Berry Heterogeneity as a Possible Factor Affecting the Potential of Seed Mechanical Properties to Classify Wine Grape Varieties and Estimate Flavanol Release in Wine-like Solution

  • F. Torchio Università di Torino, DISAFA – Dipartimento di Scienze Agrarie, Forestali e Alimentari, Via Leonardo da Vinci 44, 10095 Grugliasco, Italy
  • S. Giacosa Università di Torino, DISAFA – Dipartimento di Scienze Agrarie, Forestali e Alimentari, Via Leonardo da Vinci 44, 10095 Grugliasco, Italy
  • S. Río Segade Università di Torino, DISAFA – Dipartimento di Scienze Agrarie, Forestali e Alimentari, Via Leonardo da Vinci 44, 10095 Grugliasco, Italy
  • V. Gerbi Università di Torino, DISAFA – Dipartimento di Scienze Agrarie, Forestali e Alimentari, Via Leonardo da Vinci 44, 10095 Grugliasco, Italy
  • L. Rolle Università di Torino, DISAFA – Dipartimento di Scienze Agrarie, Forestali e Alimentari, Via Leonardo da Vinci 44, 10095 Grugliasco, Italy

Abstract

Seed mechanical properties were instrumentally measured by compression testing in thirty white and
red wine grape varieties at harvest. The effect of berry heterogeneity in a vineyard on these seed texture
parameters was also evaluated to improve the understanding of intra-sample variability. Furthermore, the
mechanical properties of the seeds were assessed as possible predictors of their phenolic extractability. The
results show that the texture parameters of the seeds are independent of the location of the berry in the
vineyard and the soluble solid content at harvest. Densimetric flotation of the berries permits the reduction
of the intra-sample variability that could hinder the differentiation and/or classification of wine grape
varieties according to seed mechanical attributes. Cluster analysis classified the wine grape varieties studied
into three groups according to seed hardness (low: 32.51 to 40.80 N, intermediate: 42.84 to 44.99 N, high:
46.71 to 57.78 N). The relationships between the seed mechanical properties and the extractable content
of phenolic compounds, determined by spectrophotometric and chromatographic reference chemical
methods, were evaluated by means of correlation analysis. Linear regression calibration models were
developed for each cluster. The statistical parameters highlighted that total flavonoids, proanthocyanidins
and flavanols reactive to vanillin can be predicted successfully from the seed mechanical properties for the
varieties having low and intermediate seed hardness (SEC% ca. 20, RPIQ > 1.6). For varieties with harder
seeds, a satisfactory predictive accuracy seems to require the construction of separate calibration models
for each cultivar (Nebbiolo, SEC% ca. 20, RPIQ > 2.2).

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Published
2016-09-21
Section
Articles