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IVES 9 IVES Conference Series 9 International Congress on Grapevine and Wine Sciences 9 2ICGWS-2023 9 A sensometabolomic approach to understand wine mouthfeel percepts

A sensometabolomic approach to understand wine mouthfeel percepts

Abstract

Targeted analytical methods can overlook compounds that are a priori unknown to play a role in the mouthfeel sensations. This limitation can be overcome with the information provided by untargeted metabolomic analysis using UPLC‐QTOF-MS. To this end, an untargeted metabolomic approach applied to 42 red wines has allowed development of a model with predictive capacity by cross-validation for the “dry”, “oily” and “unctuous” sensations perceived by a sensory panel. The optimal PLS model for “dry” retained compounds with positive regression coefficients (≥ 0.17) including a trimer procyanidin, a peptide, and four anthocyanins. The compounds with negative contribution were flavonols, hydroxycinnamic acids, and malvidin-ethyl-flavan-3-ol, which agreed with the results of the PLS model obtained from targeted analysis. The relevance of phenolics to the “dry” sensation was sensible, but the predictive models obtained for “unctuous” and “oily” also showed that the chemical composition analyzed was involved in both mouthfeel sensations. The UPLC‐QTOF-MS has allowed to identify a tripeptide with important implication in “dry”, develop “oily” and “unctuous” models and confirm again the involvement of anthocyanins in mouthfeel perception of red wines. This sensometabolomic approach has found strong correlations between some perceived sensations and the chemical compounds analyzed. The role of the key compounds identified will need to be confirmed in future studies.

Acknowledgements: MICIN (AGL-2017-87373-C3-3-R & PID2021-126031OB-C22 FEDER, UE). SFT: University of La Rioja (predoctoral fellowship, UR-CAR-2018). MPSN: MICIN (RYC2019-027995-I/AEI/10.13039/501100011033 & CAS21/00221). PA & FM: (AdP 2019 by the Autonomous Province of Trento, Italy).

DOI:

Publication date: 13/10/2023

Issue: ICGWS 2023

Type: Poster

Authors

Sara Ferrero-del-Teso1, Panagiotis Arapitsas2,3, David W. Jeffery4, Chelo Ferreira5, Fulvio Mattivi2, Purificación Fernández-Zurbano1*, María-Pilar Sáenz-Navajas1

1Instituto de Ciencias de la Vid y del Vino (UR-CSIC-GR) Department of Enology, Logroño, La Rioja, Spain

2Unit of Metabolomics, Research and Innovation Centre, Fondazione Edmund Mach, via E. Mach 1, 38010 San Michele all’Adige, Italy.

3Department of Wine, Vine and Beverage Sciences, School of Food Science, University of West Attica, Ag. Spyridonos 28, Egaleo, 12243 Athens, Greece.

4School of Agriculture, Food and Wine, and Waite Research Institute, The University of Adelaide, PMB 1, Glen Osmond, South Australia 5064, Australia.

5Laboratorio de Análisis del Aroma y Enología (LAAE), Instituto Universitario de Matemáticas y Aplicaciones (IUMA-UNIZAR), Universidad de Zaragoza, c/ Pedro Cerbuna 12, 50009 Zaragoza, Spain.

Contact the author*

Keywords

untargeted analysis, metabolomics, PLS regression, sensory analysis, UPLC‐QTOF

Tags

2ICGWS | ICGWS | ICGWS 2023 | IVES Conference Series

Citation

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