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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...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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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. |
format | Online Article Text |
id | pubmed-10651451 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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