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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. 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.

  3. Quantitative analysis of NMR spectra with chemometrics

    NASA Astrophysics Data System (ADS)

    Winning, H.; Larsen, F. H.; Bro, R.; Engelsen, S. B.

    2008-01-01

    The number of applications of chemometrics to series of NMR spectra is rapidly increasing due to an emerging interest for quantitative NMR spectroscopy e.g. in the pharmaceutical and food industries. This paper gives an analysis of advantages and limitations of applying the two most common chemometric procedures, Principal Component Analysis (PCA) and Multivariate Curve Resolution (MCR), to a designed set of 231 simple alcohol mixture (propanol, butanol and pentanol) 1H 400 MHz spectra. The study clearly demonstrates that the major advantage of chemometrics is the visualisation of larger data structures which adds a new exploratory dimension to NMR research. While robustness and powerful data visualisation and exploration are the main qualities of the PCA method, the study demonstrates that the bilinear MCR method is an even more powerful method for resolving pure component NMR spectra from mixtures when certain conditions are met.

  4. Chemometrics

    SciTech Connect

    Brown, S.D.; Bear, R.S. Jr.; Blank, T.B.

    1992-06-15

    Chemometrics is the discipline concerned with the application of statistical and mathematical methods, as well as those methods based on mathematical logic, to chemistry. This review, the ninth of the series, and the seventh with the title {open_quotes}Chemometrics{close_quotes}, covers the more significant developments in the field from December 1989 to November 1991. The format follows that of the previous review of this subject. 934 refs., 1 tab.

  5. 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. PMID:22816252

  6. 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

  7. 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

    2015-07-01

    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. PMID:25863337

  8. 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

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

    PubMed

    Wulandari, Lestyo; Retnaningtyas, Yuni; Nuri; Lukman, Hilmia

    2016-01-01

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

  10. 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.

  11. 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. PMID:25835028

  12. 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%). PMID:26920315

  13. Processing of chromatographic data for chemometric analysis of peptide profiles from cheese extracts: a novel approach.

    PubMed

    Piraino, Paolo; Parente, Eugenio; McSweeney, Paul L H

    2004-11-17

    Chemometric analysis of chromatograms plays a fundamental role in characterization of foods or in detection of adulteration. Data for multivariate analysis of chromatographic profiles are usually obtained by visual matching (VM) of peaks, the identities of which, as for peptide profiles from cheese extracts, are often unknown. To avoid the main disadvantages of VM, which is subjective and time-consuming, a novel approach was developed. Fuzzy logic was employed to handle in a systematic way uncertainty in the position of peptide peaks, and chromatograms were processed by a rule-based membership function. Processed data consisted of classes of retention time wherein peak heights were accumulated by using the distance from the center of the class as a weight. The novel approach (fuzzy approach, FA) was compared with VM by using a real data set and by performing multivariate descriptive statistical techniques (principal component analysis, multidimensional scaling, and nonhierarchical cluster analysis). FA provided a fast, reliable, and objective alternative to VM and could be successfully applied for chemometric analysis of chromatographic profiles whenever knowledge of the identity of peaks is lacking or unnecessary. PMID:15537294

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

    PubMed

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

    2009-07-01

    Using the 3114/3115 thermal activity monitor (TAM) air isothermal microcalorimeter, ampoule mode, the heat output of Candida albicans growth at 37 degrees C was measured, and the effect of emodin on C. albicans growth was evaluated by microcalorimetry coupled with chemometric methods. The similarities between the heat flow power (HFP)-time curves of C. albicans growth affected by different concentrations of emodin were calculated by similarity analysis (SA). In the correspondence analysis (CA) diagram of eight quantitative parameters taken from the HFP-time curves, it could be deduced that emodin had definite dose-effect relationship as the distance between different concentrations of it increased along with the dosage and the effect. From the principal component analysis (PCA) on eight quantitative parameters, the action of emodin on C. albicans growth could be easily evaluated by analyzing the change of values of the main two parameters, growth rate constant k (2) and maximum power output P(2)(m). The coherent results of SA, CA, and PCA showed that emodin at different concentrations had different effects on C. albicans growth metabolism: A low concentration (0-10 microg ml(-1)) poorly inhibited the growth of C. albicans, and a high concentration (15-35 microg ml(-1)) could notably inhibit growth of this fungus. This work provided a useful idea of the combination of microcalorimetry and chemometric analysis for investigating the effect of drug and other compounds on microbes. PMID:19543891

  15. 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. PMID:25263911

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  17. Comprehensive evaluation of antioxidant activity: A chemometric approach using principal component analysis

    NASA Astrophysics Data System (ADS)

    Casoni, Dorina; Sârbu, Costel

    2014-01-01

    A novel chemometric approach is described for evaluating the radical scavenging activity of biogenic amine related compounds by using the 2,2-diphenyl-1-picrylhydrazyl (DPPHrad ) procedure and principal component analysis (PCA) tool. By a comprehensive chemometric investigation of variations in the radical scavenging profiles provided by the full-range UV-Vis spectra for different test duration and different relative concentrations (different molar ratio - [AH]/[DPPHrad ]) of the investigated compounds, new antioxidant activity evaluation parameters were proposed. The new proposed parameters (PC1, mPC1, maxPC1) are in good agreement with the reference DPPHrad results (% RSA and IC50 derived from the reference DPPHrad test), obtained for the investigated amines and reference antioxidants. Much more, the PCA profiles are better patterns for the comprehensive characterization of radical scavenging activity of compounds, allowing visualization of complex information by a simple graphical representation and underlying the (dis)similarity of compounds related both to the reaction kinetics and compounds concentration.

  18. 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. PMID:27226461

  19. 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. PMID:25442555

  20. Simultaneous mixture analysis using a dynamic microbial sensor combined with chemometrics.

    PubMed

    Slama, M; Zaborosch, C; Wienke, D; Spener, F

    1996-11-01

    A biosensor consisting of immobilized microbial cells and an oxygen electrode was used in a flow-through system as a microbial sensor flow injection analyzer (FIA). For different organic analytes, the metabolism of vital cells provides individual time-resolved responses with distinct time-dependent amplitudes. Chemometrical data analysis revealed that the individual responses are additive and depend linearly on single analyte concentrations. Based on these observations, simultaneous multicomponent analysis of organic mixtures was carried out in the FIA's time domain with analytical errors of less than 10%. For mixture analysis and monitoring in processes like enzymatic conversions, the described microbial sensor FIA ("dynamic microbial sensor") offers an alternative to expensive analytical equipment. PMID:21619259

  1. 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. PMID:26471577

  2. 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

  3. 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. PMID:26093314

  4. 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. PMID:27474327

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

    PubMed Central

    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. PMID:26539304

  6. 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. PMID:25105420

  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. PMID:21858755

  8. 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

  9. Liquid chromatography and chemometric-assisted spectrophotometric methods for the analysis of two multicomponent mixtures containing cough suppressant drugs.

    PubMed

    El-Gindy, Alaa; Emara, Samy; Mesbah, Mostafa K; Hadad, Ghada M

    2005-01-01

    Three methods were applied for the analysis of 2 multicomponent mixtures containing dextromethorphan hydrobromide, phenylephrine hydrochloride, chlorpheniramine maleate, methylparaben, and propylparaben, together with either sodium benzoate (Mix 1) or ephedrine hydrochloride and benzoic acid (Mix 2). In the first method, liquid chromatography was used for their simultaneous determination using an ODS column with a mobile phase consisting of acetonitrile-phosphate buffer, pH 2.7 (40 + 60, v/v), containing 5mM heptanesulfonic acid sodium salt and ultraviolet (UV) detection at 214 nm. Also, 2 chemometric methods, principal component regression, and partial least squares were used. For both chemometric calibrations, a concentration set of the mixture consisting of each compound in each mixture was prepared in distilled water. The absorbance data in the UV spectra were measured for the 76 or 71 wavelength points in the spectral region 210-240 or 210-224 nm considering the intervals of deltagamma = 0.4 or 0.2 nm for Mix 1 and Mix 2, respectively. The 2 chemometric methods did not require any separation step. These methods were successfully applied for the analysis of the 2 multicomponent combinations in synthetic mixtures and in commercial syrups, and the results were compared with each other. PMID:16152922

  10. 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. PMID:26799976

  11. 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.

  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. PMID:25459943

  13. Analysis of essential oils and fatty acids from Platycodi Radix using chemometric methods and retention indices.

    PubMed

    He, Min; Li, Yaping; Yan, Jun; Cao, Dongsheng; Liang, Yizeng

    2013-04-01

    The chemical composition of the essential oils and fatty acids among nine groups of Platycodi Radix in China was analyzed by gas chromatography-mass spectrometry. Complicated components were resolved using chemometric methods. Simultaneously, the various features among heuristic evolving latent projections, selective ion analysis and alternative moving window factor analysis were compared by using some experimental data. Temperature-programmed retention indices were applied in further identification of the chemical composition of the essential oils. The equivalent chain length, fraction chain length, and an established special retention indices library integrated with mass spectrometry were also applied to further identify the composition of fatty acids, including total fatty acids, esterified fatty acids and free fatty acids. A total of 121 different compounds accounting for 95.12-98.74% were identified among the essential oils. Chemical polymorphisms and variation existed in the essential oils of Platycodi Radix. Sixteen components were identified in fatty acids, and linoleic acid (18:2n-6c) and other unsaturated acid possess a characteristic majority. PMID:22964951

  14. 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

    2015-01-01

    In this study, the metabolomics characterization focusing on the carotenoid composition of ten cassava (Manihot esculenta) genotypes cultivated in southern Brazil by UV-visible scanning spectrophotometry and reverse phase-high performance liquid chromatography was performed. Cassava roots rich in β-carotene are an important staple food for populations with risk of vitamin A deficiency. Cassava genotypes with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin. The data set was used for the construction of a descriptive model by chemometric analysis. The genotypes of yellow-fleshed roots were clustered by the higher concentrations of cis-β-carotene and lutein. Inversely, cream-fleshed roots genotypes were grouped precisely due to their lower concentrations of these pigments, as samples rich in lycopene (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. PMID:26673931

  15. 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. PMID:26090781

  16. Combining spectroscopic data in the forensic analysis of paint: Application of a multiblock technique as chemometric tool.

    PubMed

    Lambert, Danny; Muehlethaler, Cyril; Esseiva, Pierre; Massonnet, Geneviève

    2016-06-01

    A study (Muehlethaler et al. [9]) has demonstrated the application of chemometrics for the analysis of domestic red paints. The paints have been analyzed with IR and Raman spectroscopies. As a result of these analyses, exploratory techniques, such as principal component analysis (PCA) and hierarchical clusters analysis (HCA) have been applied to both IR and Raman spectra. This allowed to observe the structure of the data among those red paints, and infer potential groups among them and to propose a classification model based on their chemical composition. IR spectroscopy showed group patterns related mainly to the binder and extender composition of the paints, whereas Raman spectroscopy data were mainly related to the pigment composition. The aim of the present study is to evaluate the potential of a Multiblock algorithm applied to the same data set. The concept of Multiblock, as a chemometric tool, is to combine data from several different analytical techniques in order to visualize most of the information at once. IR and Raman spectroscopy are then considered as "blocks" of data of the same dataset. One algorithm called common component and specific weight analysis (CCSWA) has been used in order to produce independent PCAs for each block, and the combined (common) information in a score plot. The results of this study showed group patterns of the analyzed paints, related to both binder and pigment compositions in one single score plot. Moreover, the number of groups observed with the multiblock representation (20 groups) is higher than independent PCAs projections (12 and 7 groups for IR and Raman respectively). This new application of chemometrics showed a great potential in forensic science, as practitioners often use a combination of several analytical techniques in order to characterize samples. This could be helpful when multiple and complementary analytical techniques are used in order to characterize and compare paint samples. PMID:27060443

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

    PubMed

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

    2016-07-01

    This study assessed the feasibility of gas chromatography with flame ionization detection fingerprinting combined with chemometrics for quality analysis of Atractylodes rhizome. We extracted essential oils from 20 Atractylodes lancea and Atractylodes koreana samples by hydrodistillation. The variation in extraction yields (1.33-4.06%) suggested that contents of the essential oils differed between species. The volatile components (atractylon, atractydin, and atractylenolide I, II, and III) were quantified by gas chromatography with flame ionization detection and confirmed by gas chromatography with mass spectrometry, and the results demonstrated that the number and content of volatile components differed between A. lancea and A. koreana. We then calculated the relative peak areas of common components and similarities of samples by comparing the chromatograms of A. lancea and A. koreana extracts. Also, we employed several chemometric techniques, including similarity analysis, hierarchical clustering analysis, principal component analysis, and partial least-squares discriminate analysis, to analyze the samples. Results were consistent across analytical methods and showed that samples could be separated according to species. Five volatile components in the essential oils were quantified to further validate the results of the multivariate statistical analysis. The method is simple, stable, accurate, and reproducible. Our results provide a foundation for quality control analysis of A. lancea and A. koreana. PMID:27133960

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

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

    PubMed

    Yücel, Yasin; Sultanoğlu, Pınar

    2013-09-01

    Chemical characterisation has been carried out on 45 honey samples collected from Hatay region of Turkey. The concentrations of 17 elements were determined by inductively coupled plasma optical emission spectrometry (ICP-OES). Ca, K, Mg and Na were the most abundant elements, with mean contents of 219.38, 446.93, 49.06 and 95.91 mg kg(-1) respectively. The trace element mean contents ranged between 0.03 and 15.07 mg kg(-1). Chemometric methods such as principal component analysis (PCA) and cluster analysis (CA) techniques were applied to classify honey according to mineral content. The first most important principal component (PC) was strongly associated with the value of Al, B, Cd and Co. CA showed eight clusters corresponding to the eight botanical origins of honey. PCA explained 75.69% of the variance with the first six PC variables. Chemometric analysis of the analytical data allowed the accurate classification of the honey samples according to origin. PMID:23578638

  20. 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. PMID:20685442

  1. 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. PMID:26228790

  2. 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.

  3. 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...

  4. 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. PMID:25882413

  5. 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. PMID:26592598

  6. 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. PMID:27337563

  7. Chemometric method of spectra analysis leading to isolation of lysozyme and CtDNA spectra affected by osmolytes.

    PubMed

    Bruździak, Piotr; Rakowska, Paulina W; Stangret, Janusz

    2012-11-01

    In this paper we present a chemometric method of analysis leading to isolation of Fourier transform infrared (FT-IR) spectra of biomacromolecules (HEW lysozyme, ctDNA) affected by osmolytes (trimethylamine-N-oxide and N,N,N-trimethylglycine, respectively) in aqueous solutions. The method is based on the difference spectra method primarily used to characterize the structure of solvent affected by solute. The cyclical usage of factor analysis allows precise information to be obtained on the shape of "affected spectra" of analyzed biomacromolecules. "Affected spectra" of selected biomacromolecules give valuable information on their structure in the presence of the osmolytes in solution, as well as on the level of perturbation in dependence of osmolyte concentration. The method also gives a possibility of insight into the mechanism of interaction in presented types of systems. It can be easily adapted to various chemical and biochemical problems where vibrational or ultraviolet-visible (UV-Vis) spectroscopy is used. PMID:23146186

  8. Geographic origins and compositions of virgin olive oils determinated by chemometric analysis of NIR spectra.

    PubMed

    Galtier, O; Dupuy, N; Le Dréau, Y; Ollivier, D; Pinatel, C; Kister, J; Artaud, J

    2007-07-01

    The authentication of virgin olive oil samples requires usually the use of sophisticated and time consuming analytical techniques. There is a need for fast and simple analytical techniques for the objective of a quality control methodology. Virgin olive oils present characteristic NIR spectra. Chemometric treatment of NIR spectra was assessed for the quantification of fatty acids and triacylglycerols in virgin olive oil samples (n=125) and for their classification (PLS1-DA) into five very geographically closed registered designations of origin (RDOs) of French virgin olive oils ("Aix-en-Provence", "Haute-Provence", "Nice", "Nyons" and "Vallée des Baux"). The spectroscopic interpretation of regression vectors showed that each RDO was correlated to one or two specific components of virgin olive oils according to their cultivar compositions. The results were quite satisfactory, in spite of the similarity of cultivar compositions between two denominations of origin ("Aix-en-Provence" and "Vallée des Baux"). Chemometric treatments of NIR spectra allow us to obtain similar results than those obtained by time consuming analytical techniques such as GC and HPLC, and constitute a help fast and robust for authentication of those French virgin olive oils. PMID:17605993

  9. 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.

  10. 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

  11. Chemometric Analysis of Two Dimensional Decay Data: Application to {sup 17}O NMR Relaxation Matrices

    SciTech Connect

    Alam, M.K.; Alam, T.M.

    1999-03-18

    The use of {sup 17}O NMR spectroscopy as a tool to investigate aging in polymer systems has recently been demonstrated. Because the natural abundance of {sup 17}O is extremely low (0.037%), the use of labeled {sup 17}O{sub 2} during the oxidation of polymers produces {sup 17}O NMR spectra whose signals arise entirely from the degradation species (i.e. signals from the bulk or unaged material are not observed). This selective isotopic labeling eliminates the impact of interference from the unaged material, cause (1) above. As discussed by Alam et al. spectral overlap between different degradation species as well as errors in quantification remains a major difficulty in {sup 17}O NMR spectroscopy. As a demonstration of the DECRA and CTBSA methods, relaxation matrices obtained from {sup 17}O NMR for model alcohol systems are evaluated. The benefits and limitations of these newly developed chemometric techniques are discussed.

  12. Chemometrics meets homeopathy--an exploratory analysis of infrared spectra of homeopathic granules.

    PubMed

    Gorlowska, Kinga; Gorlowska, Joanna; Skibiński, Robert; Komsta, Łukasz

    2015-11-10

    10 homeopathic remedies commercially available (each in 3 dilutions) as sugar granules, where half of them were of organic (and half inorganic) origin were subjected to solid-state infrared spectroscopy, both in middle infrared (ATR-FTIR) and near infrared (NIR) range. Measurements were repeated six times (six days, each sample was measured once in the same day, samples were measured in random order). The obtained spectra was subjected to unsupervised (PCA) and supervised (PLS-DA) chemometric techniques to check any visible differnces in spectral data between homeopathic remedies, including also feature selection approaches. It can be concluded that the only one information encoded in this dataset is the atmospheric drift of spectra between consecutive measurement days. This proves that homeopathy is not "infrared visible" in the case of proper experimental design. These results can be useful in further investigations of possible mechanisms of action of homeopathy (if they exist). PMID:26148470

  13. 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. 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. PMID:26861578

  15. 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. PMID:26791345

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

    PubMed

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

    2015-10-01

    This study was performed to establish a method that can quickly and accurately identify adulterated syrup in the pure pineapple juice. A attenuated total internal refraction-fourier transform infrared spectroscopy was used to collect the range of 900 -1 500 cm(-1) infrared spectra of 234 samples pure pineapple juice and adulterated syrup by beet syrup, rice syrup and cassava syrup. By using linear discriminant analysis and support vector machine for the identification model, comparing the full spectral and selected wavelengths based on principal component analysis loading plots of the two models to identify adulteration. Studies showed that the correct rate of validation set by linear discriminant analysis and support vector machine model on full spectral were both higher than 88%, variables were significantly reduced from 312 to 8 after selecting the eight characteristic wavelengths, the correct rate of validation set by linear discriminant analysis model was up to 96.15% and support vector machine was increase to 94.87%. The results demonstrated that the model built using a attenuated total internal refraction-fourier transform infrared spectroscopy in combination with chemometric methods after selected characteristic wavelengths could be used for the identification of the adulterated syrup in the pure pineapple juice. PMID:26904809

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

    PubMed

    Gorrochategui, Eva; Lacorte, Sílvia; Tauler, Romà; Martin, Francis L

    2016-05-16

    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

  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. PMID:21238720

  19. 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

  20. 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.

  1. Application of merged spectroscopic data combined with chemometric analysis for resolution of hemoglobin intermediates during chemical unfolding

    NASA Astrophysics Data System (ADS)

    Fotouhi, L.; Yousefinejad, S.; Salehi, N.; Saboury, A. A.; Sheibani, N.; Moosavi-Movahedi, A. A.

    2015-02-01

    Using tetradecyltrimethylammonium bromide (TTAB) as a surfactant denaturant, and augmentation of different spectroscopic data, helped to detect the intermediates of hemoglobin (Hb) during unfolding process. UV-vis, fluorescence, and circular dichroism spectroscopy were used simultaneously to monitor different aspects of hemoglobin species from the tertiary or secondary structure points of view. Application of the multivariate curve resolution-alternating least square (MCR-ALS), using the initial estimates of spectral profiles and appropriate constraints on different parts of augmented spectroscopic data, showed good efficiency for characterization of intermediates during Hb unfolding. These results indicated the existence of five protein species, including three intermediate-like compounds in this process. The unfolding pathway in the presence of TTAB included conversion of oxyhemoglobin into deoxyhemoglobin, and then ferrylhemoglobin, ferrihemoglobin or aquamethemoglobin, which finally transformed into hemichrome. This is the first application of chemometric analysis on the merged spectroscopic data related to chemical denaturation of a protein. These types of analysis in multisubunit proteins not only increase the domain of information, but also can reduce the ambiguities of the obtained results.

  2. Application of chemometrics in river water classification.

    PubMed

    Kowalkowski, Tomasz; Zbytniewski, Radosław; Szpejna, Jacek; Buszewski, Bogusław

    2006-02-01

    The main aim of this work is focused on water quality classification of the Brda river (Poland) and evaluation of pollution data obtained by the monitoring measurement during the period 1994-2002. The study presents the application of selected chemometric techniques to the pollution monitoring dataset, namely, cluster analysis, principal component analysis, discriminant analysis and factor analysis. The obtained results allowed to determine natural clusters and groups of monitoring locations with similar pollution character and identify important discriminant variables. Chemometric analysis confirmed the classification of water purity of the Brda river made by the Inspection of Environmental Protection but the results showed more differentiation between monitored locations. This enables better evaluation of the water quality in a monitored region. On the basis of the chemometric approach, it was also found that some locations were under the high influence of municipal contamination, and some others under the influence of agriculture (discharges from fields) within the observed time period. PMID:16442142

  3. Comparability of higher order structure in proteins: chemometric analysis of second-derivative amide I Fourier transform infrared spectra.

    PubMed

    Stockdale, Gregory; Murphy, Brian M; D'Antonio, Jennifer; Manning, Mark Cornell; Al-Azzam, Wasfi

    2015-01-01

    Comparing higher order structure (HOS) in therapeutic proteins is a significant challenge. Previously, we showed that changes in solution conditions produced detectable changes in the second-derivative amide I Fourier transform infrared (FTIR) spectra for a variety of model proteins. Those comparisons utilized vector-based approaches, such as spectral overlap and spectral correlation coefficients to quantify differences between spectra. In this study, chemometric analyses of the same data were performed, to classify samples into different groups based on the solution conditions received. The solution conditions were composed of various combinations of temperature, pH, and salt types. At first, principal component analysis (PCA) was used to visually demonstrate that FTIR spectra respond to changes in solution conditions, which, presumably indicates variations in HOS. This observed when samples from the same solution condition form clusters within a PCA score plot. The second approach, called soft independent modeling of class analogy (SIMCA), was conducted to account for the within-class experimental error for the lysozyme spectra. The DModX values, indicative of the distance of each spectra to their respective class models, was found to be a more sensitive quantitative indicator of changes in HOS, when compared with the modified area of overlap algorithm. The SIMCA approach provides a metric to determine whether new observations do, or do not belong to a particular class or group. Thus, SIMCA is the recommended approach when multiple samples from each condition are available. PMID:25382804

  4. 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. PMID:22099648

  5. 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

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

    PubMed

    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

  7. 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

  8. 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. PMID:27257614

  9. 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.

  10. 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.

    PubMed

    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. PMID:26641286

  11. 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

  12. 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. PMID:24480282

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

    PubMed

    Adutwum, L A; Harynuk, J J

    2014-08-01

    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

  14. Lipid compositions and French registered designations of origins of virgin olive oils predicted by chemometric analysis of mid-infrared spectra.

    PubMed

    Galtier, O; Le Dréau, Y; Ollivier, D; Kister, J; Artaud, J; Dupuy, N

    2008-05-01

    The combination of mid-infrared (MIR) spectroscopy with multivariate analysis provides an original approach to study the profile of virgin olive oils (VOOs) in relation to composition and geographical origin. Chemometric treatment of mid-infrared spectra (n=402) is assessed for quantification of fatty acids (14 components) and triacylglycerols (19 components) in VOO samples and for classification into six very geographically closed registered designations of origin (RDOs) of French VOO ("Aix-en-Provence", "Haute-Provence", "Vallée des Baux de Provence", "Nice", "Nîmes", and "Nyons"). Spectroscopic interpretation of regression vectors has shown that each RDO is correlated to one specific component of VOO according to their cultivar compositions. The results are satisfactory, in spite of the similarity of cultivar compositions between two denominations of origin ("Aix-en-Provence" and "Vallée des Baux de Provence"). Chemometric treatment of MIR spectra makes it possible to obtain similar results to those obtained by time-consuming analytical techniques such as gas chromatography (GC) and high-performance liquid chromatography (HPLC) and constitutes a fast and robust tool for authentication of these French VOOs. PMID:18498701

  15. Rapid identification of anti-inflammatory compounds from Tongmai Yangxin Pills by liquid chromatography with high-resolution mass spectrometry and chemometric analysis.

    PubMed

    Tao, Shan; Huang, Yi; Chen, Zhui; Chen, Yaqi; Wang, Yi; Wang, Yi

    2015-06-01

    We present an integrated approach to rapidly identify anti-inflammatory compounds of TongmaiYangxin Pills (TMYXP), a botanical drug for the treatment of cardiovascular disease. Liquid chromatography coupled with high-resolution mass spectrometry was used to analyze the chemical composition of TMYXP. Eighty compounds of TMYXP including flavonoids, coumarins, iridoid glycosides, saponins, and lignans, were identified unambiguously or tentatively. After the rapid isolation and bioassay, 18 fractions of TMYXP were obtained and their anti-inflammatory activities were evaluated in lipopolysaccharide-stimulated RAW 264.7 macrophages. We performed chemometric analysis to reveal the correlation between the chemical and pharmacological information of the fractions to facilitate the identification of active compounds. To verify the reliability of the proposed method in discovering active components from a complex mixture, activities of seven compounds, which were positively or negatively related to bioactivity according to calculation, were validated in vitro. Results indicated that six active compounds with high R values exerted certain anti-inflammatory effects in a dose-dependent manner with IC50 values of 53.6-204.1 μM. Our findings suggest that the integrated use of identification based on high-resolution mass spectrometry and chemometric methods could rapidly identify active compounds from complex mixture of natural products. PMID:25943824

  16. 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. PMID:26830638

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  18. 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. PMID:27211642

  19. Characterizing biomass fast pyrolysis oils by 13C-NMR and chemometric analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Several biomass fast pyrolysis oils were characterized by 13C and DEPT NMR analysis to determine chemical functional group compositions as related to their energy content. Pyrolysis oils were produced from a variety of feedstocks including energy crops, woods, animal wastes and oil seed presscakes,...

  20. 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. PMID:25640119

  1. Spectroscopic and Chemometric Analysis of Binary and Ternary Edible Oil Mixtures: Qualitative and Quantitative Study.

    PubMed

    Jović, Ozren; Smolić, Tomislav; Primožič, Ines; Hrenar, Tomica

    2016-04-19

    The aim of this study was to investigate the feasibility of FTIR-ATR spectroscopy coupled with the multivariate numerical methodology for qualitative and quantitative analysis of binary and ternary edible oil mixtures. Four pure oils (extra virgin olive oil, high oleic sunflower oil, rapeseed oil, and sunflower oil), as well as their 54 binary and 108 ternary mixtures, were analyzed using FTIR-ATR spectroscopy in combination with principal component and discriminant analysis, partial least-squares, and principal component regression. It was found that the composition of all 166 samples can be excellently represented using only the first three principal components describing 98.29% of total variance in the selected spectral range (3035-2989, 1170-1140, 1120-1100, 1093-1047, and 930-890 cm(-1)). Factor scores in 3D space spanned by these three principal components form a tetrahedral-like arrangement: pure oils being at the vertices, binary mixtures at the edges, and ternary mixtures on the faces of a tetrahedron. To confirm the validity of results, we applied several cross-validation methods. Quantitative analysis was performed by minimization of root-mean-square error of cross-validation values regarding the spectral range, derivative order, and choice of method (partial least-squares or principal component regression), which resulted in excellent predictions for test sets (R(2) > 0.99 in all cases). Additionally, experimentally more demanding gas chromatography analysis of fatty acid content was carried out for all specimens, confirming the results obtained by FTIR-ATR coupled with principal component analysis. However, FTIR-ATR provided a considerably better model for prediction of mixture composition than gas chromatography, especially for high oleic sunflower oil. PMID:26971405

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

    PubMed

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

    2016-08-01

    Monoclonal antibodies (mAbs) compounded into the hospital pharmacy are widely used nowadays. Their fast identification after compounding and just before administration to the patient is of paramount importance for quality control at the hospital. This remains challenging due to the high similarity of the structure between mAbs. Analysis of the ultraviolet spectral data of four monoclonal antibodies (cetuximab, rituximab, bevacizumab, and trastuzumab) using unsupervised principal component analysis led us to focus exclusively on the second-derivative spectra. Partial least squares-discriminant analysis (PLS-DA) applied to these data allowed us to build models for predicting which monoclonal antibody was present in a given infusion bag. The calibration of the models was obtained from a k-fold validation. A prediction set from another batch was used to demonstrate the ability of the models to predict well. PLS-DA models performed on the spectra of the region of aromatic amino acid residues presented high ability to predict mAb identity. The region corresponding to the tyrosine residue reached the highest score of good classification with 89 %. To improve the score, standard normal variate (SNV) preprocessing was applied to the spectral data. The quality of the optimized PLS-DA models was enhanced and the region from the tyrosine/tryptophan residues allowed us excellent classification (100 %) of the four mAbs according to the matrix of confusion. The sensitivity and specificity performance parameters assessed this excellent classification. The usefulness of the combination of UV second-derivative spectroscopy to multivariate analysis with SNV preprocessing demonstrated the unambiguous identification of commercially available monoclonal antibodies. Graphical abstract PLS-DA models on the spectra of the region of aromatic amino acid residues allows mAb identification with high prediction. PMID:27334717

  3. 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

    2016-02-01

    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

  4. 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. PMID:25485767

  5. 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. PMID:26926361

  6. 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.

  7. 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. PMID:23265450

  8. 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. PMID:27081767

  9. 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

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

    PubMed

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

    2016-07-15

    Traditional Chinese herbal medicines (TCHMs) are promising approach for the treatment of various diseases which have attracted increasing attention all over the world. Chemometrics in quality control of TCHMs are great useful tools that harnessing mathematics, statistics and other methods to acquire information maximally from the data obtained from various analytical approaches. This feature article focuses on the recent studies which evaluating the pharmacological efficacy and quality of TCHMs by determining, identifying and discriminating the bioactive or marker components in different samples with the help of chemometric techniques. In this work, the application of chemometric techniques in the classification of TCHMs based on their efficacy and usage was introduced. The recent advances of chemometrics applied in the chemical analysis of TCHMs were reviewed in detail. PMID:26795190

  11. (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. PMID:27374530

  12. 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

  13. 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.

  14. 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.

  15. The effect of solvent on permeant diffusion through membranes studied using ATR-FTIR and chemometric data analysis.

    PubMed

    Dias, M; Hadgraft, J; Raghavan, S L; Tetteh, J

    2004-01-01

    One method of improving the bioavailability of a topical formulation is to add an appropriate solvent that will act as a solubilizer for the permeant and, at the same time, modify the barrier properties of the stratum corneum. It has proved very difficult to determine the precise mechanisms of action involved; this is complicated by the concurrent diffusion of the solvent and the permeant into the skin. Under these circumstances the barrier function may well be changing as a function of time as the solvent disrupts it. We have observed this phenomenon in a model silicone membrane system that we have chosen to study initially to avoid the complexity of the heterogeneous nature of skin and its inherent biological variability. Diffusion experiments were conducted using an established ATR-FTIR approach but the data interpreted using sophisticated chemometric approaches that allowed us to deconvolve the IR signals from the permeant, the solvent, and the membrane. Data are presented that show the concurrent diffusion of benzoic acid (permeant), octanol (solvent), and how the octanol modifies the characteristics of the silicone membrane. Initial data are then presented using human skin to show the power of the diffusion approach coupled to the data deconvolution technique. PMID:14648648

  16. Chemometric analysis of comprehensive LC×LC-MS data: Resolution of triacylglycerol structural isomers in corn oil.

    PubMed

    Navarro-Reig, Meritxell; Jaumot, Joaquim; van Beek, Teris A; Vivó-Truyols, Gabriel; Tauler, Romà

    2016-11-01

    Comprehensive hyphenated two-dimensional liquid chromatography mass spectrometry (LC×LC-MS) is a very powerful analytical tool achieving high throughput resolution of highly complex natural samples. However, even using this approach there is still the possibility of not resolving some of the analytes of interest. For instance, triacylglycerols (TAGs) structural isomers in oil samples are extremely difficult to separate chromatographically due to their very similar structure and chemical properties. Traditional approaches based on current vendor chromatographic software cannot distinguish these isomers from their different mass spectral features. In this work, a chemometric approach is proposed to solve this problem. First, the experimental LC×LC-MS data structure is discussed, and results achieved by different methods based on the fulfilment of the trilinear model are compared. Then, the step-by-step resolution and identification of strongly coeluted compounds from different examples of triacylglycerols (TAGs) structural isomers in corn oil samples are described. As a conclusion, the separation power of two-dimensional chromatography can be significantly improved when it is combined with the multivariate curve resolution method. PMID:27591659

  17. 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.

  18. 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. PMID:27619656

  19. 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

    2016-01-01

    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. PMID:26901179

  20. Trilinearity deviation ratio: a new metric for chemometric analysis of comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry data.

    PubMed

    Pinkerton, David K; Parsons, Brendon A; Anderson, Todd J; Synovec, Robert E

    2015-04-29

    Comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS) is a well-established instrumental platform for complex samples. However, chemometric data analysis is often required to fully extract useful information from the data. We demonstrate that retention time shifting from one modulation to the next, Δ(2)tR, is not sufficient alone to quantitatively describe the trilinearity of a single GC×GC-TOFMS run for the purpose of predicting the performance of the chemometric method parallel factor analysis (PARAFAC). We hypothesize that analyte peak width on second dimension separations, (2)Wb, also impacts trilinearity, along with Δ(2)tR. The term trilinearity deviation ratio, TDR, which is Δ(2)tR normalized by (2)Wb, is introduced as a quantitative metric to assess accuracy for PARAFAC of a GC×GC-TOFMS data cube. We explore how modulation ratio, MR, modulation period, PM, temperature programming rate, Tramp, sampling phase (in-phase and out-of-phase), and signal-to-noise ratio, S/N, all play a role in PARAFAC performance in the context of TDR. Use of a PM in the 1-2 s range provides an optimized peak capacity for the first dimension separation (500-600) for a 30 min run, with an adequate peak capacity for the second dimension separation (12-15), concurrent with an optimized two-dimensional peak capacity (6000-7500), combined with sufficiently low TDR values (0-0.05) to facilitate low quantitative errors with PARAFAC (0-0.5%). In contrast, use of a PM in the 5s or greater range provides a higher peak capacity on the second dimension (30-35), concurrent with a lower peak capacity on the first dimension (100-150) for a 30 min run, and a slightly reduced two-dimensional peak capacity (3000-4500), and furthermore, the data are not sufficiently trilinear for the more retained second dimension peaks in order to directly use PARAFAC with confidence. PMID:25847163

  1. 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. PMID:26987554

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  3. Classification of Cultivation Locations of Panax quinquefolius L Samples using High Performance Liquid Chromatography–Electrospray Ionization Mass Spectrometry and Chemometric Analysis

    PubMed Central

    Sun, Xiaobo; Chen, Pei; Cook, Shannon L.; Jackson, Glen P.; Harnly, James M.; Harrington, Peter B.

    2013-01-01

    Panax quinquefolius L (P. quinquefolius L) samples grown in the United States and China were analyzed with high performance liquid chromatography–mass spectrometry (HPLC–MS). Prior to classification, the two-way data sets were subjected to pretreatment including baseline correction and retention time (RT) alignment. Principal component analysis (PCA) and projected difference resolution (PDR) metrics were used to evaluate the data quality and the pretreatment effects. A fuzzy rule-building expert system (FuRES) classifier was used to classify the P. quinquefolius L samples grown in the United States and China with the optimized partial least-squares (o-PLS) classifier as the positively biased control method. A classification rate as high as 98 ± 3% with FuRES was obtained after baseline correction and RT alignment, which is equivalent to the result obtained by using the positively biased o-PLS control method (98 ± 3%). RT alignment improved the classification rates for both FuRES and o-PLS classifiers (18% improvement for the FuRES classification rate and 10% improvement for the o-PLS classification rate with baseline correction). From the rule obtained to classify the P. quinquefolius L samples grown in the United States and China, peaks were identified that can be prospective biomarkers for differentiating samples from different growth regions. HPLC–MS with chemometric analysis has the potential to be used as an authentication method for P. quinquefolius L grown in China and the United States. PMID:22414002

  4. Chemical characteristics of different parts of Coreopsis tinctoria in China using microwave-assisted extraction and high-performance liquid chromatography followed by chemometric analysis.

    PubMed

    Lam, Shing-Chung; Liu, Xin; Chen, Xian-Qiang; Hu, De-Jun; Zhao, Jing; Long, Ze-Rong; Fan, Bing; Li, Shao-Ping

    2016-08-01

    Coreopsis tinctoria, also called "snow chrysanthemum" in China, is a flower tea material that has been reported to possess excellent pharmacological properties such as antioxidant and antidiabetic activities. The chemical characteristics of different parts (flowers, buds, seeds, stems, and leaves) of C. tinctoria were investigated based on microwave-assisted extraction and the simultaneous determination of 13 major active compounds by high-performance liquid chromatography, including taxifolin-7-O-glucoside, chlorogenic acid, (R/S)-flavanomarein, isocoreopsin, quercetagetin-7-O-glucoside, isookanin, 5,7,3',5'-tetrahydroxyflavanone-7-O-glucoside, marein, 3,5-dicaffeoylquinic acid, coreopsin, okanin, 5,7,3',5'-tetrahydroxyflavanone, and N(1) ,N(5) ,N(10) ,N(14) -tetra-p-coumaroylspermine. Chemometric analysis based on the contents of investigated compounds from 13 samples showed that C. tinctoria and the related flower tea materials, Chrysanthemum morifolium cv "Hangju" and "Gongju," were in different clusters, and different parts (flowers, buds, seeds, stems, and leaves) of C. tinctoria were obviously different. This study is helpful for the quality control and pharmacological evaluation of different parts from C. tinctoria and its related products. PMID:27291468

  5. Fourier transform mid-infrared spectroscopy (FT-MIR) combined with chemometrics for quantitative analysis of dextrin in Danshen (Salvia miltiorrhiza) granule.

    PubMed

    Guo, Tao; Feng, Wei-Hong; Liu, Xiao-Qian; Gao, Hui-Min; Wang, Zhi-Min; Gao, Liang-Liang

    2016-05-10

    The granule of Chinese medicine (GCM) is prepared by water-soluble extract of single yinpian (WESY) of herbal medicine, and used as a drug ingredient for clinical formulation. The WESY content or corresponding yinpian amount is the most important parameter in evaluating the quality of GCM. Low WESY content reflects poor GCM. Classical quantitative methods, such as HPLC, cannot fully detect the adulteration by adding characteristic ingredients and less WESY production. GCM is composed of WESY and a high content of specific excipient. The WESY content in the GCM may be indirectly analyzed using mid-infrared spectroscopy (MIR). In this paper, a quantitative method to evaluate the quality of Danshen (Salvia miltiorrhiza) granule (DG) was developed using MIR combined with chemometrics. Appropriate characteristic quantitative regions (CQR) were extracted by selecting the spectral regions corresponding to altered excipient content in DG. The best model of dextrin content determination in DG with low RMSEC of 1.97, low RMSEP of 2.07, and excellent RPD of 5.03 (>5.0) was obtained using partial least-squares (PLS) regression, and validated using accepted values of precision and recovery. The results suggest that FT-MIR combined with PLS is a rapid and valuable analytical tool to determine the WESY in DG based on excipient content. The model enabling indirect calculation of WESY content in GCM represents a reference standard for rapid analysis of other WESYs in GCM industry. PMID:26859611

  6. 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.

  7. Analysis and assessment of Madeira wine ageing over an extended time period through GC-MS and chemometric analysis.

    PubMed

    Pereira, Ana C; Reis, Marco S; Saraiva, Pedro M; Marques, José C

    2010-02-15

    Wine is one of the world's higher value agricultural products. The present work is centred on Madeira wine, a fine and prestigious example among Portuguese liqueur wines,with the main goal to deepen our understanding of relevant phenomena going on during the winemaking process, in particular during ageing of "Malmsey" Madeira wine. In this paper we present the results obtained from the chemical characterization of how its aroma composition evolves during ageing, and the development of a robust framework for analyzing the identity of aged Madeira wines. An extended ageing period was considered, covering a time frame of twenty years, from which several samples were analyzed in terms of their aromatic composition. The multivariate structure of this chemical information was then processed through multivariate statistical feature extraction techniques such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), in order to identify the relevant patterns corresponding to trends associated with wine ageing. Classification methodologies for age prediction were developed, using data from the lower dimensional sub-spaces obtained after projecting the original data to the latent variable spaces provided by PCA or PLS-DA. Finally, the performance for each classification methodology developed was evaluated according to their error rates using cross-validation methodologies (Leave-One-Out and k-fold Monte Carlo). Results obtained so far show that quite interesting classification performances can indeed be achieved, despite the natural variability present in wine products. These results also provide solid bases which can be used to build up available frameworks which assist quality monitoring and identity assurance tasks. PMID:20103138

  8. 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. PMID:25245419

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

    PubMed

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

    2015-12-18

    Traditional Chinese medicines (TCMs)-based products are becoming more and more popular over the world. To ensure the safety and efficacy, authentication of Chinese medicinal materials has been an important issue, especially for that with multiple botanical origins (one-to-multiple). Taking Clematidis Radix et Rhizoma (CRR) as a case study, we herein developed an integrated platform based on metabolite profiling and chemometrics analysis to characterize, classify, and predict the "one-to-multiple" herbs. Firstly, the predominant constituents, triterpenoid saponins, in three Clematis CRR were rapid characterized by a novel UPLC-QTOF/MS-based strategy, and a total of 49 triterpenoid saponins were identified. Secondly, metabolite profiling was performed by UPLC-QTOF/MS, and 4623 variables were extracted and aligned as dataset. Thirdly, by using pattern recognition analysis, a clear separation of the three Clematis CRR was achieved as well as a total number of 28 variables were screened as the valuable variables for discrimination. By matching with identified saponins, these 28 variables were corresponding to 10 saponins which were identified as marker compounds. Fourthly, based on the relative intensity of the marker compounds-related variables, genetic algorithm optimized support vector machines (GA-SVM) was employed to predict the species of CRR samples. The obtained model showed excellent prediction performance with a prediction accuracy of 100%. Finally, a heatmap visualization was employed for clarifying the distribution of identified saponins, which could be useful for phytochemotaxonomy study of Clematis herbs. These results indicated that our proposed platform was a powerful tool for chemical profiling and discrimination of herbs with multiple botanical origins, providing promising perspectives in tracking the formulation processes of TCMs products. PMID:26610614

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

    ERIC Educational Resources Information Center

    Analytical Chemistry, 1985

    1985-01-01

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

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

    PubMed

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

    2015-03-25

    A quality control strategy using high-performance liquid chromatography-diode array detector-electrospray ionization-tandem mass spectrometry (HPLC-DAD-ESI-MS/MS) coupled with chemometrics analysis was proposed for Aloe barbadensis Miller. Firstly, the extraction conditions including methanol concentration, extraction time and solvent-to-material ratio were optimized by multi-responses optimization based on response surface methodology (RSM). The optimum conditions were achieved by Derringer's desirability function and experimental validation implied that the established model exhibited favorable prediction ability. Then, HPLC fingerprint consisting of 27 common peaks was developed among 15 batches of A. barbadensis samples. 25 common peaks were identified using HPLC-DAD-ESI-MS/MS method by their spectral characteristics or comparison with the authentic standards. Chemometrics techniques including similarity analysis (SA), principal components analysis (PCA) and hierarchical clustering analysis (HCA) were implemented to classify A. barbadensis samples. The results demonstrated that all A. barbadensis samples shared similar chromatographic patterns as well as differences. These achievements provided an effective, reliable and comprehensive quality control method for A. barbadensis. PMID:25590942

  12. Assessment of Groundwater Quality by Chemometrics.

    PubMed

    Papaioannou, Agelos; Rigas, George; Kella, Sotiria; Lokkas, Filotheos; Dinouli, Dimitra; Papakonstantinou, Argiris; Spiliotis, Xenofon; Plageras, Panagiotis

    2016-07-01

    Chemometric methods were used to analyze large data sets of groundwater quality from 18 wells supplying the central drinking water system of Larissa city (Greece) during the period 2001 to 2007 (8.064 observations) to determine temporal and spatial variations in groundwater quality and to identify pollution sources. Cluster analysis grouped each year into three temporal periods (January-April (first), May-August (second) and September-December (third). Furthermore, spatial cluster analysis was conducted for each period and for all samples, and grouped the 28 monitoring Units HJI (HJI=represent the observations of the monitoring site H, the J-year and the period I) into three groups (A, B and C). Discriminant Analysis used only 16 from the 24 parameters to correctly assign 97.3% of the cases. In addition, Factor Analysis identified 7, 9 and 8 latent factors for groups A, B and C, respectively. PMID:27329059

  13. Rapid direct analysis to discriminate geographic origin of extra virgin olive oils by flash gas chromatography electronic nose and chemometrics.

    PubMed

    Melucci, Dora; Bendini, Alessandra; Tesini, Federica; Barbieri, Sara; Zappi, Alessandro; Vichi, Stefania; Conte, Lanfranco; Gallina Toschi, Tullia

    2016-08-01

    At present, the geographical origin of extra virgin olive oils can be ensured by documented traceability, although chemical analysis may add information that is useful for possible confirmation. This preliminary study investigated the effectiveness of flash gas chromatography electronic nose and multivariate data analysis to perform rapid screening of commercial extra virgin olive oils characterized by a different geographical origin declared in the label. A comparison with solid phase micro extraction coupled to gas chromatography mass spectrometry was also performed. The new method is suitable to verify the geographic origin of extra virgin olive oils based on principal components analysis and discriminant analysis applied to the volatile profile of the headspace as a fingerprint. The selected variables were suitable in discriminating between "100% Italian" and "non-100% Italian" oils. Partial least squares discriminant analysis also allowed prediction of the degree of membership of unknown samples to the classes examined. PMID:26988501

  14. 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 (...

  15. 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. PMID:25678337

  16. Quarry identification of historical building materials by means of laser induced breakdown spectroscopy, X-ray fluorescence and chemometric analysis

    NASA Astrophysics Data System (ADS)

    Colao, F.; Fantoni, R.; Ortiz, P.; Vazquez, M. A.; Martin, J. M.; Ortiz, R.; Idris, N.

    2010-08-01

    To characterize historical building materials according to the geographic origin of the quarries from which they have been mined, the relative content of major and trace elements were determined by means of Laser Induced Breakdown Spectroscopy (LIBS) and X-ray Fluorescence (XRF) techniques. 48 different specimens were studied and the entire samples' set was divided in two different groups: the first, used as reference set, was composed by samples mined from eight different quarries located in Seville province; the second group was composed by specimens of unknown provenance collected in several historical buildings and churches in the city of Seville. Data reduction and analysis on laser induced breakdown spectroscopy and X-ray fluorescence measurements was performed using multivariate statistical approach, namely the Linear Discriminant Analysis (LDA), Principal Component Analysis (PCA) and Soft Independent Modeling of Class Analogy (SIMCA). A clear separation among reference sample materials mined from different quarries was observed in Principal Components (PC) score plots, then a supervised soft independent modeling of class analogy classification was trained and run, aiming to assess the provenance of unknown samples according to their elemental content. The obtained results were compared with the provenance assignments made on the basis of petrographical description. This work gives experimental evidence that laser induced breakdown spectroscopy measurements on a relatively small set of elements is a fast and effective method for the purpose of origin identification.

  17. 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. PMID:23902683

  18. 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. PMID:26898370

  19. 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

    2015-01-01

    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. PMID:26473810

  20. 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. PMID:25613562

  1. 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. PMID:21645600

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

    PubMed

    Wu, Di; He, Yong

    2014-09-01

    Developing rapid methods for measuring long-chain ω-3 (n-3) poly-unsaturated fatty acid (LCPUFA) contents has been a crucial request from the algal oil industry. In this study, four spectroscopy techniques, namely visible and short-wave near infra-red (Vis-SNIR), long-wave near infra-red (LNIR), mid-infra-red (MIR) and nuclear magnetic resonance (NMR) spectroscopy, were exploited for determining the docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) contents in algal oil. The best prediction for both DHA and EPA were achieved by NMR spectroscopy, in which the determination coefficients of cross-validation (rCV(2)) values were 0.963 and 0.967 for two LCPUFAs. The performances of Vis-SNIR and LNIR spectroscopy were also accepted. The variable selection was proved as an efficient and necessary step for the spectral analysis in this study. The results were promising and implied that spectroscopy techniques have a great potential for assessment of DHA and EPA in algal oil. PMID:24731319

  3. Potential of visible-near infrared spectroscopy combined with chemometrics for analysis of some constituents of coffee and banana residues.

    PubMed

    Rambo, M K D; Amorim, E P; Ferreira, M M C

    2013-05-01

    Banana (stalk, leaf, rhizome, rachis and stem) and coffee (leaf and husks) residues are promising feedstock for fuel and chemical production. In this work we show the potential of near-infrared spectroscopy (NIR) and multivariate analysis to replace reference methods in the characterization of some constituents of coffee and banana residues. The evaluated parameters were Klason lignin (KL), acid soluble lignin (ASL), total lignin (TL), extractives, moisture, ash and acid insoluble residue (AIR) contents of 104 banana residues (B) and 102 coffee (C) residues from Brazil. PLS models were built for banana (B), coffee (C) and pooled samples (B+C). The precision of NIR methodology was better (p<0.05) than the reference method for almost all the parameters, being worse for moisture. With the exception of ash (B and C) and ASL (C) content, which was predicted poorly (R(2)<0.80), the models for all the analytes exhibited R(2)>0.80. The range error ratios varied from 4.5 to 16.0. Based on the results of external validation, the statistical tests and figures of merit, NIR spectroscopy proved to be useful for chemical prediction of banana and coffee residues and can be used as a faster and more economical alternative to the standard methodologies. PMID:23601973

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

    PubMed Central

    Jiang, Jun; Jia, Xiaobin

    2015-01-01

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

  5. 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. PMID:26746824

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

    PubMed

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

    2015-08-01

    In the present study, a new strategy based on chemical analysis and chemometrics methods was proposed for the comprehensive analysis and profiling of underivatized free amino acids (FAAs) and small peptides among various Luo-Han-Guo (LHG) samples. Firstly, the ultrasound-assisted extraction (UAE) parameters were optimized using Plackett-Burman (PB) screening and Box-Behnken designs (BBD), and the following optimal UAE conditions were obtained: ultrasound power of 280 W, extraction time of 43 min, and the solid-liquid ratio of 302 mL/g. Secondly, a rapid and sensitive analytical method was developed for simultaneous quantification of 24 FAAs and 3 active small peptides in LHG at trace levels using hydrophilic interaction ultra-performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry (HILIC-UHPLC-QTRAP(®)/MS(2)). The analytical method was validated by matrix effects, linearity, LODs, LOQs, precision, repeatability, stability, and recovery. Thirdly, the proposed optimal UAE conditions and analytical methods were applied to measurement of LHG samples. It was shown that LHG was rich in essential amino acids, which were beneficial nutrient substances for human health. Finally, based on the contents of the 27 analytes, the chemometrics methods of unsupervised principal component analysis (PCA) and supervised counter propagation artificial neural network (CP-ANN) were applied to differentiate and classify the 40 batches of LHG samples from different cultivated forms, regions, and varieties. As a result, these samples were mainly clustered into three clusters, which illustrated the cultivating disparity among the samples. In summary, the presented strategy had potential for the investigation of edible plants and agricultural products containing FAAs and small peptides. PMID:25976704

  7. 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.

  8. 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

    2015-09-01

    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. PMID:25919327

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

    PubMed

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

    2015-04-15

    Six Tunisian virgin olive oil (VOO) varieties, Chemlali Sfax, Chetoui, Chemchali, Oueslati, Zarrazi and Zalmati, were characterised by two analytical methods. The gas chromatography allowed the determination of 14 fatty acids and squalene amounts. With fatty acids of each variety, a characteristic "morphotypes" for each oil variety was established. Chemlali Sfax and Zalmati showed strong similarities. Gas chromatography of fatty acid methyl esters (FAME) and near infrared (NIR) spectra of oils, associated to chemometric treatment, allowed the study of the inter-varietal variability and the verification of the variety origins of some Tunisian commercial VOOs. The specificity of Tunisian VOOs was evaluated by comparing the samples to Algerian, Moroccan and French Protected Designation of Origin VOOs. Classification in varietal origins by SIMCA used the FAME compositions and NIR spectra of the most represented varieties (Chemlali Sfax, Chetoui and Oueslati) showed a high potential to authenticate the varietal origin of Tunisian VOOs. PMID:25466003

  10. Fluorescence spectroscopy and chemometric modeling for bioprocess monitoring.

    PubMed

    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

  11. 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

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

    PubMed

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

    2016-10-01

    As a result of the pressure from population explosion, agricultural land resources require further protecting and rationally utilizing. Intercropping technique has been widely applied for agricultural production to save cultivated area, improve crop quality, and promote agriculture economy. In this study, we employed high-performance liquid chromatography (HPLC) and ultraviolet-visible spectroscopy (UV-vis) combined with chemometrics for determination and qualitative evaluation of several kinds of intercropping system with Gentiana rigescens Franch. ex Hemsl. (GR), which is used as an hepatic protector in local communities in China. Results revealed that GR in a Camellia sinensis intercropping system contained most gentiopicroside, sweroside, and total active constituents (six chemical indicators), whose content reached 91.09 ± 3.54, 1.03 ± 0.06, and 104.05 ± 6.48 mg g(-1), respectively. The two applied quantitative and qualitative methods reciprocally verified that GR with 2 years of growth period performed better in terms of quality than 1 year, collectively. PMID:27193013

  13. Chemometric-assisted QuEChERS extraction method for the residual analysis of thiacloprid, spirotetramat and spirotetramat's four metabolites in pepper: Application of their dissipation patterns.

    PubMed

    Li, Shasha; Liu, Xingang; Dong, Fengshou; Xu, Jun; Xu, Hanqing; Hu, Mingfeng; Zheng, Yongquan

    2016-02-01

    Chemometric tools equipped with a Plackett-Burman (P-B) design, a central composite design (CCD) and a desirability profile were employed to optimise the QuEChERS (quick, easy, cheap, effective, rugged and safe) method for the quantification of thiacloprid, spirotetramat and spirotetramat's four metabolites in pepper. The average recoveries were in the range of 71.6-119.5%, with relative standard deviations ⩽ 12.1%. The limit of quantification for the method was less than 0.01 mg/kg. The method was applied to field samples to evaluate the residual characteristics of thiacloprid and spirotetramat. The data showed that the first+first-order model is a better fit than the first order model for the dissipation of thiacloprid and spirotetramat in pepper. The half-lives of thiacloprid and spirotetramat in pepper are 0.81 and 1.21 days, respectively. The final residues were between 0.016 mg/kg and 0.13 mg/kg for thiacloprid and 0.08 mg/kg and 0.12 mg/kg for spirotetramat. PMID:26304426

  14. Origin of French virgin olive oil registered designation of origins predicted by chemometric analysis of synchronous excitation-emission fluorescence spectra.

    PubMed

    Dupuy, Nathalie; Le Dréau, Yveline; Ollivier, Denis; Artaud, Jacques; Pinatel, Christian; Kister, Jacky

    2005-11-30

    The authentication of virgin olive oil samples requires usually the use of sophisticated and very expensive analytical techniques, so there is a need for fast and inexpensive analytical techniques for use in a quality control methodology. Virgin olive oils present an intense fluorescence spectra. Synchronous excitation-emission fluorescence spectroscopy (SEEFS) was assessed for origin determination of virgin olive oil samples from five French registered designation of origins (RDOs) (Nyons, Vallée des Baux, Aix-en-Provence, Haute-Provence, and Nice). The spectra present bands between 600 and 700 nm in emission due to chlorophylls a and b and pheophytins a and b. The bands between 275 and 400 nm in emission were attributed to alpha-, beta-, and gamma-tocopherols and to phenolic compounds, which characterize the virgin olive oils compared to other edible oils. The chemometric treatment (PLS1) of synchronous excitation-emission fluorescence spectra allows one to determine the origin of the oils from five French RDOs (Baux, Aix, Haute-Provence, Nice, and Nyons). Results were quite satisfactory, despite the similarity between two denominations of origin (Baux and Aix) that are composed by some common cultivars (Aglandau and Salonenque). The interpretation of the regression coefficients shows that RDOs are correlated to chlorophylls, pheophytins, tocopherols, and phenols compounds, which are different for each origin. SEEFS is part of a global analytic methodology that associates spectroscopic and chromatographic techniques. This approach can be used for traceability and vindicates the RDOs. PMID:16302748

  15. 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. PMID:26249158

  16. 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. PMID:25438133

  17. 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. PMID:22417888

  18. 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.

  19. 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

  20. Differentiation of Organically and Conventionally Grown Tomatoes by Chemometric Analysis of Combined Data from Proton Nuclear Magnetic Resonance and Mid-infrared Spectroscopy and Stable Isotope Analysis.

    PubMed

    Hohmann, Monika; Monakhova, Yulia; Erich, Sarah; Christoph, Norbert; Wachter, Helmut; Holzgrabe, Ulrike

    2015-11-01

    Because the basic suitability of proton nuclear magnetic resonance spectroscopy ((1)H NMR) to differentiate organic versus conventional tomatoes was recently proven, the approach to optimize (1)H NMR classification models (comprising overall 205 authentic tomato samples) by including additional data of isotope ratio mass spectrometry (IRMS, δ(13)C, δ(15)N, and δ(18)O) and mid-infrared (MIR) spectroscopy was assessed. Both individual and combined analytical methods ((1)H NMR + MIR, (1)H NMR + IRMS, MIR + IRMS, and (1)H NMR + MIR + IRMS) were examined using principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and common components and specific weight analysis (ComDim). With regard to classification abilities, fused data of (1)H NMR + MIR + IRMS yielded better validation results (ranging between 95.0 and 100.0%) than individual methods ((1)H NMR, 91.3-100%; MIR, 75.6-91.7%), suggesting that the combined examination of analytical profiles enhances authentication of organically produced tomatoes. PMID:26457410

  1. 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.

  2. Feature optimization in chemometric algorithms for explosives detection

    NASA Astrophysics Data System (ADS)

    Pinkham, Daniel W.; Bonick, James R.; Woodka, Marc D.

    2012-06-01

    This paper details the use of a genetic algorithm (GA) as a method to preselect spectral feature variables for chemometric algorithms, using spectroscopic data gathered on explosive threat targets. The GA was applied to laserinduced breakdown spectroscopy (LIBS) and ultraviolet Raman spectroscopy (UVRS) data, in which the spectra consisted of approximately 10000 and 1000 distinct spectral values, respectively. The GA-selected variables were examined using two chemometric techniques: multi-class linear discriminant analysis (LDA) and support vector machines (SVM), and the performance from LDA and SVM was fed back to the GA through a fitness function evaluation. In each case, an optimal selection of features was achieved within 20 generations of the GA, with few improvements thereafter. The GA selected chemically significant signatures, such as oxygen and hydron peaks from LIBS spectra and characteristic Raman shifts for AN, TNT, and PETN. Successes documented herein suggest that this GA approach could be useful in analyzing spectroscopic data in complex environments, where the discriminating features of desired targets are not yet fully understood.

  3. Identification of monofloral honeys using HPLC-ECD and chemometrics.

    PubMed

    Zhao, Jing; Du, Xiaojing; Cheng, Ni; Chen, Lanzhen; Xue, Xiaofeng; Zhao, Jing; Wu, Liming; Cao, Wei

    2016-03-01

    A total of 77 jujube, longan and chaste honey samples were collected from 18 different areas of China. Thirteen types of phenolic acids in the honey samples were analysed using high-performance liquid chromatography with electrochemical detection (HPLC-ECD). Moreover, HPLC-ECD fingerprints of the monofloral honey samples were established. From the analysis of the HPLC-ECD fingerprints, common chromatography peak information was obtained, and principal component analysis and discriminant analysis were performed using selected common chromatography peak areas as variables. By comparing with phenolic acids as variables, using a chemometric analysis which is based on the use of common chromatography peaks as variables, 36 honey samples and 41 test samples could be correctly identified according to their floral origin. PMID:26471540

  4. 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.

  5. 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. PMID:26994313

  6. Chemometric evaluation of trace metal concentrations in some nuts and seeds.

    PubMed

    Kafaoğlu, Burcu; Fisher, Andrew; Hill, Steve; Kara, Derya

    2014-01-01

    Seventeen trace metals in acid digests of nuts and seeds were determined using inductively coupled plasma-atomic emission spectrometry and inductively coupled plasma-mass spectrometry. The data were subjected to chemometric evaluation using principal component analysis (PCA), linear discriminant analysis (LDA) and cluster analysis (CA) in an attempt to classify the samples. Hazelnuts (raw and dry roasted), almonds (raw and dry roasted), sunflower seeds (black and white), peanuts (raw and dry roasted), cashew nuts, Brazil nuts, walnuts, chickpeas (raw and dry roasted), pumpkin seeds (raw and dry roasted), and pistachio nuts were used as samples. The samples were classified into seven groups by PCA and CA. All group members determined using PCA and CA were found by LDA to be correctly classified in the predicted groups. Interestingly, the chemometric evaluation indicated that the raw and roasted nuts are very close to each other even though some originated from different countries. PMID:25058626

  7. 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

  8. 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.

  9. (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. PMID:26988481

  10. Efficacy assessment of local doxycycline treatment in periodontal patients using multivariate chemometric approach.

    PubMed

    Bogdanovska, Liljana; Poceva Panovska, Ana; Nakov, Natalija; Zafirova, Marija; Popovska, Mirjana; Dimitrovska, Aneta; Petkovska, Rumenka

    2016-08-25

    The aim of our study was application of chemometric algorithms for multivariate data analysis in efficacy assessment of the local periodontal treatment with doxycycline (DOX). Treatment efficacy was evaluated by monitoring inflammatory biomarkers in gingival crevicular fluid (GCF) samples and clinical indices before and after the local treatment as well as by determination of DOX concentration in GCF after the local treatment. The experimental values from these determinations were submitted to several chemometric algorithms: principal component analysis (PCA), partial least square discriminant analysis (PLS-DA) and orthogonal projection to latent structures-discriminant analysis (OPLS-DA). The data structure and the mutual relations of the selected variables were thoroughly investigated by PCA. The PLS-DA model identified variables responsible for discrimination of classes of data, before and after DOX treatment. The OPLS-DA model compared the efficacy of the two commonly used medications in periodontal treatment, chlorhexidine (CHX) and DOX, at the same time providing insight in their mechanism of action. The obtained results indicate that application of multivariate chemometric algorithms can be used as a valuable approach for assessment of treatment efficacy. PMID:27283484

  11. 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…

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  13. Chemometrics and vibrational spectroscopy as green tools for mine phytoremediation strategies

    NASA Astrophysics Data System (ADS)

    Mokgalaka-Matlala, N. S.; Regnier, T.; Combrinck, S.; Kouekam, C. R.; Weiersbye, I. M.

    This study describes the use of near infrared (NIR) spectroscopy in combination with chemometrics to characterise Combretum erythrophyllum plant material to determine differences in the chemical profiles of samples harvested from mine contaminated areas and those of natural populations. The chemometric computation of near infrared vibrational spectra was used to generate principal component analysis and partial least squares models. These models were used to determine seasonal differences in the chemical matrices of samples harvested from the mine sites with different levels of contamination. Principal component analysis scatter plots illustrated clustering of phenolic profiles of samples depending on whether they originated from contaminated or uncontaminated soils. A partial least squares model was developed to link the variations in the chemical composition and levels of contamination in all samples collected in the same season (autumn). The levels of total soluble phenolic compounds in leaf extracts of C. erythrophyllum were measured using the Folin-Ciocalteau assay. Data analysis of the samples revealed that plants harvested from mine sites, particularly in summer, produced a higher level of phenolic compounds than those of the natural population, thereby displaying a good correlation with the chemometric models.

  14. 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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  15. 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...

  16. Toward Bayesian chemometrics--a tutorial on some recent advances.

    PubMed

    Chen, Hongshu; Bakshi, Bhavik R; Goel, Prem K

    2007-10-17

    Chemometrics is increasingly being perceived as a maturing science. While this perception seems to be true with regards to the traditional methods and applications of chemometrics, this article argues that advances in instrumentation, computation, and statistical theory may combine to drive a resurgence in chemometrics research. Previous surges in chemometrics research activity were driven by the development of new ways of making better use of available information. Bayesian statistics can further enhance the ability to use domain specific information to obtain more accurate and useful models, and presents many research opportunities as well as challenges. Although Bayesian statistics is not new, recent advances via sampling-based Monte Carlo methods make these methods practical for large scale applications without making the common assumptions of Gaussian noise and uniform prior distributions, made by most chemometric methods. This article provides an overview of traditional chemometric methods from a Bayesian view and a tutorial of some recently developed techniques in Bayesian chemometrics, such as Bayesian PCA and Bayesian latent variable regression. New challenges and opportunities for future work are also identified. PMID:17936101

  17. Chemometric methods in data processing of mass spectrometry-based metabolomics: A review.

    PubMed

    Yi, Lunzhao; Dong, Naiping; Yun, Yonghuan; Deng, Baichuan; Ren, Dabing; Liu, Shao; Liang, Yizeng

    2016-03-31

    This review focuses on recent and potential advances in chemometric methods in relation to data processing in metabolomics, especially for data generated from mass spectrometric techniques. Metabolomics is gradually being regarded a valuable and promising biotechnology rather than an ambitious advancement. Herein, we outline significant developments in metabolomics, especially in the combination with modern chemical analysis techniques, and dedicated statistical, and chemometric data analytical strategies. Advanced skills in the preprocessing of raw data, identification of metabolites, variable selection, and modeling are illustrated. We believe that insights from these developments will help narrow the gap between the original dataset and current biological knowledge. We also discuss the limitations and perspectives of extracting information from high-throughput datasets. PMID:26965324

  18. 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.

  19. 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. PMID:25847838

  20. Chemometric analysis of chromatographic fingerprints shows potential of Cyclopia maculata (Andrews) Kies for production of standardized extracts with high xanthone content.

    PubMed

    Schulze, Alexandra E; de Beer, Dalene; de Villiers, André; Manley, Marena; Joubert, Elizabeth

    2014-10-29

    Cyclopia species are used for the production of honeybush tea and food ingredient extracts associated with many health benefits. A species-specific high-performance liquid chromatography (HPLC) method for Cyclopia maculata, developed and validated, allowed quantification of the major compounds in extracts from "unfermented" and fermented C. maculata. Two xanthones were tentatively identified for the first time in a Cyclopia species, whereas an additional four compounds were tentatively identified for the first time in C. maculata. "Fermentation" (oxidation) decreased the content of all compounds, with the exception of vicenin-2. Similarity analysis of the chromatographic fingerprints of unfermented C. maculata aqueous extracts showed extremely low variation (r ≥ 0.97) between samples. Some differences between wild-harvested and cultivated seedling plants were, however, demonstrated using principal component analysis. Quantitative data of selected compounds confirmed the low level of variation, making this Cyclopia species ideal for the production of standardized food ingredient extracts. PMID:25329526

  1. Evaluation of the Influence of Sulfur-Fumigated Paeoniae Radix Alba on the Quality of Si Wu Tang by Chromatographic and Chemometric Analysis

    PubMed Central

    Pei, Ke; Duan, Yu; Qiao, Feng-Xian; Tu, Si-Cong; Liu, Xiao; Wang, Xiao-Li; Song, Xiao-Qing; Fan, Kai-Lei; Cai, Bao-Chang

    2016-01-01

    An accurate and reliable method of high-performance liquid chromatographic fingerprint combining with multi-ingredient determination was developed and validated to evaluate the influence of sulfur-fumigated Paeoniae Radix Alba on the quality and chemical constituents of Si Wu Tang. Multivariate data analysis including hierarchical cluster analysis and principal component analysis, which integrated with high-performance liquid chromatographic fingerprint and multi-ingredient determination, was employed to evaluate Si Wu Tang in a more objective and scientific way. Interestingly, in this paper, a total of 37 and 36 peaks were marked as common peaks in ten batches of Si Wu Tang containing sun-dried Paeoniae Radix Alba and ten batches of Si Wu Tang containing sulfur-fumigated Paeoniae Radix Alba, respectively, which indicated the changed fingerprint profile of Si Wu Tang when containing sulfur-fumigated herb. Furthermore, the results of simultaneous determination for multiple ingredients showed that the contents of albiflorin and paeoniflorin decreased significantly (P < 0.01) and the contents of gallic acid and Z-ligustilide decreased to some extent at the same time when Si Wu Tang contained sulfur-fumigated Paeoniae Radix Alba. Therefore, sulfur-fumigation processing may have great influence on the quality of Chinese herbal prescription. PMID:27034892

  2. 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

  3. 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. PMID:27446633

  4. Characterization of in vitro metabolic profiles of cinitapride obtained with liver microsomes of humans and various mammal species using UHPLC and chemometric methods for data analysis.

    PubMed

    Marquez, Helena; Albertí, Joan; Salvà, Miquel; Saurina, Javier; Sentellas, Sonia

    2012-05-01

    An ultra-high performance liquid chromatographic method has been utilized to obtain metabolic profiles of cinitapride with liver microsomes of humans and various mammal species such as rats, mice, mini pigs, dogs, and monkeys. Metabolites have been generated by incubation of cinitapride in the presence of microsomes using nicotinamide adenine dinucleotide phosphate as a cofactor. Incubation times from 15 to 60 min have been assayed. Cinitapride and its metabolites have been separated by reversed-phase C(18) mode using ammonium formate aqueous solution (pH 6.5) and acetonitrile as the components of the mobile phase. Concentrations of metabolites in the incubated samples have resulted in an excellent source of multivariate data to be used to extract metabolic information. Statistic parameters and principal component analysis have been used to compare the in vitro metabolism of humans with the other species. PMID:22362276

  5. 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. PMID:26944986

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

    PubMed

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

    2010-01-01

    The present study deals with the assessment of Langat River water quality with some chemometrics approaches such as cluster and discriminant analysis coupled with an artificial neural network (ANN). The data used in this study were collected from seven monitoring stations under the river water quality monitoring program by the Department of Environment (DOE) from 1995 to 2002. Twenty three physico-chemical parameters were involved in this analysis. Cluster analysis successfully clustered the Langat River into three major clusters, namely high, moderate and less pollution regions. Discriminant analysis identified seven of the most significant parameters which contribute to the high variation of Langat River water quality, namely dissolved oxygen, biological oxygen demand, pH, ammoniacal nitrogen, chlorine, E. coli, and coliform. Discriminant analysis also plays an important role as an input selection parameter for an ANN of spatial prediction (pollution regions). The ANN showed better prediction performance in discriminating the regional area with an excellent percentage of correct classification compared to discriminant analysis. Multivariate analysis, coupled with ANN, is proposed, which could help in decision making and problem solving in the local environment. PMID:20082024

  7. 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. PMID:26963728

  8. 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.

  9. 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.

  10. 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. PMID:24274289

  11. 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. PMID:23993512

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

    PubMed

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

    2015-05-15

    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 8h, 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 720nm. In order to optimize the differences between excitation and emission wavelengths, four constant differential wavelengths, i.e., 20nm, 40nm, 60nm and 80nm, were tried. Partial least-squares discriminant analysis (PLS-DA) was used to discriminate between pure and adulterated oils. It was found that the 20nm 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. PMID:25748285

  13. Ultra high performance liquid chromatography coupled with triple quadrupole mass spectrometry and chemometric analysis of licorice based on the simultaneous determination of saponins and flavonoids.

    PubMed

    Jiang, Zhenzuo; Wang, Yuefei; Zheng, Yunfeng; Yang, Jing; Zhang, Lei

    2016-08-01

    Licorice is among the most popular herbal medicines and frequently used in traditional medicine, food products, and cosmetics. In China, only Glycyrrhiza uralensis Fisch., Glycyrrhiza inflata Bat. and Glycyrrhiza glabra L. are officially used and are usually processed with honey prior to use. To maintain the quality of commercially available herbal products, a simple, rapid, and reliable ultra high performance liquid chromatography with triple quadrupole mass spectrometry was developed to investigate the major active constituents of commercially available licorice products. Nineteen components were accurately determined, including eight triterpenoid saponins, one triterpene, and ten flavonoids. Subsequently, multivariate statistical analysis methods were employed to further explore and interpret the experimental data. The results indicated that liquiritin apioside may be considered as a candidate index for the quality control of licorice as well as 18β-glycyrrhizic acid and liquiritin. In addition, both 18β-glycyrrhizic acid and licorice-saponin G2 can be used for discrimination between crude and honey-processed licorice. Furthermore, using 18β-glycyrrhizic acid and liquiritin as markers, this work revealed that the quality of licorice products may have declined in recent years. This highlights the need for additional effort focused on good agricultural practice during the processing of licorice. In summary, this study provides a valuable reference for the quality assessment of licorice. PMID:27273927

  14. 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.

  15. 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. PMID:25191974

  16. 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. PMID:22996609

  17. Fruit juice authentication by 1H NMR spectroscopy in combination with different chemometrics tools.

    PubMed

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

    2008-01-01

    To discriminate orange juice from grapefruit juice in a context of fraud prevention, (1)H NMR data were submitted to different treatments to extract informative variables which were then analysed using multivariate techniques. Averaging contiguous data points of the spectrum followed by logarithmic transformation improved the results of the data analysis. Moreover, supervised variable selection methods gave better rates of classification of the juices into the correct groups. Last, independent-component analysis gave better classification results than principal-component analysis. Hence, ICA may be an efficient chemometric tool to detect differences in the (1)H NMR spectra of similar samples, and so may be useful for authentication of foods. PMID:18026939

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

    PubMed

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

    2016-08-01

    Flos Chimonanthi Praecocis (FCP) is one of the popular traditional Chinese medicines, which have been widely used in China. Inconspicuous appearance differences are disadvantageous for identification, and it is difficult to evaluate the quality of FCP using the current methods. In this article, a simple method that combined chemometrics and quantitative analysis was established. The samples were obtained from three typical varieties for fingerprint analysis by high-performance liquid chromatography. Contents of rutin and quercetin were determined, and then a common pattern with 16 characteristic peaks was applied for principal component analysis, similarity analysis, and the hierarchical cluster analysis heatmap (HCA heatmap) to characterize the similarity and differences among samples for identification. Furthermore, seven characteristics peaks with higher loading values were selected for chemometrics analysis after dimensionality reduction to reduce analytical difficulty, and the new common pattern showed the similar identification effects. Overall, combination with chemometrics and quantitative analysis would provide a useful and simple method for quality control of FCP in the future. PMID:27048640

  19. Discrimination of producing area of Chinese Tongshan kaoliang spirit using electronic nose sensing characteristics combined with the chemometrics methods.

    PubMed

    Peng, Qi; Tian, Rungang; Chen, Feiran; Li, Bobin; Gao, Hegang

    2015-07-01

    In the ancient history of the Yue Nation, the Chinese Tongshan kaoliang spirit (CTKS) has been one of the most popular liquor in the last 2,500 years. The most common fraudulent practice for the commercialization of CTKS is to produce and sell adulterated spirit from different geographical origins. In this study, the use of GC-flash electronic nose (EN) technique combined with chemometrics analysis has proven to provide a rapid tool for the discrimination of CTKS from different geographical origins. The discriminant models were developed by using principal component analysis (PCA), and discriminant factor analysis (DFA). In addition, the volatile organic matters of CTKS were also investigated to find out the difference between samples from varied origins and adulterated liquor. The results demonstrated that the EN technique combined with chemometrics methods could be used to fingerprinting techniques to protect the fame of the prestigious CTKS and to enable its authentication. PMID:25704715

  20. 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. PMID:23644688

  1. [Studies on Cancer Diagnosis by Using Spectroscopy Combined with Chemometrics].

    PubMed

    Zhang, Zhuo-yong

    2015-09-01

    Studies on cancer diagnosis using various spectroscopic methods combined with chemometrics are briefly reviewed. Elemental contents in serum samples were determined by inductively coupled plasma atomic emission spectroscopy (ICP-AES), bidirectional associative memory (BAM) networks were used to establish diagnosis models for the relationships between elemental contents and lung cancer, liver cancer, and stomach cancer, respectively. Near infrared spectroscopy (NIRS) is a non-destructive detection technology. Near infrared spectra of endometrial carcinoma samples were determined and spectral features were extracted by chemoometric methods, a fuzzy rule-based expert system (FuRES) was used for establishing diagnosis model, satisfactory results were obtained. We also proposed a novel variable selection method based on particle swarm optimization (PSO) for near infrared spectra of endometrial carcinoma samples. Spectra with optimized variable were then modeled by support victor machine (SVM). Terahertz technology is an emerging technology for non-destructive detection, which has some unique characteristics. Terahertz time domain spectroscopy (THz-TDS) was used for cervical carcinoma measurement. Absorption coefficients were calculated from the measured time domain spectra and then processed with derivative, orthogonal signal correction (PC-OSC) to reduce interference components, and then fuzzy rule-based expert system (FuRES), fuzzy optimal associative memory (FOAM), support victor machine (SVM), and partial least squares discriminant analysis (PLS-DA) were used for diagnosis model establishment. The above results provide useful information for cancer occurring and development, and provide novel approaches for early stage diagnosis of various cancers. PMID:26669135

  2. 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. PMID:25476739

  3. 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. PMID:25679985

  4. 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

  5. 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. PMID:26890416

  6. Discrimination of Breast Cancer from Normal Tissue with Raman Spectroscopy and Chemometrics

    NASA Astrophysics Data System (ADS)

    Li, Q.-B.; Wang, W.; Liu, Ch.-H.; Zhang, G.-J.

    2015-07-01

    Conventional Raman spectra of normal and cancerous breast tissues were acquired at an excitation wavelength of 785 nm and subjected to a discrimination analysis. First the spectra were pretreated with wavelet transform and polynomial fitting; next, cancerous tissue was identified by applying an adaptive local hyperplane K-nearest neighbor (ALHK) method to the pretreated spectra. The best discrimination accuracy of the ALHK method was 93.2%. In summary, normal and cancerous breast tissue were accurately distinguished by a miniature laser Raman spectrometer and the chemometrics method (ALHK), which might prove to be a portable and accessible diagnostic system.

  7. 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. PMID:27282749

  8. ATR-FTIR spectroscopy: a chemometric approach for studying the lipid organisation of the stratum corneum.

    PubMed

    Laugel, C; Yagoubi, N; Baillet, A

    2005-05-01

    The barrier function of skin resides in the lipid components of the stratum corneum, particularly their spatial organisation. FTIR spectroscopy has already been used as a relevant tool to study this lipid organisation: IR vibration band shifts have been attributed to the variations in lipid organisation induced by temperature. Our study included a stratum corneum model, composed of the three main lipids: palmitic acid as an example of fatty acids, cholesterol and ceramide III as an example of ceramide. Different films with various ratios of these lipids were studied. In our analytical strategy, the interest of using a chemometric analysis of global data obtained from ATR-FTIR spectra to highlight the main interactions involved in the molecular organisation of lipids has been demonstrated. Two kinds of interaction between the three main lipids have been shown: a non polar interaction between the long hydrocarbon chains and a polar interaction as the hydrogen bonding between polar functional groups. By varying the lipid ratio, we have shown first that the relative importance of each interaction was modified, second, that the induced modification of organisation can be detected by chemometric analysis of the ATR-FTIR spectra. The role of each kind of lipid in the organisation has been discussed. In conclusion, associating the ATR-FTIR with chemometric treatment is a promising tool: firstly, to understand the consequence of lipid relative compositions on the structural organisation of the stratum corneum, secondly, to show the relationship between lipid organisation and percutaneous penetration data. Indeed, this methodology will be transposed to in vivo studies with IR measurements through a probe. PMID:15854625

  9. Chemometrics and the identification of counterfeit medicines-A review.

    PubMed

    Krakowska, B; Custers, D; Deconinck, E; Daszykowski, M

    2016-08-01

    This review article provides readers with a number of actual case studies dealing with verifying the authenticity of selected medicines supported by different chemometric approaches. In particular, a general data processing workflow is discussed with the major emphasis on the most frequently selected instrumental techniques to characterize drug samples and the chemometric methods being used to explore and/or model the analytical data. However, further discussion is limited to a situation in which the collected data describes two groups of drug samples - authentic ones and counterfeits. PMID:27133184

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  11. Rapid authentication of starch adulterations in ultrafine granular powder of Shanyao by near-infrared spectroscopy coupled with chemometric methods.

    PubMed

    Ma, Hong-Liang; Wang, Ji-Wen; Chen, Yong-Jun; Cheng, Jin-le; Lai, Zhi-Tian

    2017-01-15

    Near-infrared reflectance (NIR) spectroscopy combined with chemometric techniques was developed for classification and quantification of cheaper starches (corn and wheat starch) in ultrafine granular powder of Shanyao (UGPSY). By performing orthogonal partial least squares discrimination analysis (OPLS-DA), NIR could efficiently distinguish among authentic UGPSY and UGPSY adulterated with cornstarch and wheat starch. In addition, the starch content in adulterated UGPSY was determined by NIR coupled with an appropriate multivariate calibration method. Partial least squares (PLS), interval PLS (iPLS) and synergy interval PLS (siPLS) algorithms were performed comparatively to calibrate the regression model. Experimental results showed that the performance of the siPLS model is the best compared to PLS and iPLS. These results show that the combination of NIR spectroscopy and chemometric methods offers a simple, fast and reliable method for the classification and quantification of the ultrafine granular powder of the herb. PMID:27542456

  12. TLC Profiles of Selected Cirsium Species with Chemometrics in Construction of Their Fingerprints.

    PubMed

    Hawrył, Anna; Ziobro, Agata; Świeboda, Ryszard; Hawrył, Mirosław; Waksmundzka-Hajnos, Monika

    2016-08-01

    The dried aerial parts of 12 plants of Cirsium species were extracted with the Soxhlet apparatus using dichloromethane and methanol as solvents. Next, the extracts were separated by TLC methods to obtain the fingerprint chromatograms. The analysis was performed on silica gel or RP-18 layers as stationary phases using the following eluents: ethyl acetate/formic acid/acetic acid/water (12/1.5/1.5/4; v/v) for silica gel, and 5% (v/v) aqueous solution of formic acid/methanol (70/30; v/v) for the first development and the same system in the proportion of 50/50 (v/v) for the second development for RP-18. The double development was applied in the case of RP-18 plates. The analysis was performed for all Cirsium methanolic extracts and five selected standards (naringin, apigenin, rutin, caffeic acid and chlorogenic acid). The results were analyzed using chemometrics. The comparison of individual Cirsium species and the identification of unknown species were performed using the similarity indices (Pearson's correlation coefficient, determination coefficient and congruence coefficient), distance indices (Euclidean distance, Manhattan distance and Chebyshev's distance) and Multi-Scale Structural SIMilarity. Based on chemometric analysis, the first extract of the widely grown species is identified as Cirsium arvense and the second one as Cirsium rivulare. PMID:27130878

  13. 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. PMID:24054684

  14. 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.

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

    PubMed

    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

  16. Evaluation of antibacterial effect and mode of Coptidis rhizoma by microcalorimetry coupled with chemometric techniques.

    PubMed

    Kong, Weijun; Wang, Jiabo; Xiao, Xiaohe; Chen, Shilin; Yang, Meihua

    2012-01-01

    In this study, the antibacterial effect and mode of Coptidis rhizoma on Escherichia coli was evaluated by microcalorimetry coupled with chemometric techniques. Using an isothermal microcalorimeter, the metabolic profiles of E. coli growth at 37 °C affected by 15 batches of C. rhizoma were measured. Through principal component analysis (PCA) on nine quantitative thermo-kinetic parameters obtained from the metabolic power-time profiles of E. coli, the antibacterial effects of C. rhizoma from various sources could be easily evaluated by analyzing the change of the two main thermo-kinetic parameters, growth rate constant k(2) and maximum heat-output power P(2)(m), in the second exponential phase of E. coli growth. Then, hierarchical clustering analysis (HCA) was carried out on the two parameters to distinguish those C. rhizoma samples in respect to their antibacterial effects. Clear results were obtained to show that all 15 C. rhizoma samples with different antibacterial effects could be successfully grouped in accordance with their origins. Ranked in decreasing order, the antibacterial mode of C. rhizoma samples that were from Sichuan province had the strongest antibacterial effects, followed by samples from Chongqing city and Hubei province. Our results revealed that the developed microcalorimetry with chemometric techniques had the potential perspective for evaluating the effect and mode of Coptidis rhizoma and other Chinese materia medicas. PMID:22059231

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

    PubMed

    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

  18. 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

  19. 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. PMID:27130135

  20. Chemometric modeling of organic contaminant sources in surface waters of a mediterranean river basin.

    PubMed

    García-Reiriz, Alejandro G; Olivieri, Alejandro C; Teixidó, Elisabeth; Ginebreda, Antoni; Tauler, Romà

    2014-01-01

    Chemometric methods are applied to the analysis and interpretation of large multivariate datasets obtained in environmental monitoring studies. Concentrations of multiple organic compounds were measured in river samples taken from several sampling sites, at various geographical locations, during a number of campaigns and/or sampling time periods. Samples were collected and analyzed as part of an extensive multi-annual monitoring program from a mediterranean river basin (in Catalonia, at the northeast of Spain) by the Water Quality Regional Agency. Due to the great amount of multivariate data stored in environmental databases and to their complexity, chemometric modeling methods such as Principal Component Analysis (PCA) and Multivariate Curve Resolution with Alternating Least-Squares (MCR-ALS) coupled with appropriate mapping representations are proposed for the evaluation of the environmental quality of the studied rivers. Results achieved in this study are intended to be a contribution to water quality assessment and evaluation of contamination of surface waters in river basins, and to support public policies of environmental control and management of the regions under study. PMID:24276592

  1. 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.

  2. 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

  3. 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%).

  4. 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. PMID:27211665

  5. 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. PMID:20645279

  6. 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%). PMID:26774813

  7. 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.

  8. 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

    2013-11-01

    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). PMID:24111743

  9. 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

  10. 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. PMID:25159392

  11. Chemical fingerprinting of Gardenia jasminoides Ellis by HPLC-DAD-ESI-MS combined with chemometrics methods.

    PubMed

    Han, Yan; Wen, Jun; Zhou, Tingting; Fan, Guorong

    2015-12-01

    A fingerprint analysis method has been developed for characterization and discrimination of Gardenia jasminoides Ellis from different areas. The chemometrics methods including similarity evaluation, principal components analysis (PCA) and hierarchical clustering analysis (HCA) were introduced to identify more useful chemical markers for improving the quality control standard of dried ripe fruits of G. jasminoides Ellis. Then the selected chemical markers were analyzed by high performance liquid chromatography-diode array detection-electrospray ionization mass spectrometry (HPLC-DAD-ESI-MS) qualitatively and quantitatively. 23 characteristic peaks were assigned while 19 peaks of them were identified by comparing retention times, UV and MS spectra with authentic compounds or literature data. Moreover, 14 of them were determined quantitatively which could effectively evaluate the quality of G. jasminoides Ellis. This study was expected to provide comprehensive information for the quality evaluation of G. jasminoides Ellis, which would be a valuable reference for further study and development of this herb and related medicinal products. PMID:26041243

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

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

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

  13. Identification and spatial patterns of coastal water pollution sources based on GIS and chemometric approach.

    PubMed

    Zhou, Feng; Guo, Huai-Cheng; Liu, Yong; Hao, Ze-Jia

    2007-01-01

    Comprehensive and joint applications of GIS and chemometric approach were applied in identification and spatial patterns of coastal water pollution sources with a large data set (5 years (2000-2004), 17 parameters) obtained through coastal water monitoring of Southern Water Control Zone in Hong Kong. According to cluster analysis the pollution degree was significantly different between September-next May (the 1st period) and June-August (the 2nd period). Based on these results, four potential pollution sources, such as organic/eutrophication pollution, natural pollution, mineral/anthropic pollution and fecal pollution were identified by factor analysis/principal component analysis. Then the factor scores of each monitoring site were analyzed using inverse distance weighting method, and the results indicated degree of the influence by various potential pollution sources differed among the monitoring sites. This study indicated that hybrid approach was useful and effective for identification of coastal water pollution source and spatial patterns. PMID:17966867

  14. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

    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.

  16. 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. PMID:24909771

  17. 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.

  18. 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.

  19. 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. PMID:26471531

  20. A new simplex chemometric approach to identify olive oil blends with potentially high traceability.

    PubMed

    Semmar, N; Laroussi-Mezghani, S; Grati-Kamoun, N; Hammami, M; Artaud, J

    2016-10-01

    Olive oil blends (OOBs) are complex matrices combining different cultivars at variable proportions. Although qualitative determinations of OOBs have been subjected to several chemometric works, quantitative evaluations of their contents remain poorly developed because of traceability difficulties concerning co-occurring cultivars. Around this question, we recently published an original simplex approach helping to develop predictive models of the proportions of co-occurring cultivars from chemical profiles of resulting blends (Semmar & Artaud, 2015). Beyond predictive model construction and validation, this paper presents an extension based on prediction errors' analysis to statistically define the blends with the highest predictability among all the possible ones that can be made by mixing cultivars at different proportions. This provides an interesting way to identify a priori labeled commercial products with potentially high traceability taking into account the natural chemical variability of different constitutive cultivars. PMID:27132835

  1. 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. PMID:24837923

  2. Discrimination of Gentiana rigescens from Different Origins by Fourier Transform Infrared Spectroscopy Combined with Chemometric Methods.

    PubMed

    Zhao, Yanli; Zhang, Ji; Jin, Hang; Zhang, Jinyu; Shen, Tao; Wang, Yuanzhong

    2015-01-01

    Gentiana rigescens ("Dian Longdan" in Chinese) medicinal plant is usually used for its activities of liver protection, cholagogic, anti-inflammatory, anti-fungal, anti-hyperthyroidism, anti-hypertension, hyperglycemia, and relieving spasm and pain. In this study, methods for the discrimination of different geographical origins of G. rigescens by FTIR spectroscopy in hyphenation with chemometric methods were developed. Different pretreatments including standard normal variate, multiplicative scatter correction, first or second derivative, Savitzky-Golay filter, and Norris derivative filter were applied on the spectra to optimize the calibrations. According to spectrum SD, spectrum ranges (3559-2709 and 2026-756 cm(-1)) were selected, and principal component analysis-Mahalanobis distance (PCA-MD) model was built [the cumulative contribution rate of the first 10 principal components, determination coefficient (R2), root-mean-square error of calibration (RMSEC), and root-mean-square error of prediction (RMSEP), and prediction accuracy were 96.4%, 98.6%, 0.5031, 0.7758, and 96.23%, respectively]. The spectral regions (3791-3442, 3043-2765, and 2013-646 cm(-1)) were selected by using the variable importance in projection, and partial least squares discriminant analysis (PLS-DA) model was built (the cumulative contribution rate of the first 10 principal components, R2, RMSEC, RMSEP, and prediction accuracy were 91.3%, 92.0%, 0.1171, 0.1806, and 100%, respectively). This research showed that FTIR spectroscopy in combination with chemometrics methods (PCA-MD and PLS-DA) was suitable for the discrimination of different geographical origins of G. rigescens. Furthermore, it was found that PLS-DA provided better results than PCA-MD. PMID:25857874

  3. 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. PMID:15109878

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

    PubMed Central

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

    2013-01-01

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

  5. 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

  6. Effect of Processing on the Traditional Chinese Herbal Medicine Flos Lonicerae: An NMR-based Chemometric Approach.

    PubMed

    Zhao, Jianping; Wang, Mei; Avula, Bharathi; Zhong, Lingyun; Song, Zhonghua; Xu, Qiongming; Li, Shunxiang; Khan, Ikhlas A

    2015-06-01

    The processing of medicinal materials, known as Pao Zhi in traditional Chinese medicine, is a unique part of traditional Chinese medicine and has been widely used for the preparation of Chinese materia medica. It is believed that processing can alter the properties and functions of remedies, increase medical potency, and reduce toxicity and side effects. Both processed and unprocessed Flos Lonicerae (flowers of Lonicera japonica) are important drug ingredients in traditional Chinese medicine. To gain insights on the effect of processing factors (heating temperature and duration) on the change of chemical composition, nuclear magnetic resonance combined with chemometric analysis was applied to investigate the processing of F. Lonicerae. Nuclear magnetic resonance spectral data were analyzed by means of a heat map and principal components analysis. The results indicated that the composition changed significantly, particularly when processing at the higher temperature (210 °C). Five chemical components, viz. 3,4-dicaffeoylquinic acid, 4,5-dicaffeoylquinic acid, 3,5-dicaffeoylquinic acid, chlorogenic acid, and myo-inositol, whose concentration changed significantly during the processing, were isolated and identified. The patterns for the concentration change observed from nuclear magnetic resonance analysis during the processing were confirmed and quantitatively determined by ultrahigh-performance liquid chromatography analysis. The study demonstrated that a nuclear magnetic resonance-based chemometric approach could be a promising tool for investigation of the processing of herbal medicines in traditional Chinese medicine. PMID:26039268

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

    PubMed

    Kumar, Raj; Kumar, Vinay; Sharma, Vishal

    2017-01-01

    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 4000cm(-1) wavenumber range. The qualitative feature and Chemometrics of the obtained spectral data are used for characterization and discrimination. Characterization is achieved by matching the peaks with standards of cellulose and inorganic fillers, a usual constituents of paper. Three different regions of IR, i.e. 400-2000cm(-1), 2000-4000cm(-1) and 400-4000cm(-1) were selected for differentiation by Chemometrics analysis. The discrimination is achieved on the basis of three principal components, i.e. PC 1, PC 2 and PC 3. It is observed that maximum discrimination was procured in the wave number range of i.e. 2000-4000cm(-1). Discriminating power was calculated on the basis of qualitative features as well, and it is found that the discrimination of paper samples was better achieved by Chemometrics analysis rather than qualitative features. The discriminating power by Chemometrics is 99.64% and which is larger as ever achieved by any group for present number of samples. The present result confirms that this study will be highly useful in forensic document examination work in the legal cases, where the authenticity of the document is challenged. The results are completely analytical and, therefore, overcome the problem encounter in traditional routine light/radiation scanning methods which are still in practice by various questioned document laboratories. PMID:27394012

  8. 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. PMID:21381653

  9. Application of chemometrics in understanding the spatial distribution of human pharmaceuticals in surface water.

    PubMed

    Al-Odaini, Najat Ahmed; Zakaria, Mohamad Pauzi; Zali, Muniirah Abdul; Juahir, Hafizan; Yaziz, Mohamad Ismail; Surif, Salmijah

    2012-11-01

    The growing interest in the environmental occurrence of veterinary and human pharmaceuticals is essentially due to their possible health implications to humans and ecosystem. This study assesses the occurrence of human pharmaceuticals in a Malaysian tropical aquatic environment taking a chemometric approach using cluster analysis, discriminant analysis and principal component analysis. Water samples were collected from seven sampling stations along the heavily populated Langat River basin on the west coast of peninsular Malaysia and its main tributaries. Water samples were extracted using solid-phase extraction and analyzed using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) for 18 pharmaceuticals and one metabolite, which cover a range of six therapeutic classes widely consumed in Malaysia. Cluster analysis was applied to group both pharmaceutical pollutants and sampling stations. Cluster analysis successfully clustered sampling stations and pollutants into three major clusters. Discriminant analysis was applied to identify those pollutants which had a significant impact in the definition of clusters. Finally, principal component analysis using a three-component model determined the constitution and data variance explained by each of the three main principal components. PMID:22193630

  10. 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

  11. 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.

  12. 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. PMID:26390501

  13. Study on dietary fibre by Fourier transform-infrared spectroscopy and chemometric methods.

    PubMed

    Chylińska, Monika; Szymańska-Chargot, Monika; Kruk, Beata; Zdunek, Artur

    2016-04-01

    Fresh fruit is an important part of the diet of people all over the world as a significant source of water, vitamins and natural sugars. Nowadays it is also one of the main sources of dietary fibre. In fruit the dietary fibre is simply cell wall consisting essentially of polysaccharides. The aim of present study was to predict the contents of pectins, cellulose and hemicelluloses by partial least squares regression (PLS) analysis on the basis of Fourier transform-infrared (FT-IR) spectra of fruit cell wall residue. The second purpose was to analyse the composition of dietary fibre from fruit based on FT-IR spectral information in combination with chemometric methods (principle components analysis (PCA) and hierarchical cluster analysis (HCA)). Additionally the contents of polysaccharides in studied fruits were determined by analytical methods. It has been shown that the analysis of infrared spectra and the use of multivariate statistical methods can be useful for studying the composition of dietary fibre. PMID:26593472

  14. 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)

  15. STATISTICAL SAMPLING AND DATA ANALYSIS

    EPA Science Inventory

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

  16. 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. PMID:26296251

  17. 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

  18. Nondestructive determination of compound amoxicillin powder by NIR spectroscopy with the aid of chemometrics

    NASA Astrophysics Data System (ADS)

    Qu, Nan; Zhu, Mingchao; Mi, Hong; Dou, Ying; Ren, Yulin

    2008-10-01

    Near-infrared (NIR) spectroscopy, in combination with chemometrics, enables nondestructive analysis of solid samples without time-consuming sample preparation methods. A new method for the nondestructive determination of compound amoxicillin powder drug via NIR spectroscopy combined with an improved neural network model based on principal component analysis (PCA) and radial basis function (RBF) neural networks is investigated. The PCA technique is applied to extraction relevant features from lots of spectra data in order to reduce the input variables of the RBF neural networks. Various optimum principal component analysis-radial basis function (PCA-RBF) network models based on conventional spectra and preprocessing spectra (standard normal variate (SNV) and multiplicative scatter correction (MSC)) have been established and compared. Principal component regression (PCR) and partial least squares (PLS) multivariate calibrations are also used, which are compared with PCA-RBF neural networks. Experiment results show that the proposed PCA-RBF method is more efficient than PCR and PLS multivariate calibrations. And the PCA-RBF approach with SNV preprocessing spectra is found to provide the best performance.

  19. 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. PMID:27596419

  20. Quality control of Gardeniae Fructus by HPLC-PDA fingerprint coupled with chemometric methods.

    PubMed

    Yin, Fangzhou; Wu, Xiaoyan; Li, Lin; Chen, Yan; Lu, Tuling; Li, Weidong; Cai, Baochang; Yin, Wu

    2015-01-01

    The ripe fruits of Gardenia jasminoides Ellis have been used as traditional Chinese medicine to treat diseases for a long history. Lines of evidence demonstrate that multiple active constituents are responsible for the therapeutic effects of this herbal medicine. However, effective methods for quality control of this herbal medicine are still lacking. In this study, a high-performance liquid chromatography (HPLC) fingerprint analysis was performed on a SinoChrom ODS-BP C18 column (4.6 mm × 250 mm, 5 μm) at 30°C with mobile phase of aqueous solution with 0.1% formic acid and acetonitrile. On the basis of the chromatographic data from 32 batches samples, the HPLC fingerprint pattern containing 27 common peaks was obtained. Among these common peaks, seven peaks were identified by the electrospray ionization-mass spectrometry as geniposidic acid, genipin-1-β-gentiobioside, chlorogenic acid, geniposide, rutin, crocin-1 and crocin-2 and the contents of these seven compounds were simultaneously determined. Finally, chemometric methods including hierarchical clustering analysis and principal component analysis were successfully applied to differentiate the samples from six producing regions. In sum, the data, as described in this study, offer valuable information for the quality control and proper use of Gardeniae Fructus. PMID:26071608

  1. 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.

  2. 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

    2016-02-01

    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. PMID:26694647

  3. 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. PMID:25366312

  4. 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. PMID:26807674

  5. Chemical authentication of extra virgin olive oil varieties by supervised chemometric procedures.

    PubMed

    Bucci, Remo; Magrí, Andrea D; Magrí, Antonio L; Marini, Domenico; Marini, Federico

    2002-01-30

    This work has focused on discriminating extra virgin olive oils from Sabina (Lazio, Italy) by olive fruit variety (cultivar). A set of oils from five of the most widespread cultivars (Carboncella, Frantoio, Leccino, Moraiolo, and Pendolino) in this geographical area was analyzed for chemical composition using only the Official Analytical Methods, recognized for the quality control and commercial classification of this product. The obtained data set was converted into a computer-compatible format, and principal component analysis (PCA) and a method based on the Fisher F ratio were used to reduce the number of variables without a significant loss of chemical information. Then, to differentiate these samples, two supervised chemometric procedures were applied to process the experimental data: linear discriminant analysis (LDA) and artificial neural network (ANN) using the back-propagation algorithm. It was found that both of these techniques were able to generalize and correctly predict all of the samples in the test set. However, these results were obtained using 10 variables for LDA and 6 (the major fatty acid percentages, determined by a single gas chromatogram) for ANN, which, in this case, appears to provide a better prediction ability and a simpler chemical analysis. Finally, it is pointed out that, to achieve the correct authentication of all samples, the selected training set must be representative of the whole data set. PMID:11804505

  6. A chemometric interpopulation study of the essential oils of Cistus creticus L. growing in Crete (Greece).

    PubMed

    Demetzos, Costas; Anastasaki, Thalia; Perdetzoglou, Dimitrios

    2002-01-01

    The chemical composition of the essential oils of twenty-five populations of Cistus creticus subsp. creticus L. from the island of Crete (Greece) and their interpopulation variability were analysed in detail by GC-MS. 142 compounds were identified representing an average of 56.8-89.8% of the oil composition. The components are represented here by homologous series of monoterpenes, oxygenated monoterpenes, sesquiterpenes, oxygenated sesquiterpenes, diterpenes, labdane diterpenes, aldehydes, alkanes, esters, fatty acids, ketones, and others. Labdane diterpenes were detected and identified in the essential oils and have been found in high percentage composition. The results from the chemical analysis of the essential oils were submitted to chemometric cluster analysis in order to detect some pattern distribution and to identify which constituents can differentiate the groups of individuals. Two main chemotypes (clusters) were well differentiated; the first deals with eight populations of West Crete and the second with the rest of the populations. Cluster analysis based on labdane type diterpenes patterns, proved to be the best chemotype for the examined populations among the other chemical groups. PMID:11926549

  7. 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

    2015-01-01

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

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

    PubMed

    Ortea, Ignacio; Gallardo, José M

    2015-03-01

    Three factors defining the traceability of a food product are production method (wild or farmed), geographical origin and biological species, which have to be checked and guaranteed, not only in order to avoid mislabelling and commercial fraud, but also to address food safety issues and to comply with legal regulations. The aim of this study was to determine whether these three factors could be differentiated in shrimps using stable isotope ratio analysis of carbon and nitrogen and/or multi-element composition. Different multivariate statistics methods were applied to different data subsets in order to evaluate their performance in terms of classification or predictive ability. Although the success rates varied depending on the dataset used, the combination of both techniques allowed the correct classification of 100% of the samples according to their actual origin and method of production, and 93.5% according to biological species. Even though further studies including a larger number of samples in each group are needed in order to validate these findings, we can conclude that these methodologies should be considered for studies regarding seafood product authenticity. PMID:25306329

  9. 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

  10. 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. PMID:23200507

  11. 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.

  12. Rapid discrimination of Chinese red ginseng and Korean ginseng using an electronic nose coupled with chemometrics.

    PubMed

    Li, Shan; Li, Xiang-ri; Wang, Gang-li; Nie, Li-xing; Yang, Yao-jun; Wu, Hao-zhong; Wei, Feng; Zhang, Ji; Tian, Jin-gai; Lin, Rui-chao

    2012-11-01

    Red ginseng is a precious and widely used traditional Chinese medicine. At present, Chinese red ginseng and Korean ginseng are both commonly found on the market. To rapidly and nondestructively discriminate between Chinese red ginseng and Korean ginseng, an electronic nose coupled with chemometrics was developed. Different red ginseng samples, including Chinese red ginseng (n=30) and Korean ginseng (South Korean red ginseng and North Korean red ginseng n=26), were collected. The metal oxide sensors on an electronic nose were used to measure the red ginseng samples. Multivariate statistical analyses, including principal component analysis (PCA), discriminant factorial analysis (DFA) and soft independent modeling of class analogy (SIMCA), were employed. All of the samples were analyzed by PCA. Most of the samples were used to set up DFA and SIMCA models, and then the remaining samples (Nos. 9, 10, 17, 18, 29, 30, 34, 43, 44, 50, and 51) were projected onto the DFA and SIMCA models in the form of black dots to validate the models. The results indicated that Chinese red ginseng and Korean ginseng were successfully discriminated using the electronic nose coupled with PCA, DFA and SIMCA. The checking scores of the DFA and SIMCA models were 100. The samples projected onto the DFA and SIMCA models were all correctly discriminated. The DFA and SIMCA models were robust. Electronic nose technology is a rapid, accurate, sensitive and nondestructive method to discriminate between Chinese red ginseng and Korean ginseng. PMID:22742921

  13. 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. PMID:22389175

  14. 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. PMID:25872423

  15. 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.

  16. 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.

  17. 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

  18. 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. PMID:26174663

  19. Early detection of germinated wheat grains using terahertz image and chemometrics.

    PubMed

    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

  20. Mebendazole crystal forms in tablet formulations. An ATR-FTIR/chemometrics approach to polymorph assignment.

    PubMed

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

    2016-04-15

    Structural polymorphism of active pharmaceutical ingredients (API) is a relevant concern for the modern pharmaceutical industry, since different polymorphic forms may display dissimilar properties, critically affecting the performance of the corresponding drug products. Mebendazole (MEB) is a widely used broad spectrum anthelmintic drug of the benzimidazole class, which exhibits structural polymorphism (Forms A-C). Form C, which displays the best pharmaceutical profile, is the recommended one for clinical use. The polymorphs of MEB were prepared and characterized by spectroscopic, calorimetric and microscopic means. The polymorphs were employed to develop a suitable chemometrics-assisted sample display model based on the first two principal components of their ATR-FTIR spectra in the 4000-600 cm(-1) region. The model was internally and externally validated employing the leave-one-out procedure and an external validation set, respectively. Its suitability for revealing the polymorphic identity of MEB in tablets was successfully assessed analyzing commercial tablets under different physical forms (whole, powdered, dried, sieved and aged). It was concluded that the ATR-FTIR/PCA (principal component analysis) association is a fast, efficient and non-destructive technique for assigning the solid-state forms of MEB in its drug products, with minimum sample pre-treatment. PMID:26874854

  1. 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

  2. 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. PMID:24856323

  3. 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.

  4. Fast determination of beef quality parameters with time-domain nuclear magnetic resonance spectroscopy and chemometrics.

    PubMed

    Pereira, Fabíola Manhas Verbi; Bertelli Pflanzer, Sérgio; Gomig, Thaísa; Lugnani Gomes, Carolina; de Felício, Pedro Eduardo; Colnago, Luiz Alberto

    2013-04-15

    The noteworthy of this study is to predict seven quality parameters for beef samples using time-domain nuclear magnetic resonance (TD-NMR) relaxometry data and multivariate models. Samples from 61 Bonsmara heifers were separated into five groups based on genetic (breeding composition) and feed system (grain and grass feed). Seven sample parameters were analyzed by reference methods; among them, three sensorial parameters, flavor, juiciness and tenderness and four physicochemical parameters, cooking loss, fat and moisture content and instrumental tenderness using Warner Bratzler shear force (WBSF). The raw beef samples of the same animals were analyzed by TD-NMR relaxometry using Carr-Purcell-Meiboom-Gill (CPMG) and Continuous Wave-Free Precession (CWFP) sequences. Regression models computed by partial least squares (PLS) chemometric technique using CPMG and CWFP data and the results of the classical analysis were constructed. The results allowed for the prediction of aforementioned seven properties. The predictive ability of the method was evaluated using the root mean square error (RMSE) for the calibration (RMSEC) and validation (RMSEP) data sets. The reference and predicted values showed no significant differences at a 95% confidence level. PMID:23601874

  5. 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. PMID:23087914

  6. 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.

  7. Chemometrical exploration of the wet precipitation chemistry from the Austrian Monitoring Network (1988-1999).

    PubMed

    Stanimirova, I; Daszykowski, M; Massart, D L; Questier, F; Simeonov, V; Puxbaum, H

    2005-03-01

    The present paper deals with the application of different chemometric methods to an environmental data set derived from the monitoring of wet precipitation in Austria (1988-1999). These methods are: principal component analysis (PCA); projection pursuit (PP); density-based spatial clustering of application with noise (DBSCAN); ordering points to identify the clustering structures (OPTICS); self-organizing maps (SOM), also called the Kohonen network; and the neural gas (NG) network. The aim of the study is to introduce some new approaches into environmetrics and to compare their usefulness with already existing techniques for the classification and interpretation of environmental data. The density-based approaches give information about the occurrence of natural clusters in the studied data set, which, however, do not occur in the case presented here; information about high-density zones (very similar samples) and extreme samples is also obtained. The partitioning techniques (clustering, but also neural gas and Kohonen networks) offer an opportunity to classify the objects of interest into several defined groups, the patterns of ionic concentration of which can be studied in detail. The visual aids, such as the color map and the Kohonen map, for each site are very helpful in understanding the relationships between samples and between samples and variables. All methods, and in particular projection pursuit, give information about samples with extreme characteristics. PMID:15737459

  8. 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. PMID:27260451

  9. 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. PMID:22940340

  10. 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. PMID:26896150

  11. 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. PMID:25747300

  12. 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.

  13. Determination of acetamiprid partial-intercalative binding to DNA by use of spectroscopic, chemometrics, and molecular docking techniques.

    PubMed

    Zhang, Yue; Zhang, Guowen; Zhou, Xiaoyue; Li, Yu

    2013-11-01

    Acetamiprid (ACT) is an insecticide widely used for controlling a variety of insect pests. The binding mode associated with calf thymus DNA (ctDNA) upon interaction with ACT was determined using spectroscopic, chemometrics, and molecular docking techniques to clarify the interaction mechanism at the molecular level. Fluorescence titration suggested that the fluorescence quenching of ACT by ctDNA is a static procedure. The binding constants between ACT and ctDNA at different temperatures were calculated to be of the order 10(3)-10(4) L mol(-1). The positive values of enthalpy and entropy change suggested that the binding process is primarily driven by hydrophobic interactions. Multivariate curve resolution-alternating least squares (MCR-ALS), a chemometrics approach, was used to resolve the expanded UV-visible spectral data matrix. The concentration profiles and the spectra for the three reaction components (ACT, ctDNA, and ACT-ctDNA complex) of the system, which formed a highly overlapping composite response, were then successfully obtained and used to evaluate the progress of ACT interacting with ctDNA. The results of the single-stranded ctDNA and iodide quenching experiments, ctDNA-melting investigations, and viscosity measurements indicated that ACT binds to ctDNA by means of a partial intercalation. Molecular docking studies showed that the specific binding site is mainly located between the ACT and G-C base pairs of ctDNA. This docking prediction was confirmed by use of Fourier-transform infrared (FT-IR) spectral analysis. Results from circular dichroism (CD) spectroscopy revealed that ACT induced a conformational change from the B-ctDNA form to the A-ctDNA form. PMID:23975088

  14. 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

  15. 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

  16. 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. PMID:17611742

  17. Holistic Evaluation of Quality Consistency of Ixeris sonchifolia (Bunge) Hance Injectables by Quantitative Fingerprinting in Combination with Antioxidant Activity and Chemometric Methods.

    PubMed

    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

  18. 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…

  19. 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),…

  20. Microcalorimetry coupled with chemometric techniques for toxicity evaluation of Radix Aconiti Lateralis Preparata (Fuzi) and its processed products on Escherichia coli.

    PubMed

    Zhao, Yanling; Wang, Jiabo; Sun, Xiaojiao; Jia, Lei; Li, Jianyu; Shan, Limei; Li, Ruisheng; Liu, Honghong; Wang, Ruilin; Song, Xueai; Li, Yonggang; Xiao, Xiaohe

    2014-01-01

    As a widely used traditional Chinese medicine (TCM), Radix Aconiti Lateralis Preparata (Fuzi) is not only efficacious but also poisonous. Its toxicity and processed products should be taken into account and effectively evaluated. In this study, a non-invasive and non-destructive microcalorimetric method was employed to evaluate and compare the toxicity of Fuzi and its three processed products including Yanfupian, Heifupian, and Danfupian on Escherichia coli (E. coli). Some important metabolic information, such as the power-time curves and some quantitative thermokinetic parameters including growth rate constant k, heat output power P, inhibitory ratio I, and half inhibitory concentration IC50, of E. coli growth affected by various concentrations of Fuzi and its processed products were obtained. Combined with chemometric techniques including multivariate analysis of variance and principal component analysis on this information, it could be seen that Fuzi and its processed products could be distinguished according to their toxic effects on E. coli. The IC50 values of 14.6 mg/mL for Fuzi, 59.2 mg/mL for Yanfupian, 118.3 mg/mL for Heifupian, and 182.7 mg/mL for Danfupian illustrated that the sequence of toxicity on E. coli was Fuzi > Yanfupian > Heifupian > Danfupian. This study provided a useful method and idea of the combination of microcalorimetry and chemometrics for studying the toxic effects of TCMs and other substances. PMID:24257841

  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. Application of total reflection X-ray spectrometry in combination with chemometric methods for determination of the botanical origin of Slovenian honey.

    PubMed

    Necemer, Marijan; Kosir, Iztok J; Kump, Peter; Kropf, Urska; Jamnik, Mojca; Bertoncelj, Jasna; Ogrinc, Nives; Golob, Terezija

    2009-05-27

    This work on the botanical origin of various types of honey produced in Slovenia and based on the mineral content analyses by the total reflection X-ray spectrometry (TXRF) is a continuation of this group's preliminary work (Golob, T.; Doberšek, U.; Kump, P.; Nečemer, M. Food Chem. 2005, 91, 593-600), which introduced the analytical methodology and employed only a simple statistical evaluation and which examined the possibility to determine the botanical origin of honey samples via elemental content. A much more comprehensive study on a total of 264 major types of honey samples harvested in 2004, 2005, and 2006 and interpreting the results with up to date chemometric methods was performed in this work. Slovenia is a small country by surface area, but it is pedologically and climatically diverse, therefore offering interesting possibilities for studying the influence of these diversities on the elemental content of natural products. By employing principal component analysis (PCA) and regularized discriminant analysis (RDA) it was established that from all of the measured elements only the four characteristic key elements Cl, K, Mn, and Rb could be used to best discriminate the types of honey. It was established that the employed combination of a simple, fast, and inexpensive multielement TXRF analytical approach and the evaluation of data by chemometric methods has the potential to discriminate the botanical origins of various types of honey. PMID:19364106

  3. Ligand based validated comparative chemometric modeling and pharmacophore mapping of aurone derivatives as antimalarial agents.

    PubMed

    Adhikari, Nilanjan; Halder, Amit Kumar; Mondal, Chanchal; Jha, Tarun

    2013-09-01

    Chloroquine resistance is nowadays a great problem. Aurone derivatives are effective against chloroquine resistant parasite. Ligand based validated comparative chemometric modeling through 2D-QSAR and kNN-MFA 3DQSAR studies as well as common feature 3D pharmacophore mapping were done on thirtyfive aurone derivatives having antimalarial activity. Statistically significant 2D-QSAR models were generated on unsplitted as well as splitted dataset by MLR and PLS technique. The MLR model of the unsplitted method was validated by two-deep cross validation and 10 fold cross validation for determining the predictive ability. The PLS technique of the unsplitted method was done to compare the significance of these methods. In the splitted method, model was developed on the training set by Y-based ranking method by using the same descriptors and was validated on fifty pairs of the test and the training sets by k-MCA technique. These models generated by using the same descriptors were well validated irrespective of MLR as well as PLS analysis of unsplitted as well as splitted methods and are showing similar results. Therefore, these descriptors and model generated were reliable and robust. The kNN-MFA 3D-QSAR models were generated by three variable selection methods: genetic algorithm, simulated annealing and stepwise regression. The kNN-MFA 3D-QSAR results support the 2D QSAR data and in turn validate the earlier observed SAR results. Common feature 3D-pharmacophore generation was performed on these compounds to validate both 2D and 3D-QSAR studies as well as the earlier observed SAR data. The work highlights the required structural features for the higher antimalarial activity. PMID:24010937

  4. 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

    2013-01-01

    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. PMID:24135941

  5. In situ 2D fluorometry and chemometric monitoring of mammalian cell cultures.

    PubMed

    Teixeira, Ana P; Portugal, Carla A M; Carinhas, Nuno; Dias, João M L; Crespo, João P; Alves, Paula M; Carrondo, M J T; Oliveira, Rui

    2009-03-01

    The main objective of the present study was to investigate the use of in situ 2D fluorometry for monitoring key bioprocess variables in mammalian cell cultures, namely the concentration of viable cells and the concentration of recombinant proteins. All studies were conducted using a recombinant Baby Hamster Kidney (BHK) cell line expressing a fusion glycoprotein IgG1-IL2 cultured in batch and fed-batch modes. It was observed that the intensity of fluorescence signals in the excitation/emission wavelength range of amino acids, vitamins and NAD(P)H changed along culture time, although the dynamics of single fluorophors could not be correlated with the dynamics of the target state variables. Therefore, multivariate chemometric modeling was adopted as a calibration methodology. 2D fluorometry produced large volumes of redundant spectral data, which were first filtered by principal components analysis (PCA). Then, a partial least squares (PLS) regression was applied to correlate the reduced fluorescence maps with the target state variables. Two validation strategies were used to evaluate the predictive capacity of the developed PLS models. Accurate estimations of viable cells density (r(2) = 0.95; 99.2% of variance captured in the training set; r(2) = 0.91; 97.7% of variance captured in the validation set) and of glycoprotein concentration (r(2) = 0.99 and 99.7% of variance captured in the training set; r(2) = 0.99 and 99.3% of variance captured in the validation set) were obtained over a wide range of reactor operation conditions. The results presented herein confirm that 2D fluorometry constitutes a reliable methodology for on-line monitoring of viable cells and recombinant protein concentrations in mammalian cell cultures. PMID:18853411

  6. Application of Chemometric Methods for Assessment and Modelling of Microbiological Quality Data Concerning Coastal Bathing Water in Greece

    PubMed Central

    Papaioannou, Agelos; Rigas, George; Papastergiou, Panagiotis; Hadjichristodoulou, Christos

    2014-01-01

    Background Worldwide, the aim of managing water is to safeguard human health whilst maintaining sustainable aquatic and associated terrestrial, ecosystems. Because human enteric viruses are the most likely pathogens responsible for waterborne diseases from recreational water use, but detection methods are complex and costly for routine monitoring, it is of great interest to determine the quality of coastal bathing water with a minimum cost and maximum safety. Design and methods This study handles the assessment and modelling of the microbiological quality data of 2149 seawater bathing areas in Greece over 10-year period (1997-2006) by chemometric methods. Results Cluster analysis results indicated that the studied bathing beaches are classified in accordance with the seasonality in three groups. Factor analysis was applied to investigate possible determining factors in the groups resulted from the cluster analysis, and also two new parameters were created in each group; VF1 includes E. coli, faecal coliforms and total coliforms and VF2 includes faecal streptococci/enterococci. By applying the cluster analysis in each seasonal group, three new groups of coasts were generated, group A (ultraclean), group B (clean) and group C (contaminated). Conclusions The above analysis is confirmed by the application of discriminant analysis, and proves that chemometric methods are useful tools for assessment and modeling microbiological quality data of coastal bathing water on a large scale, and thus could attribute to effective and economical monitoring of the quality of coastal bathing water in a country with a big number of bathing coasts, like Greece. Significance for public health The microbiological protection of coastal bathing water quality is of great interest for the public health authorities as well as for the economy. The present study proves that this protection can be achieved by monitoring only two microbiological parameters, E. coli and faecal streptococci

  7. Quality assessment of traditional Chinese medicine herb couple by high-performance liquid chromatography and mass spectrometry combined with chemometrics.

    PubMed

    Cheng, Tao-Fang; Jia, Yu-Ran; Zuo, Zheng; Dong, Xin; Zhou, Ping; Li, Ping; Li, Fei

    2016-04-01

    This study was designed to develop a simple, specific and reliable method to overall analyze the chemical constituents in clematidis radix et rhizome/notopterygii rhizome et radix herb couple using high-performance liquid chromatography coupled with tandem mass spectrometry and multiple chemometric analysis. First, the separation and qualitative analysis of herb couple was achieved on an Agilent Zorbax Eclipse Plus C18 column (250 mm × 4.6 mm, 5 μm), and 69 compounds were unambiguously or tentatively identified. Moreover, in quantitative analysis, eight ingredients including six coumarins and two triterpenoid sapogenins were quantified by high-performance liquid chromatography coupled with tandem mass spectrometry. In terms of good linearity (r(2) ≥ 0.9995) with a relatively wide concentration range, recovery (85.40-102.50%) and repeatability (0.99-4.45%), the validation results suggested the proposed method was reliable, and successfully used to analyze ten batches of herb couple samples. Then, hierarchical cluster analysis and principal component analysis were used to classify samples and search significant ingredients. The results showed that ten batches of herb couple samples were classified into three groups, and six compounds were found for its better quality control. PMID:26834048

  8. Near-infrared and fourier transform infrared chemometric methods for the quantification of crystalline tacrolimus from sustained-release amorphous solid dispersion.

    PubMed

    Rahman, Ziyaur; Siddiqui, Akhtar; Bykadi, Srikant; Khan, Mansoor A

    2014-08-01

    The objective of the present research was to study the feasibility of using near-infrared (NIR) and Fourier transform infrared (FTIR)-based chemometric models in quantifying crystalline and amorphous tacrolimus from its sustained-release amorphous solid dispersion (ASD). ASD contained ethyl cellulose, hydroxypropyl methyl cellulose, and lactose monohydrate as carriers, and amorphous form of tacrolimus in it was confirmed by X-ray powder diffraction. Crystalline physical mixture was mixed with ASD in various proportions to prepare sample matrices containing 0%-100% amorphous/crystalline tacrolimus. NIR and FTIR of the samples were recorded, and data were mathematically pretreated using multiple scattering correction, standard normal variate, or Savitzky-Golay before multivariate analysis, partial-least-square regression (PLSR), and principle component regression (PCR). The PLSR models were more accurate than PCR for NIR and FTIR data as indicated by low value of root-mean-squared error of prediction, standard error of prediction and bias, and high value of R(2). Additionally, NIR data-based models were more accurate and precise than FTIR data models. In conclusion, NIR chemometric models provide simple and fast method to quantitate crystalline tacrolimus in the ASD formulation. PMID:24931728

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

    PubMed

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

    2016-01-01

    Determination of benzo[a]pyrene (BaP) in cigarette smoke can be very important for the tobacco quality control and the assessment of its harm to human health. In this study, mid-infrared spectroscopy (MIR) coupled to chemometric algorithm (DPSO-WPT-PLS), which was based on the wavelet packet transform (WPT), discrete particle swarm optimization algorithm (DPSO) and partial least squares regression (PLS), was used to quantify harmful ingredient benzo[a]pyrene in the cigarette mainstream smoke with promising result. Furthermore, the proposed method provided better performance compared to several other chemometric models, i.e., PLS, radial basis function-based PLS (RBF-PLS), PLS with stepwise regression variable selection (Stepwise-PLS) as well as WPT-PLS with informative wavelet coefficients selected by correlation coefficient test (rtest-WPT-PLS). It can be expected that the proposed strategy could become a new effective, rapid quantitative analysis technique in analyzing the harmful ingredient BaP in cigarette mainstream smoke. PMID:26703252

  10. A study on the discrimination of human skeletons using X-ray fluorescence and chemometric tools in chemical anthropology.

    PubMed

    Gonzalez-Rodriguez, J; Fowler, G

    2013-09-10

    Forensic anthropological investigations are often restricted in their outcomes by the resources allocated to them, especially in terms of positively identifying the victims exhumed from commingled mass graves. Commingled mass graves can be defined as those graves that contain a number of disarticulated human remains from different individuals that have been mixed by either natural processes or human interventions. The research developed aimed to apply the technique of non-destructive XRF analysis to test whether there is substantial differentiation within the trace elemental composition and their ratios of individuals to separate them using chemometric analysis. The results of the different atomic spectroscopic analyses combined with the use of multivariate analysis on a set of 5 skeletons produced a series of plots using Principal Component Analysis that helped to separate them with a high percentage of accuracy when two, three or four skeletons needed to be separated. Also, two new elemental ratios, Zn/Fe related to metabolic activities and K/Fe related to blood flow into the bone, have been defined for their use in forensic anthropology for the first time to aid in the separation. PMID:23725985

  11. Chemometrics Tools in Detection and Quantitation of the Main Impurities Present in Aspirin/Dipyridamole Extended-Release Capsules.

    PubMed

    El-Ragehy, Nariman A; Yehia, Ali M; Hassan, Nagiba Y; Tantawy, Mahmoud A; Abdelkawy, Mohamed

    2016-07-01

    Aspirin (ASP) and dipyridamole (DIP) in combination is widely used in the prevention of secondary events after stroke and transient ischemic attack. Salicylic acid is a well-known impurity of ASP, and the DIP extended-release formulation may contain ester impurities originating from the reaction with tartaric acid. UV spectral data analysis of the active ingredients in the presence of their main impurities is presented using multivariate approaches. Four chemometric-assisted spectrophotometric methods, namely, partial least-squares, concentration residuals augmented classical least-squares (CRACLS), multivariate curve resolution (MCR) alternating least-squares (ALS), and artificial neural networks, were developed and validated. The quantitative analyses of all the proposed calibrations were compared by percentage recoveries, root mean square error of prediction, and standard error of prediction. In addition, r(2) values between the pure and estimated spectral profiles were used to evaluate the qualitative analysis of CRACLS and MCR-ALS. The lowest error was obtained by the CRACLS model, whereas the best correlation was achieved using MCR-ALS. The four multivariate calibration methods could successfully be applied for the extended-release formulation analysis. The application results were also validated by analysis of the stored dosage-form solution, which showed a susceptibility of DIP esterification in the extended-release formulation. Statistical comparison between the proposed and official methods showed no significant difference. PMID:27302874

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

    PubMed

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

    2016-05-18

    In this study, the kinetics of aldehyde formation in heated frying oils was characterized by 2-hydrazinoquinoline derivatization, liquid chromatography-mass spectrometry (LC-MS) analysis, principal component analysis (PCA), and hierarchical cluster analysis (HCA). The aldehydes contributing to time-dependent separation of heated soybean oil (HSO) in a PCA model were grouped by the HCA into three clusters (A1, A2, and B) on the basis of their kinetics and fatty acid precursors. The increases of 4-hydroxynonenal (4-HNE) and the A2-to-B ratio in HSO were well-correlated with the duration of thermal stress. Chemometric and quantitative analysis of three frying oils (soybean, corn, and canola oils) and French fry extracts further supported the associations between aldehyde profiles and fatty acid precursors and also revealed that the concentrations of pentanal, hexanal, acrolein, and the A2-to-B ratio in French fry extracts were more comparable to their values in the frying oils than other unsaturated aldehydes. All of these results suggest the roles of specific aldehydes or aldehyde clusters as novel markers of the lipid oxidation status for frying oils or fried foods. PMID:27128101

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

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

  15. Fourier transform infrared spectroscopy combined with chemometrics for discrimination of Curcuma longa, Curcuma xanthorrhiza and Zingiber cassumunar

    NASA Astrophysics Data System (ADS)

    Rohaeti, Eti; Rafi, Mohamad; Syafitri, Utami Dyah; Heryanto, Rudi

    2015-02-01

    Turmeric (Curcuma longa), java turmeric (Curcuma xanthorrhiza) and cassumunar ginger (Zingiber cassumunar) are widely used in traditional Indonesian medicines (jamu). They have similar color for their rhizome and possess some similar uses, so it is possible to substitute one for the other. The identification and discrimination of these closely-related plants is a crucial task to ensure the quality of the raw materials. Therefore, an analytical method which is rapid, simple and accurate for discriminating these species using Fourier transform infrared spectroscopy (FTIR) combined with some chemometrics methods was developed. FTIR spectra were acquired in the mid-IR region (4000-400 cm-1). Standard normal variate, first and second order derivative spectra were compared for the spectral data. Principal component analysis (PCA) and canonical variate analysis (CVA) were used for the classification of the three species. Samples could be discriminated by visual analysis of the FTIR spectra by using their marker bands. Discrimination of the three species was also possible through the combination of the pre-processed FTIR spectra with PCA and CVA, in which CVA gave clearer discrimination. Subsequently, the developed method could be used for the identification and discrimination of the three closely-related plant species.

  16. Discrimination of tomatoes bred by spaceflight mutagenesis using visible/near infrared spectroscopy and chemometrics

    NASA Astrophysics Data System (ADS)

    Shao, Yongni; Xie, Chuanqi; Jiang, Linjun; Shi, Jiahui; Zhu, Jiajin; He, Yong

    2015-04-01

    Visible/near infrared spectroscopy (Vis/NIR) based on sensitive wavelengths (SWs) and chemometrics was proposed to discriminate different tomatoes bred by spaceflight mutagenesis from their leafs or fruits (green or mature). The tomato breeds were mutant M1, M2 and their parent. Partial least squares (PLS) analysis and least squares-support vector machine (LS-SVM) were implemented for calibration models. PLS analysis was implemented for calibration models with different wavebands including the visible region (400-700 nm) and the near infrared region (700-1000 nm). The best PLS models were achieved in the visible region for the leaf and green fruit samples and in the near infrared region for the mature fruit samples. Furthermore, different latent variables (4-8 LVs for leafs, 5-9 LVs for green fruits, and 4-9 LVs for mature fruits) were used as inputs of LS-SVM to develop the LV-LS-SVM models with the grid search technique and radial basis function (RBF) kernel. The optimal LV-LS-SVM models were achieved with six LVs for the leaf samples, seven LVs for green fruits, and six LVs for mature fruits, respectively, and they outperformed the PLS models. Moreover, independent component analysis (ICA) was executed to select several SWs based on loading weights. The optimal LS-SVM model was achieved with SWs of 550-560 nm, 562-574 nm, 670-680 nm and 705-715 nm for the leaf samples; 548-556 nm, 559-564 nm, 678-685 nm and 962-974 nm for the green fruit samples; and 712-718 nm, 720-729 nm, 968-978 nm and 820-830 nm for the mature fruit samples. All of them had better performance than PLS and LV-LS-SVM, with the parameters of correlation coefficient (rp), root mean square error of prediction (RMSEP) and bias of 0.9792, 0.2632 and 0.0901 based on leaf discrimination, 0.9837, 0.2783 and 0.1758 based on green fruit discrimination, 0.9804, 0.2215 and -0.0035 based on mature fruit discrimination, respectively. The overall results indicated that ICA was an effective way for the

  17. Rapid monitoring of grapevine reserves using ATR-FT-IR and chemometrics.

    PubMed

    Schmidtke, Leigh M; Smith, Jason P; Müller, Markus C; Holzapfel, Bruno P

    2012-06-30

    Predictions of grapevine yield and the management of sugar accumulation and secondary metabolite production during berry ripening may be improved by monitoring nitrogen and starch reserves in the perennial parts of the vine. The standard method for determining nitrogen concentration in plant tissue is by combustion analysis, while enzymatic hydrolysis followed by glucose quantification is commonly used for starch. Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FT-IR) combined with chemometric modelling offers a rapid means for the determination of a range of analytes in powdered or ground samples. ATR-FT-IR offers significant advantages over combustion or enzymatic analysis of samples due to the simplicity of instrument operation, reproducibility and speed of data collection. In the present investigation, 1880 root and wood samples were collected from Shiraz, Semillon and Riesling vineyards in Australia and Germany. Nitrogen and starch concentrations were determined using standard analytical methods, and ATR-FT-IR spectra collected for each sample using a Bruker Alpha instrument. Samples were randomly assigned to either calibration or test data sets representing two thirds and one third of the samples respectively. Signal preprocessing included extended multiplicative scatter correction for water and carbon dioxide vapour, standard normal variate scaling with second derivative and variable selection prior to regression. Excellent predictive models for percent dry weight (DW) of nitrogen (range: 0.10-2.65% DW, median: 0.45% DW) and starch (range: 0.25-42.82% DW, median: 7.77% DW) using partial least squares (PLS) or support vector machine (SVM) analysis for linear and nonlinear regression respectively, were constructed and cross validated with low root mean square errors of prediction (RMSEP). Calibrations employing SVM-regression provided the optimum predictive models for nitrogen (R(2)=0.98 and RMSEP=0.07% DW) compared to PLS regression

  18. Chilean flour and wheat grain: tracing their origin using near infrared spectroscopy and chemometrics.

    PubMed

    González-Martín, Ma Inmaculada; Wells Moncada, Guillermo; González-Pérez, Claudio; Zapata San Martín, Nelson; López-González, Fernando; Lobos Ortega, Iris; Hernández-Hierro, Jose-Miguel

    2014-02-15

    Instrumental techniques such a near-infrared spectroscopy (NIRS) are used in industry to monitor and establish product composition and quality. As occurs with other food industries, the Chilean flour industry needs simple, rapid techniques to objectively assess the origin of different products, which is often related to their quality. In this sense, NIRS has been used in combination with chemometric methods to predict the geographic origin of wheat grain and flour samples produced in different regions of Chile. Here, the spectral data obtained with NIRS were analysed using a supervised pattern recognition method, Discriminat Partial Least Squares (DPLS). The method correctly classified 76% of the wheat grain samples and between 90% and 96% of the flour samples according to their geographic origin. The results show that NIRS, together with chemometric methods, provides a rapid tool for the classification of wheat grain and flour samples according to their geographic origin. PMID:24128548

  19. New chemometric approach MCR-ALS to unmix EPR spectroscopic data from complex mixtures

    NASA Astrophysics Data System (ADS)

    Fadel, Maya Abou; de Juan, Anna; Touati, Nadia; Vezin, Hervé; Duponchel, Ludovic

    2014-11-01

    Electron paramagnetic resonance (EPR) spectra of mixtures are often difficult to interpret due to the superposition of spectral contribution of various species present in the complex materials. It is challenging to accurately identify the number of pure compounds present and to extract their pure spectra. In this study, the powerful chemometric method, multivariate curve resolution-alternating least squares (MCR-ALS), is applied to identify different paramagnetic centers. This method is used to simultaneously extract, with no prior knowledge, the pure spectra and the corresponding concentration profiles of all the compounds in the unknown and unresolved mixtures. The goal of our work is to apply, for the first time, this new chemometrics methodology, MCR-ALS, on EPR spectroscopic data in order to characterize a series of distinct but strongly overlapping spectra of various paramagnetic species.

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

    PubMed

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

    2017-02-01

    NMR and chemometrics was applied to understand the variations in chemical composition of coconut water under different processing. Six processing treatments were applied to coconut water and analyzed: two control (with and without sulphite), and four samples thermally processed at 110°C and 136°C (with and without sulphite). Samples processed at lower temperature and without sulphite presented pink color under storage. According to chemometrics, samples processed at higher temperature exhibited lower levels of glucose and malic acid. Samples with sulphite processed at 136°C presented lower amount of sucrose, suggesting the degradation of the carbohydrates after harshest thermal treatment. Samples with sulphite and processed at lower temperature showed higher concentration of ethanol. However, no significant changes were verified in coconut water composition as a whole. Sulphite addition and the temperature processing to 136°C were effective to prevent the pinking and to maintain the levels of main organic compounds. PMID:27596412

  1. Exploring molecular fingerprints of selective PPARδ agonists through comparative and validated chemometric techniques.

    PubMed

    Nandy, A; Roy, K; Saha, A

    2015-01-01

    Peroxysome proliferator-activated receptors (PPARs) have grown greatly in importance due to their role in the metabolic profile. Among three subtypes (α, γ and δ), we here consider the least investigated δ subtype to explore the molecular fingerprints of selective PPARδ agonists. Validated QSAR models (regression based 2D-QSAR, HQSAR and KPLS) and molecular docking with dynamics analyses support the inference of classification-based Bayesian and recursive models. Chemometric studies indicate that the presence of ether linkages and heterocyclic rings has optimum influence in imparting selective bioactivity. Pharmacophore models and docking with molecular dynamics analyses postulate the occurrence of aromatic rings, HB acceptor and a hydrophobic region as crucial molecular fragments for development of PPARδ modulators. Multi-chemometric studies suggest the essential structural requirements of a molecule for imparting potent and selective PPARδ modulation. PMID:25986170

  2. A Useful Strategy to Evaluate the Quality Consistency of Traditional Chinese Medicines Based on Liquid Chromatography and Chemometrics.

    PubMed

    Wang, Pei; Nie, Lei; Zang, Hengchang

    2015-01-01

    Evaluation of the batch consistency of traditional Chinese medicines (TCMs) is essential for the promotion of the development and quality control of TCMs. The aim of the present work was to develop a useful strategy via liquid chromatography and chemometrics to evaluate the batch consistency of TCM preparations. Xin-Ke-Shu (XKS) tablet was chosen as a model for this method development. Four types of chromatographic fingerprint approaches were compared by using similarity analysis based on cosine of angel or correlation coefficient. Differences in the fingerprints of 71 batches of XKS tablet were illustrated by hierarchical cluster analysis. Then, Mahalanobis distance was employed for estimating the probability level (P < 0.05) of the differences mentioned above. Additionally, t-test was applied to find out the chromatographic peaks which had significant differences. For XKS tablet, the maximum wavelength fingerprint had the largest range and dispersion degree of similarity as compared with the other three ones. There were two clear clusters in all the batches of samples. And we clearly arrived at the conclusion that higher similarity does not exactly indicate small Mahalanobis distance, while lower similarity indicated larger Mahalanobis distance. Finally, a useful strategy was proposed for evaluation of the batch consistency of XKS tablet. PMID:26618023

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

    PubMed

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

    2014-12-01

    The metabolomic differences in phenolics from leaves derived from 3 artichoke cultivars (Cynara scolymus): American Green Globe, French Hyrious and Egyptian Baladi, collected at different developmental stages, were assessed using UHPLC-MS coupled to chemometrics. Ontogenic changes were considered as leaves were collected at four different time intervals and positions (top and basal) during artichoke development. Unsupervised principal component analysis (PCA) and supervised orthogonal projection to latent structures-discriminant analysis (O2PLS-DA) were used for comparing and classification of samples harvested from different cultivars at different time points and positions. A clear separation among the three investigated cultivars was revealed, with the American Green Globe samples found most enriched in caffeic acid conjugates and flavonoids vs. other cultivars. Furthermore, these metabolites also showed a marked effect on the discrimination between leaf samples from cultivars harvested at different positions, regardless of the plant age. Metabolite absolute quantifications further confirmed that discrimination was mostly influenced by phenolic compounds, namely caffeoylquinic acids and flavonoids. This study demonstrates an effect of artichoke leaf position, regardless of plant age, on its secondary metabolites composition. To the best of our knowledge, this is the first report for compositional differences among artichoke leaves, based on their positions, via a metabolomic approach and suggesting that top positioned artichoke leaves present a better source of caffeoylquinic acids, compared to basal ones. PMID:25301664

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

    PubMed

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

    2015-12-01

    The aim of this study was to predict the geographic origin of lentils by using isotope ratio mass spectrometry (IRMS) in combination with chemometrics. Lentil samples from two origins, i.e. Italy and Canada, were analysed obtaining the stable isotope ratios of δ(13)C, δ(15)N, δ(2)H, δ(18)O, and δ(34)S. A comparison between median values (U-test) highlighted statistically significant differences (p<0.05) for all isotopic parameters between the lentils produced in these two different geographic areas, except for δ(15)N. Applying principal component analysis, grouping of samples was observed on the basis of origin but with overlapping zones; consequently, two supervised discriminant techniques, i.e. partial least squares discriminant analysis and k-nearest neighbours algorithm were used. Both models showed good performances with external prediction abilities of about 93% demonstrating the suitability of the methods developed. Subsequently, isotopic determinations were also performed on the protein and starch fractions and the relevant results are reported. PMID:26041202

  5. Identification of antibody isotypes in biological fluids by means of micro-Raman spectroscopy and chemometric methods

    NASA Astrophysics Data System (ADS)

    Araujo-Andrade, C.; Pichardo-Molina, J. L.; Barbosa-Sabanero, G.; Frausto-Reyes, C.

    2008-02-01

    Clinical diagnosis of infections, generally are realized by serological methods, which identifies the antibodies presents in serum or tissue fluids of the patient. Antibodies are proteins present in our bodies that aid in the elimination of pathogens or antigens. Identification of antibodies isotypes is important because can help to predict when and whether patients will recover from infections and are commonly diagnosed by means of indirect methods such as serological test. In the other hand, the majority of these methods requires specific kits for the analysis, special sample preparation, chemical reagents, expensive equipment and require long time for getting results. In this work we show the feasibility to discriminate antibody isotypes in biological fluids like human colostrum by means of Raman spectroscopy and chemometrics. Spectra were obtained using an excitation wavelength of 514 nm over dried samples of human colostrum labeled previously as positives to specific IgG and IgM antibodies against Toxoplasma Gondii by means of ELISA test. Partial least square-discriminant analysis (PLS-DA) was used to discriminate among antibody isotypes by use second derivative of Raman spectra of colostrum samples.

  6. Determination of Cefoperazone Sodium in Presence of Related Impurities by Linear Support Vector Regression and Partial Least Squares Chemometric Models

    PubMed Central

    Naguib, Ibrahim A.; Abdelaleem, Eglal A.; Zaazaa, Hala E.; Hussein, Essraa A.

    2015-01-01

    A comparison between partial least squares regression and support vector regression chemometric models is introduced in this study. The two models are implemented to analyze cefoperazone sodium in presence of its reported impurities, 7-aminocephalosporanic acid and 5-mercapto-1-methyl-tetrazole, in pure powders and in pharmaceutical formulations through processing UV spectroscopic data. For best results, a 3-factor 4-level experimental design was used, resulting in a training set of 16 mixtures containing different ratios of interfering moieties. For method validation, an independent test set consisting of 9 mixtures was used to test predictive ability of established models. The introduced results show the capability of the two proposed models to analyze cefoperazone in presence of its impurities 7-aminocephalosporanic acid and 5-mercapto-1-methyl-tetrazole with high trueness and selectivity (101.87 ± 0.708 and 101.43 ± 0.536 for PLSR and linear SVR, resp.). Analysis results of drug products were statistically compared to a reported HPLC method showing no significant difference in trueness and precision, indicating the capability of the suggested multivariate calibration models to be reliable and adequate for routine quality control analysis of drug product. SVR offers more accurate results with lower prediction error compared to PLSR model; however, PLSR is easy to handle and fast to optimize. PMID:26664764

  7. A Useful Strategy to Evaluate the Quality Consistency of Traditional Chinese Medicines Based on Liquid Chromatography and Chemometrics

    PubMed Central

    Wang, Pei; Nie, Lei; Zang, Hengchang

    2015-01-01

    Evaluation of the batch consistency of traditional Chinese medicines (TCMs) is essential for the promotion of the development and quality control of TCMs. The aim of the present work was to develop a useful strategy via liquid chromatography and chemometrics to evaluate the batch consistency of TCM preparations. Xin-Ke-Shu (XKS) tablet was chosen as a model for this method development. Four types of chromatographic fingerprint approaches were compared by using similarity analysis based on cosine of angel or correlation coefficient. Differences in the fingerprints of 71 batches of XKS tablet were illustrated by hierarchical cluster analysis. Then, Mahalanobis distance was employed for estimating the probability level (P < 0.05) of the differences mentioned above. Additionally, t-test was applied to find out the chromatographic peaks which had significant differences. For XKS tablet, the maximum wavelength fingerprint had the largest range and dispersion degree of similarity as compared with the other three ones. There were two clear clusters in all the batches of samples. And we clearly arrived at the conclusion that higher similarity does not exactly indicate small Mahalanobis distance, while lower similarity indicated larger Mahalanobis distance. Finally, a useful strategy was proposed for evaluation of the batch consistency of XKS tablet. PMID:26618023

  8. Application of near infrared (NIR) spectroscopy coupled to chemometrics for dried egg-pasta characterization and egg content quantification.

    PubMed

    Bevilacqua, Marta; Bucci, Remo; Materazzi, Stefano; Marini, Federico

    2013-10-15

    Dried egg pasta is an important and traditional food in the Italian cuisine, and the eggs in pasta improve its nutritional value and organoleptic properties. For this reason the percentage of eggs present in the products sold as "egg pasta" has to always be clearly reported in the label. In this respect, the present research addresses the possibility of developing a method which would allow fast, simple and economic determination of egg content in dried egg-pasta, using near-infrared spectroscopy and chemometric analysis. However, as it is very likely that the spectroscopic fingerprint can also be affected by the manufacturing process of this product, in particular by drying temperature and time, the effect of the manufacturing process on the spectral profile of egg-pasta samples was thoroughly investigated, using experimental design coupled to a multivariate exploratory data analytical technique called ANOVA-Simultaneous Component Analysis (ASCA). Moreover, once confirmed the significance of the drying effect on spectral shape, with the aim of building a calibration model to quantify the egg content in pasta samples irrespective of the manufacturing protocol adopted, a non-linear approach based on local regression, namely LWR-PLS, was investigated. This method allowed the determination of the egg content in external validation samples with low error (RMSEP=1.25), resulting in predictions more accurate and precise than those obtained by a global PLS model. PMID:23692759

  9. The differentiation of fibre- and drug type Cannabis seedlings by gas chromatography/mass spectrometry and chemometric tools.

    PubMed

    Broséus, Julian; Anglada, Frédéric; Esseiva, Pierre

    2010-07-15

    Cannabis cultivation in order to produce drugs is forbidden in Switzerland. Thus, law enforcement authorities regularly ask forensic laboratories to determinate cannabis plant's chemotype from seized material in order to ascertain that the plantation is legal or not. As required by the EU official analysis protocol the THC rate of cannabis is measured from the flowers at maturity. When laboratories are confronted to seedlings, they have to lead the plant to maturity, meaning a time consuming and costly procedure. This study investigated the discrimination of fibre type from drug type Cannabis seedlings by analysing the compounds found in their leaves and using chemometrics tools. 11 legal varieties allowed by the Swiss Federal Office for Agriculture and 13 illegal ones were greenhouse grown and analysed using a gas chromatograph interfaced with a mass spectrometer. Compounds that show high discrimination capabilities in the seedlings have been identified and a support vector machines (SVMs) analysis was used to classify the cannabis samples. The overall set of samples shows a classification rate above 99% with false positive rates less than 2%. This model allows then discrimination between fibre and drug type Cannabis at an early stage of growth. Therefore it is not necessary to wait plants' maturity to quantify their amount of THC in order to determine their chemotype. This procedure could be used for the control of legal (fibre type) and illegal (drug type) Cannabis production. PMID:20456880

  10. Advanced stability indicating chemometric methods for quantitation of amlodipine and atorvastatin in their quinary mixture with acidic degradation products.

    PubMed

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

    2016-02-01

    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. PMID:26513228

  11. Classification the geographical origin of corn distillers dried grains with solubles by near infrared reflectance spectroscopy combined with chemometrics: A feasibility study.

    PubMed

    Zhou, Xingfan; Yang, Zengling; Haughey, Simon A; Galvin-King, Pamela; Han, Lujia; Elliott, Christopher T

    2015-12-15

    In this study, 137 corn distillers dried grains with solubles (DDGS) samples from a range of different geographical origins (Jilin Province of China, Heilongjiang Province of China, USA and Europe) were collected and analysed. Different near infrared spectrometers combined with different chemometric packages were used in two independent laboratories to investigate the feasibility of classifying geographical origin of DDGS. Base on the same dataset, one laboratory developed a partial least square discriminant analysis model and another laboratory developed an orthogonal partial least square discriminant analysis model. Results showed that both models could perfectly classify DDGS samples from different geographical origins. These promising results encourage the development of larger scale efforts to produce datasets which can be used to differentiate the geographical origin of DDGS and such efforts are required to provide higher level food security measures on a global scale. PMID:26190595

  12. Classification of gasoline by octane number and light gas condensate fractions by origin with using dielectric or gas-chromatographic data and chemometrics tools.

    PubMed

    Rudnev, Vasiliy A; Boichenko, Alexander P; Karnozhytskiy, Pavel V

    2011-05-15

    The approach for classification of gasoline by octane number and light gas condensate fractions by origin with using dielectric permeability data has been proposed and compared with classification of same samples on the basis of gas-chromatographic data. The precision of dielectric permeability measurements was investigated by using ANOVA. The relative standard deviation of dielectric permeability was in the range from 0.3 to 0.5% for the range of dielectric permeability from 1.8 to 4.4. The application of exploratory chemometrics tools (cluster analysis and principal component analysis) allow to explicitly differentiate the gasoline and light gas condensate fractions into groups of samples related to specific octane number or origin. The neural networks allow to perfectly classifying the gasoline and light gas condensate fractions. PMID:21482310

  13. Rapid Quantification of Methamphetamine: Using Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR) and Chemometrics

    PubMed Central

    Hughes, Juanita; Ayoko, Godwin; Collett, Simon; Golding, Gary

    2013-01-01

    In Australia and increasingly worldwide, methamphetamine is one of the most commonly seized drugs analysed by forensic chemists. The current well-established GC/MS methods used to identify and quantify methamphetamine are lengthy, expensive processes, but often rapid analysis is requested by undercover police leading to an interest in developing this new analytical technique. Ninety six illicit drug seizures containing methamphetamine (0.1%–78.6%) were analysed using Fourier Transform Infrared Spectroscopy with an Attenuated Total Reflectance attachment and Chemometrics. Two Partial Least Squares models were developed, one using the principal Infrared Spectroscopy peaks of methamphetamine and the other a Hierarchical Partial Least Squares model. Both of these models were refined to choose the variables that were most closely associated with the methamphetamine % vector. Both of the models were excellent, with the principal peaks in the Partial Least Squares model having Root Mean Square Error of Prediction 3.8, R2 0.9779 and lower limit of quantification 7% methamphetamine. The Hierarchical Partial Least Squares model had lower limit of quantification 0.3% methamphetamine, Root Mean Square Error of Prediction 5.2 and R2 0.9637. Such models offer rapid and effective methods for screening illicit drug samples to determine the percentage of methamphetamine they contain. PMID:23936058

  14. Chemometric Methods and Theoretical Molecular Descriptors in Predictive QSAR Modeling of the Environmental Behavior of Organic Pollutants

    NASA Astrophysics Data System (ADS)

    Gramatica, Paola

    This chapter surveys the QSAR modeling approaches (developed by the author's research group) for the validated prediction of environmental properties of organic pollutants. Various chemometric methods, based on different theoretical molecular descriptors, have been applied: explorative techniques (such as PCA for ranking, SOM for similarity analysis), modeling approaches by multiple-linear regression (MLR, in particular OLS), and classification methods (mainly k-NN, CART, CP-ANN). The focus of this review is on the main topics of environmental chemistry and ecotoxicology, related to the physico-chemical properties, the reactivity, and biological activity of chemicals of high environmental concern. Thus, the review deals with atmospheric degradation reactions of VOCs by tropospheric oxidants, persistence and long-range transport of POPs, sorption behavior of pesticides (Koc and leaching), bioconcentration, toxicity (acute aquatic toxicity, mutagenicity of PAHs, estrogen binding activity for endocrine disruptors compounds (EDCs)), and finally persistent bioaccumulative and toxic (PBT) behavior for the screening and prioritization of organic pollutants. Common to all the proposed models is the attention paid to model validation for predictive ability (not only internal, but also external for chemicals not participating in the model development) and checking of the chemical domain of applicability. Adherence to such a policy, requested also by the OECD principles, ensures the production of reliable predicted data, useful also in the new European regulation of chemicals, REACH.

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

    PubMed

    Farrés, Mireia; Piña, Benjamí; Tauler, Romà

    2016-08-01

    Copper containing fungicides are used to protect vineyards from fungal infections. Higher residues of copper in grapes at toxic concentrations are potentially toxic and affect the microorganisms living in vineyards, such as Saccharomyces cerevisiae. In this study, the response of the metabolic profiles of S. cerevisiae at different concentrations of copper sulphate (control, 1 mM, 3 mM and 6 mM) was analysed by liquid chromatography coupled to mass spectrometry (LC-MS) and multivariate curve resolution-alternating least squares (MCR-ALS) using an untargeted metabolomics approach. Peak areas of the MCR-ALS resolved elution profiles in control and in Cu(ii)-treated samples were compared using partial least squares regression (PLSR) and PLS-discriminant analysis (PLS-DA), and the intracellular metabolites best contributing to sample discrimination were selected and identified. Fourteen metabolites showed significant concentration changes upon Cu(ii) exposure, following a dose-response effect. The observed changes were consistent with the expected effects of Cu(ii) toxicity, including oxidative stress and DNA damage. This research confirmed that LC-MS based metabolomics coupled to chemometric methods are a powerful approach for discerning metabolomics changes in S. cerevisiae and for elucidating modes of toxicity of environmental stressors, including heavy metals like Cu(ii). PMID:27302082

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    PubMed

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

    2013-04-15

    This study investigated polycyclic aromatic hydrocarbons (PAHs) pollution in surface sediments within aquaculture areas in Peninsular Malaysia using chemometric techniques, forensics and univariate methods. The samples were analysed using soxhlet extraction, silica gel column clean-up and gas chromatography mass spectrometry. The total PAH concentrations ranged from 20 to 1841 ng/g with a mean of 363 ng/g dw. The application of chemometric techniques enabled clustering and discrimination of the aquaculture sediments into four groups according to the contamination levels. A combination of chemometric and molecular indices was used to identify the sources of PAHs, which could be attributed to vehicle emissions, oil combustion and biomass combustion. Source apportionment using absolute principle component scores-multiple linear regression showed that the main sources of PAHs are vehicle emissions 54%, oil 37% and biomass combustion 9%. Land-based pollution from vehicle emissions is the predominant contributor of PAHs in the aquaculture sediments of Peninsular Malaysia. PMID:23452623

  19. Characterization and Visualization of Vesicles in the Endo-Lysosomal Pathway with Surface-Enhanced Raman Spectroscopy and Chemometrics.

    PubMed

    Huefner, Anna; Kuan, Wei-Li; Müller, Karin H; Skepper, Jeremy N; Barker, Roger A; Mahajan, Sumeet

    2016-01-26

    Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive vibrational fingerprinting technique widely used in analytical and biosensing applications. For intracellular sensing, typically gold nanoparticles (AuNPs) are employed as transducers to enhance the otherwise weak Raman spectroscopy signals. Thus, the signature patterns of the molecular nanoenvironment around intracellular unlabeled AuNPs can be monitored in a reporter-free manner by SERS. The challenge of selectively identifying molecular changes resulting from cellular processes in large and multidimensional data sets and the lack of simple tools for extracting this information has resulted in limited characterization of fundamental cellular processes by SERS. Here, this shortcoming in analysis of SERS data sets is tackled by developing a suitable methodology of reference-based PCA-LDA (principal component analysis-linear discriminant analysis). This method is validated and exemplarily used to extract spectral features characteristic of the endocytic compartment inside cells. The voluntary uptake through vesicular endocytosis is widely used for the internalization of AuNPs into cells, but the characterization of the individual stages of this pathway has not been carried out. Herein, we use reporter-free SERS to identify and visualize the stages of endocytosis of AuNPs in cells and map the molecular changes via the adaptation and advantageous use of chemometric methods in combination with tailored sample preparation. Thus, our study demonstrates the capabilities of reporter-free SERS for intracellular analysis and its ability to provide a way of characterizing intracellular composition. The developed analytical approach is generic and enables the application of reporter-free SERS to identify unknown components in different biological matrices and materials. PMID:26649752

  20. Early detection of Zygosaccharomyces rouxii--spawned spoilage in apple juice by electronic nose combined with chemometrics.

    PubMed

    Wang, Huxuan; Hu, Zhongqiu; Long, Fangyu; Guo, Chunfeng; Yuan, Yahong; Yue, Tianli

    2016-01-18

    Spoilage spawned by Zygosaccharomyces rouxii can cause sensory defect in apple juice, which could hardly be perceived in the early stage and therefore would lead to the serious economic loss. Thus, it is essential to detect the contamination in early stage to avoid costly waste of products or recalls. In this work the performance of an electronic nose (e-nose) coupled with chemometric analysis was evaluated for diagnosis of the contamination in apple juice, using test panel evaluation as reference. The feasibility of using e-nose responses to predict the spoilage level of apple juice was also evaluated. Coupled with linear discriminant analysis (LDA), detection of the contamination was achieved after 12h, corresponding to the cell concentration of less than 2.0 log 10 CFU/mL, the level at which the test panelists could not yet identify the contamination, indicating that the signals of e-nose could be utilized as early indicators for the onset of contamination. Loading analysis indicated that sensors 2, 6, 7 and 8 were the most important in the detection of Z. rouxii-contaminated apple juice. Moreover, Z. rouxii counts in unknown samples could be well predicted by the established models using partial least squares (PLS) algorithm with high correlation coefficient (R) of 0.98 (Z. rouxii strain ATCC 2623 and ATCC 8383) and 0.97 (Z. rouxii strain B-WHX-12-53). Based on these results, e-nose appears to be promising for rapid analysis of the odor in apple juice during processing or on the shelf to realize the early detection of potential contamination caused by Z. rouxii strains. PMID:26490651

  1. Chemometric approach to open validation protocols: Prediction of validation parameters in multi-residue ultra-high performance liquid chromatography-tandem mass spectrometry methods.

    PubMed

    Alladio, Eugenio; Pirro, Valentina; Salomone, Alberto; Vincenti, Marco; Leardi, Riccardo

    2015-06-01

    The recent technological advancements of liquid chromatography-tandem mass spectrometry allow the simultaneous determination of tens, or even hundreds, of target analytes. In such cases, the traditional approach to quantitative method validation presents three major drawbacks: (i) it is extremely laborious, repetitive and rigid; (ii) it does not allow to introduce new target analytes without starting the validation from its very beginning and (iii) it is performed on spiked blank matrices, whose very nature is significantly modified by the addition of a large number of spiking substances, especially at high concentration. In the present study, several predictive chemometric models were developed from closed sets of analytes in order to estimate validation parameters on molecules of the same class, but not included in the original training set. Retention time, matrix effect, recovery, detection and quantification limits were predicted with partial least squares regression method. In particular, iterative stepwise elimination, iterative predictors weighting and genetic algorithms approaches were utilized and compared to achieve effective variables selection. These procedures were applied to data reported in our previously validated ultra-high performance liquid chromatography-tandem mass spectrometry multi-residue method for the determination of pharmaceutical and illicit drugs in oral fluid samples in accordance with national and international guidelines. Then, the partial least squares model was successfully tested on naloxone and lormetazepam, in order to introduce these new compounds in the oral fluid validated method, which adopts reverse-phase chromatography. Retention time, matrix effect, recovery, limit of detection and limit of quantification parameters for naloxone and lormetazepam were predicted by the model and then positively compared with their corresponding experimental values. The whole study represents a proof-of-concept of chemometrics potential to

  2. Determination of metabolite profiles in tropical wines by 1H NMR spectroscopy and chemometrics.

    PubMed

    da Silva Neto, Humberto G; da Silva, João B P; Pereira, Giuliano E; Hallwass, Fernando

    2009-12-01

    Traditionally, wines are produced in temperate climate zones, with one harvest per year. Tropical wines are a new concept of vitiviniculture that is being developed, principally in Brazil. The new Brazilian frontier is located in the northeast region (São Francisco River Valley) in Pernambuco State, close to the equator, between 8 and 9 degrees S. Compared with other Brazilian and worldwide vineyards, the grapes of this region possess peculiar characteristics. The aim of this work is a preliminary study of commercial São Francisco River Valley wines, analyzing their metabolite profiles by (1)H NMR and chemometric methods. PMID:19810052

  3. Implementation of quality control methods in conjunction with chemometrics toward authentication of dairy products.

    PubMed

    Arvanitoyannis, Ioannis S; Tzouros, Nikolaos E

    2005-01-01

    The implementation of novel and accurate quality and safety control methods in conjunction with chemometrics in various fields of science, particularly in food science, showed that this combination stands for a very powerful tool for detecting food authenticity. The latter reflects both geographic origin and variety. Dairy products, in particular, have repeatedly worried the public authorities in terms of authentication regarding origin and in view of the many illnesses occasionally due to products of specific origin. Therefore, the development of a robust and reliable system endowed with this discriminatory power (varietal and/or geographic) is of great importance, both in terms of public health and consumer protection. PMID:16047492

  4. Improved chemometric methodologies for the assessment of soil carbon sequestration mechanisms

    NASA Astrophysics Data System (ADS)

    Jiménez-González, Marco A.; Almendros, Gonzalo; Álvarez, Ana M.; González-Vila, Francisco J.

    2016-04-01

    The factors involved soil C sequestration, which is reflected in the highly variable content of organic matter in the soils, are not yet well defined. Therefore, their identification is crucial for understanding Earth's biogeochemical cycle and global change. The main objective of this work is to contribute to a better qualitative and quantitative assessment of the mechanisms of organic C sequestration in the soil, using omic approaches not requiring the detailed knowledge of the structure of the material under study. With this purpose, we have carried out a series of chemometric approaches on a set of widely differing soils (35 representative ecosystems). In an exploratory phase, we used multivariate statistical models (e.g., multidimensional scaling, discriminant analysis with automatic backward variable selection…) to analyze arrays of more than 200 independent soil variables (physicochemical, spectroscopic, pyrolytic...) in order to select those factors (descriptors or proxies) that explain most of the total system variance (content and stability of the different C forms). These models showed that the factors determining the stabilization of organic material are greatly dependent on the soil type. In some cases, the molecular structure of organic matter seemed strongly correlated with their resilience, while in other soil types the organo-mineral interactions played a significant bearing on the accumulation of selectively preserved C forms. In any case, it was clear that the factors driving the resilience of organic matter are manifold and not exclusive. Consequently, in a second stage, prediction models of the soil C content and their biodegradability (laboratory incubation experiments) were carried out by massive data processing by partial least squares (PLS) regression of data from Py-GC-MS and Py-MS. In some models, PLS was applied to a matrix of 150 independent variables corresponding to major pyrolysis compounds (peak areas) from the 35 samples of whole

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

    PubMed Central

    2011-01-01

    Background Fourier transform infrared spectroscopy (FTIR) has been used as analytical tool in chemistry for many years. In addition, FTIR can also be applied as a rapid and non-invasive method to detect and identify microorganisms. The specific and fingerprint-like spectra allow - under optimal conditions - discrimination down to the species level. The aim of this study was to develop a fast and reproducible non-molecular method to differentiate pure samples of Bacillus spores originating from different species as well as to identify spores in a simple matrix, such as the clay mineral, bentonite. Results We investigated spores from pure cultures of seven different Bacillus species by FTIR in reflection or transmission mode followed by chemometrical data treatment. All species investigated (B. atrophaeus, B. brevis, B. circulans, B. lentus, B. megaterium, B. subtilis, B. thuringiensis) are typical aerobic soil-borne spore formers. Additionally, a solid matrix (bentonite) and mixtures of benonite with spores of B. megaterium at various wt/wt ratios were included in the study. Both hierarchical cluster analysis and principal component analysis of the spectra along with multidimensional scaling allowed the discrimination of different species and spore-matrix-mixtures. Conclusions Our results show that FTIR spectroscopy is a fast method for species-level discrimination of Bacillus spores. Spores were still detectable in the presence of the clay mineral bentonite. Even a tenfold excess of bentonite (corresponding to 2.1 × 1010 colony forming units per gram of mineral matrix) still resulted in an unambiguous identification of B. megaterium spores. PMID:21756333

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

    PubMed

    Li, Xiaoli; Zhang, Yuying; He, Yong

    2016-01-01

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

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

    PubMed Central

    Li, Xiaoli; Zhang, Yuying; He, Yong

    2016-01-01

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

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

    PubMed Central

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

    2014-01-01

    This paper addresses the precision in factor loadings during partial least squares (PLS) and principal components regression (PCR) of wood chemistry content from near infrared reflectance (NIR) spectra. The precision of the loadings is considered important because these estimates are often utilized to interpret chemometric models or selection of meaningful wavenumbers. Standard laboratory chemistry methods were employed on a mixed genus/species hardwood sample set. PLS and PCR, before and after 1st derivative pretreatment, was utilized for model building and loadings investigation. As demonstrated by others, PLS was found to provide better predictive diagnostics. However, PCR exhibited a more precise estimate of loading peaks which makes PCR better for interpretation. Application of the 1st derivative appeared to assist in improving both PCR and PLS loading precision, but due to the small sample size, the two chemometric methods could not be compared statistically. This work is important because to date most research works have committed to PLS because it yields better predictive performance. But this research suggests there is a tradeoff between better prediction and model interpretation. Future work is needed to compare PLS and PCR for a suite of spectral pretreatment techniques. PMID:25068863

  9. Chemometric methods for studying the relationships between trace elements in laryngeal cancer and healthy tissues.

    PubMed

    Dobrowolski, R; Klatka, J; Brodnjak-Voncina, D; Trojanowska, A; Myśliwiec, D; Ostrowski, J; Remer, M

    2014-06-01

    A quick and reliable method for the evaluation and classification of two types of tissues is presented. Several chemometric methods were applied to evaluate multivariate data of the tissue samples with respect to the content of trace elements. The content of Pb, Al, Zn, Cd, Cu, Ni and Co was determined in samples of healthy and cancerous tissue obtained from 26 patients. Determination was done at milligram/kilogram level with inductively coupled plasma optical emission spectrometry (ICP-OES) and atomic absorption spectroscopy (AAS) techniques. Contents of trace metals in studied tissues are not normally distributed; however, normal distribution was confirmed for log values. There is a statistically significant difference in the content of Zn, Cd, Cu and Al (p<0.01) and Ni and Co (p<0.05) when healthy tissue is compared to cancerous one. Correlation between contents of trace elements for studied tissues was positive; the highest was found between Zn and Cu. A chemometric methodology seems to be a promising tool for classifications of the tissue samples. PMID:24838928

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

    PubMed

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

    2016-07-20

    Multielement and stable isotope (δ(13)C, δ(15)N, δ(2)H, δ(18)O, (207)Pb/(206)Pb, and (208)Pb/(206)Pb) analyses were combined to provide a new chemometric approach to improve the discrimination between organic and conventional Brassica vegetable production. Different combinations of organic and conventional fertilizer treatments were used to demonstrate this authentication approach using Brassica chinensis planted in experimental test pots. Stable isotope analyses (δ(15)N and δ(13)C) of B. chinensis using elemental analyzer-isotope ratio mass spectrometry easily distinguished organic and chemical fertilizer treatments. However, for low-level application fertilizer treatments, this dual isotope approach became indistinguishable over time. Using a chemometric approach (combined isotope and elemental approach), organic and chemical fertilizer mixes and low-level applications of synthetic and organic fertilizers were detectable in B. chinensis and their associated soils, improving the detection limit beyond the capacity of individual isotopes or elemental characterization. LDA shows strong promise as an improved method to discriminate genuine organic Brassica vegetables from produce treated with chemical fertilizers and could be used as a robust test for organic produce authentication. PMID:27355562

  11. Classification of commercial Catuaba samples by NMR, HPLC and chemometrics.

    PubMed

    Daolio, Cristina; Beltrame, Flávio L; Ferreira, Antonio G; Cass, Quezia B; Cortez, Diógenes Aparício Garcia; Ferreira, Márcia M C

    2008-01-01

    For over a century, Catuaba has been used in Brazilian folk medicine as an aphrodisiac even though the identity of the plant material employed is often uncertain. The species recommended by the Brazilian Pharmacopeia is Anemopaegma arvense (Bignoniaceae), but many other plants, regionally known as Catuaba, are commercialised. Frequently, the quality control of such a complex system is based on chemical markers that do not supply a general idea of the system. With the advent of the metabolomics approach, a global analysis of samples becomes possible. It appears that (1)H-NMR is the most useful method for such application, since it can be used as a wide-spectrum chemical analysis technique. Unfortunately, the generated spectra is complex so a possible approach is to look at the metabolite profile as a whole using multivariate methods, for example, by application of principal component analysis (PCA). In the present paper, we describe for the first time a proton high-resolution magic angle spinning nuclear magnetic resonance ((1)H-HR-MAS NMR) method coupled with PCA for the metabolomic analysis of some commercial Catuaba samples, which provided a reduction in the time required for such analysis. A comparative study of HPLC, HR-MAS and liquid-NMR techniques is also reported. PMID:17890569

  12. Chemometric resolution of coeluting peaks of eleven antihypertensives from multiple classes in high performance liquid chromatography: a comprehensive research in human serum, health product and Chinese patent medicine samples.

    PubMed

    Zhao, Juan; Wu, Hai-Long; Niu, Jing-Fang; Yu, Yong-Jie; Yu, Li-Li; Kang, Chao; Li, Quan; Zhang, Xiao-Hua; Yu, Ru-Qin

    2012-08-01

    A novel chemometric-assisted high performance liquid chromatography method coupled with diode array detector (HPLC-DAD) was presented for the simultaneous determination of eleven antihypertensives from multiple classes in most concerned matrix systems. With the aid of second-order calibration which enables specific information of analytes to be well extracted, the heavily overlapping profiles between analytes and the coeluting interferences can be successfully separated and thus accurately quantified. A great advantage of the novel strategy lies in the fact that the analysis could be carried out with the same isocratic mobile phase (methanol/KH(2)PO(4): 58:42, v/v, pH 2.60) in a short time regardless of the changes of matrices, such as human serum, health product and Chinese patent medicine. Both qualitative and quantitative results indicate that the hybrid strategy that using HPLC-DAD coupled with second-order chemometric method would be a high performance approach for the purpose of simultaneously quantifying multiple classes of antihypertensives in complex systems. Additionally, the analytical strategy can potentially benefit drug monitoring in both therapeutic research and pharmaceutical quality control. Moreover, the accuracy and reliability of the proposed methodology has been evaluated using several statistical parameters such as root mean squared error of prediction (RMSEP), figures of merit (FOM) and reproducibility of inter-day analysis. PMID:22795572

  13. Terahertz imaging diagnostics of cancer tissues with a chemometrics technique

    NASA Astrophysics Data System (ADS)

    Nakajima, Sachiko; Hoshina, Hiromichi; Yamashita, Masatsugu; Otani, Chiko; Miyoshi, Norio

    2007-01-01

    Terahertz spectroscopic images of paraffin-embedded cancer tissues have been measured by a terahertz time domain spectrometer. For the systematic identification of cancer tumors, the principal component analysis and the clustering analysis were applied. In three of the four samples, the cancer tissue was recognized as an aggregate of the data points in the principal component plots. By the agglomerative hierarchical clustering, the data points were well categorized into cancer and the other tissues. This method can be also applied to various kinds of automatic discrimination of plural components by terahertz spectroscopic imaging.

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

    PubMed

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

    2016-06-14

    The combination of ion mobility and mass spectrometry (MS) affords significant improvements over conventional MS/MS, especially in the characterization of isomeric metabolites due to the differences in their collision cross sections (CCS). Experimentally obtained CCS values are typically matched with theoretical CCS values from Trajectory Method (TM) and/or Projection Approximation (PA) calculations. In this paper, predictive models for CCS of deprotonated phenolics were developed using molecular descriptors and chemometric tools, stepwise multiple linear regression (SMLR), principal components regression (PCR), and partial least squares regression (PLS). A total of 102 molecular descriptors were generated and reduced to 28 after employing a feature selection tool, composed of mass, topological descriptors, Jurs descriptors and shadow indices. Therefore, the generated models considered the effects of mass, 3D conformation and partial charge distribution on CCS, which are the main parameters for either TM or PA (only 3D conformation) calculations. All three techniques yielded highly predictive models for both the training (R(2)SMLR = 0.9911; R(2)PCR = 0.9917; R(2)PLS = 0.9918) and validation datasets (R(2)SMLR = 0.9489; R(2)PCR = 0.9761; R(2)PLS = 0.9760). Also, the high cross validated R(2) values indicate that the generated models are robust and highly predictive (Q(2)SMLR = 0.9859; Q(2)PCR = 0.9748; Q(2)PLS = 0.9760). The predictions were also very comparable to the results from TM calculations using modified mobcal (N2). Most importantly, this method offered a rapid (<10 min) alternative to TM calculations without compromising predictive ability. These methods could therefore be used in routine analysis and could be easily integrated to metabolite identification platforms. PMID:27181646

  15. Application of chemometrics methods with kinetic constraints for estimation of rate constants of second order consecutive reactions.

    PubMed

    Kompany-Zareh, Mohsen; Khoshkam, Maryam

    2008-05-01

    To determine the rate constants for the second order consecutive reactions of the form U + V -(k1)--> W -(k2)--> P, a number of chemometrics and hard modeling-based methods are described. The absorption spectroscopic data from the reaction were utilized for performing the analysis. Concentrations and extinctions of components were comparable, and all of them were absorbing species. The number of steps in the reaction was less than the number of absorbing species, which resulted in a rank-deficient response matrix. This can cause difficulties for some of the methods described in the literature. The standard MATLAB functions were used for determining the solutions of the differential equations as well as for finding the optimal rate constants to describe the kinetic profiles. The available knowledge about the system determines the approaches described in this paper. The knowledge includes the spectra of reactants and products, the initial concentrations, and the exact kinetics. Some of this information is sometimes not available or is hard to estimate. Multiple linear regression for fitting the kinetic parameters to the obtained concentration profiles, rank augmentation using multiple batch runs, a mixed spectral approach which treats the reaction using a pseudo species concept, and principal components regression are the four groups of methods discussed in this study. In one of the simulated datasets the spectra are quite different, and in the other one the spectra of one reactant and of the product share a high degree of overlap. Instrumental noise, sampling error are the sources of error considered. Our aim was the investigation of the relative merits of each method. PMID:18469471

  16. Spectroscopic and dynamic properties of arachidonoyl serotonin- β-lactoglobulin complex: A molecular modeling and chemometric study.

    PubMed

    Gholami, Samira; Bordbar, Abdol-Khalegh; Akvan, Nadia

    2016-09-01

    UV-Vis absorption data of β-lactoglobulin (BLG) and arachidonoyl serotonin (AA-5HT) in BLG complex were examined and analyzed using chemometrics method. Analysis of the spectral data matrices by using the multivariate curve resolution-alternating least squares (MCR-ALS) algorithm resulted to the pure concentration calculation and spectral profiles resolution of the chemical constituents and the values of (6.433±0.019)×10(4)M(-1), (4.532±0.007)×10(4)M(-1), (3.364±0.010)×10(4)M(-1) and (2.977±0.013)×10(4)M(-1) as estimated equilibrium constants at 288, 293, 298 and 303K, respectively. The number of chemical constituents involved in the interaction which was extracted by PCA method were free and bound BLG. The spontaneity of the binding process and critical role of hydrogen bonding and van der Waals interactions in stabilizing protein-ligand complex have been designated by negative values of Gibbs free energy, entropy and enthalpy changes. Molecular docking study showed that AA-5HT binds to Val(41), Leu(39), Leu(54), Ile(71), Phe(82), Asn(90), Val(92), Phe(105), Met(107), Glu(108) with the free binding energy of -37.478kJ/mol. Computational studies predicted that in spite of serotonin (5HT) which anchors to the outer surface of BLG by hydrogen bonds, AA-5HT is situated in the calyx pose and stayed there during the entire time of simulation. This binding is accompanying with no apparent influence on secondary structure and partially destabilization of tertiary structure of BLG which pointed the suitability of this protein as drug carrier for AA-5HT. PMID:27472903

  17. Simultaneous Determination of Octinoxate, Oxybenzone, and Octocrylene in a Sunscreen Formulation Using Validated Spectrophotometric and Chemometric Methods.

    PubMed

    Abdel-Ghany, Maha F; Abdel-Aziz, Omar; Ayad, Miriam F; Mikawy, Neven N

    2015-01-01

    Accurate, reliable, and sensitive spectrophotometric and chemometric methods were developed for simultaneous determination of octinoxate (OMC), oxybenzone (OXY), and octocrylene (OCR) in a sunscreen formulation without prior separation steps, including derivative ratio spectra zero crossing (DRSZ), double divisor ratio spectra derivative (DDRD), mean centering ratio spectra (MCR), and partial least squares (PLS-2). With the DRSZ technique, the UV filters could be determined in the ranges of 0.5-13.0, 0.3-9.0, and 0.5-9.0 μg/mL at 265.2, 246.6, and 261.8 nm, respectively. By utilizing the DDRD technique, UV filters could be determined in the above ranges at 237.8, 241.0, and 254.2 nm, respectively. With the MCR technique, the UV filters could be determined in the above ranges at 381.7, 383.2, and 355.6 nm, respectively. The PLS-2 technique successfully quantified the examined UV filters in the ranges of 0.5-9.3, 0.3-7.1, and 0.5-6.9 μg/mL, respectively. All the methods were validated according to the International Conference on Harmonization guidelines and successfully applied to determine the UV filters in pure form, laboratory-prepared mixtures, and a sunscreen formulation. The obtained results were statistically compared with reference and reported methods of analysis for OXY, OMC, and OCR, and there were no significant differences with respect to accuracy and precision of the adopted techniques. PMID:26525239

  18. Rapid field identification of subjects involved in firearm-related crimes based on electroanalysis coupled with advanced chemometric data treatment.

    PubMed

    Cetó, Xavier; O'Mahony, Aoife M; Samek, Izabela A; Windmiller, Joshua R; del Valle, Manel; Wang, Joseph

    2012-12-01

    We demonstrate a novel system for the detection and discrimination of varying levels of exposure to gunshot residue from subjects in various control scenarios. Our aim is to address the key challenge of minimizing the false positive identification of individuals suspected of discharging a firearm. The chemometric treatment of voltammetric data from different controls using Canonical Variate Analysis (CVA) provides several distinct clusters for each scenario examined. Multiple samples were taken from subjects in controlled tests such as secondary contact with gunshot residue (GSR), loading a firearm, and postdischarge of a firearm. These controls were examined at both bare carbon and gold-modified screen-printed electrodes using different sampling methods: the 'swipe' method with integrated sampling and electroanalysis and a more traditional acid-assisted q-tip swabbing method. The electroanalytical fingerprint of each sample was examined using square-wave voltammetry; the resulting data were preprocessed with Fast Fourier Transform (FFT), followed by CVA treatment. High levels of discrimination were thus achieved in each case over 3 classes of samples (reflecting different levels of involvement), achieving maximum accuracy, sensitivity, and specificity values of 100% employing the leave-one-out validation method. Further validation with the 'jack-knife' technique was performed, and the resulting values were in good agreement with the former method. Additionally, samples from subjects in daily contact with relevant metallic constituents were analyzed to assess possible false positives. This system may serve as a potential method for a portable, field-deployable system aimed at rapidly identifying a subject who has loaded or discharged a firearm to verify involvement in a crime, hence providing law enforcement personnel with an invaluable forensic tool in the field. PMID:23121395

  19. Pyrohydrolytic determination of fluorine in coal: a chemometric approach.

    PubMed

    Sredović, I; Rajaković, Lj

    2010-05-15

    Corrosion effects in thermal power plants and environmental impact cause an increase in demand for fluorine analysis in coal. Solid sample decomposition, organic and inorganic fluorine compounds, volatility of fluorine species are problems which deserve a special attention. The aim of this work was to optimize the pyrohydrolytic (Phy) determination of fluorine content in the lignite coal. The parameters of pyrohydrolysis were evaluated and optimized by two statistical methods: Plackett-Burman (PB) design and response surface methodology (RSM). The content of fluorine in the absorption solution was measured by fluoride ion-selective electrode. The limit of detection of the proposed method was 20 microg g(-1), with good recovery (95%) and relative standard deviation less than 5%. With such benefits as simplicity, precision, accuracy and economy, this method is highly suitable for routine analysis of coal. PMID:20060216

  20. APPLICATION OF CHEMOMETRICS FOR IDENTIFICATION OF PSYCHOACTIVE PLANTS.

    PubMed

    Kowalczuk, Anna Paulina; Łozak, Anna; Kiljan, Monika; Mętrak, Krystyna; Zjawiony, Jordan Kordian

    2015-01-01

    Drug market changes dynamically causing many analytical challenges for police experts. Among illicit substances there are synthetic designer products but also herbal material. Plant material is usually in fine-cut or powdered form, thus difficult to identify. For such fragmented material classic taxonomical identification methods using anatomical and morphological features of the plant cannot be employed. The aim of the study was to develop an identification method of the powdered material with employment of multidimensional data analysis techniques. Principal Component Analysis (PCA) was chosen as a method of data exploration. The study was conducted on four plants controlled in Poland: Salvia divinorum, Mitragyna speciosa, Psychotria viridis and Calea zacatechichi. The compatibility of grouping features of selected species was compared in two variants: chemical and elemental composition. In a first variant, GC-MS chromatograms of extracts were analyzed and in the second, elements composition with the AAS and the ICP-MS techniques. The GC-MS method, based on the qualitative interpretation of results, allows for clear differentiation of samples with regard to their species affiliation. Even the plants belonging to the same family Rubiaceae, P. viridis and M. speciosa formed homogeneous and clearly separated clusters. Additionally, the cluster analysis was performed, as a method confirming sample grouping. PMID:26642660

  1. Evaluation of phytochemical composition of fresh and dried raw material of introduced Chamerion angustifolium L. using chromatographic, spectrophotometric and chemometric techniques.

    PubMed

    Kaškonienė, Vilma; Stankevičius, Mantas; Drevinskas, Tomas; Akuneca, Ieva; Kaškonas, Paulius; Bimbiraitė-Survilienė, Kristina; Maruška, Audrius; Ragažinskienė, Ona; Kornyšova, Olga; Briedis, Vitalis; Ugenskienė, Rasa

    2015-07-01

    Due to the wide spectrum of biological activities, Chamerion angustifolium L. as medicinal plant is used for the production of food supplements. However, it should be kept in mind that quality (biological activity) of the herb depends on its geographic origin, the way of raw material preparation or extraction and chemotype. The purpose of this study was to evaluate and compare the compositions of volatile, non-volatile compounds and antioxidant activities of C. angustifolium grown in Kaunas Botanical Garden after the introduction from different locations in Lithuania. The compositions of fresh and air-dried samples were compared. The profile of volatile compounds was analyzed using headspace solid phase microextraction coupled with GC/MS. trans-2-Hexenal (16.0-55.9% of all volatiles) and trans-anethole (2.6-46.2%) were determined only in the dried samples, while cis-3-hexenol (17.5-68.6%) only in fresh samples. Caryophyllenes (α- and β-) were found in all analyzed samples, contributing together from 2.4% to 52.3% of all volatiles according to the origin and preparation (fresh or dried) of a sample. Total amount of phenolic compounds, total content of flavonoids and radical scavenging activity (using 2,2-diphenyl-1-picrylhydrazyl (DPPH)) were determined using spectrophotometric assays. The variation of total phenolic compounds content was dependent on the sample origin, moreover, drying reduced amount of phenolics 1.5-3.5 times. The DPPH free radical scavenging activity was in the range of 238.6-557.1mg/g (expressed in rutin equivalents) in the fresh samples and drastically reduced to 119.9-124.8 mg/g after drying. The qualitative analysis of phenolic compounds in the aqueous methanolic extracts of C. angustifolium was performed by means of HPLC with UV detection. Oenothein B and rutin were predominant in the samples; also caffeic and chlorogenic acids, and quercetin were determined. Chemometric methods, namely principal component analysis, hierarchical cluster

  2. Soil VisNIR chemometric performance statistics should be interpreted as random variables

    NASA Astrophysics Data System (ADS)

    Brown, David J.; Gasch, Caley K.; Poggio, Matteo; Morgan, Cristine L. S.

    2015-04-01

    Chemometric models are normally evaluated using performance statistics such as the Standard Error of Prediction (SEP) or the Root Mean Squared Error of Prediction (RMSEP). These statistics are used to evaluate the quality of chemometric models relative to other published work on a specific soil property or to compare the results from different processing and modeling techniques (e.g. Partial Least Squares Regression or PLSR and random forest algorithms). Claims are commonly made about the overall success of an application or the relative performance of different modeling approaches assuming that these performance statistics are fixed population parameters. While most researchers would acknowledge that small differences in performance statistics are not important, rarely are performance statistics treated as random variables. Given that we are usually comparing modeling approaches for general application, and given that the intent of VisNIR soil spectroscopy is to apply chemometric calibrations to larger populations than are included in our soil-spectral datasets, it is more appropriate to think of performance statistics as random variables with variation introduced through the selection of samples for inclusion in a given study and through the division of samples into calibration and validation sets (including spiking approaches). Here we look at the variation in VisNIR performance statistics for the following soil-spectra datasets: (1) a diverse US Soil Survey soil-spectral library with 3768 samples from all 50 states and 36 different countries; (2) 389 surface and subsoil samples taken from US Geological Survey continental transects; (3) the Texas Soil Spectral Library (TSSL) with 3000 samples; (4) intact soil core scans of Texas soils with 700 samples; (5) approximately 400 in situ scans from the Pacific Northwest region; and (6) miscellaneous local datasets. We find the variation in performance statistics to be surprisingly large. This has important

  3. Antioxidant Characterization of Oak Extracts Combining Spectrophotometric Assays and Chemometrics

    PubMed Central

    Popović, Boris M.; Štajner, Dubravka; Orlović, Saša; Galić, Zoran

    2013-01-01

    Antioxidant characteristics of leaves, twigs, and acorns from two Serbian oak species Quercus robur L. and Quercus petraea L. from Vojvodina province (northern Serbia) were investigated. 80% ethanol (in water) extracts were used for antiradical power (ARP) determinations against DPPH•, •NO, and O2•− radicals, ferric reducing antioxidant power (FRAP), total phenol, tannin, flavonoid, and proanthocyanidin contents. Permanganate reducing antioxidant capacity (PRAC) was determined using water extracts. Beside, mentioned parameters, soluble proteins, lipid peroxidation (LP), pigments and proline contents were also determined. The data of different procedures were compared and analyzed by multivariate techniques (correlation matrix calculation and principal component analysis (PCA)). PCA found that investigated organs of two different oak tree species possess similar antioxidant characteristics. The superior antioxidant characteristics showed oak leaves over twigs and acorns and seem to be promising source of antioxidants with possible use in industry and pharmacy. PMID:24453789

  4. Using chemometrics to evaluate anthropogenic effects in Daya Bay, China

    NASA Astrophysics Data System (ADS)

    Wu, Mei-Lin; Wang, You-Shao

    2007-05-01

    In this work, we have monitored 12 stations to study the effects caused by natural, marine and anthropogenic activities on water quality in Daya Bay, China. Results show that the N:P ratios are 71.54, 41.29, 81.50 and 98.27 in winter, spring, summer and autumn, respectively. Compared with the data of the past 20 years, the atomic N:P ratios have increased, indicating increased potential for P limitation; the atomic Si:N ratios have decreased; the nutrient structure has substantially changed over a period of 20 years. These findings show that the nutrient structure may be related to anthropogenic influence. The data matrix has been built according to the results, which were analyzed by principal component analysis (PCA). This analysis extracted the first four principal components (PC), explaining 73.58% of the total variance of the raw data. PC1 (25.53% of the variance) is associated with temperature, salinity and nitrate. PC2 (21.64% of the variance) is characterized by dissolved oxygen and silicate. PC3 (15.91% of the variance) participates mainly by nitrite (NO 2-N) and ammonia (NH 4-N). PC4 explaining 10.50% of the variance is mainly contributed by parameters of organic pollution (dissolved oxygen, 5-day biochemical oxygen demand and chemical oxygen demand). PCA has found the important factors that can describe the natural, marine and anthropogenic influences. Temperature and salinity are important indicators of natural and marine characters in this bay. The northeast monsoons from October to April and southwest monsoons from May to September have important effects on the waters in Daya Bay. It has been demonstrated that anthropogenic activities have significant influence on nitrogen form character. In spatial pattern, a marine aquaculture area and a non-aquaculture area are widely identified by the scores of stations. In seasonal pattern, dry and wet season characters have been demonstrated.

  5. Partial Least-Squares and Linear Support Vector Regression Chemometric Methods for Simultaneous Determination of Amoxicillin Trihydrate and Dicloxacillin Sodium in the Presence of Their Common Impurity.

    PubMed

    Naguib, Ibrahim A; Abdelaleem, Eglal A; Zaazaa, Hala E; Hussein, Essraa A

    2016-07-01

    Two multivariate chemometric models, namely, partial least-squares regression (PLSR) and linear support vector regression (SVR), are presented for the analysis of amoxicillin trihydrate and dicloxacillin sodium in the presence of their common impurity (6-aminopenicillanic acid) in raw materials and in pharmaceutical dosage form via handling UV spectral data and making a modest comparison between the two models, highlighting the advantages and limitations of each. For optimum analysis, a three-factor, four-level experimental design was established, resulting in a training set of 16 mixtures containing different ratios of interfering species. To validate the prediction ability of the suggested models, an independent test set consisting of eight mixtures was used. The presented results show the ability of the two proposed models to determine the two drugs simultaneously in the presence of small levels of the common impurity with high accuracy and selectivity. The analysis results of the dosage form were statistically compared to a reported HPLC method, with no significant difference regarding accuracy and precision, indicating the ability of the suggested multivariate calibration models to be reliable and suitable for routine analysis of the drug product. Compared to the PLSR model, the SVR model gives more accurate results with a lower prediction error, as well as high generalization ability; however, the PLSR model is easy to handle and fast to optimize. PMID:27305461

  6. Relationships between 1H NMR Relaxation Data and Some Technological Parameters of Meat: A Chemometric Approach

    NASA Astrophysics Data System (ADS)

    Brown, Robert J. S.; Capozzi, Francesco; Cavani, Claudio; Cremonini, Mauro A.; Petracci, Massimiliano; Placucci, Giuseppe

    2000-11-01

    In this paper chemometrics (ANOVA and PCR) is used to measure unbiased correlations between NMR spin-echo decays of pork M. Longissimus dorsi obtained through Carr-Purcell-Meiboom-Gill (CPMG) experiments at low frequency (20 MHz) and the values of 14 technological parameters commonly used to assess pork meat quality. On the basis of the ANOVA results, it is also found that the CPMG decays of meat cannot be best interpreted with a "discrete" model (i.e., by expanding the decays in a series of a discrete number of exponential components, each with a different transverse relaxation time), but rather with a "continuous" model, by which a continuous distribution of T2's is allowed. The latter model also agrees with literature histological results.

  7. Quantification of Pharmaceutical Compounds Based on Powder X-Ray Diffraction with Chemometrics.

    PubMed

    Otsuka, Yuta; Ito, Akira; Matsumura, Saki; Takeuchi, Masaki; Pal, Suvra; Tanaka, Hideji

    2016-01-01

    We propose an approach for the simultaneous determination of multiple components in pharmaceutical mixed powder based on powder X-ray diffraction (PXRD) method coupled with chemometrics. Caffeine anhydrate, acetaminophen and lactose monohydrate were mixed at various ratios. The samples were analyzed by PXRD method in the ranges of 2θ=5.00-30.0 and 35.0-45.0 degrees. Obtained diffractograms were analyzed by conventional peak intensity method, multi curve resolution (MCR)-alternating least squares (ALS) method and partial least squares (PLS) method. Constructed PLS models can most accurately predict the concentrations among different methods used. Each regression vector of PLS correlates not only to the compound of interest but also to the coexisting compounds. The combination of PXRD and PLS methods is concluded to be powerful approach for analyzing multi components in pharmaceutical formulations. PMID:27477651

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

    PubMed

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

    2016-01-01

    A combination of Fourier transform infrared spectroscopy with chemometrics tools provided an approach for studying Marsdenia tenacissima according to its geographical origin. A total of 128 M. tenacissima samples from four provinces in China were analyzed with FTIR spectroscopy. Six pattern recognition methods were used to construct the discrimination models: support vector machine-genetic algorithms, support vector machine-particle swarm optimization, K-nearest neighbors, radial basis function neural network, random forest and support vector machine-grid search. Experimental results showed that K-nearest neighbors was superior to other mathematical algorithms after data were preprocessed with wavelet de-noising, with a discrimination rate of 100% in both the training and prediction sets. This study demonstrated that FTIR spectroscopy coupled with K-nearest neighbors could be successfully applied to determine the geographical origins of M. tenacissima samples, thereby providing reliable authentication in a rapid, cheap and noninvasive way. PMID:26233789

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

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

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

  10. Discriminating olive and non-olive oils using HPLC-CAD and chemometrics.

    PubMed

    de la Mata-Espinosa, P; Bosque-Sendra, J M; Bro, R; Cuadros-Rodríguez, L

    2011-02-01

    This work presents a method for an efficient differentiation of olive oil and several types of vegetable oils using chemometric tools. Triacylglycerides (TAGs) profiles of 126 samples of different categories and varieties of olive oils, and types of edible oils, including corn, sunflower, peanut, soybean, rapeseed, canola, seed, sesame, grape seed, and some mixed oils, have been analyzed. High-performance liquid chromatography coupled to a charged aerosol detector was used to characterize TAGs. The complete chromatograms were evaluated by PCA, PLS-DA, and MCR in combination with suitable preprocessing. The chromatographic data show two clusters; one for olive oil samples and another for the non-olive oils. Commercial oil blends are located between the groups, depending on the concentration of olive oil in the sample. As a result, a good classification among olive oils and non-olive oils and a chemical justification of such classification was achieved. PMID:21060998

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

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

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

    USGS Publications Warehouse

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

    2013-01-01

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

  13. Improving the performance of hollow waveguide-based infrared gas sensors via tailored chemometrics.

    PubMed

    Perez-Guaita, David; Wilk, Andreas; Kuligowski, Julia; Quintás, Guillermo; de la Guardia, Miguel; Mizaikoff, Boris

    2013-10-01

    The use of chemometrics in order to improve the molecular selectivity of infrared (IR) spectra has been evaluated using classic least squares (CLS), partial least squares (PLS), science-based calibration (SBC), and multivariate curve resolution-alternate least squares (MCR-ALS) techniques for improving the discriminatory and quantitative performance of infrared hollow waveguide gas sensors. Spectra of mixtures of isobutylene, methane, carbon dioxide, butane, and cyclopropane were recorded, analyzed, and validated for optimizing the prediction of associated concentrations. PLS, CLS, and SBC provided equivalent results in the absence of interferences. After addition of the spectral characteristics of water by humidifying the sample mixtures, CLS and SBC results were similar to those obtained by PLS only if the water spectrum was included in the calibration model. In the presence of an unknown interferant, CLS revealed errors up to six times higher than those obtained by PLS. However, SBC provided similar results compared to PLS by adding a measured noise matrix to the model. Using MCR-ALS provided an excellent estimation of the spectra of the unknown interference. Furthermore, this method also provided a qualitative and quantitative estimation of the components of an unknown set of samples. In summary, using the most suitable chemometrics approach could improve the selectivity and quality of the calibration model derived for a sensor system, and may avoid the need to analyze expensive calibration data sets. The results obtained in the present study demonstrated that (1) if all sample components of the system are known, CLS provides a sufficiently accurate solution; (2) the selection between PLS and SBC methods depends on whether it is easier to measure a calibration data set or a noise matrix; and (3) MCR-ALS appears to be the most suitable method for detecting interferences within a sample. However, the latter approach requires the most extensive calculations and

  14. Chemometric analysis of infrared emission spectra for quantitative analysis of BPSG films on silicon

    SciTech Connect

    Franke, J.E.; Chen, Chuenyuan S.; Zhang, Songbaio; Niemczyk, T.M.; Haaland, D.M.

    1993-11-01

    Infrared emission spectra of 21 borophosphosilicate glass (BPSG) thin films on silicon wafers were collected with the samples held at constant temperature between 125--400{degree}C using a heating stage designed for precise temperature control ({plus_minus}{degree}C). Partial test squares calibrations applied to the BPSG infrared emittance spectra allowed four BPSG thin-film properties to be simultaneously quantified with precisions of 0.1 wt. % for boron and phosphorus, 35 {Angstrom} for film thickness, and 1.2{degree}C for temperature.

  15. Joint NMR and Solid-Phase Microextraction-Gas Chromatography Chemometric Approach for Very Complex Mixtures: Grape and Zone Identification in Wines.

    PubMed

    Martin-Pastor, Manuel; Guitian, Esteban; Riguera, Ricardo

    2016-06-21

    In very complex mixtures, classification by chemometric methods may be limited by the difficulties to extract from the NMR or gas chromatography/mass spectrometry (GC/MS) experimental data information useful for a reliable classification. The joint analysis of both data has showed its superiority in the biomedical field but is scarcely used in foodstuffs and never in wine in spite of the complexity of their spectra and classification. In this article we show that univariate and multivariate principal component analysis-discriminant analysis (PCA-DA) statistics applied to the combined (1)H NMR and solid-phase microextraction-gas chromatography (SPME-GC) data of a collection of 270 wines from Galicia (northwest Spain) allows a discrimination and classification not attainable from the separate data, distinguishing wines from autochthonous and nonautochthonous grapes, mono- from the plurivarietals, and identifying, in part, the geographical subzone of origin of the albariño wines. A general and automatable protocol, based on the signal integration of selected ROIs (regions of interest), is proposed that allows the fast and reliable identification of the grape in Galician wines. PMID:27247992

  16. Combining chromatography and chemometrics for the characterization and authentication of fats and oils from triacylglycerol compositional data--a review.

    PubMed

    Bosque-Sendra, Juan M; Cuadros-Rodríguez, Luis; Ruiz-Samblás, Cristina; de la Mata, A Paulina

    2012-04-29

    The characterization and authentication of fats and oils is a subject of great importance for market and health aspects. Identification and quantification of triacylglycerols in fats and oils can be excellent tools for detecting changes in their composition due to the mixtures of these products. Most of the triacylglycerol species present in either fats or oils could be analyzed and identified by chromatographic methods. However, the natural variability of these samples and the possible presence of adulterants require the application of chemometric pattern recognition methods to facilitate the interpretation of the obtained data. In view of the growing interest in this topic, this paper reviews the literature of the application of exploratory and unsupervised/supervised chemometric methods on chromatographic data, using triacylglycerol composition for the characterization and authentication of several foodstuffs such as olive oil, vegetable oils, animal fats, fish oils, milk and dairy products, cocoa and coffee. PMID:22483203

  17. Spectroscopic-Based Chemometric Models for Quantifying Low Levels of Solid-State Transitions in Extended Release Theophylline Formulations.

    PubMed

    Korang-Yeboah, Maxwell; Rahman, Ziyaur; Shah, Dhaval A; Khan, Mansoor A

    2016-01-01

    Variations in the solid state form of a pharmaceutical solid have profound impact on the product quality and clinical performance. Quantitative models that allow rapid and accurate determination of polymorphic changes in pharmaceutical products are essential in ensuring product quality throughout its lifecycle. This study reports the development and validation of chemometric models of Raman and near infrared spectroscopy (NIR) for quantifying the extent of pseudopolymorphic transitions of theophylline in extended release formulations. The chemometric models were developed using sample matrices consisting of the commonly used excipients and at the ratios in commercially available products. A combination of scatter removal (multiplicative signal correction and standard normal variate) and derivatization (Savitzky-Golay second derivative) algorithm were used for data pretreatment. Partial least squares and principal component regression models were developed and their performance assessed. Diagnostic statistics such as the root mean square error, correlation coefficient, bias and Q(2) were used as parameters to test the model fit and performance. The models developed had a good fit and performance as shown by the values of the diagnostic statistics. The model diagnostic statistics were similar for MSC-SG and SNV-SG treated spectra. Similarly, PLSR and PCR models had comparable performance. Raman chemometric models were slightly better than their corresponding NIR model. The Raman and NIR chemometric models developed had good accuracy and precision as demonstrated by closeness of the predicted values for the independent observations to the actual TMO content hence the developed models can serve as useful tools in quantifying and controlling solid state transitions in extended release theophylline products. PMID:26852844

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

    PubMed

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

    2016-01-01

    Analysis of phenolic profile and tocopherol fractions in conjunction with chemometrics techniques were used for the accurate characterization of extra virgin argan oil and eight other edible vegetable virgin oils (olive, soybean, wheat germ, walnut, almond, sesame, avocado, and linseed) and to establish similarities among them. Phenolic profile and tocopherols were determined by HPLC coupled with diode-array and fluorescence detectors, respectively. Multivariate factor analysis (MFA) and linear correlations were applied. Significant negative correlations were found between tocopherols and some of the polyphenols identified, but more intensely (P < 0.001) between the γ-tocopherol and oleuropein, pinoresinol, and luteolin. MFA revealed that tocopherols, especially γ-fraction, most strongly influenced the oil characterization. Among the phenolic compounds, syringic acid, dihydroxybenzoic acid, oleuropein, pinoresinol, and luteolin also contributed to the discrimination of the oils. According to the variables analyzed in the present study, argan oil presented the greatest similarity with walnut oil, followed by sesame and linseed oils. Olive, avocado, and almond oils showed close similarities. PMID:26953066

  19. Comparative determination of polymorphs of indomethacin in powders and tablets by chemometrical near-infrared spectroscopy and x-ray powder diffractometry.

    PubMed

    Otsuka, Makoto; Kato, Fumie; Matsuda, Yoshihisa; Ozaki, Yukihiro

    2003-01-01

    The purpose of this research was to develop a rapid chemometrical method based on near-infrared (NIR) spectroscopy to determine indomethacin (IMC) polymorphic content in mixed pharmaceutical powder and tablets. Mixed powder samples with known polymorphic contents of forms alpha and gamma were obtained from physical mixing of 50% of IMC standard polymorphic sample and 50% of excipient mixed powder sample consisting of lactose, corn starch, and hydroxypropylcellulose. The tablets were obtained by compressing the mixed powder at 245 MPa. X-ray powder diffraction profiles and NIR spectra were recorded for 6 kinds of standard materials with various polymorphic contents. The principal component regression analysis was performed based on normalized NIR spectra sets of mixed powder standard samples and tablets. The relationships between the actual and predicted polymorphic contents of form g in the mixed powder measured using x-ray powder diffraction and NIR spectroscopy show a straight line with a slope of 0.960 and 0.995, and correlation coefficient constants of 0.970 and 0.993, respectively. The predicted content values of unknown samples by x-ray powder diffraction and NIR spectroscopy were reproducible and in close agreement, but those by NIR spectroscopy had smaller SDs than those by x-ray powder diffraction. The results suggest that NIR spectroscopy provides a more accurate quantitative analysis of polymorphic content in pharmaceutical mixed powder and tablets than does conventional x-ray powder diffractometry. PMID:12916901

  20. Relationship between geographical origin and contents of Pb, Cd, and Cr in honey samples from the state of Paraná (Brazil) with chemometric approach.

    PubMed

    de Andrade, Camila Kulek; dos Anjos, Vanessa Egéa; Felsner, Maria Lurdes; Torres, Yohandra Reyes; Quináia, Sueli Pércio

    2014-11-01

    The aim of this study was to determine the trace elements, Pb, Cd, and Cr in honey samples from eight different regions from the state of Paraná (Brazil), using slurry sampling graphite furnace atomic absorption spectrometry. Chemometric analysis (principal component analysis (PCA)) was applied to classify honey samples according to their levels of the trace elements Pb, Cd, and Cr, which is also related to the geographical origin of honey samples. The mean concentration for the elements followed the order Pb > Cr > > Cd. The mean values were 200 ± 76, 88 ± 14, and 4.1 ± 4 ng g(-1) for Pb, Cr, and Cd, respectively. It could be verified that honey samples are geographically separated, especially with regard to Pb and Cd contents. Thus, honey can be considered a bioindicator of environmental contamination, suggesting possible contamination in soil, water, and air. This contamination can be related to natural or anthropogenic sources present in the study regions. PMID:24938816

  1. Orthogonal array design as a chemometric method for the optimization of analytical procedures. Part 5. Three-level design and its application in microwave dissolution of biological samples.

    PubMed

    Lan, W G; Wong, M K; Chen, N; Sin, Y M

    1995-04-01

    The theory and methodology of a three-level orthogonal array design as a chemometric method for the optimization of analytical procedures were developed. In the theoretical section, firstly, the matrix of a three-level orthogonal array design is described and orthogonality is proved by a quadratic regression model. Next, the assignment of experiments in a three-level orthogonal array design and the use of the triangular table associated with the corresponding orthogonal array matrix are illustrated, followed by the data analysis strategy, in which significance of the different factor effects is quantitatively evaluated by the analysis of variance (ANOVA) technique and the percentage contribution method. Then, a quadratic regression equation representing the response surface is established to estimate each factor that has a significant influence. Finally, on the basis of the quadratic regression equation established, the derivative algorithm is used to find the optimum value for each variable considered. In the application section, microwave dissolution for the determination of selenium in biological samples by hydride generation atomic absorption spectrometry is employed, as a practical example, to demonstrate the application of the proposed three-level orthogonal array design in analytical chemistry. PMID:7771675

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

    PubMed

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

    2017-01-15

    High Performance Liquid Chromatography (HPLC) with diode array (DAD) and fluorescence (FLD) detection was used to acquire the fingerprints of the phenolic fraction of monovarietal extra-virgin olive oils (extra-VOOs) collected over three consecutive crop seasons (2011/2012-2013/2014). The chromatographic fingerprints of 140 extra-VOO samples processed from olive fruits of seven olive varieties, were recorded and statistically treated for varietal authentication purposes. First, DAD and FLD chromatographic-fingerprint datasets were separately processed and, subsequently, were joined using "Low-level" and "Mid-Level" data fusion methods. After the preliminary examination by principal component analysis (PCA), three supervised pattern recognition techniques, Partial Least Squares Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogies (SIMCA) and K-Nearest Neighbors (k-NN) were applied to the four chromatographic-fingerprinting matrices. The classification models built were very sensitive and selective, showing considerably good recognition and prediction abilities. The combination "chromatographic dataset+chemometric technique" allowing the most accurate classification for each monovarietal extra-VOO was highlighted. PMID:27542473

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

    PubMed

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

    2016-04-01

    FT-Raman spectroscopy has been explored as a quick screening method to evaluate the presence of lactose and identify milk powder samples adulterated with maltodextrin (2.5-50% w/w). Raman measurements can easily differentiate samples of milk powder, without the need for sample preparation, while traditional quality control methods, including high performance liquid chromatography, are cumbersome and slow. FT-Raman spectra were obtained from samples of whole lactose and low-lactose milk powder, both without and with addition of maltodextrin. Differences were observed between the spectra involved in identifying samples with low lactose content, as well as adulterated samples. Exploratory data analysis using Raman spectroscopy and multivariate analysis was also developed to classify samples with PCA and PLS-DA. The PLS-DA models obtained allowed to correctly classify all samples. These results demonstrate the utility of FT-Raman spectroscopy in combination with chemometrics to infer about the quality of milk powder. PMID:26593531

  4. Multivariate concentration determination using principal component regression with residual analysis

    PubMed Central

    Keithley, Richard B.; Heien, Michael L.; Wightman, R. Mark

    2009-01-01

    Data analysis is an essential tenet of analytical chemistry, extending the possible information obtained from the measurement of chemical phenomena. Chemometric methods have grown considerably in recent years, but their wide use is hindered because some still consider them too complicated. The purpose of this review is to describe a multivariate chemometric method, principal component regression, in a simple manner from the point of view of an analytical chemist, to demonstrate the need for proper quality-control (QC) measures in multivariate analysis and to advocate the use of residuals as a proper QC method. PMID:20160977

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

    PubMed

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

    2015-11-01

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

  6. Identification and quantification of turkey meat adulteration in fresh, frozen-thawed and cooked minced beef by FT-NIR spectroscopy and chemometrics.

    PubMed

    Alamprese, Cristina; Amigo, José Manuel; Casiraghi, Ernestina; Engelsen, Søren Balling

    2016-11-01

    This work aims at the development of a method based on FT-NIR spectroscopy and multivariate analysis for the identification and quantification of minced beef meat adulteration with turkey meat. Samples were analyzed as raw, frozen-thawed and cooked. Different multivariate regression and class-modeling strategies were evaluated. PLS regression models with R(2) in prediction higher than 0.884 and RMSEP lower than 10.8% were developed. PLS-DA applied to discriminate each type of sample in two classes (adulteration threshold=20%) showed values of sensitivity and specificity in prediction higher than 0.84 and 0.76, respectively. Thus, the study demonstrates that FT-NIR spectroscopy coupled with suitable chemometric strategies is a reliable tool for the identification and quantification of minced beef adulteration with turkey meat not only in fresh products, but also in frozen-thawed and cooked samples. This achievement is of crucial importance in the meat industry due to the increasing number of processed meat products, in which technological treatments can mask a possible inter-species adulteration. PMID:27337677

  7. Rapid discrimination of pork in Halal and non-Halal Chinese ham sausages by Fourier transform infrared (FTIR) spectroscopy and chemometrics.

    PubMed

    Xu, L; Cai, C B; Cui, H F; Ye, Z H; Yu, X P

    2012-12-01

    Rapid discrimination of pork in Halal and non-Halal Chinese ham sausages was developed by Fourier transform infrared (FTIR) spectrometry combined with chemometrics. Transmittance spectra ranging from 400 to 4000 cm⁻¹ of 73 Halal and 78 non-Halal Chinese ham sausages were measured. Sample preparation involved finely grinding of samples and formation of KBr disks (under 10 MPa for 5 min). The influence of data preprocessing methods including smoothing, taking derivatives and standard normal variate (SNV) on partial least squares discriminant analysis (PLSDA) and least squares support vector machine (LS-SVM) was investigated. The results indicate removal of spectral background and baseline plays an important role in discrimination. Taking derivatives, SNV can improve classification accuracy and reduce the complexity of PLSDA. Possibly due to the loss of detailed high-frequency spectral information, smoothing degrades the model performance. For the best models, the sensitivity and specificity was 0.913 and 0.929 for PLSDA with SNV spectra, 0.957 and 0.929 for LS-SVM with second derivative spectra, respectively. PMID:22726700

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

    PubMed

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

    2016-07-01

    Avocado oil is a high-value and nutraceutical oil whose authentication is very important since the addition of low-cost oils could lower its beneficial properties. Mid-FTIR spectroscopy combined with chemometrics was used to detect and quantify adulteration of avocado oil with sunflower and soybean oils in a ternary mixture. Thirty-seven laboratory-prepared adulterated samples and 20 pure avocado oil samples were evaluated. The adulterated oil amount ranged from 2% to 50% (w/w) in avocado oil. A soft independent modelling class analogy (SIMCA) model was developed to discriminate between pure and adulterated samples. The model showed recognition and rejection rate of 100% and proper classification in external validation. A partial least square (PLS) algorithm was used to estimate the percentage of adulteration. The PLS model showed values of R(2) > 0.9961, standard errors of calibration (SEC) in the range of 0.3963-0.7881, standard errors of prediction (SEP estimated) between 0.6483 and 0.9707, and good prediction performances in external validation. The results showed that mid-FTIR spectroscopy could be an accurate and reliable technique for qualitative and quantitative analysis of avocado oil in ternary mixtures. PMID:27314226

  9. Determination of Nicotine in Tobacco by Chemometric Optimization and Cation-Selective Exhaustive Injection in Combination with Sweeping-Micellar Electrokinetic Chromatography

    PubMed Central

    Lin, Yi-Hui; Feng, Chia-Hsien; Wang, Shih-Wei; Ko, Po-Yun; Lee, Ming-Hsun; Chen, Yen-Ling

    2015-01-01

    Nicotine is a potent chemical that excites the central nervous system and refreshes people. It is also physically addictive and causes dependence. To reduce the harm of tobacco products for smokers, a law was introduced that requires tobacco product containers to be marked with the amount of nicotine as well as tar. In this paper, an online stacking capillary electrophoresis (CE) method with cation-selective exhaustive injection sweeping-micellar electrokinetic chromatography (CSEI-sweeping-MEKC) is proposed for the optimized analysis of nicotine in tobacco. A higher conductivity buffer (160 mM phosphate buffer (pH 3)) zone was injected into the capillary, allowing for the analytes to be electrokinetically injected at a voltage of 15 kV for 15 min. Using 50 mM sodium dodecyl sulfate and 25% methanol in the sweeping buffer, nicotine was detected with high sensitivity. Thus, optimized conditions adapted from a chemometric approach provided a 6000-fold increase in the nicotine detection sensitivity using the CSEI-sweeping-MEKC method in comparison to normal CZE. The limits of detection were 0.5 nM for nicotine. The stacking method in combination with direct injection which matrix components would not interfere with assay performance was successfully applied to the detection of nicotine in tobacco samples. PMID:26101695

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

    PubMed

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

    2015-09-01

    Speciation, i.e. identification and quantification, of surface species on heterogeneous surfaces by infrared spectroscopy is important in many fields but remains a challenging task when facing strongly overlapped spectra of multiple adspecies. Here, we propose a new methodology, combining state of the art instrumental developments for quantitative infrared spectroscopy of adspecies and chemometrics tools, mainly a novel data processing algorithm, called SORB-MCR (SOft modeling by Recursive Based-Multivariate Curve Resolution) and multivariate calibration. After formal transposition of the general linear mixture model to adsorption spectral data, the main issues, i.e. validity of Beer-Lambert law and rank deficiency problems, are theoretically discussed. Then, the methodology is exposed through application to two case studies, each of them characterized by a specific type of rank deficiency: (i) speciation of physisorbed water species over a hydrated silica surface, and (ii) speciation (chemisorption and physisorption) of a silane probe molecule over a dehydrated silica surface. In both cases, we demonstrate the relevance of this approach which leads to a thorough surface speciation based on comprehensive and fully interpretable multivariate quantitative models. Limitations and drawbacks of the methodology are also underlined. PMID:26388366

  11. Chemometrical classification of pumpkin seed oils using UV-Vis, NIR and FTIR spectra.

    PubMed

    Lankmayr, Ernst; Mocak, Jan; Serdt, Katja; Balla, Branko; Wenzl, Thomas; Bandoniene, Donata; Gfrerer, Marion; Wagner, Siegfried

    2004-10-29

    The main outcome of this work is elaboration of classification models for edible oil samples representing the most widespread brands of Austrian pumpkin seed oil. A complete spectral characterisation of the pumpkin seed oil samples by UV-Vis, NIR and FTIR spectra was obtained together with their basic sensorial classification. Chemometrical processing of the measured data enabled the detection of the most important spectral features, which are crucial for categorising the oils into two or three classes according to their sensory quality evaluated by a panel of experts. The elaborated models thus make it possible to predict the category into which a hitherto unclassified oil sample belongs--considering classification into either two categories, containing oils with overall acceptable scores or oils that were not accepted, or three categories, involving oils fulfilling all quality criteria, oils with good scores and not accepted oils. This will perspectively facilitate the determination of chemical substances responsible for bad taste, odour and colour of the respective oil brands, as well as finding substances contributing to the excellent sensorial perception of some tested products. PMID:15560925

  12. A simplified FTIR chemometric method for simultaneous determination of four oxidation parameters of frying canola oil.

    PubMed

    Talpur, M Younis; Hassan, S Sara; Sherazi, S T H; Mahesar, S A; Kara, Huseyin; Kandhro, Aftab A; Sirajuddin

    2015-01-01

    Transmission Fourier transform infrared (FTIR) spectroscopic method using 100 μm KCl cell was applied for the determination of total polar compounds (TPC), carbonyl value (CV), conjugated diene (CD) and conjugated triene (CT) in canola oil (CLO) during potato chips frying at 180 °C. The calibration models were developed for TPC, CV, CD and CT using partial least square (PLS) chemometric technique. Excellent regression coefficients (R(2)) and root mean square error of prediction values for TPC, CV, CD and CT were found to be 0.999, 0.992, 0.998 and 0.999 and 0.809, 0.690, 1.26 and 0.735, respectively. The developed calibration models were applied on samples of canola oil drawn during potato chips frying process. A linear relationship was obtained between CD and TPC with a good correlation of coefficient (R(2)=0.9816). Results of the study clearly indicated that transmission FTIR-PLS method could be used for quick and precise evaluation of oxidative changes during the frying process without using any organic solvent. PMID:25985130

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

    PubMed

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

    2016-10-01

    Effect of data manipulation in preprocessing step proceeding construction of chemometric models was assessed. The same set of UV spectral data was used for construction of PLS and PCR models directly and after mathematically manipulation as per well known first and second derivatives of the absorption spectra, ratio spectra and first and second derivatives of the ratio spectra spectrophotometric methods, meanwhile the optimal working wavelength ranges were carefully selected for each model and the models were constructed. Unexpectedly, number of latent variables used for models' construction varied among the different methods. The prediction power of the different models was compared using a validation set of 8 mixtures prepared as per the multilevel multifactor design and results were statistically compared using two-way ANOVA test. Root mean squares error of prediction (RMSEP) was used for further comparison of the predictability among different constructed models. Although no significant difference was found between results obtained using Partial Least Squares (PLS) and Principal Component Regression (PCR) models, however, discrepancies among results was found to be attributed to the variation in the discrimination power of adopted spectrophotometric methods on spectral data. PMID:27235828

  14. Impact of Roasting on Identification of Hazelnut (Corylus avellana L.) Origin: A Chemometric Approach.

    PubMed

    Locatelli, Monica; Coïsson, Jean Daniel; Travaglia, Fabiano; Bordiga, Matteo; Arlorio, Marco

    2015-08-19

    Hazelnuts belonging to different cultivars or cultivated in different geographic areas can be differentiated by their chemical profile; however, the roasting process may affect the composition of raw hazelnuts, thus compromising the possibility to identify their origin in processed foods. In this work, we characterized raw and roasted hazelnuts (Tonda Gentile Trilobata, TGT, from Italy and from Chile, Tonda di Giffoni from Italy, and Tombul from Turkey), as well as hazelnuts isolated from commercial products, with the aim to discriminate their cultivar and origin. The chemometric evaluation of selected chemical parameters (proximate composition, fatty acids, total polyphenols, antioxidant activity, and protein fingerprint by SDS-PAGE) permitted us to identify hazelnuts belonging to different cultivars and, concerning TGT samples, their different geographic origin. Also commercial samples containing Piedmontese TGT hazelnuts were correctly assigned to TGT cluster. In conclusion, even if the roasting process modifies the composition of roasted hazelnuts, this preliminary model study suggests that the identification of their origin is still possible. PMID:26230075

  15. Chemometrics-assisted spectrophotometric method for simultaneous determination of Pb2+ and Cu2+ ions in different foodstuffs, soil and water samples using 2-benzylspiro [isoindoline-1,5‧-oxazolidine]-2‧,3,4‧-trione using continuous wavelet transformation and partial least squares - Calculation of pKf of complexes with rank annihilation factor analysis

    NASA Astrophysics Data System (ADS)

    Abbasi Tarighat, Maryam; Nabavi, Masoume; Mohammadizadeh, Mohammad Reza

    2015-06-01

    A new multi-component analysis method based on zero-crossing point-continuous wavelet transformation (CWT) was developed for simultaneous spectrophotometric determination of Cu2+ and Pb2+ ions based on the complex formation with 2-benzyl espiro[isoindoline-1,5oxasolidine]-2,3,4 trione (BSIIOT). The absorption spectra were evaluated with respect to synthetic ligand concentration, time of complexation and pH. Therefore according the absorbance values, 0.015 mmol L-1 BSIIOT, 10 min after mixing and pH 8.0 were used as optimum values. The complex formation between BSIIOT ligand and the cations Cu2+ and Pb2+ by application of rank annihilation factor analysis (RAFA) were investigated. Daubechies-4 (db4), discrete Meyer (dmey), Morlet (morl) and Symlet-8 (sym8) continuous wavelet transforms for signal treatments were found to be suitable among the wavelet families. The applicability of new synthetic ligand and selected mother wavelets were used for the simultaneous determination of strongly overlapped spectra of species without using any pre-chemical treatment. Therefore, CWT signals together with zero crossing technique were directly applied to the overlapping absorption spectra of Cu2+ and Pb2+. The calibration graphs for estimation of Pb2+ and Cu 2+were obtained by measuring the CWT amplitudes at zero crossing points for Cu2+ and Pb2+ at the wavelet domain, respectively. The proposed method was validated by simultaneous determination of Cu2+ and Pb2+ ions in red beans, walnut, rice, tea and soil samples. The obtained results of samples with proposed method have been compared with those predicted by partial least squares (PLS) and flame atomic absorption spectrophotometry (FAAS).

  16. Chemometrics-assisted spectrophotometric method for simultaneous determination of Pb²⁺ and Cu²⁺ ions in different foodstuffs, soil and water samples using 2-benzylspiro [isoindoline-1,5'-oxazolidine]-2',3,4'-trione using continuous wavelet transformation and partial least squares - calculation of pKf of complexes with rank annihilation factor analysis.

    PubMed

    Abbasi Tarighat, Maryam; Nabavi, Masoume; Mohammadizadeh, Mohammad Reza

    2015-06-15

    A new multi-component analysis method based on zero-crossing point-continuous wavelet transformation (CWT) was developed for simultaneous spectrophotometric determination of Cu(2+) and Pb(2+) ions based on the complex formation with 2-benzyl espiro[isoindoline-1,5 oxasolidine]-2,3,4 trione (BSIIOT). The absorption spectra were evaluated with respect to synthetic ligand concentration, time of complexation and pH. Therefore according the absorbance values, 0.015 mmol L(-1) BSIIOT, 10 min after mixing and pH 8.0 were used as optimum values. The complex formation between BSIIOT ligand and the cations Cu(2+) and Pb(2+) by application of rank annihilation factor analysis (RAFA) were investigated. Daubechies-4 (db4), discrete Meyer (dmey), Morlet (morl) and Symlet-8 (sym8) continuous wavelet transforms for signal treatments were found to be suitable among the wavelet families. The applicability of new synthetic ligand and selected mother wavelets were used for the simultaneous determination of strongly overlapped spectra of species without using any pre-chemical treatment. Therefore, CWT signals together with zero crossing technique were directly applied to the overlapping absorption spectra of Cu(2+) and Pb(2+). The calibration graphs for estimation of Pb(2+) and Cu (2+)were obtained by measuring the CWT amplitudes at zero crossing points for Cu(2+) and Pb(2+) at the wavelet domain, respectively. The proposed method was validated by simultaneous determination of Cu(2+) and Pb(2+) ions in red beans, walnut, rice, tea and soil samples. The obtained results of samples with proposed method have been compared with those predicted by partial least squares (PLS) and flame atomic absorption spectrophotometry (FAAS). PMID:25766479

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

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

  18. Chemometric-based determination of polycyclic aromatic hydrocarbons in aqueous samples using ultrasound-assisted emulsification microextraction combined to gas chromatography-mass spectrometry.

    PubMed

    Ahmadvand, Mohammad; Sereshti, Hassan; Parastar, Hadi

    2015-09-25

    In the present research, ultrasonic-assisted emulsification-microextraction (USAEME) coupled with gas chromatography-mass spectrometry (GC-MS) has been proposed for analysis of thirteen environmental protection agency (EPA) polycyclic aromatic hydrocarbons (PAHs) in aqueous samples. Tetrachloroethylene was selected as extraction solvent. The main parameters of USAEME affecting the efficiency of the method were modeled and optimized using a central composite design (CCD). Under the optimum conditions (9μL for extraction solvent, 1.15% (w/v) NaCl (salt concentration) and 10min for ultrasonication time), preconcentration factor (PF) of the PAHs was in the range of 500-950. In order to have a comprehensive analysis, multivariate curve resolution-alternating least squares (MCR-ALS) as a second-order calibration algorithm was used for resolution, identification and quantification of the target PAHs in the presence of uncalibrated interferences. The regression coefficients and relative errors (REs, %) of calibration curves of the PAHs were in the satisfactory range of 0.9971-0.9999 and 1.17-6.59%, respectively. Furthermore, analytical figures of merit (AFOM) for univariate and second-order calibrations were obtained and compared. As an instance, the limit of detections (LODs) of target PAHs were in the range of 1.87-18.9 and 0.89-6.49ngmL(-1) for univariate and second-order calibration, respectively. Finally, the proposed strategy was used for determination of target PAHs in real water samples (tap and hookah waters). The relative recoveries (RR) and the relative standard deviations (RSDs) were 68.4-109.80% and 2.15-6.93%, respectively. It was concluded that combination of multivariate chemometric methods with USAEME-GC-MS can be considered as a new insight for the analysis of target analytes in complex sample matrices. PMID:26319375

  19. Anti-acetylcholinesterase potential and metabolome classification of 4 Ocimum species as determined via UPLC/qTOF/MS and chemometric tools.

    PubMed

    Farag, M A; Ezzat, S M; Salama, M M; Tadros, M G

    2016-06-01

    Ocimum (sweet basil) is a plant of considerable commercial importance in traditional medicine worldwide as well as for the flavor and food industry. The goal of this study was to examine Ocimum extracts anti-acetylcholinesterase activity and to correlate the activity with their secondary metabolites profiles via a metabolome based ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) approach coupled to chemometrics. The metabolomic differences in phenolics from leaves derived from 4 Ocimum species: Ocimum basilicum, Ocimum africanum, Ocimum americanum and Ocimum minimum were assessed. Under optimized conditions, 81 metabolites were identified including 21 hydroxy cinnamic acids, 4 benzoic acid conjugates, 14C/O flavonoid conjugates, 2 alcohols, 5 acyl sugars, 4 triterpenes and 12 fatty acids. Several salviolanic acid derivatives including salviolanic acid A, B, C & I found in Salvia, were found in Ocimum herein for the first time. Unsupervised principal component analysis (PCA) and supervised orthogonal projection to latent structures-discriminant analysis (OPLS-DA) were further used for comparing and classification of samples. A clear separation among the four investigated Ocimum species was revealed, with O. africanum samples found most enriched in hydroxy cinnamates conjugates (HC) and flavonoids. To the best of our knowledge, this is the first report for compositional differences among Ocimum leaves via a metabolomic approach revealing that among examined species O. africanum leaves present a better source of Ocimum bioactive metabolites. The anticholinesrase activity of examined species was further assessed with a potent IC50 values for O. americanum, O. africanum, O. basilicum ranging from 2.5 to 6.6mg/ml, whereas O. minimum was least active with IC50 of 31.4mg/ml. Furthermore, major HC i.e., caftaric, chlorogenic and rosmarinic acids identified in extracts via UPLC-MS analysis exhibited IC50 values of 24, 0.5 and 7.9mg/ml respectively

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

    PubMed

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

    2013-09-01

    Potatoes from Galicia (northwestern Spain) are subjected to a Protected Geographic Indication (PGI) according to European legislation. Ten trace elements (Li, Na, K, Rb, Ca, Fe, Mg, Mn, Cu, and Zn) have been determined by atomic spectrometry in two sets of potato samples: Geo-Origin.set and Variety.set. The first data set is composed of samples of the only variety authorized by PGI (Kennebec) with two geographical origins: Galician and non-Galician. The second set corresponds to samples from different varieties but with only Galician geographical origin. Chemometric pattern recognition techniques have been applied to the study of potato geographical and varietal origins in relation to their capability for translocating metals from soil to tuber. Also, authentication models for classifying potato samples with Galician PGI based on metal fingerprints have been developed. The results obtained showed that samples of the same variety, Kennebec, have different metal fingerprints when they have been produced in different geographic locations. Also, diverse potato varieties cultivated on equal geographic Galician origin presented different metal profiles as well. Therefore, it can be concluded that classification studies on the differentiation of geographical origin of foods should take into account information of production area together with varietal data. Otherwise, classification obtained on the basis of the geographical origin could be due to the different variety or vice versa. Finally, two models were constructed for Kennebec Galician samples against Kennebec from other origins as well as against other varieties cultivated in Galicia (Liseta and Baraka). Both models achieved adequate classification rates (93-100%), good sensitivities, and total specificities (100%), allowing the fraud detection in the PGI label. PMID:23909659

  1. A chemometric optimization of method for determination of nitrosamines in gastric juices by GC-MS.

    PubMed

    Akyüz, Mehmet; Ata, Şevket; Dinç, Erdal

    2016-01-01

    A chemometrically optimized isolation procedure combined with gas chromatography-mass spectrometry detection technique has been proposed for quantitative determination of trace levels of nitrosamines in gastric juice samples of patients with the gastrointestinal tract problems. The extraction conditions of each nitrosamine were optimized using regression modelling based on central composite design. The extraction conditions for all nitrosamines were selected to be 10.7 min for extraction time, 4.2 for pH and 23 for 2-propanol percentage in extraction solution. The obtained recoveries of nitrosamines ranged from 94.0 (NDMA) to 99.3 (NDPheA) %, and the precision of this method, as indicated by the relative standard deviations was within the range of 0.7 (NDPheA) and 2.6 (NDMA) %. The detection limits obtained from calculations by using GC-MS results based on S/N=3 were found within the range from 0.3 to 1.1 pg/mL. Total nitrosamine concentrations were found at the highest concentration up to 2431.12 pg/mL in cancer patients, whereas they were found at the lowest concentration down to 12.18 pg/mL in gastritis patients. The classification results of the gastric juice samples in different patient groups were very satisfactory, allowing 100% of patients to be correctly grouped. A new mathematical model has been developed allowing for the classification of gastric juices with a 93.1% success rate based on just the ratio of MNPIZ to DNPIZ. The ratio of MNPIZ to DNPIZ might be considered as a biomarker for the classification of gastric juices of patients and might act as an indicator of increased risk for stomach cancer. PMID:26342445

  2. Resolution of five-component mixture using mean centering ratio and inverse least squares chemometrics

    PubMed Central

    2013-01-01

    Background A comparative study of the use of mean centering of ratio spectra and inverse least squares for the resolution of paracetamol, methylparaben, propylparaben, chlorpheniramine maleate and pseudoephedrine hydrochloride has been achieved showing that the two chemometric methods provide a good example of the high resolving power of these techniques. Method (I) is the mean centering of ratio spectra which depends on using the mean centered ratio spectra in four successive steps that eliminates the derivative steps and therefore the signal to noise ratio is improved. The absorption spectra of prepared solutions were measured in the range of 220–280 nm. Method (II) is based on the inverse least squares that depend on updating developed multivariate calibration model. The absorption spectra of the prepared mixtures in the range 230–270 nm were recorded. Results The linear concentration ranges were 0–25.6, 0–15.0, 0–15.0, 0–45.0 and 0–100.0 μg mL-1 for paracetamol, methylparaben, propylparaben, chlorpheniramine maleate and pseudoephedrine hydrochloride, respectively. The mean recoveries for simultaneous determination were between 99.9-101.3% for the two methods. The two developed methods have been successfully used for prediction of five-component mixture in Decamol Flu syrup with good selectivity, high sensitivity and extremely low detection limit. Conclusion No published method has been reported for simultaneous determination of the five components of this mixture so that the results of the mean centering of ratio spectra method were compared with those of the proposed inverse least squares method. Statistical comparison was performed using t-test and F-ratio at P = 0.05. There was no significant difference between the results. PMID:24028626

  3. Merits of random forests emerge in evaluation of chemometric classifiers by external validation.

    PubMed

    Scott, I M; Lin, W; Liakata, M; Wood, J E; Vermeer, C P; Allaway, D; Ward, J L; Draper, J; Beale, M H; Corol, D I; Baker, J M; King, R D

    2013-11-01

    Real-world applications will inevitably entail divergence between samples on which chemometric classifiers are trained and the unknowns requiring classification. This has long been recognized, but there is a shortage of empirical studies on which classifiers perform best in 'external validation' (EV), where the unknown samples are subject to sources of variation relative to the population used to train the classifier. Survey of 286 classification studies in analytical chemistry found only 6.6% that stated elements of variance between training and test samples. Instead, most tested classifiers using hold-outs or resampling (usually cross-validation) from the same population used in training. The present study evaluated a wide range of classifiers on NMR and mass spectra of plant and food materials, from four projects with different data properties (e.g., different numbers and prevalence of classes) and classification objectives. Use of cross-validation was found to be optimistic relative to EV on samples of different provenance to the training set (e.g., different genotypes, different growth conditions, different seasons of crop harvest). For classifier evaluations across the diverse tasks, we used ranks-based non-parametric comparisons, and permutation-based significance tests. Although latent variable methods (e.g., PLSDA) were used in 64% of the surveyed papers, they were among the less successful classifiers in EV, and orthogonal signal correction was counterproductive. Instead, the best EV performances were obtained with machine learning schemes that coped with the high dimensionality (914-1898 features). Random forests confirmed their resilience to high dimensionality, as best overall performers on the full data, despite being used in only 4.5% of the surveyed papers. Most other machine learning classifiers were improved by a feature selection filter (ReliefF), but still did not out-perform random forests. PMID:24139571

  4. Chemometric extraction of analyte-specific chromatograms in on-line gradient LC-infrared spectrometry.

    PubMed

    Kuligowski, Julia; Quintás, Guillermo; Garrigues, Salvador; de la Guardia, Miguel

    2009-12-01

    This work exploits the possibilities offered by the recently developed multivariate method named Science-Based Calibration (SBC), for the extraction of 'analyte-specific' chromatograms in on-line gradient reversed phase LC-infrared spectrometry (IR) in the presence of a high spectral and chromatographic overlapping between the analyte of interest, co-eluting sample matrix constituents and the mobile phase components. The SBC method uses an experimentally measured single response spectrum of the analyte of interest and representative noise to calculate an optimum regression vector (b(opt(1))). Then, the b(opt(1)) vector is used to predict the concentration of the analyte of interest in the spectra of the LC-IR sample chromatograms. To evaluate the advantages and pitfalls of the proposed approach, two different situations were analysed on real LC-IR data sets obtained from the injection of a series of standard solutions of four nitrophenols (p-nitrophenol, 3-methyl-4-nitrophenol, 2,4-dinitrophenol and 4-nitrophenol) in a reversed phase system under gradient conditions. In the first situation, the extraction of the 'analyte-specific' chromatogram was carried out without previous knowledge of the spectral features of other interferents present in the sample matrix. In a second situation evaluated, data obtained from the LC injection of a sample blank is available. Results show the potential applicability of this technique in a variety of situations and evidenced that the proposed chemometric approach improves the selectivity and sensitivity of the LC-IR hyphenation. PMID:19877149

  5. Elucidation of the primary ultrafast steps in photo-switchable systems using chemometric analysis

    NASA Astrophysics Data System (ADS)

    Sliwa, M.; Mouton, N.; Debus, B.; de Juan, A.; Burdzinski, G.; Miyasaka, H.; Abe, J.; Ruckebusch, C.

    2015-01-01

    We emphasize the potential of soft-modeling multivariate curve resolution method to extract pure difference spectra and kinetic profiles from data sets obtained by femtosecond transient absorption experiments. The example of the photo-switching of photochromic salicylidene aniline after 266 nm excitation will be detailed.

  6. Determination of Rhealogical Properties from Vibrational Spectra Using Chemometric Two- Dimensional Analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The ability to predict viscoelastic properties from vibrational spectra of grain flours was investigated. Both dispersive near-infrared (NIR) and Fourier-transform Raman (FT-Raman) spectra were used to generate two-dimensional matrix maps versus Rapid Visco Analyzer (RVA) generated viscograms. Aft...

  7. Identification of citrus greening disease using FTIR spectroscopy and chemometric analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Huanglongbing (HLB), also called citrus greening disease, is difficult to detect in plants before visual symptoms appear, by which time the disease is likely to have spread to other nearby plants. An accurate, early detection method is needed to identify diseased plants. Current methods are both c...

  8. Improved Quantitative Analysis of Ion Mobility Spectrometry by Chemometric Multivariate Calibration

    SciTech Connect

    Fraga, Carlos G.; Kerr, Dayle; Atkinson, David A.

    2009-09-01

    Traditional peak-area calibration and the multivariate calibration methods of principle component regression (PCR) and partial least squares (PLS), including unfolded PLS (U-PLS) and multi-way PLS (N-PLS), were evaluated for the quantification of 2,4,6-trinitrotoluene (TNT) and cyclo-1,3,5-trimethylene-2,4,6-trinitramine (RDX) in Composition B samples analyzed by temperature step desorption ion mobility spectrometry (TSD-IMS). The true TNT and RDX concentrations of eight Composition B samples were determined by high performance liquid chromatography with UV absorbance detection. Most of the Composition B samples were found to have distinct TNT and RDX concentrations. Applying PCR and PLS on the exact same IMS spectra used for the peak-area study improved quantitative accuracy and precision approximately 3 to 5 fold and 2 to 4 fold, respectively. This in turn improved the probability of correctly identifying Composition B samples based upon the estimated RDX and TNT concentrations from 11% with peak area to 44% and 89% with PLS. This improvement increases the potential of obtaining forensic information from IMS analyzers by providing some ability to differentiate or match Composition B samples based on their TNT and RDX concentrations.

  9. Chemometric evaluation of temperature-dependent surface-enhanced Raman spectra of riboflavin: What is the best multivariate approach to describe the effect of temperature?

    NASA Astrophysics Data System (ADS)

    Kokaislová, Alžběta; Kalhousová, Milena; Gráfová, Michaela; Matějka, Pavel

    2014-10-01

    Riboflavin is an essential nutrient involved in energetic metabolism. It is used as a pharmacologically active substance in treatment of several diseases. From analytical point of view, riboflavin can be used as an active part of sensors for substances with affinity to riboflavin molecules. In biological environment, metal substrates coated with riboflavin are exposed to temperatures that are different from room temperature. Hence, it is important to describe the influence of temperature on adsorbed molecules of riboflavin, especially on orientation of molecules towards the metal surface and on stability of adsorbed molecular layer. Surface-enhanced Raman scattering (SERS) spectroscopy is a useful tool for investigation of architecture of molecular layers adsorbed on metal surfaces because the spectral features in SERS spectra change with varying orientation of molecules towards the metal surface, as well as with changes in mutual interactions among adsorbed molecules. In this study, riboflavin was adsorbed on electrochemically prepared massive silver substrates that were exposed to temperature changes according to four different temperature programs. Raman spectra measured at different temperatures were compared considering positions of spectral bands, their intensities, bandwidths and variability of all these parameters. It was found out that increase of substrate temperature up to 50 °C does not lead to any observable decomposition of riboflavin molecules, but the changes of band intensity ratios within individual spectra are apparent. To distinguish sources of variability beside changes in band intensities and widths, Principal Component Analysis (PCA) was applied. Discriminant Analysis (DA) was used to explore if the SERS spectra can be separated according to temperature. The results of Partial Least Squares (PLS) regression demonstrate the possibility to predict the sample temperature using SERS spectral features. Results of all performed experiments and

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

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

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

  11. Application of NIR chemometric methods for quantification of the crystalline fraction of warfarin sodium in drug product.

    PubMed

    Korang-Yeboah, Maxwell; Akhtar, Sohail; Siddiqui, Akhtar; Rahman, Ziyaur; Khan, Mansoor A

    2016-01-01

    Monitoring of the physical state of warfarin sodium (WS) in products is essential for minimizing product quality variability in order to ensure consistent clinical performance. This study reports the development of chemometric models for quantifying the crystalline and amorphous fractions of WS in commercial drug products using NIR spectroscopy. Formulations based on commercially available products with different API to excipient ratio were used for the study. For each content, two formulations containing either lactose monohydrate or lactose anhydrous as the predominant formulation excipient were prepared. Two formulations containing either 100% amorphous WS (AWS) or crystalline WS (CWS) were prepared and mixed in various ratios to obtain sample matrices containing AWS/CWS 0-100%. The uniformity of the samples was confirmed by near infrared chemical imaging. Data were mathematically pretreated by multiplicative signal correction and Savitzky-Golay second derivative. Principal component regression and partial least square regression models were developed from mathematically treated data. All the models showed linear trend for amorphous and crystalline fractions of the WS as indicated by correlation and R(2) > 0.99 and >0.98, respectively. The models demonstrated good performance parameters with a low-root mean squared error, standard error and bias. The model predicted CWS and AWS contents were in very close agreement with the actual values. The study indicated the utility of NIR chemometric methods in quantification of the crystalline and/or amorphous fraction of WS in its products. PMID:26161939

  12. Simultaneous spectrophotometric determination of Celecoxib and Diacerein in bulk and capsule by absorption correction method and chemometric methods

    NASA Astrophysics Data System (ADS)

    Patel, N. S.; Nandurbarkar, V. P.; Patel, A. J.; Patel, S. G.

    Two methods, absorption correction and multivariate spectrophotometric methods were developed for simultaneous estimation of Celecoxib (CEL) and Diacerein (DIA) in combined dosage form. Absorption correction method involves direct estimation of DIA at wavelength 341 nm in which CEL has zero absorbance and shows no interference. For estimation of CEL, corrected absorbance was calculated at 253 nm due to the interference of DIA at this wavelength. Linearity was observed in the range of 6-22 μg mL-1 for CEL and 3-11 μg mL-1 for DIA. The method was validated as per ICH guidelines. Chemometric methods including classical least square (CLS), inverse least square (ILS), principal component regression (PCR) and partial least square (PLS) were studied for simultaneous determination of CEL and DIA in capsule using spectrophotometry. A set of 25 standard mixtures containing both drugs were prepared in range of 5-25 μg mL-1 for CEL and 3-15 μg mL-1 for DIA. Analytical figure of merit (FOM), such as sensitivity, selectivity, analytical sensitivity, limit of detection and limit of quantitation were determined for chemometric methods. The proposed methods were applied for determination of two components from combined dosage form.

  13. Sensor combination and chemometric modelling for improved process monitoring in recombinant E. coli fed-batch cultivations.

    PubMed

    Clementschitsch, Franz; Jürgen, Kern; Florentina, Pötschacher; Karl, Bayer

    2005-11-01

    The key objective for the optimisation of recombinant protein production in bacteria is to optimize the exploitation of the host cell's synthesis potential. Recent studies show that the novel concept of transcription rate control allows the tuning of recombinant gene expression in relation to the metabolic capacity of the host cell. To adjust the inducer-biomass ratio to a tolerable level, real-time knowledge about key process variables is paramount. Since there are no reliable online-sensors for key variables such as biomass or recombinant product, it is necessary to relate available online signals to process variables by mathematical models. To improve chemometric modelling of process variables, dielectric spectroscopy and a multi-wavelength online fluorescence sensor for two-dimensional fluorescence spectroscopy were applied in a series of recombinant Escherichia coli fed-batch cultivations applying two different process operation states. Dielectric spectroscopy signals were closely correlated to biomass, while two-dimensional fluorescence spectroscopy allowed the monitoring of fluorescent biogenic components. Chemometric modelling of key process variables with two different modelling techniques showed that this sensor combination greatly improved the estimation (i.e. reduce error magnitude) of process variables in recombinant E. coli cultivations, thereby enhancing process monitoring capabilities. PMID:16139381

  14. FTIR-ATR determination of solid non fat (SNF) in raw milk using PLS and SVM chemometric methods.

    PubMed

    Bassbasi, M; Platikanov, S; Tauler, R; Oussama, A

    2014-03-01

    Fourier transform infrared spectroscopy (FTIR) attenuated total reflectance (ATR) spectroscopy, coupled with chemometrics methods have been applied to the fast and non-destructive quantitative determination of solid non fat (SNF) content in raw milk. Partial least squares regression (PLS) and support vector machine (SVM) regression methods were used to model and predict SNF contents in raw milk based on FTIR spectral transmission measurements. Both methods, PLS and SVM, showed good performances in SNF prediction with relative prediction errors in the external validation of between 0.2% and 0.3% depending on the spectral range and regression method. Coefficient of determination of the global fit was always above 0.99. Since, the relative prediction errors were low, it can be concluded that FTIR-ATR with chemometrics can be used for accurate quantitative determinations of SNF contents in raw milk within the investigated calibration range of 79-100g/L. The proposed procedure is fast, non-destructive, simple and easy to implement. PMID:24176339

  15. Phytochemical fingerprint and chemometrics for natural food preparation pattern recognition: an innovative technique in food supplement quality control.

    PubMed

    Donno, D; Boggia, R; Zunin, P; Cerutti, A K; Guido, M; Mellano, M G; Prgomet, Z; Beccaro, G L

    2016-02-01

    Recently, the fingerprint approach using chromatography has become one of the most effective tools for quality assessment of herbal medicines and food supplements: due to the complexity of the chromatographic fingerprint and the irreproducibility of chromatographic instruments and experimental conditions, chemometric approach is employed to deal with the chromatographic fingerprint. The study was aimed at developing new analytical methods for the multivariate phytochemical fingerprinting of bioactive compounds in eight tree-species bud-preparations, commonly used in phytotherapy. Methods was used to identify and quantify the main bioactive compounds (polyphenols, organic acids and vitamins), and obtain a specific botanical profile in order to assess the contribution of each single bioactive class to the total bud preparation phytocomplex. A chemometric approach was used to distinguish among different genotypes assuring the identity, safety and quality of the botanical raw materials. The established protocol was simple, sensitive and reliable and it could be used for the evaluation and quality control of bud-extracts and natural food supplements: the proposed method was successfully applied to the characterization of commercial bud-preparations, demonstrating to be an effective tool for the fingerprinting of this plant material. The new approach developed in this study represents a good alternative for improving the classification results of herbal materials with complex chromatograms. It should be necessary to develop a "multivariate chromatographic fingerprint", in order to differentiate the herbal preparations according to their genotype, avoiding substitutions, changes or adulterations with other species or synthetic drugs. PMID:27162387

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

    PubMed

    Yu, Gloria Qingyu; Yu, Peiqiang

    2015-09-01

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

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

    PubMed

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

    2014-03-25

    Different chemometric models were applied for the quantitative analysis of Amlodipine (AML), Valsartan (VAL) and Hydrochlorothiazide (HCT) in ternary mixture, namely, Partial Least Squares (PLS) as traditional chemometric model and Artificial Neural Networks (ANN) as advanced model. PLS and ANN were applied with and without variable selection procedure (Genetic Algorithm GA) and data compression procedure (Principal Component Analysis PCA). The chemometric methods applied are PLS-1, GA-PLS, ANN, GA-ANN and PCA-ANN. The methods were used for the quantitative analysis of the drugs in raw materials and pharmaceutical dosage form via handling the UV spectral data. A 3-factor 5-level experimental design was established resulting in 25 mixtures containing different ratios of the drugs. Fifteen mixtures were used as a calibration set and the other ten mixtures were used as validation set to validate the prediction ability of the suggested methods. The validity of the proposed methods was assessed using the standard addition technique. PMID:24378624

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Niazi, Ali; Khorshidi, Neda; Ghaemmaghami, Pegah

    2015-01-01

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

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

    PubMed

    Niazi, Ali; Khorshidi, Neda; Ghaemmaghami, Pegah

    2015-01-25

    In this study an analytical procedure based on microwave-assisted dispersive liquid-liquid microextraction (MA-DLLME) and spectrophotometric coupled with chemometrics methods is proposed to determine uranium. In the proposed method, 4-(2-pyridylazo) resorcinol (PAR) is used as a chelating agent, and chloroform and ethanol are selected as extraction and dispersive solvent. The optimization strategy is carried out by using two level full factorial designs. Results of the two level full factorial design (2(4)) based on an analysis of variance demonstrated that the pH, concentration of PAR, amount of dispersive and extraction solvents are statistically significant. Optimal condition for three variables: pH, concentration of PAR, amount of dispersive and extraction solvents are obtained by using Box-Behnken design. Under the optimum conditions, the calibration graphs are linear in the range of 20.0-350.0 ng mL(-1) with detection limit of 6.7 ng mL(-1) (3δB/slope) and the enrichment factor of this method for uranium reached at 135. The relative standard deviation (R.S.D.) is 1.64% (n=7, c=50 ng mL(-1)). The partial least squares (PLS) modeling was used for multivariate calibration of the spectrophotometric data. The orthogonal signal correction (OSC) was used for preprocessing of data matrices and the prediction results of model, with and without using OSC, were statistically compared. MA-DLLME-OSC-PLS method was presented for the first time in this study. The root mean squares error of prediction (RMSEP) for uranium determination using PLS and OSC-PLS models were 4.63 and 0.98, respectively. This procedure allows the determination of uranium synthesis and real samples such as waste water with good reliability of the determination. PMID:25062051

  1. Monitoring of the manufacturing process for ambroxol hydrochloride tablet using NIR-chemometric methods: compression effect on content uniformity model and relevant process parameters testing.

    PubMed

    Yang, Hongqin; Liao, Xiaoxiang; Peng, Feng; Wang, Wan; Liu, Yanxin; Yan, Jin; Li, Hui

    2015-01-01

    This study aimed at using near-infrared (NIR) spectroscopy to monitor compaction pressure for simultaneously determining the tensile strength and content uniformity, as well as moisture and mean particle size of ambroxol hydrochloride tablets. The content uniformity, compression force and tensile strength of the laboratory samples were obtained by pressing a mixture of active principle and excipient components into tablets. To reduce the spectral baseline shift of the laboratory samples, the compaction pressure applied to the mixture was assessed by a variable pressure test. Production samples were added to the test and subjected to principal component analysis. The expanded partial least-squares (PLS) calibration model used to quantify the active content was more accurate than the model constructed from laboratory samples using the production tablets included in the calibration set. The model showed good predictability, with correlation coefficient (R) 0.9977. The validation and reliability of the content model were evaluated to determine trueness and reliability for the measurement of individual production tablets and the laboratory tablets with drug content ranging from 24 to 36 mg. The PLS calibration models for compression force and tensile strength were constructed using the same spectral set assuming both were highly related. These models yielded high R values (0.9955 and 0.9910). The R values of the moisture and mean particle size were 0.9994 and 0.9919, respectively. This study demonstrated that NIR spectroscopy combined with chemometric techniques can be successfully used to quantitatively monitor the tablet manufacturing process in the pharmaceutical industry. PMID:25738811

  2. Antimicrobial Activity of Serbian Propolis Evaluated by Means of MIC, HPTLC, Bioautography and Chemometrics

    PubMed Central

    Trifković, Jelena; Berić, Tanja; Vovk, Irena; Milojković-Opsenica, Dušanka; Stanković, Slaviša

    2016-01-01

    New information has come to light about the biological activity of propolis and the quality of natural products which requires a rapid and reliable assessment method such as High Performance Thin-Layer Chromatography (HPTLC) fingerprinting. This study investigates chromatographic and chemometric approaches for determining the antimicrobial activity of propolis of Serbian origin against various bacterial species. A linear multivariate calibration technique, using Partial Least Squares, was used to extract the relevant information from the chromatographic fingerprints, i.e. to indicate peaks which represent phenolic compounds that are potentially responsible for the antimicrobial capacity of the samples. In addition, direct bioautography was performed to localize the antibacterial activity on chromatograms. The biological activity of the propolis samples against various bacterial species was determined by a minimum inhibitory concentration assay, confirming their affiliation with the European poplar type of propolis and revealing the existence of two types (blue and orange) according to botanical origin. The strongest antibacterial activity was exhibited by sample 26 against Staphylococcus aureus, with a MIC value of 0.5 mg/mL, and Listeria monocytogenes, with a MIC as low as 0.1 mg/mL, which was also the lowest effective concentration observed in our study. Generally, the orange type of propolis shows higher antimicrobial activity compared to the blue type. PLS modelling was performed on the HPTLC data set and the resulting models might qualitatively indicate compounds that play an important role in the activity exhibited by the propolis samples. The most relevant peaks influencing the antimicrobial activity of propolis against all bacterial strains were phenolic compounds at RF values of 0.37, 0.40, 0.45, 0.51, 0.60 and 0.70. The knowledge gained through this study could be important for attributing the antimicrobial activity of propolis to specific chemical

  3. Antimicrobial Activity of Serbian Propolis Evaluated by Means of MIC, HPTLC, Bioautography and Chemometrics.

    PubMed

    Ristivojević, Petar; Dimkić, Ivica; Trifković, Jelena; Berić, Tanja; Vovk, Irena; Milojković-Opsenica, Dušanka; Stanković, Slaviša

    2016-01-01

    New information has come to light about the biological activity of propolis and the quality of natural products which requires a rapid and reliable assessment method such as High Performance Thin-Layer Chromatography (HPTLC) fingerprinting. This study investigates chromatographic and chemometric approaches for determining the antimicrobial activity of propolis of Serbian origin against various bacterial species. A linear multivariate calibration technique, using Partial Least Squares, was used to extract the relevant information from the chromatographic fingerprints, i.e. to indicate peaks which represent phenolic compounds that are potentially responsible for the antimicrobial capacity of the samples. In addition, direct bioautography was performed to localize the antibacterial activity on chromatograms. The biological activity of the propolis samples against various bacterial species was determined by a minimum inhibitory concentration assay, confirming their affiliation with the European poplar type of propolis and revealing the existence of two types (blue and orange) according to botanical origin. The strongest antibacterial activity was exhibited by sample 26 against Staphylococcus aureus, with a MIC value of 0.5 mg/mL, and Listeria monocytogenes, with a MIC as low as 0.1 mg/mL, which was also the lowest effective concentration observed in our study. Generally, the orange type of propolis shows higher antimicrobial activity compared to the blue type. PLS modelling was performed on the HPTLC data set and the resulting models might qualitatively indicate compounds that play an important role in the activity exhibited by the propolis samples. The most relevant peaks influencing the antimicrobial activity of propolis against all bacterial strains were phenolic compounds at RF values of 0.37, 0.40, 0.45, 0.51, 0.60 and 0.70. The knowledge gained through this study could be important for attributing the antimicrobial activity of propolis to specific chemical

  4. Predicting New Indications for Approved Drugs Using a Proteo-Chemometric Method

    PubMed Central

    Dakshanamurthy, Sivanesan; Issa, Naiem T; Assefnia, Shahin; Seshasayee, Ashwini; Peters, Oakland J; Madhavan, Subha; Uren, Aykut; Brown, Milton L; Byers, Stephen W

    2012-01-01

    The most effective way to move from target identification to the clinic is to identify already approved drugs with the potential for activating or inhibiting unintended targets (repurposing or repositioning). This is usually achieved by high throughput chemical screening, transcriptome matching or simple in silico ligand docking. We now describe a novel rapid computational proteo-chemometric method called “Train, Match, Fit, Streamline” (TMFS) to map new drug-target interaction space and predict new uses. The TMFS method combines shape, topology and chemical signatures, including docking score and functional contact points of the ligand, to predict potential drug-target interactions with remarkable accuracy. Using the TMFS method, we performed extensive molecular fit computations on 3,671 FDA approved drugs across 2,335 human protein crystal structures. The TMFS method predicts drug-target associations with 91% accuracy for the majority of drugs. Over 58% of the known best ligands for each target were correctly predicted as top ranked, followed by 66%, 76%, 84% and 91% for agents ranked in the top 10, 20, 30 and 40, respectively, out of all 3,671 drugs. Drugs ranked in the top 1–40, that have not been experimentally validated for a particular target now become candidates for repositioning. Furthermore, we used the TMFS method to discover that mebendazole, an anti-parasitic with recently discovered and unexpected anti-cancer properties, has the structural potential to inhibit VEGFR2. We confirmed experimentally that mebendazole inhibits VEGFR2 kinase activity as well as angiogenesis at doses comparable with its known effects on hookworm. TMFS also predicted, and was confirmed with surface plasmon resonance, that dimethyl celecoxib and the anti-inflammatory agent celecoxib can bind cadherin-11, an adhesion molecule important in rheumatoid arthritis and poor prognosis malignancies for which no targeted therapies exist. We anticipate that expanding our TMFS

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

    PubMed

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

    2016-01-01

    The chemical composition of volatile oils from 22 genotypes of Citrus and related genera was poorly differentiated, but chemometric techniques have clarified the relationships between the 22 genotypes, and allowed us to understand their resistance to D. citri. The most convincing similarities include the synthesis of (Z)-β-ocimene and (E)-caryophyllene for all 11 genotypes of group A. Genotypes of group B are not uniformly characterized by essential oil compounds. When stimulated with odor sources of 22 genotypes in a Y-tube olfactometer D. citri preferentially entered the arm containing the volatile oils of Murraya paniculata, confirming orange jasmine as its best host. C. reticulata × C. sinensis was the least preferred genotype, and is characterized by the presence of phytol, (Z)-β-ocimene, and β-elemene, which were not found in the most preferred genotype. We speculate that these three compounds may act as a repellent, making these oils less attractive to D. citri. PMID:27338332

  6. Chemometric evaluation of Cd, Co, Cr, Cu, Ni (inductively coupled plasma optical emission spectrometry) and Pb (graphite furnace atomic absorption spectrometry) concentrations in lipstick samples intended to be used by adults and children.

    PubMed

    Batista, Érica Ferreira; Augusto, Amanda dos Santos; Pereira-Filho, Edenir Rodrigues

    2016-04-01

    A method was developed for determining the concentrations of Cd, Co, Cr, Cu, Ni and Pb in lipstick samples intended to be used by adults and children using inductively coupled plasma optical emission spectrometry (ICP OES) and graphite furnace atomic absorption spectrometry (GF AAS) after treatment with dilute HNO3 and hot block. The combination of fractional factorial design and Desirability function was used to evaluate the ICP OES operational parameters and the regression models using Central Composite and Doehlert designs were calculated to stablish the best working condition for all analytes. Seventeen lipstick samples manufactured in different countries with different colors and brands were analyzed. Some samples contained high concentrations of toxic elements, such as Cr and Pb, which are carcinogenic and cause allergic and eczematous dermatitis. The maximum concentration detected was higher than the permissible safe limits for human use, and the samples containing these high metal concentrations were intended for use by children. Principal component analysis (PCA) was used as a chemometrics tool for exploratory analysis to observe the similarities between samples relative to the metal concentrations (a correlation between Cd and Pb was observed). PMID:26838401

  7. Quantitative analysis of cefalexin based on artificial neural networks combined with modified genetic algorithm using short near-infrared spectroscopy

    NASA Astrophysics Data System (ADS)

    Huan, Yanfu; Feng, Guodong; Wang, Bin; Ren, Yulin; Fei, Qiang

    2013-05-01

    In this paper, a novel chemometric method was developed for rapid, accurate, and quantitative analysis of cefalexin in samples. The experiments were carried out by using the short near-infrared spectroscopy coupled with artificial neural networks. In order to enhancing the predictive ability of artificial neural networks model, a modified genetic algorithm was used to select fixed number of wavelength.

  8. The basis function regression in pharmaceutical analysis. Theory and example of application.

    PubMed

    Komsta, Lukasz; Skibiński, Robert; Paryło, Marta; Dudek, Karolina

    2008-08-01

    The BFR (Basis Function Regression) is an interesting alternative to common techniques (such as PCR or PLS) in chemometrics. It is based on projecting the spectral information onto some number of equally spaced spline bases, than obtaining integrals of resulted curves. Existing references show that in certain cases it can reduce almost twice the RMSEP values. As this technique is not so popular in chemometrics nor applied in pharmaceutical analysis, it is desirable to present its theoretical considerations and implementation (with example MATLAB/Octave code). As an illustrative example we present the chemometric model for content recognition of a tablet (12 possible compounds in binary or ternary combinations) from the UV spectrum of its methanolic extract. The BFR technique gave lowest prediction error and the estimators obtained have more meritorical meaning than in case of PCR, PLS and other techniques used for comparison. In our opinion this technique should be considered in any chemometric approach as it often shows better performance. PMID:18450403

  9. Photocatalytic reduction of vanadium(V) in TiO₂ suspension: chemometric optimization and application to wastewaters.

    PubMed

    Sturini, Michela; Rivagli, Elisa; Maraschi, Federica; Speltini, Andrea; Profumo, Antonella; Albini, Angelo

    2013-06-15

    The photocatalytic reduction of V(V) to V(IV) over TiO₂ in aqueous solution is presented. Experiments were undertaken on air-equilibrated water spiked with V(V) (0.6-20 mgL(-1)), under UV-A or solar light. A chemometric study was performed to optimize the reduction yield, by considering the most important variables recognized to affect the photocatalytic process. Among pH, irradiation time and catalyst concentration, the two latter proved to be determinant. The good yields achieved (up to 98%), along with the possibility of working in aerated solution, make this procedure simple, rapid and efficient. Although a deep insight on the photochemical mechanisms was beyond our scope, the role of electron donors was investigated, proving the efficiency of 2-propanol, citric acid and formic acid in the acceleration and improvement of V(V) conversion. After irradiation, total vanadium and aqueous V(V) and V(IV) after solid-phase separation on Chelex-100 resin, were determined by inductively coupled plasma optical emission spectroscopy (ICP-OES). The procedure was applied to contaminated wastewaters, combining remediation and possible vanadium recovery as V(IV). PMID:23611800

  10. Phenolic compounds of Brazilian beers from different types and styles and application of chemometrics for modeling antioxidant capacity.

    PubMed

    Moura-Nunes, Nathália; Brito, Thárcila Cazaroti; da Fonseca, Nívea Dias; de Aguiar, Paula Fernandes; Monteiro, Mariana; Perrone, Daniel; Torres, Alexandre Guedes

    2016-05-15

    In the present study we aimed at investigating, for the first time, phenolic compounds in Brazilian beers of different types and styles. We also aimed at applying chemometrics for modeling beer's antioxidant capacity as a function of their physicochemical attributes (density, refractive index, bitterness and ethanol content). Samples (n=29) were analyzed by PCA originating five groups, especially according to ethanol contents and bitterness. In general, Group V (alcoholic beers with very high bitterness) presented higher refractive index, bitterness, ethanol and phenolics contents than Groups I (non-alcoholic beers) and II (alcoholic beers with low bitterness). Brazilian beers phenolics profile was distinct from that of European beers, with high contents of gallic acid (0.5-14.7 mg/L) and low contents of ferulic acid (0.2-1.8 mg/L). Using PLS, beer's antioxidant capacity measured by FRAP assay could be predicted with acceptable precision by data of ethanol content and density, bitterness and refractive index values. PMID:26775950

  11. Comparison of Four Chemometric Techniques for Estimating Leaf Nitrogen Concentrations in Winter Wheat (Triticum Aestivum) Based on Hyperspectral Features

    NASA Astrophysics Data System (ADS)

    Li, Zh.; Nie, Ch.; Wei, Ch.; Xu, X.; Song, X.; Wang, J.

    2016-05-01

    Four chemometric techniques for estimating LNC in winter wheat were compared by spectral features. The predictive power and impact of sample size were evaluated. Key results include: (1) partial least squares regression (PLSR) and support vector machines regression (SVR) performed better than the other two methods, with coefficient of determination (r 2) values in the calibration set of 0.82 and 0.81 and the normalized root mean square error (NRMSE) values in the validation set of 5.48 and 5.94%, respectively; (2) the lowest accuracy was achieved using stepwise multiple linear regression (SMLR), with r 2 and NRMSE values of 0.78 and 6.52%, respectively; (3) the predictive power of the back propagation neural network (BPN) was enhanced as sample size increased. Sample size less than 80 is not recommended when using BPN. These results suggest that PLSR and SVR are preferred choices to estimate LNC in winter wheat, and BPN is recommended when a sufficient sample size is available.

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

    NASA Astrophysics Data System (ADS)

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

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

  13. Total ion chromatographic fingerprints combined with chemometrics and mass defect filter to predict antitumor components of Picrasma quassioids.

    PubMed

    Shi, Yuanyuan; Zhan, Hao; Zhong, Liuyi; Yan, Fangrong; Feng, Feng; Liu, Wenyuan; Xie, Ning

    2016-07-01

    A method of total ion chromatogram combined with chemometrics and mass defect filter was established for the prediction of active ingredients in Picrasma quassioides samples. The total ion chromatogram data of 28 batches were pretreated with wavelet transformation and correlation optimized warping to correct baseline drifts and retention time shifts. Then partial least squares regression was applied to construct a regression model to bridge the total ion chromatogram fingerprints and the antitumor activity of P. quassioides. Finally, the regression coefficients were used to predict the active peaks in total ion chromatogram fingerprints. In this strategy, mass defect filter was employed to classify and characterize the active peaks from a chemical point of view. A total of 17 constituents were predicted as the potential active compounds, 16 of which were identified as alkaloids by this developed approach. The results showed that the established method was not only simple and easy to operate, but also suitable to predict ultraviolet undetectable compounds and provide chemical information for the prediction of active compounds in herbs. PMID:27135885

  14. Antileishmanial activity of new thiophene-indole hybrids: Design, synthesis, biological and cytotoxic evaluation, and chemometric studies.

    PubMed

    Félix, Mayara B; de Souza, Edson R; de Lima, Maria do C A; Frade, Daiana Karla G; Serafim, Vanessa de L; Rodrigues, Klinger Antonio da F; Néris, Patrícia Lima do N; Ribeiro, Frederico F; Scotti, Luciana; Scotti, Marcus T; de Aquino, Thiago M; Mendonça Junior, Francisco Jaime B; de Oliveira, Márcia R

    2016-09-15

    In the present work, thirty-two hybrid compounds containing cycloalka[b]thiophene and indole moieties (TN5, TN5 1-7, TN6, TN6 1-7, TN7, TN7 1-7, TN8, TN8 1-7) were designed, synthesized and evaluated for their cytotoxic and antileishmanial activity against Leishmania amazonensis promastigotes. More than half of the compounds (18 compounds) exhibited significant antileishmanial activity (IC50 lower than 10.0μg/L), showing better performance than the reference drugs (tri- and penta-valent antimonials). The most active compounds were TN8-7, TN6-1 and TN7 with respective IC50 values of 2.1, 2.3 and 3.2μg/mL. Demonstrating that all of the compounds were less toxic than the reference drugs, even at the highest evaluated concentration (400μg/mL), no compound tested presented human erythrocyte cytotoxicity. Compound TN8-7's effectiveness against a trivalent antimony-resistant culture was demonstrated. It was observed that TN8-7's antileishmanial activity is associated with DNA fragmentation of L. amazonensis promastigotes. Chemometric studies (CPCA, PCA, and PLS) highlight intrinsic solubility/lipophilicity, and compound size and shape as closely related to activity. Our results suggest that hybrid cycloalka[b]thiophene-indole derivatives may be considered as lead compounds for further development of new drugs for the treatment of leishmaniasis. PMID:27515718

  15. Towards the chemometric dissection of peptide--HLA-A*0201 binding affinity: comparison of local and global QSAR models.

    PubMed

    Doytchinova, Irini A; Walshe, Valerie; Borrow, Persephone; Flower, Darren R

    2005-03-01

    The affinities of 177 nonameric peptides binding to the HLA-A*0201 molecule were measured using a FACS-based MHC stabilisation assay and analysed using chemometrics. Their structures were described by global and local descriptors, QSAR models were derived by genetic algorithm, stepwise regression and PLS. The global molecular descriptors included molecular connectivity chi indices, kappa shape indices, E-state indices, molecular properties like molecular weight and log P, and three-dimensional descriptors like polarizability, surface area and volume. The local descriptors were of two types. The first used a binary string to indicate the presence of each amino acid type at each position of the peptide. The second was also position-dependent but used five z-scales to describe the main physicochemical properties of the amino acids forming the peptides. The models were developed using a representative training set of 131 peptides and validated using an independent test set of 46 peptides. It was found that the global descriptors could not explain the variance in the training set nor predict the affinities of the test set accurately. Both types of local descriptors gave QSAR models with better explained variance and predictive ability. The results suggest that, in their interactions with the MHC molecule, the peptide acts as a complicated ensemble of multiple amino acids mutually potentiating each other. PMID:16059672

  16. Application and validation of chemometrics-assisted spectrophotometry and liquid chromatography for the simultaneous determination of six-component pharmaceuticals.

    PubMed

    El-Gindy, Alaa; Emara, Samy; Mostafa, Ahmed

    2006-05-01

    Three methods are developed for the simultaneous determination of theophylline anhydrous (TH), guaiphenesin (GP), diphenhydramine hydrochloride (DP), methylparaben (MP), propylparaben (PP) and sodium benzoate (BZ) in pharmaceutical syrup. The chromatographic method depends on a high performance liquid chromatographic separation on a reversed-phase C(18) column at ambient temperature with mobile phase consisting of 25 mM KH2PO4, pH 3.2-acetonitrile (60:40, v/v). Quantitation was achieved with UV detection at 222 nm based on peak area. The other two chemometric methods applied were partial least squares (PLS-1) and principal component regression (PCR). These approaches were successfully applied to quantify the six components in the studied mixture using information included in the UV absorption spectra of appropriate solutions in the wavelength range of 220-270 nm with Deltalambda=0.4 nm. The calibration PLS-1 and PCR models were evaluated by internal validation (prediction of compounds in its own designed training set of calibration), by cross-validation (obtaining statistical parameters that show the efficiency for a calibration fit model) and by external validation over synthetic and pharmaceutical preparation. The results of PLS-1 and PCR methods were compared with the HPLC method and a good agreement was found. PMID:16414231

  17. Determining the influence of the physicochemical parameters of urban soils on As availability using chemometric methods: A preliminary study.

    PubMed

    Waterlot, Christophe; Pelfrêne, Aurélie; Douay, Francis

    2016-09-01

    An initial exploration was conducted using mathematical and statistical methods to obtain relevant information about the determination of the physicochemical parameters capable of controlling As uptake by ryegrass grown on contaminated topsoils. Concentrations of As in the soils were from 10 to 47mg/kg, mainly in the As(V) form (57%-73%). Concentrations of As in water extracts were very low (61-700μg/kg). It was suggested that As(III) was mainly in the uncharged species and As(V) in the charged species. Chemometric methods revealed that the values of the ratio As(III)/As(V) depended on the assimilated-phosphorus, the pseudo-total and water-extractable Fe contents and the soil pH. Arsenic concentrations measured in ryegrass shoots ranged from 119 to 1602μg/kg. Positive linear correlations were obtained between As in ryegrass shoots and water extractable-As. The transfer coefficient of As correlated well with the ratio assimilated-phosphorus/Fe-oxides. As(III) uptake by the shoot of ryegrass was controlled by the organic matter and Fe-oxide contents. PMID:27593285

  18. In-situ monitoring of Saccharomyces cerevisiae ITV01 bioethanol process using near-infrared spectroscopy NIRS and chemometrics.

    PubMed

    Corro-Herrera, Víctor Abel; Gómez-Rodríguez, Javier; Hayward-Jones, Patricia Margaret; Barradas-Dermitz, Dulce María; Aguilar-Uscanga, María Guadalupe; Gschaedler-Mathis, Anne Christine

    2016-03-01

    The application feasibility of in-situ or in-line monitoring of S. cerevisiae ITV01 alcoholic fermentation process, employing Near-Infrared Spectroscopy (NIRS) and Chemometrics, was investigated. During the process in a bioreactor, in the complex analytical matrix, biomass, glucose, ethanol and glycerol determinations were performed by a transflection fiber optic probe immersed in the culture broth and connected to a Near-Infrared (NIR) process analyzer. The NIR spectra recorded between 800 and 2,200 nm were pretreated using Savitzky-Golay smoothing and second derivative in order to perform a partial least squares regression (PLSR) and generate the calibration models. These calibration models were tested by external validation and then used to predict concentrations in batch alcoholic fermentations. The standard errors of calibration (SEC) for biomass, ethanol, glucose and glycerol were 0.212, 0.287, 0.532, and 0.296 g/L and standard errors of prediction (SEP) were 0.323, 0.369, 0.794, and 0.507 g/L, respectively. Calibration and validation criteria were defined and evaluated in order to generate robust and reliable models for an alcoholic fermentation process matrix. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:510-517, 2016. PMID:26743160

  19. Chemometric resolution of fully overlapped CE peaks: quantitation of carbamazepine in human serum in the presence of several interferences.

    PubMed

    Vera-Candioti, Luciana; Culzoni, María J; Olivieri, Alejandro C; Goicoechea, Héctor C

    2008-11-01

    Drug monitoring in serum samples was performed using second-order data generated by CE-DAD, processed with a suitable chemometric strategy. Carbamazepine could be accurately quantitated in the presence of its main metabolite (carbamazepine epoxide), other therapeutic drugs (lamotrigine, phenobarbital, phenytoin, phenylephrine, ibuprofen, acetaminophen, theophylline, caffeine, acetyl salicylic acid), and additional serum endogenous components. The analytical strategy consisted of the following steps: (i) serum sample clean-up to remove matrix interferences, (ii) data pre-processing, in order to reduce the background and to correct for electrophoretic time shifts, and (iii) resolution of fully overlapped CE peaks (corresponding to carbamazepine, its metabolite, lamotrigine and unexpected serum components) by the well-known multivariate curve resolution-alternating least squares algorithm, which extracts quantitative information that can be uniquely ascribed to the analyte of interest. The analyte concentration in serum samples ranged from 2.00 to 8.00 mg/L. Mean recoveries were 102.6% (s=7.7) for binary samples, and 94.8% (s=13.5) for spiked serum samples, while CV (%)=4.0 was computed for five replicate, indicative of the acceptable accuracy and precision of the proposed method. PMID:19035405

  20. Comparison of Four Chemometric Techniques for Estimating Leaf Nitrogen Concentrations in Winter Wheat ( Triticum Aestivum) Based on Hyperspectral Features

    NASA Astrophysics Data System (ADS)

    Li, Zh.; Nie, Ch.; Wei, Ch.; Xu, X.; Song, X.; Wang, J.

    2016-05-01

    Four chemometric techniques for estimating LNC in winter wheat were compared by spectral features. The predictive power and impact of sample size were evaluated. Key results include: (1) partial least squares regression (PLSR) and support vector machines regression (SVR) performed better than the other two methods, with coefficient of determination ( r 2) values in the calibration set of 0.82 and 0.81 and the normalized root mean square error (NRMSE) values in the validation set of 5.48 and 5.94%, respectively; (2) the lowest accuracy was achieved using stepwise multiple linear regression (SMLR), with r 2 and NRMSE values of 0.78 and 6.52%, respectively; (3) the predictive power of the back propagation neural network (BPN) was enhanced as sample size increased. Sample size less than 80 is not recommended when using BPN. These results suggest that PLSR and SVR are preferred choices to estimate LNC in winter wheat, and BPN is recommended when a sufficient sample size is available.

  1. Chemometric methods applied to the calibration of a Vis-NIR sensor for gas engine's condition monitoring.

    PubMed

    Villar, Alberto; Gorritxategi, Eneko; Otaduy, Deitze; Ciria, Jose I; Fernandez, Luis A

    2011-10-31

    This paper describes the calibration process of a Visible-Near Infrared sensor for the condition monitoring of a gas engine's lubricating oil correlating transmittance oil spectra with the degradation of a gas engine's oil via a regression model. Chemometric techniques were applied to determine different parameters: Base Number (BN), Acid Number (AN), insolubles in pentane and viscosity at 40 °C. A Visible-Near Infrared (400-1100 nm) sensor developed in Tekniker research center was used to obtain the spectra of artificial and real gas engine oils. In order to improve sensor's data, different preprocessing methods such as smoothing by Saviztky-Golay, moving average with Multivariate Scatter Correction or Standard Normal Variate to eliminate the scatter effect were applied. A combination of these preprocessing methods was applied to each parameter. The regression models were developed by Partial Least Squares Regression (PLSR). In the end, it was shown that only some models were valid, fulfilling a set of quality requirements. The paper shows which models achieved the established validation requirements and which preprocessing methods perform better. A discussion follows regarding the potential improvement in the robustness of the models. PMID:21962360

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

    PubMed

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

    2016-07-01

    The increased marketing of fake perfumes has encouraged us to investigate how to identify such products by their chemical characteristics and multivariate analysis. The aim of this study was to present an alternative approach to distinguish original from fake perfumes by means of the investigation of sodium, potassium, chloride ions, and ethanol contents by chemometric tools. For this, 50 perfumes were used (25 original and 25 counterfeit) for the analysis of ions (ion chromatography) and ethanol (gas chromatography). The results demonstrated that the fake perfume had low levels of ethanol and high levels of chloride compared to the original product. The data were treated by chemometric tools such as principal component analysis and linear discriminant analysis. This study proved that the analysis of ethanol is an effective method of distinguishing original from the fake products, and it may potentially be used to assist legal authorities in such cases. PMID:27364290

  3. Assessment of repeatability of composition of perfumed waters by high-performance liquid chromatography combined with numerical data analysis based on cluster analysis (HPLC UV/VIS - CA).

    PubMed

    Ruzik, L; Obarski, N; Papierz, A; Mojski, M

    2015-06-01

    High-performance liquid chromatography (HPLC) with UV/VIS spectrophotometric detection combined with the chemometric method of cluster analysis (CA) was used for the assessment of repeatability of composition of nine types of perfumed waters. In addition, the chromatographic method of separating components of the perfume waters under analysis was subjected to an optimization procedure. The chromatograms thus obtained were used as sources of data for the chemometric method of cluster analysis (CA). The result was a classification of a set comprising 39 perfumed water samples with a similar composition at a specified level of probability (level of agglomeration). A comparison of the classification with the manufacturer's declarations reveals a good degree of consistency and demonstrates similarity between samples in different classes. A combination of the chromatographic method with cluster analysis (HPLC UV/VIS - CA) makes it possible to quickly assess the repeatability of composition of perfumed waters at selected levels of probability. PMID:25533703

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  5. Chemometric tools to evaluate the spatial distribution of trace metals in surface sediments of two Spanish rías.

    PubMed

    Quelle, Cristina; Besada, Victoria; Andrade, José Manuel; Gutiérrez, Noemí; Schultze, Fernando; Gago, Jesús; González, Juan José

    2011-12-15

    A suite of relevant trace metals (Hg, Pb, Cd, Cu, Zn and Ni) was measured in surface sediment samples to assess the environmental situation of the largest two Atlantic Spanish 'rías' (a form of estuaries, ría of Pontevedra, ROP, and ría of Vigo, ROV). The level of contamination originated by these metals was assessed against international guidelines, the threshold effect, ERL, and the midrange effect, ERM. Six unsupervised and supervised multivariate chemometric techniques were applied to model each ría, compare them and select those metals that characterize the samples. This is first time that such a study is performed for these two important seafood-producing areas. Maximum concentrations at ROP occurred in the vicinities of an inner island, where Cu, Zn, Ni and Pb presented concentrations over the ERL and Hg over the ERM. Highest concentrations of metals in ROV were observed in the proximities of Vigo shipyards and port, except for Pb, with peak values in San Simon Bay. ERL limits were exceeded in the inner part of this ría for Cu, Zn and Hg and in a wider area for Pb and Ni. Levels for Pb went beyond the ERM boundary in the axial part of San Simon Bay. In general, the distribution of the metals was more homogeneous in ría of Pontevedra than in ría of Vigo (where three morphological zones were characterized). Both rías could be differentiated using only two metals: Ni and Hg, as deduced from the multivariate techniques. PMID:22099668

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

    PubMed

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

    2016-03-15

    New accurate, sensitive and selective spectrophotometric and chemometric methods were developed and subsequently validated for determination of Imipenem (IMP), ciprofloxacin hydrochloride (CIPRO), dexamethasone sodium phosphate (DEX), paracetamol (PAR) and cilastatin sodium (CIL) in human urine. These methods include a new derivative ratio method, namely extended derivative ratio (EDR), principal component regression (PCR) and partial least-squares (PLS) methods. A novel EDR method was developed for the determination of these drugs, where each component in the mixture was determined by using a mixture of the other four components as divisor. Peak amplitudes were recorded at 293.0 nm, 284.0 nm, 276.0 nm, 257.0 nm and 221.0 nm within linear concentration ranges 3.00-45.00, 1.00-15.00, 4.00-40.00, 1.50-25.00 and 4.00-50.00 μg mL(-1) for IMP, CIPRO, DEX, PAR and CIL, respectively. PCR and PLS-2 models were established for simultaneous determination of the studied drugs in the range of 3.00-15.00, 1.00-13.00, 4.00-12.00, 1.50-9.50, and 4.00-12.00 μg mL(-1) for IMP, CIPRO, DEX, PAR and CIL, respectively, by using eighteen mixtures as calibration set and seven mixtures as validation set. The suggested methods were validated according to the International Conference of Harmonization (ICH) guidelines and the results revealed that they were accurate, precise and reproducible. The obtained results were statistically compared with those of the published methods and there was no significant difference. PMID:26709018

  7. The current practice in the application of chemometrics for correlation of sensory and gas chromatographic data.

    PubMed

    Seisonen, Sirli; Vene, Kristel; Koppel, Kadri

    2016-11-01

    A lot of research has been conducted in correlating the sensory properties of food with different analytical measurements in recent years. Various statistical methods have been used in order to get the most reliable results and to create prediction models with high statistical performance. The current review summarises the latest practices in the field of correlating attributes from sensory analysis with volatile data obtained by gas chromatographic analysis. The review includes the origin of the data, different pre-processing and variable selection methods and finally statistical methods of analysis and validation. Partial least squares regression analysis appears as the most commonly used statistical method in the area. The main shortcomings were identified in the steps of pre-processing, variable selection and also validation of models that have not gained enough attention. As the association between volatiles and sensory perception is often nonlinear, future studies should test the application of different nonlinear techniques. PMID:27211679

  8. Differentiation of leaf and whole-plant samples of di- and tetraploid Gynostemma pentaphyllum (Thunb.) Makino using flow-injection mass spectrometric(FIMS) fingerprinting method combined with chemometric approaches

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In the present study, the feasibility and advantages of employing a flow-injection mass spectrometry (FIMS) fingerprinting method combined with chemometric analyses for assessment of di- and tetraploid leaf and whole-plant Gynostemma. pentaphyllum (Thunb.) Makino samples were investigated for the fi...

  9. Differentiation of leaf and whole-plant samples of di- and tetraploid Gynostemma pentaphyllum (Thunb.) Makino using flow-injection mass spectrometric(FIMS) fingerprinting method combined with chemometric approaches

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In the present study, the feasibility and advantages of employing a flow-injection mass spectrometry (FIMS) fingerprinting method combined with chemometric analyses for quality assessment of di- and tetraploid leaf and whole-plant Gynostemma. pentaphyllum (Thunb.) Makino samples were investigated fo...

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

    PubMed

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

    2016-04-15

    As a popular detection model, the fluorescence "turn-off" sensor based on quantum dots (QDs) has already been successfully employed in the detections of many materials, especially in the researches on the interactions between pesticides. However, the previous studies are mainly focused on simple single track or the comparison based on similar concentration of drugs. In this work, a new detection method based on the fluorescence "turn-off" model with water-soluble ZnCdSe and CdSe QDs simultaneously as the fluorescent probes is established to detect various pesticides. The fluorescence of the two QDs can be quenched by different pesticides with varying degrees, which leads to the differences in positions and intensities of two peaks. By combining with chemometrics methods, all the pesticides can be qualitative and quantitative respectively even in real samples with the limit of detection was 2 × 10(-8) mol L(-1) and a recognition rate of 100%. This work is, to the best of our knowledge, the first report on the detection of pesticides based on the fluorescence quenching phenomenon of double quantum dots combined with chemometrics methods. What's more, the excellent selectivity of the system has been verified in different mediums such as mixed ion disruption, waste water, tea and water extraction liquid drugs. PMID:27016442

  11. Chemometrics-assisted excitation-emission fluorescence analytical data for rapid and selective determination of optical brighteners in the presence of uncalibrated interferences

    NASA Astrophysics Data System (ADS)

    Gholami, Ali; Masoum, Saeed; Mohsenikia, Atefeh; Abbasi, Saleheh

    2016-01-01

    This study describes a novel approach for the simultaneous determination of CBS-X and CXT as widely used optical brighteners in household detergent, by combining the advantage of the high sensitivity of molecular fluorescence, and the selectivity of second-order chemometric methods. The proposed method is assisted by second-order chemometric analyses employing the PARAFAC, SWATLD and APTLD that help us to determine CBS-X and CXT in laundry powders and environmental samples, through the unique decomposition of the three-way data array. Proposed method can provide the extraction of relative concentrations of the analytes, as well as the spectral profiles. This approach achieves the second-order advantage and in principle could be able to overcome the spectral uncalibrated interference problems in the determination of CBS-X and CXT at the ng g- 1 level. By spiking the known concentrations of these compounds to the real samples, the accuracy of the proposed methods was validated and recoveries of the spiked values were calculated. High recoveries (90.00%-113.33%) for the spiked laundry powders and real environmental samples indicate the present method successfully faces this complex challenge without the necessity of applying separation and preconcentration steps in environmental contaminations.

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

    PubMed

    Ayoub, Bassam M

    2016-11-01

    New univariate spectrophotometric method and multivariate chemometric approach were developed and compared for simultaneous determination of empagliflozin and metformin manipulating their zero order absorption spectra with application on their pharmaceutical preparation. Sample enrichment technique was used to increase concentration of empagliflozin after extraction from tablets to allow its simultaneous determination with metformin without prior separation. Validation parameters according to ICH guidelines were satisfactory over the concentration range of 2-12μgmL(-1) for both drugs using simultaneous equation with LOD values equal to 0.20μgmL(-1) and 0.19μgmL(-1), LOQ values equal to 0.59μgmL(-1) and 0.58μgmL(-1) for empagliflozin and metformin, respectively. While the optimum results for the chemometric approach using partial least squares method (PLS-2) were obtained using concentration range of 2-10μgmL(-1). The optimized validated methods are suitable for quality control laboratories enable fast and economic determination of the recently approved pharmaceutical combination Synjardy® tablets. PMID:27288963

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

    PubMed

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

    2014-11-01

    Single bounce attenuated total reflectance (SB-ATR) Fourier transform infrared (FTIR) spectroscopy in conjunction with chemometrics was used for accurate determination of free fatty acid (FFA), peroxide value (PV), iodine value (IV), conjugated diene (CD) and conjugated triene (CT) of cottonseed oil (CSO) during potato chips frying. Partial least square (PLS), stepwise multiple linear regression (SMLR), principal component regression (PCR) and simple Beer׳s law (SBL) were applied to develop the calibrations for simultaneous evaluation of five stated parameters of cottonseed oil (CSO) during frying of French frozen potato chips at 170°C. Good regression coefficients (R(2)) were achieved for FFA, PV, IV, CD and CT with value of >0.992 by PLS, SMLR, PCR, and SBL. Root mean square error of prediction (RMSEP) was found to be less than 1.95% for all determinations. Result of the study indicated that SB-ATR FTIR in combination with multivariate chemometrics could be used for accurate and simultaneous determination of different parameters during the frying process without using any toxic organic solvent. PMID:25127621

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

    PubMed

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

    2015-03-18

    GC/MS, chiral GC/MS, and chemometric techniques were used to evaluate a large set (n=104) of tea tree oils (TTO) and commercial products purported to contain TTO. Twenty terpenoids were determined in each sample and compared with the standards specified by ISO-4730-2004. Several of the oil samples that were ISO compliant when distilled did not meet the ISO standards in this study primarily due to the presence of excessive p-cymene and/or depletion of terpinenes. Forty-nine percent of the commercial products did not meet the ISO specifications. Four terpenes, viz., α-pinene, limonene, terpinen-4-ol, and α-terpineol, present in TTOs with the (+)-isomer predominant were measured by chiral GC/MS. The results clearly indicated that 28 commercial products contained excessive (+)-isomer or contained the (+)-isomer in concentrations below the norm. Of the 28 outliers, 7 met the ISO standards. There was a substantial subset of commercial products that met ISO standards but displayed unusual enantiomeric+/-ratios. A class predictive model based on the oils that met ISO standards was constructed. The outliers identified by the class predictive model coincided with the samples that displayed an abnormal chiral ratio. Thus, chiral and chemometric analyses could be used to confirm the identification of abnormal commercial products including those that met all of the ISO standards. PMID:25727364

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

    PubMed Central

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

    2015-01-01

    Background: Tulsi, Banyan, and Jamun are popular Indian medicinal plants with notable hypoglycemic potentials. Now the work reports chemo-profiling of the three species with in-vitro screening approach for natural enzyme inhibitors (NEIs) against enzymes pathogenic for type 2 diabetes. Further along with the chemometrics optimized extraction process technology, phyto-synergistic studies of the composite polyherbal blends have also been reported. Objective: Chemometrically optimized extraction procedures, ratios of polyherbal composites to achieve phyto-synergistic actions, and in-vitro screening of NEIs amongst leaves of Tulsi, Banyan, and Jamun. Materials and Methods: The extraction process parameters of the leaves of three plant species (Ficus benghalensis, Syzigium cumini and Ocimum sanctum) were optimized by rotatable central composite design of chemometrics so as to get maximal yield of bio-actives. Phyto-blends of three species were prepared so as to achieve synergistic antidiabetic and antioxidant potentials and the ratios were optimized by chemometrics. Next, for in vitro screening of natural enzyme inhibitors the individual leaf extracts as well as composite blends were subjected to assay procedures to see their inhibitory potentials against the enzymes pathogenic in type 2 diabetes. The antioxidant potentials were also estimated by DPPH radical scavenging, ABTS, FRAP and Dot Blot assay. Results: Considering response surface methodology studies and from the solutions obtained using desirability function, it was found that hydro-ethanolic or methanolic solvent ratio of 52.46 ± 1.6 and at a temperature of 20.17 ± 0.6 gave an optimum yield of polyphenols with minimal chlorophyll leaching. The species also showed the presence of glycosides, alkaloids, and saponins. Composites in the ratios of 1:1:1 and 1:1:2 gave synergistic effects in terms of polyphenol yield and anti-oxidant potentials. All composites (1:1:1, 1:2:1, 2:1:1, 1:1:2) showed synergistic anti

  16. Nuclear magnetic resonance spectroscopy and chemometrics to identify pine nuts that cause taste disturbance.

    PubMed

    Kobler, Helmut; Monakhova, Yulia B; Kuballa, Thomas; Tschiersch, Christopher; Vancutsem, Jeroen; Thielert, Gerhard; Mohring, Arne; Lachenmeier, Dirk W

    2011-07-13

    Nontargeted 400 MHz (13)C and (1)H nuclear magnetic resonance (NMR) spectroscopy was used in the context of food surveillance to reveal Pinus species whose nuts cause taste disturbance following their consumption, the so-called pine nut syndrome (PNS). Using principal component analysis, three groups of pine nuts were distinguished. PNS-causing products were found in only one of the groups, which however also included some normal products. Sensory analysis was still required to confirm PNS, but NMR allowed the sorting of 53% of 57 samples, which belong to the two groups not containing PNS species. Furthermore, soft independent modeling of class analogy was able to classify the samples between the three groups. NMR spectroscopy was judged as suitable for the screening of pine nuts for PNS. This process may be advantageous as a means of importation control that will allow the identification of samples suitable for direct clearance and those that require further sensory analysis. PMID:21615074

  17. Visualization of latent blood stains using visible reflectance hyperspectral imaging and chemometrics.

    PubMed

    Edelman, Gerda J; van Leeuwen, Ton G; Aalders, Maurice C

    2015-01-01

    The detection of latent traces is an important aspect of crime scene investigation. Blood stains on black backgrounds can be visualized using chemiluminescence, which is invasive and requires a darkened room, or near-infrared photography, for which investigators need to change filters manually to optimize contrast. We demonstrated the performance of visible reflectance hyperspectral imaging (400-720 nm) for this purpose. Several processing methods were evaluated: single wavelength bands, ratio images, principal component analysis (PCA), and "SIMPLe-to-use Interactive Self-modeling Mixture Analysis" (SIMPLISMA). Using these methods, we were able to enhance the contrast between blood stains and 12 different fabrics. On black cotton, blood dilutions were visible with a minimal concentration of 25% of whole blood. The hyperspectral camera system used in this study is portable and wireless, which makes it suitable for crime scene use. The described technique is noncontact and nondestructive, so all traces are preserved for further analysis. PMID:25382735

  18. Traceability of 'Limone di Siracusa PGI' by a multidisciplinary analytical and chemometric approach.

    PubMed

    Amenta, M; Fabroni, S; Costa, C; Rapisarda, P

    2016-11-15

    Food traceability is increasingly relevant with respect to safety, quality and typicality issues. Lemon fruits grown in a typical lemon-growing area of southern Italy (Siracusa), have been awarded the PGI (Protected Geographical Indication) recognition as 'Limone di Siracusa'. Due to its peculiarity, consumers have an increasing interest about this product. The detection of potential fraud could be improved by using the tools linking the composition of this production to its typical features. This study used a wide range of analytical techniques, including conventional techniques and analytical approaches, such as spectral (NIR spectra), multi-elemental (Fe, Zn, Mn, Cu, Li, Sr) and isotopic ((13)C/(12)C, (18)O/(16)O) marker investigations, joined with multivariate statistical analysis, such as PLS-DA (Partial Least Squares Discriminant Analysis) and LDA (Linear Discriminant Analysis), to implement a traceability system to verify the authenticity of 'Limone di Siracusa' production. The results demonstrated a very good geographical discrimination rate. PMID:27283690

  19. Application of chemometrics in determination of the acid dissociation constants (pKa) of several benzodiazepine derivatives as poorly soluble drugs in the presence of ionic surfactants.

    PubMed

    Shayesteh, Tavakol Heidary; Radmehr, Moojan; Khajavi, Farzad; Mahjub, Reza

    2015-03-10

    In this study, the acid dissociation constants (pKa) of some benzodiazepine derivatives including chlordiazepoxide, clonazepam, lorazepam, and oxazepam in aqueous micellar solution were determined spectrophotometrically at an ionic strength of 0.1M at 25°C. The effect of cetyl trimethylammonium bromide (CTAB) as a cationic and sodium n-dodecyl sulfate(SDS) as an anionic surfactant on the absorption spectra of benzodiazepine drugs at different pH values were studied. The acidity constants of all related species are estimated by considering the surfactant concept and the application of chemometric methods using the whole spectral fitting of the collected data to an established factor analysis model. DATAN® software (Ver. 5.0, Multid Analyses AB, and Goteborg, Sweden) was applied to determine the acidity constants. In this study, a simple and fast method to determine the ionization constant (pKa) of poorly soluble drugs was developed using surfactants. The acidity constant (i.e. pKa) for chlordiazepoxide, clonazepam, lorazepam, and oxazepam were reported as 4.62, pKa1 value of 1.52 and pKa2 value of 10.51, pKa1 value of 1.53 and pKa2 value of 10.92 and pKa1 value 1.63 and pKa2 value of 11.21 respectively. The results showed that the peak values in the spectrophotometric absorption spectra of drugs are influenced by the presence of anionic and cationic surfactants. According to the results, by changing the SDS concentration from 0 to 0.05M, the pKa of chlordiazepoxide was increased to 5.9, the pKa1 of lorazepam was decreased to 0.1 while the pKa2 was increased to 11.5. Increase in SDS concentration has not shown significant alteration in pKa of clonazepam and oxazepam. Results indicate that by Changing the CTAB concentration from 0 to 0.05M, the pKa of chlordiazepoxide was reduced to 4.4, the pKa1 of clonazepam was decreased to 0.1 and the pKa2 was decreased to 9.1, the pKa1 of lorazepam was decreased to 0.4 and the pKa2 was decreased to 9.4, the pKa1 of oxazepam was

  20. Chemometrics optimization of carbohydrate separations in six food matrices by micellar electrokinetic chromatography with anionic surfactant.

    PubMed

    Meinhart, Adriana D; Ballus, Cristiano A; Bruns, Roy E; Pallone, Juliana A Lima; Godoy, Helena T

    2011-07-15

    Multivariate statistical design modeling and the Derringer-Suich desirability function analysis were applied to micellar electrokinetic chromatography (MEKC) results with anionic surfactant to separate carbohydrates (CHOs) in different food matrices. This strategy has been studied with success to analyze compounds of difficult separation, but has not been explored for carbohydrates. Six procedures for the analysis of different sets of CHOs present in six food matrices were developed. The effects of pH, electrolyte and surfactant concentrations on the separation of the compounds were investigated using a central composite design requiring 17 experiments. The simultaneous optimization of the responses for separation of six sets of CHOs was performed employing empirical models for prediction of optimal resolution conditions in six matrices, condensed milk, orange juices, rice bran, red wine, roasted and ground coffee and breakfast cereal samples. The results indicate good separation for the samples, with appropriate detectability and selectivity, short analysis time, low reagent cost and little waste generation, demonstrating that the proposed technique is a viable alternative for carbohydrate analysis in foods. PMID:21645694

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Techniques including ultraviolet-visible spectra (UV), high performance size-exclusion chromatography (HPSEC), fourier-transform infrared spectroscopy (FT-IR) and pre-column derivatization high-performance liquid chromatography (PCD-HPLC) were used in the fingerprinting analysis of Lycium barbarum p...

  3. Chemometric study of retention on binary stationary phases in gas chromatography.

    PubMed

    Bouzouane, S; Righezza, M; Touabet, A

    2012-02-01

    Using gas chromatography, data analysis is performed on a dataset consisting of 486 retention indices, 27 standards (ramified alkanes, aliphatic alcohols, and aromatic compounds), 6 pure and binary stationary phases, and three temperatures. The behavior of the pure stationary phases (OV-3, OV-225, OV-61-OH, and OV-1701-OH) and the binary stationary phases (OV-3/OV-225 and OV-61-OH/OV-1701-OH) at different temperatures (60°C-100°C) is investigated with factor and topological analysis. The influence of temperature and the nature of the mixed stationary phases on the retention indices is studied by correspondence factor analysis (CFA). The non-additivity of the retention properties of the pure phases used as mixed phases is clearly established by CFA. The topological analysis of the substituent's effect is investigated with a DARC/PELCO procedure and shows the particular influence of the stationary phase composition on the retention. The substituent effect is measured for the pure and binary stationary phases at various temperatures. The evolution of the substituent effect from the pure stationary phases to the binary phases is discussed. PMID:22298764

  4. Rapid screening for ethyl carbamate in stone-fruit spirits using FTIR spectroscopy and chemometrics.

    PubMed

    Lachenmeier, Dirk W

    2005-07-01

    Ethyl carbamate (EC, urethane, C2H5OCONH2) is a known genotoxic carcinogen of widespread occurrence in fermented food and beverages with the highest concentrations being found in stone-fruit spirits. Time-consuming procedures requiring extraction and gas chromatographic-mass spectrometric determination are regarded as reference procedures for the analysis of EC in alcoholic beverages. In this study, the rapid method of Fourier transform infrared (FTIR) spectroscopy in combination with partial least-squares (PLS) regression using selected wavelength bands is applied for the first time to the screening analysis of EC in stone fruit spirits (analysis time only 2 min). Apart from the actual content of EC in the sample, additional information was available from the FTIR spectra. This included data concerning the EC precursor hydrocyanic acid (HCN) and the maximum EC concentration which could be formed during storage. The PLS procedure was validated using an independent set of samples (Q(2) = 0.71-0.76, SEP = 0.42-0.67). The method was found to lack the accuracy required for a quantitative determination; it could only be used semi-quantitatively in the context of a screening analysis. If a rejection level of 0.8 mg L(-1) is applied as cut-off, overall correct classification rates of 85-91% for the calibration set and 77-85% for the validation set were achieved. False negative results can be avoided by lowering the cut-off to 0.6 mg L(-1). Through use of FTIR screening, 60-70% of all samples can be classified as negative and removed, leaving only conspicuous analysis results exceeding cut-off to be confirmed by complex and labour-intensive reference analyses. PMID:15995863

  5. Non-destructive fraud detection in rosehip oil by MIR spectroscopy and chemometrics.

    PubMed

    Santana, Felipe Bachion de; Gontijo, Lucas Caixeta; Mitsutake, Hery; Mazivila, Sarmento Júnior; Souza, Leticia Maria de; Borges Neto, Waldomiro

    2016-10-15

    Rosehip oil (Rosa eglanteria L.) is an important oil in the food, pharmaceutical and cosmetic industries. However, due to its high added value, it is liable to adulteration with other cheaper or lower quality oils. With this perspective, this work provides a new simple, fast and accurate methodology using mid-infrared (MIR) spectroscopy and partial least squares discriminant analysis (PLS-DA) as a means to discriminate authentic rosehip oil from adulterated rosehip oil containing soybean, corn and sunflower oils in different proportions. The model showed excellent sensitivity and specificity with 100% correct classification. Therefore, the developed methodology is a viable alternative for use in the laboratory and industry for standard quality analysis of rosehip oil since it is fast, accurate and non-destructive. PMID:27173556

  6. Automatic and Rapid Discrimination of Cotton Genotypes by Near Infrared Spectroscopy and Chemometrics

    PubMed Central

    Cui, Hai-Feng; Ye, Zi-Hong; Xu, Lu; Fu, Xian-Shu; Fan, Cui-Wen; Yu, Xiao-Ping

    2012-01-01

    This paper reports the application of near infrared (NIR) spectroscopy and pattern recognition methods to rapid and automatic discrimination of the genotypes (parent, transgenic, and parent-transgenic hybrid) of cotton plants. Diffuse reflectance NIR spectra of representative cotton seeds (n = 120) and leaves (n = 123) were measured in the range of 4000–12000 cm−1. A practical problem when developing classification models is the degradation and even breakdown of models caused by outliers. Considering the high-dimensional nature and uncertainty of potential spectral outliers, robust principal component analysis (rPCA) was applied to each separate sample group to detect and exclude outliers. The influence of different data preprocessing methods on model prediction performance was also investigated. The results demonstrate that rPCA can effectively detect outliers and maintain the efficiency of discriminant analysis. Moreover, the classification accuracy can be significantly improved by second-order derivative and standard normal variate (SNV). The best partial least squares discriminant analysis (PLSDA) models obtained total classification accuracy of 100% and 97.6% for seeds and leaves, respectively. PMID:22666635

  7. Treated water quality assurance and description of distribution networks by multivariate chemometrics.

    PubMed

    Smeti, E M; Thanasoulias, N C; Lytras, E S; Tzoumerkas, P C; Golfinopoulos, S K

    2009-10-01

    Throughout the year 2007, 89 treated water samples from three water treatment plants (WTPs) of the Athens Water Supply and Sewerage Company (EYDAP S.A.) and 180 samples from network tanks (NWTs) were analyzed for electrical conductivity (EC), alkalinity (TA), pH, aluminium (Al), total hardness (TH), chloride (Cl(-)), residual chlorine (free Cl), calcium (Ca(2+)) and magnesium (Mg(2+)). The results regarding the WTPs were subjected to a principal component analysis (PCA) with 75% of the total variance being explained. A stepwise linear discriminant analysis (LDA) model constructed from the 89 treated water samples was used to predict class membership of the samples from the NWTs with a view to estimating the propagation of a possible water quality deterioration originating from the WTPs. The model utilized Cl(-), Al and EC and yielded a 96% correct classification of the training dataset, whereas the cross-validation yielded a 94% correct classification. Network tank samples were 95% correctly classified with regard to their theoretically expected origin. The stepwise discriminant analysis based on separate covariance matrices of the canonical discriminant functions yielded a 98% correct classification of both the training dataset and the network tank samples. The classification and regression tree (C&RT) algorithm showed that the main parameters used in the discrimination of the WTP samples were EC and Al. The post-hoc classification of the training dataset was 99%, whereas 88% of NWT samples were correctly classified. PMID:19674765

  8. Urban air quality assessment using monitoring data of fractionized aerosol samples, chemometrics and meteorological conditions.

    PubMed

    Yotova, Galina I; Tsitouridou, Roxani; Tsakovski, Stefan L; Simeonov, Vasil D

    2016-01-01

    The present article deals with assessment of urban air by using monitoring data for 10 different aerosol fractions (0.015-16 μm) collected at a typical urban site in City of Thessaloniki, Greece. The data set was subject to multivariate statistical analysis (cluster analysis and principal components analysis) and, additionally, to HYSPLIT back trajectory modeling in order to assess in a better way the impact of the weather conditions on the pollution sources identified. A specific element of the study is the effort to clarify the role of outliers in the data set. The reason for the appearance of outliers is strongly related to the atmospheric condition on the particular sampling days leading to enhanced concentration of pollutants (secondary emissions, sea sprays, road and soil dust, combustion processes) especially for ultra fine and coarse particles. It is also shown that three major sources affect the urban air quality of the location studied-sea sprays, mineral dust and anthropogenic influences (agricultural activity, combustion processes, and industrial sources). The level of impact is related to certain extent to the aerosol fraction size. The assessment of the meteorological conditions leads to defining of four downwind patterns affecting the air quality (Pelagic, Western and Central Europe, Eastern and Northeastern Europe and Africa and Southern Europe). Thus, the present study offers a complete urban air assessment taking into account the weather conditions, pollution sources and aerosol fractioning. PMID:26942452

  9. Classification of commercial wines from the Canary Islands (Spain) by chemometric techniques using metallic contents.

    PubMed

    Frías, Sergio; Conde, José E; Rodríguez-Bencomo, Juan J; García-Montelongo, Francisco; Pérez-Trujillo, Juan P

    2003-02-01

    Eleven elements, K, Na, Ca, Mg, Fe, Cu, Zn, Mn, Sr, Li and Rb, were determined in dry and sweet wines bearing the denominations of origin of El Hierro, La Palma and Lanzarote islands (Canary Islands, Spain). Analyses were performed by flame atomic absorption spectrophotometry, with the exceptions of lithium and rubidium for which flame atomic emission spectrophotometry was used. Sweet wines from La Palma were elaborated as naturally sweet with over-ripe grapes and significant differences were found in all the analysed elements with the exceptions of sodium, iron and rubidium with regard to dry wines from the same island. Contrarily, sweet wines from Lanzarote elaborated with grapes in a similar ripening state to dry wines did not present significant differences between them with the exception of strontium, the content of which was greater in dry wines. Among the three islands, significant differences in mean content were found with the exceptions of iron and copper. Cluster analysis and principal component analysis show differences in wines according to the island of origin and the ripening state of the grapes. Linear discriminant analysis using rubidium, sodium, manganese and strontium, the four most discriminant elements, gave 100% recognition ability and 95.6% prediction ability. The sensitivity and specificity obtained using soft independent modelling of class analogy (SIMCA) as a modelling multivariate technique were both 100% for El Hierro and Lanzarote, and 100 and 95%, respectively, for La Palma. The modelling and discriminant capacities of the different metals were also studied. PMID:18968916

  10. Simultaneously detection of calcium and magnesium in various samples by calmagite and chemometrics data processing.

    PubMed

    Rasouli, Zolaikha; Ghavami, Raouf

    2016-12-01

    The current study describes results of the application of radial basis function-partial least squares (RBF-PLS), partial robust M-regression (PRM), singular value decomposition (SVD), evolving factor analysis (EFA), multivariate curve resolution with alternating least squares (MCR-ALS) and rank annihilation factor analysis (RAFA) methods for the purposes of simultaneous determination of trace amounts calcium (Ca(2+)) and magnesium (Mg(2+)) and exploratory analysis based on their colored complexes formation with 1-(1-hydroxy-4-methyl-2-phenylazo)-2-naphthol-4-sulfonic acid (calmagite) as chromomeric reagent. The complex formation Ca(2+) and Mg(2+) with calmagite was investigated under pH10.20. The performance of RBF-PLS model in detection of minerals was compared with PRM as a linear model. The pure concentration and spectral profiles were obtained using MCR-ALS. EFA and SVD were used to distinguish the number species. The stability constants of the complexes were derived using RAFA. Finally, RBF-PLS was utilized for simultaneous determination of minerals in pharmaceutical formulation and various vegetable samples. PMID:27341399

  11. Quantitative analysis of total amino acid in barley leaves under herbicide stress using spectroscopic technology and chemometrics.

    PubMed

    Bao, Yidan; Kong, Wenwen; He, Yong; Liu, Fei; Tian, Tian; Zhou, Weijun

    2012-01-01

    Visible and near infrared (Vis/NIR) spectroscopy were employed for the fast and nondestructive estimation of the total amino acid (TAA) content in barley (Hordeum vulgare L.) leaves. The calibration set was composed of 50 samples; and the remaining 25 samples were used for the validation set. Seven different spectral preprocessing methods and six different calibration methods (linear and nonlinear) were applied for a comprehensive prediction performance comparison. Successive projections algorithm (SPA) and regression coefficients (RC) were applied to select effective wavelengths (EWs). The results indicated that the latent variables-least-squares-support vector machine (LV-LS-SVM) model achieved the optimal performance. The prediction results by LV-LS-SVM with raw spectra were achieved with a correlation coefficients (r) = 0.937 and root mean squares error of prediction (RMSEP) = 0.530. The overall results showed that the NIR spectroscopy could be used for determination of TAA content in barley leaves with an excellent prediction precision; and the results were also helpful for on-field monitoring of barley growing status under herbicide stress during different growth stages. PMID:23202000

  12. Chemometric analysis of attenuated total reflectance infrared spectra of Proteus mirabilis strains with defined structures of LPS.

    PubMed

    Zarnowiec, Paulina; Mizera, Andrzej; Chrapek, Magdalena; Urbaniak, Mariusz; Kaca, Wieslaw

    2016-07-01

    Proteus spp. strains are some of the most important pathogens associated with complicated urinary tract infections and bacteremia affecting patients with immunodeficiency and long-term urinary catheterization. For epidemiological purposes, various molecular typing methods have been developed for this pathogen. However, these methods are labor intensive and time consuming. We evaluated a new method of differentiation between strains. A collection of Proteus spp. strains was analyzed by attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy in the mid-infrared region. ATR FT-IR spectroscopy used in conjunction with a diamond ATR accessory directly produced the biochemical profile of the surface chemistry of bacteria. We conclude that a combination of ATR FT-IR spectroscopy and mathematical modeling provides a fast and reliable alternative for discrimination between Proteus isolates, contributing to epidemiological research. PMID:27189426

  13. Use of flow injection mass spectrometric fingerprinting and chemometrics for differentiation of three black cohosh species

    NASA Astrophysics Data System (ADS)

    Huang, Huilian; Sun, Jianghao; McCoy, Joe-Ann; Zhong, Haiyan; Fletcher, Edward J.; Harnly, James; Chen, Pei

    2015-03-01

    Flow injection mass spectrometry (FIMS) was used to provide chemical fingerprints of black cohosh (Actaea racemosa L.) in a manner of minutes by omitting the separation step. This method has proven to be a powerful tool for botanical authentication and in this study it was used to distinguish between three Actaea species prior to a more detailed chemical analysis using ultra high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS). Black cohosh has become increasingly popular as a dietary supplement in the United States for the treatment of symptoms related to menopause. However, it has been known to be adulterated with the Asian Actaea dahurica (Turcz. ex Fisch. & C.A.Mey.) Franch. species (syn. Cimicifuga dahurica (Turcz.) Maxim). Existing methods for identification of black cohosh and differentiation of Actaea species are usually lengthy, laborious, and lack robustness, often based on the comparison of a few pre-selected components. Chemical fingerprints were obtained for 77 black cohosh samples and their related species using FIMS in the negative ion mode. The analysis time for each sample was less than 2 min. All data were processed using principal component analysis (PCA). FIMS fingerprints could readily differentiate all three species. Representative samples from each of the three species were further examined using UHPLC-MS to provide detailed profiles of the chemical differences between the three species and were compared to the PCA loadings. This study demonstrates a simple, fast, and easy analytical method that can be used to differentiate A. racemosa, Actaea podocarpa, and A. dahurica.

  14. A comparison of different chemometrics approaches for the robust classification of electronic nose data.

    PubMed

    Gromski, Piotr S; Correa, Elon; Vaughan, Andrew A; Wedge, David C; Turner, Michael L; Goodacre, Royston

    2014-11-01

    Accurate detection of certain chemical vapours is important, as these may be diagnostic for the presence of weapons, drugs of misuse or disease. In order to achieve this, chemical sensors could be deployed remotely. However, the readout from such sensors is a multivariate pattern, and this needs to be interpreted robustly using powerful supervised learning methods. Therefore, in this study, we compared the classification accuracy of four pattern recognition algorithms which include linear discriminant analysis (LDA), partial least squares-discriminant analysis (PLS-DA), random forests (RF) and support vector machines (SVM) which employed four different kernels. For this purpose, we have used electronic nose (e-nose) sensor data (Wedge et al., Sensors Actuators B Chem 143:365-372, 2009). In order to allow direct comparison between our four different algorithms, we employed two model validation procedures based on either 10-fold cross-validation or bootstrapping. The results show that LDA (91.56% accuracy) and SVM with a polynomial kernel (91.66% accuracy) were very effective at analysing these e-nose data. These two models gave superior prediction accuracy, sensitivity and specificity in comparison to the other techniques employed. With respect to the e-nose sensor data studied here, our findings recommend that SVM with a polynomial kernel should be favoured as a classification method over the other statistical models that we assessed. SVM with non-linear kernels have the advantage that they can be used for classifying non-linear as well as linear mapping from analytical data space to multi-group classifications and would thus be a suitable algorithm for the analysis of most e-nose sensor data. PMID:25286877

  15. Detection and quantification of hogwash oil in soybean oils using low-cost spectroscopy and chemometrics

    NASA Astrophysics Data System (ADS)

    Mignani, A. G.; Ciaccheri, L.; Mencaglia, A. A.; Cichelli, A.; Xing, J.; Yang, X.; Sun, W.; Yuan, L.

    2013-05-01

    This paper presents the detection and quantification of hogwash oil in soybean oils by means of absorption spectroscopy. Three types of soybean oils were adulterated with different concentrations of hogwash oil. The spectra were measured in the visible band using a white LED and a low-cost spectrometer. The measured spectra were processed by means of multivariate analysis to distinguish the adulteration and, for each soybean oil, to quantify the adulterant concentration. Then the visible spectra were sliced into two bands for modeling a simple setup made of two LEDs only. The successful results indicate potentials for implementing a smartphone-compatible device for self-assessment of soybean oil quality.

  16. Application of chemometric studies to metal concentrations in molluscs from the Strait of Magellan (Chile).

    PubMed

    España, M S Astorga; Rodríguez, E M Rodríguez; Romero, C Díaz

    2007-05-01

    Na, K, Ca, Mg, Fe, Cu, Zn, Mn, Se, Ni, and Cd concentrations were determined in 126 mollusc samples belonging to five different species (Mytilus chilensis, n = 47; Nacella deaurata, n = 65; Aulacomya ater, n = 4; Fissurella picta, n = 4; Acanthina monodon, n = 6) collected from the coasts of the Strait of Magellan. The metals analysed presented significant differences between the mean concentrations for the mollusc species considered. Factor and discriminant analyses made possible the differentiation of the mollusc species. In addition, when discriminant analysis was used, good classifications were obtained according to sampling zone and weight-to-length ratio of the organisms. PMID:17375348

  17. Screening of prostate cancer by analyzing trace elements in hair and chemometrics.

    PubMed

    Tan, Chao; Chen, Hui

    2011-12-01

    Prostate cancer is the most common non-cutaneous malignancy and second leading cause of cancer mortality in men. The principle goal of this study was explore the feasibility of applying boosting coupled with trace element analysis of hair, for accurately distinguishing prostate cancer from healthy person. A total of 113 subjects containing 55 healthy men and 58 prostate cancers were collected. Based on a special index of variable importance and a forward selection scheme, only nine elements (i.e., Zn, Cr, Mg, Ca, Al, P, Cd, Fe, and Mo) were picked out from 20 candidate elements for modeling the relationship. As a result, an ensemble classifier consisting of only eight decision stumps achieved an overall accuracy of 98.2%, a sensitivity of 100%, and a specificity of 96.4% on the independent test set while all subjects on the training set are classified correctly. It seems that integrating boosting and element analysis of hair can serve as a valuable tool of diagnosing prostate cancer in practice. PMID:21452047

  18. Freshness estimation of intact frozen fish using fluorescence spectroscopy and chemometrics of excitation-emission matrix.

    PubMed

    ElMasry, Gamal; Nagai, Hiroto; Moria, Keisuke; Nakazawa, Naho; Tsuta, Mizuki; Sugiyama, Junichi; Okazaki, Emiko; Nakauchi, Shigeki

    2015-10-01

    The current study attempted to provide a convenient, non-invasive and time-saving method to estimate the freshness of intact horse mackerel (Trachurus japonicus) fish in a frozen state using autofluorescence spectroscopy in tandem with multivariate analysis of fluorescence excitation-emission matrices (EEM). The extracted fluorescence data from different freshness conditions were pretreated, masked and reorganized to resolve fish fluorescence spectra from overlapping signals and scattering profiles for detecting and characterizing freshness changes. The real freshness values of the examined fish samples were then traditionally determined by the hard chemical analysis using the high performance liquid chromatography (HPLC) method and expressed as K-values. The fluorescence EEM data and the real freshness values were modeled using partial least square (PLS) regression and a novel algorithm was proposed to identify the ideal combinations of excitation and emission wavelengths being used as perfect predictors. The results revealed that freshness of frozen fish could be accurately predicted with R(2) of 0.89 and root mean square error estimated by cross validation (RMSECV) of 9.66%. This work substantially demonstrated that the autofluorescence spectroscopy associated with the proposed technical approaches has a high potential in non-destructive sensing of fish freshness in the frozen state. PMID:26078142

  19. Anionic Forensic Signatures for Sample Matching of Potassium Cyanide Using High Performance Ion Chromatography and Chemometrics

    SciTech Connect

    Fraga, Carlos G.; Farmer, Orville T.; Carman, April J.

    2011-01-30

    Potassium cyanide, a known poison, was used a model compound to determine the feasibility of using anionic impurities as a forensic signature for matching KCN samples back to their source. In this study, portions of eight KCN stocks originating from four countries were separately dissolved in water and analyzed by high performance ion chromatography (HPIC) using an anion exchange column and conductivity detection. Sixty KCN aqueous samples were produced from the eight stocks and analyzed for 11anionic impurities. Hierarchal cluster analysis and principal component analysis were used to demonstrate that KCN samples cluster according to source based on the concentrations of their anionic impurities. The F-ratio method and degree-of-class separation (DCS) were used for feature selection on a training set of KCN samples in order to optimize sample clustering. The optimal subset of anions needed for sample classification was determined to be sulfate, oxalate, phosphate, and an unknown anion named unk5. Using K-nearest neighbors (KNN) and the optimal subset of anions, KCN test samples from different KCN stocks were correctly determined to be manufactured in the United States. In addition, KCN samples from stocks manufactured in Belgium, Germany, and the Czech Republic were all correctly matched back to their original stocks because each stock had a unique anionic impurity profile. The application of the F-ratio method and DCS for feature selection improved the accuracy and confidence of sample classification by KNN.

  20. Compression map, functional groups and fossilization: A chemometric approach (Pennsylvanian neuropteroid foliage, Canada)

    USGS Publications Warehouse

    D'Angelo, J. A.; Zodrow, E.L.; Mastalerz, Maria

    2012-01-01

    Nearly all of the spectrochemical studies involving Carboniferous foliage of seed-ferns are based on a limited number of pinnules, mainly compressions. In contrast, in this paper we illustrate working with a larger pinnate segment, i.e., a 22-cm long neuropteroid specimen, compression-preserved with cuticle, the compression map. The objective is to study preservation variability on a larger scale, where observation of transparency/opacity of constituent pinnules is used as a first approximation for assessing the degree of pinnule coalification/fossilization. Spectrochemical methods by Fourier transform infrared spectrometry furnish semi-quantitative data for principal component analysis.The compression map shows a high degree of preservation variability, which ranges from comparatively more coalified pinnules to less coalified pinnules that resemble fossilized-cuticles, noting that the pinnule midveins are preserved more like fossilized-cuticles. A general overall trend of coalified pinnules towards fossilized-cuticles, i.e., variable chemistry, is inferred from the semi-quantitative FTIR data as higher contents of aromatic compounds occur in the visually more opaque upper location of the compression map. The latter also shows a higher condensation of the aromatic nuclei along with some variation in both ring size and degree of aromatic substitution. From principal component analysis we infer correspondence between transparency/opacity observation and chemical information which correlate with varying degree to fossilization/coalification among pinnules. ?? 2011 Elsevier B.V.

  1. Chemometric Study of Trace Elements in Hard Coals of the Upper Silesian Coal Basin, Poland

    PubMed Central

    Rompalski, Przemysław; Cybulski, Krzysztof; Chećko, Jarosław

    2014-01-01

    The objective of the study was the analysis of trace elements contents in coals of the Upper Silesian Coal Basin (USCB), which may pose a potential threat to the environment when emitted from coal processing systems. Productive carbon overburden in central and southern zones of the USCB is composed mostly of insulating tertiary formations of a thickness from a few m to 1,100 m, and is represented by Miocene and Pliocene formations. In the data study the geological conditions of the coal seams of particular zones of the USCB were taken into account and the hierarchical clustering analysis was applied, which enabled the exploration of the dissimilarities between coal samples of various zones of the USCB in terms of basic physical and chemical parameters and trace elements contents. Coals of the northern and eastern zones of the USCB are characterized by high average Hg and low average Ba, Cr, and Ni contents, whereas coals of southern and western zones are unique due to high average concentrations of Ba, Co, Cu, Ni, and V. Coals of the central part of the USCB are characterized by the highest average concentration of Mn and the lowest average concentrations of As, Cd, Pb, V, and Zn. PMID:24967424

  2. Chemometric treatment of multimode laser-induced fluorescence (LIF) data of fuel-spiked soils

    NASA Astrophysics Data System (ADS)

    Van Benthem, Mark H.; Mitchell, Ben C.; Gillispie, Gregory D.; St. Germain, Randy W.

    1996-11-01

    Field screening of fuel-contaminated soils using laser- induced fluorescence is a cost effective and timely method of characterizing contaminated sites. Data collected with laser-based screening tools are often extensive and difficult to interpret. Pattern recognition algorithms can be utilized to enable less highly trained personnel to identify contaminants. In this work, fluorescence intensity of various hydrocarbon fuels deposited on various soil types was measured as a function of emission wavelength and decay time, generating wavelength-time matrices. The data were arranged into a three mode array and subjected to trilinear decomposition (TLD). The results of the TLD were then utilized in pattern recognition schemes, specifically, linear discrimination and classification and hierarchical cluster analysis. Classification rates and clustering results indicate that these techniques can be very valuable tools in site characterization.

  3. Chemometric treatment of multimode laser-induced fluorescence (LIF) data of fuel-spiked soils

    SciTech Connect

    Van Benthem, M.H.; Mitchell, B.C.; Gillispie, G.D.; St. Germain, R.W.

    1996-12-31

    Field screening of fuel-contaminated soils using laser-induced fluorescence is a cost effective and timely method of characterizing contaminated sites. Data collected with laser-based screening tools are often extensive and difficult to interpret. Pattern recognition algorithms can be utilized to enable less highly trained personnel to identify contaminants. In this work, fluorescence intensity of various hydrocarbon fuels deposited on various soil types was measured as a function of emission wavelength and decay time, generating wavelength-time matrices (WTMs). The data were arranged into a three mode array and subjected to trilinear decomposition (TLD). The results of the TLD were then utilized in pattern recognition schemes, specifically, linear discrimination and classification and hierarchical cluster analysis. Classification rates and clustering results indicate that these techniques can be very valuable tools in site characterization.

  4. Nuclear magnetic resonance and chemometrics to assess geographical origin and quality of traditional food products.

    PubMed

    Consonni, R; Cagliani, L R

    2010-01-01

    In this globalization era, the opening of the markets has put at almost everybody's disposal a wide variety of foods, allowing everybody to taste food flavors and aromas from different nations. Notwithstanding this opportunity, countries try to preserve their markets by developing protection policies. A few countries have adopted different denominations to label their "typical food" products in order to give them additional value. Besides, the term "typical food" is widely thought of as something anchored to the local traditions, with geographical meaning and made with typical raw materials. Then a "typical food" starts to be considered "traditional" when it is made following specific and old recipes. As a matter of fact, these products acquire particular organoleptic characteristics that are not reproducible when produced in different places. In this review, NMR studies coupled to multivariate statistical analysis are presented with the aim of determining geographical origin and key quality characteristics. PMID:20610175

  5. A novel approach for honey pollen profile assessment using an electronic tongue and chemometric tools.

    PubMed

    Dias, Luís G; Veloso, Ana C A; Sousa, Mara E B C; Estevinho, Letícia; Machado, Adélio A S C; Peres, António M

    2015-11-01

    Nowadays the main honey producing countries require accurate labeling of honey before commercialization, including floral classification. Traditionally, this classification is made by melissopalynology analysis, an accurate but time-consuming task requiring laborious sample pre-treatment and high-skilled technicians. In this work the potential use of a potentiometric electronic tongue for pollinic assessment is evaluated, using monofloral and polyfloral honeys. The results showed that after splitting honeys according to color (white, amber and dark), the novel methodology enabled quantifying the relative percentage of the main pollens (Castanea sp., Echium sp., Erica sp., Eucaliptus sp., Lavandula sp., Prunus sp., Rubus sp. and Trifolium sp.). Multiple linear regression models were established for each type of pollen, based on the best sensors' sub-sets selected using the simulated annealing algorithm. To minimize the overfitting risk, a repeated K-fold cross-validation procedure was implemented, ensuring that at least 10-20% of the honeys were used for internal validation. With this approach, a minimum average determination coefficient of 0.91 ± 0.15 was obtained. Also, the proposed technique enabled the correct classification of 92% and 100% of monofloral and polyfloral honeys, respectively. The quite satisfactory performance of the novel procedure for quantifying the relative pollen frequency may envisage its applicability for honey labeling and geographical origin identification. Nevertheless, this approach is not a full alternative to the traditional melissopalynologic analysis; it may be seen as a practical complementary tool for preliminary honey floral classification, leaving only problematic cases for pollinic evaluation. PMID:26572837

  6. Chemometrics models for assessment of oxidative stress risk in chrome-electroplating workers.

    PubMed

    Zendehdel, Rezvan; Shetab-Boushehri, Seyed Vahid; Azari, Mansoor R; Hosseini, Vajihe; Mohammadi, Hamidreza

    2015-04-01

    Oxidative stress is the main cause of hexavalant chromium-induced damage in chrome electroplating workers. The main goal of this study is toxicity analysis and the possibility of toxicity risk categorizing in the chrome electroplating workers based on oxidative stress parameters as prognostic variables. We assessed blood chromium levels and biomarkers of oxidative stress such as lipid peroxidation, thiol (SH) groups and antioxidant capacity of plasma. Data were subjected to principle component analysis (PCA) and artificial neuronal network (ANN) to obtain oxidative stress pattern for chrome electroplating workers. Blood chromium levels increased from 4.42 ppb to 10.6 ppb. Induction of oxidative stress was observed by increased in lipid peroxidation (22.38 ± 10.47 μM versus 14.74 ± 4.82 μM, p < 0.0008), decreased plasma antioxidant capacity (3.17 ± 1.35 μM versus 7.74 ± 4.45 μM, p < 0.0001) and plasma total thiol (SH groups) (0.21 ± 0.07 μM versus 0.45 ± 0.41 μM, p < 0.0042) in comparison to controls. Based on the oxidative parameters, two groups were identified by PCA methods. One category is workers with the risk of oxidative stress and second group is subjects with probable risk of oxidative stress induction. ANN methods can predict oxidative-risk category for assessment of toxicity induction in chrome electroplaters. The result showed multivariate modeling can be interpreted as the induced biochemical toxicity in the workers exposed to hexavalent chromium. Different occupation groups were assessed on the basis of risk level of oxidative stress which could further justify proceeding engineering control measures. PMID:24896654

  7. Irradiation dose detection of irradiated milk powder using visible and near-infrared spectroscopy and chemometrics.

    PubMed

    Kong, W W; Zhang, C; Liu, F; Gong, A P; He, Y

    2013-08-01

    The objective of this study was to examine the possibility of applying visible and near-infrared spectroscopy to the quantitative detection of irradiation dose of irradiated milk powder. A total of 150 samples were used: 100 for the calibration set and 50 for the validation set. The samples were irradiated at 5 different dose levels in the dose range 0 to 6.0 kGy. Six different pretreatment methods were compared. The prediction results of full spectra given by linear and nonlinear calibration methods suggested that Savitzky-Golay smoothing and first derivative were suitable pretreatment methods in this study. Regression coefficient analysis was applied to select effective wavelengths (EW). Less than 10 EW were selected and they were useful for portable detection instrument or sensor development. Partial least squares, extreme learning machine, and least squares support vector machine were used. The best prediction performance was achieved by the EW-extreme learning machine model with first-derivative spectra, and correlation coefficients=0.97 and root mean square error of prediction=0.844. This study provided a new approach for the fast detection of irradiation dose of milk powder. The results could be helpful for quality detection and safety monitoring of milk powder. PMID:23769357

  8. Chemometric discrimination of genetically modified Coffea arabica cultivars using spectroscopic and chromatographic fingerprints.

    PubMed

    Moreira, Ivanira; Scarminio, Ieda Spacino

    2013-03-30

    Multivariate statistical design and principal component analysis (PCA) applied to RP-HPLC-DAD and FTIR spectroscopic data were performed to investigate the fingerprints of four coffee cultivars, traditional red bourbon and three genetically modified cultivars. The design and response surface results showed that extraction dependence on solvent composition of one of the genetically modified cultivars, IAPAR 59, was very similar to that found for the red bourbon standard. PCA of the FTIR spectra obtained from all the simplex centroid design mixtures indicated that the 1:1 binary ethanol-dichloromethane solution resulted in the best separation of the four cultivars. The IPR 108 cultivar has more intense vibrational bands in the 3200-3,600 cm(-1) and 1100-1,600 cm(-1) regions indicating higher acid and fat levels than those of the other cultivars. The UV absorptions close to 275 nm of the RP-HPLC-DAD spectra are correlated with the strengths of the infrared absorptions between 3400 and 3,460 cm(-1) and can be explained by varying caffeine concentrations in the four cultivars. PMID:23598243

  9. Chemometrics in biomonitoring: Distribution and correlation of trace elements in tree leaves.

    PubMed

    Deljanin, Isidora; Antanasijević, Davor; Bjelajac, Anđelika; Urošević, Mira Aničić; Nikolić, Miroslav; Perić-Grujić, Aleksandra; Ristić, Mirjana

    2016-03-01

    The concentrations of 15 elements were measured in the leaf samples of Aesculus hippocastanum, Tilia spp., Betula pendula and Acer platanoides collected in May and September of 2014 from four different locations in Belgrade, Serbia. The objective was to assess the chemical characterization of leaf surface and in-wax fractions, as well as the leaf tissue element content, by analyzing untreated, washed with water and washed with chloroform leaf samples, respectively. The combined approach of self-organizing networks (SON) and Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) aided by Geometrical Analysis for Interactive Aid (GAIA) was used in the interpretation of multiple element loads on/in the tree leaves. The morphological characteristics of the leaf surfaces and the elemental composition of particulate matter (PM) deposited on tree leaves were studied by using scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS) detector. The results showed that the amounts of retained and accumulated element concentrations depend on several parameters, such as chemical properties of the element and morphological properties of the leaves. Among the studied species, Tilia spp. was found to be the most effective in the accumulation of elements in leaf tissue (70% of the total element concentration), while A. hippocastanum had the lowest accumulation (54%). After water and chloroform washing, the highest percentages of removal were observed for Al, V, Cr, Cu, Zn, As, Cd and Sb (>40%). The PROMETHEE/SON ranking/classifying results were in accordance with the results obtained from the GAIA clustering techniques. The combination of the techniques enabled extraction of additional information from datasets. Therefore, the use of both the ranking and clustering methods could be a useful tool to be applied in biomonitoring studies of trace elements. PMID:26748000

  10. Identification of Different Varieties of Sesame Oil Using Near-Infrared Hyperspectral Imaging and Chemometrics Algorithms

    PubMed Central

    Xie, Chuanqi; Wang, Qiaonan; He, Yong

    2014-01-01

    This study investigated the feasibility of using near infrared hyperspectral imaging (NIR-HSI) technique for non-destructive identification of sesame oil. Hyperspectral images of four varieties of sesame oil were obtained in the spectral region of 874–1734 nm. Reflectance values were extracted from each region of interest (ROI) of each sample. Competitive adaptive reweighted sampling (CARS), successive projections algorithm (SPA) and x-loading weights (x-LW) were carried out to identify the most significant wavelengths. Based on the sixty-four, seven and five wavelengths suggested by CARS, SPA and x-LW, respectively, two classified models (least squares-support vector machine, LS-SVM and linear discriminant analysis,LDA) were established. Among the established models, CARS-LS-SVM and CARS-LDA models performed well with the highest classification rate (100%) in both calibration and prediction sets. SPA-LS-SVM and SPA-LDA models obtained better results (95.59% and 98.53% of classification rate in prediction set) with only seven wavelengths (938, 1160, 1214, 1406, 1656, 1659 and 1663 nm). The x-LW-LS-SVM and x-LW-LDA models also obtained satisfactory results (>80% of classification rate in prediction set) with the only five wavelengths (921, 925, 995, 1453 and 1663 nm). The results showed that NIR-HSI technique could be used to identify the varieties of sesame oil rapidly and non-destructively, and CARS, SPA and x-LW were effective wavelengths selection methods. PMID:24879306

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

    PubMed Central

    Thornton, Mark A.; Thornton, Roy J.

    2013-01-01

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

  12. Simultaneous determination of hydrocarbon renewable diesel, biodiesel and petroleum diesel contents in diesel fuel blends using near infrared (NIR) spectroscopy and chemometrics.

    PubMed

    Alves, Julio Cesar Laurentino; Poppi, Ronei Jesus

    2013-11-01

    Highly polluting fuels based on non-renewable resources such as fossil fuels need to be replaced with potentially less polluting renewable fuels derived from vegetable or animal biomass, these so-called biofuels, are a reality nowadays and many countries have started the challenge of increasing the use of different types of biofuels, such as ethanol and biodiesel (fatty acid alkyl esters), often mixed with petroleum derivatives, such as gasoline and diesel, respectively. The quantitative determination of these fuel blends using simple, fast and low cost methods based on near infrared (NIR) spectroscopy combined with chemometric methods has been reported. However, advanced biofuels based on a mixture of hydrocarbons or a single hydrocarbon molecule, such as farnesane (2,6,10-trimethyldodecane), a hydrocarbon renewable diesel, can also be used in mixtures with biodiesel and petroleum diesel fuel and the use of NIR spectroscopy for the quantitative determination of a ternary fuel blend of these two hydrocarbon-based fuels and biodiesel can be a useful tool for quality control. This work presents a development of an analytical method for the quantitative determination of hydrocarbon renewable diesel (farnesane), biodiesel and petroleum diesel fuel blends using NIR spectroscopy combined with chemometric methods, such as partial least squares (PLS) and support vector machines (SVM). This development leads to a more accurate, simpler, faster and cheaper method when compared to the standard reference method ASTM D6866 and with the main advantage of providing the individual quantification of two different biofuels in a mixture with petroleum diesel fuel. Using the developed PLS model the three fuel blend components were determined simultaneously with values of root mean square error of prediction (RMSEP) of 0.25%, 0.19% and 0.38% for hydrocarbon renewable diesel, biodiesel and petroleum diesel, respectively, the values obtained were in agreement with those suggested by

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

    PubMed Central

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

    2013-01-01

    Chemometrics-assisted UV spectrophotometric and RP-HPLC methods are presented for the simultaneous determination of tolperisone hydrochloride (TOL) and diclofenac sodium (DIC) from their combined pharmaceutical dosage form. Chemometric methods are based on principal component regression and partial least-square regression models. Two sets of standard mixtures, calibration sets, and validation sets were prepared. Both models were optimized to quantify each drug in the mixture using the information included in the UV absorption spectra of the appropriate solution in the range 241–290 nm with the intervals λ = 1 nm at 50 wavelengths. The optimized models were successfully applied to the simultaneous determination of these drugs in synthetic mixture and pharmaceutical formulation. In addition, an HPLC method was developed using a reversed-phase C18 column at ambient temperature with a mobile phase consisting of methanol:acetonitrile:water (60:30:10 v/v/v), pH-adjusted to 3.0, with UV detection at 275 nm. The methods were validated in terms of linearity, accuracy, precision, sensitivity, specificity, and robustness in the range of 3–30 μg/mL for TOL and 1–10 μg/mL for DIC. The robustness of the HPLC method was tested using an experimental design approach. The developed HPLC method, and the PCR and PLS models were used to determine the amount of TOL and DIC in tablets. The data obtained from the PCR and PLS models were not significantly different from those obtained from the HPLC method at 95% confidence limit. PMID:24482768

  14. The feasibility of using near-infrared spectroscopy and chemometrics for untargeted detection of protein adulteration in yogurt: removing unwanted variations in pure yogurt.

    PubMed

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

    2013-01-01

    Untargeted detection of protein adulteration in Chinese yogurt was performed using near-infrared (NIR) spectroscopy and chemometrics class modelling techniques. sixty yogurt samples were prepared with pure and fresh milk from local market, and 197 adulterated yogurt samples were prepared by blending the pure yogurt objects with different levels of edible gelatin, industrial gelatin, and soy protein powder, which have been frequently used for yogurt adulteration. A recently proposed one-class partial least squares (OCPLS) model was used to model the NIR spectra of pure yogurt objects and analyze those of future objects. To improve the raw spectra, orthogonal projection (OP) of raw spectra onto the spectrum of pure water and standard normal variate (SNV) transformation were used to remove unwanted spectral variations. The best model was obtained with OP preprocessing with sensitivity of 0.900 and specificity of 0.949. Moreover, adulterations of yogurt with 1% (w/w) edible gelatin, 2% (w/w) industrial gelatin, and 2% (w/w) soy protein powder can be safely detected by the proposed method. This study demonstrates the potential of combining NIR spectroscopy and OCPLS as an untargeted detection tool for protein adulteration in yogurt. PMID:23844318

  15. The Feasibility of Using Near-Infrared Spectroscopy and Chemometrics for Untargeted Detection of Protein Adulteration in Yogurt: Removing Unwanted Variations in Pure Yogurt

    PubMed Central

    Xu, Lu; Yan, Si-Min; Wang, Zhen-Ji; Yu, Xiao-Ping

    2013-01-01

    Untargeted detection of protein adulteration in Chinese yogurt was performed using near-infrared (NIR) spectroscopy and chemometrics class modelling techniques. sixty yogurt samples were prepared with pure and fresh milk from local market, and 197 adulterated yogurt samples were prepared by blending the pure yogurt objects with different levels of edible gelatin, industrial gelatin, and soy protein powder, which have been frequently used for yogurt adulteration. A recently proposed one-class partial least squares (OCPLS) model was used to model the NIR spectra of pure yogurt objects and analyze those of future objects. To improve the raw spectra, orthogonal projection (OP) of raw spectra onto the spectrum of pure water and standard normal variate (SNV) transformation were used to remove unwanted spectral variations. The best model was obtained with OP preprocessing with sensitivity of 0.900 and specificity of 0.949. Moreover, adulterations of yogurt with 1% (w/w) edible gelatin, 2% (w/w) industrial gelatin, and 2% (w/w) soy protein powder can be safely detected by the proposed method. This study demonstrates the potential of combining NIR spectroscopy and OCPLS as an untargeted detection tool for protein adulteration in yogurt. PMID:23844318

  16. A chemometric approach toward the detection and quantification of coffee adulteration by solid-phase microextraction using polymeric ionic liquid sorbent coatings.

    PubMed

    Toledo, Bruna R; Hantao, Leandro W; Ho, Tien D; Augusto, Fabio; Anderson, Jared L

    2014-06-13

    Solid-phase microextraction (SPME) using cross-linked polymeric ionic liquid (PIL)-based sorbent coatings was used to extract volatile aroma-related compounds from coffee samples. Several PIL-based coatings were screened alongside a commercial poly(acrylate) (PA) SPME coating. The best performing PIL-based SPME fiber, poly(1-vinyl-3-hexadecylimidazolium bis[(trifluoromethyl)sulfonylimide]) with 50% (w/w) 1,12-di(3-vinylbenzylimidazolium)dodecane dibis[(trifluoromethyl)sulfonyl]imide incorporated cross-linker, was used to isolate the volatile fraction of Arabica coffee. To illustrate the importance of trace analyte isolation, a method for the detection and quantification of coffee adulteration is described. Chromatographic profiles obtained by gas chromatography/mass spectrometry (GC/MS) were used to create the chemometric model. Partial least squares (PLS) regression was employed to correlate the aroma-related chemical fingerprint to the degree of adulteration. The proposed method successfully detected fraud down to 1% (w/w) of adulterant and accurately determined the degree of coffee adulteration (i.e, root mean square error of calibration and prediction of 0.54% and 0.83% (w/w), respectively). Finally, important aroma-related compounds including furans, methoxyphenols, pyrazines, and ketones were identified. PMID:24786655

  17. Spectrometric and voltammetric studies of the interaction between quercetin and bovine serum albumin using warfarin as site marker with the aid of chemometrics

    NASA Astrophysics Data System (ADS)

    Ni, Yongnian; Zhang, Xia; Kokot, Serge

    2009-01-01

    The interaction of quercetin, which is a bioflavonoid, with bovine serum albumin (BSA) was investigated under pseudo-physiological conditions by the application of UV-vis spectrometry, spectrofluorimetry and cyclic voltammetry (CV). These studies indicated a cooperative interaction between the quercetin-BSA complex and warfarin, which produced a ternary complex, quercetin-BSA-warfarin. It was found that both quercetin and warfarin were located in site I. However, the spectra of these three components overlapped and the chemometrics method - multivariate curve resolution-alternating least squares (MCR-ALS) was applied to resolve the spectra. The resolved spectra of quercetin-BSA and warfarin agreed well with their measured spectra, and importantly, the spectrum of the quercetin-BSA-warfarin complex was extracted. These results allowed the rationalization of the behaviour of the overlapping spectra. At lower concentrations ([warfarin] < 1 × 10 -5 mol L -1), most of the site marker reacted with the quercetin-BSA, but free warfarin was present at higher concentrations. Interestingly, the ratio between quercetin-BSA and warfarin was found to be 1:2, suggesting a quercetin-BSA-(warfarin) 2 complex, and the estimated equilibrium constant was 1.4 × 10 11 M -2. The results suggest that at low concentrations, warfarin binds at the high-affinity sites (HAS), while low-affinity binding sites (LAS) are occupied at higher concentrations.

  18. Antioxidant Activity/Capacity Measurement. 3. Reactive Oxygen and Nitrogen Species (ROS/RNS) Scavenging Assays, Oxidative Stress Biomarkers, and Chromatographic/Chemometric Assays.

    PubMed

    Apak, Reşat; Özyürek, Mustafa; Güçlü, Kubilay; Çapanoğlu, Esra

    2016-02-10

    There are many studies in which the antioxidant potential of different foods have been analyzed. However, there are still conflicting results and lack of information as a result of unstandardized assay techniques and differences between the principles of the methods applied. The measurement of antioxidant activity, especially in the case of mixtures, multifunctional or complex multiphase systems, cannot be evaluated satisfactorily using a simple antioxidant test due to the many variables influencing the results. In the literature, there are many antioxidant assays that are used to measure the total antioxidant activity/capacity of food materials. In this review, reactive oxygen and nitrogen species (ROS/RNS) scavenging assays are evaluated with respect to their mechanism, advantages, disadvantages, and potential use in food systems. On the other hand, in vivo antioxidant activity (AOA) assays including oxidative stress biomarkers and cellular-based assays are covered within the scope of this review. Finally, chromatographic and chemometric assays are reviewed, focusing on their benefits especially with respect to their time saving, cost-effective, and sensitive nature. PMID:26689748

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

    PubMed

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

    2016-02-01

    A newly synthesized bis thiosemicarbazone ligand, (2Z,2'Z)-2,2'-((4S,5R)-4,5,6-trihydroxyhexane-1,2-diylidene)bis(N-phenylhydrazinecarbothioamide), was used to make a complex with Cu(2+), Ni(2+), Co(2+) and Fe(3+) for their simultaneous spectrophotometric determination using chemometric methods. By Job's method, the ratio of metal to ligand in Ni(2+) was found to be 1:2, whereas it was 1:4 for the others. The effect of pH on the sensitivity and selectivity of the formed complexes was studied according to the net analyte signal (NAS). Under optimum conditions, the calibration graphs were linear in the ranges of 0.10-3.83, 0.20-3.83, 0.23-5.23 and 0.32-8.12 mg L(-1) with the detection limits of 2, 3, 4 and 10 μg L(-1) for Cu(2+), Co(2+), Ni(2+) and Fe(3+) respectively. The OSC-PLS1 for Cu(2+) and Ni(2+), the PLS1 for Co(2+) and the PC-FFANN for Fe(3+) were selected as the best models. The selected models were successfully applied for the simultaneous determination of elements in some foodstuffs and vegetables. PMID:26304369

  20. The use of poly(ethylene oxide) for the efficient stabilization of entrapped alpha-chymotrypsin in silicone elastomers: a chemometric study.

    PubMed

    Ragheb, Amro M; Hileman, Oliver E; Brook, Michael

    2005-12-01

    The enzyme alpha-chymotrypsin, a model for catalytic proteins, was entrapped in different silicone elastomers that were formed via the condensation-cure room temperature vulcanization (CC-RTV) of silanol terminated poly(dimethylsiloxane) with tetraethyl orthosilicate as a crosslinker, in the presence of different poly(ethylene oxide) oligomers that were functionalized with triethoxysilyl groups. The effects of various chemical factors on both the activity and entrapping efficiency of proteins (leaching) were studied using a 2-level fractional factorial design--a chemometrics approach. The factors studied include the concentration and chain length of poly(ethylene oxide), enzyme content, and crosslinker (TEOS) concentration. The study indicated that poly(ethylene oxide) can stabilize the entrapped alpha-chymotrypsin in silicone rubber: the specific activity can be maximized by incorporating a relatively high content of short chain, functional PEO. Increased enzyme concentration was found to adversely affect the specific activity. The effect of TEOS was found to be insignificant when PEO was present in the elastomer, however, it does affect the activity positively in the case of simple elastomers. PMID:15992922

  1. Spectrophotometric Analysis of Caffeine.

    PubMed

    Ahmad Bhawani, Showkat; Fong, Sim Siong; Mohamad Ibrahim, Mohamad Nasir

    2015-01-01

    The nature of caffeine reveals that it is a bitter white crystalline alkaloid. It is a common ingredient in a variety of drinks (soft and energy drinks) and is also used in combination with various medicines. In order to maintain the optimum level of caffeine, various spectrophotometric methods have been developed. The monitoring of caffeine is very important aspect because of its consumption in higher doses that can lead to various physiological disorders. This paper incorporates various spectrophotometric methods used in the analysis of caffeine in various environmental samples such as pharmaceuticals, soft and energy drinks, tea, and coffee. A range of spectrophotometric methodologies including chemometric techniques and derivatization of spectra have been used to analyse the caffeine. PMID:26604926

  2. Spectrophotometric Analysis of Caffeine

    PubMed Central

    Ahmad Bhawani, Showkat; Fong, Sim Siong; Mohamad Ibrahim, Mohamad Nasir

    2015-01-01

    The nature of caffeine reveals that it is a bitter white crystalline alkaloid. It is a common ingredient in a variety of drinks (soft and energy drinks) and is also used in combination with various medicines. In order to maintain the optimum level of caffeine, various spectrophotometric methods have been developed. The monitoring of caffeine is very important aspect because of its consumption in higher doses that can lead to various physiological disorders. This paper incorporates various spectrophotometric methods used in the analysis of caffeine in various environmental samples such as pharmaceuticals, soft and energy drinks, tea, and coffee. A range of spectrophotometric methodologies including chemometric techniques and derivatization of spectra have been used to analyse the caffeine. PMID:26604926

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  4. Combination of chemometrically assisted voltammetry, calorimetry, and circular dichroism as a new method for the study of bioinorganic substances: application to selenocystine metal complexes.

    PubMed

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

    2012-02-01

    Selenium-containing compounds play an important role in antioxidant defense systems, binding to toxic metals, preventing their uptake into cells, and thus protecting cells from metal-induced formation of reactive oxygen species. Here, we present a proposal for a relatively new method as a complement to the more usual methods used in selenium studies. A systematic study of the metal-binding properties of selenocystine (SeCyst) in the presence of divalent metal cations (Cd, Co, Hg, Ni, and Zn) is reported. Isothermal titration calorimetry provides thermodynamic parameters of the systems. Titrations produced curves that could be fit reasonably well to the one set of sites model. The data clearly demonstrate that one M(2+) binds one SeCyst molecule, and the stable M(SeCyst) complex is formed under these conditions. The order of the SeCyst binding constant for the metal ions is Hg(2+) > Cd(2+) ~ Zn(2+) > Ni(2+)> Co(2+). Cadmium ion was selected as a modulator for the behavior of SeCyst in the presence of a nonessential metal, and zinc was selected for the case of an essential element. These interactions of SeCyst with Cd(2+) and Zn(2+), either individually or combined, were studied in aqueous buffered solutions at physiological pH by differential pulse polarography and circular dichroism spectroscopy. Furthermore, recently developed chemometric tools were applied to differential pulse polarography data obtained in mixtures of SeCyst and glutathione in the presence of Cd(2+) at physiological pH. PMID:22015398

  5. Impurity Profiling of a Chemical Weapon Precursor for Possible Forensic Signatures by Comprehensive Two-Dimensional Gas Chromatography/Mass Spectrometry and Chemometrics

    SciTech Connect

    Hoggard, Jamin C.; Wahl, Jon H.; Synovec, Robert E.; Mong, Gary M.; Fraga, Carlos G.

    2010-01-15

    In this work we present the feasibility of using analytical chemical and chemometric methodologies to reveal and exploit the organic impurity profiles from commercial dimethyl methylphosphonate (DMMP) samples to illustrate the type of forensic information that may be obtained from chemical-attack evidence. Using DMMP as a model compound for a toxicant that may be used in a chemical attack, we used comprehensive two-dimensional gas chromatography mass spectrometric detection (GC × GC-TOFMS) to detect and identify trace organic impurities in six samples of commercially acquired DMMP. The GC x GC-TOFMS data were analyzed to produce impurity profiles for all six DMMP samples using 29 analyte impurities. The use of PARAFAC for the mathematical resolution of overlap GC x GC peaks ensured clean spectra for the identification of many of the detected analytes by spectral library matching. The use of statistical pairwise comparison revealed that there were trace impurities that were quantitatively similar and different among five of the six DMMP samples. Two of the DMMP samples were revealed to have identical impurity profiles by this approach. The use of nonnegative matrix factorization proved that there were five distinct DMMP sample types as illustrated by the clustering of the multiple DMMP analyses into 5 distinct clusters in the scores plots. The two indistinguishable DMMP samples were confirmed by their chemical supplier to be from the same bulk source. Sample information from the other chemical suppliers supported that the other five DMMP samples were likely from different bulk sources. These results demonstrate that the matching of synthesized products from the same source is possible using impurity profiling. In addition, the identified impurities common to all six DMMP samples provide strong evidence that basic route information can be obtained from impurity profiles. In addition, impurities that may be unique to the sole bulk manufacturer of DMMP were found in

  6. Chemometrics resolution and quantification power evaluation: Application on pharmaceutical quaternary mixture of Paracetamol, Guaifenesin, Phenylephrine and p-aminophenol.

    PubMed

    Yehia, Ali M; Mohamed, Heba M

    2016-01-01

    Three advanced chemmometric-assisted spectrophotometric methods namely; Concentration Residuals Augmented Classical Least Squares (CRACLS), Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and Principal Component Analysis-Artificial Neural Networks (PCA-ANN) were developed, validated and benchmarked to PLS calibration; to resolve the severely overlapped spectra and simultaneously determine; Paracetamol (PAR), Guaifenesin (GUA) and Phenylephrine (PHE) in their ternary mixture and in presence of p-aminophenol (AP) the main degradation product and synthesis impurity of Paracetamol. The analytical performance of the proposed methods was described by percentage recoveries, root mean square error of calibration and standard error of prediction. The four multivariate calibration methods could be directly used without any preliminary separation step and successfully applied for pharmaceutical formulation analysis, showing no excipients' interference. PMID:26254602

  7. Chemometrics resolution and quantification power evaluation: Application on pharmaceutical quaternary mixture of Paracetamol, Guaifenesin, Phenylephrine and p-aminophenol

    NASA Astrophysics Data System (ADS)

    Yehia, Ali M.; Mohamed, Heba M.

    2016-01-01

    Three advanced chemmometric-assisted spectrophotometric methods namely; Concentration Residuals Augmented Classical Least Squares (CRACLS), Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and Principal Component Analysis-Artificial Neural Networks (PCA-ANN) were developed, validated and benchmarked to PLS calibration; to resolve the severely overlapped spectra and simultaneously determine; Paracetamol (PAR), Guaifenesin (GUA) and Phenylephrine (PHE) in their ternary mixture and in presence of p-aminophenol (AP) the main degradation product and synthesis impurity of Paracetamol. The analytical performance of the proposed methods was described by percentage recoveries, root mean square error of calibration and standard error of prediction. The four multivariate calibration methods could be directly used without any preliminary separation step and successfully applied for pharmaceutical formulation analysis, showing no excipients' interference.

  8. Association of ignitable liquid residues to neat ignitable liquids in the presence of matrix interferences using chemometric procedures.

    PubMed

    Baerncopf, Jamie M; McGuffin, Victoria L; Smith, Ruth W

    2011-01-01

    In fire debris analysis, weathering of ignitable liquids and matrix interferences can make the identification of ignitable liquid residues (ILRs) difficult. An objective method was developed to associate ILRs with the corresponding neat liquid with discrimination from matrix interferences using principal components analysis (PCA) and Pearson product moment correlation (PPMC) coefficients. Six ignitable liquids (gasoline, diesel, ultra pure paraffin lamp oil, adhesive remover, torch fuel, paint thinner) were spiked onto carpet, which was burned, then extracted using passive headspace extraction, and analyzed by gas chromatography-mass spectrometry. Both light and heavy burn conditions were investigated. In the PCA scores plot, ignitable liquids were discriminated based on alkane and aromatic content. All ILRs were successfully associated with the corresponding neat liquid using both PCA and PPMC coefficients, regardless of the extent of burning. The method developed in this research may make the association of ILRs with corresponding neat liquids more objective. PMID:20854360

  9. Botanical and geographical characterization of green coffee (Coffea arabica and Coffea canephora): chemometric evaluation of phenolic and methylxanthine contents.

    PubMed

    Alonso-Salces, Rosa M; Serra, Francesca; Reniero, Fabiano; Héberger, Károly

    2009-05-27

    Green coffee beans of the two main commercial coffee varieties, Coffea arabica (Arabica) and Coffea canephora (Robusta), from the major growing regions of America, Africa, Asia, and Oceania were studied. The contents of chlorogenic acids, cinnamoyl amides, cinnamoyl glycosides, free phenolic acids, and methylxanthines of green coffee beans were analyzed by liquid chromatography coupled with UV spectrophotometry to determine their botanical and geographical origins. The analysis of caffeic acid, 3-feruloylquinic acid, 5-feruloylquinic acid, 4-feruloylquinic acid, 3,4-dicaffeoylquinic acid, 3-caffeoyl-5-feruloylquinic acid, 3-caffeoyl-4-feruloylquinic acid, 3-p-coumaroyl-4-caffeoylquinic acid, 3-caffeoyl-4-dimethoxycinnamoylquinic acid, 3-caffeoyl-5-dimethoxycinnamoylquinic acid, p-coumaroyl-N-tryptophan, feruloyl-N-tryptophan, caffeoyl-N-tryptophan, and caffeine enabled the unequivocal botanical characterization of green coffee beans. Moreover, some free phenolic acids and cinnamate conjugates of green coffee beans showed great potential as means for the geographical characterization of coffee. Thus, p-coumaroyl-N-tyrosine, caffeoyl-N-phenylalanine, caffeoyl-N-tyrosine, 3-dimethoxycinnamoyl-5-feruloylquinic acid, and dimethoxycinnamic acid were found to be characteristic markers for Ugandan Robusta green coffee beans. Multivariate data analysis of the phenolic and methylxanthine profiles provided preliminary results that allowed showing their potential for the determination of the geographical origin of green coffees. Linear discriminant analysis (LDA) and partial least-squares discriminant analysis (PLS-DA) provided classification models that correctly identified all authentic Robusta green coffee beans from Cameroon and Vietnam and 94% of those from Indonesia. Moreover, PLS-DA afforded independent models for Robusta samples from these three countries with sensitivities and specificities of classifications close to 100% and for Arabica samples from America and

  10. Isolation and identification of nontuberculous mycobacteria from hospitalized patients and drinking water samples--examination of their correlation by chemometrics.

    PubMed

    Dovriki, Eleni; Gerogianni, Irini; Petinaki, Efi; Hadjichristodoulou, Christos; Papaioannou, Agelos; Gourgoulianis, Kostas

    2016-04-01

    Nontuberculous mycobacteria (NTM) have been found to be widely dispersed in the environment and are being considered potentially pathogenic for humans and animals, while reports of their human to human transmission are absent. Water and aerosols are potential transmission modes of NTM to humans. Hospitalized patients with NTM infections were studied together with drinking water samples from their respective residence areas during 2003-2013. Cluster analysis and factor analysis were used to analyze the data matrix. A total of 367 hospitalized patients living in 30 localities in the Prefecture of Larissa were tested positive for NTM. The most frequently isolated NTM species of the 383 NTM isolates from the clinical specimens were Mycobacterium fortuitum (n = 118, 30.8 %), M. gordonae (n = 87, 22.7 %), M. peregrinum (n = 46, 12.0 %), M. chelonae (n = 11, 2.9 %), M. avium (n = 8, 2.1 %), and M. intracellulare (n = 7, 1.8 %), while 88 (23.0 %) of these isolates were not identified. It is noted that in 8 patients, M. tuberculosis was isolated simultaneously with one NTM, in 15 patients, together with two types of NTM, while in 1 patient, it was found at the same time as three different NTM. In addition, 3360 drinking water samples were collected from 30 localities and analyzed during 2010 to 2013; they were found 11.2 % NTM positive. Cluster analysis and factor analysis results confirm that NTM strains are correlated to each other in both isolated samples from patients and drinking water, while the strength of their correlation varied from weak to moderate (e.g., factor loadings ranged from 0.69 to 0.74 when all data are considered). These results provide indications that drinking water could be linked with NTM cases in humans. PMID:27021690

  11. Identification of Imitation Cheese and Imitation Ice Cream Based on Vegetable Fat Using NMR Spectroscopy and Chemometrics

    PubMed Central

    Monakhova, Yulia B.; Godelmann, Rolf; Andlauer, Claudia; Kuballa, Thomas; Lachenmeier, Dirk W.

    2013-01-01

    Vegetable oils and fats may be used as cheap substitutes for milk fat to manufacture imitation cheese or imitation ice cream. In this study, 400 MHz nuclear magnetic resonance (NMR) spectroscopy of the fat fraction of the products was used in the context of food surveillance to validate the labeling of milk-based products. For sample preparation, the fat was extracted using an automated Weibull-Stoldt methodology. Using principal component analysis (PCA), imitation products can be easily detected. In both cheese and ice cream, a differentiation according to the type of raw material (milk fat and vegetable fat) was possible. The loadings plot shows that imitation products were distinguishable by differences in their fatty acid ratios. Furthermore, a differentiation of several types of cheese (Edamer, Gouda, Emmentaler, and Feta) was possible. Quantitative data regarding the composition of the investigated products can also be predicted from the same spectra using partial least squares (PLS) regression. The models obtained for 13 compounds in cheese (R2 0.75–0.95) and 17 compounds in ice cream (R2 0.83–0.99) (e.g., fatty acids and esters) were suitable for a screening analysis. NMR spectroscopy was judged as suitable for the routine analysis of dairy products based on milk or on vegetable fat substitutes. PMID:26904597

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

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

  13. Capillary zone electrophoresis for fatty acids with chemometrics for the determination of milk adulteration by whey addition.

    PubMed

    de Oliveira Mendes, Thiago; Porto, Brenda Lee Simas; Bell, Maria José Valenzuela; Perrone, Ítalo Tuler; de Oliveira, Marcone Augusto Leal

    2016-12-15

    Adulteration of milk with whey is difficult to detect because these two have similar physical and chemical characteristics. The traditional methodologies to monitor this fraud are based on the analysis of caseinomacropeptide. The present study proposes a new approach to detect and quantify this fraud using the fatty acid profiles of milk and whey. Fatty acids C14:0, C16:0, C18:0, C18:1, C18:2 and C18:3 were selected by gas chromatography associated with discriminant analysis to differentiate milk and whey, as they are present in quite different amounts. These six fatty acids were quantified withi