Modeling grape taste and mouthfeel from chemical composition.

Astringency sub-qualities Rate-k-attributes Sensory analysis Sorting task Tannin activity

Journal

Food chemistry
ISSN: 1873-7072
Titre abrégé: Food Chem
Pays: England
ID NLM: 7702639

Informations de publication

Date de publication:
01 Mar 2022
Historique:
received: 07 04 2021
revised: 20 08 2021
accepted: 15 09 2021
pubmed: 4 10 2021
medline: 24 11 2021
entrez: 3 10 2021
Statut: ppublish

Résumé

This research aims at predicting sensory properties generated by the phenolic fraction (PF) of grapes from chemical composition. Thirty-one grape extracts of different grape lots were obtained by maceration of grapes in hydroalcoholic solution; afterward they were submitted to solid phase extraction. The recovered PFs were reconstituted in a wine model. Subsequently the wine models, containing the PFs, were sensory (taste, mouthfeel) and chemically characterized. Significant sensory differences among the 31 PFs were identified. Sensory variables were predicted from chemical parameters by PLS-regression. Tannin activity and concentration along with mean degree of polymerization were found to be good predictors of dryness, while the concentration of large polymeric pigments seems to be involved in the "sticky" percept and flavonols in the "bitter" taste. Four fully validated PLS-models predicting sensory properties from chemical variables were obtained. Two out of the three sensory dimensions could be satisfactorily modeled. These results increase knowledge about grape properties and proposes the measurement of chemical variables to infer grape quality.

Identifiants

pubmed: 34601211
pii: S0308-8146(21)02174-9
doi: 10.1016/j.foodchem.2021.131168
pii:
doi:

Substances chimiques

Tannins 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

131168

Informations de copyright

Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Auteurs

Sara Ferrero-Del-Teso (S)

Instituto de Ciencias de la Vid y del Vino (ICVV) (Universidad de La Rioja-CSIC-Gobierno de La Rioja), Carretera de Burgos Km. 6, Finca La Grajera, 26007 Logroño, La Rioja, Spain.

Alejandro Suárez (A)

Instituto de Ciencias de la Vid y del Vino (ICVV) (Universidad de La Rioja-CSIC-Gobierno de La Rioja), Carretera de Burgos Km. 6, Finca La Grajera, 26007 Logroño, La Rioja, Spain.

Chelo Ferreira (C)

Laboratorio de Análisis del Aroma y Enología (LAAE), Department of Analytical Chemistry, Universidad de Zaragoza, Instituto Agroalimentario de Aragón (IA2) (UNIZAR-CITA), c/ Pedro Cerbuna 12, 50009 Zaragoza, Spain.

Daniele Perenzoni (D)

Research and Innovation Centre, Food Quality and Nutrition Department, and Technology Transfer Centre, Fondazione Edmund Mach, via E. Mach 1, 38010 San Michele all'Adige, Italy.

Panagiotis Arapitsas (P)

Research and Innovation Centre, Food Quality and Nutrition Department, and Technology Transfer Centre, Fondazione Edmund Mach, via E. Mach 1, 38010 San Michele all'Adige, Italy.

Fulvio Mattivi (F)

Research and Innovation Centre, Food Quality and Nutrition Department, and Technology Transfer Centre, Fondazione Edmund Mach, via E. Mach 1, 38010 San Michele all'Adige, Italy; University of Trento, Department of Cellular, Computational and Integrative Biology, CIBIO, 38122 Trento, Italy.

Vicente Ferreira (V)

Laboratorio de Análisis del Aroma y Enología (LAAE), Department of Analytical Chemistry, Universidad de Zaragoza, Instituto Agroalimentario de Aragón (IA2) (UNIZAR-CITA), c/ Pedro Cerbuna 12, 50009 Zaragoza, Spain.

Purificación Fernández-Zurbano (P)

Instituto de Ciencias de la Vid y del Vino (ICVV) (Universidad de La Rioja-CSIC-Gobierno de La Rioja), Carretera de Burgos Km. 6, Finca La Grajera, 26007 Logroño, La Rioja, Spain.

María-Pilar Sáenz-Navajas (MP)

Instituto de Ciencias de la Vid y del Vino (ICVV) (Universidad de La Rioja-CSIC-Gobierno de La Rioja), Carretera de Burgos Km. 6, Finca La Grajera, 26007 Logroño, La Rioja, Spain. Electronic address: mpsaenz@icvv.es.

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Classifications MeSH