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

doi:10.1016/j.crfs.2023.100626

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

Curr Res Food Sci. 2023 Oct 26:7:100626. doi: 10.1016/j.crfs.2023.100626. eCollection 2023.

Authors

Cristian Galaz Torres¹, Arianna Ricci¹, Giuseppina Paola Parpinello¹, Angelita Gambuti², Alessandra Rinaldi², Luigi Moio², Luca Rolle³, Maria Alessandra Paissoni³, Fulvio Mattivi⁴, Daniele Perenzoni⁴, Panagiotis Arapitsas^{4

5}, Matteo Marangon⁶, Christine Mayr Marangon⁶, Davide Slaghenaufi⁷, Maurizio Ugliano⁷, Andrea Versari¹

Affiliations

¹ Department of Agricultural and Food Sciences, University of Bologna, Italy.
² Department of Agricultural Sciences, Division of Vine and Wine Sciences, University of Napoli Federico II, 83100, Avellino, Italy.
³ Department of Agricultural, Forest and Food Sciences, University of Torino, 10095, Grugliasco, Italy.
⁴ Metabolomic Unit, Research and Innovation Centre, Fondazione Edmund Mach, 38010, San Michele all'Adige, Italy.
⁵ Department of Wine, Vine and Beverage Sciences, School of Food Science, University of West Attica, Egaleo, 12243, Athens, Greece.
⁶ Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, 35020, Legnaro, Italy.
⁷ Department of Biotechnology, University of Verona, via della Pieve 70, San Pietro in Cariano, VR, Italy.

Abstract

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 R²_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.

Keywords: Chemometric analysis; Grape variety; Polyphenolic compounds; Sensory analysis; Tannins.