting lemon juice adulteration. However, by using the LC-MS datasets, including both chromatographic and mass spectrometric information, 100% lemon juice samples were successfully differentiated from adulterated samples containing 30% lemon juice in the PCA score plot. LC-MS coupled with chemometric analysis can be a complement to existing methods for detecting juice adulteration.

  8. Evaluation of chemical components and properties of the jujube fruit using near infrared spectroscopy and chemometrics.

    PubMed

    Guo, Ying; Ni, Yongnian; Kokot, Serge

    2016-01-15

    Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of spectra of the jujube (Zizyphus jujuba Mill.) fruit samples from four geographical regions. Prediction models were developed for the quantitative prediction of the contents of jujube fruit, i.e., total sugar, total acid, total phenolic content, and total antioxidant activity. Four pattern recognition methods, principal component analysis (PCA), linear discriminant analysis (LDA), least squares-support vector machines (LS-SVM), and back propagation-artificial neural networks (BP-ANN), were used for the geographical origin classification. Furthermore, three multivariate calibration models based on the standard normal variate (SNV) pretreated NIR spectroscopy, partial least squares (PLS), BP-ANN, and LS-SVM were constructed for quantitative analysis of the four analytes described above. PCA provided a useful qualitative plot of the four types of NIR spectra from the fruit. The LS-SVM model produced best quantitative prediction results. Thus, NIR spectroscopy in conjunction with chemometrics, is a very useful and rapid technique for the discrimination of jujube fruit. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. Evaluation of chemical components and properties of the jujube fruit using near infrared spectroscopy and chemometrics

    NASA Astrophysics Data System (ADS)

    Guo, Ying; Ni, Yongnian; Kokot, Serge

    2016-01-01

    Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of spectra of the jujube (Zizyphus jujuba Mill.) fruit samples from four geographical regions. Prediction models were developed for the quantitative prediction of the contents of jujube fruit, i.e., total sugar, total acid, total phenolic content, and total antioxidant activity. Four pattern recognition methods, principal component analysis (PCA), linear discriminant analysis (LDA), least squares-support vector machines (LS-SVM), and back propagation-artificial neural networks (BP-ANN), were used for the geographical origin classification. Furthermore, three multivariate calibration models based on the standard normal variate (SNV) pretreated NIR spectroscopy, partial least squares (PLS), BP-ANN, and LS-SVM were constructed for quantitative analysis of the four analytes described above. PCA provided a useful qualitative plot of the four types of NIR spectra from the fruit. The LS-SVM model produced best quantitative prediction results. Thus, NIR spectroscopy in conjunction with chemometrics, is a very useful and rapid technique for the discrimination of jujube fruit.

  10. A rapid new approach for the quality evaluation of the folk medicine Dianbaizhu based on chemometrics.

    PubMed

    Liu, Zizhen; Jiang, Rui; Xie, Meng; Xu, Guanling; Liu, Weirui; Wang, Xiaohong; Lin, Hongying; Lu, Jianqiu; She, Gaimei

    2014-01-01

    Dianbaizhu, a folk medicine from Gaultheria leucocarpa BLUME var. yunnanensis (FRANCH.) T. Z. HSU & R. C. FANG (Ericaceae) used as an antirheumatic, has multiple plant origins and officinal parts. A rapid high-performance liquid chromatography with diode array detector (HPLC-DAD) method was established for the simultaneous determination of the characteristic ingredient methyl benzoate-2-O-β-D-glucopyranosyl(1 → 2) [O-β-D-xylopyranosyl(1 → 6)]-O-β-D-glucopyranoside and seven bioactive constituents in eight Gaultheria species. This chromatographic method is precise, accurate, and stable. Kruskal-Wallis analysis, hierarchical cluster analysis, and factor analysis were used to analyze the content of reference compounds in different Gaultheria species and officinal parts. The analyses showed significant differences (p<0.05) in Gaultheria species but few differences (p>0.05) in their medicinal parts. G. leucocarpa var. yunnanensis appeared to the best among the Gaultheria species tested for the treatment of rheumatic diseases. Taken together, the results show that this simultaneous quantification of multiple active constituents using HPLC-DAD combined with chemometrics can be reliably applied to evaluate the quality of Dianbaizhu.

  11. Spatial assessment of water quality using chemometrics in the Pearl River Estuary, China

    NASA Astrophysics Data System (ADS)

    Wu, Meilin; Wang, Youshao; Dong, Junde; Sun, Fulin; Wang, Yutu; Hong, Yiguo

    2017-03-01

    A cruise was commissioned in the summer of 2009 to evaluate water quality in the Pearl River Estuary (PRE). Chemometrics such as Principal Component Analysis (PCA), Cluster analysis (CA) and Self-Organizing Map (SOM) were employed to identify anthropogenic and natural influences on estuary water quality. The scores of stations in the surface layer in the first principal component (PC1) were related to NH4-N, PO4-P, NO2-N, NO3-N, TP, and Chlorophyll a while salinity, turbidity, and SiO3-Si in the second principal component (PC2). Similarly, the scores of stations in the bottom layers in PC1 were related to PO4-P, NO2-N, NO3-N, and TP, while salinity, Chlorophyll a, NH4-N, and SiO3-Si in PC2. Results of the PCA identified the spatial distribution of the surface and bottom water quality, namely the Guangzhou urban reach, Middle reach, and Lower reach of the estuary. Both cluster analysis and PCA produced the similar results. Self-organizing map delineated the Guangzhou urban reach of the Pearl River that was mainly influenced by human activities. The middle and lower reaches of the PRE were mainly influenced by the waters in the South China Sea. The information extracted by PCA, CA, and SOM would be very useful to regional agencies in developing a strategy to carry out scientific plans for resource use based on marine system functions.

  12. Multi-elemental profiling and chemo-metric validation revealed nutritional qualities of Zingiber officinale.

    PubMed

    Pandotra, Pankaj; Viz, Bhavana; Ram, Gandhi; Gupta, Ajai Prakash; Gupta, Suphla

    2015-04-01

    Ginger rhizome is a valued food, spice and an important ingredient of traditional systems of medicine of India, China and Japan. An Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) based multi-elemental profiling was performed to assess the quantitative complement of elements, nutritional quality and toxicity of 46 ginger germplasms, collected from the north western Himalayan India. The abundance of eighteen elements quantified in the acid digested rhizomes was observed to be K>Mg>Fe>Ca>Na>Mn>Zn>Ba>Cu>Cr>Ni>Pb>Co>Se>As>Be>Cd. Toxic element, Hg was not detected in any of the investigated samples. Chemometric analyses showed positive correlation among most of the elements. No negative correlation was observed in any of the metals under investigation. UPGMA based clustering analysis of the quantitative data grouped all the 46 samples into three major clusters, displaying 88% similarity in their metal composition, while eighteen metals investigated grouped into two major clusters. Quantitatively, all the elements analyzed were below the permissible limits laid down by World Health Organization. The results were further validated by cluster analysis (CA) and principal component analysis (PCA) to understand the ionome of the ginger rhizome. The study suggested raw ginger to be a good source of beneficial elements/minerals like Mg, Ca, Mn, Fe, Cu and Zn and will provide platform for understanding the functional and physiological status of ginger rhizome.

  13. Chemometric Assessment of Chromatographic Methods for Herbal Medicines Authentication and Fingerprinting.

    PubMed

    Sima, Ioana Anamaria; Andrási, Melinda; Sârbu, Costel

    2017-09-07

    Nowadays, increasingly more individuals turn to supplementation of the diet with herbal medicines and many such products are marketed lately. Thus the problem that this article focuses on is that these products are not subjected to rigorous quality control like synthetic drugs are, which rises a constant debate whether the supplements actually contain the herb or mixture of herbs that the manufacturer claims they do. As a solution, micellar electrokinetic chromatography and high performance liquid chromatography were investigated in order to fingerprint and authenticate herbal medicines. For this purpose, minimal sample pre-treatment was applied to several fruit based herbal medicines, which were compared with the ethanolic extract of the respective fruit. The holistic evaluation of the electropherograms and chromatograms was made by using appropriate chemometric tools, such as principal component analysis (PCA), cluster analysis and a combination of PCA and linear discriminant analysis (PCA-LDA). The results suggest that the developed method was able to successfully discriminate between different herbal medicines, based on their raw material content. Moreover, this simple and efficient methodology might also be used for routine screening and authenticity control of different products and could be implemented in any quality control laboratory. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  14. Multivariate Chemometrics with Regression and Classification Analyses in Heroin Profiling Based on the Chromatographic Data

    PubMed Central

    B. Gadžurić, Slobodan; O. Podunavac Kuzmanović, Sanja; B. Vraneš, Milan; Petrin, Marija; Bugarski, Tatjana; Kovačević, Strahinja Z.

    2016-01-01

    The purpose of this work is to promote and facilitate forensic profiling and chemical analysis of illicit drug samples in order to determine their origin, methods of production and transfer through the country. The article is based on the gas chromatography analysis of heroin samples seized from three different locations in Serbia. Chemometric approach with appropriate statistical tools (multiple-linear regression (MLR), hierarchical cluster analysis (HCA) and Wald-Wolfowitz run (WWR) test) were applied on chromatographic data of heroin samples in order to correlate and examine the geographic origin of seized heroin samples. The best MLR models were further validated by leave-one-out technique as well as by the calculation of basic statistical parameters for the established models. To confirm the predictive power of the models, external set of heroin samples was used. High agreement between experimental and predicted values of acetyl thebaol and diacetyl morphine peak ratio, obtained in the validation procedure, indicated the good quality of derived MLR models. WWR test showed which examined heroin samples come from the same population, and HCA was applied in order to overview the similarities among the studied heroine samples. PMID:28243268

  15. Comparisons of large (Vaccinium macrocarpon Ait.) and small (Vaccinium oxycoccos L., Vaccinium vitis-idaea L.) cranberry in British Columbia by phytochemical determination, antioxidant potential, and metabolomic profiling with chemometric analysis.

    PubMed

    Brown, Paula N; Turi, Christina E; Shipley, Paul R; Murch, Susan J

    2012-04-01

    There is a long history of use and modern commercial importance of large and small cranberries in North America. The central objective of the current research was to characterize and compare the chemical composition of 2 west coast small cranberry species traditionally used (Vaccinium oxycoccos L. and Vaccinium vitis-idaea L.) with the commercially cultivated large cranberry (Vaccinium macrocarpon Ait.) indigenous to the east coast of North America. V. oxycoccos and V. macrocarpon contained the 5 major anthocyanins known in cranberry; however, the ratio of glycosylated peonidins to cyanidins varied, and V. vitis-idaea did not contain measurable amounts of glycosylated peonidins. Extracts of all three berries were found to contain serotonin, melatonin, and ascorbic acid. Antioxidant activity was not found to correlate with indolamine levels while anthocyanin content showed a negative correlation, and vitamin C content positively correlated. From the metabolomics profiles, 4624 compounds were found conserved across V. macrocarpon, V. oxycoccoS, and V. vitis-idaea with a total of approximately 8000-10 000 phytochemicals detected in each species. From significance analysis, it was found that 2 compounds in V. macrocarpoN, 3 in V. oxycoccos, and 5 in V. vitis-idaea were key to the characterization and differentiation of these cranberry metabolomes. Through multivariate modeling, differentiation of the species was observed, and univariate statistical analysis was employed to provide a quality assessment of the models developed for the metabolomics data. © Georg Thieme Verlag KG Stuttgart · New York.

  16. A novel strategy for the determination of enantiomeric compositions of chiral compounds by chemometric analysis of the UV-vis spectra of bovine serum albumin receptor-ligand mixtures

    NASA Astrophysics Data System (ADS)

    Wang, Yunxia; Zhang, Fang; Liang, Jing; Li, Hua; Kong, Jilie

    2007-10-01

    In this work, a novel strategy was constructed to determine the enantiomeric composition of chiral substances discriminated by bovine serum albumin (BSA) based on the UV-vis spectra of the receptor-ligand mixtures coupled with partial least squares (PLS-1) analysis. Taking tryptophan (Trp) enantiomer as an example, when 20 μM BSA was used, the enantiomeric composition was accurately determined with concentration of only 100 nM and the corresponding enantiomeric excess as high as 98% (or -98%), which is relatively more sensitive than in literature. Furthermore, the BSA-based approach was also used to predict the enantiomeric composition of other chiral compounds, such as phenylalanine (Phe), tyrosine (Tyr), alanine (Ala), cysteine (Cys), DOPA and propranolol (Prop). The results fully demonstrate that BSA is effective in determination of enantiomeric composition of some chiral compounds.

  17. Kinetic fluorescence quenching of CdS quantum dots in the presence of Cu(II): chemometrics-assisted resolving of the kinetic data and quantitative analysis of Cu(II).

    PubMed

    Abdollahi, Hamid; Shamsipur, Mojtaba; Barati, Ali

    2014-06-05

    In this work, the kinetic fluorescence behavior of CdS quantum dots (QDs) in the presence of Cu(II) was investigated. In contrast to some other transition metal ions such as Ag(I), Ni(II), and Hg(II), a gradual red-shift in the emission spectrum of CdS QDs was observed for Cu(II) during the reaction course. More investigations revealed the existence of two chemical components in the recorded kinetic data in the presence of Cu(II). Multivariate curve resolution-alternating least squares (MCR-ALS) method was applied in order to extract pure emission spectra and time-dependent profiles of these two components at different concentrations of Cu(II). The results obtained from resolving the data by MCR-ALS got some information about the mechanism of the interaction between CdS QDs and Cu(II) ions which were in good agreement with those reported in the literature. Moreover, the multivariate method of analysis, partial least-squares (PLS) method, was used to develop a multivariate calibration model for quantitative analysis of Cu(II) using the entire kinetic data sets. The calibration and validation sets were created ranging from 0.02 to 1μM of Cu(II) and were successfully calibrated and predicted by the PLS model. This method allowed a sensitive determination of Cu(II) ions with a detection limit of 13nM based on three times of the standard deviation corresponding to PLS regression.

  18. 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

  19. Chemometric approach to develop frying stable sunflower oil blends stabilized with oleoresin rosemary and ascorbyl palmitate.

    PubMed

    Upadhyay, Rohit; Sehwag, Sneha; Niwas Mishra, Hari

    2017-03-01

    The frying performance of sunflower oil blends (SOBs) stabilized with oleoresin rosemary (Rosmarinus officinalis L.) (ROSM) (200-1500mg/kg) and ascorbyl palmitate (AP) (100-300mg/kg) were tested for 18hopen pan-frying. Sunflower oil with TBHQ (SOTBHQ) (200mg/kg) and without additives (SOcontrol) served as positive and negative controls, respectively. The frying stability was monitored over time by estimating the levels of conjugated dienes, total polar compounds, polymeric compounds viz., triglyceride polymers, dimers, oxidized triglyceride monomers, diglycerides and free fatty acids, and induction period based on Rancimat. Chemometric tools were used to classify the oil samples based on frying stability. Thermo-oxidative changes were reduced significantly for blends stabilized with ROSM and AP (p<0.05). Principal component analysis (PCA) and hierarchical cluster analysis (HCA) distinguished SOBs from positive controls. A formulation consisting of 1309.62 and 129.29mg/kg of ROSM and AP, respectively, was optimized using a hybrid PCA-RSM approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. 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.

  1. Laser induced breakdown spectroscopy and characterization of environmental matrices utilizing multivariate chemometrics

    NASA Astrophysics Data System (ADS)

    Mukhono, P. M.; Angeyo, K. H.; Dehayem-Kamadjeu, A.; Kaduki, K. A.

    2013-09-01

    We exploited multivariate chemometric methods to reduce the spectral complexity and to retrieve trace heavy metal analyte concentration signatures directly from the LIBS spectra as well as, to extract their latent characteristics in two important environmental samples i.e. soils and rocks from a geothermal field lying in a high background radiation area (HBRA). As, Cr, Cu, Pb and Ti were modeled for direct trace (quantitative) analysis using partial least squares (PLS) and artificial neural networks (ANNs). PLS performed better in soils than in rocks; the use of ANN improved the accuracies in rocks because ANNs are more robust than PLS at modeling spectral non-linearities and correcting matrix effects. The predicted trace metal profiles together with atomic and molecular signatures acquired using single ablation in the 200-545 nm spectral range were utilized to successfully classify and identify the soils and rocks with regard to whether they were derived from (i) a high background radiation area (HBRA)-geothermal, (ii) HBRA-non-geothermal or (iii) normal background radiation area (NBRA)-geothermal field using principal components analysis (PCA) and soft independent modeling of class analogy (SIMCA).

  2. 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.

  3. Influence of minerals on the taste of bottled and tap water: a chemometric approach.

    PubMed

    Platikanov, Stefan; Garcia, Veronica; Fonseca, Ignacio; Rullán, Elena; Devesa, Ricard; Tauler, Roma

    2013-02-01

    Chemometric analysis was performed on two sets of sensory data obtained from two separate studies. Twenty commercially-available bottled mineral water samples (from the first study) and twenty-five drinking tap and bottled water samples (from the second study) were blind tasted by trained panelists. The panelists expressed their overall liking of the water samples by rating from 0 (worst flavor) to 10 (best flavor). The mean overall score was compared to the physicochemical properties of the samples. Thirteen different physicochemical parameters were considered in both studies and, additionally, residual chlorine levels were assessed in the second study. Principal component analysis performed on the physicochemical parameters and the panelists' mean scores generated models that explain most of the total data variance. Moreover, partial least squares regression of the panelists' sensory evaluations of the physicochemical data helped elucidate the main features underlying the panelists' ratings. The preferred bottled and tap water samples were associated with moderate (relatively to the parameters mean values) contents of total dissolved solids and with relatively high concentrations of HCO₃⁻, SO₄²⁻, Ca²⁺ and Mg²⁺ as well as with relatively high pH values. High concentrations of Na⁺, K⁺ and Cl⁻ were scored low by many of the panelists, while residual chlorine did not affect the ratings, but did enable the panel to distinguish between bottled mineral water and tap water samples. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    2011-02-01

    Quality control of toys for avoiding children exposure to potentially toxic elements is of utmost relevance and it is a common requirement in national and/or international norms for health and safety reasons. Laser-induced breakdown spectroscopy (LIBS) was recently evaluated at authors' laboratory for direct analysis of plastic toys and one of the main difficulties for the determination of Cd, Cr and Pb was the variety of mixtures and types of polymers. As most norms rely on migration (lixiviation) protocols, chemometric classification models from LIBS spectra were tested for sampling toys that present potential risk of Cd, Cr and Pb contamination. The classification models were generated from the emission spectra of 51 polymeric toys and by using Partial Least Squares - Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogy (SIMCA) and K-Nearest Neighbor (KNN). The classification models and validations were carried out with 40 and 11 test samples, respectively. Best results were obtained when KNN was used, with corrected predictions varying from 95% for Cd to 100% for Cr and Pb.

  5. Investigation of the chemical composition-antibacterial activity relationship of essential oils by chemometric methods.

    PubMed

    Miladinović, Dragoljub L; Ilić, Budimir S; Mihajilov-Krstev, Tatjana M; Nikolić, Nikola D; Miladinović, Ljiljana C; Cvetković, Olga G

    2012-05-01

    The antibacterial effects of Thymus vulgaris (Lamiaceae), Lavandula angustifolia (Lamiaceae), and Calamintha nepeta (Lamiaceae) Savi subsp. nepeta var. subisodonda (Borb.) Hayek essential oils on five different bacteria were estimated. Laboratory control strain and clinical isolates from different pathogenic media were researched by broth microdilution method, with an emphasis on a chemical composition-antibacterial activity relationship. The main constituents of thyme oil were thymol (59.95%) and p-cymene (18.34%). Linalool acetate (38.23%) and β-linalool (35.01%) were main compounds in lavender oil. C. nepeta essential oil was characterized by a high percentage of piperitone oxide (59.07%) and limonene (9.05%). Essential oils have been found to have antimicrobial activity against all tested microorganisms. Classification and comparison of essential oils on the basis of their chemical composition and antibacterial activity were made by utilization of appropriate chemometric methods. The chemical principal component analysis (PCA) and hierachical cluster analysis (HCA) separated essential oils into two groups and two sub-groups. Thyme essential oil forms separate chemical HCA group and exhibits highest antibacterial activity, similar to tetracycline. Essential oils of lavender and C. nepeta in the same chemical HCA group were classified in different groups, within antibacterial PCA and HCA analyses. Lavender oil exhibits higher antibacterial ability in comparison with C. nepeta essential oil, probably based on the concept of synergistic activity of essential oil components.

  6. Pharmacophore identification by molecular modeling and chemometrics: The case of HMG-CoA reductase inhibitors

    NASA Astrophysics Data System (ADS)

    Cosentino, U.; Moro, G.; Pitea, D.; Scolastico, S.; Todeschini, R.; Scolastico, C.

    1992-02-01

    A methodology based on molecular modeling and chemometrics is applied to identify the geometrical pharmacophore and the stereoelectronic requirements for the activity in a series of inhibitors of 3-hydroxy 3-methylglutaryl coenzyme A (HMG-CoA) reductase, an enzyme involved in cholesterol biosynthesis. These inhibitors present two common structural features—a 3,5-dihydroxy heptanoic acid which mimics the active portion of the natural substrate HMG-CoA and a lipophilic region which carries both polar and bulky groups. A total of 432 minimum energy conformations of 11 homologous compounds showing different levels of biological activity are calculated by the molecular mechanics MM2 method. Five atoms are selected as representatives of the relevant fragments of these compounds and three interatomic distances, selected among 10 by means of a Principal Component Analysis (PCA), are used to describe the three-dimensional disposition of these atoms. A cluster analysis procedure, performed on the whole set of conformations described by these three distances, allows the selection of one cluster whose centroid represents a geometrical model for the HMG-CoA reductase pharmacophore and the conformations included are candidates as binding conformations. To obtain a refinement of the geometrical model and to have a better insight into the requirements for the activity of these inhibitors, the Molecular Electrostatic Potential (MEP) distributions are determined by the MNDO semiempirical method.

  7. Identification of Colitis and Cancer in Colon Biopsies by Fourier Transform Infrared Spectroscopy and Chemometrics

    PubMed Central

    Li, Xiang; Li, Qing-Bo; Zhang, Guang-Jun; Xu, Yi-Zhuang; Sun, Xue-Jun; Shi, Jing-Sen; Zhang, Yuan-Fu; Wu, Jin-Guang

    2012-01-01

    Cancer is a disease that does great harms to the health of human beings. FT-IR spectroscopy could identify variability at the molecular level in biological specimens. It is a rapid and noninvasive method, which could be used intraoperatively to modify surgical procedures. The aim of this paper is to identify and separate cancer from colitis in endoscopic colon biopsies through the use of FT-IR spectroscopy. A total of 88 endoscopic colon samples, including 41 cases of colitis and 47 cases of colon cancer, were obtained. Specimens were placed on an ATR accessory linked to FT-IR spectrometer with a MCT detector for greater stability and sensitivity. Later, specimens were sent for the histological examination as the reference in the spectral analysis. 41 colitis and 47 cancer specimens were compared. Spectra preprocessed with smoothing and normalization were used for discrimination analysis. PCA was processed to simplify the spectrum data set. Naive Bayes classifier model was constructed for diagnostic classification. Leave-one-out cross-validation method was utilized to assess the discrimination results. The sensitivity of FT-IR detection for cancer achieves 97.6%. The results showed that colon cancer could be distinguished from colitis with high accuracy using FT-IR spectroscopy and chemometrics. PMID:22645472

  8. 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.

  9. Preliminary chemometric study on the use of honey as an environmental marker in Galicia (northwestern Spain).

    PubMed

    Rodríguez García, Juan Carlos; Iglesias Rodríguez, Roberto; Peña Crecente, Rosa María; Barciela García, Julia; García Martín, Sagrario; Herrero Latorre, Carlos

    2006-09-20

    Thirteen metal elements were determined in 40 honey samples from Galicia with different environmental origins: rural, urban, and industrial areas. The data set of the honey metallic profiles was studied with a double purpose: first, to make a preliminary evaluation of honey as an environmental indicator in Galicia with the aim of monitoring pollution and, second, to compare the different capabilities of diverse pattern recognition prediction procedures for modeling the environmental surrounding of the hive. A certain level of similarity for urban and industrial samples was obtained using principal component analysis and cluster analysis, whereas significant differences for urban and industrial honeys were found in relation to rural honey samples. Different classification rules to associate metal content of honeys with their environmental surrounding were obtained by chemometric pattern recognition procedures. In general, the classification methods developed by neural networks provided better results than the traditional pattern recognition procedures. The metal profiles of honey seem to provide sufficient information to enable categorization criteria for classifying samples according to their environmental surrounding. Thus, honey could be a potential pollution indicator for the Galician area.

  10. 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

  11. Discrimination and identification of RDX/PETN explosives by chemometrics applied to terahertz time-domain spectral imaging

    NASA Astrophysics Data System (ADS)

    Bou-Sleiman, J.; Perraud, J.-B.; Bousquet, B.; Guillet, J.-P.; Palka, N.; Mounaix, P.

    2015-10-01

    Detection of explosives has always been a priority for homeland security. Jointly, terahertz spectroscopy and imaging are emerging and promising candidates as contactless and safe systems. In this work, we treated data resulting from hyperspectral imaging obtained by THz-time domain spectroscopy, with chemometric tools. We found efficient identification and sorting of targeted explosives in the case of pure and mixture samples. In this aim, we applied to images Principal Component Analysis (PCA) to discriminate between RDX, PETN and mixtures of the two materials, using the absorbance as the key-parameter. Then we applied Partial Least Squares-Discriminant Analysis (PLS-DA) to each pixel of the hyperspectral images to sort the explosives into different classes. The results clearly show successful identification and categorization of the explosives under study.

  12. 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.

  13. 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.

  14. Prediction of tablet hardness based on near infrared spectra of raw mixed powders by chemometrics.

    PubMed

    Otsuka, Makoto; Yamane, Ikuro

    2006-07-01

    The purpose of this research is to elucidate the effect of lubricant mixing on tablet hardness by near-infrared (NIR) chemometrics as a basic study of process analytical technology. Formulation cellulose (F-C) consisted of sulpyrine (SP), microcrystalline cellulose (MC), and magnesium stearate (MgSt). Formulation lactose/starch (F-L) consisted of SP bulk drug powder, spray-dried lactose (SL), corn starch (CS), and MgSt. First, F-L and F-C without MgSt were mixed in a twin-shell mixer for 60 min. MgSt was added to the mixed powder, and was mixed for various mixing times, after which the mixed powders were compressed by 8-mm diameter punch and die. NIR spectra of raw mixed powders of F-L and F-C were taken using a reflection type of Fourier transform NIR spectra spectrometer, and chemometric analysis was performed using principal component regression (PCR). The tablet hardnesses of F-L and F-C decreased with increasing mixing time. All NIR spectra of the mixed powders of F-L and F-C fluctuated depending on mixing time. In order to predict tablet hardness before tablet compression, NIR spectra of F-L and F-C mixed powders were analyzed and evaluated for hardness by PCR. The minimum standard error of cross-validation values could be realized by using five- and six-principal component models, respectively. In the cases of F-L and F-C, the relationships between the actual and predicted tablet hardnesses showed straight lines, respectively. In the regression vectors of F-L and FC, the peaks related to hydrogen groups of SP, CS, and MC appeared as positive peaks. In contrast, the peaks related to hydrocarbon due to MgSt appeared as negative peaks in the regression vectors. The calibration models to evaluate the tablet hardness were obtained based on NIR spectra of raw mixed powders by PCR. This approach to predicting tablet hardness prior to compression could be used as a routine test to indicate the quality of the final product without spending time and energy to produce

  15. Quality assessment of crude and processed ginger by high-performance liquid chromatography with diode array detection and mass spectrometry combined with chemometrics.

    PubMed

    Deng, Xianmei; Yu, Jiangyong; Zhao, Ming; Zhao, Bin; Xue, Xingyang; Che, ChunTao; Meng, Jiang; Wang, Shumei

    2015-09-01

    A sensitive, simple, and validated high-performance liquid chromatography with diode array detection and mass spectrometry detection method was developed for three ginger-based traditional Chinese herbal drugs, Zingiberis Rhizoma, Zingiberis Rhizome Preparatum, and Zingiberis Rhizome Carbonisata. Chemometrics methods, such as principal component analysis, hierarchical cluster analysis, and analysis of variance, were also employed in the data analysis. The results clearly revealed significant differences among Zingiberis Rhizoma, Zingiberis Rhizome Preparatum, and Zingiberis Rhizome Carbonisata, indicating variations in their chemical compositions during the processing, which may elucidate the relationship of the thermal treatment with the change of the constituents and interpret their different clinical uses. Furthermore, the sample consistency of Zingiberis Rhizoma, Zingiberis Rhizome Preparatum, and Zingiberis Rhizome Carbonisata can also be visualized by high-performance liquid chromatography with diode array detection and mass spectrometry analysis followed by principal component analysis/hierarchical cluster analysis. The comprehensive strategy of liquid chromatography with mass spectrometry analysis coupled with chemometrics should be useful in quality assurance for ginger-based herbal drugs and other herbal medicines.

  16. 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

  17. Chemometrics-assisted solid-state characterization of pharmaceutically relevant materials. Polymorphic substances.

    PubMed

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

    2017-06-13

    Current regulations command to properly characterize pharmaceutically relevant solid systems. Chemometrics comprise a range of valuable tools, suitable to process large amounts of data and extract valuable information hidden in their structure. This review aims to detail the results of the fruitful association between analytical techniques and chemometrics methods, focusing on those which help to gain insight into the characteristics of drug polymorphism as an important aspect of the solid state of bulk drugs and drug products. Hence, the combination of Raman, terahertz, mid- and near- infrared spectroscopies, as well as instrumental signals resulting from X-ray powder diffraction, (13)C solid state nuclear magnetic resonance spectroscopy and thermal methods with quali-and quantitative chemometrics methodologies are examined. The main issues reviewed, concerning pharmaceutical drug polymorphism, include the use of chemometrics-based approaches to perform polymorph classification and assignment of polymorphic identity, as well as the determination of given polymorphs in simple mixtures and complex systems. Aspects such as the solvation/desolvation of solids, phase transformation, crystallinity and the recrystallization from the amorphous state are also discussed. A brief perspective of the field for the next future is provided, based on the developments of the last decade and the current state of the art of analytical instrumentation and chemometrics methodologies. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Polarographic chemometric determination of zinc and nickel in aqueous samples.

    PubMed

    Moneeb, Marwa S

    2006-12-15

    Polarographic chemometric methods were applied to the determination of zinc and nickel in aqueous solutions previously acidified with 0.1M acetate buffer (pH 4.2). The studied methods are multivariate methods including classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS); derivative ratio methods (first, (1)D and second, (2)D derivative ratio). A comparative study was considered. The studied chemometric methods do not need the presence of any reduction potential shift reagent in spite of the great overlap between the two metals polarograms. A training set consisting of 10 binary mixture solutions in the possible combinations containing 0.13-9.30mug/ml Zn(II) and 0.20-12.25mug/ml Ni(II) was used to develop the chemometric calibrations (CLS, PCR and PLS). A validation set containing the synthetic mixtures in the range of 0.29-9.00mug/ml for Zn(II) and 0.30-11.60mug/ml for Ni(II) was used to validate the multivariate calibrations. Same mixtures were used to develop the derivative ratio methods. The polarograms were recorded and their current values were measured within the potential range -920 to -1052mV at 2mV intervals. The mean percentage recoveries obtained using CLS, PCR and PLS were found to be 99.5+/-1.5%, 100.0+/-1.1% and 100.0+/-1.0% for Zn(II) and 99.4+/-1.3%, 99.7+/-1.2% and 99.9+/-1.0% for Ni(II), respectively. The mean percentage recoveries obtained using (1)D at -950mV, (1)D at -1010mV, (1)D at -950mV-(1)D at -1010mV and (2)D at -986mV for Zn(II) were found to be 99.7+/-1.2%, 99.2+/-1.6%, 99.4+/-1.4% and 99.4+/-1.4%; and using (1)D at -1030mV and (2)D at -1010mV for Ni(II) were found to be 100.5+/-1.3% and 100.4+/-1.3%, respectively. Interferences due to the presence of Cd, Co, Pb, Fe, Mn, Ca, Mg, Cu and Al were studied. The applicability of the proposed methods was assessed through the determination of both metals in tap drinking-water. Samples were subjected if required up to a 20-fold preconcentration

  19. 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.

  20. Classification of frankfurters by FT-Raman spectroscopy and chemometric methods.

    PubMed

    Campos, Náira da Silva; Oliveira, Kamila Sá; Almeida, Mariana Ramos; Stephani, Rodrigo; de Oliveira, Luiz Fernando Cappa

    2014-11-18

    Frankfurters are widely consumed all over the world, and the production requires a wide range of meat and non-meat ingredients. Due to these characteristics, frankfurters are products that can be easily adulterated with lower value meats, and the presence of undeclared species. Adulterations are often still difficult to detect, due the fact that the adulterant components are usually very similar to the authentic product. In this work, FT-Raman spectroscopy was employed as a rapid technique for assessing the quality of frankfurters. Based on information provided by the Raman spectra, a multivariate classification model was developed to identify the frankfurter type. The aim was to study three types of frankfurters (chicken, turkey and mixed meat) according to their Raman spectra, based on the fatty vibrational bands. Classification model was built using partial least square discriminant analysis (PLS-DA) and the performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency and Matthews's correlation coefficient. The PLS-DA models give sensitivity and specificity values on the test set in the ranges of 88%-100%, showing good performance of the classification models. The work shows the Raman spectroscopy with chemometric tools can be used as an analytical tool in quality control of frankfurters.

  1. Tracing the origin of beer samples by NMR and chemometrics: Trappist beers as a case study.

    PubMed

    Mannina, Luisa; Marini, Federico; Antiochia, Riccarda; Cesa, Stefania; Magrì, Antonio; Capitani, Donatella; Sobolev, Anatoly P

    2016-10-01

    An NMR and chemometric analytical approach to classify beers according to their brand identity was developed within the European TRACE project (FP6-2003-FOOD-2-A, contract number: 0060942). Rochefort 8 Trappist beers (47 samples), other Trappist beers (76 samples) and non-Trappist beers (110 samples) were analyzed by (1) H NMR spectroscopy. Selected NMR signals were measured and used to build classification models. Three different classification problems were identified, namely Trappist versus non-Trappist, Rochefort versus Non-Rochefort, and Rochefort 8 versus non-Rochefort 8. In all the three cases, both a discriminant and a modeling approaches were followed, using partial least squares discriminant analysis (PLS-DA) and soft independent modeling of class analogies (SIMCA), respectively, leading to very high classification accuracy as evaluated by external validation. Information regarding chemical composition was also obtained: Trappist beers contain a higher amount of formic and pyruvic acids and a lower amount of acetic acid and alanine with respect to non-Trappist ones. Rochefort beers turned out to have also a higher content of propanol and isopentanol with respect to non-Rochefort samples. Finally, Rochefort 8, shows the highest content of pyruvic acid and the lowest content of gallic, fumaric, acetic acids, adenosine, uridine, 2-phenylethanol, GABA, and alanine.

  2. 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.

  3. The detection and quantification of adulteration in olive oil by near-infrared spectroscopy and chemometrics.

    PubMed

    Christy, Alfred A; Kasemsumran, Sumaporn; Du, Yiping; Ozaki, Yukihiro

    2004-06-01

    A new procedure has been developed for the classification and quantification of the adulteration of pure olive oil by soya oil, sun flower oil, corn oil, walnut oil and hazelnut oil. The study was based on a chemometric analysis of the near-infrared (NIR) spectra of olive-oil mixtures containing different adulterants. The adulteration of olive oil was carefully carried out gravimetrically in a 4 mm quartz cuvette, starting with pure olive oil in the cuvette first. NIR spectra of the 525 adulterated mixtures were measured in the region of 12,000-4000 cm(-1). The spectra were subjected batch wise to multiplicative signal correction (MSC) before calculating the principal component (PCA) models. The MSC-corrected data were subjected to Savitzky-Golay smoothing and a mean normalization procedure before developing partial least-squares calibration (PLS) models. The results revealed that the models predicted the adulterants, corn oil, sun flower oil, soya oil, walnut oil and hazelnut oil involved in olive oil with error limits +/-0.57, +/-1.32, +/-0.96, +/-0.56 and +/-0.57% weight/weight, respectively. Furthermore, the PCA developed models were able to classify unknown adulterated olive oil mixtures with almost 100% certainty. Quantification of the adulterants was carried out using their respective PLS models within the same error limits as mentioned above.

  4. Screening Brazilian C gasoline quality: application of the SIMCA chemometric method to gas chromatographic data.

    PubMed

    Flumignan, Danilo Luiz; Tininis, Aristeu G; Ferreira, Fabrício de O; de Oliveira, José Eduardo

    2007-07-09

    A total of 2400 samples of commercial Brazilian C gasoline were collected over a 6-month period from different gas stations in the São Paulo state, Brazil, and analysed with respect to 12 physicochemical parameters according to regulation 309 of the Brazilian Government Petroleum, Natural Gas and Biofuels Agency (ANP). The percentages (v/v) of hydrocarbons (olefins, aromatics and saturated) were also determined. Hierarchical cluster analysis (HCA) was employed to select 150 representative samples that exhibited least similarity on the basis of their physicochemical parameters and hydrocarbon compositions. The chromatographic profiles of the selected samples were measured by gas chromatography with flame ionisation detection and analysed using soft independent modelling of class analogy (SIMCA) method in order to create a classification scheme to identify conform gasolines according to ANP 309 regulation. Following the optimisation of the SIMCA algorithm, it was possible to classify correctly 96% of the commercial gasoline samples present in the training set of 100. In order to check the quality of the model, an external group of 50 gasoline samples (the prediction set) were analysed and the developed SIMCA model classified 94% of these correctly. The developed chemometric method is recommended for screening commercial gasoline quality and detection of potential adulteration.

  5. Early detection of germinated wheat grains using terahertz image and chemometrics

    PubMed Central

    Jiang, Yuying; Ge, Hongyi; Lian, Feiyu; Zhang, Yuan; Xia, Shanhong

    2016-01-01

    In this paper, we propose a feasible tool that uses a terahertz (THz) imaging system for identifying wheat grains at different stages of germination. The THz spectra of the main changed components of wheat grains, maltose and starch, which were obtained by THz time spectroscopy, were distinctly different. Used for original data compression and feature extraction, principal component analysis (PCA) revealed the changes that occurred in the inner chemical structure during germination. Two thresholds, one indicating the start of the release of α-amylase and the second when it reaches the steady state, were obtained through the first five score images. Thus, the first five PCs were input for the partial least-squares regression (PLSR), least-squares support vector machine (LS-SVM), and back-propagation neural network (BPNN) models, which were used to classify seven different germination times between 0 and 48 h, with a prediction accuracy of 92.85%, 93.57%, and 90.71%, respectively. The experimental results indicated that the combination of THz imaging technology and chemometrics could be a new effective way to discriminate wheat grains at the early germination stage of approximately 6 h. PMID:26892180

  6. Application of chemometric methods to differential scanning calorimeter (DSC) to estimate nimodipine polymorphs from cosolvent system.

    PubMed

    Siddiqui, Akhtar; Rahman, Ziyaur; Khan, Mansoor A

    2015-06-01

    The focus of this study was to evaluate the applicability of chemometrics to differential scanning calorimetry data (DSC) to evaluate nimodipine polymorphs. Multivariate calibration models were built using DSC data from known mixtures of the nimodipine modification. The linear baseline correction treatment of data was used to reduce dispersion in thermograms. Principal component analysis of the treated and untreated data explained 96% and 89% of the data variability, respectively. Score and loading plots correlated variability between samples with change in proportion of nimodipine modifications. The R(2) for principal component regression (PCR) and partial lease square regression (PLS) were found to be 0.91 and 0.92. The root mean square of standard error of the treated samples for calibration and validation in PCR and PLS was found to be lower than the untreated sample. These models were applied to samples recrystallized from a cosolvent system, which indicated different proportion of modifications in the mixtures than those obtained by placing samples under different storage conditions. The model was able to predict the nimodipine modifications with known margin of error. Therefore, these models can be used as a quality control tool to expediently determine the nimodipine modification in an unknown mixture.

  7. 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.

  8. A study of adulteration in gasoline samples using flame emission spectroscopy and chemometrics tools.

    PubMed

    de Paulo, Jaqueline M; Mendes, Gisele; Barros, José E M; Barbeira, Paulo J S

    2012-12-21

    This work presents a low cost system based on Flame Emission Spectroscopy (FES) that enables the prediction of fuel adulteration. The spectral data acquired using FES were associated with chemometric tools--Partial Least Squares Discriminant Analysis (PLS-DA) and Partial Least Squares (PLS), aiming to predict gasoline adulterations with different solvents. The classification of the Brazilian adulterated gasoline samples with turpentine, thinner, kerosene, rubber solvent and ethanol was carried out through a PLS-DA model built using five latent variables (LV) with an accumulated variance of 100% on X and 76.78% on Y. The combination of these techniques provided the discrimination of distinct groups for each one of the studied adulterants. Subsequent to the classification, samples of adulterated gasoline with the same solvents with contents varying from 1 to 50% (v/v) were analyzed through FES and multivariate calibration curves were employed in order to predict the contents of the respective solvents. The results obtained by the combination of FES and PLS provided the determination of gasoline adulterants with small calibration and validation errors and also lower values than the ones reported in the literature using other spectroscopic techniques.

  9. HRMAS NMR spectroscopy combined with chemometrics as an alternative analytical tool to control cigarette authenticity.

    PubMed

    Shintu, Laetitia; Caldarelli, Stefano; Campredon, Mylène

    2013-11-01

    In this paper, we present for the first time the use of high-resolution magic angle spinning nuclear magnetic resonance (HRMAS NMR) spectroscopy combined with chemometrics as an alternative tool for the characterization of tobacco products from different commercial international brands as well as for the identification of counterfeits. Although cigarette filling is a very complex chemical mixture, we were able to discriminate between dark, bright, and additive-free cigarette blends belonging to six different filter-cigarette brands, commercially available, using an approach for which no extraction procedure is required. Second, we focused our study on a specific worldwide-distributed brand for which established counterfeits were available. We discriminated those from their genuine counterparts with 100% accuracy using unsupervised multivariate statistical analysis. The counterfeits that we analyzed showed a higher amount of nicotine and solanesol and a lower content of sugars, all endogenous tobacco leaf metabolites. This preliminary study demonstrates the great potential of HRMAS NMR spectroscopy to help in controlling cigarette authenticity.

  10. Quantification of pH-dependent speciation of organic compounds with spectroscopy and chemometrics.

    PubMed

    Ritschel, Thomas; Totsche, Kai Uwe

    2017-04-01

    Fluorescence and UV/Vis spectra of aqueous solutions with numerous organic compounds are a superposition of single spectra of the chemical species present. Thus, an isolation of individual spectra with chemometrics is required for their quantification. We investigated UV/Vis spectra and fluorescence excitation-emission matrices of vanillic acid, salicylic acid, phenoxyacetic acid and phthalic acid with positive matrix factorization (PMF) and non-negativity constrained parallel factor analysis (PARAFAC) in combination with the law of mass action. In consideration of the pH-dependent speciation of organic acids, we first reconstructed the pH-specific spectra of each compound. Using these spectra as known components in a constrained algorithm, we could successfully quantify species of multiple compounds and reconstruct the solution pH. In addition, we estimated the uncertainty of reconstructed spectra and concentrations in order to assess the most probable number of components for PMF/PARAFAC. Therefore, we could derive a framework to reconstruct the number of relevant species and their individual concentration present in spectroscopic data of aqueous solutions containing multiple organic compounds.

  11. Early detection of germinated wheat grains using terahertz image and chemometrics

    NASA Astrophysics Data System (ADS)

    Jiang, Yuying; Ge, Hongyi; Lian, Feiyu; Zhang, Yuan; Xia, Shanhong

    2016-02-01

    In this paper, we propose a feasible tool that uses a terahertz (THz) imaging system for identifying wheat grains at different stages of germination. The THz spectra of the main changed components of wheat grains, maltose and starch, which were obtained by THz time spectroscopy, were distinctly different. Used for original data compression and feature extraction, principal component analysis (PCA) revealed the changes that occurred in the inner chemical structure during germination. Two thresholds, one indicating the start of the release of α-amylase and the second when it reaches the steady state, were obtained through the first five score images. Thus, the first five PCs were input for the partial least-squares regression (PLSR), least-squares support vector machine (LS-SVM), and back-propagation neural network (BPNN) models, which were used to classify seven different germination times between 0 and 48 h, with a prediction accuracy of 92.85%, 93.57%, and 90.71%, respectively. The experimental results indicated that the combination of THz imaging technology and chemometrics could be a new effective way to discriminate wheat grains at the early germination stage of approximately 6 h.

  12. Optimization of preparation of chitosan-coated iron oxide nanoparticles for biomedical applications by chemometrics approaches

    NASA Astrophysics Data System (ADS)

    Honary, Soheila; Ebrahimi, Pouneh; Rad, Hossein Asgari; Asgari, Mahsa

    2013-08-01

    Functionalized magnetic nanoparticles are used in several biomedical applications, such as drug delivery, magnetic cell separation, and magnetic resonance imaging. Size and surface properties of iron oxide nanoparticles are the two important factors which could dramatically affect the nanoparticle efficiency as well as their stability. In this study, the chemometrics approach was applied to optimize the coating process of iron oxide nanoparticles. To optimize the size of nanoparticles, the effect of two experimental parameters on size was investigated by means of multivariate analysis. The factors considered were chitosan molecular weight and chitosan-to-tripolyphosphate concentration ratio. The experiments were performed according to face-centered cube central composite response surface design. A second-order regression model was obtained which characterized by both descriptive and predictive abilities. The method was optimized with respect to the percent of Z average diameter's increasing after coating as response. It can be concluded that experimental design provides a suitable means of optimizing and testing the robustness of iron oxide nanoparticle coating method.

  13. Prediction of peroxide value in omega-3 rich microalgae oil by ATR-FTIR spectroscopy combined with chemometrics.

    PubMed

    Cebi, Nur; Yilmaz, Mustafa Tahsin; Sagdic, Osman; Yuce, Hande; Yelboga, Emrah

    2017-06-15

    Our work explored, for the first time, monitoring peroxide value (PV) of omega-3 rich algae oil using ATR-FTIR spectroscopic technique. The PV of the developed method was compared by that obtained by standard method of Association of Official Analytical Chemists (AOAC). In this study, peak area integration (PAI), Partial Least Squares Regression (PLSR), and Principal Component Regression (PCR) were used as the calibration techniques. PV obtained by the AOAC method and by FTIR-ATR technique were well correlated considering the peak area related to trans double bonds and chemometrics techniques of PLSR and PCR. Calibration model was established using the band with a peak point at 966cm(-1) (990-940cm(-1)) related to CH out of plane deformation vibration of trans double bond. Algae oil oxidation could be successfully quantified using PAI, PLSR and PCR techniques. Additionally, hierarchical cluster analysis was performed and significant discrimination was observed coherently with oxidation process.

  14. Combination of 1H NMR and chemometrics to discriminate manuka honey from other floral honey types from Oceania.

    PubMed

    Spiteri, Marc; Rogers, Karyne M; Jamin, Eric; Thomas, Freddy; Guyader, Sophie; Lees, Michèle; Rutledge, Douglas N

    2017-02-15

    Manuka honey is a product produced essentially in New Zealand, and has been widely recognised for its antibacterial properties and specific taste. In this study, 264 honeys from New Zealand and Australia were analysed using proton NMR spectroscopy coupled with chemometrics. Known manuka markers, methylglyoxal and dihydroxyacetone, have been characterised and quantified, together with a new NMR marker, identified as being leptosperin. Manuka honey profiling using 1H NMR is shown to be a possible alternative to chromatography with the added advantage that it can measure methylglyoxal (MGO), dihydroxyacetone (DHA) and leptosperin simultaneously. By combining the information from these three markers, we established a model to estimate the proportion of manuka in a given honey. Markers of other botanical origins were also identified, which makes 1H NMR a convenient and efficient tool, complementary to pollen analysis, to control the botanical origin of Oceania honeys.

  15. Application of mid-infrared chemical imaging and multivariate chemometrics analyses to characterise a population of microalgae cells.

    PubMed

    Tan, Suat-Teng; Balasubramanian, Rajesh Kumar; Das, Probir; Obbard, Jeffrey Philip; Chew, Wee

    2013-04-01

    A suite of multivariate chemometrics methods was applied to a mid-infrared imaging dataset of a eustigmatophyte, marine Nannochloropsis sp. microalgae strain. This includes the improved leader-follower cluster analysis (iLFCA) to interrogate spectra in an unsupervised fashion, a resonant Mie optical scatter correction algorithm (RMieS-EMSC) that improves data linearity, the band-target entropy minimization (BTEM) self-modeling curve resolution for recovering component spectra, and a multi-linear regression (MLR) for estimating relative concentrations and plotting chemical maps of component spectra. A novel Alpha-Stable probability calculation for microalgae cellular lipid-to-protein ratio Λi is introduced for estimating population characteristics.

  16. Chemometric study on the electrochemical incineration of nitrilotriacetic acid using platinum and boron-doped diamond anode.

    PubMed

    Zhang, Chunyong; He, Zhenzhu; Wu, Jingyu; Fu, Degang

    2015-07-01

    This study investigated the electrochemical incineration of nitrilotriacetic acid (NTA) at boron-doped diamond (BDD) and platinum (Pt) anodes. Trials were performed in the presence of sulfate electrolyte media under recirculation mode. The parameters that influence the degradation efficiency were investigated, including applied current density, flow rate, supporting electrolyte concentration and reaction time. To reduce the number of experiments, the system had been managed under chemometric technique named Doehlert matrix. As a consequence, the mineralization of NTA demonstrated similar behavior upon operating parameters on these two anodes. Further kinetic study indicated that the degradations followed pseudo-first-order reactions for both BDD and Pt anodes, and the reaction rate constant of the former was found to be higher than that of the latter. Such difference could be interpreted by results from fractal analysis. In addition, a reaction sequence for NTA mineralization considering all the detected intermediates was also proposed.

  17. 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.

  18. 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.

  19. Chemometric optimization of a low-temperature plasma source design for ambient desorption/ionization mass spectrometry

    NASA Astrophysics Data System (ADS)

    Albert, Anastasia; Engelhard, Carsten

    2015-03-01

    Low-temperature plasmas (LTPs) are attractive sources for atomic and molecular mass spectrometry (MS). In the past, the LTP probe, which was first described by Harper et al., was used successfully for direct molecular mass spectrometric analysis with minimal sample pretreatment in a variety of applications. Unfortunately, the desorption/ionization source itself is commercially not available and custom-built LTP set-ups with varying geometry and operational configurations were utilized in the past. In the present study, a rapid chemometrics approach based on systematic experiments and multivariate data analysis was used to optimize the LTP probe geometry and positioning relative to the atmospheric-pressure inlet of a mass spectrometer. Several parameters were studied including the probe geometry, electrode configuration, quartz tube dimensions, probe positioning and operating conditions. It was found that the plasma-to-MS-inlet distance, the plasma-to-sample-plate distance, and the angle between the latter are very important. Additional effects on the analytical performance were found for the outer electrode width, the positioning of the electrodes, the inner diameter of the quartz tube, the quartz wall thickness, and the gas flow. All experiments were performed using additional heating of the sample to enhance thermal desorption and maximize the signal (T = 150 °C). After software-assisted optimization, attractive detection limits were achieved (e.g., 1.8 × 10- 7 mol/L for 4-acetamidothiophenol). Moreover, relative standard deviation (RSD) improved from values of up to 30% before optimization to < 15% RSD after the procedure was completed. This chemometrics approach for method optimization is not limited to LTP-MS and considered to be attractive for other plasma-based instrumentation as well.

  20. Chemometrics applications in biotech processes: assessing process comparability.

    PubMed

    Bhushan, Nitish; Hadpe, Sandip; Rathore, Anurag S

    2012-01-01

    A typical biotech process starts with the vial of the cell bank, ends with the final product and has anywhere from 15 to 30 unit operations in series. The total number of process variables (input and output parameters) and other variables (raw materials) can add up to several hundred variables. As the manufacturing process is widely accepted to have significant impact on the quality of the product, the regulatory agencies require an assessment of process comparability across different phases of manufacturing (Phase I vs. Phase II vs. Phase III vs. Commercial) as well as other key activities during product commercialization (process scale-up, technology transfer, and process improvement). However, assessing comparability for a process with such a large number of variables is nontrivial and often companies resort to qualitative comparisons. In this article, we present a quantitative approach for assessing process comparability via use of chemometrics. To our knowledge this is the first time that such an approach has been published for biotech processing. The approach has been applied to an industrial case study involving evaluation of two processes that are being used for commercial manufacturing of a major biosimilar product. It has been demonstrated that the proposed approach is able to successfully identify the unit operations in the two processes that are operating differently. We expect this approach, which can also be applied toward assessing product comparability, to be of great use to both the regulators and the industry which otherwise struggle to assess comparability.

  1. Design of natural food antioxidant ingredients through a chemometric approach.

    PubMed

    Mendiola, Jose A; Martín-Alvarez, Pedro J; Señoráns, F Javier; Reglero, Guillermo; Capodicasa, Alessandro; Nazzaro, Filomena; Sada, Alfonso; Cifuentes, Alejandro; Ibáñez, Elena

    2010-01-27

    In the present work, an environmentally friendly extraction process using subcritical conditions has been tested to obtain potential natural food ingredients from natural sources such as plants, fruits, spirulina, propolis, and tuber, with the scope of substituting synthetic antioxidants, which are subject to regulation restrictions and might be harmful for human health. A full characterization has been undertaken from the chemical and biochemical point of view to be able to understand their mechanism of action. Thus, an analytical method for profiling the compounds responsible for the antioxidant activity has been used, allowing the simultaneous determination of water-soluble vitamins, fat-soluble vitamins, phenolic compounds, carotenoids, and chlorophylls in a single run. This information has been integrated and analyzed using a chemometrical approach to correlate the bioactive compounds profile with the antioxidant activity and thus to be able to predict antioxidant activities of complex formulations. As a further step, a simplex centroid mixture design has been tested to find the optimal formulation and to calculate the effect of the interaction among individual extracts in the mixture.

  2. Infrared spectroscopic and chemometric approach for identifying binding medium in Sukias mansion's wall paintings.

    PubMed

    Haghighi, Zahra; Karimy, Amir-Hossein; Karami, Farshad; Bagheri Garmarudi, Amir; Khanmohammadi, Mohammadreza

    2015-11-11

    This paper addresses the application of infrared spectroscopy in combination with chemometrics to identify wall painting's binding medium while employing pattern recognition techniques to process FTIR data-set of complex samples. In this regard, based on the historical documents and previous researches, firstly 56 standard samples were prepared to represent strata of Persian wall paintings in the Safavid period in addition to real historic samples from the case study; Sukias mansion. Then, each sample was analysed by the means of FTIR and chemometrics. Finally, SIMCA was applied to the whole region of studied IR spectra which predicted egg yolk as the binding medium of Sukias mansion samples.

  3. Chemometric classification of morphologically similar Umbelliferae medicinal herbs by DART-TOF-MS fingerprint.

    PubMed

    Lee, Sang Min; Kim, Hye-Jin; Jang, Young Pyo

    2012-01-01

    It needs many years of special training to gain expertise on the organoleptic classification of botanical raw materials and, even for those experts, discrimination among Umbelliferae medicinal herbs remains an intricate challenge due to their morphological similarity. To develop a new chemometric classification method using a direct analysis in real time-time of flight-mass spectrometry (DART-TOF-MS) fingerprinting for Umbelliferae medicinal herbs and to provide a platform for its application to the discrimination of other herbal medicines. Angelica tenuissima, Angelica gigas, Angelica dahurica and Cnidium officinale were chosen for this study and ten samples of each species were purchased from various Korean markets. DART-TOF-MS was employed on powdered raw materials to obtain a chemical fingerprint of each sample and the orthogonal partial-least squares method in discriminant analysis (OPLS-DA) was used for multivariate analysis. All samples of collected species were successfully discriminated from each other according to their characteristic DART-TOF-MS fingerprint. Decursin (or decursinol angelate) and byakangelicol were identified as marker molecules for Angelica gigas and A. dahurica, respectively. Using the OPLS method for discriminant analysis, Angelica tenuissima and Cnidium officinale were clearly separated into two groups. Angelica tenuissima was characterised by the presence of ligustilide and unidentified molecular ions of m/z 239 and 283, while senkyunolide A together with signals with m/z 387 and 389 were the marker compounds for Cnidium officinale. Elaborating with chemoinformatics, DART-TOF-MS fingerprinting with chemoinformatic tools results in a powerful method for the classification of morphologically similar Umbelliferae medicinal herbs and quality control of medicinal herbal products, including the extracts of these crude drugs. Copyright © 2012 John Wiley & Sons, Ltd.

  4. Simple and rapid simultaneous profiling of minor components of honey by size exclusion chromatography (SEC) coupled to ultraviolet diode array detection (UV-DAD), combined with chemometric methods.

    PubMed

    Beretta, Giangiacomo; Fermo, Paola; Maffei Facino, Roberto

    2012-01-25

    This paper discusses the importance of profiling UV-responsive components, properly integrated with chemometric techniques, in detecting indicative parameters for quality control of honey. The minor components in honeys of different botanical and geographical origins were investigated by size SEC-UV-DAD. We diluted honey with mobile phase before injection into the chromatographic apparatus and a single chromatographic run gave a fast profile of high- (proteins and enzymes), intermediate- (e.g. terpenoid glycosides in lime tree honey) and low-molecular-weight components (secondary metabolites, e.g. kynurenic acid in chestnut honey). The analysis of a total number of 32 honey samples from different regions (Italy, Western Balkan countries, Brazil, Cameroon, Kenya) and of different botanical origins (herbal flower and arboreal flower nectars/honeydews) showed peculiar and characteristic distribution of these markers, which were basically related to their floral origin. Chemometric examination carried out using principal component analysis (PCA) and hierarchical cluster analysis (HCA) of the chromatograms (RT vs. absorption) detected four main clusters in which the groups of (i) chestnut honeys, (ii) honeys from rain forests and (iii) counterfeit/adulterated honeys were clearly separated from the main group of flower nectar honeys. The method is fast, requiring minimal sample handling, and the chromatographic data can be analyzed by multivariate statistical techniques to obtain descriptive information about the honey's quality and composition.

  5. Holistic Evaluation of Quality Consistency of Ixeris sonchifolia (Bunge) Hance Injectables by Quantitative Fingerprinting in Combination with Antioxidant Activity and Chemometric Methods

    PubMed Central

    Yang, Lanping; Sun, Guoxiang; Guo, Yong; Hou, Zhifei; Chen, Shuai

    2016-01-01

    A widely used herbal medicine, Ixeris sonchifolia (Bge.) Hance Injectable (ISHI) was investigated for quality consistency. Characteristic fingerprints of 23 batches of the ISHI samples were generated at five wavelengths and evaluated by the systematic quantitative fingerprint method (SQFM) as well as simultaneous analysis of the content of seven marker compounds. Chemometric methods, i.e., support vector machine (SVM) and principal component analysis (PCA) were performed to assist in fingerprint evaluation of the ISHI samples. Qualitative classification of the ISHI samples by SVM was consistent with PCA, and in agreement with the quantitative evaluation by SQFM. In addition, the antioxidant activities of the ISHI samples were determined by both the off-line and on-line DPPH (2, 2-diphenyl-1-picryldrazyl) radical scavenging assays. A fingerprint–efficacy relationship linking the chemical components and in vitro antioxidant activity was established and validated using the partial least squares (PLS) and orthogonal projection to latent structures (OPLS) models; and the online DPPH assay further revealed those components that had position contribution to the total antioxidant activity. Therefore, the combined use of the chemometric methods, quantitative fingerprint evaluation by SQFM, and multiple marker compound analysis in conjunction with the assay of antioxidant activity provides a powerful and holistic approach to evaluate quality consistency of herbal medicines and their preparations. PMID:26872364

  6. Characteristic Fingerprint Based on Low Polar Constituents for Discrimination of Wolfiporia extensa according to Geographical Origin Using UV Spectroscopy and Chemometrics Methods

    PubMed Central

    Li, Yan; Zhao, Yanli; Li, Zhimin; Li, Tao

    2014-01-01

    The fungus species Wolfiporia extensa has a long history of medicinal usage and has also been commercially used to formulate nutraceuticals and functional foods in certain Asian countries. In the present study, a practical and promising method has been developed to discriminate the dried sclerotium of W. extensa collected from different geographical sites based on UV spectroscopy together with chemometrics methods. Characteristic fingerprint of low polar constituents of sample extracts that originated from chloroform has been obtained in the interval 250–400 nm. Chemometric pattern recognition methods such as partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) were applied to enhance the authenticity of discrimination of the specimens. The results showed that W. extensa samples were well classified according to their geographical origins. The proposed method can fully utilize diversified fingerprint characteristics of sclerotium of W. extensa and requires low-cost equipment and short-time analysis in comparison with other techniques. Meanwhile, this simple and efficient method may serve as a basis for the authentication of other medicinal fungi. PMID:25544933

  7. Characteristic Fingerprint Based on Low Polar Constituents for Discrimination of Wolfiporia extensa according to Geographical Origin Using UV Spectroscopy and Chemometrics Methods.

    PubMed

    Li, Yan; Zhang, Ji; Zhao, Yanli; Li, Zhimin; Li, Tao; Wang, Yuanzhong

    2014-01-01

    The fungus species Wolfiporia extensa has a long history of medicinal usage and has also been commercially used to formulate nutraceuticals and functional foods in certain Asian countries. In the present study, a practical and promising method has been developed to discriminate the dried sclerotium of W. extensa collected from different geographical sites based on UV spectroscopy together with chemometrics methods. Characteristic fingerprint of low polar constituents of sample extracts that originated from chloroform has been obtained in the interval 250-400 nm. Chemometric pattern recognition methods such as partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) were applied to enhance the authenticity of discrimination of the specimens. The results showed that W. extensa samples were well classified according to their geographical origins. The proposed method can fully utilize diversified fingerprint characteristics of sclerotium of W. extensa and requires low-cost equipment and short-time analysis in comparison with other techniques. Meanwhile, this simple and efficient method may serve as a basis for the authentication of other medicinal fungi.

  8. 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.

  9. Cholorpheniramine tannate complexes: physicochemical, chemometric, and taste masking evaluation.

    PubMed

    Rahman, Ziyaur; Zidan, Ahmed S; Khan, Saeed R; Reddy, Indra K; Khan, Mansoor A

    2012-10-15

    The focus of present investigation was to evaluate the tannic acid (TA) complexes of cholorpheniramine maleate (CPM) and characterize it by a variety of physicochemical, dissolution, and electronic tongue methods. The complexes were prepared in various molar ratios by solvent evaporation method. They were characterized by spectroscopic, thermal, powder X-ray, electronic tongue, solubility and dissolution methods. FTIR (infrared red) spectra showed complex formation between the TA and CPM. Complex formation has significantly lowered the drug solubility and sustained its release for more than 24 h in phosphate buffer pH 6.8. On the contrary, the release was much faster in the presence of Avicel PH 113 in the same molar ratio complex. The complex formulation has suppressed the bitter taste of CPM as indicated by Euclidean distance in electronic tongue evaluation. NIR-CI (near infrared chemical imaging) showed lower skew value that indicated the homogenous distribution of formulation components. The chemometric models were also developed using the NIR data. The model based on second derivative data was better in predicting the TA and CPM loading as indicated by higher values of R, R(2) and lower values of root mean square error and standard errors. Furthermore, it has a better accuracy and less biased in comparison to other models. In conclusion, the CPM tannate has a sustained release behavior and excipients play a major role in modifying its release. Additionally, the complexes with varying molar ratio of tannate to CPM have differential taste masking abilities than that of the pure drug. Published by Elsevier B.V.

  10. [Identifying the origin of chromophoric dissolved organic matter in Xiamen Bay using fluorescence spectroscopy and chemometrics].

    PubMed

    Lin, Hui; Guo, Wei-Dong; Xu, Jing; Hu, Ming-Hui

    2013-02-01

    The fluorescent components of chromophoric dissolved matter (CDOM) in water samples collected from Xiamen Bay in spring and autumn, 2009 were examined using excitation-emission matrix fluorescence spectroscopy combined with parallel factor analysis (EEMs-PARAFAC). PARAFAC decomposed the fluorescence matrices of CDOM into three humic-like (C1: 250, 345/454 nm; C2: 230, 310/374 nm; C5: 265, 424/478 nm) and two protein-like (C3: 230/342 nm; C4: 230, 275/322 nm) components. Good linear correlation occurred among three humic-like components and between two protein-like components, respectively. This demonstrated that the same types of components (humic-like or protein-like) have similar origin and geochemical behaviors. High abundances of humic-like components were found at the upstream zone of the Jiulong Estuary, while the high abundance of protein-like components occurred at the northern part of semi-enclosed Western Xiamen Harbor. The significant negative correlations were found between the abundances of all fluorescence components and salinity in the estuary area. However, the high contents of chlorophyll a were in line with the high abundances of C3 and C4 in non-estuarine area, which implies that phytoplankton activity could be another important source of protein-like components besides the river runoff. A principal component analysis(PCA) of fluorescent components revealed that terrestrial runoff was the dominant sources of CDOM fluorescence components in Xiamen Bay, while the contribution of the in situ biological processes was relatively lower. This study demonstrates that the combination use of PARAFAC modeling and chemometrics (i. e. PCA) is very useful in identifying the origin of CDOM and quantifying the primary factors influencing their distributions.

  11. Chemometrics quality assessment of wastewater treatment plant effluents using physicochemical parameters and UV absorption measurements.

    PubMed

    Platikanov, S; Rodriguez-Mozaz, S; Huerta, B; Barceló, D; Cros, J; Batle, M; Poch, G; Tauler, R

    2014-07-01

    Chemometric techniques like Principal Component Analysis (PCA) and Partial Least Squares Regression (PLS) are used to explore, analyze and model relationships among different water quality parameters in wastewater treatment plants (WWTP). Different data sets generated by laboratory analysis and by an automatic multi-parametric monitoring system with a new designed optical device have been investigated for temporal variations on water quality parameters measured in the water influent and effluent of a WWTP over different time scales. The obtained results allowed the discovery of the more important relationships among the monitored parameters and of their cyclic dependence on time (daily, monthly and annual cycles) and on different plant management procedures. This study intended also the modeling and prediction of concentrations of several water components and parameters, especially relevant for water quality assessment, such as Dissolved Organic Matter (DOM), Total Organic Carbon (TOC) nitrate, detergent, and phenol concentrations. PLS models were built to correlate target concentrations of these constituents with UV spectra measured in samples collected at (1) laboratory conditions (in synthetic water mixtures); and at (2) WWTP conditions (in real water samples from the plant). Using synthetic water mixtures, specific wavelengths were selected with the aim to establish simple and reliable prediction models, which gave good relative predictions with errors of around 3-4% for nitrates, detergent and phenols concentrations and of around 15% for the DOM in external validation. In the case of nitrate and TOC concentrations modeling in real water samples from the effluent of the WWTP using the reduced spectral data set, results were also promising with low prediction errors (less than 20%).

  12. Chemometric approach for development, optimization, and validation of different chromatographic methods for separation of opium alkaloids.

    PubMed

    Acevska, J; Stefkov, G; Petkovska, R; Kulevanova, S; Dimitrovska, A

    2012-05-01

    The excessive and continuously growing interest in the simultaneous determination of poppy alkaloids imposes the development and optimization of convenient high-throughput methods for the assessment of the qualitative and quantitative profile of alkaloids in poppy straw. Systematic optimization of two chromatographic methods (gas chromatography (GC)/flame ionization detector (FID)/mass spectrometry (MS) and reversed-phase (RP)-high-performance liquid chromatography (HPLC)/diode array detector (DAD)) for the separation of alkaloids from Papaver somniferum L. (Papaveraceae) was carried out. The effects of various conditions on the predefined chromatographic descriptors were investigated using chemometrics. A full factorial linear design of experiments for determining the relationship between chromatographic conditions and the retention behavior of the analytes was used. Central composite circumscribed design was utilized for the final method optimization. By conducting the optimization of the methods in very rational manner, a great deal of excessive and unproductive laboratory research work was avoided. The developed chromatographic methods were validated and compared in line with the resolving power, sensitivity, accuracy, speed, cost, ecological aspects, and compatibility with the poppy straw extraction procedure. The separation of the opium alkaloids using the GC/FID/MS method was achieved within 10 min, avoiding any derivatization step. This method has a stronger resolving power, shorter analysis time, better cost/effectiveness factor than the RP-HPLC/DAD method and is in line with the "green trend" of the analysis. The RP-HPLC/DAD method on the other hand displayed better sensitivity for all tested alkaloids. The proposed methods provide both fast screening and an accurate content assessment of the six alkaloids in the poppy samples obtained from the selection program of Papaver strains.

  13. 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),…

  14. 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…

  15. 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),…

  16. Chemometric modelling based on 2D-fluorescence spectra without a calibration measurement.

    PubMed

    Solle, D; Geissler, D; Stärk, E; Scheper, T; Hitzmann, B

    2003-01-22

    2D fluorescence spectra provide information from intracellular compounds. Fluorophores like trytophan, tyrosine and phenylalanin as well as NADH and flavins make the corresponding measurement systems very important for bioprocess supervision and control. The evaluation is usually based on chemometric modelling using for their calibration procedure off-line measurements of the desired process variables. Due to the data driven approach lots of off-line measurements are required. Here a methodology is presented, which enables to perform a calibration procedure of chemometric models without any further measurement. The necessary information for the calibration procedure is provided by means of the a priori knowledge about the process, i.e. a mathematical model, whose model parameters are estimated during the calibration procedure, as well as the fact that the substrate should be consumed at the end of the process run. The new methodology for chemometric calibration is applied for a batch cultivation of aerobically grown S. cerevisiae on the glucose Schatzmann medium. As will be presented the chemometric models, which are determined by this method, can be used for prediction during new process runs. The MATHLAB routine is free available on request from the authors.

  17. 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…

  18. 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.

  19. 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.

  20. Signature-discovery approach for sample matching of a nerve-agent precursor using liquid chromatography-mass spectrometry, XCMS, and chemometrics.

    PubMed

    Fraga, Carlos G; Clowers, Brian H; Moore, Ronald J; Zink, Erika M

    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 trace forensic signatures for sample matching of ten stocks of the nerve-agent precursor known as methylphosphonic dichloride (dichlor). XCMS, a software tool primarily used in bioinformatics, 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. 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 seven dichlor samples were all correctly matched to their source stock. The sample preparation and LC-MS method permitted the detection of dichlor impurities quantitatively estimated to be 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 assist investigations following chemical attacks.

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

    SciTech Connect

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

    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. 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.

  2. 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.

  3. Spectroscopic on-line monitoring of reactions in dispersed medium: chemometric challenges.

    PubMed

    Reis, Marlon M; Araújo, Pedro H H; Sayer, Claudia; Giudici, Reinaldo

    2007-07-09

    Emulsion and suspension polymerizations are important industrial processes for polymer production. The end-user properties of polymers depend strongly on how the polymerization reactions proceed in time (i.e. a batch or semicontinuous, rate of reagents feeding, etc.). In other words, these reactions are process dependent, which makes the successful process control a key point to ensure high-quality products. In several process control strategies the on-line monitoring of reaction performance is required. Due to the multiphase nature of the emulsion and suspension processes, there is a lack of sensors to perform successful on-line monitoring. Near infrared and Raman spectroscopies have been pointed out as useful approaches for monitoring emulsion and suspension polymerizations and several applications have been described. In such instance, the chemometric approach on relating near infrared and Raman spectra to polymer properties is widely used and has proven to be useful. Nevertheless, the multiphase nature of emulsion and suspension polymerizations also represents a challenge for the chemometric approach based on multivariate calibration models and demands the development of new methods. In this work, a set novel results is presented from the monitoring of 15 batch emulsion reactions that show the chemometric challenge to be faced on development of new methods for successful monitoring of processes taken under dispersed medium. In order to discuss these results, several chemometric approaches were revised. It is shown that Raman and NIR spectroscopic techniques are suitable for on-line monitoring of monomer concentration and polymer content during the polymerizations, as well as medium heterogeneity properties, i.e. average particle size. It is also shown that Hotteling and Q statistics, widely used in chemometrics, might fail in monitoring these reactions, while an approach based on principal curves is able to overcome such restriction.

  4. Interaction between 8-methoxypsoralen and trypsin: Monitoring by spectroscopic, chemometrics and molecular docking approaches

    NASA Astrophysics Data System (ADS)

    Liu, Yingying; Zhang, Guowen; Zeng, Ni; Hu, Song

    2017-02-01

    8-Methoxypsoralen (8-MOP) is a naturally occurring furanocoumarin with various biological activities. However, there is little information on the binding mechanism of 8-MOP with trypsin. Here, the interaction between 8-MOP and trypsin in vitro was determined by multi-spectroscopic methods combined with the multivariate curve resolution-alternating least squares (MCR-ALS) chemometrics approach. An expanded UV-vis spectral data matrix was analysed by MCR-ALS, the concentration profiles and pure spectra for the three reaction species (trypsin, 8-MOP and 8-MOP-trypsin) were obtained to monitor the interaction between 8-MOP and trypsin. The fluorescence data suggested that a static type of quenching mechanism occurred in the binding of 8-MOP to trypsin. Hydrophobic interaction dominated the formation of the 8-MOP-trypsin complex on account of the positive enthalpy and entropy changes, and trypsin had one high affinity binding site for 8-MOP with a binding constant of 3.81 × 104 L mol- 1 at 298 K. Analysis of three dimensional fluorescence, UV-vis absorption and circular dichroism spectra indicated that the addition of 8-MOP induced the rearrangement of the polypeptides carbonyl hydrogen-bonding network and the conformational changes in trypsin. The molecular docking predicted that 8-MOP interacted with the catalytic residues His57, Asp102 and Ser195 in trypsin. The binding patterns and trypsin conformational changes may result in the inhibition of trypsin activity. This study has provided insights into the binding mechanism of 8-MOP with trypsin.

  5. Investigation of Drug–Polymer Compatibility Using Chemometric-Assisted UV-Spectrophotometry

    PubMed Central

    Mohamed, Amir Ibrahim; Abd-Motagaly, Amr Mohamed Elsayed; Ahmed, Osama A. A.; Amin, Suzan; Mohamed Ali, Alaa Ibrahim

    2017-01-01

    A simple chemometric-assisted UV-spectrophotometric method was used to study the compatibility of clindamycin hydrochloride (HC1) with two commonly used natural controlled-release polymers, alginate (Ag) and chitosan (Ch). Standard mixtures containing 1:1, 1:2, and 1:0.5 w/w drug–polymer ratios were prepared and UV scanned. A calibration model was developed with partial least square (PLS) regression analysis for each polymer separately. Then, test mixtures containing 1:1 w/w drug–polymer ratios with different sets of drug concentrations were prepared. These were UV scanned initially and after three and seven days of storage at 25 °C. Using the calibration model, the drug recovery percent was estimated and a decrease in concentration of 10% or more from initial concentration was considered to indicate instability. PLS models with PC3 (for Ag) and PC2 (for Ch) showed a good correlation between actual and found values with root mean square error of cross validation (RMSECV) of 0.00284 and 0.01228, and calibration coefficient (R2) values of 0.996 and 0.942, respectively. The average drug recovery percent after three and seven days was 98.1 ± 2.9 and 95.4 ± 4.0 (for Ag), and 97.3 ± 2.1 and 91.4 ± 3.8 (for Ch), which suggests more drug compatibility with an Ag than a Ch polymer. Conventional techniques including DSC, XRD, FTIR, and in vitro minimum inhibitory concentration (MIC) for (1:1) drug–polymer mixtures were also performed to confirm clindamycin compatibility with Ag and Ch polymers. PMID:28275214

  6. Characterizing the pollution produced by an industrial area: chemometric methods applied to the Lagoon of Venice.

    PubMed

    Carrer, Sebastiano; Leardi, Riccardo

    2006-10-15

    The industrial area of Porto Marghera discharges every year about 1.85 10(9) m(3) of waste waters in the Lagoon of Venice through its 142 discharge points, 17 of them being constantly active. The Anti-Pollution Department of Magistrato alle Acque, the Venice Water Authority, has been controlling these discharges for many years. The huge database built up during the last years could help the authorities in making choices regarding the water quality of the Venetian environment. The application of chemometric methods to the dataset obtained from chemical analyses of industrial waste water samples (almost 250, for each of them up to 57 chemical variables having been measured) is useful to answer fundamental questions related to the pollution generated by the industrial area: i) which are the main differences among the individual discharge points? ii) is there a temporal trend in global and punctual pollution? iii) which is the discharge point having the strongest relative impact on the waters? The results of the present work allow to 1) identify two different groups of discharge points, discriminated by the level of contamination and by the presence of different contaminants; 2) detect a relevant temporal trend in one of the main outfalls (the industrial and civil waste treatment plant); 3) set up a multivariate strategy to "measure" the relative modification induced on receiving lagoon waters by a single discharge. The application of such a "3-STEP multivariate analysis" to the present and future data of water quality could represent a relevant tool for monitoring industrial activities, providing at the same time a support in management decision processes.

  7. Ghanaian cocoa bean fermentation characterized by spectroscopic and chromatographic methods and chemometrics.

    PubMed

    Aculey, Patrick C; Snitkjaer, Pia; Owusu, Margaret; Bassompiere, Marc; Takrama, Jemmy; Nørgaard, Lars; Petersen, Mikael A; Nielsen, Dennis S

    2010-08-01

    Export of cocoa beans is of great economic importance in Ghana and several other tropical countries. Raw cocoa has an astringent, unpleasant taste, and flavor, and has to be fermented, dried, and roasted to obtain the characteristic cocoa flavor and taste. In an attempt to obtain a deeper understanding of the changes in the cocoa beans during fermentation and investigate the possibility of future development of objective methods for assessing the degree of fermentation, a novel combination of methods including cut test, colorimetry, fluorescence spectroscopy, NIR spectroscopy, and GC-MS evaluated by chemometric methods was used to examine cocoa beans sampled at different durations of fermentation and samples representing fully fermented and dried beans from all cocoa growing regions of Ghana. Using colorimetry it was found that samples moved towards higher a* and b* values as fermentation progressed. Furthermore, the degree of fermentation could, in general, be well described by the spectroscopic methods used. In addition, it was possible to link analysis of volatile compounds with predictions of fermentation time. Fermented and dried cocoa beans from the Volta and the Western regions clustered separately in the score plots based on colorimetric, fluorescence, NIR, and GC-MS indicating regional differences in the composition of Ghanaian cocoa beans. The study demonstrates the potential of colorimetry and spectroscopic methods as valuable tools for determining the fermentation degree of cocoa beans. Using GC-MS it was possible to demonstrate the formation of several important aroma compounds such 2-phenylethyl acetate, propionic acid, and acetoin and the breakdown of others like diacetyl during fermentation. Practical Application: The present study demonstrates the potential of using colorimetry and spectroscopic methods as objective methods for determining cocoa bean quality along the processing chain. Development of objective methods for determining cocoa bean

  8. Relationships between volatile compounds and sensory characteristics in virgin olive oil by analytical and chemometric approaches.

    PubMed

    Procida, Giuseppe; Cichelli, Angelo; Lagazio, Corrado; Conte, Lanfranco S

    2016-01-15

    The volatile fraction of virgin olive oil is characterised by low molecular weight compounds that vaporise at room temperature. In order to obtain an aroma profile similar to natural olfactory perception, the composition of the volatile compounds was determined by applying dynamic headspace gas chromatography, performed at room temperature, with a cryogenic trap directly connected to a gas chromatograph-mass spectrometer system. Samples were also evaluated according to European Union and International Olive Council official methods for sensory evaluation. In this paper, the composition of the volatile fraction of 25 extra virgin olive oils from different regions of Italy was analysed and some preliminary considerations on relationships between chemical composition of volatile fraction and sensory characteristics are reported. Forty-two compounds were identified by means of the particular analytical technique used. All the analysed samples, classified as extra virgin by the panel test, never present peaks whose magnitude is important enough in defected oils. The study was focused on the evaluation of volatile compounds responsible for the positive impact on olive odour properties ('green-fruity' and 'sweet') and olfactory perception. Chemometric evaluation of data, obtained through headspace analysis and the panel test evaluation, showed a correlation between chemical compounds and sensory properties. On the basis of the results, the positive attributes of virgin olive oil are divided into two separated groups: sweet types or green types. Sixteen volatile compounds with known positive impact on odour properties were extracted and identified. In particular, eight compounds seem correlated with sweet properties whereas the green sensation appears to be correlated with eight other different substances. The content of the compounds at six carbon atoms proves to be very important in defining positive attributes of extra virgin olive oils and sensory evaluation. © 2015

  9. Simultaneous kinetic-spectrophotometric determination of maltol and ethyl maltol in food samples by using chemometrics.

    PubMed

    Ni, Yongnian; Wang, Yong; Kokot, Serge

    2008-07-15

    A fast and accurate procedure has been researched and developed for the simultaneous determination of maltol and ethyl maltol, based on their reaction with iron(III) in the presence of o-phenanthroline in sulfuric acid medium. This reaction was the basis for an indirect kinetic spectrophotometric method, which followed the development of the pink ferroin product (λmax=524nm). The kinetic data were collected in the 370-900nm range over 0-30s. The optimized method indicates that individual analytes followed Beer's law in the concentration range of 4.0-76.0mgL(-1) for both maltol and ethyl maltol. The LOD values of 1.6mgL(-1) for maltol and 1.4mgL(-1) for ethyl maltol agree well with those obtained by the alternative high performance liquid chromatography with ultraviolet detection (HPLC-UV). Three chemometrics methods, principal component regression (PCR), partial least squares (PLS) and principal component analysis-radial basis function-artificial neural networks (PC-RBF-ANN), were used to resolve the measured data with small kinetic differences between the two analytes as reflected by the development of the pink ferroin product. All three performed satisfactorily in the case of the synthetic verification samples, and in their application for the prediction of the analytes in several food products. The figures of merit for the analytes based on the multivariate models agreed well with those from the alternative HPLC-UV method involving the same samples.

  10. Chemometric evaluation of urinary steroid hormone levels as potential biomarkers of neuroendocrine tumors.

    PubMed

    Plenis, Alina; Miękus, Natalia; Olędzka, Ilona; Bączek, Tomasz; Lewczuk, Anna; Woźniak, Zofia; Koszałka, Patrycja; Seroczyńska, Barbara; Skokowski, Jarosław

    2013-10-16

    Neuroendocrine tumors (NETs) are uncommon tumors which can secrete specific hormone products such as peptides, biogenic amines and hormones. So far, the diagnosis of NETs has been difficult because most NET markers are not specific for a given tumor and none of the NET markers can be used to fulfil the criteria of high specificity and high sensitivity for the screening procedure. However, by combining the measurements of different NET markers, they become highly sensitive and specific diagnostic tests. The aim of the work was to identify whether urinary steroid hormones can be identified as potential new biomarkers of NETs, which could be used as prognostic and clinical course monitoring factors. Thus, a rapid and sensitive reversed-phase high-performance liquid chromatographic method (RP-HPLC) with UV detection has been developed for the determination of cortisol, cortisone, corticosterone, testosterone, epitestosterone and progesterone in human urine. The method has been validated for accuracy, precision, selectivity, linearity, recovery and stability. The limits of detection and quantification were 0.5 and 1 ng mL-1 for each steroid hormone, respectively. Linearity was confirmed within a range of 1-300 ng mL-1 with a correlation coefficient greater than 0.9995 for all analytes. The described method was successfully applied for the quantification of six endogenous steroid levels in human urine. Studies were performed on 20 healthy volunteers and 19 patients with NETs. Next, for better understanding of tumor biology in NETs and for checking whether steroid hormones can be used as potential biomarkers of NETs, a chemometric analysis of urinary steroid hormone levels in both data sets was performed.

  11. Robustness of chemometrics-based feature selection methods in early cancer detection and biomarker discovery.

    PubMed

    Lee, Hae Woo; Lawton, Carl; Na, Young Jeong; Yoon, Seongkyu

    2013-03-13

    In omics studies aimed at the early detection and diagnosis of cancer, bioinformatics tools play a significant role when analyzing high dimensional, complex datasets, as well as when identifying a small set of biomarkers. However, in many cases, there are ambiguities in the robustness and the consistency of the discovered biomarker sets, since the feature selection methods often lead to irreproducible results. To address this, both the stability and the classification power of several chemometrics-based feature selection algorithms were evaluated using the Monte Carlo sampling technique, aiming at finding the most suitable feature selection methods for early cancer detection and biomarker discovery. To this end, two data sets were analyzed, which comprised of MALDI-TOF-MS and LC/TOF-MS spectra measured on serum samples in order to diagnose ovarian cancer. Using these datasets, the stability and the classification power of multiple feature subsets found by different feature selection methods were quantified by varying either the number of selected features, or the number of samples in the training set, with special emphasis placed on the property of stability. The results show that high consistency does not necessarily guarantee high predictive power. In addition, differences in the stability, as well as agreement in feature lists between several feature selection methods, depend on several factors, such as the number of available samples, feature sizes, quality of the information in the dataset, etc. Among the tested methods, only the variable importance in projection (VIP)-based method shows complementary properties, providing both highly consistent and accurate subsets of features. In addition, successive projection analysis (SPA) was excellent with regards to maintaining high stability over a wide range of experimental conditions. The stability of several feature selection methods is highly variable, stressing the importance of making the proper choice among

  12. Investigating hydrochemistry of groundwater in Indo-Gangetic alluvial plain using multivariate chemometric approaches.

    PubMed

    Singh, Kunwar P; Gupta, Shikha; Rai, Premanjali

    2014-05-01

    Groundwater hydrochemistry of an urban industrial region in Indo-Gangetic plains of north India was investigated. Groundwater samples were collected both from the industrial and non-industrial areas of Kanpur. The hydrochemical data were analyzed using various water quality indices and nonparametric statistical methods. Principal components analysis (PCA) was performed to identify the factors responsible for groundwater contamination. Ensemble learning-based decision treeboost (DTB) models were constructed to develop discriminating and regression functions to differentiate the groundwater hydrochemistry of the three different areas, to identify the responsible factors, and to predict the groundwater quality using selected measured variables. The results indicated non-normal distribution and wide variability of water quality variables in all the study areas, suggesting for nonhomogenous distribution of sources in the region. PCA results showed contaminants of industrial origin dominating in the region. DBT classification model identified pH, redox potential, total-Cr, and λ 254 as the discriminating variables in water quality of the three areas with the average accuracy of 99.51 % in complete data. The regression model predicted the groundwater chemical oxygen demand values exhibiting high correlation with measured values (0.962 in training; 0.918 in test) and the respective low root mean-squared error of 2.24 and 2.01 in training and test arrays. The statistical and chemometric approaches used here suggest that groundwater hydrochemistry differs in the three areas and is dominated by different variables. The proposed methods can be used as effective tools in groundwater management.