Spectralprint techniques coupled with chemometric tools for vinegar classifications
[Display omitted] •First study to classify vinegar by agronomic method of raw material cultivation.•Vinegar classification by type of raw materials and aging time.•NMR with PLS-DA had the best performance, followed by FT-IR with UV–vis and NIR.•Vinegar classification according to the agronomic culti...
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Veröffentlicht in: | Food chemistry 2023-06, Vol.410, p.135373-135373, Article 135373 |
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creator | Avanzi Barbosa Mascareli, Vinícius Galvan, Diego Craveiro de Andrade, Jelmir Lelis, Carini Adam Conte-Junior, Carlos Michelino Gaeta Lopes, Giancarlo César de Macedo Júnior, Fernando Aparecida Spinosa, Wilma |
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•First study to classify vinegar by agronomic method of raw material cultivation.•Vinegar classification by type of raw materials and aging time.•NMR with PLS-DA had the best performance, followed by FT-IR with UV–vis and NIR.•Vinegar classification according to the agronomic cultivation mode is more complex.•Spectralprint techniques with chemometrics were useful for vinegar quality control.
Vinegar is a versatile product used for food preservation, cooking, healthcare, and cleaning. In this study, 80 vinegar of different raw materials, aging time, and for the first time by the agronomic method of raw material cultivation were classified by spectralprint techniques with chemometrics. Datasets were obtained by proton nuclear magnetic resonance (1H NMR), Fourier transforms mid-infrared (FT-IR), near-infrared (NIR), and ultraviolet–visible (UV–vis); then evaluated by common dimension (ComDim) and partial least squares-discriminant analysis (PLS-DA). NMR with PLS-DA had the best prediction performance compared to other techniques, with accuracy values between 92.3 and 100 %, followed by FT-IR and UV–vis of 80.8 and 96.0 % and NIR between 69.2 and 84.0 %. The results indicated that the classification of vinegar according to the agronomic cultivation method is more complex than aging time or raw material. However, any of these spectralprint techniques have demonstrated that they can be used in the classification of vinegar. |
doi_str_mv | 10.1016/j.foodchem.2022.135373 |
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•First study to classify vinegar by agronomic method of raw material cultivation.•Vinegar classification by type of raw materials and aging time.•NMR with PLS-DA had the best performance, followed by FT-IR with UV–vis and NIR.•Vinegar classification according to the agronomic cultivation mode is more complex.•Spectralprint techniques with chemometrics were useful for vinegar quality control.
Vinegar is a versatile product used for food preservation, cooking, healthcare, and cleaning. In this study, 80 vinegar of different raw materials, aging time, and for the first time by the agronomic method of raw material cultivation were classified by spectralprint techniques with chemometrics. Datasets were obtained by proton nuclear magnetic resonance (1H NMR), Fourier transforms mid-infrared (FT-IR), near-infrared (NIR), and ultraviolet–visible (UV–vis); then evaluated by common dimension (ComDim) and partial least squares-discriminant analysis (PLS-DA). NMR with PLS-DA had the best prediction performance compared to other techniques, with accuracy values between 92.3 and 100 %, followed by FT-IR and UV–vis of 80.8 and 96.0 % and NIR between 69.2 and 84.0 %. The results indicated that the classification of vinegar according to the agronomic cultivation method is more complex than aging time or raw material. However, any of these spectralprint techniques have demonstrated that they can be used in the classification of vinegar.</description><identifier>ISSN: 0308-8146</identifier><identifier>EISSN: 1873-7072</identifier><identifier>DOI: 10.1016/j.foodchem.2022.135373</identifier><identifier>PMID: 36608560</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Acetic Acid - chemistry ; Aging ; Agriculture ; Chemometrics ; ComDim ; Discriminant Analysis ; Fingerprint ; Fruit fermented ; Least-Squares Analysis ; Multivariate analysis ; Organic product ; Quality control ; Spectroscopic technique ; Spectroscopy, Fourier Transform Infrared - methods</subject><ispartof>Food chemistry, 2023-06, Vol.410, p.135373-135373, Article 135373</ispartof><rights>2022 Elsevier Ltd</rights><rights>Copyright © 2022 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c368t-a46fbfeee688683bd32c44156b12635b1c177a27e268de3a3080d2389d85db243</citedby><cites>FETCH-LOGICAL-c368t-a46fbfeee688683bd32c44156b12635b1c177a27e268de3a3080d2389d85db243</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0308814622033350$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36608560$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Avanzi Barbosa Mascareli, Vinícius</creatorcontrib><creatorcontrib>Galvan, Diego</creatorcontrib><creatorcontrib>Craveiro de Andrade, Jelmir</creatorcontrib><creatorcontrib>Lelis, Carini</creatorcontrib><creatorcontrib>Adam Conte-Junior, Carlos</creatorcontrib><creatorcontrib>Michelino Gaeta Lopes, Giancarlo</creatorcontrib><creatorcontrib>César de Macedo Júnior, Fernando</creatorcontrib><creatorcontrib>Aparecida Spinosa, Wilma</creatorcontrib><title>Spectralprint techniques coupled with chemometric tools for vinegar classifications</title><title>Food chemistry</title><addtitle>Food Chem</addtitle><description>[Display omitted]
•First study to classify vinegar by agronomic method of raw material cultivation.•Vinegar classification by type of raw materials and aging time.•NMR with PLS-DA had the best performance, followed by FT-IR with UV–vis and NIR.•Vinegar classification according to the agronomic cultivation mode is more complex.•Spectralprint techniques with chemometrics were useful for vinegar quality control.
Vinegar is a versatile product used for food preservation, cooking, healthcare, and cleaning. In this study, 80 vinegar of different raw materials, aging time, and for the first time by the agronomic method of raw material cultivation were classified by spectralprint techniques with chemometrics. Datasets were obtained by proton nuclear magnetic resonance (1H NMR), Fourier transforms mid-infrared (FT-IR), near-infrared (NIR), and ultraviolet–visible (UV–vis); then evaluated by common dimension (ComDim) and partial least squares-discriminant analysis (PLS-DA). NMR with PLS-DA had the best prediction performance compared to other techniques, with accuracy values between 92.3 and 100 %, followed by FT-IR and UV–vis of 80.8 and 96.0 % and NIR between 69.2 and 84.0 %. The results indicated that the classification of vinegar according to the agronomic cultivation method is more complex than aging time or raw material. However, any of these spectralprint techniques have demonstrated that they can be used in the classification of vinegar.</description><subject>Acetic Acid - chemistry</subject><subject>Aging</subject><subject>Agriculture</subject><subject>Chemometrics</subject><subject>ComDim</subject><subject>Discriminant Analysis</subject><subject>Fingerprint</subject><subject>Fruit fermented</subject><subject>Least-Squares Analysis</subject><subject>Multivariate analysis</subject><subject>Organic product</subject><subject>Quality control</subject><subject>Spectroscopic technique</subject><subject>Spectroscopy, Fourier Transform Infrared - methods</subject><issn>0308-8146</issn><issn>1873-7072</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkMtOwzAQRS0EoqXwC1WWbBL8SGx3B6p4SZVYFNaWY0-oqyQutlvE35OqLVtWszkzd-5BaEpwQTDhd-ui8d6aFXQFxZQWhFVMsDM0JlKwXGBBz9EYMyxzSUo-QlcxrjHGFBN5iUaMcywrjsdoudyASUG3m-D6lCUwq959bSFmxm83Ldjs26VVtg_yHaTgTJa8b2PW-JDtXA-fOmSm1TG6xhmdnO_jNbpodBvh5jgn6OPp8X3-ki_enl_nD4vcMC5Trkve1A0AcCm5ZLVl1JQlqXhNKGdVTQwRQlMBlEsLTA9lsKVMzqysbE1LNkG3h7ub4PcvJ9W5aKBtdQ9-GxUVnMxEVQk6oPyAmuBjDNCooW-nw48iWO2FqrU6CVV7oeogdFicHjO2dQf2b-1kcADuDwAMTXcOgorGQW_AujCYVda7_zJ-AWM9i3o</recordid><startdate>20230601</startdate><enddate>20230601</enddate><creator>Avanzi Barbosa Mascareli, Vinícius</creator><creator>Galvan, Diego</creator><creator>Craveiro de Andrade, Jelmir</creator><creator>Lelis, Carini</creator><creator>Adam Conte-Junior, Carlos</creator><creator>Michelino Gaeta Lopes, Giancarlo</creator><creator>César de Macedo Júnior, Fernando</creator><creator>Aparecida Spinosa, Wilma</creator><general>Elsevier Ltd</general><scope>6I.</scope><scope>AAFTH</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20230601</creationdate><title>Spectralprint techniques coupled with chemometric tools for vinegar classifications</title><author>Avanzi Barbosa Mascareli, Vinícius ; Galvan, Diego ; Craveiro de Andrade, Jelmir ; Lelis, Carini ; Adam Conte-Junior, Carlos ; Michelino Gaeta Lopes, Giancarlo ; César de Macedo Júnior, Fernando ; Aparecida Spinosa, Wilma</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c368t-a46fbfeee688683bd32c44156b12635b1c177a27e268de3a3080d2389d85db243</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Acetic Acid - chemistry</topic><topic>Aging</topic><topic>Agriculture</topic><topic>Chemometrics</topic><topic>ComDim</topic><topic>Discriminant Analysis</topic><topic>Fingerprint</topic><topic>Fruit fermented</topic><topic>Least-Squares Analysis</topic><topic>Multivariate analysis</topic><topic>Organic product</topic><topic>Quality control</topic><topic>Spectroscopic technique</topic><topic>Spectroscopy, Fourier Transform Infrared - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Avanzi Barbosa Mascareli, Vinícius</creatorcontrib><creatorcontrib>Galvan, Diego</creatorcontrib><creatorcontrib>Craveiro de Andrade, Jelmir</creatorcontrib><creatorcontrib>Lelis, Carini</creatorcontrib><creatorcontrib>Adam Conte-Junior, Carlos</creatorcontrib><creatorcontrib>Michelino Gaeta Lopes, Giancarlo</creatorcontrib><creatorcontrib>César de Macedo Júnior, Fernando</creatorcontrib><creatorcontrib>Aparecida Spinosa, Wilma</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Food chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Avanzi Barbosa Mascareli, Vinícius</au><au>Galvan, Diego</au><au>Craveiro de Andrade, Jelmir</au><au>Lelis, Carini</au><au>Adam Conte-Junior, Carlos</au><au>Michelino Gaeta Lopes, Giancarlo</au><au>César de Macedo Júnior, Fernando</au><au>Aparecida Spinosa, Wilma</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spectralprint techniques coupled with chemometric tools for vinegar classifications</atitle><jtitle>Food chemistry</jtitle><addtitle>Food Chem</addtitle><date>2023-06-01</date><risdate>2023</risdate><volume>410</volume><spage>135373</spage><epage>135373</epage><pages>135373-135373</pages><artnum>135373</artnum><issn>0308-8146</issn><eissn>1873-7072</eissn><abstract>[Display omitted]
•First study to classify vinegar by agronomic method of raw material cultivation.•Vinegar classification by type of raw materials and aging time.•NMR with PLS-DA had the best performance, followed by FT-IR with UV–vis and NIR.•Vinegar classification according to the agronomic cultivation mode is more complex.•Spectralprint techniques with chemometrics were useful for vinegar quality control.
Vinegar is a versatile product used for food preservation, cooking, healthcare, and cleaning. In this study, 80 vinegar of different raw materials, aging time, and for the first time by the agronomic method of raw material cultivation were classified by spectralprint techniques with chemometrics. Datasets were obtained by proton nuclear magnetic resonance (1H NMR), Fourier transforms mid-infrared (FT-IR), near-infrared (NIR), and ultraviolet–visible (UV–vis); then evaluated by common dimension (ComDim) and partial least squares-discriminant analysis (PLS-DA). NMR with PLS-DA had the best prediction performance compared to other techniques, with accuracy values between 92.3 and 100 %, followed by FT-IR and UV–vis of 80.8 and 96.0 % and NIR between 69.2 and 84.0 %. The results indicated that the classification of vinegar according to the agronomic cultivation method is more complex than aging time or raw material. However, any of these spectralprint techniques have demonstrated that they can be used in the classification of vinegar.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>36608560</pmid><doi>10.1016/j.foodchem.2022.135373</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Acetic Acid - chemistry Aging Agriculture Chemometrics ComDim Discriminant Analysis Fingerprint Fruit fermented Least-Squares Analysis Multivariate analysis Organic product Quality control Spectroscopic technique Spectroscopy, Fourier Transform Infrared - methods |
title | Spectralprint techniques coupled with chemometric tools for vinegar classifications |
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