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Estimation of Total Phenols, Flavanols and Extractability of Phenolic Compounds in Grape Seeds Using Vibrational Spectroscopy and Chemometric Tools

Near infrared hyperspectral data were collected for 200 Syrah and Tempranillo grape seed samples. Next, a sample selection was carried out and the phenolic content of these samples was determined. Then, quantitative (modified partial least square regressions) and qualitative (K-means and lineal disc...

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Autores principales: Baca-Bocanegra, Berta, Nogales-Bueno, Julio, Heredia, Francisco José, Hernández-Hierro, José Miguel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6111751/
https://www.ncbi.nlm.nih.gov/pubmed/30049946
http://dx.doi.org/10.3390/s18082426
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author Baca-Bocanegra, Berta
Nogales-Bueno, Julio
Heredia, Francisco José
Hernández-Hierro, José Miguel
author_facet Baca-Bocanegra, Berta
Nogales-Bueno, Julio
Heredia, Francisco José
Hernández-Hierro, José Miguel
author_sort Baca-Bocanegra, Berta
collection PubMed
description Near infrared hyperspectral data were collected for 200 Syrah and Tempranillo grape seed samples. Next, a sample selection was carried out and the phenolic content of these samples was determined. Then, quantitative (modified partial least square regressions) and qualitative (K-means and lineal discriminant analyses) chemometric tools were applied to obtain the best models for predicting the reference parameters. Quantitative models developed for the prediction of total phenolic and flavanolic contents have been successfully developed with standard errors of prediction (SEP) in external validation similar to those previously reported. For these parameters, SEPs were respectively, 11.23 mg g(−1) of grape seed, expressed as gallic acid equivalents and 4.85 mg g(−1) of grape seed, expressed as catechin equivalents. The application of these models to the whole sample set (selected and non-selected samples) has allowed knowing the distributions of total phenolic and flavanolic contents in this set. Moreover, a discriminant function has been calculated and applied to know the phenolic extractability level of the samples. On average, this discrimination function has allowed a 76.92% of samples correctly classified according their extractability level. In this way, the bases for the control of grape seeds phenolic state from their near infrared spectra have been stablished.
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spelling pubmed-61117512018-08-30 Estimation of Total Phenols, Flavanols and Extractability of Phenolic Compounds in Grape Seeds Using Vibrational Spectroscopy and Chemometric Tools Baca-Bocanegra, Berta Nogales-Bueno, Julio Heredia, Francisco José Hernández-Hierro, José Miguel Sensors (Basel) Article Near infrared hyperspectral data were collected for 200 Syrah and Tempranillo grape seed samples. Next, a sample selection was carried out and the phenolic content of these samples was determined. Then, quantitative (modified partial least square regressions) and qualitative (K-means and lineal discriminant analyses) chemometric tools were applied to obtain the best models for predicting the reference parameters. Quantitative models developed for the prediction of total phenolic and flavanolic contents have been successfully developed with standard errors of prediction (SEP) in external validation similar to those previously reported. For these parameters, SEPs were respectively, 11.23 mg g(−1) of grape seed, expressed as gallic acid equivalents and 4.85 mg g(−1) of grape seed, expressed as catechin equivalents. The application of these models to the whole sample set (selected and non-selected samples) has allowed knowing the distributions of total phenolic and flavanolic contents in this set. Moreover, a discriminant function has been calculated and applied to know the phenolic extractability level of the samples. On average, this discrimination function has allowed a 76.92% of samples correctly classified according their extractability level. In this way, the bases for the control of grape seeds phenolic state from their near infrared spectra have been stablished. MDPI 2018-07-26 /pmc/articles/PMC6111751/ /pubmed/30049946 http://dx.doi.org/10.3390/s18082426 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Baca-Bocanegra, Berta
Nogales-Bueno, Julio
Heredia, Francisco José
Hernández-Hierro, José Miguel
Estimation of Total Phenols, Flavanols and Extractability of Phenolic Compounds in Grape Seeds Using Vibrational Spectroscopy and Chemometric Tools
title Estimation of Total Phenols, Flavanols and Extractability of Phenolic Compounds in Grape Seeds Using Vibrational Spectroscopy and Chemometric Tools
title_full Estimation of Total Phenols, Flavanols and Extractability of Phenolic Compounds in Grape Seeds Using Vibrational Spectroscopy and Chemometric Tools
title_fullStr Estimation of Total Phenols, Flavanols and Extractability of Phenolic Compounds in Grape Seeds Using Vibrational Spectroscopy and Chemometric Tools
title_full_unstemmed Estimation of Total Phenols, Flavanols and Extractability of Phenolic Compounds in Grape Seeds Using Vibrational Spectroscopy and Chemometric Tools
title_short Estimation of Total Phenols, Flavanols and Extractability of Phenolic Compounds in Grape Seeds Using Vibrational Spectroscopy and Chemometric Tools
title_sort estimation of total phenols, flavanols and extractability of phenolic compounds in grape seeds using vibrational spectroscopy and chemometric tools
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6111751/
https://www.ncbi.nlm.nih.gov/pubmed/30049946
http://dx.doi.org/10.3390/s18082426
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