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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

    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

  9. 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

  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. 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

  12. 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.

  13. 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

  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. 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

  5. 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

  6. 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

  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. 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.

  1. 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.

  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. 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

  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. 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

  6. 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

  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. 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

  16. 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

  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. 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

  20. 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,...

  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. 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

  7. 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.

  8. 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

  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. 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

  19. 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

  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. 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).

  2. 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

  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. 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

  5. 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

  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. 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.

  16. 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

  17. 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

  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. 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

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

    PubMed

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

    2016-07-01

    Sixty-seven pork bacon samples from Hunan, Sichuan Guangdong, Jiangxi, and Yunnan Provinces in China were analyzed to understand their geographical properties. Classification was performed by determining their physicochemical properties through chemometric techniques, including variance analysis, principal component analysis (PCA), and discriminant analysis (DA). Results showed that certain differences existed in terms of nine physicochemical determinations in traditional Chinese pork bacon. PCA revealed the distinction among Hunan, Sichuan, and Guangdong style bacon. Meanwhile, seven key physicochemical determination criteria were identified in line with DA and could be reasonably applied to the classification of traditional Chinese pork bacon. Furthermore, the ratio of overall correct classification was 97.76% and that of cross-validation was 91.76%. These findings indicated that chemometric techniques, together with several physicochemical determination, were effective for the classification of traditional Chinese pork bacon with geographical features. Our study provided a theoretical reference for the classification of traditional Chinese pork bacon. PMID:26994313

  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. 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....

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

    ERIC Educational Resources Information Center

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

    2011-01-01

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

  13. 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. 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

  19. 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.

  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. 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

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. 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

  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. 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

  15. 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.

  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. 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

  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. 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

  3. 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

  4. 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%).

  5. 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

  6. 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.

  7. 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

  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. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. 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

  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. 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

  3. 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

  4. 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

  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. 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

  11. 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

  12. 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.

  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. 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

  17. 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.

  18. 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

  19. 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

  20. 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

  1. 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.

  2. 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

  3. 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

  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. 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

  6. 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

  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. 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

  10. High-Throughput Metabolic Fingerprinting of Legume Silage Fermentations via Fourier Transform Infrared Spectroscopy and Chemometrics

    PubMed Central

    Johnson, Helen E.; Broadhurst, David; Kell, Douglas B.; Theodorou, Michael K.; Merry, Roger J.; Griffith, Gareth W.

    2004-01-01

    Silage quality is typically assessed by the measurement of several individual parameters, including pH, lactic acid, acetic acid, bacterial numbers, and protein content. The objective of this study was to use a holistic metabolic fingerprinting approach, combining a high-throughput microtiter plate-based fermentation system with Fourier transform infrared (FT-IR) spectroscopy, to obtain a snapshot of the sample metabolome (typically low-molecular-weight compounds) at a given time. The aim was to study the dynamics of red clover or grass silage fermentations in response to various inoculants incorporating lactic acid bacteria (LAB). The hyperspectral multivariate datasets generated by FT-IR spectroscopy are difficult to interpret visually, so chemometrics methods were used to deconvolute the data. Two-phase principal component-discriminant function analysis allowed discrimination between herbage types and different LAB inoculants and modeling of fermentation dynamics over time. Further analysis of FT-IR spectra by the use of genetic algorithms to identify the underlying biochemical differences between treatments revealed that the amide I and amide II regions (wavenumbers of 1,550 to 1,750 cm−1) of the spectra were most frequently selected (reflecting changes in proteins and free amino acids) in comparisons between control and inoculant-treated fermentations. This corresponds to the known importance of rapid fermentation for the efficient conservation of forage proteins. PMID:15006782