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

Chemometric analysis Grape variety Polyphenolic compounds Sensory analysis Tannins

Journal

Current research in food science
ISSN: 2665-9271
Titre abrégé: Curr Res Food Sci
Pays: Netherlands
ID NLM: 101771059

Informations de publication

Date de publication:
2023
Historique:
received: 04 09 2023
revised: 18 10 2023
accepted: 24 10 2023
medline: 29 11 2023
pubmed: 29 11 2023
entrez: 29 11 2023
Statut: epublish

Résumé

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

Identifiants

pubmed: 38021261
doi: 10.1016/j.crfs.2023.100626
pii: S2665-9271(23)00194-6
pmc: PMC10651451
doi:

Types de publication

Journal Article

Langues

eng

Pagination

100626

Informations de copyright

© 2023 The Authors.

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Auteurs

Cristian Galaz Torres (C)

Department of Agricultural and Food Sciences, University of Bologna, Italy.

Arianna Ricci (A)

Department of Agricultural and Food Sciences, University of Bologna, Italy.

Giuseppina Paola Parpinello (GP)

Department of Agricultural and Food Sciences, University of Bologna, Italy.

Angelita Gambuti (A)

Department of Agricultural Sciences, Division of Vine and Wine Sciences, University of Napoli Federico II, 83100, Avellino, Italy.

Alessandra Rinaldi (A)

Department of Agricultural Sciences, Division of Vine and Wine Sciences, University of Napoli Federico II, 83100, Avellino, Italy.

Luigi Moio (L)

Department of Agricultural Sciences, Division of Vine and Wine Sciences, University of Napoli Federico II, 83100, Avellino, Italy.

Luca Rolle (L)

Department of Agricultural, Forest and Food Sciences, University of Torino, 10095, Grugliasco, Italy.

Maria Alessandra Paissoni (MA)

Department of Agricultural, Forest and Food Sciences, University of Torino, 10095, Grugliasco, Italy.

Fulvio Mattivi (F)

Metabolomic Unit, Research and Innovation Centre, Fondazione Edmund Mach, 38010, San Michele all'Adige, Italy.

Daniele Perenzoni (D)

Metabolomic Unit, Research and Innovation Centre, Fondazione Edmund Mach, 38010, San Michele all'Adige, Italy.

Panagiotis Arapitsas (P)

Metabolomic Unit, Research and Innovation Centre, Fondazione Edmund Mach, 38010, San Michele all'Adige, Italy.
Department of Wine, Vine and Beverage Sciences, School of Food Science, University of West Attica, Egaleo, 12243, Athens, Greece.

Matteo Marangon (M)

Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, 35020, Legnaro, Italy.

Christine Mayr Marangon (C)

Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, 35020, Legnaro, Italy.

Davide Slaghenaufi (D)

Department of Biotechnology, University of Verona, via della Pieve 70, San Pietro in Cariano, VR, Italy.

Maurizio Ugliano (M)

Department of Biotechnology, University of Verona, via della Pieve 70, San Pietro in Cariano, VR, Italy.

Andrea Versari (A)

Department of Agricultural and Food Sciences, University of Bologna, Italy.

Classifications MeSH