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
Hauptverfasser: 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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container_end_page 135373
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container_start_page 135373
container_title Food chemistry
container_volume 410
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
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.
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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. 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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 ; 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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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