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
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
131168Informations de copyright
Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.