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

    PubMed

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

    2014-10-01

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

  4. Chemometric analysis of Ragusano cheese flavor.

    PubMed

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

    2002-02-27

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

  5. 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

  6. Chemometric analysis of the water purification process data.

    PubMed

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

    2007-11-15

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

  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.

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

    PubMed

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

    2015-09-15

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

  9. Multivariate analysis and chemometric characterisation of textile wastewater streams.

    PubMed

    Kavsek, Darja; Jeric, Tina; Le Marechal, Alenka Majcen; Vajnhandl, Simona; Bednárová, Adriána; Voncina, Darinka Brodnjak

    2013-01-01

    The aim of this work was to design a quick and reliable method for the evaluation and classification of wastewater streams into treatable and non-treatable effluents for reuse/recycling. Different chemometric methods were used for this purpose handling the enormous amount of data, and additionally to find any hidden information, which would increase our knowledge and improve the classification. The data obtained from the processes description, together with the analytical results of measured parameters' characterising the wastewater of a particular process, enabled us to build a fast-decision model for separating different textile wastewater outlets. Altogether 49 wastewater samples from the textile finishing company were analysed, and 19 different physical chemical measurements were performed for each of them. The resulting classification model was aimed at an automated decision about the choice of treatment technologies or a prediction about the reusability of wastewaters within any textile finishing or other company having similar characteristics of wastewater streams.

  10. Multivariate analysis and chemometric characterisation of textile wastewater streams.

    PubMed

    Kavsek, Darja; Jeric, Tina; Le Marechal, Alenka Majcen; Vajnhandl, Simona; Bednárová, Adriána; Voncina, Darinka Brodnjak

    2013-01-01

    The aim of this work was to design a quick and reliable method for the evaluation and classification of wastewater streams into treatable and non-treatable effluents for reuse/recycling. Different chemometric methods were used for this purpose handling the enormous amount of data, and additionally to find any hidden information, which would increase our knowledge and improve the classification. The data obtained from the processes description, together with the analytical results of measured parameters' characterising the wastewater of a particular process, enabled us to build a fast-decision model for separating different textile wastewater outlets. Altogether 49 wastewater samples from the textile finishing company were analysed, and 19 different physical chemical measurements were performed for each of them. The resulting classification model was aimed at an automated decision about the choice of treatment technologies or a prediction about the reusability of wastewaters within any textile finishing or other company having similar characteristics of wastewater streams. PMID:23878942

  11. 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

  12. 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

  13. 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.

  14. Analysis of volatiles in Pinotage wines by stir bar sorptive extraction and chemometric profiling.

    PubMed

    Weldegergis, Berhane T; Crouch, Andrew M

    2008-11-12

    A fast, simple, cost-effective, and reliable method based on stir bar sorptive extraction (SBSE) in the headspace mode was used for the analysis of 39 volatile components in Pinotage wines. The method was sensitive, with LODs ranging from 50.0 pg/L to 281 ng/L and LOQs between 180 pg/L and 938 ng/L. Precision was between 6 and 20%. The intermediate precision was within the acceptable range. Moreover, good calibration curves with R(2) > 0.99 for all compounds were achieved. The method was successfully applied for the analysis of 87 young Pinotage wines of vintages 2005 and 2006 collected from various South African regions. To characterize the results based on vintage and origin, the obtained concentrations of the compounds were subjected to chemometric analysis. Exploratory factor analysis (FA), principal component analysis (PCA), and analysis of variance (one-way ANOVA) were consecutively done. The chemometrics approach revealed a reasonable correlation among the volatile components of these wines, as well as with respect to their year of production.

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

    PubMed

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

    2014-07-01

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

  16. Chemometric analysis of spectroscopic data on shape evolution of silver nanoparticles induced by hydrogen peroxide.

    PubMed

    Wongravee, Kanet; Parnklang, Tewarak; Pienpinijtham, Prompong; Lertvachirapaiboon, Chutiparn; Ozaki, Yukihiro; Thammacharoen, Chuchaat; Ekgasit, Sanong

    2013-03-28

    The study on the shape evolution of metal nanoparticles (MNPs) is crucial to gain an understanding on controlling the shape and size of metal nanostructures. In this work, a detailed study on shape evolution of silver (Ag) nanospheres to nanoplates induced by hydrogen peroxide (H2O2) was performed. According to the growth mechanism of Ag nanoplates, the spectrophotometric method combined with chemometric analysis has potential to reveal the structural evolution process as observed by surface plasmon resonance phenomena. The extinction spectra of the evolving nanostructures were analyzed by factor analysis and error indicator functions. Five major components attributed to the different particle shapes and sizes were theoretically predicted. Furthermore, the concentration profiles and pure spectra of these components were resolved using multivariate curve resolution-alternative least squares (MCR-ALS) analysis. The evolution profiles show that the spherical Ag particles systematically evolved into plate structures of different sizes. Larger nanoplates were obtained when higher concentrations of H2O2 were employed. An evidence of nanoplate disintegration was observed when a large amount of H2O2 was employed. The predicted structural morphologies of each component given by chemometric calculation were in excellent agreement with those observed by transmission electron microscope (TEM) images.

  17. 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.

  18. 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 ...

  19. 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.

  20. 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.

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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

  6. 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

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

    PubMed

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

    2011-06-01

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

  8. 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

  9. Chemometric analysis of MALDI mass spectrometric images of three-dimensional cell culture systems

    PubMed Central

    Weaver, Eric M.; Hummon, Amanda B.; Keithley, Richard B.

    2015-01-01

    As imaging mass spectrometry (IMS) has grown in popularity in recent years, the applications of this technique have become increasingly diverse. Currently there is a need for sophisticated data processing strategies that maximize the information gained from large IMS data sets. Traditional two-dimensional heat maps of single ions generated in IMS experiments lack analytical detail, yet manual analysis of multiple peaks across hundreds of pixels within an entire image is time-consuming, tedious and subjective. Here, various chemometric methods were used to analyze data sets obtained by matrix-assisted laser desorption/ionization (MALDI) IMS of multicellular spheroids. HT-29 colon carcinoma multicellular spheroids are an excellent in vitro model system that mimic the three dimensional morphology of tumors in vivo. These data are especially challenging to process because, while different microenvironments exist, the cells are clonal which can result in strong similarities in the mass spectral profiles within the image. In this proof-of-concept study, a combination of principal component analysis (PCA), clustering methods, and linear discriminant analysis was used to identify unique spectral features present in spatially heterogeneous locations within the image. Overall, the application of these exploratory data analysis tools allowed for the isolation and detection of proteomic changes within IMS data sets in an easy, rapid, and unsupervised manner. Furthermore, a simplified, non-mathematical theoretical introduction to the techniques is provided in addition to full command routines within the MATLAB programming environment, allowing others to easily utilize and adapt this approach. PMID:26604989

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

    PubMed Central

    2014-01-01

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

  11. 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

  12. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

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

    PubMed

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

    2015-09-01

    In the present work, relationships between the textural characteristics of fermented milk products obtained by kombucha inoculums with various teas were investigated by using chemometric analysis. The presented data which describe numerically the textural characteristics (firmness, consistency, cohesiveness and index of viscosity) were analysed. The quadratic correlation was determined between the textural characteristics of fermented milk products obtained at fermentation temperatures of 40 and 43 °C, using milk with 0.8, 1.6 and 2.8% milk fat and kombucha inoculums cultivated on the extracts of peppermint, stinging nettle, wild thyme and winter savory. Hierarchical cluster analysis (HCA) was performed to identify the similarities among the fermented products. The best mathematical models predicting the textural characteristics of investigated samples were developed. The results of this study indicate that textural characteristics of sample based on winter savory have a significant effect on textural characteristics of samples based on peppermint, stinging nettle and wild thyme, which can be very useful in the determination of products texture profile. PMID:26345015

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  16. Chemometric analysis for extraction of individual fluorescence spectrum and lifetimes from a target mixture

    NASA Technical Reports Server (NTRS)

    Hallidy, William H. (Inventor); Chin, Robert C. (Inventor)

    1999-01-01

    The present invention is a system for chemometric analysis for the extraction of the individual component fluorescence spectra and fluorescence lifetimes from a target mixture. The present invention combines a processor with an apparatus for generating an excitation signal to transmit at a target mixture and an apparatus for detecting the emitted signal from the target mixture. The present invention extracts the individual fluorescence spectrum and fluorescence lifetime measurements from the frequency and wavelength data acquired from the emitted signal. The present invention uses an iterative solution that first requires the initialization of several decision variables and the initial approximation determinations of intermediate matrices. The iterative solution compares the decision variables for convergence to see if further approximation determinations are necessary. If the solution converges, the present invention then determines the reduced best fit error for the analysis of the individual fluorescence lifetime and the fluorescence spectrum before extracting the individual fluorescence lifetime and fluorescence spectrum from the emitted signal of the target mixture.

  17. 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

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

    PubMed

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

    2015-10-21

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

  19. Chemometric analysis of soil pollution data using the Tucker N-way method.

    PubMed

    Stanimirova, I; Zehl, K; Massart, D L; Vander Heyden, Y; Einax, J W

    2006-06-01

    N-way methods, particularly the Tucker method, are often the methods of choice when analyzing data sets arranged in three- (or higher) way arrays, which is the case for most environmental data sets. In the future, applying N-way methods will become an increasingly popular way to uncover hidden information in complex data sets. The reason for this is that classical two-way approaches such as principal component analysis are not as good at revealing the complex relationships present in data sets. This study describes in detail the application of a chemometric N-way approach, namely the Tucker method, in order to evaluate the level of pollution in soil from a contaminated site. The analyzed soil data set was five-way in nature. The samples were collected at different depths (way 1) from two locations (way 2) and the levels of thirteen metals (way 3) were analyzed using a four-step-sequential extraction procedure (way 4), allowing detailed information to be obtained about the bioavailability and activity of the different binding forms of the metals. Furthermore, the measurements were performed under two conditions (way 5), inert and non-inert. The preferred Tucker model of definite complexity showed that there was no significant difference in measurements analyzed under inert or non-inert conditions. It also allowed two depth horizons, characterized by different accumulation pathways, to be distinguished, and it allowed the relationships between chemical elements and their biological activities and mobilities in the soil to be described in detail.

  20. Estimating cocoa bean parameters by FT-NIRS and chemometrics analysis.

    PubMed

    Teye, Ernest; Huang, Xingyi; Sam-Amoah, Livingstone K; Takrama, Jemmy; Boison, Daniel; Botchway, Francis; Kumi, Francis

    2015-06-01

    Rapid analysis of cocoa beans is an important activity for quality assurance and control investigations. In this study, Fourier transform near infrared spectroscopy (FT-NIRS) and chemometric techniques were attempted to estimate cocoa bean quality categories, pH and fermentation index (FI). The performances of the models were optimised by cross-validation and examined by identification rate (%), correlation coefficient (Rpre) and root mean square error of prediction (RMSEP) in the prediction set. The optimal identification model by back propagation artificial neural network (BPANN) was 99.73% at 5 principal components. The efficient variable selection model derived by synergy interval back propagation artificial neural network regression (Si-BPANNR) was superior for pH and FI estimation. Si-BPANNR model for pH was Rpre=0.98 and RMSEP=0.06, while for FI was Rpre=0.98 and RMSEP=0.05. The results demonstrated that FT-NIRS together with BPANN and Si-BPANNR model could successfully be used for cocoa beans examination.

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

    PubMed

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

    2016-09-01

    A novel approach for the rapid discrimination of bergamot essential oil from other citrus fruits oils is presented. The method was developed using paper spray mass spectrometry (PS-MS) allowing for a rapid molecular profiling coupled with a statistic tool for a precise and reliable discrimination between the bergamot complex matrix and other similar matrices, commonly used for its reconstitution. Ambient mass spectrometry possesses the ability to record mass spectra of ordinary samples, in their native environment, without sample preparation or pre-separation by creating ions outside the instrument. The present study reports a PS-MS method for the determination of oxygen heterocyclic compounds such as furocoumarins, psoralens and flavonoids present in the non-volatile fraction of citrus fruits essential oils followed by chemometric analysis. The volatile fraction of Bergamot is one of the most known and fashionable natural products, which found applications in flavoring industry as ingredient in beverages and flavored foodstuff. The development of the presented method employed bergamot, sweet orange, orange, cedar, grapefruit and mandarin essential oils. PS-MS measurements were carried out in full scan mode for a total run time of 2 min. The capability of PS-MS profiling to act as marker for the classification of bergamot essential oils was evaluated by using multivariate statistical analysis. Two pattern recognition techniques, linear discriminant analysis and soft independent modeling of class analogy, were applied to MS data. The cross-validation procedure has shown excellent results in terms of the prediction ability because both models have correctly classified all samples for each category. Copyright © 2016 John Wiley & Sons, Ltd. PMID:27460885

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

    PubMed

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

    2015-01-01

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

  3. 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.

  4. 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.

  5. 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

  6. 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...

  7. Chemometric analysis of frequency-domain photon migration data: quantitative measurements of optical properties and chromophore concentrations in multicomponent turbid media

    SciTech Connect

    Berger, Andrew J.; Venugopalan, Vasan; Durkin, Anthony J.; Pham, Tuan; Tromberg, Bruce J.

    2000-04-01

    Frequency-domain photon migration (FDPM) is a widely used technique for measuring the optical properties (i.e., absorption, {mu}{sub a}, and reduced scattering, {mu}{sub s}{sup '}, coefficients) of turbid samples. Typically, FDPM data analysis is performed with models based on a photon diffusion equation; however, analytical solutions are difficult to obtain for many realistic geometries. Here, we describe the use of models based instead on representative samples and multivariate calibration (chemometrics). FDPM data at seven wavelengths (ranging from 674 to 956 nm) and multiple modulation frequencies (ranging from 50 to 600 MHz) were gathered from turbid samples containing mixtures of three absorbing dyes. Values for {mu}{sub a} and {mu}{sub s}{sup '} were extracted from the FDPM data in different ways, first with the diffusion theory and then with the chemometric technique of partial least squares. Dye concentrations were determined from the FDPM data by three methods, first by least-squares fits to the diffusion results and then by two chemometric approaches. The accuracy of the chemometric predictions was comparable or superior for all three dyes. Our results indicate that chemometrics can recover optical properties and dye concentrations from the frequency-dependent behavior of photon density waves, without the need for diffusion-based models. Future applications to more complicated geometries, lower-scattering samples, and simpler FDPM instrumentation are discussed. (c) 2000 Optical Society of America.

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

    PubMed

    Ni, Yongnian; Wang, Yong; Kokot, Serge

    2009-04-30

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

  9. Identification of heparin samples that contain impurities or contaminants by chemometric pattern recognition analysis of proton NMR spectral data.

    PubMed

    Zang, Qingda; Keire, David A; Buhse, Lucinda F; Wood, Richard D; Mital, Dinesh P; Haque, Syed; Srinivasan, Shankar; Moore, Christine M V; Nasr, Moheb; Al-Hakim, Ali; Trehy, Michael L; Welsh, William J

    2011-08-01

    Chemometric analysis of a set of one-dimensional (1D) (1)H nuclear magnetic resonance (NMR) spectral data for heparin sodium active pharmaceutical ingredient (API) samples was employed to distinguish USP-grade heparin samples from those containing oversulfated chondroitin sulfate (OSCS) contaminant and/or unacceptable levels of dermatan sulfate (DS) impurity. Three chemometric pattern recognition approaches were implemented: classification and regression tree (CART), artificial neural network (ANN), and support vector machine (SVM). Heparin sodium samples from various manufacturers were analyzed in 2008 and 2009 by 1D (1)H NMR, strong anion-exchange high-performance liquid chromatography, and percent galactosamine in total hexosamine tests. Based on these data, the samples were divided into three groups: Heparin, DS ≤ 1.0% and OSCS = 0%; DS, DS > 1.0% and OSCS = 0%; and OSCS, OSCS > 0% with any content of DS. Three data sets corresponding to different chemical shift regions (1.95-2.20, 3.10-5.70, and 1.95-5.70 ppm) were evaluated. While all three chemometric approaches were able to effectively model the data in the 1.95-2.20 ppm region, SVM was found to substantially outperform CART and ANN for data in the 3.10-5.70 ppm region in terms of classification success rate. A 100% prediction rate was frequently achieved for discrimination between heparin and OSCS samples. The majority of classification errors between heparin and DS involved cases where the DS content was close to the 1.0% DS borderline between the two classes. When these borderline samples were removed, nearly perfect classification results were attained. Satisfactory results were achieved when the resulting models were challenged by test samples containing blends of heparin APIs spiked with non-, partially, or fully oversulfated chondroitin sulfate A, heparan sulfate, or DS at the 1.0%, 5.0%, and 10.0% (w/w) levels. This study demonstrated that the combination of 1D (1)H NMR spectroscopy with

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

    PubMed

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

    2015-10-01

    Frankincense has gained increasing attention in the pharmaceutical industry because of its pharmacologically active components such as boswellic acids. However, the identity and overall quality evaluation of three different frankincense species in different Pharmacopeias and the literature have less been reported. In this paper, quantitative analysis and chemometric evaluation were established and applied for the quality control of frankincense. Meanwhile, quantitative and chemometric analysis could be conducted under the same analytical conditions. In total 55 samples from four habitats (three species) of frankincense were collected and six boswellic acids were chosen for quantitative analysis. Chemometric analyses such as similarity analysis, hierarchical cluster analysis, and principal component analysis were used to identify frankincense of three species to reveal the correlation between its components and species. In addition, 12 chromatographic peaks have been tentatively identified explored by reference substances and quadrupole time-of-flight mass spectrometry. The results indicated that the total boswellic acid profiles of three species of frankincense are similar and their fingerprints can be used to differentiate between them. PMID:26228790

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

    PubMed

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

    2014-11-28

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

  12. 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.

  13. 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.

  14. 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

  15. Rapid analysis of Origanum majorana L. fragrance using a nanofiber sheet, gas chromatography with mass spectrometry, and chemometrics.

    PubMed

    Asadollahi-Baboli, Mohammad; Aghakhani, Ali

    2014-04-01

    Headspace nanofiber sheet microextraction together with GC-MS and chemometrics resolution techniques were implemented to separate and identify the volatiles emitted by intact marjoram (Origanum majorana L.) and their relative concentrations. A novel polyaniline-nylon-6 nanofiber composite was applied for headspace microextraction. Characteristics such as high surface-to-volume ratio and π-π functional groups in polyaniline together with the NH and C=O functional groups in nylon-6 make the polyaniline-nylon-6 nanofiber composite a suitable candidate for the extraction of volatiles and semivolatiles. The extracted constituents were desorbed and injected into the GC-MS system under the optimum conditions. Chemometric resolution techniques were utilized to solve the baseline offset, asymmetric peaks, and overlapped peaks problems that arise from GC-MS analysis. By means of these techniques and resolving the overlapped peak clusters, the number of identified constituents was increased to 67 compounds. The major released constituents from the intact marjoram leaves are 4-terpineol, β-linalool, cis-sabinol, and trans-geraniol.

  16. 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.

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

    PubMed

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

    2014-01-01

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

  18. Simultaneous determination of sugars and organic acids in aged vinegars and chemometric data analysis.

    PubMed

    Cocchi, M; Durante, C; Grandi, M; Lambertini, P; Manzini, D; Marchetti, A

    2006-07-15

    Aceto Balsamico Tradizionale of Modena (ABTM) is a typical product (PDO denomination) of the province of Modena produced by cooked grape must which undergoes a long ageing period (at least 12 years) in series of wooden casks (batterie). The study of the transformations of this product during ageing is extremely relevant in order to control the authenticity of ABTM towards succedaneous products and mislabelling of age. This paper presents the results of the investigation of sugars and fixed organic acids in ABTM samples of different ages, coming from different batterie. The analytes were simultaneously determined by a gas chromatographic method optimised for this peculiar matrix. The method shows good separation and resolution of the investigated chemical species and allows their determination in the concentration ranges reported in brackets: malic (7.6-15.5 g kg(-1)), tartaric (4.0-9.7 g kg(-1)), citric (0.6-1.5 g kg(-1)) and succinic (0.36-0.62 g kg(-1)) acid and glucose (153-294 g kg(-1)), fructose (131-279 g kg(-1)), xylose (011-0.39 g kg(-1)), ribose (0.078-0.429 g kg(-1)), rhamnose (0.061-0.195 g kg(-1)), galactose (0.136-0.388 g kg(-1)), mannose (0.41-1.46 g kg(-1)), arabinose (0.33-1.00 g kg(-1)) and sucrose (0.46-6.84 g kg(-1)), with mean associated errors ranging from 5 to 19% depending on the analytes. Moreover, the recovery values are always satisfactory, being close to one for most of the analytes. Furthermore, in order to assess the degree of variability of the different analytes content with vinegar ageing and the similarity/dissimilarity among series of casks a three-way data analysis method (Tucker3) is proposed. The chemometric technique applied on the data set shows differences between the samples on the bases of their different ageing period, and between the batterie, which traditionally have an own peculiar production procedure.

  19. Analysis and assessment of four commercial products of Asian ginseng by ultra-performance liquid chromatography and chemometric analysis.

    PubMed

    Zhang, Cuiying; Chen, Shilin; Dong, Liang

    2015-05-01

    Ginseng Radix et Rhizoma (GRR, also named as white ginseng), Ginseng Radix et Rhizoma Rubra (GRR Rubra. also named as red ginseng), Ginseng Folium (GF) and Ginseng Rootlet (GR) products from Asian ginseng, one of the well-known Chinese traditional medicine for thousands of years, are now widely used around the world. Thus the comprehensive quality control is of paramount concern basing on the contents of the bioactive ginsenosides. A rapid, sensitive and reliable method of ultra-performance liquid chromatography coupled with a photodiode array detection (UPLC-PAD) was developed for the quantitative analysis of the 12 ginsenosides in the four commercial ginseng products of Asian ginseng. The chromatography was performed on an ACQUITY UPLC™ BEH C18 column using a gradient elution with acetonitrile/water as the mobile phases. Method validation including calibration curves, accuracies, precisions, repeatabilities and recoveries was investigated. The contents of the 12 ginsenosides were determined in 20 GRR, 4 GF, 4 GR and 11 GRR Rubra samples. To evaluate the sample quality. chenometric methods including hierarchical cluster analysis (HCA) and principal components analysis (PCA) were engaged in evaluating the GRR, GRR Rubra, GF and GR products from Asian ginseng. The results showed that HCA and PCA can be considered as the attractive chemometric techniques in situations where high sample throughput and multiple analytes are required.

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

    PubMed

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

    2011-03-01

    Single and sequential extraction procedures are used for studying element mobility and availability in solid matrices, like soils, sediments, sludge, and airborne particulate matter. In the first part of this review we reported an overview on these procedures and described the applications of chemometric uni- and bivariate techniques and of multivariate pattern recognition techniques based on variable reduction to the experimental results obtained. The second part of the review deals with the use of chemometrics not only for the visualization and interpretation of data, but also for the investigation of the effects of experimental conditions on the response, the optimization of their values and the calculation of element fractionation. We will describe the principles of the multivariate chemometric techniques considered, the aims for which they were applied and the key findings obtained. The following topics will be critically addressed: pattern recognition by cluster analysis (CA), linear discriminant analysis (LDA) and other less common techniques; modelling by multiple linear regression (MLR); investigation of spatial distribution of variables by geostatistics; calculation of fractionation patterns by a mixture resolution method (Chemometric Identification of Substrates and Element Distributions, CISED); optimization and characterization of extraction procedures by experimental design; other multivariate techniques less commonly applied. PMID:21334477

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

    PubMed

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

    2012-01-01

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

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

    PubMed

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

    2015-01-01

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

  3. 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.

  4. 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.

  5. 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

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

    NASA Astrophysics Data System (ADS)

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

    2009-09-01

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

  7. 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).

  8. [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

  9. Micro-Raman spectroscopy and chemometrical analysis for the distinction of copper phthalocyanine polymorphs in paint layers.

    PubMed

    Defeyt, C; Van Pevenage, J; Moens, L; Strivay, D; Vandenabeele, P

    2013-11-01

    In art analysis, copper phthalocyanine (CuPc) is often identified as an important pigment (PB15) in 20th century artworks. Raman spectroscopy is a very valuable technique for the detection of this pigment in paint systems. However, PB15 is used in different polymorphic forms and identification of the polymorph could retrieve information on the production process of the pigment at the moment. Raman spectroscopy, being a molecular spectroscopic method of analysis, is able to discriminate between polymorphs of crystals. However, in the case of PB15, spectral interpretation is not straightforward, and Raman data treatment requires some improvements concerning the PB15 polymorphic discrimination in paints. Here, Raman spectroscopy is combined with chemometrical analysis in order to develop a procedure allowing us to identify the PB15 crystalline structure in painted layers and in artworks. The results obtained by Linear Discriminant Analysis (LDA), using intensity ratios as variables, demonstrate the ability of this procedure to predict the crystalline structure of a PB15 pigment in unknown paint samples.

  10. 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

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

    PubMed

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

    2012-01-11

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

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

    PubMed

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

    2011-10-01

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

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

    PubMed

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

    2014-05-15

    The burden of nosocomial or health care-associated infection (HCAI) is increasing worldwide. According to the World Health Organization (WHO), it is several fold higher in low- and middle-income countries. Considering the multidrug-resistant infections, the development of new and more effective drugs is crucial. Herein, two series (I and II) of 5-nitrofuran derivatives were designed, synthesized and assayed against microorganisms, including Gram-positive and -negative bacteria, and fungi. The pathogens screened was directly related to either the most currently relevant HCAI, or to multidrug-resistant infection caused by MRSA/VRSA strains, for instance. The sets I and II were composed by substituted-[N'-(5-nitrofuran-2-yl)methylene]benzhydrazide and 3-acetyl-5-(substituted-phenyl)-2-(5-nitro-furan-2-yl)-2,3-dihydro-1,3,4-oxadiazole compounds, respectively. The selection of the substituent groups was based upon physicochemical properties, such as hydrophobicity and electronic effect. The compounds have showed better activity against Staphylococcus aureus, Escherichia coli, and Enterococcus faecalis. The findings from S. aureus strain, which was more susceptible, were used to investigate the intersamples and intervariables relationships by applying chemometric methods. It is noteworthy that the compound 4-butyl-[N'-(5-nitrofuran-2-yl)methylene]benzhydrazide has showed similar MIC value to vancomycin, which is the reference drug for multidrug-resistant S. aureus infections. Taken the findings together, the 5-nitrofuran derivatives might be indeed considered as promising hits to develop novel antimicrobial drugs to fight against nosocomial infection. PMID:24751553

  14. 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

    2016-01-19

    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.

  15. 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.

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

    PubMed

    Zeng, Yihang; Cai, Wensheng; Shao, Xueguang

    2015-06-01

    A method was developed for quantifying 17 amino acids in tobacco leaves by using an A300 amino acid analyzer and chemometric resolution. In the method, amino acids were eluted by the buffer solution on an ion-exchange column. After reacting with ninhydrin, the derivatives of amino acids were detected by ultraviolet detection. Most amino acids are separated by the elution program. However, five peaks of the derivatives are still overlapping. A non-negative immune algorithm was employed to extract the profiles of the derivatives from the overlapping signals, and then peak areas were adopted for quantitative analysis of the amino acids. The method was validated by the determination of amino acids in tobacco leaves. The relative standard deviations (n = 5) are all less than 2.54% and the recoveries of the spiked samples are in a range of 94.62-108.21%. The feasibility of the method was proved by analyzing the 17 amino acids in 30 tobacco leaf samples. PMID:25866370

  17. 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

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

    PubMed

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

    2014-09-15

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

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

    PubMed

    Zeng, Yihang; Cai, Wensheng; Shao, Xueguang

    2015-06-01

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

  20. 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

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

    PubMed

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

    2015-01-01

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

  2. 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.

  3. 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.

  4. 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.

  5. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-09-01

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

  7. 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.

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

    PubMed

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

    2015-06-01

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

  9. A novel method for simultaneous analysis of three β2-agonists in foods with the use of a gold-nanoparticle modified glassy carbon electrode and chemometrics.

    PubMed

    Lin, Xiaoyun; Ni, Yongnian; Li, Shuzhen; Kokot, Serge

    2012-05-01

    An electrochemical method involving a gold nanoparticle modified glassy carbon electrode (AuNPs/GCE) was researched and developed for the simultaneous analysis of three β(2)-agonists, ractopamine (RAC), salbutamol (SAL) and clenbuterol (CLB). The three analytes were electrocatalytically oxidized at the AuNP/GCE, which enhanced the oxidation peak current and influenced the shift of the oxidation potentials to lower values in comparison with the analysis involving only the GCE. The differential pulse stripping voltammetry (DPSV) voltammograms from the drug mixture produced complex, overlapping profiles, and chemometrics methods were applied for calibration modeling. The peak currents associated with RAC, SAL and CLB measurements were linear as a function of their concentrations (ranges within 0.005-0.150 μg mL(-1)); the detection limits for RAC, SAL and CLB were 2.4, 5.8 and 2.6 ng mL(-1), respectively. It was shown that satisfactory quantitative results were obtained with the use of the MVC1 package of chemometrics methods e.g. the PLS1 calibration model produced a relative prediction error (RPE(T)) of 7.0% and an average recovery of 97.6%. The above AuNP/GCE was successfully employed for the simultaneous analysis of RAC, SAL and CLB in pork meat, liver and pig feed samples.

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

    PubMed

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

    2015-10-01

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

  11. 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

  12. 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

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

    PubMed

    Arvanitoyannis, Ioannis S; Vaitsi, Olga B

    2007-01-01

    Authenticity and traceability have been two of the most important issues in the food chain. Authenticity in particular, is closely related with both food quality and safety issues. Vegetables stand for a category of foods heavily affected by adulteration either in terms of geographic origin (national or international level) or production methods (organic or conventional production, fertilizers, pesticides, genetically modified vegetables). This review aims at addressing most of the currently applied methods for ensuring quality control of vegetables; a) instrumental: ion chromatography, high pressure liquid chromatography, atomic absorption spectrophotometry, electronic nose and mass spectroscopy and b) sensory analysis. The results of all the above mentioned methods were analyzed by means of multivariate analysis (principal component analysis, discriminant analysis, cluster analysis, canonical analysis, and factor analysis). All ensuing results and conclusions are summarized in eight comprehensive tables. PMID:17943497

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

    PubMed

    Arvanitoyannis, Ioannis S; Vaitsi, Olga B

    2007-01-01

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

  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.

  16. 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.

  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. 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

  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.

  20. 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.

  1. Spatial aspects of surface water quality in the Jakara Basin, Nigeria using chemometric analysis.

    PubMed

    Mustapha, Adamu; Aris, Ahmad Zaharin

    2012-01-01

    Multivariate statistical techniques such as hierarchical Agglomerated cluster analysis (HACA), discriminant analysis (DA), principal component analysis (PCA), and factor analysis (FA) were applied to identify the spatial variation and pollution sources of Jakara River, Kano, Nigeria. Thirty surface water samples were collected: 23 along Getsi River and 7 along the main channel of River Jakara. Twenty-three water quality parameters, namely pH, temperature, turbidity, electrical conductivity (EC), dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD(5)), Faecal coliform, total solids (TS), nitrates (NO(3)(-)), phosphates (PO(4)(3-)), cobalt (Co), iron (Fe), nickel (Ni), manganese (Mn), copper (Cu), sodium (Na), potassium (K), mercury (Hg), chromium (Cr), cadmium (Cd), lead (Pb), magnesium (Mg), and calcium(Ca) were analysed. HACA grouped the sampling points into three clusters based on the similarities of river water quality characteristics: industrial, domestic, and agricultural water pollution sources. Forward and backward DA effectively discriminated 5 and 15 water quality variables, respectively, each assigned with 100% correctness from the original 23 variables. PCA and FA were used to investigate the origin of each water quality parameter due to various land use activities, 7 principal components were obtained with 77.5% total variance, and in addition PCA identified 3 latent pollution sources to support HACA. From this study, one can conclude that the application of multivariate techniques derives meaningful information from water quality data. PMID:22571534

  2. Spatial aspects of surface water quality in the Jakara Basin, Nigeria using chemometric analysis.

    PubMed

    Mustapha, Adamu; Aris, Ahmad Zaharin

    2012-01-01

    Multivariate statistical techniques such as hierarchical Agglomerated cluster analysis (HACA), discriminant analysis (DA), principal component analysis (PCA), and factor analysis (FA) were applied to identify the spatial variation and pollution sources of Jakara River, Kano, Nigeria. Thirty surface water samples were collected: 23 along Getsi River and 7 along the main channel of River Jakara. Twenty-three water quality parameters, namely pH, temperature, turbidity, electrical conductivity (EC), dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD(5)), Faecal coliform, total solids (TS), nitrates (NO(3)(-)), phosphates (PO(4)(3-)), cobalt (Co), iron (Fe), nickel (Ni), manganese (Mn), copper (Cu), sodium (Na), potassium (K), mercury (Hg), chromium (Cr), cadmium (Cd), lead (Pb), magnesium (Mg), and calcium(Ca) were analysed. HACA grouped the sampling points into three clusters based on the similarities of river water quality characteristics: industrial, domestic, and agricultural water pollution sources. Forward and backward DA effectively discriminated 5 and 15 water quality variables, respectively, each assigned with 100% correctness from the original 23 variables. PCA and FA were used to investigate the origin of each water quality parameter due to various land use activities, 7 principal components were obtained with 77.5% total variance, and in addition PCA identified 3 latent pollution sources to support HACA. From this study, one can conclude that the application of multivariate techniques derives meaningful information from water quality data.

  3. 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,...

  4. 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.

  5. Direct rapid analysis of trace bioavailable soil macronutrients by chemometrics-assisted energy dispersive X-ray fluorescence and scattering spectrometry.

    PubMed

    Kaniu, M I; Angeyo, K H; Mwala, A K; Mangala, M J

    2012-06-01

    Precision agriculture depends on the knowledge and management of soil quality (SQ), which calls for affordable, simple and rapid but accurate analysis of bioavailable soil nutrients. Conventional SQ analysis methods are tedious and expensive. We demonstrate the utility of a new chemometrics-assisted energy dispersive X-ray fluorescence and scattering (EDXRFS) spectroscopy method we have developed for direct rapid analysis of trace 'bioavailable' macronutrients (i.e. C, N, Na, Mg, P) in soils. The method exploits, in addition to X-ray fluorescence, the scatter peaks detected from soil pellets to develop a model for SQ analysis. Spectra were acquired from soil samples held in a Teflon holder analyzed using (109)Cd isotope source EDXRF spectrometer for 200 s. Chemometric techniques namely principal component analysis (PCA), partial least squares (PLS) and artificial neural networks (ANNs) were utilized for pattern recognition based on fluorescence and Compton scatter peaks regions, and to develop multivariate quantitative calibration models based on Compton scatter peak respectively. SQ analyses were realized with high CMD (R(2)>0.9) and low SEP (0.01% for N and Na, 0.05% for C, 0.08% for Mg and 1.98 μg g(-1) for P). Comparison of predicted macronutrients with reference standards using a one-way ANOVA test showed no statistical difference at 95% confidence level. To the best of the authors' knowledge, this is the first time that an XRF method has demonstrated utility in trace analysis of macronutrients in soil or related matrices.

  6. Analysis and classification of bacteria by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and a chemometric approach.

    PubMed

    Parisi, Daniela; Magliulo, Maria; Nanni, Paolo; Casale, Monica; Forina, Michele; Roda, Aldo

    2008-07-01

    Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a useful technique for the identification of bacteria on the basis of their characteristic protein mass spectrum fingerprint. Highly standardized instrumental analytical performance and bacterial culture conditions are required to achieve useful information. A chemometric approach based on multivariate analysis techniques was developed for the analysis of MALDI data of different bacteria to allow their identification from their fingerprint. Principal component analysis, linear discriminant analysis (LDA) and soft independent modelling of class analogy (SIMCA) were applied to the analysis of the MALDI MS mass spectra of two pathogenic bacteria, Escherichia coli O157:H7 and Yersinia enterocolitica, and the non-pathogenic E. coli MC1061. Spectra variability was assessed by growing bacteria in different media and analysing them at different culture growth times. After selection of the relevant variables, which allows the evaluation of an m/z value pattern with high discriminant power, the identification of bacteria by LDA and SIMCA was performed independently of the experimental conditions used. In order to better evaluate the analytical performance of the approach used, the ability to correctly classify different bacteria, six wild-type strains of E. coli O157:H7, was also studied and a combination of different chemometric techniques with a severe validation was developed. The analysis of spiked bovine meat samples and the agreement with an independent chemiluminescent enzyme immunoassay demonstrated the applicability of the method developed for the detection of bacteria in real samples. The easy automation of the MALDI method and the ability of multivariate techniques to reduce interlaboratory variability associated with bacterial growth time and conditions suggest the usefulness of the proposed MALDI MS approach for rapid routine food safety checks.

  7. Fluorescence, electrophoretic and chromatographic fingerprints of herbal medicines and their comparative chemometric analysis.

    PubMed

    Mazina, Jekaterina; Vaher, Merike; Kuhtinskaja, Maria; Poryvkina, Larisa; Kaljurand, Mihkel

    2015-07-01

    The aim of the present study was to compare the polyphenolic compositions of 47 medicinal herbs (HM) and four herbal tea mixtures from Central Estonia by rapid, reliable and sensitive Spectral Fluorescence Signature (SFS) method in a front face mode. The SFS method was validated for the main identified HM representatives including detection limits (0.037mgL(-1) for catechin, 0.052mgL(-1) for protocatechuic acid, 0.136mgL(-1) for chlorogenic acid, 0.058mgL(-1) for syringic acid and 0.256mgL(-1) for ferulic acid), linearity (up to 5.0-15mgL(-1)), intra-day precision (RSDs=6.6-10.6%), inter-day precision (RSDs=6.4-13.8%), matrix effect (-15.8 to +5.5) and recovery (85-107%). The phytochemical fingerprints were differentiated by parallel factor analysis (PARAFAC) combined with hierarchical cluster analysis (CA) and principal component analysis (PCA). HM were clustered into four main clusters (catechin-like, hydroxycinnamic acid-like, dihydrobenzoic acid-like derivatives containing HM and HM with low/very low content of fluorescent constituents) and 14 subclusters (rich, medium, low/very low contents). The average accuracy and precision of CA for validation HM set were 97.4% (within 85.2-100%) and 89.6%, (within 66.7-100%), respectively. PARAFAC-PCA/CA has improved the analysis of HM by the SFS method. The results were verified by two separation methods CE-DAD and HPLC-DAD-MS also combined with PARAFAC-PCA/CA. The SFS-PARAFAC-PCA/CA method has potential as a rapid and reliable tool for investigating the fingerprints and predicting the composition of HM or evaluating the quality and authenticity of different standardised formulas. Moreover, SFS-PARAFAC-PCA/CA can be implemented as a laboratory and/or an onsite method.

  8. Groundwater quality assessment using chemometric analysis in the Adyar River, South India.

    PubMed

    Venugopal, T; Giridharan, L; Jayaprakash, M

    2008-08-01

    A multivariate statistical technique has been used to assess the factors responsible for the chemical composition of the groundwater near the highly polluted Adyar River. Basic chemical parameters of the groundwater have been pooled together for evaluating and interpreting a few empirical factors controlling the chemical nature of the water. Twenty-three groundwater samples were collected in the vicinity of the Adyar River. Box-whisker plots were drawn to evaluate the chemical variation and the seasonal effect on the variables. R-mode factor analysis and cluster analysis were applied to the geochemical parameters of the water to identify the factors affecting the chemical composition of the groundwater. Dendograms of both the seasons gives two major clusters reflecting the groups of polluted and unpolluted stations. The other two minor clusters and the movement of stations from one cluster to another clearly bring out the seasonal variation in the chemical composition of the groundwater. The results of the R-mode factor analysis reveal that the groundwater chemistry of the study area reflects the influence of anthropogenic activities, rock-water interactions, saline water intrusion into the river water, and subsequent percolation into the groundwater. The complex geochemical data of the groundwater were interpreted by reducing them to seven major factors, and the seasonal variation in the chemistry of water was clearly brought out by these factors. The higher concentration of heavy metals such as Fe and Cr is attributed to the rock-water interaction and effluents from industries such as tanning, chrome-plating, and dyeing. In the urban area, the Pb concentration is high due to industrial as well as urban runoff of the atmospheric deposition from automobile pollution. Factor score analysis was used successfully to delineate the stations under study with the contributing factors, and the seasonal effect on the sample stations was identified and evaluated.

  9. 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

  10. 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

  11. 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

  12. 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

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

    PubMed

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

    2013-09-15

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

  14. 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.

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

    PubMed

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

    2011-05-01

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

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

    PubMed

    Fahmy, Usama A

    2016-01-01

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

  17. Near-infrared chemometric approach to exhaustive analysis of rice straw pretreated for bioethanol conversion.

    PubMed

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

    2011-05-01

    We report a simple analytical procedure combining near-infrared (NIR) spectroscopy with multivariate analysis to detect the saccharification efficiency of pretreated rice straw. Three types of sample preparation methods were tested to develop a powerful calibration model, with the disk sample used as the standard protocol. From the spectra dataset of NaOH-treated biomass, we obtained a good calibration for the saccharification ratio and some major structural components by partial least-squares regression. Adding dataset from hot water and dilute sulfuric acid pretreatments to NaOH sample dataset, an acceptable calibration model to predict the saccharification ratio as well as the glucose, xylose, and lignin contents was generated. NIR has a great potential for rapid screening of saccharification efficiency of pretreated biomass, which would allows us to control the quality of processing toward better bioethanol production.

  18. Chemometric Approach to Fatty Acid Profiles in Soybean Cultivars by Principal Component Analysis (PCA).

    PubMed

    Shin, Eui-Cheol; Hwang, Chung Eun; Lee, Byong Won; Kim, Hyun Tae; Ko, Jong Min; Baek, In Youl; Lee, Yang-Bong; Choi, Jin Sang; Cho, Eun Ju; Seo, Weon Taek; Cho, Kye Man

    2012-09-01

    The purpose of this study was to investigate the fatty acid profiles in 18 soybean cultivars grown in Korea. A total of eleven fatty acids were identified in the sample set, which was comprised of myristic (C14:0), palmitic (C16:0), palmitoleic (C16:1, ω7), stearic (C18:0), oleic (C18:1, ω9), linoleic (C18:2, ω6), linolenic (C18:3, ω3), arachidic (C20:0), gondoic (C20:1, ω9), behenic (C22:0), and lignoceric (C24:0) acids by gas-liquid chromatography with flame ionization detector (GC-FID). Based on their color, yellow-, black-, brown-, and green-colored cultivars were denoted. Correlation coefficients (r) between the nine major fatty acids identified (two trace fatty acids, myristic and palmitoleic, were not included in the study) were generated and revealed an inverse association between oleic and linoleic acids (r=-0.94, p<0.05), while stearic acid was positively correlated to arachidic acid (r=0.72, p<0.05). Principal component analysis (PCA) of the fatty acid data yielded four significant principal components (PCs; i.e., eigenvalues>1), which together account for 81.49% of the total variance in the data set; with PC1 contributing 28.16% of the total. Eigen analysis of the correlation matrix loadings of the four significant PCs revealed that PC1 was mainly contributed to by oleic, linoleic, and gondoic acids, PC2 by stearic, linolenic and arachidic acids, PC3 by behenic and lignoceric acids, and PC4 by palmitic acid. The score plots generated between PC1-PC2 and PC3-PC4 segregated soybean cultivars based on fatty acid composition. PMID:24471082

  19. 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

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

    PubMed

    Fahmy, Usama A

    2016-01-01

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

  1. 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.

  2. (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

  3. (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.

  4. Rapidly differentiating grape seeds from different sources based on characteristic fingerprints using direct analysis in real time coupled with time-of-flight mass spectrometry combined with chemometrics.

    PubMed

    Song, Yuqiao; Liao, Jie; Dong, Junxing; Chen, Li

    2015-09-01

    The seeds of grapevine (Vitis vinifera) are a byproduct of wine production. To examine the potential value of grape seeds, grape seeds from seven sources were subjected to fingerprinting using direct analysis in real time coupled with time-of-flight mass spectrometry combined with chemometrics. Firstly, we listed all reported components (56 components) from grape seeds and calculated the precise m/z values of the deprotonated ions [M-H](-) . Secondly, the experimental conditions were systematically optimized based on the peak areas of total ion chromatograms of the samples. Thirdly, the seven grape seed samples were examined using the optimized method. Information about 20 grape seed components was utilized to represent characteristic fingerprints. Finally, hierarchical clustering analysis and principal component analysis were performed to analyze the data. Grape seeds from seven different sources were classified into two clusters; hierarchical clustering analysis and principal component analysis yielded similar results. The results of this study lay the foundation for appropriate utilization and exploitation of grape seed samples. Due to the absence of complicated sample preparation methods and chromatographic separation, the method developed in this study represents one of the simplest and least time-consuming methods for grape seed fingerprinting.

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

    PubMed

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

    2007-03-12

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

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. The use of Vis/NIRS and chemometric analysis to predict fruit defects and postharvest behaviour of 'Nules Clementine' mandarin fruit.

    PubMed

    Magwaza, Lembe Samukelo; Landahl, Sandra; Cronje, Paul J R; Nieuwoudt, Hélène H; Mouazen, Abdul Mounem; Nicolaï, Bart M; Terry, Leon A; Opara, Umezuruike Linus

    2014-11-15

    The use of chemometrics to analyse Vis/NIRS signal collected from intact 'Nules Clementine' mandarin fruit at harvest, to predict the rind physico-chemical profile after eight weeks postharvest was explored. Vis/NIRS signals of 150 fruit were obtained immediately after harvest. Reference data on the rind were obtained after eight-week storage, including colour index (CI), rind dry matter (DM), and concentration of sugars. Partial least squares (PLS) regression was applied to develop models. Principal component analysis (PCA) followed by PLS-discriminant analysis (PLS-DA) were used to classify fruit according to canopy position. Optimal PLS model performances for DM, sucrose, glucose and fructose were obtained using multiple scatter correction pre-processing, showing respective residual predictive deviation (RPD) of 3.39, 1.75, 2.19 and 3.08. Clusters of sample distribution in the PCA and PLS-DA models based on canopy position were obtained. The results demonstrated the potential applications of Vis/NIRS to predict postharvest behaviour of mandarin fruit.

  17. 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

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

    PubMed

    Shimoyama, Masahiko; Morimoto, Susumu; Ozaki, Yukihiro

    2004-06-01

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

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

    PubMed

    Shimoyama, Masahiko; Morimoto, Susumu; Ozaki, Yukihiro

    2004-06-01

    Visible (VIS) and short-wave near infrared (SW-NIR) spectroscopy was used for non-destructive analysis of ivories. VIS-SW-NIR (500-1000 nm) spectra were measured in situ for five kinds of ivories, that is two subspecies of African elephants, mammoth, hippopotamus, and sperm whale. Chemometrics analyses were carried out for the spectral data from 500 to 1000 nm region. The five kinds of ivories were clearly discriminated from each other on the scores plot of two principal components (PCs) obtained by principal component analysis (PCA). It was noteworthy that the ivories of the two subspecies of African elephants were discriminated by the scores of PC 1. The loadings plot for PC 1 showed that the discrimination relies on the intensity changes in bands due to collagenous proteins and water interacting with proteins. It was found that the scores plot of PC 2 is useful to distinguish between the ivories of the two subspecies of African elephants and the other ivories. We also developed a calibration model that predicted the specific gravity of five kinds of ivories from their VIS-SW-NIR spectral data using partial least squares (PLS)-1 regression. The correlation coefficient and root mean square error of cross validation (RMSECV) of this model were 0.960 and 0.037, respectively. PMID:15152335

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

    PubMed

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

    2015-03-01

    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). PMID:25544186

  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. 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

  3. 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

  4. 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.

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

    PubMed

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

    2007-07-01

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

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

    PubMed

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

    2013-12-01

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

  7. 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.

  8. 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

  9. 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

  10. 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.

  11. Chemometric brains for artificial tongues.

    PubMed

    Oliveri, Paolo; Casolino, M Chiara; Forina, Michele

    2010-01-01

    The last years showed a significant trend toward the exploitation of rapid and economic analytical devices able to provide multiple information about samples. Among these, the so-called artificial tongues represent effective tools which allow a global sample characterization comparable to a fingerprint. Born as taste sensors for food evaluation, such devices proved to be useful for a wider number of purposes. In this review, a critical overview of artificial tongue applications over the last decade is outlined. In particular, the focus is centered on the chemometric techniques, which allow the extraction of valuable information from nonspecific data. The basic steps of signal processing and pattern recognition are discussed and the principal chemometric techniques are described in detail, highlighting benefits and drawbacks of each one. Furthermore, some novel methods recently introduced and particularly suitable for artificial tongue data are presented.

  12. Metabolomic fingerprint classification of Brachychiton acerifolius organs via UPLC-qTOF-PDA-MS analysis and chemometrics.

    PubMed

    Farag, Mohamed A; Abou Zeid, Aisha H; Hamed, Manal A; Kandeel, Zeinab; El-Rafie, Hanaa M; El-Akad, Radwa H

    2015-01-01

    Brachychiton acerifolius, or Sterculia acerifolia as formerly known, is a member of a genus reported for a myriad of bioactive compounds. Metabolome analysis of B. acerifolius--leaves, flowers and seeds--and quantification of its major compounds are demonstrated in this study. Metabolites were analysed via UPLC-PDA-qTOF-(±) ESI-MS and UPLC/ITMS, with a total of 56 metabolites characterised including 30 flavonoids, 2 anthocyanins, 6 phenolic acids (i.e. citric and hydroxycitric acid conjugates) and 8 fatty acids (FAs). Multivariate data analyses (i.e. principle component analysis and orthogonal partial least square-discriminate analysis) were applied to identify metabolite markers for each organ. Pelargonidin-O-glucoside and naringenin-O-glucuronide were found exclusively in flowers versus flavone enrichment in leaves (i.e. luteolin-O-glucuronide and apigenin-O-rhamnosyl glucuronide). Gas chromatography/mass spectrometry analysis revealed the presence of toxic cyclopropene FAs in seeds which may restrict its use. Antioxidant activity assessment for the three organs was performed in comparison with vitamin C as positive control. Leaves showed the highest activity (IC50 0.015 mg/mL). PMID:25296242

  13. 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 (...

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

    PubMed

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

    2014-02-15

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

  15. 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

  16. 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

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

    PubMed

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

    2013-11-01

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

  18. 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.

  19. 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

  20. Near infrared spectroscopic (NIRS) analysis of drug-loading rate and particle size of risperidone microspheres by improved chemometric model.

    PubMed

    Song, Jia; Xie, Jing; Li, Chenliang; Lu, Jia-Hui; Meng, Qing-Fan; Yang, Zhaogang; Lee, Robert J; Wang, Di; Teng, Le-Sheng

    2014-09-10

    Microspheres have been developed as drug carriers in controlled drug delivery systems for years. In our present study, near infrared spectroscopy (NIRS) is applied to analyze the particle size and drug loading rate in risperidone poly(d,l-lactide-co-glycolide) (PLGA) microspheres. Various batches of risperidone PLGA microspheres were designed and prepared successfully. The particle size and drug-loading rate of all the samples were determined by a laser diffraction particle size analyzer and high performance liquid chromatography (HPLC) system. Monte Carlo algorithm combined with partial least squares (MCPLS) method was applied to identify the outliers and choose the numbers of calibration set. Furthermore, a series of preprocessing methods were performed to remove signal noise in NIR spectra. Moving window PLS and radical basis function neural network (RBFNN) methods were employed to establish calibration model. Our data demonstrated that PLS-developed model was only suitable for drug loading analysis in risperidone PLGA microspheres. Comparatively, RBFNN-based predictive models possess better fitting quality, predictive effect, and stability for both drug loading rate and particle size analysis. The correlation coefficients of calibration set (Rc(2)) were 0.935 and 0.880, respectively. The performance of optimum RBFNN models was confirmed by independent verification test with 15 samples. Collectively, our method is successfully performed to monitor drug-loading rate and particle size during risperidone PLGA microspheres preparation.

  1. 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

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

    PubMed

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

    2015-10-09

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

  3. 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.

  4. Assessment of the sequential principal component analysis chemometric tool to identify the soluble atmospheric pollutants in rainwater.

    PubMed

    Montoya-Mayor, Rocío; Fernández-Espinosa, Antonio José; Ternero-Rodríguez, Miguel

    2011-02-01

    In this study a new method of principal component (PC) analysis, sequential PC analysis (SPCA), is proposed and assessed on real samples. The aim was to identify the atmospheric emission sources of soluble compounds in rainwater samples, and the sample collection was performed with an automatic sampler. Anions and cations were separated and quantified by ion chromatography, whereas trace metals and metalloids were determined by inductively coupled plasma mass spectrometry. SPCA results showed eight interfering PCs and ten significant PCs. The interfering cases originated from different atmospheric sources, such as resuspended crustal particles, marine aerosols, urban traffic and a fertilizer factory. The significant PCs explained 84.6% of the total variance; 28.1% accounted for the main contribution, which was resuspended industrial soil from a fertilizer factory containing NO(2)(-), NH(4)(+), NO(3)(-), SO(4)(2-), F(-), Al, K(+), Mn, Sb and Ca(2+) as indicators of the fertilizer factory. Another important source (15.0%) was found for Na(+), Mg(2+), K(+), Cl(-) and SO(4)(2-) , which represents the marine influence from south and southwest directions. Emissions of Ba(2+), Pb, Sr(2+), Sb and Mo, which represent a traffic source deposited in soils, were identified as another abundant contribution (12.1%) to the rainwater composition. Other important contributions to the rainwater samples that were identified through SPCA included the following: different urban emissions (Cu, As, Cd, Zn, Mo and Co, 18.1%), emissions from vegetation (HCOO(-), 7.7%) and emissions from industrial combustion processes (Ni, V 15.6%). The application of SPCA proved to be a useful tool to identify the complete information on rainwater samples as indicators of urban air pollution in a city influenced mainly by vehicle traffic emissions and resuspended polluted soils.

  5. 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.

  6. 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.

  7. 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

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

    PubMed

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

    2014-04-01

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

  9. 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.

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

    PubMed

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

    2005-01-01

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

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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.

  1. 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.

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

    PubMed Central

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

    2002-01-01

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

  3. Chemometrics applications in biotech processes: a review.

    PubMed

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

    2011-01-01

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

  4. Does chemometrics enhance the performance of electroanalysis?

    PubMed

    Ni, Yongnian; Kokot, Serge

    2008-09-26

    This review explores the question whether chemometrics methods enhance the performance of electroanalytical methods. Electroanalysis has long benefited from the well-established techniques such as potentiometric titrations, polarography and voltammetry, and the more novel ones such as electronic tongues and noses, which have enlarged the scope of applications. The electroanalytical methods have been improved with the application of chemometrics for simultaneous quantitative prediction of analytes or qualitative resolution of complex overlapping responses. Typical methods include partial least squares (PLS), artificial neural networks (ANNs), and multiple curve resolution methods (MCR-ALS, N-PLS and PARAFAC). This review aims to provide the practising analyst with a broad guide to electroanalytical applications supported by chemometrics. In this context, after a general consideration of the use of a number of electroanalytical techniques with the aid of chemometrics methods, several overviews follow with each one focusing on an important field of application such as food, pharmaceuticals, pesticides and the environment. The growth of chemometrics in conjunction with electronic tongue and nose sensors is highlighted, and this is followed by an overview of the use of chemometrics for the resolution of complicated profiles for qualitative identification of analytes, especially with the use of the MCR-ALS methodology. Finally, the performance of electroanalytical methods is compared with that of some spectrophotometric procedures on the basis of figures-of-merit. This showed that electroanalytical methods can perform as well as the spectrophotometric ones. PLS-1 appears to be the method of practical choice if the %relative prediction error of approximately +/-10% is acceptable.

  5. 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.

  6. 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.

  7. 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

  8. Chemometric techniques in oil classification from oil spill fingerprinting.

    PubMed

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

    2016-10-15

    Extended use of GC-FID and GC-MS in oil spill fingerprinting and matching is significantly important for oil classification from the oil spill sources collected from various areas of Peninsular Malaysia and Sabah (East Malaysia). Oil spill fingerprinting from GC-FID and GC-MS coupled with chemometric techniques (discriminant analysis and principal component analysis) is used as a diagnostic tool to classify the types of oil polluting the water. Clustering and discrimination of oil spill compounds in the water from the actual site of oil spill events are divided into four groups viz. diesel, Heavy Fuel Oil (HFO), Mixture Oil containing Light Fuel Oil (MOLFO) and Waste Oil (WO) according to the similarity of their intrinsic chemical properties. Principal component analysis (PCA) demonstrates that diesel, HFO, MOLFO and WO are types of oil or oil products from complex oil mixtures with a total variance of 85.34% and are identified with various anthropogenic activities related to either intentional releasing of oil or accidental discharge of oil into the environment. Our results show that the use of chemometric techniques is significant in providing independent validation for classifying the types of spilled oil in the investigation of oil spill pollution in Malaysia. This, in consequence would result in cost and time saving in identification of the oil spill sources. PMID:27397593

  9. Chemometric techniques in oil classification from oil spill fingerprinting.

    PubMed

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

    2016-10-15

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

  10. Chemometric characterization of river water quality.

    PubMed

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

    2013-04-01

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

  11. Combining metabolomic non-targeted GC×GC-ToF-MS analysis and chemometric ASCA-based study of variances to assess dietary influence on type 2 diabetes development in a mouse model.

    PubMed

    Ly-Verdú, Saray; Gröger, Thomas Maximilian; Arteaga-Salas, Jose Manuel; Brandmaier, Stefan; Kahle, Melanie; Neschen, Susanne; Harbě de Angelis, Martin; Zimmermann, Ralf

    2015-01-01

    Insulin resistance (IR) lies at the origin of type 2 diabetes. It induces initial compensatory insulin secretion until insulin exhaustion and subsequent excessive levels of glucose (hyperglycemia). A high-calorie diet is a major risk factor contributing to the development of this metabolic disease. For this study, a time-course experiment was designed that consisted of two groups of mice. The aim of this design was to reproduce the dietary conditions that parallel the progress of IR over time. The first group was fed with a high-fatty-acid diet for several weeks and followed by 1 week of a low-fatty-acid intake, while the second group was fed with a low-fatty-acid diet during the entire experiment. The metabolomic fingerprint of C3HeB/FeJ mice liver tissue extracts was determined by means of two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-ToF-MS). This article addresses the application of ANOVA-simultaneous component analysis (ASCA) to the found metabolomic profile. By performing hyphenated high-throughput analytical techniques together with multivariate chemometric methodology on metabolomic analysis, it enables us to investigate the sources of variability in the data related to each experimental factor of the study design (defined as time, diet and individual). The contribution of the diet factor in the dissimilarities between the samples appeared to be predominant over the time factor contribution. Nevertheless, there is a significant contribution of the time-diet interaction factor. Thus, evaluating the influences of the factors separately, as it is done in classical statistical methods, may lead to inaccurate interpretation of the data, preventing achievement of consistent biological conclusions.

  12. Quantitative evaluation of mefenamic acid polymorphs by terahertz-chemometrics.

    PubMed

    Otsuka, Makoto; Nishizawa, Jun-ichi; Shibata, Jiro; Ito, Masahiko

    2010-09-01

    The purpose of the present study is to measure polymorphic content in a bulk powder, mefenamic acid polymorph of pharmaceuticals, as a model drug by THz-spectrometer using frequency-tunable THz wave generators based on difference-frequency generation in gallium phosphate crystals. Mefenamic acid polymorphic forms I and II were obtained by recrystallisation. Eleven standard samples varying a various polymorphic form I content (0-100%) were prepared by physical mixing. After smoothing and area normalising, the THz-spectra of all standard samples showed an isosbestic point at 3.70 THz. After the THz-spectral data sets were arranged into five frequency ranges, and pretreated using various functions, calibration models were calculated by the partial least square regression method. The effect of spectral data management on the chemometric parameters of the calibration models was investigated. The relationship between predicted and actual form I content was the best linear plot. On the regression vector (RV) that corresponded to absorption THz-spectral data, the peak at 1.45 THz was the highest value, and the peak at 2.25 THz was the lowest on RV. THz-spectroscopy with chemometrics would be useful for the quantitative evaluation of mefenamic acid polymorphs in the pharmaceutical industry. This method is expected to provide a rapid and nondestructive quantitative analysis of polymorphs. PMID:20665848

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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

  19. (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.

  20. 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

  1. 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…

  2. 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....

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

    PubMed

    Yudthavorasit, Soparat; Wongravee, Kanet; Leepipatpiboon, Natchanun

    2014-09-01

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

  4. 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.

  5. Analysis of the Correlation between Commodity Grade and Quality of Angelica sinensis by Determination of Active Compounds Using Ultraperformance Liquid Chromatography Coupled with Chemometrics

    PubMed Central

    Wang, Zenghui; Wang, Dongmei; Huang, Linfang

    2014-01-01

    The contents of ferulic acid, senkyunolide A, butylidenephthalide, ligustilide, and n-butylphthalide were determined by UPLC analytical method; the correlation among the grade, average weight, and content was explored by correlation analysis and analysis of variance (ANOVA); the different commercial grades with average weight and content were revealed by principal component analysis (PCA) and then rationality analysis grade classification of A. sinensis. The results showed that various commercial grades can be distinguished by PCA analysis. And there was significant negative correlation between the commodity grades and average weight, commodity, and the content of bioactive compounds, while the content of senkyunolide A had significant negative correlation with commodity grades (P < 0.01). Average weight had no correlation with chemicals compounds. Additionally, there was significant positive correlation among the bioactive compounds (content of ferulic acid and phthalides) of different grades of A. sinensis. The content of senkyunolide A, butylidenephthalide, and ligustilide had significant positive correlation with the content of ferulic acid. The content of ligustilide and butylidenephthalide had significant positive correlation with the content of senkyunolide A. The content of ligustilide had significant positive correlation with the content of butylidenephthalide. The basis of grades classification is related with the difference levels of the bioactive compounds. PMID:24826193

  6. 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

  7. The start-to-end chemometric image processing of 2D thin-layer videoscans.

    PubMed

    Komsta, Łukasz; Cieśla, Łukasz; Bogucka-Kocka, Anna; Józefczyk, Aleksandra; Kryszeń, Jakub; Waksmundzka-Hajnos, Monika

    2011-05-13

    The purpose of the research was to recommend a unified procedure of image preprocessing of 2D thin layer videoscans for further supervised or unsupervised chemometric analysis. All work was done with open source software. The videoscans saved as JPG files underwent the following procedures: denoising using a median filter, baseline removal with the rollerball algorithm and nonlinear warping using spline functions. The application of the proposed procedure enabled filtration of random difference between images (background intensity changes and spatial differences of the spots location). After the preprocessing only spot intensities have an influence on the performed PCA or other techniques. The proposed technique was successfully applied to recognize the differences between three Carex species from the 2D videoscans of the extracts. The proposed solution may be of value for the any chemometric task--both unsupervised and supervised.

  8. 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.

  9. 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...

  10. Fingerprint analysis, multi-component quantitation, and antioxidant activity for the quality evaluation of Salvia miltiorrhiza var. alba by high-performance liquid chromatography and chemometrics.

    PubMed

    Zhang, Danlu; Duan, Xiaoju; Deng, Shuhong; Nie, Lei; Zang, Hengchang

    2015-10-01

    Salvia miltiorrhiza Bge. var. alba C.Y. Wu and H.W. Li has wide prospects in clinical practice. A useful comprehensive method was developed for the quality evaluation of S. miltiorrhiza var. alba by three quantitative parameters: high-performance liquid chromatography fingerprint, ten-component contents, and antioxidant activity. The established method was validated for linearity, precision, repeatability, stability, and recovery. Principal components analysis and hierarchical clustering analysis were both used to evaluate the quality of the samples from different origins. The results showed that there were category discrepancies in quality of S. miltiorrhiza var. alba samples according to the three quantitative parameters. Multivariate linear regression was adopted to explore the relationship between components and antioxidant activity. Three constituents, namely, danshensu, rosmarinic acid, and salvianolic acid B, significantly correlated with antioxidant activity, and were successfully elucidated by the optimized multivariate linear regression model. The combined use of high-performance liquid chromatography fingerprint analysis, simultaneous multicomponent quantitative analysis, and antioxidant activity for the quality evaluation of S. miltiorrhiza var. alba is a reliable, comprehensive, and promising approach, which might provide a valuable reference for other herbal products in general to improve their quality control.

  11. 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.

  12. Classification and characterisation of Spanish red wines according to their appellation of origin based on chromatographic profiles and chemometric data analysis.

    PubMed

    Serrano-Lourido, Daniel; Saurina, Javier; Hernández-Cassou, Santiago; Checa, Antonio

    2012-12-01

    Chromatographic profiles of wines have been used as a fingerprint for the discrimination of Spanish wines based on oenological practices. In order to extract information of different families of phenolic compounds, profiles of different UV-vis absorption wavelengths (280, 310, 370 and 520nm) and fluorescence (ex=260nm; em=360nm) were analysed. A total of thirteen phenolic compounds which allowed the discrimination of wines of three different Spanish appellations (Penedes, Rioja and Ribera del Duero) were selected by means of principal component analysis (PCA). Afterwards, these compounds were used to build partial least squares discriminant analysis (PLS1-DA and PLS2-DA) models which allowed the discrimination of wines according to their appellation with classification rates for independent test sets higher than 96% and 93% for PLS1-DA and PLS2-DA models respectively. Finally, characteristic compounds of each appellation were tentatively identified by means of liquid chromatography-mass spectrometry (LC-MS) analysis. Thus, ten out of thirteen compounds (i.e., gallic acid for Penedes, trans-coumaroyltartaric and trans-caffeoyltartaric acids for Rioja and myricetin for Ribera del Duero wines) have been proposed.

  13. 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

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

    PubMed

    Pei, Ke; Cai, Hao; 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.

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

    PubMed

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

    2012-06-21

    We examined the correlation between the dynamically sampled anharmonic frequency of the OH stretching motion and the corresponding instantaneous geometric parameters associated with the structure of crystalline sodium hydrogen bis(sulfate), which is a benchmark system with an extremely short hydrogen bond. We analyzed the trajectory obtained by a conventional Car-Parrinello molecular dynamics simulation, followed by an a posteriori quantization of the proton motion. For statistical analysis we applied the established methodologies of multiple linear regression, principal component analysis, principal component regression, and Kohonen neural networks. No simple correlation scheme between the OH stretching frequency and any particular geometry parameter (or their combination) was found. In comparison to the established correlation schemes (e.g., Mikenda and Novak) that consider a series of systems, our study provides a complementary insight into the nature of hydrogen bonding of a single system, in the sense that it considers the important aspects of fluctuations of the environment and the resulting broadening of the OH stretching band, which cannot be adequately assessed by experiment. The absence of appreciable correlations gives strong evidence of the extreme complexity of short hydrogen bonding. PMID:22594525

  16. 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

  17. 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

  18. Chemometric processing of second-order liquid chromatographic data with UV-vis and fluorescence detection. A comparison of multivariate curve resolution and parallel factor analysis 2.

    PubMed

    Bortolato, Santiago A; Olivieri, Alejandro C

    2014-09-01

    Second-order liquid chromatographic data with multivariate spectral (UV-vis or fluorescence) detection usually show changes in elution time profiles from sample to sample, causing a loss of trilinearity in the data. In order to analyze them with an appropriate model, the latter should permit a given component to have different time profiles in different samples. Two popular models in this regard are multivariate curve resolution-alternating least-squares (MCR-ALS) and parallel factor analysis 2 (PARAFAC2). The conditions to be fulfilled for successful application of the latter model are discussed on the basis of simple chromatographic concepts. An exhaustive analysis of the multivariate calibration models is carried out, employing both simulated and experimental chromatographic data sets. The latter involve the quantitation of benzimidazolic and carbamate pesticides in fruit and juice samples using liquid chromatography with diode array detection, and of polycyclic aromatic hydrocarbons in water samples, in both cases in the presence of potential interferents using liquid chromatography with fluorescence spectral detection, thereby achieving the second-order advantage. The overall results seem to favor MCR-ALS over PARAFAC2, especially in the presence of potential interferents.

  19. 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.

  20. 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

  1. 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.

  2. 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.

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

    PubMed

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

    2014-05-15

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

  4. 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

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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

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

    PubMed

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

    2014-01-01

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

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

    PubMed

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

    2014-05-15

    Nigella sativa, commonly known as black cumin seed, is a popular herbal supplement that contains numerous phytochemicals including terpenoids, saponins, flavonoids, alkaloids. Only a few of the ca. 15 species in the genus Nigella have been characterized in terms of phytochemical or pharmacological properties. Here, large scale metabolic profiling including UPLC-PDA-MS and GC-MS with further multivariate analysis was utilized to classify 6 Nigella species. Under optimized conditions, we were able to annotate 52 metabolites including 8 saponins, 10 flavonoids, 6 phenolics, 10 alkaloids, and 18 fatty acids. Major peaks in UPLC-MS spectra contributing to the discrimination among species were assigned as kaempferol glycosidic conjugates, with kaempferol-3-O-[glucopyranosyl-(1→2)-galactopyranosyl-(1→2)-glucopyranoside, identified as potential taxonomic marker for N. sativa. Compared with GC-MS, UPLC-MS was found much more efficient in Nigella sample classification based on genetic and geographical origin. Nevertheless, both GC-MS and UPLC-MS support the remote position of Nigella nigellastrum in relation to the other taxa. PMID:24423541

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

    PubMed

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

    2015-03-01

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

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

    PubMed

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

    2012-07-15

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

  14. 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.

  15. A comprehensive strategy using chromatographic profiles combined with chemometric methods: Application to quality control of Polygonum cuspidatum Sieb. et Zucc.

    PubMed

    Gao, Fangyuan; Xu, Zihua; Wang, Weizhong; Lu, Guocai; Vander Heyden, Yvan; Zhou, Tingting; Fan, Guorong

    2016-09-30

    For the strict quality control of herbs, a comprehensive strategy based on chromatographic profiles and chemometric methods which could reliably select quantitative indices, robustly quantitate multi-markers and systematically compare different chemometric methods was proposed and successfully applied to the quality analysis of P. cuspidatum. Based on the construction of chromatographic profiles by an efficient accelerated solvent extraction (ASE) and reliable high-performance liquid chromatography-ultraviolet (HPLC-UV) methods, different chemometric methods were employed, namely similarity analyses (SA), hierarchical clustering analysis (HCA) and linear discriminant analysis (LDA). The differences in classification of herb samples were studied for the first time. To reasonably determine the quality of herbs and evaluate different chemometric methods, a comprehensive strategy containing three key steps was performed including selection of quantitative indices, development of a reliable quantification method and adoption of an easily calculated and visible parameter. The quantitative method which was acceptable with good linearity with correlation coefficients >0.9995 and satisfactory repeatability (RSD<1.5%), precision (RSD<2.84%), reproducibility (RSD<2.88%), stability (RSD<2.85%) and recoveries (91.5%-105.6%, RSD<2.83%) was applied to quality evaluation of fourteen batches of the P. cuspidatum samples through simultaneous quantitative determination of fifteen marker compounds. The limits of quantitation of fifteen compounds ranged from 1 to 60μg/ml. From the results of the quality evaluation, it was found that the different calculation theories of the chemometric methods resulted in the variation of classifiers of samples: SA classified samples through the mean values and HCA & LDA classified similar objects. PMID:27634211

  16. A comprehensive strategy using chromatographic profiles combined with chemometric methods: Application to quality control of Polygonum cuspidatum Sieb. et Zucc.

    PubMed

    Gao, Fangyuan; Xu, Zihua; Wang, Weizhong; Lu, Guocai; Vander Heyden, Yvan; Zhou, Tingting; Fan, Guorong

    2016-09-30

    For the strict quality control of herbs, a comprehensive strategy based on chromatographic profiles and chemometric methods which could reliably select quantitative indices, robustly quantitate multi-markers and systematically compare different chemometric methods was proposed and successfully applied to the quality analysis of P. cuspidatum. Based on the construction of chromatographic profiles by an efficient accelerated solvent extraction (ASE) and reliable high-performance liquid chromatography-ultraviolet (HPLC-UV) methods, different chemometric methods were employed, namely similarity analyses (SA), hierarchical clustering analysis (HCA) and linear discriminant analysis (LDA). The differences in classification of herb samples were studied for the first time. To reasonably determine the quality of herbs and evaluate different chemometric methods, a comprehensive strategy containing three key steps was performed including selection of quantitative indices, development of a reliable quantification method and adoption of an easily calculated and visible parameter. The quantitative method which was acceptable with good linearity with correlation coefficients >0.9995 and satisfactory repeatability (RSD<1.5%), precision (RSD<2.84%), reproducibility (RSD<2.88%), stability (RSD<2.85%) and recoveries (91.5%-105.6%, RSD<2.83%) was applied to quality evaluation of fourteen batches of the P. cuspidatum samples through simultaneous quantitative determination of fifteen marker compounds. The limits of quantitation of fifteen compounds ranged from 1 to 60μg/ml. From the results of the quality evaluation, it was found that the different calculation theories of the chemometric methods resulted in the variation of classifiers of samples: SA classified samples through the mean values and HCA & LDA classified similar objects.

  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.

  18. 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.

  19. [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

  20. 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

  1. 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.

  2. 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.

  3. 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

  4. Usefulness of near-infrared reflectance (NIR) spectroscopy and chemometrics to discriminate fishmeal batches made with different fish species.

    PubMed

    Cozzolino, Daniel; Chree, A; Scaife, J R; Murray, Ian

    2005-06-01

    Near-infrared reflectance (NIR) spectroscopy combined with chemometrics was used to identify and authenticate fishmeal batches made with different fish species. Samples from a commercial fishmeal factory (n = 60) were scanned in the NIR region (1100-2500 nm) in a monochromator instrument in reflectance. Principal component analysis (PCA), dummy partial least-squares regression (DPLS), and linear discriminant analysis (LDA) based on PCA scores were used to identify the origin of fishmeal produced using different fish species. Cross-validation was used as validation method when classification models were developed. DPLS correctly classified 80 and 82% of the fishmeal samples. LDA calibration models correctly classified >80% of fishmeal samples according to fish species The results demonstrated the usefulness of NIR spectra combined with chemometrics as an objective and rapid method for the authentication and identification of fish species used to manufacture the fishmeal.

  5. A fast chemometric procedure based on NIR data for authentication of honey with protected geographical indication.

    PubMed

    Herrero Latorre, C; Peña Crecente, R M; García Martín, S; Barciela García, J

    2013-12-15

    In this work, information contained in near infrared (NIR) spectra of honeys with protected geographical indication (PGI) "Mel de Galicia" was processed by means of different chemometric techniques to develop an authentication system for this high quality food product. Honey spectra were obtained in a fast and single way, and they were pretreated by means of standard normal variate transformation in order to remove the influence of particle size, scattering and other factors, and prior to their use as input data. As the first step in chemometric study, display techniques such as principal component analysis and cluster analysis were applied in order to demonstrate that the NIR data contained useful information to develop a pattern recognition classification system to authenticate honeys with PGI. The second step consisted in the application of different pattern recognition techniques (such as D-PLS: Discriminant partial least squares regression; SIMCA: Soft independent modelling of class analogy; KNN: K-nearest neighbours; and MLF-NN: Multilayer feedforward neural networks) to derive diverse models for PGI-honey class with the objective of detecting possible falsification of these high-quality honeys. Amongst all the classification chemometric procedures, SIMCA achieved to be the best PGI-model with 93.3% of sensitivity and 100% of specificity. Therefore, the combination of NIR information data with SIMCA developed a single and fast method in order to differentiate between genuine PGI-Galician honey samples and other commercial honey samples from other origins that, due to their lower price, could be used as substrates for falsification of genuine PGI ones.

  6. 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

  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. 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...

  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. 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

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

    PubMed

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

    2014-10-01

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

  12. 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.

  13. 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

  14. 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.

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

    PubMed

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

    2013-11-15

    In 1819 Alexander Marcet proposed that seawater contains small amounts of all soluble substances and that the relative abundances of some of them were constant. This hypothesis is nowadays known as Marcet's Principle or the principle of constancy of the composition of seawater. Based on this principle, the present research tried to prove that it is possible to detect polluted seawater samples using the seawater H(+) affinity spectrum by the application of the possibilities provided by chemometric tools. Seawater samples were classified using the principal component analysis (PCA) of the HBound spectra of the samples. It was concluded that the sampling points location does not have any influence in the cluster formation, while the season in which they were collected is significant. On the other hand, the seawater composition was calibrated using estuary water samples of different salinities. Once the major constituents were measured, the data analysis concluded that it is possible to make a calibration of the HBound spectrum vs. any of these constituents by means of partial least square (PLS) regression. Thus, the experimental evidence collected in this work confirms that it is possible to detect polluted sea or estuary water samples using these chemometric tools and the H(+) affinity spectrum because with polluted samples these multivariate methods lead to incoherent results. So, suspect polluted zones may be monitored in a simple way with a low cost method and spending much less time. PMID:24148380

  17. 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.

  18. 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

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

    PubMed

    Zhang, Hongguang; Yang, Qinmin; Lu, Jiangang

    2014-01-01

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

  20. 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%).

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

    PubMed

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

    2016-11-01

    Discrimination of genetically modified organisms is increasingly demanded by legislation and consumers worldwide. The feasibility of a non-destructive discrimination of transgenic rice seeds from its non-transgenic counterparts was examined by terahertz spectroscopy imaging system combined with chemometrics. Principal component analysis (PCA), least squares support vector machines (LS-SVM), PCA-back propagation neural network (PCA-BPNN), and random forest (RF) models with the first and second derivative and standard normal variate transformation (SNV) pre-treatments were applied to classify rice seeds based on genotype. The results demonstrated that differences between non-transgenic and transgenic rice seeds did exist, and an excellent classification (accuracy was 96.67% in the prediction set) could be achieved using the RF model combined with the first derivative pre-treatment. The results indicated that THz spectroscopy imaging together with chemometrics would be a promising technique to identify transgenic rice seeds with high efficiency and without any sample preparation. PMID:27211665

  2. Chemometrics applications in biotechnology processes: predicting column integrity and impurity clearance during reuse of chromatography resin.

    PubMed

    Rathore, Anurag S; Mittal, Shachi; Lute, Scott; Brorson, Kurt

    2012-01-01

    Separation media, in particular chromatography media, is typically one of the major contributors to the cost of goods for production of a biotechnology therapeutic. To be cost-effective, it is industry practice that media be reused over several cycles before being discarded. The traditional approach for estimating the number of cycles a particular media can be reused for involves performing laboratory scale experiments that monitor column performance and carryover. This dataset is then used to predict the number of cycles the media can be used at manufacturing scale (concurrent validation). Although, well accepted and widely practiced, there are challenges associated with extrapolating the laboratory scale data to manufacturing scale due to differences that may exist across scales. Factors that may be different include: level of impurities in the feed material, lot to lot variability in feedstock impurities, design of the column housing unit with respect to cleanability, and homogeneity of the column packing. In view of these challenges, there is a need for approaches that may be able to predict column underperformance at the manufacturing scale over the product lifecycle. In case such an underperformance is predicted, the operators can unpack and repack the chromatography column beforehand and thus avoid batch loss. Chemometrics offers one such solution. In this article, we present an application of chemometrics toward the analysis of a set of chromatography profiles with the intention of predicting the various events of column underperformance including the backpressure buildup and inefficient deoxyribonucleic acid clearance.

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

    NASA Astrophysics Data System (ADS)

    Glavanović, Siniša; Glavanović, Marija; Tomišić, Vladislav

    2016-03-01

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

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

    SciTech Connect

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

    2007-10-24

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

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

    PubMed

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

    2014-12-01

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

  6. 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

  7. 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.

  8. 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.

  9. Evaluation of chemometric techniques to select orthogonal chromatographic systems.

    PubMed

    Van Gyseghem, E; Dejaegher, B; Put, R; Forlay-Frick, P; Elkihel, A; Daszykowski, M; Héberger, K; Massart, D L; Heyden, Y Vander

    2006-04-11

    Several chemometric techniques were compared for their performance to determine the orthogonality and similarity between chromatographic systems. Pearson's correlation coefficient (r) based color maps earlier were used to indicate selectivity differences between systems. These maps, in which the systems were ranked according to decreasing or increasing dissimilarities observed in the weighted-average-linkage dendrogram, were now applied as reference method. A number of chemometric techniques were evaluated as potential alternative (visualization) methods for the same purpose. They include hierarchical clustering techniques (single, complete, unweighted-average-linkage, centroid and Ward's method), the Kennard and Stone algorithm, auto-associative multivariate regression trees (AAMRT), and the generalized pairwise correlation method (GPCM) with McNemar's statistical test. After all, the reference method remained our preferred technique to select orthogonal and identify similar systems.

  10. Chemometric classification of casework arson samples based on gasoline content.

    PubMed

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

    2014-02-01

    Detection and identification of ignitable liquids (ILs) in arson debris is a critical part of arson investigations. The challenge of this task is due to the complex and unpredictable chemical nature of arson debris, which also contains pyrolysis products from the fire. ILs, most commonly gasoline, are complex chemical mixtures containing hundreds of compounds that will be consumed or otherwise weathered by the fire to varying extents depending on factors such as temperature, air flow, the surface on which IL was placed, etc. While methods such as ASTM E-1618 are effective, data interpretation can be a costly bottleneck in the analytical process for some laboratories. In this study, we address this issue through the application of chemometric tools. Prior to the application of chemometric tools such as PLS-DA and SIMCA, issues of chromatographic alignment and variable selection need to be addressed. Here we use an alignment strategy based on a ladder consisting of perdeuterated n-alkanes. Variable selection and model optimization was automated using a hybrid backward elimination (BE) and forward selection (FS) approach guided by the cluster resolution (CR) metric. In this work, we demonstrate the automated construction, optimization, and application of chemometric tools to casework arson data. The resulting PLS-DA and SIMCA classification models, trained with 165 training set samples, have provided classification of 55 validation set samples based on gasoline content with 100% specificity and sensitivity. PMID:24447448

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

    PubMed

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

    2010-06-01

    Chemometric Modeling Markup Language (CMML) is developed by us for containing chemometrics models within one document through converting binary data into strings by base64 encode/decode algorithms to solve the interoperability issue in sharing chemometrics models. It provides a base functionality for storage of sampling, variable selection, pretreating, outlier and modeling parameters and data. With the help of base64 algorithm, the usability of CMML is in equilibrium with size by transforming the binary data into base64 encoded string. Due to the advantages of Extensible Markup Language (XML), models stored in CMML can be easily reused in various other software and programming languages as long as the programming language has XML parsing library. One can also use the XML Path Language (XPath) query language to select desired data from the CMML file effectively. The application of this language in near infrared spectroscopy model storage is implemented as a class in C++ language and available as open source software (http://code.google.com/p/cmml), and the implementations in other languages, such as MATLAB and R are in progress. PMID:20493291

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

    PubMed

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

    2004-01-28

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

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

    PubMed

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

    2015-01-01

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

  14. Overview of the Usage of Chemometric Methods for Remediation Techniques of Radionuclides

    NASA Astrophysics Data System (ADS)

    Yilmaz, C.; Aslani, M. A. A.

    The aim of this study is to investigate the treatment of chemometric tools on remediation techniques for removal of Cs-137, Sr-90 and Ra-226 from environmental samples. In this study; statistical data are collected from literature about applications of chemometric methods.

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

    PubMed

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

    2015-11-27

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

  16. Combining (1)H NMR spectroscopy and chemometrics to identify heparin samples that may possess dermatan sulfate (DS) impurities or oversulfated chondroitin sulfate (OSCS) contaminants.

    PubMed

    Zang, Qingda; Keire, David A; Wood, Richard D; Buhse, Lucinda F; Moore, Christine M V; Nasr, Moheb; Al-Hakim, Ali; Trehy, Michael L; Welsh, William J

    2011-04-01

    Heparin is a naturally produced, heterogeneous compound consisting of variably sulfated and acetylated repeating disaccharide units. The structural complexity of heparin complicates efforts to assess the purity of the compound, especially when differentiating between similar glycosaminoglycans. Recently, heparin sodium contaminated with oversulfated chondroitin sulfate A (OSCS) has been associated with a rapid and acute onset of an anaphylactic reaction. In addition, naturally occurring dermatan sulfate (DS) was found to be present in these and other heparin samples as an impurity due to incomplete purification. The present study was undertaken to determine whether chemometric analysis of these NMR spectral data would be useful for discrimination between USP-grade samples of heparin sodium API and those deemed unacceptable based on their levels of DS, OSCS, or both. Several multivariate chemometric methods for clustering and classification were evaluated; specifically, principal components analysis (PCA), partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and the k-nearest-neighbor (kNN) method. Data dimension reduction and variable selection techniques, implemented to avoid over-fitting the training set data, markedly improved the performance of the classification models. Under optimal conditions, a perfect classification (100% success rate) was attained on external test sets for the Heparin vs OSCS model. The predictive rates for the Heparin vs DS, Heparin vs [DS+OSCS], and Heparin vs DS vs OSCS models were 89%, 93%, and 90%, respectively. In most cases, misclassifications can be ascribed to the similarity in NMR chemical shifts of heparin and DS. Among the chemometric methods evaluated in this study, we found that the LDA models were superior to the PLS-DA and kNN models for classification. Taken together, the present results demonstrate the utility of chemometric methods when applied in combination with (1)H NMR spectral

  17. 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.

  18. 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.

  19. Metabolites profiling of Chrysanthemum pacificum Nakai parts using UPLC-PDA-MS coupled to chemometrics.

    PubMed

    Farag, Nermeen F; Farag, Mohamed A; Abdelrahman, Enas H; Azzam, Shadia M; El-Kashoury, El-Sayeda A

    2015-01-01

    Methanol-soluble constituents from the flowers, non-flowering aerial parts and roots of Chrysanthemum pacificum Nakai were analysed via high resolution UPLC-PDA-qTOF-MS followed by chemometrics. Forty-seven chromatographic peaks belonging to various metabolite classes were detected. Most metabolite classes showed qualitative and quantitative differences across parts, with luteolin conjugates being mostly enriched in flowers whereas non-flowering aerial parts contained mostly quercetin and methoxylated flavone conjugates. Root sample ranked the lowest for all flavones and dicaffeoylquinic acids. In contrast, 1,5-di-caffeoylquinic acid levels were found at high levels in flowers and aerial parts reaching 3145 and 1390 μg/g, respectively, suggesting that C. pacificum could serve as a natural resource of this well-recognised anti-hepatotoxic phenolic. Principal component analysis was further used for organs classification in an untargeted manner. This study provides the first map of secondary metabolites distribution in C. pacificum Nakai organs.

  20. Determination and discrimination of biodiesel fuels by gas chromatographic and chemometric methods

    NASA Astrophysics Data System (ADS)

    Milina, R.; Mustafa, Z.; Bojilov, D.; Dagnon, S.; Moskovkina, M.

    2016-03-01

    Pattern recognition method (PRM) was applied to gas chromatographic (GC) data for a fatty acid methyl esters (FAME) composition of commercial and laboratory synthesized biodiesel fuels from vegetable oils including sunflower, rapeseed, corn and palm oils. Two GC quantitative methods to calculate individual fames were compared: Area % and internal standard. The both methods were applied for analysis of two certified reference materials. The statistical processing of the obtained results demonstrates the accuracy and precision of the two methods and allows them to be compared. For further chemometric investigations of biodiesel fuels by their FAME-profiles any of those methods can be used. PRM results of FAME profiles of samples from different vegetable oils show a successful recognition of biodiesels according to the feedstock. The information obtained can be used for selection of feedstock to produce biodiesels with certain properties, for assessing their interchangeability, for fuel spillage and remedial actions in the environment.

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

    PubMed

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

    2008-08-01

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

  2. 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

  3. 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.

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

    PubMed

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

    2014-10-15

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

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

    PubMed

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

    2009-11-01

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

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

    PubMed Central

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

    2016-01-01

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

  7. Quick discrimination of heavy metal resistant bacterial populations using infrared spectroscopy coupled with chemometrics.

    PubMed

    Gurbanov, Rafig; Simsek Ozek, Nihal; Gozen, Ayse Gul; Severcan, Feride

    2015-10-01

    Lead and cadmium are frequently encountered heavy metals in industrially polluted areas. Many heavy metal resistant bacterial strains have a high biosorption capacity and thus are good candidates for the removal of toxic metals from the environment. However, as of yet there is no accurate method for discrimination of highly adaptive bacterial strains among the populations present in a given habitat. In this study, we aimed to find distinguishing molecular features of lead and cadmium resistant bacteria using Attenuated Total Reflectance-Fourier Transformed Infrared (ATR-FT-IR) spectroscopy and chemometric approaches. Our results demonstrated that both control and metal exposed E. coli and S. aureus strains could be successfully discriminated from each other using hierarchical cluster and principal component analysis methods. Moreover, we found that lead exposed bacterial strains could be successfully discriminated from cadmium exposed ones with a high heterogeneity value. These clear discriminations can be described by the ability of a bacterium to change its metabolism in terms of the content and structure of cellular macromolecules under heavy metal stress. In our case, cadmium and lead-induced genetic response systems in bacteria caused remarkable alterations in overall cellular metabolism. Bacteria deal with a heavy metal stress by altering nucleic acid methylations and lipid and protein synthesis. Heavy metal burden led to the development of relevant metabolic changes in proteins, lipids, and nucleic acids of the resistant bacteria described in this study. Our approach showed that infrared spectra obtained via ATR-FT-IR spectroscopy coupled with chemometric analysis can be utilized for rapid, low-cost, informative, reliable, and operator-independent discrimination of resistant bacterial populations.

  8. 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

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

    USGS Publications Warehouse

    Schwartz, Ted R.; Stalling, David L.

    1991-01-01

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

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

    PubMed

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

    2014-06-15

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

  11. 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.

  12. 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

  13. Automated optimization and construction of chemometric models based on highly variable raw chromatographic data.

    PubMed

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

    2011-07-01

    Direct chemometric interpretation of raw chromatographic data (as opposed to integrated peak tables) has been shown to be advantageous in many circumstances. However, this approach presents two significant challenges: data alignment and feature selection. In order to interpret the data, the time axes must be precisely aligned so that the signal from each analyte is recorded at the same coordinates in the data matrix for each and every analyzed sample. Several alignment approaches exist in the literature and they work well when the samples being aligned are reasonably similar. In cases where the background matrix for a series of samples to be modeled is highly variable, the performance of these approaches suffers. Considering the challenge of feature selection, when the raw data are used each signal at each time is viewed as an individual, independent variable; with the data rates of modern chromatographic systems, this generates hundreds of thousands of candidate variables, or tens of millions of candidate variables if multivariate detectors such as mass spectrometers are utilized. Consequently, an automated approach to identify and select appropriate variables for inclusion in a model is desirable. In this research we present an alignment approach that relies on a series of deuterated alkanes which act as retention anchors for an alignment signal, and couple this with an automated feature selection routine based on our novel cluster resolution metric for the construction of a chemometric model. The model system that we use to demonstrate these approaches is a series of simulated arson debris samples analyzed by passive headspace extraction, GC-MS, and interpreted using partial least squares discriminant analysis (PLS-DA).

  14. 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

  15. 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

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

    PubMed

    Shimoyama, Masahiko; Ninomiya, Toshio; Ozaki, Yukihiro

    2003-07-01

    Fourier-transform (FF) Raman spectroscopy and chemometrics were used for nondestructive analysis of ivories. The discrimination of five kinds of ivories, two subspecies of African elephant, mammoth, hippopotamus, and sperm whale, was investigated, and a calibration model for predicting their specific gravity was developed. FT-Raman spectra were measured in situ for them and chemometrics analyses were carried out for the 3050-350 cm(-1) region. The five kinds of ivories were clearly discriminated from each other on the scores plots of two or three principal components (PCs) obtained by principal component analysis (PCA). The loadings plot for PC 1 shows that the discrimination relies on the content ratio of organic collagenous protein and inorganic hydroxyapatite of ivories. The loadings plot for PC 2 shows that bands due to the CH3 and CH2 stretching modes of the protein also play a role in the discrimination. Using partial least squares regression (PLSR), we developed a calibration model that predicts the specific gravity of the ivories from the FT-Raman spectra. The correlation coefficient and root mean square error of cross validation (RMSECV) of this model were 0.980 and 0.024, respectively. PMID:12894836

  17. A chemometric approach based on a novel similarity/diversity measure for the characterisation and selection of electronic nose sensors.

    PubMed

    Ballabio, Davide; Cosio, Maria Stella; Mannino, Saverio; Todeschini, Roberto

    2006-09-25

    Electronic nose sensor signals provide a digital fingerprint of the product in analysis, which can be subsequently investigated by means of chemometrics. In this paper, the fingerprint characterisation of electronic nose data has been studied by means of a novel chemometric approach based on the partial ordering technique and the Hasse matrix. This matrix can be associated to each data sequence and the similarity between two sequences can be evaluated with the definition of a distance between the corresponding Hasse matrices. Since all the signals achieved along time are intrinsically ordered, the data provided by electronic nose can be also considered as sequential data and consequently characterized by means of the proposed approach. The similarity/diversity measure has been here applied in order to characterize the class discrimination capability of each electronic nose sensor: extra virgin olive oil samples of different geographical origin have been considered and Hasse distances have been used to select the sensors which appear more able to discriminate the olive oil origins. The distance based on the Hasse matrix has showed some useful properties and proved to be able to link each electronic nose time profile to a meaningful mathematical term (the Hasse matrix), which can be consequently studied by multivariate analysis.

  18. 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

  19. 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.

  20. 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)

  1. 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

  2. Study of the structure-activity relationship for theoretical molecular descriptors using density functional theory and chemometric methods in cannabinoid metabolites

    NASA Astrophysics Data System (ADS)

    Silva, Tânia B. E.; Pereira, Mariano A.; Malta, Valéria S.; Bento, Edson S.; San-Miguel, Miguel A.; Ziolli, Roberta L.; Martins, João B. L.; Sih, Andre; Taft, Carlton A.

    A set of 30 cannabinoid metabolites has been investigated from a combination of electronic and chemometric methods. Density functional calculations have been carried out to obtain optimized geometries, energies, and selected molecular properties. These molecular descriptors take into account steric effects, electronic properties, and chemical reactivity. The use of statistical methods including principal component analysis (PCA), hierarchical cluster analysis (HCA) and nonhierarchical cluster analysis (K-means), nearest neighbor (KNN) and artificial neural networks (ANN) has enabled to classify the compounds into psychoactive, moderately psychoactive and psychoinactive groups in good agreement with experimental evidences.

  3. 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.

  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. Chemometric expertise of the quality of groundwater sources for domestic use.

    PubMed

    Spanos, Thomas; Ene, Antoaneta; Simeonova, Pavlina

    2015-01-01

    In the present study 49 representative sites have been selected for the collection of water samples from central water supplies with different geographical locations in the region of Kavala, Northern Greece. Ten physicochemical parameters (pH, electric conductivity, nitrate, chloride, sodium, potassium, total alkalinity, total hardness, bicarbonate and calcium) were analyzed monthly, in the period from January 2010 to December 2010. Chemometric methods were used for monitoring data mining and interpretation (cluster analysis, principal components analysis and source apportioning by principal components regression). The clustering of the chemical indicators delivers two major clusters related to the water hardness and the mineral components (impacted by sea, bedrock and acidity factors). The sampling locations are separated into three major clusters corresponding to the spatial distribution of the sites - coastal, lowland and semi-mountainous. The principal components analysis reveals two latent factors responsible for the data structures, which are also an indication for the sources determining the groundwater quality of the region (conditionally named "mineral" factor and "water hardness" factor). By the apportionment approach it is shown what the contribution is of each of the identified sources to the formation of the total concentration of each one of the chemical parameters. The mean values of the studied physicochemical parameters were found to be within the limits given in the 98/83/EC Directive. The water samples are appropriate for human consumption. The results of this study provide an overview of the hydrogeological profile of water supply system for the studied area. PMID:26191984

  6. Chemometric expertise of the quality of groundwater sources for domestic use.

    PubMed

    Spanos, Thomas; Ene, Antoaneta; Simeonova, Pavlina

    2015-01-01

    In the present study 49 representative sites have been selected for the collection of water samples from central water supplies with different geographical locations in the region of Kavala, Northern Greece. Ten physicochemical parameters (pH, electric conductivity, nitrate, chloride, sodium, potassium, total alkalinity, total hardness, bicarbonate and calcium) were analyzed monthly, in the period from January 2010 to December 2010. Chemometric methods were used for monitoring data mining and interpretation (cluster analysis, principal components analysis and source apportioning by principal components regression). The clustering of the chemical indicators delivers two major clusters related to the water hardness and the mineral components (impacted by sea, bedrock and acidity factors). The sampling locations are separated into three major clusters corresponding to the spatial distribution of the sites - coastal, lowland and semi-mountainous. The principal components analysis reveals two latent factors responsible for the data structures, which are also an indication for the sources determining the groundwater quality of the region (conditionally named "mineral" factor and "water hardness" factor). By the apportionment approach it is shown what the contribution is of each of the identified sources to the formation of the total concentration of each one of the chemical parameters. The mean values of the studied physicochemical parameters were found to be within the limits given in the 98/83/EC Directive. The water samples are appropriate for human consumption. The results of this study provide an overview of the hydrogeological profile of water supply system for the studied area.

  7. Spatial assessment of water quality using chemometrics in the Pearl River Estuary, China

    NASA Astrophysics Data System (ADS)

    Wu, Meilin; Wang, Youshao; Dong, Junde; Sun, Fulin; Wang, Yutu; Hong, Yiguo

    2016-09-01

    A cruise was commissioned in the summer of 2009 to evaluate water quality in the Pearl River Estuary (PRE). Chemometrics such as Principal Component Analysis (PCA), Cluster analysis (CA) and Self-Organizing Map (SOM) were employed to identify anthropogenic and natural influences on estuary water quality. The scores of stations in the surface layer in the first principal component (PC1) were related to NH4-N, PO4-P, NO2-N, NO3-N, TP, and Chlorophyll a while salinity, turbidity, and SiO3-Si in the second principal component (PC2). Similarly, the scores of stations in the bottom layers in PC1 were related to PO4-P, NO2-N, NO3-N, and TP, while salinity, Chlorophyll a, NH4-N, and SiO3-Si in PC2. Results of the PCA identified the spatial distribution of the surface and bottom water quality, namely the Guangzhou urban reach, Middle reach, and Lower reach of the estuary. Both cluster analysis and PCA produced the similar results. Self-organizing map delineated the Guangzhou urban reach of the Pearl River that was mainly influenced by human activities. The middle and lower reaches of the PRE were mainly influenced by the waters in the South China Sea. The information extracted by PCA, CA, and SOM would be very useful to regional agencies in developing a strategy to carry out scientific plans for resource use based on marine system functions.

  8. 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

  9. 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

  10. 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

  11. Multi-elemental profiling and chemo-metric validation revealed nutritional qualities of Zingiber officinale.

    PubMed

    Pandotra, Pankaj; Viz, Bhavana; Ram, Gandhi; Gupta, Ajai Prakash; Gupta, Suphla

    2015-04-01

    Ginger rhizome is a valued food, spice and an important ingredient of traditional systems of medicine of India, China and Japan. An Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) based multi-elemental profiling was performed to assess the quantitative complement of elements, nutritional quality and toxicity of 46 ginger germplasms, collected from the north western Himalayan India. The abundance of eighteen elements quantified in the acid digested rhizomes was observed to be K>Mg>Fe>Ca>Na>Mn>Zn>Ba>Cu>Cr>Ni>Pb>Co>Se>As>Be>Cd. Toxic element, Hg was not detected in any of the investigated samples. Chemometric analyses showed positive correlation among most of the elements. No negative correlation was observed in any of the metals under investigation. UPGMA based clustering analysis of the quantitative data grouped all the 46 samples into three major clusters, displaying 88% similarity in their metal composition, while eighteen metals investigated grouped into two major clusters. Quantitatively, all the elements analyzed were below the permissible limits laid down by World Health Organization. The results were further validated by cluster analysis (CA) and principal component analysis (PCA) to understand the ionome of the ginger rhizome. The study suggested raw ginger to be a good source of beneficial elements/minerals like Mg, Ca, Mn, Fe, Cu and Zn and will provide platform for understanding the functional and physiological status of ginger rhizome.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Comparisons of large (Vaccinium macrocarpon Ait.) and small (Vaccinium oxycoccos L., Vaccinium vitis-idaea L.) cranberry in British Columbia by phytochemical determination, antioxidant potential, and metabolomic profiling with chemometric analysis.

    PubMed

    Brown, Paula N; Turi, Christina E; Shipley, Paul R; Murch, Susan J

    2012-04-01

    There is a long history of use and modern commercial importance of large and small cranberries in North America. The central objective of the current research was to characterize and compare the chemical composition of 2 west coast small cranberry species traditionally used (Vaccinium oxycoccos L. and Vaccinium vitis-idaea L.) with the commercially cultivated large cranberry (Vaccinium macrocarpon Ait.) indigenous to the east coast of North America. V. oxycoccos and V. macrocarpon contained the 5 major anthocyanins known in cranberry; however, the ratio of glycosylated peonidins to cyanidins varied, and V. vitis-idaea did not contain measurable amounts of glycosylated peonidins. Extracts of all three berries were found to contain serotonin, melatonin, and ascorbic acid. Antioxidant activity was not found to correlate with indolamine levels while anthocyanin content showed a negative correlation, and vitamin C content positively correlated. From the metabolomics profiles, 4624 compounds were found conserved across V. macrocarpon, V. oxycoccoS, and V. vitis-idaea with a total of approximately 8000-10 000 phytochemicals detected in each species. From significance analysis, it was found that 2 compounds in V. macrocarpoN, 3 in V. oxycoccos, and 5 in V. vitis-idaea were key to the characterization and differentiation of these cranberry metabolomes. Through multivariate modeling, differentiation of the species was observed, and univariate statistical analysis was employed to provide a quality assessment of the models developed for the metabolomics data.

  17. A novel strategy for the determination of enantiomeric compositions of chiral compounds by chemometric analysis of the UV-vis spectra of bovine serum albumin receptor-ligand mixtures

    NASA Astrophysics Data System (ADS)

    Wang, Yunxia; Zhang, Fang; Liang, Jing; Li, Hua; Kong, Jilie

    2007-10-01

    In this work, a novel strategy was constructed to determine the enantiomeric composition of chiral substances discriminated by bovine serum albumin (BSA) based on the UV-vis spectra of the receptor-ligand mixtures coupled with partial least squares (PLS-1) analysis. Taking tryptophan (Trp) enantiomer as an example, when 20 μM BSA was used, the enantiomeric composition was accurately determined with concentration of only 100 nM and the corresponding enantiomeric excess as high as 98% (or -98%), which is relatively more sensitive than in literature. Furthermore, the BSA-based approach was also used to predict the enantiomeric composition of other chiral compounds, such as phenylalanine (Phe), tyrosine (Tyr), alanine (Ala), cysteine (Cys), DOPA and propranolol (Prop). The results fully demonstrate that BSA is effective in determination of enantiomeric composition of some chiral compounds.

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

    PubMed

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

    2015-10-21

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

  19. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

    Two advanced, accurate and precise chemometric methods are developed for the simultaneous determination of amlodipine besylate (AML) and atorvastatin calcium (ATV) in the presence of their acidic degradation products in tablet dosage forms. The first method was Partial Least Squares (PLS-1) and the second was Artificial Neural Networks (ANN). PLS was compared to ANN models with and without variable selection procedure (genetic algorithm (GA)). For proper analysis, a 5-factor 5-level experimental design was established resulting in 25 mixtures containing different ratios of the interfering species. Fifteen mixtures were used as calibration set and the other ten mixtures were used as validation set to validate the prediction ability of the suggested models. The proposed methods were successfully applied to the analysis of pharmaceutical tablets containing AML and ATV. The methods indicated the ability of the mentioned models to solve the highly overlapped spectra of the quinary mixture, yet using inexpensive and easy to handle instruments like the UV-VIS spectrophotometer.

  1. Discrimination and identification of RDX/PETN explosives by chemometrics applied to terahertz time-domain spectral imaging

    NASA Astrophysics Data System (ADS)

    Bou-Sleiman, J.; Perraud, J.-B.; Bousquet, B.; Guillet, J.-P.; Palka, N.; Mounaix, P.

    2015-10-01

    Detection of explosives has always been a priority for homeland security. Jointly, terahertz spectroscopy and imaging are emerging and promising candidates as contactless and safe systems. In this work, we treated data resulting from hyperspectral imaging obtained by THz-time domain spectroscopy, with chemometric tools. We found efficient identification and sorting of targeted explosives in the case of pure and mixture samples. In this aim, we applied to images Principal Component Analysis (PCA) to discriminate between RDX, PETN and mixtures of the two materials, using the absorbance as the key-parameter. Then we applied Partial Least Squares-Discriminant Analysis (PLS-DA) to each pixel of the hyperspectral images to sort the explosives into different classes. The results clearly show successful identification and categorization of the explosives under study.

  2. 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

  3. Laser induced breakdown spectroscopy and characterization of environmental matrices utilizing multivariate chemometrics

    NASA Astrophysics Data System (ADS)

    Mukhono, P. M.; Angeyo, K. H.; Dehayem-Kamadjeu, A.; Kaduki, K. A.

    2013-09-01

    We exploited multivariate chemometric methods to reduce the spectral complexity and to retrieve trace heavy metal analyte concentration signatures directly from the LIBS spectra as well as, to extract their latent characteristics in two important environmental samples i.e. soils and rocks from a geothermal field lying in a high background radiation area (HBRA). As, Cr, Cu, Pb and Ti were modeled for direct trace (quantitative) analysis using partial least squares (PLS) and artificial neural networks (ANNs). PLS performed better in soils than in rocks; the use of ANN improved the accuracies in rocks because ANNs are more robust than PLS at modeling spectral non-linearities and correcting matrix effects. The predicted trace metal profiles together with atomic and molecular signatures acquired using single ablation in the 200-545 nm spectral range were utilized to successfully classify and identify the soils and rocks with regard to whether they were derived from (i) a high background radiation area (HBRA)-geothermal, (ii) HBRA-non-geothermal or (iii) normal background radiation area (NBRA)-geothermal field using principal components analysis (PCA) and soft independent modeling of class analogy (SIMCA).

  4. Component development and integration issues for bio/chemometric appliations of VCSEL and MOEMS arrays

    NASA Astrophysics Data System (ADS)

    Castracane, James; Baks, Christian; Oktyabrsky, Serge; Xu, Bai; Yao, Yahong

    2001-05-01

    The rapid advancement of electro-optical components and micro-mechanical devices has led to increased functionality in decreasing package sizes. In particular, the development of massively parallel arrays of optical sources such as Vertical Cavity Surface Emitting Lasers (VCSEL) and innovative micro-opto-electro-mechanical systems (MOEMS) has opened the door for new possibilities. Recently, there has been a drive toward integration of the sensing, processing and actuation functions in a single package for fully integrated performance. One area which can benefit from this research is real time, spectroscopic analysis of biological and chemical samples. Numerous situations require a compact, self-contained bio/chemometric system for rapid, low cost spectral analysis or monitoring. To fully realize this potential, further component development and integration issues must be addressed. This paper will present the status of the VCSEL and MOEMS programs at the Institute and initial integration activities. The VCSELs are based on multiple quantum well Ga/As/InGaAs and GaAs/AlGaAs architectures with monolithic, epitaxially grown distributed Bragg reflectors. The VCSEL arrays have 6-15 micron apertures, 100 micron pitch and a mA threshold current. In parallel, the MOEMS program is focused on the development of active, reconfigurable diffractive and reflective arrays whose surface topology can be changed in real time. These MOEMS arrays can be sued to redirect light for flexible interrogation of samples. The combination of these two technologies offers a unique opportunity for fully functional systems on a chip.

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

    PubMed

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

    2003-03-01

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

  6. Influence of minerals on the taste of bottled and tap water: a chemometric approach.

    PubMed

    Platikanov, Stefan; Garcia, Veronica; Fonseca, Ignacio; Rullán, Elena; Devesa, Ricard; Tauler, Roma

    2013-02-01

    Chemometric analysis was performed on two sets of sensory data obtained from two separate studies. Twenty commercially-available bottled mineral water samples (from the first study) and twenty-five drinking tap and bottled water samples (from the second study) were blind tasted by trained panelists. The panelists expressed their overall liking of the water samples by rating from 0 (worst flavor) to 10 (best flavor). The mean overall score was compared to the physicochemical properties of the samples. Thirteen different physicochemical parameters were considered in both studies and, additionally, residual chlorine levels were assessed in the second study. Principal component analysis performed on the physicochemical parameters and the panelists' mean scores generated models that explain most of the total data variance. Moreover, partial least squares regression of the panelists' sensory evaluations of the physicochemical data helped elucidate the main features underlying the panelists' ratings. The preferred bottled and tap water samples were associated with moderate (relatively to the parameters mean values) contents of total dissolved solids and with relatively high concentrations of HCO₃⁻, SO₄²⁻, Ca²⁺ and Mg²⁺ as well as with relatively high pH values. High concentrations of Na⁺, K⁺ and Cl⁻ were scored low by many of the panelists, while residual chlorine did not affect the ratings, but did enable the panel to distinguish between bottled mineral water and tap water samples.

  7. Investigation of the chemical composition-antibacterial activity relationship of essential oils by chemometric methods.

    PubMed

    Miladinović, Dragoljub L; Ilić, Budimir S; Mihajilov-Krstev, Tatjana M; Nikolić, Nikola D; Miladinović, Ljiljana C; Cvetković, Olga G

    2012-05-01

    The antibacterial effects of Thymus vulgaris (Lamiaceae), Lavandula angustifolia (Lamiaceae), and Calamintha nepeta (Lamiaceae) Savi subsp. nepeta var. subisodonda (Borb.) Hayek essential oils on five different bacteria were estimated. Laboratory control strain and clinical isolates from different pathogenic media were researched by broth microdilution method, with an emphasis on a chemical composition-antibacterial activity relationship. The main constituents of thyme oil were thymol (59.95%) and p-cymene (18.34%). Linalool acetate (38.23%) and β-linalool (35.01%) were main compounds in lavender oil. C. nepeta essential oil was characterized by a high percentage of piperitone oxide (59.07%) and limonene (9.05%). Essential oils have been found to have antimicrobial activity against all tested microorganisms. Classification and comparison of essential oils on the basis of their chemical composition and antibacterial activity were made by utilization of appropriate chemometric methods. The chemical principal component analysis (PCA) and hierachical cluster analysis (HCA) separated essential oils into two groups and two sub-groups. Thyme essential oil forms separate chemical HCA group and exhibits highest antibacterial activity, similar to tetracycline. Essential oils of lavender and C. nepeta in the same chemical HCA group were classified in different groups, within antibacterial PCA and HCA analyses. Lavender oil exhibits higher antibacterial ability in comparison with C. nepeta essential oil, probably based on the concept of synergistic activity of essential oil components. PMID:22389175

  8. Quality assessment of crude and processed ginger by high-performance liquid chromatography with diode array detection and mass spectrometry combined with chemometrics.

    PubMed

    Deng, Xianmei; Yu, Jiangyong; Zhao, Ming; Zhao, Bin; Xue, Xingyang; Che, ChunTao; Meng, Jiang; Wang, Shumei

    2015-09-01

    A sensitive, simple, and validated high-performance liquid chromatography with diode array detection and mass spectrometry detection method was developed for three ginger-based traditional Chinese herbal drugs, Zingiberis Rhizoma, Zingiberis Rhizome Preparatum, and Zingiberis Rhizome Carbonisata. Chemometrics methods, such as principal component analysis, hierarchical cluster analysis, and analysis of variance, were also employed in the data analysis. The results clearly revealed significant differences among Zingiberis Rhizoma, Zingiberis Rhizome Preparatum, and Zingiberis Rhizome Carbonisata, indicating variations in their chemical compositions during the processing, which may elucidate the relationship of the thermal treatment with the change of the constituents and interpret their different clinical uses. Furthermore, the sample consistency of Zingiberis Rhizoma, Zingiberis Rhizome Preparatum, and Zingiberis Rhizome Carbonisata can also be visualized by high-performance liquid chromatography with diode array detection and mass spectrometry analysis followed by principal component analysis/hierarchical cluster analysis. The comprehensive strategy of liquid chromatography with mass spectrometry analysis coupled with chemometrics should be useful in quality assurance for ginger-based herbal drugs and other herbal medicines. PMID:26174663

  9. Quality assessment of crude and processed ginger by high-performance liquid chromatography with diode array detection and mass spectrometry combined with chemometrics.

    PubMed

    Deng, Xianmei; Yu, Jiangyong; Zhao, Ming; Zhao, Bin; Xue, Xingyang; Che, ChunTao; Meng, Jiang; Wang, Shumei

    2015-09-01

    A sensitive, simple, and validated high-performance liquid chromatography with diode array detection and mass spectrometry detection method was developed for three ginger-based traditional Chinese herbal drugs, Zingiberis Rhizoma, Zingiberis Rhizome Preparatum, and Zingiberis Rhizome Carbonisata. Chemometrics methods, such as principal component analysis, hierarchical cluster analysis, and analysis of variance, were also employed in the data analysis. The results clearly revealed significant differences among Zingiberis Rhizoma, Zingiberis Rhizome Preparatum, and Zingiberis Rhizome Carbonisata, indicating variations in their chemical compositions during the processing, which may elucidate the relationship of the thermal treatment with the change of the constituents and interpret their different clinical uses. Furthermore, the sample consistency of Zingiberis Rhizoma, Zingiberis Rhizome Preparatum, and Zingiberis Rhizome Carbonisata can also be visualized by high-performance liquid chromatography with diode array detection and mass spectrometry analysis followed by principal component analysis/hierarchical cluster analysis. The comprehensive strategy of liquid chromatography with mass spectrometry analysis coupled with chemometrics should be useful in quality assurance for ginger-based herbal drugs and other herbal medicines.

  10. Prediction of tablet hardness based on near infrared spectra of raw mixed powders by chemometrics.

    PubMed

    Otsuka, Makoto; Yamane, Ikuro

    2006-07-01

    The purpose of this research is to elucidate the effect of lubricant mixing on tablet hardness by near-infrared (NIR) chemometrics as a basic study of process analytical technology. Formulation cellulose (F-C) consisted of sulpyrine (SP), microcrystalline cellulose (MC), and magnesium stearate (MgSt). Formulation lactose/starch (F-L) consisted of SP bulk drug powder, spray-dried lactose (SL), corn starch (CS), and MgSt. First, F-L and F-C without MgSt were mixed in a twin-shell mixer for 60 min. MgSt was added to the mixed powder, and was mixed for various mixing times, after which the mixed powders were compressed by 8-mm diameter punch and die. NIR spectra of raw mixed powders of F-L and F-C were taken using a reflection type of Fourier transform NIR spectra spectrometer, and chemometric analysis was performed using principal component regression (PCR). The tablet hardnesses of F-L and F-C decreased with increasing mixing time. All NIR spectra of the mixed powders of F-L and F-C fluctuated depending on mixing time. In order to predict tablet hardness before tablet compression, NIR spectra of F-L and F-C mixed powders were analyzed and evaluated for hardness by PCR. The minimum standard error of cross-validation values could be realized by using five- and six-principal component models, respectively. In the cases of F-L and F-C, the relationships between the actual and predicted tablet hardnesses showed straight lines, respectively. In the regression vectors of F-L and FC, the peaks related to hydrogen groups of SP, CS, and MC appeared as positive peaks. In contrast, the peaks related to hydrocarbon due to MgSt appeared as negative peaks in the regression vectors. The calibration models to evaluate the tablet hardness were obtained based on NIR spectra of raw mixed powders by PCR. This approach to predicting tablet hardness prior to compression could be used as a routine test to indicate the quality of the final product without spending time and energy to produce

  11. Characterisation and authentication of A. senegal and A. seyal exudates by infrared spectroscopy and chemometrics.

    PubMed

    Vanloot, Pierre; Dupuy, Nathalie; Guiliano, Michel; Artaud, Jacques

    2012-12-15

    The authentication of Acacia gums 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. Commercial Acacia senegal and Acacia seyal gums present characteristic MIR spectra. Principal Component Analysis of the infrared spectra of gum exudates of trees allow to distinguish Acacia gums from another gum exudates (Combretum, Ghatti, Karaya, Tragacanth). Moreover, gums of A. senegal and A. seyal separate them and from other Acacia species (Acacia dealbata, Acacia karoo, Acacia nilotica, Acacia sieberiana). Chemometric treatments of A. senegal and A. seyal MIR spectra were assessed for the quantification of moisture content in Acacia gums, for the classification into the two species and for the adulteration detection and quantification. Results were quite satisfactory, the moisture content was estimated at 3.1%, adulteration was detected at 3.4% and quantified at 5.6%. The discrimination of the two species is done without any ambiguity. PMID:22980842

  12. Classification of frankfurters by FT-Raman spectroscopy and chemometric methods.

    PubMed

    Campos, Náira da Silva; Oliveira, Kamila Sá; Almeida, Mariana Ramos; Stephani, Rodrigo; de Oliveira, Luiz Fernando Cappa

    2014-11-18

    Frankfurters are widely consumed all over the world, and the production requires a wide range of meat and non-meat ingredients. Due to these characteristics, frankfurters are products that can be easily adulterated with lower value meats, and the presence of undeclared species. Adulterations are often still difficult to detect, due the fact that the adulterant components are usually very similar to the authentic product. In this work, FT-Raman spectroscopy was employed as a rapid technique for assessing the quality of frankfurters. Based on information provided by the Raman spectra, a multivariate classification model was developed to identify the frankfurter type. The aim was to study three types of frankfurters (chicken, turkey and mixed meat) according to their Raman spectra, based on the fatty vibrational bands. Classification model was built using partial least square discriminant analysis (PLS-DA) and the performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency and Matthews's correlation coefficient. The PLS-DA models give sensitivity and specificity values on the test set in the ranges of 88%-100%, showing good performance of the classification models. The work shows the Raman spectroscopy with chemometric tools can be used as an analytical tool in quality control of frankfurters.

  13. Chemometric evaluation of physicochemical properties of carbonated-apatitic preparations by Fourier transform infrared spectroscopy.

    PubMed

    Otsuka, Makoto; Papangkorn, Kongnara; Baig, Arif A; Higuchi, William I

    2012-08-01

    The purpose of this study was to develop a simple and quick method of evaluating the physicochemical properties of carbonated apatite preparations (CAP) as an index of the bioaffinity of implantable materials based on Fourier-transformed-infrared (IR) spectra by chemometrics. The wet-synthesized CAPs contained various levels of carbonate content (CO(3)), and were analyzed microstrain parameter (MS), crystallite size parameter (CP), specific surface area (Sw), CO(3), and solubility parameter (pK(HAP)) using by X-ray powder diffraction, nitrogen gas adsorption, IR, and UV absorption. The IR spectral results of CAPs suggested that the peak intensities of CAP reflected the physicochemical properties of the samples. The IR data sets were calculated to obtain calibration models evaluating the physicochemical properties of CAPs by a partial least squares regression analysis (PLS). As validation of the calibration model, physicochemical properties of CAP could be evaluated based on validation IR data sets of independent samples, and those values had sufficient accuracy. The regression vector of each calibration model suggested that the physicochemical properties of CAP, such as CO(3), Sw, MS, CP, and pK(HAP), were affected by phosphate, hydroxyl, and carbonate groups.

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

    PubMed Central

    Jiang, Yuying; Ge, Hongyi; Lian, Feiyu; Zhang, Yuan; Xia, Shanhong

    2016-01-01

    In this paper, we propose a feasible tool that uses a terahertz (THz) imaging system for identifying wheat grains at different stages of germination. The THz spectra of the main changed components of wheat grains, maltose and starch, which were obtained by THz time spectroscopy, were distinctly different. Used for original data compression and feature extraction, principal component analysis (PCA) revealed the changes that occurred in the inner chemical structure during germination. Two thresholds, one indicating the start of the release of α-amylase and the second when it reaches the steady state, were obtained through the first five score images. Thus, the first five PCs were input for the partial least-squares regression (PLSR), least-squares support vector machine (LS-SVM), and back-propagation neural network (BPNN) models, which were used to classify seven different germination times between 0 and 48 h, with a prediction accuracy of 92.85%, 93.57%, and 90.71%, respectively. The experimental results indicated that the combination of THz imaging technology and chemometrics could be a new effective way to discriminate wheat grains at the early germination stage of approximately 6 h. PMID:26892180

  15. Optimization of preparation of chitosan-coated iron oxide nanoparticles for biomedical applications by chemometrics approaches

    NASA Astrophysics Data System (ADS)

    Honary, Soheila; Ebrahimi, Pouneh; Rad, Hossein Asgari; Asgari, Mahsa

    2013-08-01

    Functionalized magnetic nanoparticles are used in several biomedical applications, such as drug delivery, magnetic cell separation, and magnetic resonance imaging. Size and surface properties of iron oxide nanoparticles are the two important factors which could dramatically affect the nanoparticle efficiency as well as their stability. In this study, the chemometrics approach was applied to optimize the coating process of iron oxide nanoparticles. To optimize the size of nanoparticles, the effect of two experimental parameters on size was investigated by means of multivariate analysis. The factors considered were chitosan molecular weight and chitosan-to-tripolyphosphate concentration ratio. The experiments were performed according to face-centered cube central composite response surface design. A second-order regression model was obtained which characterized by both descriptive and predictive abilities. The method was optimized with respect to the percent of Z average diameter's increasing after coating as response. It can be concluded that experimental design provides a suitable means of optimizing and testing the robustness of iron oxide nanoparticle coating method.

  16. Characterisation and authentication of A. senegal and A. seyal exudates by infrared spectroscopy and chemometrics.

    PubMed

    Vanloot, Pierre; Dupuy, Nathalie; Guiliano, Michel; Artaud, Jacques

    2012-12-15

    The authentication of Acacia gums 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. Commercial Acacia senegal and Acacia seyal gums present characteristic MIR spectra. Principal Component Analysis of the infrared spectra of gum exudates of trees allow to distinguish Acacia gums from another gum exudates (Combretum, Ghatti, Karaya, Tragacanth). Moreover, gums of A. senegal and A. seyal separate them and from other Acacia species (Acacia dealbata, Acacia karoo, Acacia nilotica, Acacia sieberiana). Chemometric treatments of A. senegal and A. seyal MIR spectra were assessed for the quantification of moisture content in Acacia gums, for the classification into the two species and for the adulteration detection and quantification. Results were quite satisfactory, the moisture content was estimated at 3.1%, adulteration was detected at 3.4% and quantified at 5.6%. The discrimination of the two species is done without any ambiguity.

  17. Application of chemometric methods to differential scanning calorimeter (DSC) to estimate nimodipine polymorphs from cosolvent system.

    PubMed

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

    2015-06-01

    The focus of this study was to evaluate the applicability of chemometrics to differential scanning calorimetry data (DSC) to evaluate nimodipine polymorphs. Multivariate calibration models were built using DSC data from known mixtures of the nimodipine modification. The linear baseline correction treatment of data was used to reduce dispersion in thermograms. Principal component analysis of the treated and untreated data explained 96% and 89% of the data variability, respectively. Score and loading plots correlated variability between samples with change in proportion of nimodipine modifications. The R(2) for principal component regression (PCR) and partial lease square regression (PLS) were found to be 0.91 and 0.92. The root mean square of standard error of the treated samples for calibration and validation in PCR and PLS was found to be lower than the untreated sample. These models were applied to samples recrystallized from a cosolvent system, which indicated different proportion of modifications in the mixtures than those obtained by placing samples under different storage conditions. The model was able to predict the nimodipine modifications with known margin of error. Therefore, these models can be used as a quality control tool to expediently determine the nimodipine modification in an unknown mixture. PMID:24856323

  18. A chemometric method to identify enzymatic reactions leading to the transition from glycolytic oscillations to waves

    NASA Astrophysics Data System (ADS)

    Zimányi, László; Khoroshyy, Petro; Mair, Thomas

    2010-06-01

    In the present work we demonstrate that FTIR-spectroscopy is a powerful tool for the time resolved and noninvasive measurement of multi-substrate/product interactions in complex metabolic networks as exemplified by the oscillating glycolysis in a yeast extract. Based on a spectral library constructed from the pure glycolytic intermediates, chemometric analysis of the complex spectra allowed us the identification of many of these intermediates. Singular value decomposition and multiple level wavelet decomposition were used to separate drifting substances from oscillating ones. This enabled us to identify slow and fast variables of glycolytic oscillations. Most importantly, we can attribute a qualitative change in the positive feedback regulation of the autocatalytic reaction to the transition from homogeneous oscillations to travelling waves. During the oscillatory phase the enzyme phosphofructokinase is mainly activated by its own product ADP, whereas the transition to waves is accompanied with a shift of the positive feedback from ADP to AMP. This indicates that the overall energetic state of the yeast extract determines the transition between spatially homogeneous oscillations and travelling waves.

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

    NASA Astrophysics Data System (ADS)

    Jiang, Yuying; Ge, Hongyi; Lian, Feiyu; Zhang, Yuan; Xia, Shanhong

    2016-02-01

    In this paper, we propose a feasible tool that uses a terahertz (THz) imaging system for identifying wheat grains at different stages of germination. The THz spectra of the main changed components of wheat grains, maltose and starch, which were obtained by THz time spectroscopy, were distinctly different. Used for original data compression and feature extraction, principal component analysis (PCA) revealed the changes that occurred in the inner chemical structure during germination. Two thresholds, one indicating the start of the release of α-amylase and the second when it reaches the steady state, were obtained through the first five score images. Thus, the first five PCs were input for the partial least-squares regression (PLSR), least-squares support vector machine (LS-SVM), and back-propagation neural network (BPNN) models, which were used to classify seven different germination times between 0 and 48 h, with a prediction accuracy of 92.85%, 93.57%, and 90.71%, respectively. The experimental results indicated that the combination of THz imaging technology and chemometrics could be a new effective way to discriminate wheat grains at the early germination stage of approximately 6 h.

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

    PubMed

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

    2016-08-15

    Authentication of extra virgin olive oil (EVOO) is an important topic for olive oil industry. The fraudulent practices in this sector are a major problem affecting both producers and consumers. This study analyzes the capability of FT-Raman combined with chemometric treatments of prediction of the fatty acid contents (quantitative information), using gas chromatography as the reference technique, and classification of diverse EVOOs as a function of the harvest year, olive variety, geographical origin and Andalusian PDO (qualitative information). The optimal number of PLS components that summarizes the spectral information was introduced progressively. For the estimation of the fatty acid composition, the lowest error (both in fitting and prediction) corresponded to MUFA, followed by SAFA and PUFA though such errors were close to zero in all cases. As regards the qualitative variables, discriminant analysis allowed a correct classification of 94.3%, 84.0%, 89.0% and 86.6% of samples for harvest year, olive variety, geographical origin and PDO, respectively. PMID:27260451

  1. Application of chemometric methods to differential scanning calorimeter (DSC) to estimate nimodipine polymorphs from cosolvent system.

    PubMed

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

    2015-06-01

    The focus of this study was to evaluate the applicability of chemometrics to differential scanning calorimetry data (DSC) to evaluate nimodipine polymorphs. Multivariate calibration models were built using DSC data from known mixtures of the nimodipine modification. The linear baseline correction treatment of data was used to reduce dispersion in thermograms. Principal component analysis of the treated and untreated data explained 96% and 89% of the data variability, respectively. Score and loading plots correlated variability between samples with change in proportion of nimodipine modifications. The R(2) for principal component regression (PCR) and partial lease square regression (PLS) were found to be 0.91 and 0.92. The root mean square of standard error of the treated samples for calibration and validation in PCR and PLS was found to be lower than the untreated sample. These models were applied to samples recrystallized from a cosolvent system, which indicated different proportion of modifications in the mixtures than those obtained by placing samples under different storage conditions. The model was able to predict the nimodipine modifications with known margin of error. Therefore, these models can be used as a quality control tool to expediently determine the nimodipine modification in an unknown mixture.

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

    PubMed

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

    2016-08-15

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

  3. Chemometric analyses for the characterization of raw and processed seeds of Descurainia sophia (L.) based on HPLC fingerprints.

    PubMed

    Zhou, Xidan; Tang, Liying; Wu, Hongwei; Zhou, Guohong; Wang, Ting; Kou, Zhenzhen; Li, Shunxin; Wang, Zhuju

    2015-01-01

    The seeds of Descurainia sophia (L.) (short for DSS below), with a long history of medicinal utilization in China, have attracted the attention of many Chinese medicine practitioners for the potent efficacy. In the present study, the raw and processed DSS were differentiated by several chemometrics methods based on HPLC fingerprints. Moreover, peaks which were mainly responsible for the differentiation between raw and roasted DSS were found. Therefore, the method of the chromatographic fingerprints combined with multivariate statistical analysis was effective and reasonable in orientating chemical constituents which were mainly responsible for the differentiation between raw and roasted materials, thus shedding light on illustrating the processing mechanism. What's more, this method can also be applied in the identification of authenticity. PMID:25828506

  4. Chemometric study on the electrochemical incineration of nitrilotriacetic acid using platinum and boron-doped diamond anode.

    PubMed

    Zhang, Chunyong; He, Zhenzhu; Wu, Jingyu; Fu, Degang

    2015-07-01

    This study investigated the electrochemical incineration of nitrilotriacetic acid (NTA) at boron-doped diamond (BDD) and platinum (Pt) anodes. Trials were performed in the presence of sulfate electrolyte media under recirculation mode. The parameters that influence the degradation efficiency were investigated, including applied current density, flow rate, supporting electrolyte concentration and reaction time. To reduce the number of experiments, the system had been managed under chemometric technique named Doehlert matrix. As a consequence, the mineralization of NTA demonstrated similar behavior upon operating parameters on these two anodes. Further kinetic study indicated that the degradations followed pseudo-first-order reactions for both BDD and Pt anodes, and the reaction rate constant of the former was found to be higher than that of the latter. Such difference could be interpreted by results from fractal analysis. In addition, a reaction sequence for NTA mineralization considering all the detected intermediates was also proposed.

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

    PubMed

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

    2012-11-01

    A bacterial consortium-AVS, consisting of Pseudomonas desmolyticum NCIM 2112, Kocuria rosea MTCC 1532 and Micrococcus glutamicus NCIM 2168 was formulated chemometrically, using the mixture design matrix based on the design of experiments methodology. The formulated consortium-AVS decolorized acid blue 15 and methylene blue with a higher average decolorization rate, which is more rapid than that of the pure cultures. The UV-vis spectrophotometric, Fourier transform infra red spectrophotometric and high performance liquid chromatographic analysis confirm that the decolorization was due to biodegradation by oxido-reductive enzymes, produced by the consortium-AVS. The toxicological assessment of plant growth parameters and the chlorophyll pigment concentrations of Phaseolus mungo and Triticum aestivum seedlings revealed the reduced toxic nature of the biodegraded products. PMID:22940340

  6. Combination of 1H NMR and chemometrics to discriminate manuka honey from other floral honey types from Oceania.

    PubMed

    Spiteri, Marc; Rogers, Karyne M; Jamin, Eric; Thomas, Freddy; Guyader, Sophie; Lees, Michèle; Rutledge, Douglas N

    2017-02-15

    Manuka honey is a product produced essentially in New Zealand, and has been widely recognised for its antibacterial properties and specific taste. In this study, 264 honeys from New Zealand and Australia were analysed using proton NMR spectroscopy coupled with chemometrics. Known manuka markers, methylglyoxal and dihydroxyacetone, have been characterised and quantified, together with a new NMR marker, identified as being leptosperin. Manuka honey profiling using 1H NMR is shown to be a possible alternative to chromatography with the added advantage that it can measure methylglyoxal (MGO), dihydroxyacetone (DHA) and leptosperin simultaneously. By combining the information from these three markers, we established a model to estimate the proportion of manuka in a given honey. Markers of other botanical origins were also identified, which makes 1H NMR a convenient and efficient tool, complementary to pollen analysis, to control the botanical origin of Oceania honeys.

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

    PubMed

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

    2016-04-01

    Body fluids are evidence of great forensic interest due to the DNA extracted from them, which allows genetic identification of people. This study focuses on the discrimination among semen, vaginal fluid, and urine stains (main fluids in sexual crimes) placed on different colored cotton fabrics by external reflection Fourier transform infrared spectroscopy (FT-IR) combined with chemometrics. Semen-vaginal fluid mixtures and potential false positive substances commonly found in daily life such as soaps, milk, juices, and lotions were also studied. Results demonstrated that the IR spectral signature obtained for each body fluid allowed its identification and the correct classification of unknown stains by means of principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA). Interestingly, results proved that these IR spectra did not show any bands due to the color of the fabric and no substance of those present in daily life which were analyzed, provided a false positive. PMID:26896150

  8. Combination of 1H NMR and chemometrics to discriminate manuka honey from other floral honey types from Oceania.

    PubMed

    Spiteri, Marc; Rogers, Karyne M; Jamin, Eric; Thomas, Freddy; Guyader, Sophie; Lees, Michèle; Rutledge, Douglas N

    2017-02-15

    Manuka honey is a product produced essentially in New Zealand, and has been widely recognised for its antibacterial properties and specific taste. In this study, 264 honeys from New Zealand and Australia were analysed using proton NMR spectroscopy coupled with chemometrics. Known manuka markers, methylglyoxal and dihydroxyacetone, have been characterised and quantified, together with a new NMR marker, identified as being leptosperin. Manuka honey profiling using 1H NMR is shown to be a possible alternative to chromatography with the added advantage that it can measure methylglyoxal (MGO), dihydroxyacetone (DHA) and leptosperin simultaneously. By combining the information from these three markers, we established a model to estimate the proportion of manuka in a given honey. Markers of other botanical origins were also identified, which makes 1H NMR a convenient and efficient tool, complementary to pollen analysis, to control the botanical origin of Oceania honeys. PMID:27664696

  9. Chemometric study on the electrochemical incineration of nitrilotriacetic acid using platinum and boron-doped diamond anode.

    PubMed

    Zhang, Chunyong; He, Zhenzhu; Wu, Jingyu; Fu, Degang

    2015-07-01

    This study investigated the electrochemical incineration of nitrilotriacetic acid (NTA) at boron-doped diamond (BDD) and platinum (Pt) anodes. Trials were performed in the presence of sulfate electrolyte media under recirculation mode. The parameters that influence the degradation efficiency were investigated, including applied current density, flow rate, supporting electrolyte concentration and reaction time. To reduce the number of experiments, the system had been managed under chemometric technique named Doehlert matrix. As a consequence, the mineralization of NTA demonstrated similar behavior upon operating parameters on these two anodes. Further kinetic study indicated that the degradations followed pseudo-first-order reactions for both BDD and Pt anodes, and the reaction rate constant of the former was found to be higher than that of the latter. Such difference could be interpreted by results from fractal analysis. In addition, a reaction sequence for NTA mineralization considering all the detected intermediates was also proposed. PMID:25747300

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

    PubMed

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

    2012-11-01

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

  11. Chemometric optimization of a low-temperature plasma source design for ambient desorption/ionization mass spectrometry

    NASA Astrophysics Data System (ADS)

    Albert, Anastasia; Engelhard, Carsten

    2015-03-01

    Low-temperature plasmas (LTPs) are attractive sources for atomic and molecular mass spectrometry (MS). In the past, the LTP probe, which was first described by Harper et al., was used successfully for direct molecular mass spectrometric analysis with minimal sample pretreatment in a variety of applications. Unfortunately, the desorption/ionization source itself is commercially not available and custom-built LTP set-ups with varying geometry and operational configurations were utilized in the past. In the present study, a rapid chemometrics approach based on systematic experiments and multivariate data analysis was used to optimize the LTP probe geometry and positioning relative to the atmospheric-pressure inlet of a mass spectrometer. Several parameters were studied including the probe geometry, electrode configuration, quartz tube dimensions, probe positioning and operating conditions. It was found that the plasma-to-MS-inlet distance, the plasma-to-sample-plate distance, and the angle between the latter are very important. Additional effects on the analytical performance were found for the outer electrode width, the positioning of the electrodes, the inner diameter of the quartz tube, the quartz wall thickness, and the gas flow. All experiments were performed using additional heating of the sample to enhance thermal desorption and maximize the signal (T = 150 °C). After software-assisted optimization, attractive detection limits were achieved (e.g., 1.8 × 10- 7 mol/L for 4-acetamidothiophenol). Moreover, relative standard deviation (RSD) improved from values of up to 30% before optimization to < 15% RSD after the procedure was completed. This chemometrics approach for method optimization is not limited to LTP-MS and considered to be attractive for other plasma-based instrumentation as well.

  12. Chemometrics applications in biotech processes: assessing process comparability.

    PubMed

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

    2012-01-01

    A typical biotech process starts with the vial of the cell bank, ends with the final product and has anywhere from 15 to 30 unit operations in series. The total number of process variables (input and output parameters) and other variables (raw materials) can add up to several hundred variables. As the manufacturing process is widely accepted to have significant impact on the quality of the product, the regulatory agencies require an assessment of process comparability across different phases of manufacturing (Phase I vs. Phase II vs. Phase III vs. Commercial) as well as other key activities during product commercialization (process scale-up, technology transfer, and process improvement). However, assessing comparability for a process with such a large number of variables is nontrivial and often companies resort to qualitative comparisons. In this article, we present a quantitative approach for assessing process comparability via use of chemometrics. To our knowledge this is the first time that such an approach has been published for biotech processing. The approach has been applied to an industrial case study involving evaluation of two processes that are being used for commercial manufacturing of a major biosimilar product. It has been demonstrated that the proposed approach is able to successfully identify the unit operations in the two processes that are operating differently. We expect this approach, which can also be applied toward assessing product comparability, to be of great use to both the regulators and the industry which otherwise struggle to assess comparability.

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

    PubMed

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

    2013-11-01

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

  14. Chemometric characterisation of Basque and French ciders according to their polyphenolic profiles.

    PubMed

    Alonso-Salces, R M; Guyot, S; Herrero, C; Berrueta, L A; Drilleau, J F; Gallo, B; Vicente, F

    2004-06-01

    Polyphenolic compositions of Basque and French ciders were determined by HPLC-DAD following thiolysis, in order to characterise and differentiate these beverages and then develop a classification system capable of confirming the authenticities of both kinds of cider. A data set consisting of 165 cider samples and 27 measured features was evaluated using multivariate chemometric techniques, such as cluster analysis and principal component analysis, in order to perform a preliminary study of data structure. Supervised pattern recognition techniques such as linear discriminant analysis (LDA), K-nearest neighbours (KNN), soft independent modelling of class analogy (SIMCA), and multilayer feed-forward artificial neural networks (MLF-ANN) attained classification rules for the two categories using the chemical data, which produced satisfactory results. Authentication systems obtained by combining two of these techniques were proposed. We found that SIMCA and LDA or KNN models achieved 100% hit-rates, since LDA and KNN permit the detection of every Basque cider and SIMCA provides a model for Basque cider that excludes all French ciders. Polyphenolic profiles of the ciders provided enough information to be able to develop classification rules for identifying ciders according to their geographical origin (Basque or French regions). Chemical and organoleptic differences between these two types of cider are probably due to the original and distinctive cidermaking technologies used for their elaboration. Using polyphenic profiles, about 80% of French ciders could be distinguished according to their region of origin (Brittany or Normandy). Although their polyphenolic profiles did not provide enough information to achieve an authentication system for Breton and Norman ciders. PMID:15118797

  15. Characteristic Fingerprint Based on Low Polar Constituents for Discrimination of Wolfiporia extensa according to Geographical Origin Using UV Spectroscopy and Chemometrics Methods

    PubMed Central

    Li, Yan; Zhao, Yanli; Li, Zhimin; Li, Tao

    2014-01-01

    The fungus species Wolfiporia extensa has a long history of medicinal usage and has also been commercially used to formulate nutraceuticals and functional foods in certain Asian countries. In the present study, a practical and promising method has been developed to discriminate the dried sclerotium of W. extensa collected from different geographical sites based on UV spectroscopy together with chemometrics methods. Characteristic fingerprint of low polar constituents of sample extracts that originated from chloroform has been obtained in the interval 250–400 nm. Chemometric pattern recognition methods such as partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) were applied to enhance the authenticity of discrimination of the specimens. The results showed that W. extensa samples were well classified according to their geographical origins. The proposed method can fully utilize diversified fingerprint characteristics of sclerotium of W. extensa and requires low-cost equipment and short-time analysis in comparison with other techniques. Meanwhile, this simple and efficient method may serve as a basis for the authentication of other medicinal fungi. PMID:25544933

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

    PubMed Central

    Yang, Lanping; Sun, Guoxiang; Guo, Yong; Hou, Zhifei; Chen, Shuai

    2016-01-01

    A widely used herbal medicine, Ixeris sonchifolia (Bge.) Hance Injectable (ISHI) was investigated for quality consistency. Characteristic fingerprints of 23 batches of the ISHI samples were generated at five wavelengths and evaluated by the systematic quantitative fingerprint method (SQFM) as well as simultaneous analysis of the content of seven marker compounds. Chemometric methods, i.e., support vector machine (SVM) and principal component analysis (PCA) were performed to assist in fingerprint evaluation of the ISHI samples. Qualitative classification of the ISHI samples by SVM was consistent with PCA, and in agreement with the quantitative evaluation by SQFM. In addition, the antioxidant activities of the ISHI samples were determined by both the off-line and on-line DPPH (2, 2-diphenyl-1-picryldrazyl) radical scavenging assays. A fingerprint–efficacy relationship linking the chemical components and in vitro antioxidant activity was established and validated using the partial least squares (PLS) and orthogonal projection to latent structures (OPLS) models; and the online DPPH assay further revealed those components that had position contribution to the total antioxidant activity. Therefore, the combined use of the chemometric methods, quantitative fingerprint evaluation by SQFM, and multiple marker compound analysis in conjunction with the assay of antioxidant activity provides a powerful and holistic approach to evaluate quality consistency of herbal medicines and their preparations. PMID:26872364

  17. Simple and rapid simultaneous profiling of minor components of honey by size exclusion chromatography (SEC) coupled to ultraviolet diode array detection (UV-DAD), combined with chemometric methods.

    PubMed

    Beretta, Giangiacomo; Fermo, Paola; Maffei Facino, Roberto

    2012-01-25

    This paper discusses the importance of profiling UV-responsive components, properly integrated with chemometric techniques, in detecting indicative parameters for quality control of honey. The minor components in honeys of different botanical and geographical origins were investigated by size SEC-UV-DAD. We diluted honey with mobile phase before injection into the chromatographic apparatus and a single chromatographic run gave a fast profile of high- (proteins and enzymes), intermediate- (e.g. terpenoid glycosides in lime tree honey) and low-molecular-weight components (secondary metabolites, e.g. kynurenic acid in chestnut honey). The analysis of a total number of 32 honey samples from different regions (Italy, Western Balkan countries, Brazil, Cameroon, Kenya) and of different botanical origins (herbal flower and arboreal flower nectars/honeydews) showed peculiar and characteristic distribution of these markers, which were basically related to their floral origin. Chemometric examination carried out using principal component analysis (PCA) and hierarchical cluster analysis (HCA) of the chromatograms (RT vs. absorption) detected four main clusters in which the groups of (i) chestnut honeys, (ii) honeys from rain forests and (iii) counterfeit/adulterated honeys were clearly separated from the main group of flower nectar honeys. The method is fast, requiring minimal sample handling, and the chromatographic data can be analyzed by multivariate statistical techniques to obtain descriptive information about the honey's quality and composition.

  18. Chemometrics quality assessment of wastewater treatment plant effluents using physicochemical parameters and UV absorption measurements.

    PubMed

    Platikanov, S; Rodriguez-Mozaz, S; Huerta, B; Barceló, D; Cros, J; Batle, M; Poch, G; Tauler, R

    2014-07-01

    Chemometric techniques like Principal Component Analysis (PCA) and Partial Least Squares Regression (PLS) are used to explore, analyze and model relationships among different water quality parameters in wastewater treatment plants (WWTP). Different data sets generated by laboratory analysis and by an automatic multi-parametric monitoring system with a new designed optical device have been investigated for temporal variations on water quality parameters measured in the water influent and effluent of a WWTP over different time scales. The obtained results allowed the discovery of the more important relationships among the monitored parameters and of their cyclic dependence on time (daily, monthly and annual cycles) and on different plant management procedures. This study intended also the modeling and prediction of concentrations of several water components and parameters, especially relevant for water quality assessment, such as Dissolved Organic Matter (DOM), Total Organic Carbon (TOC) nitrate, detergent, and phenol concentrations. PLS models were built to correlate target concentrations of these constituents with UV spectra measured in samples collected at (1) laboratory conditions (in synthetic water mixtures); and at (2) WWTP conditions (in real water samples from the plant). Using synthetic water mixtures, specific wavelengths were selected with the aim to establish simple and reliable prediction models, which gave good relative predictions with errors of around 3-4% for nitrates, detergent and phenols concentrations and of around 15% for the DOM in external validation. In the case of nitrate and TOC concentrations modeling in real water samples from the effluent of the WWTP using the reduced spectral data set, results were also promising with low prediction errors (less than 20%). PMID:24726963

  19. Chemometrics quality assessment of wastewater treatment plant effluents using physicochemical parameters and UV absorption measurements.

    PubMed

    Platikanov, S; Rodriguez-Mozaz, S; Huerta, B; Barceló, D; Cros, J; Batle, M; Poch, G; Tauler, R

    2014-07-01

    Chemometric techniques like Principal Component Analysis (PCA) and Partial Least Squares Regression (PLS) are used to explore, analyze and model relationships among different water quality parameters in wastewater treatment plants (WWTP). Different data sets generated by laboratory analysis and by an automatic multi-parametric monitoring system with a new designed optical device have been investigated for temporal variations on water quality parameters measured in the water influent and effluent of a WWTP over different time scales. The obtained results allowed the discovery of the more important relationships among the monitored parameters and of their cyclic dependence on time (daily, monthly and annual cycles) and on different plant management procedures. This study intended also the modeling and prediction of concentrations of several water components and parameters, especially relevant for water quality assessment, such as Dissolved Organic Matter (DOM), Total Organic Carbon (TOC) nitrate, detergent, and phenol concentrations. PLS models were built to correlate target concentrations of these constituents with UV spectra measured in samples collected at (1) laboratory conditions (in synthetic water mixtures); and at (2) WWTP conditions (in real water samples from the plant). Using synthetic water mixtures, specific wavelengths were selected with the aim to establish simple and reliable prediction models, which gave good relative predictions with errors of around 3-4% for nitrates, detergent and phenols concentrations and of around 15% for the DOM in external validation. In the case of nitrate and TOC concentrations modeling in real water samples from the effluent of the WWTP using the reduced spectral data set, results were also promising with low prediction errors (less than 20%).

  20. Quantification of blockiness in pectins-A comparative study using vibrational spectroscopy and chemometrics.

    PubMed

    Winning, Hanne; Viereck, Nanna; Salomonsen, Tina; Larsen, Jan; Engelsen, Søren B

    2009-09-28

    The gelling properties of pectins are related not only to the degree of esterification (DE), but also to the distribution of the ester groups. In this study, we have examined an experimentally designed series of 31 pectins originating from the same mother pectin and de-esterified using combinations of two different enzymatic mechanisms. The potential of using infrared (IR), Raman, and near infrared (NIR) spectroscopies combined with chemometrics for reliable and rapid determination of the DE and distribution patterns of methyl ester groups in a designed set of pectin powders was investigated. Quantitative calibration models using partial least squares (PLS) regression were developed and compared. The calibration models for prediction of DE obtained on extended inverse signal correction (EISC)-treated spectra of all three spectroscopic methods yielded models with cross-validated prediction errors (RMSECV) between 1.1%p and 1.6%p DE and correlation coefficients of 0.99. A calibration model predicting degree of random de-esterification (R) and block de-esterification (B) was developed for each spectroscopic method, yielding RMSECV values between 4.4 and 6.7 and correlation coefficients (r) between 0.79 and 0.92. Variable selection using interval PLS (iPLS) significantly improved the prediction of R for IR spectroscopy, yielding RMSECV of 3.5 and correlation coefficients of 0.95. All three spectroscopic methods were able to distinguish the spectral patterns of pectins with different enzyme treatments in simple classification models by principal component analysis (PCA). Extended canonical variate analysis revealed one specific signal in the Raman (1045cm(-1)) spectrum and one significant area (1250-1400cm(-1)) in the IR spectrum which are able to classify the pectin samples according to the four different enzyme treatments. In both Raman and IR spectra, the signal intensity decreased in the sequence R-B>B>B-R>R>re-methylated pectin. PMID:19101665

  1. Chemometric approach for development, optimization, and validation of different chromatographic methods for separation of opium alkaloids.

    PubMed

    Acevska, J; Stefkov, G; Petkovska, R; Kulevanova, S; Dimitrovska, A

    2012-05-01

    The excessive and continuously growing interest in the simultaneous determination of poppy alkaloids imposes the development and optimization of convenient high-throughput methods for the assessment of the qualitative and quantitative profile of alkaloids in poppy straw. Systematic optimization of two chromatographic methods (gas chromatography (GC)/flame ionization detector (FID)/mass spectrometry (MS) and reversed-phase (RP)-high-performance liquid chromatography (HPLC)/diode array detector (DAD)) for the separation of alkaloids from Papaver somniferum L. (Papaveraceae) was carried out. The effects of various conditions on the predefined chromatographic descriptors were investigated using chemometrics. A full factorial linear design of experiments for determining the relationship between chromatographic conditions and the retention behavior of the analytes was used. Central composite circumscribed design was utilized for the final method optimization. By conducting the optimization of the methods in very rational manner, a great deal of excessive and unproductive laboratory research work was avoided. The developed chromatographic methods were validated and compared in line with the resolving power, sensitivity, accuracy, speed, cost, ecological aspects, and compatibility with the poppy straw extraction procedure. The separation of the opium alkaloids using the GC/FID/MS method was achieved within 10 min, avoiding any derivatization step. This method has a stronger resolving power, shorter analysis time, better cost/effectiveness factor than the RP-HPLC/DAD method and is in line with the "green trend" of the analysis. The RP-HPLC/DAD method on the other hand displayed better sensitivity for all tested alkaloids. The proposed methods provide both fast screening and an accurate content assessment of the six alkaloids in the poppy samples obtained from the selection program of Papaver strains.

  2. A chemometrics as a powerful tool in the elucidation of the role of metals in the biosynthesis of volatile organic compounds in Hungarian thyme samples.

    PubMed

    Arsenijević, Jelena; Marković, Jelena; Soštarić, Ivan; Ražić, Slavica

    2013-10-01

    The volatile fraction of the leaves of Thymus pannonicus All. (Lamiaceae) was analyzed by headspace extraction followed by GC-FID and GC-MS analysis. The different headspace profiles were recognized, with citral and with monoterpene hydrocarbons as dominant compounds. In addition, the determination of Cr, Co, Ni, Mo, Cu, Zn, Mn, Fe, Mg, Ca, K and Na was conducted by spectroscopic techniques (FAAS, GFAAS and ICP-OES). In order to evaluate the relationship between volatile organic compounds and metals, a chemometrics approach was applied. The data obtained by analysis of the headspace and elemental content were subjected to correlation analysis, factor analysis, principal component analysis and cluster analysis. A number of significant correlations of metals with plant volatiles were found. Correlation of Zn with citral, Mn with oxygenated monoterpenes and Mg with β-bourbonene, could be explained by involvement of metals in the biosynthesis of volatile organic compounds.

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

    ERIC Educational Resources Information Center

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

    2008-01-01

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

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

    ERIC Educational Resources Information Center

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

    2012-01-01

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

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

    PubMed

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

    2016-09-01

    Organic, semiorganic, and conventional "Hayward" kiwifruits, treated with ethylene for 24 h and stored during 10 days, were assessed by UV spectrometry, fluorometry, and chemometrical analysis for changes in selected characteristics of quality (firmness, dry matter and soluble solid contents, pH, and acidity) and bioactivity (concentration of polyphenols via Folin-Ciocalteu and p-hydroxybenzoic acid assays). All of the monitored qualitative parameters and characteristics related to bioactivity were affected either by cultivation practices or by ethylene treatment and storage. Results obtained, supported by statistical evaluation (Friedman two-way ANOVA) and chemometric analysis, clearly proved that the most significant impact on the majority of the evaluated parameters of quality and bioactivity of "Hayward" kiwifruit had the ethylene treatment followed by the cultivation practices and the postharvest storage. Total concentration of polyphenols expressed via p-hydroxybenzoic acid assay exhibited the most significant sensitivity to all three evaluated parameters, reaching a 16.5% increase for fresh organic compared to a conventional control sample. As a result of postharvest storage coupled with ethylene treatment, the difference increased to 26.3%. Three-dimensional fluorescence showed differences in the position of the main peaks and their fluorescence intensity for conventional, semiorganic, and organic kiwifruits in comparison with ethylene nontreated samples. PMID:27472553

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

    SciTech Connect

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

    2010-05-15

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

  7. Chemometrics methods for the investigation of methylmercury and total mercury contamination in mollusks samples collected from coastal sites along the Chinese Bohai Sea.

    PubMed

    Yawei, Wang; Lina, Liang; Jianbo, Shi; Guibin, Jiang

    2005-06-01

    The development and application of chemometrics methods, principal component analysis (PCA), cluster analysis and correlation analysis for the determination of methylmercury (MeHg) and total mecury (HgT) in gastropod and bivalve species collected from eight coastal sites along the Chinese Bohai Sea are described. HgT is directly determined by atomic fluorescence spectrometry (AFS), while MeHg is measured by a laboratory established high performance liquid chromatography-atomic fluorescence spectrometry system (HPLC-AFS). One-way ANOVA and cluster analysis indicated that the bioaccumulation of Rap to accumulate Hg was significantly (P<0.05) different from other mollusks. Correlation analysis shows that there is linear relationship between MeHg and HgT in mollusks samples collected from coastal sites along the Chinese Bohai Sea, while in mollusks samples collected from Hongqiao market in Beijing City, there is not any linear relationship. PMID:15749543

  8. Ghanaian cocoa bean fermentation characterized by spectroscopic and chromatographic methods and chemometrics.

    PubMed

    Aculey, Patrick C; Snitkjaer, Pia; Owusu, Margaret; Bassompiere, Marc; Takrama, Jemmy; Nørgaard, Lars; Petersen, Mikael A; Nielsen, Dennis S

    2010-08-01

    Export of cocoa beans is of great economic importance in Ghana and several other tropical countries. Raw cocoa has an astringent, unpleasant taste, and flavor, and has to be fermented, dried, and roasted to obtain the characteristic cocoa flavor and taste. In an attempt to obtain a deeper understanding of the changes in the cocoa beans during fermentation and investigate the possibility of future development of objective methods for assessing the degree of fermentation, a novel combination of methods including cut test, colorimetry, fluorescence spectroscopy, NIR spectroscopy, and GC-MS evaluated by chemometric methods was used to examine cocoa beans sampled at different durations of fermentation and samples representing fully fermented and dried beans from all cocoa growing regions of Ghana. Using colorimetry it was found that samples moved towards higher a* and b* values as fermentation progressed. Furthermore, the degree of fermentation could, in general, be well described by the spectroscopic methods used. In addition, it was possible to link analysis of volatile compounds with predictions of fermentation time. Fermented and dried cocoa beans from the Volta and the Western regions clustered separately in the score plots based on colorimetric, fluorescence, NIR, and GC-MS indicating regional differences in the composition of Ghanaian cocoa beans. The study demonstrates the potential of colorimetry and spectroscopic methods as valuable tools for determining the fermentation degree of cocoa beans. Using GC-MS it was possible to demonstrate the formation of several important aroma compounds such 2-phenylethyl acetate, propionic acid, and acetoin and the breakdown of others like diacetyl during fermentation. Practical Application: The present study demonstrates the potential of using colorimetry and spectroscopic methods as objective methods for determining cocoa bean quality along the processing chain. Development of objective methods for determining cocoa bean

  9. Application of inorganic element ratios to chemometrics for determination of the geographic origin of welsh onions.

    PubMed

    Ariyama, Kaoru; Horita, Hiroshi; Yasui, Akemi

    2004-09-22

    The composition of concentration ratios of 19 inorganic elements to Mg (hereinafter referred to as 19-element/Mg composition) was applied to chemometric techniques to determine the geographic origin (Japan or China) of Welsh onions (Allium fistulosum L.). Using a composition of element ratios has the advantage of simplified sample preparation, and it was possible to determine the geographic origin of a Welsh onion within 2 days. The classical technique based on 20 element concentrations was also used along with the new simpler one based on 19 elements/Mg in order to validate the new technique. Twenty elements, Na, P, K, Ca, Mg, Mn, Fe, Cu, Zn, Sr, Ba, Co, Ni, Rb, Mo, Cd, Cs, La, Ce, and Tl, in 244 Welsh onion samples were analyzed by flame atomic absorption spectroscopy, inductively coupled plasma atomic emission spectrometry, and inductively coupled plasma mass spectrometry. Linear discriminant analysis (LDA) on 20-element concentrations and 19-element/Mg composition was applied to these analytical data, and soft independent modeling of class analogy (SIMCA) on 19-element/Mg composition was applied to these analytical data. The results showed that techniques based on 19-element/Mg composition were effective. LDA, based on 19-element/Mg composition for classification of samples from Japan and from Shandong, Shanghai, and Fujian in China, classified 101 samples used for modeling 97% correctly and predicted another 119 samples excluding 24 nonauthentic samples 93% correctly. In discriminations by 10 times of SIMCA based on 19-element/Mg composition modeled using 101 samples, 220 samples from known production areas including samples used for modeling and excluding 24 nonauthentic samples were predicted 92% correctly. PMID:15366824

  10. Investigating hydrochemistry of groundwater in Indo-Gangetic alluvial plain using multivariate chemometric approaches.

    PubMed

    Singh, Kunwar P; Gupta, Shikha; Rai, Premanjali

    2014-05-01

    Groundwater hydrochemistry of an urban industrial region in Indo-Gangetic plains of north India was investigated. Groundwater samples were collected both from the industrial and non-industrial areas of Kanpur. The hydrochemical data were analyzed using various water quality indices and nonparametric statistical methods. Principal components analysis (PCA) was performed to identify the factors responsible for groundwater contamination. Ensemble learning-based decision treeboost (DTB) models were constructed to develop discriminating and regression functions to differentiate the groundwater hydrochemistry of the three different areas, to identify the responsible factors, and to predict the groundwater quality using selected measured variables. The results indicated non-normal distribution and wide variability of water quality variables in all the study areas, suggesting for nonhomogenous distribution of sources in the region. PCA results showed contaminants of industrial origin dominating in the region. DBT classification model identified pH, redox potential, total-Cr, and λ 254 as the discriminating variables in water quality of the three areas with the average accuracy of 99.51 % in complete data. The regression model predicted the groundwater chemical oxygen demand values exhibiting high correlation with measured values (0.962 in training; 0.918 in test) and the respective low root mean-squared error of 2.24 and 2.01 in training and test arrays. The statistical and chemometric approaches used here suggest that groundwater hydrochemistry differs in the three areas and is dominated by different variables. The proposed methods can be used as effective tools in groundwater management.

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

    PubMed

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

    2014-08-01

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

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

    PubMed

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

    2014-08-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed

    Gonzalez-Rodriguez, J; Fowler, G

    2013-09-10

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

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

    PubMed

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

    2016-05-18

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

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

    PubMed

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

    2016-07-01

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

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

    PubMed

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

    2016-05-18

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

  18. Coordinating fingerprint determination of solid-phase microextraction/gas chromatography-mass spectrometry and chemometric methods for quality control of oxidized tallow.

    PubMed

    Song, Shiqing; Zhang, Xiaoming; Hayat, Khizar; Xiao, Zuobing; Niu, Yunwei; Eric, Karangwa

    2013-02-22

    Based on optimized solid-phase microextraction/gas chromatography-mass spectrometry (SPME/GC-MS) and chemometric methods, simple, reliable and reproducible methods were described for the first time for developing a chromatographic fingerprint of oxidized tallow. Eight optimal oxidized tallow samples were used to establish the chromatographic fingerprint. Spectral correlative chromatogram was adopted to identify 33 "common components". The validation of fingerprint analysis was performed based on the relative retention time, the relative peak area of common peaks, sample stability and similarity analysis. The correlation coefficient of similarity of eight optimal oxidized tallow samples was more than 0.962, which showed that samples from different batches were consistent to some extent in spite of slightly different chemical indexes. Through principal component analysis (PCA), 14 constituents were further screened out to be the main chemical markers, which could be applied to more accurate quantitative discrimination and quality control of oxidized tallow.

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

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

  1. Chemometric and environmental assessment of arsenic, antimony, and chromium speciation form occurrence in a water reservoir subjected to thermal anthropopressure.

    PubMed

    Jabłońska-Czapla, Magdalena; Szopa, Sebastian; Zerzucha, Piotr; Łyko, Aleksandra; Michalski, Rajmund

    2015-10-01

    In the study, arsenic, antimony, and chromium concentrations and selected physicochemical parameters in water and sediment samples from the thermal anthroporessure subjected Rybnik Reservoir (Poland) were determined. As(III), As(V), Sb(III), and Sb(V) ions were successfully separated on Dionex IonPac AS7 column, and Cr(III) and Cr(VI) on Dionex IonPac AG7 column. The obtained limits of detection were 0.18, 0.22, 0.009, 0.012, 0.11, and 0.17 μg/L, respectively. Water and bottom sediment samples were collected monthly at three-point transect between January and November 2013. The As(III) and Sb(III) speciation forms dominated in the bottom water, and Cr(VI) concentration in the bottom water was twice as high as the value measured for the surface water. The oxidized arsenic, antimony, and chromium forms dominated in the bottom sediments in the heated water discharge zone of the Rybnik Power Plant. The location of sampling point had a significant influence on the observed transformations and contents of the analyzed speciation forms. The chemometric analysis coupled with the dissimilarity analysis and principal component analysis helped to visualize the variability in the concentrations of the element speciation forms within the researched period and analyzing correlations.

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

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

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

    PubMed

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

    2015-02-25

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

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

    PubMed

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

    2015-04-01

    Visible/near infrared spectroscopy (Vis/NIR) based on sensitive wavelengths (SWs) and chemometrics was proposed to discriminate different tomatoes bred by spaceflight mutagenesis from their leafs or fruits (green or mature). The tomato breeds were mutant M1, M2 and their parent. Partial least squares (PLS) analysis and least squares-support vector machine (LS-SVM) were implemented for calibration models. PLS analysis was implemented for calibration models with different wavebands including the visible region (400-700 nm) and the near infrared region (700-1000 nm). The best PLS models were achieved in the visible region for the leaf and green fruit samples and in the near infrared region for the mature fruit samples. Furthermore, different latent variables (4-8 LVs for leafs, 5-9 LVs for green fruits, and 4-9 LVs for mature fruits) were used as inputs of LS-SVM to develop the LV-LS-SVM models with the grid search technique and radial basis function (RBF) kernel. The optimal LV-LS-SVM models were achieved with six LVs for the leaf samples, seven LVs for green fruits, and six LVs for mature fruits, respectively, and they outperformed the PLS models. Moreover, independent component analysis (ICA) was executed to select several SWs based on loading weights. The optimal LS-SVM model was achieved with SWs of 550-560 nm, 562-574 nm, 670-680 nm and 705-71 5 nm for the leaf samples; 548-556 nm, 559-564 nm, 678-685 nm and 962-974 nm for the green fruit samples; and 712-718 nm, 720-729 nm, 968-978 nm and 820-830 nm for the mature fruit samples. All of them had better performance than PLS and LV-LS-SVM, with the parameters of correlation coefficient (rp), root mean square error of prediction (RMSEP) and bias of 0.9792, 0.2632 and 0.0901 based on leaf discrimination, 0.9837, 0.2783 and 0.1758 based on green fruit discrimination, 0.9804, 0.2215 and -0.0035 based on mature fruit discrimination, respectively. The overall results indicated that ICA was an effective way for the

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    PubMed

    Ni, Yongnian; Wang, Lin; Kokot, Serge

    2011-01-01

    A novel differential pulse voltammetry method (DPV) was researched and developed for the simultaneous determination of Pendimethalin, Dinoseb and sodium 5-nitroguaiacolate (5NG) with the aid of chemometrics. The voltammograms of these three compounds overlapped significantly, and to facilitate the simultaneous determination of the three analytes, chemometrics methods were applied. These included classical least squares (CLS), principal component regression (PCR), partial least squares (PLS) and radial basis function-artificial neural networks (RBF-ANN). A separately prepared verification data set was used to confirm the calibrations, which were built from the original and first derivative data matrices of the voltammograms. On the basis relative prediction errors and recoveries of the analytes, the RBF-ANN and the DPLS (D - first derivative spectra) models performed best and are particularly recommended for application. The DPLS calibration model was applied satisfactorily for the prediction of the three analytes from market vegetables and lake water samples. PMID:21512931

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

    PubMed

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

    2017-02-01

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

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

    PubMed

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

    2017-02-01

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

  9. Main differences between volatiles of sparkling and base wines accessed through comprehensive two dimensional gas chromatography with time-of-flight mass spectrometric detection and chemometric tools.

    PubMed

    Welke, Juliane Elisa; Zanus, Mauro; Lazzarotto, Marcelo; Pulgati, Fernando Hepp; Zini, Cláudia Alcaraz

    2014-12-01

    The main changes in the volatile profile of base wines and their corresponding sparkling wines produced by traditional method were evaluated and investigated for the first time using headspace solid-phase microextraction combined with comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry detection (GC×GC/TOFMS) and chemometric tools. Fisher ratios helped to find the 119 analytes that were responsible for the main differences between base and sparkling wines and principal component analysis explained 93.1% of the total variance related to the selected 78 compounds. It was also possible to observe five subclusters in base wines and four subclusters in sparkling wines samples through hierarchical cluster analysis, which seemed to have an organised distribution according to the regions where the wines came from. Twenty of the most important volatile compounds co-eluted with other components and separation of some of them was possible due to GC×GC/TOFMS performance.

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

    PubMed

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

    2011-05-15

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

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

    PubMed

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

    2011-05-15

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

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

    NASA Astrophysics Data System (ADS)

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

    2008-02-01

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

  13. Estimation of honey authenticity by multielements characteristics using inductively coupled plasma-mass spectrometry (ICP-MS) combined with chemometrics.

    PubMed

    Chudzinska, M; Baralkiewicz, D

    2010-01-01

    In our study the mineral content of 55 honey samples, which represented three different types of honey: honeydew, buckwheat and rape honey from different areas in Poland, was evaluated. Determination of 13 elements (Al, B, Ba, Ca, Cd, Cu, K, Mg, Mn, Na, Ni, Pb, Zn) was performed using inductively coupled plasma-mass spectrometry. We tried to prove that the analysis of quality and quantity of honey elements could be used to define honey origin by using ICP-MS as a technique for simultaneous determination of elements. Chemometric methods, such as CA and PCA, were applied to classify honey according to mineral content. CA showed three clusters corresponding to the three botanical origins of honey. PCA permitted the reduction of 13 variables to four principal components explaining 77.19% of the total variance. The first most important principal component was strongly associated with the value of K, Al, Ni and Cd. This study revealed that CA and PCA analysis appear useful tools for differentiation of honey samples authenticity using the profile of mineral content and they highlighted the relationship between the elements distribution and honey type.

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

    PubMed

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

    2014-12-01

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

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

    PubMed

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

    2013-11-15

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

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

    PubMed Central

    Wang, Pei; Nie, Lei; Zang, Hengchang

    2015-01-01

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

  17. A copper interdigitated electrode and chemometrical tools used for the discrimination of the adulteration of ethanol fuel with water.

    PubMed

    Bueno, Lígia; Paixão, Thiago R L C

    2011-12-15

    A new approach for the discrimination of the adulteration process of ethanol fuel with water is reported using a copper interdigitated electrode and chemometrical tools. The sensor was constructed using copper sheets with non-chemical modification of the electrode surface. The discrimination process was performed using capacitance values recorded at different frequencies (1,000 Hz to 0.1 MHz) as the input data for non-supervised pattern recognition methods (PCA: principal component analysis and HCA: hierarchical cluster analysis). The relative standard deviation for the capacitance signals obtained from ten independent interdigitated sensors was below 5.0%. The ability of the device to differentiate non-adulterated ethanol samples from those adulterated with water was demonstrated. In all analysed cases, there was good separation between the different samples in the score plots and the dendrograms obtained from PCA and hierarchical cluster analyses, respectively. Furthermore, the water content was quantified using a PCA approach. The results were consistent with those obtained using the Karl-Fischer method at a 95% confidence level, as measured using Student's t-test.

  18. Use of direct headspace-mass spectrometry coupled with chemometrics to predict aroma properties in Australian Riesling wine.

    PubMed

    Cozzolino, Daniel; Smyth, Heather E; Cynkar, Wies; Janik, Les; Dambergs, Robert G; Gishen, Mark

    2008-07-21

    The aim of this study was to investigate the potential use of a direct headspace-mass spectrometry electronic nose instrument (MS e_nose) combined with chemometrics as rapid, objective and low cost technique to measure aroma properties in Australian Riesling wines. Commercial bottled Riesling wines were analyzed using a MS e_nose instrument and by a sensory panel. The MS e_nose data generated were analyzed using principal components analysis (PCA) and partial least squares (PLS1) regression using full cross validation (leave one out method). Calibration models between MS e_nose data and aroma properties were developed using partial least squares (PLS1) regression, yielding coefficients of correlation in calibration (R) and root mean square error of cross validation of 0.75 (RMSECV: 0.85) for estery, 0.89 (RMSECV: 0.94) for perfume floral, 0.82 (RMSECV: 0.62) for lemon, 0.82 (RMSECV: 0.32) for stewed apple, 0.67 (RMSECV: 0.99) for passion fruit and 0.90 (RMSECV: 0.86) for honey, respectively. The relative benefits of using MS e_nose will provide capability for rapid screening of wines before sensory analysis. However, the basic deficiency of this technique is lack of possible identification and quantitative determination of individual compounds responsible for the different aroma notes in the wine.

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

    PubMed

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

    2011-07-27

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

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

    PubMed

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

    2014-12-01

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

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

    PubMed

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

    2015-12-01

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

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

    PubMed

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

    2013-10-15

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

  3. MALDI-TOF MS and chemometric based identification of the Acinetobacter calcoaceticus-Acinetobacter baumannii complex species.

    PubMed

    Sousa, Clara; Botelho, João; Silva, Liliana; Grosso, Filipa; Nemec, Alexandr; Lopes, João; Peixe, Luísa

    2014-07-01

    MALDI-TOF MS is becoming the technique of choice for rapid bacterial identification at species level in routine diagnostics. However, some drawbacks concerning the identification of closely related species such as those belonging to the Acinetobacter calcoaceticus-Acinetobacter baumannii (Acb) complex lead to high rates of misidentifications. In this work we successfully developed an approach that combines MALDI-TOF MS and chemometric tools to discriminate the six Acb complex species (A. baumannii, Acinetobacter nosocomialis, Acinetobacter pittii, A. calcoaceticus, genomic species "Close to 13TU" and genomic species "Between 1 and 3"). Mass spectra of 83 taxonomically well characterized clinical strains, reflecting the breadth of currently known phenetic diversity within the Acb complex, were achieved from intact cells and cell extracts and analyzed with hierarchical cluster analysis (HCA) and partial least squares discriminant analysis (PLSDA). This combined approach lead to 100% of correct species identification using mass spectra obtained from intact cells. Moreover, it was possible to discriminate two Acb complex species (genomic species "Close to 13TU" and genomic species "Between 1 and 3") not included in the MALDI Biotyper database.

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

    NASA Astrophysics Data System (ADS)

    Gramatica, Paola

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

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

    PubMed

    Farrés, Mireia; Piña, Benjamí; Tauler, Romà

    2016-08-01

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

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2017-02-15

    The objective of the present study was: i) to characterize Mediterranean citrus honeys based on conventional physicochemical parameter values, volatile compounds, and mineral content ii) to investigate the potential of above parameters to differentiate citrus honeys according to geographical origin using chemometrics. Thus, 37 citrus honey samples were collected during harvesting periods 2013 and 2014 from Greece, Egypt, Morocco, and Spain. Conventional physicochemical and CIELAB colour parameters were determined using official methods of analysis and the Commission Internationale de l' Eclairage recommendations, respectively. Minerals were determined using ICP-OES and volatiles using SPME-GC/MS. Results showed that honey samples analyzed, met the standard quality criteria set by the EU and were successfully classified according to geographical origin. Correct classification rates were 97.3% using 8 physicochemical parameter values, 86.5% using 15 volatile compound data and 83.8% using 13 minerals. PMID:27664657

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

    PubMed

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    PubMed

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

    2015-04-15

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

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

    PubMed

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

    2013-04-15

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

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

    PubMed

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

    2013-04-15

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

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

    PubMed

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

    2016-01-26

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

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

    PubMed

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

    2016-01-18

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

  15. Performance assessment of chemometric resolution methods utilized for extraction of pure components from overlapped signals in gas chromatography-mass spectrometry.

    PubMed

    Seifi, Hooman; Masoum, Saeed; Seifi, Soodabe

    2014-10-24

    Multivariate resolution technique is a set of mathematical tools that uncovers the underlying profiles from a set of measurements of time evolving chemical systems. This technique was proposed for resolving the overlapping GC-MS peaks into pure chromatogram and mass spectra. In this paper, several common resolution chemometric techniques in GC-MS resolution such as mean field-independent component analysis (MF-ICA), multivariate curve resolution-alternating least squares (MCR-ALS), and multivariate curve resolution-objective function minimization (MCR-FMIN) were investigated. The obtained solutions using chemometric methods are assessed by lack of fit (LOF) and R(2). Results show that all solutions by fulfilling the same constraints have same performance in resolving high overlapping peaks. Also, the differences obtained in each case should be related to the unresolved rotational ambiguity. Among the different ambiguities such as intensity, permutation and rotation in resolution methods, rotational ambiguity is the most difficult and critical one. Because of rotational ambiguity, there is a set of feasible MCR solutions, which explain equally well the observed experimental data, and fulfill sufficiently the imposed constraints of the system. So in these methods, a range of feasible solutions exist. The rotational ambiguities of the profiles are a challenging fact which complicates the development of stable and universal self-modeling curve resolution (SMCR) algorithms. The relative component contribution (RCC) function values for the component profiles obtained by the different methods are calculated by MCR-BANDS. The values of RCC for these three methods are equivalent. Rotational ambiguities of the solutions of SMCR methods can be reduced by applying suitable constraints. The obtained results show, using data sets, which are arranged in a single augmented data matrix could be the best solution for reducing or removing of rotational ambiguity.

  16. [Application of ICP-MS method in the determination of mineral elements in vitex honey for the classification of their geographical origins with chemometric approach].

    PubMed

    Chen, Hui; Fan, Chun-lin; Chang, Qiao-ying; Pang, Guo-fang; Cao, Ya-fei; Jin, Ling-he; Hu, Xue-yan

    2015-01-01

    In the present work, the contents of 38 elements of 65 vitex (Vitex negundo var. heterophylla Rehd. ) honey samples from Shunyi of Beijing, Fuping and Pingshan of Hebei province were determined by inductively coupled plasma mass spectrometry (ICP-MS). Among them, B, Na, Mg, P, K, Ca, Fe and Zn were the most abundant elements with mean contents more than 1 mg kg-1. It can be found that there were relationships between the contents of elements and the geographical origin of vitex honey samples. Taking the contents of 29 out of 38 mineral elements (Na, Mg, Al, K, Ti, V, Mn, Fe, Ni, Cu, Zn, Ga, As, Sr, Y, Mo, Cd, Ba, La, Ce, Pr, Nd, Sm, Gd, Dy, Ho, T1, Pb and U) as variables, the chemometric methods, such as principal component analysis (PCA) and back-propagation artificial neural network (BP-ANN), were applied to classify vitex honey samples according to their geographical origins. PCA reduced all of the variables to four principal components and could explain 81. 6% of the total variances. The results indicated that PCA could mainly classify the vitex honey samples into three groups. BP-ANN was explored to construct classification model of vitex honeys according to their geographical origin. For the whole data set, the overall correct classification rate and cross-validation (leave one out method) rate of proposed BP-ANN model was 100% and 95. 4%, respectively. To further test the stability of the model developed for prediction, 75% of honey samples of each geographical origin were randomly selected for the model training set, and the remaining samples were classified with the use of the constructed model. Both the overall correct classification rate and prediction rate of proposed BP-ANN model were 100%. It is concluded that the profiles of multi-element by ICP-MS with chemometric methods could be a potential and powerful tool for the classification of vitex honey samples from different geographical origins.

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

    PubMed

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

    2015-06-01

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

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

    PubMed

    Arvanitoyannis, Ioannis S; Tzouros, Nikolaos E

    2005-01-01

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

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

    PubMed

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

    2009-12-01

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

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

    PubMed

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

    2009-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    PubMed Central

    Li, Xiaoli; Zhang, Yuying; He, Yong

    2016-01-01

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

  3. HPLC and chemometric methods for the simultaneous determination of cyproheptadine hydrochloride, multivitamins, and sorbic acid.

    PubMed

    el-Gindy, Alaa; el-Yazby, Fawzy; Mostafa, Ahmed; Maher, Moustafa M

    2004-06-29

    Three methods are presented for the simultaneous determination of cyproheptadine hydrochloride (CP), thiamine hydrochloride (B1), riboflavin-5-phosphate sodium dihydrate (B2), nicotinamide (B3), pyridoxine hydrochloride (B6), and sorbic acid (SO). The chromatographic method depends on a high performance liquid chromatographic (HPLC) separation on a reversed-phase, RP 18 column. Elution was carried out with 0.1% methanolic hexane sulphonic acid sodium salt (solvent A) and 0.01 M phosphate buffer containing 0.1% hexane sulphonic acid sodium salt, adjusted to an apparent pH of 2.7 (solvent B). Gradient HPLC was used with the solvent ratio changed from 20:80 to 70:30 (over 9 min), then to 80:20 (over 11 min) for solvent A:B, respectively. Quantitation was achieved with UV detection at 220 and 288 nm based on peak area. The other two chemometric methods applied were principal component regression (PCR) and partial least squares (PLS). These approaches were successfully applied to quantify each drug in the mixture using the information included in the UV absorption spectra of appropriate solutions in the range 250-290 nm with the intervals Deltalambda = 0.4 nm at 100 wavelengths. The chemometric methods do not require any separation step. The three methods were successfully applied to a pharmaceutical formulation and the results were compared with each other.

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

    PubMed

    Li, Xiaoli; Zhang, Yuying; He, Yong

    2016-01-01

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

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

    PubMed

    Li, Xiaoli; Zhang, Yuying; He, Yong

    2016-07-29

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

  6. Cluster resolution: a metric for automated, objective and optimized feature selection in chemometric modeling.

    PubMed

    Sinkov, Nikolai A; Harynuk, James J

    2011-01-30

    A novel metric termed cluster resolution is presented. This metric compares the separation of clusters of data points while simultaneously considering the shapes of the clusters and their relative orientations. Using cluster resolution in conjunction with an objective variable ranking metric allows for fully automated feature selection for the construction of chemometric models. The metric is based upon considering the maximum size of confidence ellipses around clusters of points representing different classes of objects that can be constructed without any overlap of the ellipses. For demonstration purposes we utilized PCA to classify samples of gasoline based upon their octane rating. The entire GC-MS chromatogram of each sample comprising over 2 × 10(6) variables was considered. As an example, automated ranking by ANOVA was applied followed by a forward selection approach to choose variables for inclusion. This approach can be generally applied to feature selection for a variety of applications and represents a significant step towards the development of fully automated, objective construction of chemometric models.

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

    PubMed

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

    2016-07-20

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

  8. Simultaneous Determination of Amiloride and Hydrochlorothiazide in a Compound Tablet by Diffuse Reflectance Spectroscopy and Chemometrics

    NASA Astrophysics Data System (ADS)

    Tang, J.; Li, X.; Feng, Y.; Liang, B.

    2016-09-01

    This paper studies the simultaneous determination of amiloride hydrochloride (AMH) and hydrochlorothiazide (HCTZ) in amiloride hydrochloride tablets by ultraviolet-visible-shortwave near-infrared diffuse reflectance spectroscopy (UV-Vis-swNIR DRS) and chemometrics. Quantitative models for the two components were established by partial least squares (PLS) and support vector regression (SVR), respectively. For the PLS models of AMH and HCTZ, the determination coefficient R2 of the calibration set was 0.9503 and 0.9538, and the coefficient R2 of the prediction set was 0.8983 and 0.9260, respectively. The root mean square error of the calibration set (RMSEC) was 0.8 mg and 8.1 mg, while the root mean square error of the prediction set (RMSEP) was 1.0 mg and 8.7 mg, respectively. For the SVR models of AMH and HCTZ, the R2 of the calibration set was 0.9668 and 0.9609; the R2 of the prediction set was 0.9145 and 0.9446, respectively. The RMSEC was 0.7 and 7.5 mg, and the RMSEP was 0.9 and 8.9 mg, respectively. The results show that SVR modeling has a satisfactory prediction effect. The proposed method based on UV-vis-swNIR and chemometrics is efficient, nondestructive, and expected to be used for online quality monitoring in the production of drugs.

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

    NASA Astrophysics Data System (ADS)

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

    2007-01-01

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

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

    PubMed

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

    2016-09-01

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

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

    PubMed

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

    2016-09-01

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

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

    PubMed

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

    2012-12-01

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

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

    PubMed

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

    2016-06-14

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

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

    PubMed

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

    2015-01-01

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

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

    PubMed

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

    2006-09-15

    In food production, reliable analytical methods for confirmation of purity or degree of spoilage are required by growers, food quality assessors, processors, and consumers. Seven parameters of physico-chemical properties, such as acid number, colority, density, refractive index, moisture and volatility, saponification value and peroxide value, were measured for quality and adulterated soybean, as well as quality and rancid rapeseed oils. Chemometrics methods were then applied for qualitative and quantitative discrimination and prediction of the oils by methods such exploratory principal component analysis (PCA), partial least squares (PLS), radial basis function-artificial neural networks (RBF-ANN), and multi-criteria decision making methods (MCDM), PROMETHEE and GAIA. In general, the soybean and rapeseed oils were discriminated by PCA, and the two spoilt oils behaved differently with the rancid rapeseed samples exhibiting more object scatter on the PC-scores plot, than the adulterated soybean oil. For the PLS and RBF-ANN prediction methods, suitable training models were devised, which were able to predict satisfactorily the category of the four different oil samples in the verification set. Rank ordering with the use of MCDM models indicated that the oil types can be discriminated on the PROMETHEE II scale. For the first time, it was demonstrated how ranking of oil objects with the use of PROMETHEE and GAIA could be utilized as a versatile indicator of quality performance of products on the basis of a standard selected by the stakeholder. In principle, this approach provides a very flexible method for assessment of product quality directly from the measured data. PMID:18970766

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

    PubMed

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

    2015-01-01

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

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

    PubMed

    Sredović, I; Rajaković, Lj

    2010-05-15

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

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

    PubMed

    Sredović, I; Rajaković, Lj

    2010-05-15

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

  19. APPLICATION OF CHEMOMETRICS FOR IDENTIFICATION OF PSYCHOACTIVE PLANTS.

    PubMed

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

    2015-01-01

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

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

    PubMed

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

    2015-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    PubMed Central

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Wu, Mei-Lin; Wang, You-Shao

    2007-05-01

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

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

    PubMed

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

    2016-07-01

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

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

    PubMed

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

    2012-06-01

    Concentrations of selected heavy metals (Cd, Pb, Zn, Cu, Mn, and Fe) in surface sediments from 66 sites in both northern and eastern Mediterranean Sea-Boughrara lagoon exchange areas (southeastern Tunisia) were studied in order to understand current metal contamination due to the urbanization and economic development of nearby several coastal regions of the Gulf of Gabès. Multiple approaches were applied for the sediment quality assessment. These approaches were based on GIS coupled with chemometric methods (enrichment factors, geoaccumulation index, principal component analysis, and cluster analysis). Enrichment factors and principal component analysis revealed two distinct groups of metals. The first group corresponded to Fe and Mn derived from natural sources, and the second group contained Cd, Pb, Zn, and Cu originated from man-made sources. For these latter metals, cluster analysis showed two distinct distributions in the selected areas. They were attributed to temporal and spatial variations of contaminant sources input. The geoaccumulation index (I (geo)) values explained that only Cd, Pb, and Cu can be considered as moderate to extreme pollutants in the studied sediments. PMID:21792517

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2015-08-19

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

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

  9. Chemometrics-assisted UV-spectroscopic strategies for the determination of theophylline in syrups.

    PubMed

    Culzoni, María J; De Zan, María M; Robles, Juan Carlos; Mantovani, Víctor E; Goicoechea, Héctor C

    2005-10-01

    Two spectrophotometric methods, assisted by chemometric tools, were developed for the determination of theophylline in syrups: derivative spectroscopy (DS) and partial least-squares regression (PLS), the latter using both artificial and natural calibration sets. HPLC technique was employed to apply a reference method in order to achieve a complete assessment of performance. Calibrations presented excellent analytical figures of merits (i.e. LOD ranged from 0.03 to 0.4 mg L(-1) and analytical sensitivity ranged from 1.7 to 8.3 L mg(-1)). The intermediate precision presented pooled coefficients of variation ranged between 0.54 and 1.08%. Accuracy was studied trough an elliptical joint confidence region test (EJCR) comparing the obtained values when analysing spiked real samples by the HPLC and the studied methodologies. Both studied methods can be considered acceptable for the pharmaceutical quality assurance of theophylline in syrup samples.

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

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

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

    USGS Publications Warehouse

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

    2013-01-01

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

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

    PubMed

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

    2013-10-01

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

  13. Determination and comparison of mineral elements in traditional Chinese herbal formulae at different decoction times used to improve kidney function--chemometric approach.

    PubMed

    Kolasani, Archana; Xu, Hong; Millikan, Mary

    2011-01-01

    Traditional Chinese herbal formulae Liu wei di huang (LW) (six-ingredient pill with Rehmannia) and Jin gui shen qi wan (JG) (kidney Qi pill from the golden cabinet) were analysed for Ca, Fe, Mg, Mn, Na, K and Zn at different decoction intervals by atomic absorption spectroscopy. LW and JG were used to improve the kidney function. JG was higher in all elements than LW. K (1691.29 - 2372.71 mg l(-1)) was highest in both formulae LW and JG followed by Ca (245.31 - 562.91 mg l(-1)). Ca, Fe, Mg, Mn and K were highest at 40 min for LW and Fe, Mn, Na and K were highest at 40 min for JG. Chemometrics such as principal component analysis, hierarchical cluster analysis and linear discriminate analysis were applied to classify the data and to understand the relation between the elements. Metal intake related to the consumption of decoction has also been studied. Mn made the highest contribution to average daily dietary intakes from the formulae.

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

    PubMed

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

    2016-06-21

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

  15. Photochemical behavior under UVA radiation of β-cyclodextrin included Parsol ® 1789 with a chemometric approach

    NASA Astrophysics Data System (ADS)

    Biloti, D. N.; dos Reis, M. M.; Ferreira, M. M. C.; Pessine, F. B. T.

    1999-05-01

    In this work, the photochemical behavior of β-cyclodextrin ( βCD) encapsulated Parsol ® 1789 sunscreen under ultraviolet radiation UVA (320-400 nm) is reported using chemometrics. The photochemical study on the free and βCD included molecule in some solvents was carried out under UVA light and probing by fluorescence and absorption spectroscopies. The chemometric method developed by Lawton and Sylvestre was employed in order to resolve the spectra and the concentration profiles. The results showed that βCD complexation did not increase the Parsol ® photochemical stability, regardless of the employed solvents. However, it may reduce the effects related to photoallergy/phototoxicity through inclusion of the photoproducts.

  16. Determination of the geographic origin of rice by chemometrics with strontium and lead isotope ratios and multielement concentrations.

    PubMed

    Ariyama, Kaoru; Shinozaki, Miyuki; Kawasaki, Akira

    2012-02-22

    The objective of this study was to develop a technique for determining the country of origin of rice in the Japanese market. The rice samples included a total of 350 products grown in Japan (n = 200), the United States (n = 50), China (n = 50), and Thailand (n = 50). In this study, (87)Sr/(86)Sr and Pb isotope ((204)Pb, (206)Pb, (207)Pb, and (208)Pb) ratios and multielement concentrations (Al, Fe, Co, Ni, Cu, Rb, Sr, and Ba) were determined by high-resolution inductively coupled plasma mass spectrometry. By combining three chemometric techniques based on different principles and determination criteria, the countries of origin of rice were determined. The predictions made by 10-fold cross-validation were around 97% accurate. The presented method demonstrated the effectiveness of determining the geographic origin of an agricultural product by combining several chemometric techniques using heavy element isotope ratios and multielement concentrations.

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

    PubMed

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

    2012-04-29

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

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

    PubMed Central

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

    2009-01-01

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

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

    PubMed

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

    2016-04-01

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

  20. Chemometric evaluation of time-of-flight secondary ion mass spectrometry data of minerals in the frame of future in situ analyses of cometary material by COSIMA onboard ROSETTA.

    PubMed

    Engrand, Cecile; Kissel, Jochen; Krueger, Franz R; Martin, Philippe; Silén, Johan; Thirkell, Laurent; Thomas, Roger; Varmuza, Kurt

    2006-01-01

    Chemometric data evaluation methods for time-of-flight secondary ion mass spectrometry (TOF-SIMS) have been tested for the characterization and classification of minerals. Potential applications of these methods include the expected data from cometary material to be measured by the COSIMA instrument onboard the ESA mission ROSETTA in the year 2014. Samples of the minerals serpentine, enstatite, olivine, and talc have been used as proxies for minerals existing in extraterrestrial matter. High mass resolution TOF-SIMS data allow the selection of peaks from inorganic ions relevant for minerals. Multivariate cluster analysis of peak intensity data by principal components analysis and the new method CORICO showed a good separation of the mineral classes. Classification by k nearest-neighbor classification (KNN) or binary decision trees (CART method) results in more than 90% correct class assignments in a leave-one-out cross validation.

  1. Can odors of TCM be captured by electronic nose? The novel quality control method for musk by electronic nose coupled with chemometrics.

    PubMed

    Ye, Tao; Jin, Cheng; Zhou, Jian; Li, Xingfeng; Wang, Haitao; Deng, Pingye; Yang, Ying; Wu, Yanwen; Xiao, Xiaohe

    2011-07-15

    Musk is a precious and wide applied material in traditional Chinese medicine, also, an important material for the perfume industry all over the world. To establish a rapid, cost-effective and relatively objective assessment for the quality of musk, different musk samples, including authentic, fake and adulterate, were collected. A oxide sensor based electronic nose (E-nose) was employed to measure the musk samples, the E-nose generated data were analyzed by principal component analysis (PCA), the responses of 18 sensors of E-nose were evaluated by loading analysis. Results showed that a rapid evaluation of complex response of the samples could be obtained, in combination with PCA and the perception level of the E-nose was given better results in the recognition values of the musk aroma. The authentic, fake and adulterate musk could be distinguished by E-nose coupled with PCA, sensor 2, 3, 5, 12, 15 and 17 were found to be able to better discriminate between musk samples, confirming the potential application of an electronic instrument coupled with chemometrics for a rapid and on-line quality control for the traditional medicines.

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

    PubMed

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

    2017-01-15

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2017-01-15

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

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

    PubMed

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

    2016-07-01

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

  7. Evaluation of the anthropogenic influx of metal and metalloid contaminants into the Moulay Bousselham lagoon, Morocco, using chemometric methods coupled to geographical information systems.

    PubMed

    Maanan, Mehdi; Landesman, Catherine; Maanan, Mohamed; Zourarah, Bendahhou; Fattal, Paul; Sahabi, Mohamed

    2013-07-01

    Superficial and cored sediment samples from the Moulay Bousselham lagoon and sub-watershed were analyzed for Al, Fe, Cu, Zn, Pb, Mn, Ni, Cr, As, Hg, and Cd. The temporal and spatial distributions of the main contamination sources of heavy metals were identified and described using chemometric and geographic information system (GIS) methods. Sediments from coastal lagoons near urban and agricultural areas are commonly contaminated with heavy metals, and the concentrations found in surface sediments are significantly higher than those from 50-100 years ago. The concentrations of these elements decrease sharply with depth in the sediment column, and the elements are preferentially enriched in the <2-μm-sized fraction of the sediment. The zones of enhanced risk of heavy metals were detected by means of GIS-based geostatistical modeling. According to sediment pollution indices and statistical analysis, heavy metals (Pb, Cu, Ni, Zn, Cr, and Hg) that pose a risk have become largely enriched in the lagoon sediments during the recent period of agricultural intensification.

  8. Chemometric assisted ultrasound leaching-solid phase extraction followed by dispersive-solidification liquid-liquid microextraction for determination of organophosphorus pesticides in soil samples.

    PubMed

    Ahmadi, Kamyar; Abdollahzadeh, Yaser; Asadollahzadeh, Mehdi; Hemmati, Alireza; Tavakoli, Hamed; Torkaman, Rezvan

    2015-05-01

    Ultrasound leaching-solid phase extraction (USL-SPE) followed by dispersive-solidification liquid-liquid microextraction (DSLLME) was developed for preconcentration and determination of organophosphorus pesticides (OPPs) in soil samples prior gas chromatography-mass spectrometry analysis. At first, OPPs were ultrasonically leached from soil samples by using methanol. After centrifugation, the separated methanol was diluted to 50 mL with double-distillated water and passed through the C18 SPE cartridge. OPPs were eluted with 1 mL acetonitrile. Thus, 1 mL acetonitrile extract (disperser solvent) and 10 µL 1-undecanol (extraction solvent) were added to 5 mL double-distilled water and a DSLLME technique was applied. The variables of interest in the USL-SPE-DSLLME method were optimized with the aid of chemometric approaches. First, in screening experiments, fractional factorial design (FFD) was used for selecting the variables which significantly affected the extraction procedure. Afterwards, the significant variables were optimized using response surface methodology (RSM) based on central composite design (CCD). Under the optimum conditions, the enrichment factors were 6890-8830. The linear range was 0.025-625 ng g(-1) and limits of detection (LODs) were between 0.012 and 0.2 ng g(-1). The relative standard deviations (RSDs) were in the range of 4.06-8.9% (n=6). The relative recoveries of OPPs from different soil samples were 85-98%.

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

    PubMed

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

    2016-07-01

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

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

    PubMed Central

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

    2015-01-01

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

  11. Combined effects of reduced malaxation oxygen levels and storage time on extra-virgin olive oil volatiles investigated by a novel chemometric approach.

    PubMed

    Raffo, Antonio; Bucci, Remo; D'Aloise, Antonio; Pastore, Gianni

    2015-09-01

    Combined effects of oxygen level reduction in the malaxation headspace and storage time up to 6 months on the volatile composition of a monovarietal extra-virgin olive oil (EVOO), obtained from cv. Carboncella olives, were investigated by applying a full factorial design approach (4 oxygen levels × 4 storage times) on EVOOs extracted on an industrial scale in two mills, equipped with "two-phase" and "three-phase" centrifugation systems, respectively. The outcoming data were analysed by the chemometric technique called ANOVA-simultaneous component analysis (ASCA). Both reduction of oxygen malaxation levels and storage time significantly affected the volatile profile of the extracted EVOOs. Reduction of oxygen malaxation levels hindered the formation of lipoxygenase derived volatiles (hexanal, 1-hexanol, (Z)-2-hexenal, (E)-2-hexen-1-ol, (Z)-2-penten-1-ol, 2,4-hexadienals), whereas prolonged storage times were associated with increased levels of autoxidation products (octane, hexanal, C10 hydrocarbons) and other compounds that could originate from exogenous microbial activity (1-octen-3-ol, 6-methyl-5-hepten-2-one, benzaldehyde, methyl salicylate). PMID:25842336

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

    PubMed

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

    2016-11-01

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

  13. Large volume sample stacking with EOF and sweeping in CE for determination of common preservatives in cosmetic products by chemometric experimental design.

    PubMed

    Cheng, Yi-Cian; Wang, Chun-Chi; Chen, Yen-Ling; Wu, Shou-Mei

    2012-05-01

    This study proposes a capillary electrophoresis method incorporating large volume sample stacking, EOF and sweeping for detection of common preservatives used in cosmetic products. The method was developed using chemometric experimental design (fractional factorial design and central composite design) to determine multiple separation variables by efficient steps. The samples were loaded by hydrodynamic injection (10 psi, 90 s), and separated by phosphate buffer (50 mM, pH 3) containing 30% methanol and 80 mM SDS at -20 kV. During method validation, calibration curves were found to be linear over a range of 5-100 μg/mL for butyl paraben and isobutyl paraben; 0.05-10 μg/mL for ethyl paraben; 0.2-50 μg/mL for dehydroacetic acid; 0.5-70 μg/mL for methyl paraben; 5-350 μg/mL for sorbic acid; 0.02-450 μg/mL for p-hydroxybenzoic acid and 0.05-10 μg/mL for salicylic acid and benzoic acid. The analytes were analysed simultaneously and their detection limits (S/N = 3) were down to 0.005-2 μg/mL. The analysis method was successfully used for detection of preservatives used in commercial cosmetics.

  14. Application of headspace sorptive extraction and gas chromatographic/mass spectrometric and chemometric methods to the quantification of pine nuts and pecorino in Pesto Genovese.

    PubMed

    Zunin, Paola; Leardi, Riccardo; Boggia, Raffaella

    2009-01-01

    Headspace sorptive extraction and GC/MS, coupled with chemometric tools, were used to predict the amounts of pine nuts and Pecorino in Pesto Genovese, a typical Italian basil-based pasta sauce. Two groups of samples were prepared at different times and with ingredients from different batches for building the predicting models and testing their performances. Principal component analysis and partial least-squares regression (PLS) were applied to the chromatographic data. The 24 most-predictive variables were selected, and the application of PLS to the training set samples led to two models that explained approximately 70% of the variance in cross-validation, with prediction errors of 0.1 g for Pecorino and 0.6 g for pine nuts, thus confirming the reliability of the analytical method and the predicting ability of the models. The results obtained for the test set samples were not completely satisfactory, with a prediction error and a bias of 5.0 and -4.1 g, respectively, for Pecorino and corresponding values of 4.1 and 2.0 g for pine nuts. This preliminary study shows that the analytical methods used can allow construction of models with high predictive ability only if the great variability of the headspace composition of the ingredients and the effect of Twister are considered.

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

    PubMed

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

    2015-11-01

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

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

    PubMed

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

    2015-11-01

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

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

    PubMed

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

    2016-10-01

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

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

    PubMed

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

    2015-09-01

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

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

    PubMed

    Pojić, Milica; Rakić, Dušan; Lazić, Zivorad

    2015-01-01

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

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

    PubMed

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

    2015-08-19

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  2. Chemometric QSAR Modeling and In Silico Design of Antioxidant NO Donor Phenols

    PubMed Central

    Mitra, Indrani; Saha, Achintya; Roy, Kunal

    2011-01-01

    An acceleration of free radical formation within human system exacerbates the incidence of several life-threatening diseases. The systemic antioxidants often fall short for neutralizing the free radicals thereby demanding external antioxidant supplementation. Therein arises the need for development of new antioxidants with improved potency. In order to search for efficient antioxidant molecules, the present work deals with quantitative structure-activity relationship (QSAR) studies of a series of antioxidants belonging to the class of phenolic derivatives bearing NO donor groups. In this study, several QSAR models with appreciable statistical significance have been reported. Models were built using various chemometric tools and validated both internally and externally. These models chiefly infer that presence of substituted aromatic carbons, long chain branched substituents, an oxadiazole-N-oxide ring with an electronegative atom containing group substituted at the 5 position and high degree of methyl substitutions of the parent moiety are conducive to the antioxidant activity profile of these molecules. The novelty of this work is not only that the structural attributes of NO donor phenolic compounds required for potent antioxidant activity have been explored in this study, but new compounds with possible antioxidant activity have also been designed and their antioxidant activity has been predicted in silico. PMID:21617771

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

    PubMed

    Pojić, Milica; Rakić, Dušan; Lazić, Zivorad

    2015-01-01

    A chemometric approach was applied for the optimization of the robustness of the NIRS method for wheat quality control. Due to the high number of experimental (n=6) and response variables to be studied (n=7) the optimization experiment was divided into two stages: screening stage in order to evaluate which of the considered variables were significant, and optimization stage to optimize the identified factors in the previously selected experimental domain. The significant variables were identified by using fractional factorial experimental design, whilst Box-Wilson rotatable central composite design (CCRD) was run to obtain the optimal values for the significant variables. The measured responses included: moisture, protein and wet gluten content, Zeleny sedimentation value and deformation energy. In order to achieve the minimal variation in responses, the optimal factor settings were found by minimizing the propagation of error (POE). The simultaneous optimization of factors was conducted by desirability function. The highest desirability of 87.63% was accomplished by setting up experimental conditions as follows: 19.9°C for sample temperature, 19.3°C for ambient temperature and 240V for instrument voltage. PMID:25281098

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

    PubMed

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

    2015-01-01

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

  5. Process monitored spectrophotometric titration coupled with chemometrics for simultaneous determination of mixtures of weak acids.

    PubMed

    Liao, Lifu; Yang, Jing; Yuan, Jintao

    2007-05-15

    A new spectrophotometric titration method coupled with chemometrics for the simultaneous determination of mixtures of weak acids has been developed. In this method, the titrant is a mixture of sodium hydroxide and an acid-base indicator, and the indicator is used to monitor the titration process. In a process of titration, both the added volume of titrant and the solution acidity at each titration point can be obtained simultaneously from an absorption spectrum by least square algorithm, and then the concentration of each component in the mixture can be obtained from the titration curves by principal component regression. The method only needs the information of absorbance spectra to obtain the analytical results, and is free of volumetric measurements. The analyses are independent of titration end point and do not need the accurate values of dissociation constants of the indicator and the acids. The method has been applied to the simultaneous determination of the mixtures of benzoic acid and salicylic acid, and the mixtures of phenol, o-chlorophenol and p-chlorophenol with satisfactory results.

  6. Chemometric QSAR modeling and in silico design of antioxidant NO donor phenols.

    PubMed

    Mitra, Indrani; Saha, Achintya; Roy, Kunal

    2011-03-01

    An acceleration of free radical formation within human system exacerbates the incidence of several life-threatening diseases. The systemic antioxidants often fall short for neutralizing the free radicals thereby demanding external antioxidant supplementation. Therein arises the need for development of new antioxidants with improved potency. In order to search for efficient antioxidant molecules, the present work deals with quantitative structure-activity relationship (QSAR) studies of a series of antioxidants belonging to the class of phenolic derivatives bearing NO donor groups. In this study, several QSAR models with appreciable statistical significance have been reported. Models were built using various chemometric tools and validated both internally and externally. These models chiefly infer that presence of substituted aromatic carbons, long chain branched substituents, an oxadiazole-N-oxide ring with an electronegative atom containing group substituted at the 5 position and high degree of methyl substitutions of the parent moiety are conducive to the antioxidant activity profile of these molecules. The novelty of this work is not only that the structural attributes of NO donor phenolic compounds required for potent antioxidant activity have been explored in this study, but new compounds with possible antioxidant activity have also been designed and their antioxidant activity has been predicted in silico.

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

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

    PubMed

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

    2015-06-15

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

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

    PubMed

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

    2015-06-15

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

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

    PubMed

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

    2016-06-01

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

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

    PubMed