Original research articles

Rapid methods for the evaluation of total phenol content and extractability in intact grape seeds of Cabernet-Sauvignon: instrumental mechanical properties and FT-NIR spectrum

Abstract

Aims: Fourier Transform-Near Infrared (FT-NIR) spectrum and instrumental texture parameters were assessed as total phenol content and extractability predictors in intact grape seeds.

Methods and results:The study was carried out on Cabernet-Sauvignon seeds from grapes harvested at six different advanced physiological stages throughout ripening and calibrated by flotation to reduce the in-field heterogeneity inside each sample. Among the instrumental mechanical properties tested (i. e., break force, break energy, Young’s modulus of elasticity and deformation index), the seed Young’s modulus of elasticity showed an increase during the first four weeks of ripening. This parameter also showed significant correlations with phenol content and extractability, although with low R coefficients. These correlations highlighted that the springier seed tissues greatly increase phenol extractability. Nevertheless, the best prediction of seed phenol content, performed directly on intact seeds, was found using FT-NIR spectroscopy in transmittance mode. The standard error of prediction for total phenol content was less than 8 %, while that for phenol extractability was worse.

Conclusion: On the basis of these results, the two analytical methods could be applied in oenology for the rapid monitoring of seed phenolic maturity.

Significance and impact of the study: The phenolic composition of grapes at the harvest time is a key factor determining their quality, and thus the quality of the finished wine. The chemical methods used for the determination of seed phenol content and extractability are generally slow because they require a preliminary extraction. Therefore, a rapid evaluation of these parameters could be highly interesting for the oenological sector.

Authors


Luca Rolle

Affiliation : DIVAPRA - Food Technology Sector, University of Turin, via Leonardo da Vinci 44, 10095 Grugliasco, Torino, Italy

luca.rolle@unito.it

Fabrizio Torchio

Affiliation : DIVAPRA - Food Technology Sector, University of Turin, via Leonardo da Vinci 44, 10095 Grugliasco, Torino, Italy


Bénédicte Lorrain

Affiliation : Université Bordeaux Segalen, Unité de recherche oenologie, EA 4577, USC 1219 INRA, IPB, Faculté d'oenologie, Institut des sciences de la vigne et du vin, 210 chemin de Leysotte, CS 50008, 33882 Villenave d'Ornon cedex, France


Simone Giacosa

Affiliation : DIVAPRA - Food Technology Sector, University of Turin, via Leonardo da Vinci 44, 10095 Grugliasco, Torino, Italy


Susana Río Segade

Affiliation : DIVAPRA - Food Technology Sector, University of Turin, via Leonardo da Vinci 44, 10095 Grugliasco, Torino, Italy


Enzo Cagnasso

Affiliation : DIVAPRA - Food Technology Sector, University of Turin, via Leonardo da Vinci 44, 10095 Grugliasco, Torino, Italy


Vincenzo Gerbi

Affiliation : DIVAPRA - Food Technology Sector, University of Turin, via Leonardo da Vinci 44, 10095 Grugliasco, Torino, Italy


Pierre-Louis Teissedre

Affiliation : Université de Bordeaux, Institut des Sciences de la Vigne et du Vin, Faculté d’OEnologie, 210 chemin de Leysotte, CS 50008 33882, Villenave d’Ornon Cedex, France

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