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Multivariate prediction of Saliva Precipitation Index for relating selected chemical parameters of red wines to the sensory perception of astringency

Astringency is an essential sensory attribute of red wine closely related to the saliva precipitation upon contact with the wine. In this study a data matrix of 52 physico-chemical parameters was used to predict the Saliva Precipitation Index (SPI) in 110 Italian mono-varietal red wines using partia...

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Autores principales: Galaz Torres, Cristian, Ricci, Arianna, Parpinello, Giuseppina Paola, Gambuti, Angelita, Rinaldi, Alessandra, Moio, Luigi, Rolle, Luca, Paissoni, Maria Alessandra, Mattivi, Fulvio, Perenzoni, Daniele, Arapitsas, Panagiotis, Marangon, Matteo, Mayr Marangon, Christine, Slaghenaufi, Davide, Ugliano, Maurizio, Versari, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10651451/
https://www.ncbi.nlm.nih.gov/pubmed/38021261
http://dx.doi.org/10.1016/j.crfs.2023.100626
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author Galaz Torres, Cristian
Ricci, Arianna
Parpinello, Giuseppina Paola
Gambuti, Angelita
Rinaldi, Alessandra
Moio, Luigi
Rolle, Luca
Paissoni, Maria Alessandra
Mattivi, Fulvio
Perenzoni, Daniele
Arapitsas, Panagiotis
Marangon, Matteo
Mayr Marangon, Christine
Slaghenaufi, Davide
Ugliano, Maurizio
Versari, Andrea
author_facet Galaz Torres, Cristian
Ricci, Arianna
Parpinello, Giuseppina Paola
Gambuti, Angelita
Rinaldi, Alessandra
Moio, Luigi
Rolle, Luca
Paissoni, Maria Alessandra
Mattivi, Fulvio
Perenzoni, Daniele
Arapitsas, Panagiotis
Marangon, Matteo
Mayr Marangon, Christine
Slaghenaufi, Davide
Ugliano, Maurizio
Versari, Andrea
author_sort Galaz Torres, Cristian
collection PubMed
description Astringency is an essential sensory attribute of red wine closely related to the saliva precipitation upon contact with the wine. In this study a data matrix of 52 physico-chemical parameters was used to predict the Saliva Precipitation Index (SPI) in 110 Italian mono-varietal red wines using partial least squares regression (PLSr) with variable selection by Variable Importance for Projection (VIP) and the significance of regression coefficients. The final PLSr model, evaluated using a test data set, had 3 components and yielded an R(2)(test) of 0.630 and an RMSE(test) of 0.994, with 19 independent variables whose regression coefficients were all significant at p < 0.05. Variables selected in the final model according to the decreasing magnitude of their absolute regression coefficient include the following: Procyanidin B1, Epicatechin terminal unit, Total aldehydes, Protein content, Vanillin assay, 520 nm, Polysaccharide content, Epigallocatechin PHL, Tartaric acid, Volatile acidity, Titratable acidity, Catechin terminal unit, Proanthocyanidin assay, pH, Tannin-Fe/Anthocyanin, Buffer capacity, Epigallocatechin PHL gallate, Catechin + epicatechin PHL, and Tannin-Fe. These results can be used to better understand the physico-chemical relationship underlying astringency in red wine.
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spelling pubmed-106514512023-10-26 Multivariate prediction of Saliva Precipitation Index for relating selected chemical parameters of red wines to the sensory perception of astringency Galaz Torres, Cristian Ricci, Arianna Parpinello, Giuseppina Paola Gambuti, Angelita Rinaldi, Alessandra Moio, Luigi Rolle, Luca Paissoni, Maria Alessandra Mattivi, Fulvio Perenzoni, Daniele Arapitsas, Panagiotis Marangon, Matteo Mayr Marangon, Christine Slaghenaufi, Davide Ugliano, Maurizio Versari, Andrea Curr Res Food Sci Research Article Astringency is an essential sensory attribute of red wine closely related to the saliva precipitation upon contact with the wine. In this study a data matrix of 52 physico-chemical parameters was used to predict the Saliva Precipitation Index (SPI) in 110 Italian mono-varietal red wines using partial least squares regression (PLSr) with variable selection by Variable Importance for Projection (VIP) and the significance of regression coefficients. The final PLSr model, evaluated using a test data set, had 3 components and yielded an R(2)(test) of 0.630 and an RMSE(test) of 0.994, with 19 independent variables whose regression coefficients were all significant at p < 0.05. Variables selected in the final model according to the decreasing magnitude of their absolute regression coefficient include the following: Procyanidin B1, Epicatechin terminal unit, Total aldehydes, Protein content, Vanillin assay, 520 nm, Polysaccharide content, Epigallocatechin PHL, Tartaric acid, Volatile acidity, Titratable acidity, Catechin terminal unit, Proanthocyanidin assay, pH, Tannin-Fe/Anthocyanin, Buffer capacity, Epigallocatechin PHL gallate, Catechin + epicatechin PHL, and Tannin-Fe. These results can be used to better understand the physico-chemical relationship underlying astringency in red wine. Elsevier 2023-10-26 /pmc/articles/PMC10651451/ /pubmed/38021261 http://dx.doi.org/10.1016/j.crfs.2023.100626 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Galaz Torres, Cristian
Ricci, Arianna
Parpinello, Giuseppina Paola
Gambuti, Angelita
Rinaldi, Alessandra
Moio, Luigi
Rolle, Luca
Paissoni, Maria Alessandra
Mattivi, Fulvio
Perenzoni, Daniele
Arapitsas, Panagiotis
Marangon, Matteo
Mayr Marangon, Christine
Slaghenaufi, Davide
Ugliano, Maurizio
Versari, Andrea
Multivariate prediction of Saliva Precipitation Index for relating selected chemical parameters of red wines to the sensory perception of astringency
title Multivariate prediction of Saliva Precipitation Index for relating selected chemical parameters of red wines to the sensory perception of astringency
title_full Multivariate prediction of Saliva Precipitation Index for relating selected chemical parameters of red wines to the sensory perception of astringency
title_fullStr Multivariate prediction of Saliva Precipitation Index for relating selected chemical parameters of red wines to the sensory perception of astringency
title_full_unstemmed Multivariate prediction of Saliva Precipitation Index for relating selected chemical parameters of red wines to the sensory perception of astringency
title_short Multivariate prediction of Saliva Precipitation Index for relating selected chemical parameters of red wines to the sensory perception of astringency
title_sort multivariate prediction of saliva precipitation index for relating selected chemical parameters of red wines to the sensory perception of astringency
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10651451/
https://www.ncbi.nlm.nih.gov/pubmed/38021261
http://dx.doi.org/10.1016/j.crfs.2023.100626
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