Current Research in Food Science (Jan 2023)

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

  • Cristian Galaz Torres,
  • Arianna Ricci,
  • Giuseppina Paola Parpinello,
  • Angelita Gambuti,
  • Alessandra Rinaldi,
  • Luigi Moio,
  • Luca Rolle,
  • Maria Alessandra Paissoni,
  • Fulvio Mattivi,
  • Daniele Perenzoni,
  • Panagiotis Arapitsas,
  • Matteo Marangon,
  • Christine Mayr Marangon,
  • Davide Slaghenaufi,
  • Maurizio Ugliano,
  • Andrea Versari

Journal volume & issue
Vol. 7
p. 100626

Abstract

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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 R2test of 0.630 and an RMSEtest 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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