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Cruz-Tirado JP, Lima Brasil Y, Freitas Lima A, Alva Pretel H, Teixeira Godoy H, Barbin D, Siche R. Rapid and non-destructive cinnamon authentication by NIR-hyperspectral imaging and classification chemometrics tools. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 289:122226. [PMID: 36512964 DOI: 10.1016/j.saa.2022.122226] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 11/30/2022] [Accepted: 12/05/2022] [Indexed: 06/17/2023]
Abstract
Cinnamon is a valuable aromatic spice widely used in pharmaceutical and food industry. Commonly, two-cinnamon species are available in the market, Cinnamomum verum (true cinnamon), cropped only in Sri Lanka, and Cinnamomum cassia (false cinnamon), cropped in different geographical origins. Thus, this work aimed to develop classification models based on NIR-hyperspectral imaging (NIR-HSI) coupled to chemometrics to classify C. verum and C. cassia sticks. First, principal component analysis (PCA) was applied to explore hyperspectral images. Scores surface displayed the high similarity between species supported by comparable macronutrient concentration. PC3 allowed better class differentiation compared to PC1 and PC2, with loadings exhibiting peaks related to phenolics/aromatics compounds, such as coumarin (C. cassia) or catechin (C. verum). Partial least square discriminant analysis (PLS-DA) and Support vector machine (SVM) reached similar performance to classify samples according to origin, with error = 3.3 % and accuracy = 96.7 %. A permutation test with p < 0.05 validated PLS-DA predictions have real spectral data dependency, and they are not result of chance. Pixel-wise (approach A) and sample-wise (approach B, C and D) classification maps reached a correct classification rate (CCR) of 98.3 % for C. verum and 100 % for C. cassia. NIR-HSI supported by classification chemometrics tools can be used as reliable analytical method for cinnamon authentication.
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Affiliation(s)
- J P Cruz-Tirado
- Department of Food Engineering, School of Food Engineering, University of Campinas, Campinas, SP, Brazil
| | - Yasmin Lima Brasil
- Department of Food Engineering, School of Food Engineering, University of Campinas, Campinas, SP, Brazil
| | - Adriano Freitas Lima
- Department of Food Science, School of Food Engineering, University of Campinas, Campinas, SP, Brazil
| | - Heiler Alva Pretel
- Escuela de Ingeniería Agroindustrial, Facultad de Ciencias Agropecuarias, Universidad Nacional de Trujillo, Av. Juan Pablo II s/n, Trujillo, Peru
| | - Helena Teixeira Godoy
- Department of Food Science, School of Food Engineering, University of Campinas, Campinas, SP, Brazil
| | - Douglas Barbin
- Department of Food Engineering, School of Food Engineering, University of Campinas, Campinas, SP, Brazil
| | - Raúl Siche
- Escuela de Ingeniería Agroindustrial, Facultad de Ciencias Agropecuarias, Universidad Nacional de Trujillo, Av. Juan Pablo II s/n, Trujillo, Peru.
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Applications of UV–Visible, Fluorescence and Mid-Infrared Spectroscopic Methods Combined with Chemometrics for the Authentication of Apple Vinegar. Foods 2023; 12:foods12061139. [PMID: 36981065 PMCID: PMC10048337 DOI: 10.3390/foods12061139] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/02/2023] [Accepted: 03/06/2023] [Indexed: 03/11/2023] Open
Abstract
Spectroscopic techniques as untargeted methods have great potential in food authentication studies, and the evaluation of spectroscopic data with chemometric methods can provide accurate predictions of adulteration even for hard-to-identify cases such as the mixing of vinegar with adulterants having a very similar chemical nature. In this study, we aimed to compare the performances of three spectroscopic methods (fluorescence, UV–visible, mid-infrared) in the detection of acetic-acid/apple-vinegar and spirit-vinegar/apple-vinegar mixtures (1–50%). Data obtained with the three spectroscopic techniques were used in the generation of classification models with partial least square discriminant analysis (PLS-DA) and orthogonal partial least square discriminant analysis (OPLS-DA) to differentiate authentic and mixed samples. An improved classification approach was used in choosing the best models through a number of calibration and validation sets. Only the mid-infrared data provided robust and accurate classification models with a high classification rate (up to 96%), sensitivity (1) and specificity (up to 0.96) for the differentiation of the adulterated samples from authentic apple vinegars. Therefore, it was concluded that mid-infrared spectroscopy is a useful tool for the rapid authentication of apple vinegars and it is essential to test classification models with different datasets to obtain a robust model.
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Tessaro L, da Silva Mutz Y, Lelis CA, Andrade JCD, Aquino A, Panzenhagen P, Ochioni AC, Sousa Vieira IR, Conte-Junior CA. Combination of RT-LAMP and fluorescence spectroscopy using chemometric techniques for an ultra-sensitive and rapid alternative for the detection of SARS-CoV-2. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2022; 14:4922-4930. [PMID: 36426753 DOI: 10.1039/d2ay01502a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
The increased spread of COVID-19 caused by SARS-CoV-2 has made it necessary to develop more efficient, fast, accurate, specific, sensitive and easy-to-use detection platforms to overcome the disadvantages of gold standard methods (RT-qPCR). Here an approach was developed for the detection of the SARS-CoV-2 virus using the loop-mediated isothermal amplification (LAMP) technique for SARS-CoV-2 RNA target amplification in samples of nasopharyngeal swabs. The discrimination between positive and negative SARS-CoV-2 samples was achieved by using fluorescence spectra generated by the excitation of the LAMP's DNA intercalator dye at λ497 nm in a fluorescence spectrophotometer and chemometric tools. Exploratory analysis of the 83 sample spectra using principal component analysis (PCA) indicated a trend in differentiation between positive and negative samples resulting from the peak emission of the fluorescent dye. The classification was performed by partial least squares discriminant analysis (PLS-DA) achieving a sensitivity, a specificity and an accuracy of 100%, 95% and 89%, respectively for the discrimination between negative and positive samples from 1.58 to 0.25 ng L-1 after LAMP amplification. Therefore, this study indicates that the use of the LAMP technique in fluorescence spectroscopy may offer a fast (<1 hour), sensitive and low-cost method.
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Affiliation(s)
- Leticia Tessaro
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, Rio de Janeiro RJ, 21941-598, Brazil
- Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, Brazil
- Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil
- Post-Graduation Program of Chemistry (PGQu), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro, RJ, Brazil
| | - Yhan da Silva Mutz
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, Rio de Janeiro RJ, 21941-598, Brazil
- Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, Brazil
- Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil
| | - Carini Aparecida Lelis
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, Rio de Janeiro RJ, 21941-598, Brazil
- Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, Brazil
- Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil
| | - Jelmir Craveiro de Andrade
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, Rio de Janeiro RJ, 21941-598, Brazil
- Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, Brazil
- Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil
- Post-Graduation Program of Chemistry (PGQu), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro, RJ, Brazil
| | - Adriano Aquino
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, Rio de Janeiro RJ, 21941-598, Brazil
- Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, Brazil
- Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil
- Post-Graduation Program of Chemistry (PGQu), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro, RJ, Brazil
| | - Pedro Panzenhagen
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, Rio de Janeiro RJ, 21941-598, Brazil
- Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, Brazil
- Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil
| | - Alan Clavelland Ochioni
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, Rio de Janeiro RJ, 21941-598, Brazil
- Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, Brazil
- Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil
| | - Italo Rennan Sousa Vieira
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, Rio de Janeiro RJ, 21941-598, Brazil
- Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, Brazil
- Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil
| | - Carlos Adam Conte-Junior
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, Rio de Janeiro RJ, 21941-598, Brazil
- Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, Brazil
- Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil
- Post-Graduation Program of Chemistry (PGQu), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro, RJ, Brazil
- Department of Biochemistry, Institute of Chemistry, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, RJ, 21941-901, Brazil
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Unsupervised recognition of components from the interaction of BSA with Fe cluster in different conditions utilizing 2D fluorescence spectroscopy. Sci Rep 2022; 12:16875. [PMID: 36207446 PMCID: PMC9547014 DOI: 10.1038/s41598-022-20768-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 09/16/2022] [Indexed: 11/08/2022] Open
Abstract
The excitation-emission fluorescence spectroscopy combined with three-way analysis was applied for discriminating the pure BSA and BSA/Fe3O(OAc)6ClO4 (Fe) using unsupervised classification methods. Herein, the interaction of bovine serum albumin (BSA) and Fe clusters as an artificial enzyme is studied by extracting the intrinsic excitation-emission (EEM) fluorescence of BSA. The conformation of BSA changes with pH, temperature, and Fe concentration. Three-way fluorescence data were recorded for BSA and BSA/Fe during different days. The obtained results showed that the Fe clusters cause changes in the structure of BSA conformation as a function of pH, temperature, and Fe concentration. Also, the denaturation pathway of the BSA molecule is significantly different in the presence of Fe clusters. Both techniques of PARAFAC and PCA were used in the excitation-emission fluorescence matrices (EEM) of solutions at three different pH (5.0, 7.0, and 9.0) and temperatures (15.0, 25.0, and 35.0 °C) values. Also, we reported the results of the change in concentrations of Fe (4.0, 6.0, and 8.0 mg) using these methods. These three amino acids (tyrosine, tryptophan, and phenylalanine) indicate all datasets and their similarities and differences. The spectral differences were more remarkable in different pH values compared to different temperatures. Also, we could distinguish between the groups of protein samples properly in different concentrations of Fe using low-cost EEM spectral images and PARAFAC.
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PALOMINO-VASCO M, RODRÍGUEZ-CÁCERES MI, MORA-DÍEZ N. DISCRIMINATION BASED ON COMMERCIAL/CRAFT ORIGIN AND ON LAGER/ALE FERMENTATION OF UNDILUTED SPANISH BEER SAMPLES- FRONT-FACE EXCITATION-EMISSION MATRICES AND CHEMOMETRICS. J Food Compost Anal 2022. [DOI: 10.1016/j.jfca.2022.104946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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6
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Buvé C, Saeys W, Rasmussen MA, Neckebroeck B, Hendrickx M, Grauwet T, Van Loey A. Application of multivariate data analysis for food quality investigations: An example-based review. Food Res Int 2022; 151:110878. [PMID: 34980408 DOI: 10.1016/j.foodres.2021.110878] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 11/29/2021] [Accepted: 12/04/2021] [Indexed: 11/15/2022]
Abstract
These days, large multivariate data sets are common in the food research area. This is not surprising as food quality, which is important for consumers, and its changes are the result of a complex interplay of multiple compounds and reactions. In order to comprehensively extract information from these data sets, proper data analysis tools should be applied. The application of multivariate data analysis (MVDA) is therefore highly recommended. However, at present the use of MVDA for food quality investigations is not yet fully explored. This paper focusses on a number of MVDA methods (PCA (Principal Component Analysis), PLS (Partial Least Squares Regression), PARAFAC (Parallel Factor Analysis) and ASCA (ANOVA Simultaneous Component Analysis)) useful for food quality investigations. The terminology, main steps and the theoretical basis of each method will be explained. As this is an example-based review, each method was applied on the same experimental data set to give the reader an idea about each selected MVDA method and to make a comparison between the outcomes. Numerous MVDA methods are available in literature. Which method to select depends on the data set and objective. PCA should be the first choice for data exploration of two-dimensional data. For predictive purposes, PLS is the most appropriate method. Given an underlying experimental design, ASCA takes into account both the relation between the different variables and the design factors. In case of a multi-way data set, PARAFAC can be used for data exploration. While these methods have already proven their value in research, there is a need to further explore their potential to investigate the complex interplay of compounds and reactions contributing to food quality. With this work we would like to encourage food scientists with no or limited knowledge of MVDA to get some first insights into the selected methods.
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Affiliation(s)
- Carolien Buvé
- KU Leuven Department of Microbial and Molecular Systems, Laboratory of Food Technology, Kasteelpark Arenberg 22 Box 2457, 3001 Leuven, Belgium
| | - Wouter Saeys
- KU Leuven Department of Biosystems, MeBioS division, Kasteelpark Arenberg 30, 3001 Leuven, Belgium
| | - Morten Arendt Rasmussen
- University of Copenhagen, Department of Food Science, Faculty of Science, Rolighedsvej 26, 1958 Frederiksberg, Denmark; COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Bram Neckebroeck
- KU Leuven Department of Microbial and Molecular Systems, Laboratory of Food Technology, Kasteelpark Arenberg 22 Box 2457, 3001 Leuven, Belgium
| | - Marc Hendrickx
- KU Leuven Department of Microbial and Molecular Systems, Laboratory of Food Technology, Kasteelpark Arenberg 22 Box 2457, 3001 Leuven, Belgium
| | - Tara Grauwet
- KU Leuven Department of Microbial and Molecular Systems, Laboratory of Food Technology, Kasteelpark Arenberg 22 Box 2457, 3001 Leuven, Belgium
| | - Ann Van Loey
- KU Leuven Department of Microbial and Molecular Systems, Laboratory of Food Technology, Kasteelpark Arenberg 22 Box 2457, 3001 Leuven, Belgium.
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Ríos-Reina R, Camiña JM, Callejón RM, Azcarate SM. Spectralprint techniques for wine and vinegar characterization, authentication and quality control: Advances and projections. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2020.116121] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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Palomino-Vasco M, Acedo-Valenzuela MI, Rodríguez-Cáceres MI, Mora-Díez N. Monitoring winemaking process using tyrosine influence in the excitation-emission matrices of wine. Food Chem 2020; 344:128721. [PMID: 33272754 DOI: 10.1016/j.foodchem.2020.128721] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 11/17/2020] [Accepted: 11/20/2020] [Indexed: 11/28/2022]
Abstract
Wine samples collected during the winemaking process have been analyzed employing a previously optimized UHPLC-FD method, determining their biogenic amines and amino acids profile. The results obtained have been submitted to a statistical analysis from which it was extracted that the most influential analyte was tyrosine. Thanks to its fluorescence, a method for its determination by excitation-emission matrices has been proposed. The accuracy of the method has been checked by means of Elliptical Joint Confidence Region test. The winemaking process has been monitored with this method, obtaining a faster and cheaper way to follow the process.
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Affiliation(s)
- Mónica Palomino-Vasco
- Department of Analytical Chemistry and Research Institute on Water, Climate Change and Sustainability (IACYS), Faculty of Sciences, University of Extremadura, Badajoz 06006, Spain.
| | - María Isabel Acedo-Valenzuela
- Department of Analytical Chemistry and Research Institute on Water, Climate Change and Sustainability (IACYS), Faculty of Sciences, University of Extremadura, Badajoz 06006, Spain
| | - María Isabel Rodríguez-Cáceres
- Department of Analytical Chemistry and Research Institute on Water, Climate Change and Sustainability (IACYS), Faculty of Sciences, University of Extremadura, Badajoz 06006, Spain
| | - Nielene Mora-Díez
- Department of Analytical Chemistry and Research Institute on Water, Climate Change and Sustainability (IACYS), Faculty of Sciences, University of Extremadura, Badajoz 06006, Spain
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Rocha WFDC, do Prado CB, Blonder N. Comparison of Chemometric Problems in Food Analysis Using Non-Linear Methods. Molecules 2020; 25:E3025. [PMID: 32630676 PMCID: PMC7411792 DOI: 10.3390/molecules25133025] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 06/25/2020] [Accepted: 06/29/2020] [Indexed: 11/16/2022] Open
Abstract
Food analysis is a challenging analytical problem, often addressed using sophisticated laboratory methods that produce large data sets. Linear and non-linear multivariate methods can be used to process these types of datasets and to answer questions such as whether product origin is accurately labeled or whether a product is safe to eat. In this review, we present the application of non-linear methods such as artificial neural networks, support vector machines, self-organizing maps, and multi-layer artificial neural networks in the field of chemometrics related to food analysis. We discuss criteria to determine when non-linear methods are better suited for use instead of traditional methods. The principles of algorithms are described, and examples are presented for solving the problems of exploratory analysis, classification, and prediction.
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Affiliation(s)
- Werickson Fortunato de Carvalho Rocha
- National Institute of Metrology, Quality and Technology (INMETRO), Av. N. S. das Graças, 50, Xerém, Duque de Caxias 25250-020, RJ, Brazil; (W.F.C.R.); (C.B.d.P.)
- National Institute of Standards and Technology (NIST), 100 Bureau Drive, Stop 8390 Gaithersburg, MD 20899, USA
| | - Charles Bezerra do Prado
- National Institute of Metrology, Quality and Technology (INMETRO), Av. N. S. das Graças, 50, Xerém, Duque de Caxias 25250-020, RJ, Brazil; (W.F.C.R.); (C.B.d.P.)
| | - Niksa Blonder
- National Institute of Standards and Technology (NIST), 100 Bureau Drive, Stop 8390 Gaithersburg, MD 20899, USA
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Lia F, Formosa JP, Zammit-Mangion M, Farrugia C. The First Identification of the Uniqueness and Authentication of Maltese Extra Virgin Olive Oil Using 3D-Fluorescence Spectroscopy Coupled with Multi-Way Data Analysis. Foods 2020; 9:foods9040498. [PMID: 32326532 PMCID: PMC7230349 DOI: 10.3390/foods9040498] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 04/06/2020] [Accepted: 04/13/2020] [Indexed: 11/16/2022] Open
Abstract
The potential application of multivariate three-way data analysis techniques, namely parallel factor analysis (PARAFAC) and discriminant multi-way partial least squares regression (DN-PLSR), on three-dimensional excitation emission matrix (3D-EEM) fluorescent data were used to identify the uniqueness and authenticity of Maltese extra virgin olive oil (EVOO). A non-negativity constrained PARAFAC model revealed that a four-component model provided the most appropriate solution. Examination of the extracted components in mode 2 and 3 showed that these belonged to different fluorophores present in extra virgin olive oil. Application of linear discriminate analysis (LDA) and binary logistic regression analysis on the concentration of the four extracted fluorophores, showed that it is possible to discriminate Maltese EVOOs from non-Maltese EVOOs. The application of DN-PLSR provided superior means for discrimination of Maltese EVOOs. Further inspection of the extracted latent variables and their variable importance plots (VIPs) provided strong proof of the existence of four types of fluorophores present in EVOOs and their potential application for the discrimination of Maltese EVOOs.
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Affiliation(s)
- Frederick Lia
- Department of Chemistry, University of Malta, 2080 Msida MSD, Malta; (J.P.F.); (C.F.)
- Correspondence:
| | - Jean Paul Formosa
- Department of Chemistry, University of Malta, 2080 Msida MSD, Malta; (J.P.F.); (C.F.)
| | - Marion Zammit-Mangion
- Department of Physiology and Biochemistry, University of Malta, 2080 Msida MSD, Malta;
| | - Claude Farrugia
- Department of Chemistry, University of Malta, 2080 Msida MSD, Malta; (J.P.F.); (C.F.)
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11
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Ríos-Reina R, Azcarate SM, Camiña JM, Callejón RM. Sensory and spectroscopic characterization of Argentinean wine and balsamic vinegars: A comparative study with European vinegars. Food Chem 2020; 323:126791. [PMID: 32330651 DOI: 10.1016/j.foodchem.2020.126791] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Revised: 03/18/2020] [Accepted: 04/10/2020] [Indexed: 01/17/2023]
Abstract
In Argentina, vinegars are cheap agro-food products without exhaustive regulation and the production of high-quality vinegars has not been exploited yet. In fact, Argentinean vinegars have not been studied. In this context, a first study of Argentinean balsamic and wine vinegars was carried out by a sensory and spectroscopic characterization and by a comparison with well-recognized European vinegars. For that, ultraviolet-visible and fluorescence spectroscopies were applied together with principal component analysis (PCA) and parallel factor analysis (PARAFAC) performed on each data set, respectively. Results showed differences between acetification processes, origin countries and a wide variability within Argentinean production. The sensory characterization on Argentinean wine vinegars was performed by triangular and ordering preference tests showing statistically significant preferences toward the traditional and the rapid vinegars. This work highlights the effect of production on quality in order to provide added value to the Argentinean vinegars.
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Affiliation(s)
- R Ríos-Reina
- Área de Nutrición y Bromatología, Fac. Farmacia, Univ. Sevilla, C/P. García Gonzalez no. 2, E-41012 Sevilla, Spain
| | - S M Azcarate
- CONICET-Facultad de Ciencias Exactas y Naturales, Universidad Nacional de La Pampa, and Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP), Santa Rosa, Argentina.
| | - J M Camiña
- CONICET-Facultad de Ciencias Exactas y Naturales, Universidad Nacional de La Pampa, and Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP), Santa Rosa, Argentina
| | - R M Callejón
- Área de Nutrición y Bromatología, Fac. Farmacia, Univ. Sevilla, C/P. García Gonzalez no. 2, E-41012 Sevilla, Spain.
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12
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Kong D, Cui Y, Kong L, Wang S. Classification of oil pollutants based on excitation-emission matrix fluorescence spectroscopy and two-dimensional discriminant analysis. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2020; 228:117799. [PMID: 31806481 DOI: 10.1016/j.saa.2019.117799] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Revised: 11/10/2019] [Accepted: 11/14/2019] [Indexed: 06/10/2023]
Abstract
Excitation-Emission Matrix (EEM) Fluorescence spectroscopy and two-dimensional (2D) discriminant analysis were used to classify oil pollutants. Firstly, the EEM fluorescence spectroscopy of the oil samples was collected using the FS920 steady-state fluorescence spectrometer, and EEM was preprocessed by removing scattering and normalization. Secondly, EEM was analyzed and characterized by parallel factor analysis (PARAFAC). Finally, all the collected samples were divided into training and test sets by the Kennard-Stone algorithm. The classification models of the training set samples were established by using 2D-PCA, 2D-LDA, PARAFAC-2DPCA, PARAFAC-2DLDA, PARAFAC-LDA and NPLS-DA algorithms, respectively. These models were then used to classify test set samples. The classification performance of the used models was assessed by accuracy, sensitivity and specificity. The best classification results in the used models were obtained by using 2D-PCA and 2D-LDA with 95% and 95% accuracy, respectively. These results provide an important reference for classification of oil pollutants.
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Affiliation(s)
- Deming Kong
- School of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China; Department of Telecommunications and Information Processing, Ghent University, B-9000 Ghent, Belgium
| | - Yaoyao Cui
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China.
| | - Lingfu Kong
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China
| | - Shutao Wang
- School of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China
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Dramićanin T, Zeković I, Periša J, Dramićanin MD. The Parallel Factor Analysis of Beer Fluorescence. J Fluoresc 2019; 29:1103-1111. [PMID: 31396828 DOI: 10.1007/s10895-019-02421-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Accepted: 07/29/2019] [Indexed: 11/25/2022]
Abstract
Fluorescence excitation-emission matrices were measured for 111 samples of different types of beer and studied by the parallel factor analysis (PARAFAC). The 5-component PARAFAC model was found to suitably describes the beer fluorescence, accounting for 99.4% of the fluorescence variance in the measured set of samples, and providing the completely resolved excitation and emission spectra of each component. The model was chosen based on a model's core consistency and split-half analysis. It is shown that beer fluorescence is the sum of fluorescence of aromatic amino acids (tryptophan, tyrosine, and phenylalanine), different forms of vitamin B, and phenolic compounds. Obtained PARAFAC model of beer fluorescence demonstrated the potential for the quantification and quality analysis of beer fluorophores and classification of different beer types.
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Affiliation(s)
- Tatjana Dramićanin
- Vinča Institute of Nuclear Sciences, University of Belgrade, P.O. Box 522, Belgrade, 11001, Serbia
| | - Ivana Zeković
- Vinča Institute of Nuclear Sciences, University of Belgrade, P.O. Box 522, Belgrade, 11001, Serbia
| | - Jovana Periša
- Vinča Institute of Nuclear Sciences, University of Belgrade, P.O. Box 522, Belgrade, 11001, Serbia
| | - Miroslav D Dramićanin
- Vinča Institute of Nuclear Sciences, University of Belgrade, P.O. Box 522, Belgrade, 11001, Serbia.
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Developing an Excitation-Emission Matrix Fluorescence Spectroscopy Method Coupled with Multi-way Classification Algorithms for the Identification of the Adulteration of Shanxi Aged Vinegars. FOOD ANAL METHOD 2019. [DOI: 10.1007/s12161-019-01586-5] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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15
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Excitation-emission fluorescence as a tool to assess the presence of grape-must caramel in PDO wine vinegars. Food Chem 2019; 287:115-125. [DOI: 10.1016/j.foodchem.2019.02.008] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Revised: 01/28/2019] [Accepted: 02/02/2019] [Indexed: 11/17/2022]
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16
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Unsupervised classification of PSII with and without water-oxidizing complex samples by PARAFAC resolution of excitation-emission fluorescence images. JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY B-BIOLOGY 2019; 195:58-66. [PMID: 31100638 DOI: 10.1016/j.jphotobiol.2019.03.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Revised: 03/12/2019] [Accepted: 03/13/2019] [Indexed: 11/19/2022]
Abstract
The potential of excitation-emission fluorescence spectroscopy combined with three-way analysis was investigated for discriminating the photosystem II (PSII) (with the water-oxidizing complex) and without the water-oxidizing complex (wPSII) using unsupervised classification methods. The water-oxidizing complex within PSII carry out the reaction of water splitting which is as a vital process on the earth. Therefore, discriminating the presence of the water-oxidizing complex in protein samples is crucial. Low cost and accurate spectroscopic determination of the amount of clusters inside PSII or any other protein containing species are important when investigating the inclusion and exclusion of such clusters into and from species. Fluorescence data of samples were similar, and we showed the potential usefulness of multivariate methods, such as parallel factor analysis (PARAFAC) and principal component analysis (PCA) for recognition of the two types of samples. Both techniques were applied to the excitation-emission fluorescence matrices (EEM) of solutions at two of different pH values (2.0 and 12.0). Three fluorescent components were found for all samples that are related to tyrosine (Tyr), tryptophan (Trp) and phenylalanine (Phe) amino acids. These three amino acids are representative of all datasets and indicate their similarities and differences. We then found the effectual wavelengths for separation of samples in a specific acidity, including the excitation wavelengths of 220 and 230 nm and the emission wavelengths of 300 and 305 nm. The acidity of the solutions has various influences on the conformation of proteins. In PSII and PSII the without water-oxidizing complex samples conformational changes can change their spectra which was applied for discrimination purpose. This separation was better in pH = 12.0. We also showed the effect of time on small conformational changes within datasets were higher in pH = 2.0. In the end, for indicating the high distribution of spectral data from proteins which is the result of conformational changes, we compared the distribution of measured spectral data with that from a simple organic molecule, fluorescein. Altogether, we could distinguish between the two groups of protein samples properly at pH = 12.0 using low-cost EEM spectral images and PARAFAC.
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Ríos-Reina R, Callejón RM, Savorani F, Amigo JM, Cocchi M. Data fusion approaches in spectroscopic characterization and classification of PDO wine vinegars. Talanta 2019; 198:560-572. [PMID: 30876600 DOI: 10.1016/j.talanta.2019.01.100] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 01/25/2019] [Accepted: 01/29/2019] [Indexed: 11/24/2022]
Abstract
Spain is one of the major producers of high-quality wine vinegars having three protected designations of origin (a.k.a. PDOs): "Vinagre de Jerez", "Vinagre de Condado de Huelva" and "Vinagre de Montilla-Moriles". Their high prices due to their high quality and their high production costs explain the need for developing an adequate quality control technique and the interest in extensive characterization in order to capture the identity of each denomination. In this framework, methodologies based on non-targeted techniques, such as spectroscopies, are becoming popular in food authentication. Thus, for improving vinegar quality assessment, fusion of data blocks obtained from the same samples but different analytical techniques could be a good strategy, since the quantity and quality of sample knowledge could be enhanced providing new insights into the differentiation of vinegars. Therefore, the aim of this manuscript is the development of a multi-platform methodology and a model able to classify the Spanish wine vinegar PDOs. Sixty-five PDO wine vinegars were analyzed by four spectroscopic techniques: Fourier-transform mid-infrared spectroscopy (MIR), near infrared spectroscopy (NIR), multidimensional fluorescence spectroscopy (EEM) and proton nuclear magnetic resonance (1H-NMR). Two different data fusion strategies were evaluated: Mid-level data fusion with different preprocessing, and Common Component and Specific Weights analysis multiblock method. Exploratory and classification analysis on the data from individual techniques were also performed and compared with data fusion models. The data fusion models improved the classification, providing a more efficient differentiation, than the models based on single methods, and supporting the approach to combine these methods to achieve synergies for an optimized PDO differentiation.
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Affiliation(s)
- Rocío Ríos-Reina
- Dpto. de Nutrición y Bromatología, Toxicología y Medicina Legal, Facultad de Farmacia, Universidad de Sevilla, C/P. García González n°2, E-41012 Sevilla, Spain.
| | - Raquel M Callejón
- Dpto. de Nutrición y Bromatología, Toxicología y Medicina Legal, Facultad de Farmacia, Universidad de Sevilla, C/P. García González n°2, E-41012 Sevilla, Spain
| | - Francesco Savorani
- Department of Applied Science and Technology (DISAT), Polytechnic University of Turin, Corso Duca degli Abruzzi 24, 10129 Torino, TO, Italy
| | - José M Amigo
- Chemometrics and Analytical Techniques, Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark
| | - Marina Cocchi
- Dipartimento di Scienze Chimiche e Geologiche, Università di Modena e Reggio Emilia, Via Campi 103, 41125 Modena, Italy.
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Sinanoglou VJ, Zoumpoulakis P, Fotakis C, Kalogeropoulos N, Sakellari A, Karavoltsos S, Strati IF. On the Characterization and Correlation of Compositional, Antioxidant and Colour Profile of Common and Balsamic Vinegars. Antioxidants (Basel) 2018; 7:E139. [PMID: 30314353 PMCID: PMC6210356 DOI: 10.3390/antiox7100139] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2018] [Revised: 10/05/2018] [Accepted: 10/05/2018] [Indexed: 01/23/2023] Open
Abstract
Commercially available common and balsamic vinegars were examined, using a combination of spectrophotometric, chromatographic, colorimetric and spectroscopic methods. Total phenolic content, antioxidant activity, radical scavenging capacity, phenolic profile, colour parameters, Fourier Transform Infrared (FT-IR) absorbance spectra and Nuclear Magnetic Resonance (¹H NMR) spectra were comparatively studied. The main scope was the assessment of vinegar antioxidant and metabolic profiles and the identification of the most appropriate features influencing their type and subtypes. Red grape balsamic vinegars exhibited the strongest antioxidant profile. High total phenolic content and radical scavenging-antioxidant activity of vinegars was strongly correlated with high hue-angle and colour density values and low lightness and a* values. FT-IR spectra analysis confirmed the presence of organic acids and carbohydrates and, in combination with Gas Chromatography-Mass Spectrometry (GC-MS), the occurrence of phenolic compounds. NMR spectroscopy enabled the identification of 27 characteristic metabolites in each type of vinegar. The combination of all applied techniques provides critical information on compositional differences among the vinegars and could serve as an application tool for similar fermentation products.
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Affiliation(s)
- Vassilia J Sinanoglou
- Laboratory of Chemistry, Analysis & Design of Food Processes, Department of Food Science and Technology, University of West Attica, Ag. Spyridonos, 12243 Egaleo, Greece.
| | - Panagiotis Zoumpoulakis
- Institute of Biology, Medicinal Chemistry & Biotechnology, National Hellenic Research Foundation, 48, Vas. Constantinou Ave., 11635 Athens, Greece.
| | - Charalambos Fotakis
- Institute of Biology, Medicinal Chemistry & Biotechnology, National Hellenic Research Foundation, 48, Vas. Constantinou Ave., 11635 Athens, Greece.
| | - Nick Kalogeropoulos
- Department of Dietetics-Nutrition, School of Health Science and Education, Harokopio University of Athens, Eleftheriou Venizelou 70, 17676 Kallithea, Greece.
| | - Aikaterini Sakellari
- Laboratory of Environmental Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimioupolis, Zografou, 15784 Athens, Greece.
| | - Sotirios Karavoltsos
- Laboratory of Environmental Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimioupolis, Zografou, 15784 Athens, Greece.
| | - Irini F Strati
- Laboratory of Chemistry, Analysis & Design of Food Processes, Department of Food Science and Technology, University of West Attica, Ag. Spyridonos, 12243 Egaleo, Greece.
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Azcarate SM, de Araújo Gomes A, Muñoz de la Peña A, Goicoechea HC. Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applications. Trends Analyt Chem 2018. [DOI: 10.1016/j.trac.2018.07.022] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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21
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Hu Y, Wu HL, Yin XL, Gu HW, Liu Z, Xiao R, Xie LX, Fang H, Yu RQ. A flexible and novel strategy of alternating trilinear decomposition method coupled with two-dimensional linear discriminant analysis for three-way chemical data analysis: Characterization and classification. Anal Chim Acta 2018; 1021:28-40. [DOI: 10.1016/j.aca.2018.03.050] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2017] [Revised: 03/11/2018] [Accepted: 03/15/2018] [Indexed: 10/17/2022]
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22
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Ríos-Reina R, García-González DL, Callejón RM, Amigo JM. NIR spectroscopy and chemometrics for the typification of Spanish wine vinegars with a protected designation of origin. Food Control 2018. [DOI: 10.1016/j.foodcont.2018.01.031] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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23
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Ortiz-Romero C, Ríos-Reina R, Morales ML, García-González DL, Callejón RM. A viability study of C–O isotope fingerprint for different geographical provenances of Spanish wine vinegars. Eur Food Res Technol 2018. [DOI: 10.1007/s00217-017-3026-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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24
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Ríos-Reina R, Callejón RM, Oliver-Pozo C, Amigo JM, García-González DL. ATR-FTIR as a potential tool for controlling high quality vinegar categories. Food Control 2017. [DOI: 10.1016/j.foodcont.2017.02.065] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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25
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Elemental characterisation of Andalusian wine vinegars with protected designation of origin by ICP-OES and chemometric approach. Food Control 2017. [DOI: 10.1016/j.foodcont.2016.12.006] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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26
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Ríos-Reina R, Elcoroaristizabal S, Ocaña-González JA, García-González DL, Amigo JM, Callejón RM. Characterization and authentication of Spanish PDO wine vinegars using multidimensional fluorescence and chemometrics. Food Chem 2017; 230:108-116. [PMID: 28407890 DOI: 10.1016/j.foodchem.2017.02.118] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2016] [Revised: 02/12/2017] [Accepted: 02/23/2017] [Indexed: 01/22/2023]
Abstract
This work assesses the potential of multidimensional fluorescence spectroscopy combined with chemometrics for characterization and authentication of Spanish Protected Designation of Origin (PDO) wine vinegars. Seventy-nine vinegars of different categories (aged and sweet) belonging to the Spanish PDOs "Vinagre de Jerez", "Vinagre de Montilla-Moriles" and "Vinagre de Condado de Huelva", were analyzed by excitation-emission fluorescence spectroscopy. A visual assessment of fluorescence landscapes pointed out different trends with vinegar categories. PARAllel FACtor analysis (PARAFAC) extracted the potential fluorophores and their values in the PDO vinegars. This information, coupled with different classification methods (Partial Least Square Discrimination Analysis "PLS-DA" and Support Vectors Machines "SVM"), was able to discriminate the wine vinegar category within each PDO, for which SVM models obtained better results (>92% of classification). In each category, SVM also allows the differentiation between PDOs. The proposed methodology could be used as an analysis method for the authentication of Spanish PDO wine vinegars.
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Affiliation(s)
- Rocío Ríos-Reina
- Área de Nutrición y Bromatología, Facultad de Farmacia, Universidad de Sevilla, C/P. García González n°2, E-41012 Sevilla, Spain
| | - Saioa Elcoroaristizabal
- Chemical and Environmental Engineering Department, Faculty of Engineering, University of the Basque Country, Alameda de Urquijo s/n, E-48013 Bilbao, Spain
| | - Juan A Ocaña-González
- Departamento Química Analítica, Facultad de Química, Universidad de Sevilla, C/P. García González s/n, E-41012 Sevilla, Spain
| | - Diego L García-González
- Instituto de la Grasa (CSIC), Campus University Pablo de Olavide - Building 46, Ctra. de Utrera, km. 1, E-41013 Sevilla, Spain
| | - José M Amigo
- Chemometric Analytical Technologies, Department of Food Sciences, Faculty of Science, University of Copenhagen, Rolighedsvej 30, Frederiksberg CDK-1958, Denmark
| | - Raquel M Callejón
- Área de Nutrición y Bromatología, Facultad de Farmacia, Universidad de Sevilla, C/P. García González n°2, E-41012 Sevilla, Spain.
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27
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A detection method of vegetable oils in edible blended oil based on three-dimensional fluorescence spectroscopy technique. Food Chem 2016; 212:72-7. [DOI: 10.1016/j.foodchem.2016.05.158] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2014] [Revised: 05/21/2016] [Accepted: 05/24/2016] [Indexed: 11/22/2022]
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28
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Cabrera-Bañegil M, Hurtado-Sánchez MDC, Galeano-Díaz T, Durán-Merás I. Front-face fluorescence spectroscopy combined with second-order multivariate algorithms for the quantification of polyphenols in red wine samples. Food Chem 2016; 220:168-176. [PMID: 27855885 DOI: 10.1016/j.foodchem.2016.09.152] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Revised: 09/19/2016] [Accepted: 09/24/2016] [Indexed: 12/19/2022]
Abstract
The potential of front-face fluorescence spectroscopy combined with second-order chemometric methods was investigated for the quantification of the main polyphenols present in wine samples. Parallel factor analysis (PARAFAC) and unfolded-partial least squares coupled to residual bilinearization (U-PLS/RBL) were assessed for the quantification of catechin, epicatechin, quercetin, resveratrol, caffeic acid, gallic acid, p-coumaric acid, and vanillic acid in red wines. Excitation-emission matrices of different red wine samples, without pretreatment, were obtained in front-face mode, recording emission between 290 and 450 nm, exciting between 240 and 290 nm, for the analysis of epicatechin, catechin, caffeic acid, gallic acid, and vanillic acid; and excitation and emission between 300-360 and 330-400nm, respectively, for the analysis of resveratrol. U-PLS/RBL algorithm provided the best results and this methodology was validated by an optimized liquid chromatographic coupled to diode array and fluorimetric detectors procedure, obtaining a very good correlation for vanillic acid, caffeic acid, epicatechin and resveratrol.
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Affiliation(s)
- Manuel Cabrera-Bañegil
- Technological Institute of Food and Agriculture (CICYTEX-INTAEX), Junta de Extremadura, Avda. Adolfo Suárez S/N, 06007 Badajoz, Spain
| | | | - Teresa Galeano-Díaz
- Department of Analytical Chemistry and Research Institute on Water, Climate Change and Sustainability (IACYS), University of Extremadura, 06006 Badajoz, Spain
| | - Isabel Durán-Merás
- Department of Analytical Chemistry and Research Institute on Water, Climate Change and Sustainability (IACYS), University of Extremadura, 06006 Badajoz, Spain.
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29
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Two-dimensional linear discriminant analysis for classification of three-way chemical data. Anal Chim Acta 2016; 938:53-62. [DOI: 10.1016/j.aca.2016.08.009] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2016] [Revised: 07/15/2016] [Accepted: 08/04/2016] [Indexed: 11/22/2022]
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30
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Enhancing Electronic Nose Performance Based on a Novel QPSO-KELM Model. SENSORS 2016; 16:s16040520. [PMID: 27077860 PMCID: PMC4851034 DOI: 10.3390/s16040520] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2016] [Revised: 03/27/2016] [Accepted: 04/07/2016] [Indexed: 01/08/2023]
Abstract
A novel multi-class classification method for bacteria detection termed quantum-behaved particle swarm optimization-based kernel extreme learning machine (QPSO-KELM) based on an electronic nose (E-nose) technology is proposed in this paper. Time and frequency domain features are extracted from E-nose signals used for detecting four different classes of wounds (uninfected and infected with Staphylococcu aureus, Escherichia coli and Pseudomonas aeruginosa) in this experiment. In addition, KELM is compared with five existing classification methods: Linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), extreme learning machine (ELM), k-nearest neighbor (KNN) and support vector machine (SVM). Meanwhile, three traditional optimization methods including particle swarm optimization algorithm (PSO), genetic algorithm (GA) and grid search algorithm (GS) and four kernel functions (Gaussian kernel, linear kernel, polynomial kernel and wavelet kernel) for KELM are discussed in this experiment. Finally, the QPSO-KELM model is also used to deal with another two experimental E-nose datasets in the previous experiments. The experimental results demonstrate the superiority of QPSO-KELM in various E-nose applications.
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31
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Azcarate SM, de Araújo Gomes A, Alcaraz MR, Ugulino de Araújo MC, Camiña JM, Goicoechea HC. Modeling excitation–emission fluorescence matrices with pattern recognition algorithms for classification of Argentine white wines according grape variety. Food Chem 2015; 184:214-9. [DOI: 10.1016/j.foodchem.2015.03.081] [Citation(s) in RCA: 64] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2014] [Revised: 03/21/2015] [Accepted: 03/23/2015] [Indexed: 11/30/2022]
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32
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Coelho C, Aron A, Roullier-Gall C, Gonsior M, Schmitt-Kopplin P, Gougeon RD. Fluorescence fingerprinting of bottled white wines can reveal memories related to sulfur dioxide treatments of the must. Anal Chem 2015; 87:8132-7. [PMID: 26190639 DOI: 10.1021/acs.analchem.5b00388] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
For the first time, Excitation Emission Matrix (EEM) fluorescence spectroscopy was combined with parallel factor statistical analysis (PARAFAC) and applied to a set of 320 dry white wines of the Chardonnay grape variety. A four component PARAFAC model (C1, C2, C3 and C4) best explained the variability of fluorescence signatures of white wines. Subtle changes were observed in EEMs of white wines from two different vintages (2006 and 2007), where different concentrations of sulfur dioxide (0, 4, and 8 g·hL(-1)) were added to the grape must at pressing. PARAFAC results clearly indicated that sulfur dioxide added to the must subsequently influenced white wine chemistry into three distinct sulfur dioxide dose-dependent aging mechanisms. For both vintages, C1 and C2 were the dominant components affected by sulfur dioxide and likely reacting with phenolic compounds associated with some presumably proteinaceous material. Distinct component combinations revealed either SO2 dependent or vintage-dependent signatures, thus, showing the extent of the complex versatile significance underlying such fluorescence spectra, even after several years of bottle aging.
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Affiliation(s)
- Christian Coelho
- †UMR PAM Université de Bourgogne/AgroSupDijon, Institut Universitaire de la Vigne et du Vin, Jules Guyot, Dijon, France
| | - Alissa Aron
- †UMR PAM Université de Bourgogne/AgroSupDijon, Institut Universitaire de la Vigne et du Vin, Jules Guyot, Dijon, France
| | - Chloé Roullier-Gall
- †UMR PAM Université de Bourgogne/AgroSupDijon, Institut Universitaire de la Vigne et du Vin, Jules Guyot, Dijon, France.,‡Research Unit Analytical BioGeoChemistry, Department of Environmental Sciences, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, 85764 Neuherberg, Germany.,§Chair of Analytical Food Chemistry, Technische Universität München, Alte Akademie 10, 85354 Freising-Weihenstephan, Germany
| | - Michael Gonsior
- ∥University of Maryland Center for Environmental Science, Chesapeake Biological Laboratory, Solomons, Maryland 20688, United States
| | - Philippe Schmitt-Kopplin
- ‡Research Unit Analytical BioGeoChemistry, Department of Environmental Sciences, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, 85764 Neuherberg, Germany.,§Chair of Analytical Food Chemistry, Technische Universität München, Alte Akademie 10, 85354 Freising-Weihenstephan, Germany
| | - Régis D Gougeon
- †UMR PAM Université de Bourgogne/AgroSupDijon, Institut Universitaire de la Vigne et du Vin, Jules Guyot, Dijon, France
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Shi W, Liu Y, Kong W, Shen Q. Tea Classification by Near Infrared Spectroscopy with Projection Discriminant Analysis and Gene Expression Programming. ANAL LETT 2015. [DOI: 10.1080/00032719.2015.1055574] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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34
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Polyphenolic Profile of Red Wines for the Discrimination of Controlled Designation of Origin. FOOD ANAL METHOD 2015. [DOI: 10.1007/s12161-015-0193-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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35
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Fluorescence spectroscopy coupled with PARAFAC and PLS DA for characterization and classification of honey. Food Chem 2015; 175:284-91. [DOI: 10.1016/j.foodchem.2014.11.162] [Citation(s) in RCA: 145] [Impact Index Per Article: 16.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2014] [Revised: 11/29/2014] [Accepted: 11/29/2014] [Indexed: 11/22/2022]
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36
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Xu J, Wang YT, Liu XF. A novel pretreatment method of three-dimensional fluorescence data for quantitative measurement of component contents in mixture. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2015; 140:484-488. [PMID: 25638431 DOI: 10.1016/j.saa.2014.12.112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2014] [Revised: 11/04/2014] [Accepted: 12/28/2014] [Indexed: 06/04/2023]
Abstract
Three-dimensional fluorescence technique is commonly used for the determination of component contents in the mixture. Fluorescence intensity data are used directly in the fluorescent spectrum data processing method. The relationship between fluorescence intensity values and concentrations is linear. Random noise is inevitable in the process of measuring due to fluorescence spectrometer. The measurement accuracy is reduced due to the existence of noise. To reduce random noise and improve the measurement sensitivity, a novel pretreatment method of three-dimensional fluorescence data is proposed. The method is based on Quasi-Monte-Carlo integral. Due to the increased slope of fluorescence intensity data during the integral, the measurement sensitivity is improved. At the same time, the sum of different exponentials of fluorescence intensity at the points reduces the random noise, so the measurement sensitivity is improved more. The recovery rates of the mixture mixed by gasoline, kerosene and diesel oil are calculated to validate the effectiveness of the method.
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Affiliation(s)
- Jing Xu
- Measurement Technology and Instrumentation Key Lab of Hebei Province, Yanshan University, Qinhuangdao, Hebei 066004, China.
| | - Yu-Tian Wang
- Measurement Technology and Instrumentation Key Lab of Hebei Province, Yanshan University, Qinhuangdao, Hebei 066004, China
| | - Xiao-Fei Liu
- Hebei Provincial Key Laboratory of Parallel Robot and Mechatronic System, Yanshan University, Qinhuangdao, Hebei 066004, China
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37
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Schott J, Kretzschmar J, Tsushima S, Drobot B, Acker M, Barkleit A, Taut S, Brendler V, Stumpf T. The interaction of Eu(iii) with organoborates – a further approach to understand the complexation in the An/Ln(iii)–borate system. Dalton Trans 2015; 44:11095-108. [DOI: 10.1039/c5dt00213c] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
A combination of different spectroscopy techniques, DFT calculations and advanced data analysis explained the Eu(iii)–organoborate complexation.
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Affiliation(s)
- Juliane Schott
- Helmholtz-Zentrum Dresden-Rossendorf
- Institute of Resource Ecology
- 01328 Dresden
- Germany
- Technische Universität Dresden
| | - Jerome Kretzschmar
- Helmholtz-Zentrum Dresden-Rossendorf
- Institute of Resource Ecology
- 01328 Dresden
- Germany
| | - Satoru Tsushima
- Helmholtz-Zentrum Dresden-Rossendorf
- Institute of Resource Ecology
- 01328 Dresden
- Germany
| | - Björn Drobot
- Helmholtz-Zentrum Dresden-Rossendorf
- Institute of Resource Ecology
- 01328 Dresden
- Germany
| | - Margret Acker
- Technische Universität Dresden
- Central Radionuclide Laboratory
- 01062 Dresden
- Germany
| | - Astrid Barkleit
- Helmholtz-Zentrum Dresden-Rossendorf
- Institute of Resource Ecology
- 01328 Dresden
- Germany
| | - Steffen Taut
- Technische Universität Dresden
- Central Radionuclide Laboratory
- 01062 Dresden
- Germany
| | - Vinzenz Brendler
- Helmholtz-Zentrum Dresden-Rossendorf
- Institute of Resource Ecology
- 01328 Dresden
- Germany
| | - Thorsten Stumpf
- Helmholtz-Zentrum Dresden-Rossendorf
- Institute of Resource Ecology
- 01328 Dresden
- Germany
- Technische Universität Dresden
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38
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Fan Y, Li Y, Cai H, Li J, Miao J, Fu D, Su K. Three-dimensional fluorescence characteristics of white chrysanthemum flowers. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2014; 130:411-415. [PMID: 24810027 DOI: 10.1016/j.saa.2014.04.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2014] [Revised: 03/18/2014] [Accepted: 04/03/2014] [Indexed: 06/03/2023]
Abstract
White chrysanthemum flower is one of the most popular plants found everywhere in China and used as herbs. In the present work, three-dimensional fluorescence technique was used to discriminate species of white chrysanthemum flowers. Parameters affecting extraction efficiency were investigated. Under the optimal conditions, the three-dimensional fluorescence characteristics of three types of white chrysanthemum flowers were obtained. It was found that there were two main fluorescence peaks with remarkable difference in fluorescence intensity, one was corresponding to flavonoids and another was attributed to chlorophyll-like compounds. There were remarkable differences among the contours of the three white chrysanthemum flowers. Further studies showed that the fluorescence intensity ratios of chlorophyll-like compounds to flavonoids had a certain relationship with the species; those for Huai, Hang and Huangshan white chrysanthemum flowers were 6.9-7.4, 18.9-21.4 and 73.6-84.5, respectively. All of the results suggest that three-dimensional fluorescence spectra can be used for the discrimination of white chrysanthemum flowers with the advantages of low cost, ease for operation and intuition.
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Affiliation(s)
- Yunchang Fan
- College of Physics and Chemistry, Henan Polytechnic University, Jiaozuo 454003, China
| | - Yang Li
- College of Chemistry and Molecular Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Hongxin Cai
- College of Physics and Chemistry, Henan Polytechnic University, Jiaozuo 454003, China.
| | - Jing Li
- Yunnan Academy of Tobacco Science, Kunming 650106, China
| | - Juan Miao
- College of Physics and Chemistry, Henan Polytechnic University, Jiaozuo 454003, China
| | - Dexue Fu
- Jiaozuo University, Jiaozuo 454000, China.
| | - Kun Su
- College of Physics and Chemistry, Henan Polytechnic University, Jiaozuo 454003, China
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39
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Fluorescence spectroscopy and multivariate methods for the determination of brandy adulteration with mixed wine spirit. Food Chem 2014; 159:193-9. [DOI: 10.1016/j.foodchem.2014.02.085] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2013] [Revised: 02/05/2014] [Accepted: 02/18/2014] [Indexed: 11/23/2022]
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40
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Martelo-Vidal MJ, Vázquez M. Classification of red wines from controlled designation of origin by ultraviolet-visible and near-infrared spectral analysis. CIÊNCIA E TÉCNICA VITIVINÍCOLA 2014. [DOI: 10.1051/ctv/20142901035] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
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41
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Schott J, Kretzschmar J, Acker M, Eidner S, Kumke MU, Drobot B, Barkleit A, Taut S, Brendler V, Stumpf T. Formation of a Eu(iii) borate solid species from a weak Eu(iii) borate complex in aqueous solution. Dalton Trans 2014; 43:11516-28. [DOI: 10.1039/c4dt00843j] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Using time-resolved laser-induced fluorescence spectroscopy (TRLFS) the transformation of a dissolved Eu(iii) borate species into a solid Eu(iii) borate was observed.
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Affiliation(s)
- Juliane Schott
- Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
- Institute of Resource Ecology
- 01314 Dresden, Germany
- Technische Universität Dresden (TUD)
- Central Radionuclide Laboratory
| | - Jerome Kretzschmar
- Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
- Institute of Resource Ecology
- 01314 Dresden, Germany
| | - Margret Acker
- Technische Universität Dresden (TUD)
- Central Radionuclide Laboratory
- 01062 Dresden, Germany
| | - Sascha Eidner
- University of Potsdam
- Institute of Chemistry (Physical Chemistry)
- 14476 Potsdam-Golm, Germany
| | - Michael U. Kumke
- University of Potsdam
- Institute of Chemistry (Physical Chemistry)
- 14476 Potsdam-Golm, Germany
| | - Björn Drobot
- Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
- Institute of Resource Ecology
- 01314 Dresden, Germany
| | - Astrid Barkleit
- Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
- Institute of Resource Ecology
- 01314 Dresden, Germany
- Technische Universität Dresden (TUD)
- Division of Radiochemistry and Radioecology
| | - Steffen Taut
- Technische Universität Dresden (TUD)
- Central Radionuclide Laboratory
- 01062 Dresden, Germany
| | - Vinzenz Brendler
- Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
- Institute of Resource Ecology
- 01314 Dresden, Germany
| | - Thorsten Stumpf
- Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
- Institute of Resource Ecology
- 01314 Dresden, Germany
- Technische Universität Dresden (TUD)
- Division of Radiochemistry and Radioecology
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42
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Classification Methods of Multiway Arrays as a Basic Tool for Food PDO Authentication. FOOD PROTECTED DESIGNATION OF ORIGIN - METHODOLOGIES AND APPLICATIONS 2013. [DOI: 10.1016/b978-0-444-59562-1.00014-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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43
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44
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de Juan A, Mas S. Multivariate Curve Resolution Methods for Food Chemistry. DATA HANDLING IN SCIENCE AND TECHNOLOGY 2013. [DOI: 10.1016/b978-0-444-59528-7.00006-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
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45
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Multiway Methods. ACTA ACUST UNITED AC 2013. [DOI: 10.1016/b978-0-444-59528-7.00007-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
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