Resumen

TORCHIO, F. et al. 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. S. Afr. J. Enol. Vitic. [online]. 2014, vol.35, n.1, pp.20-42. ISSN 2224-7904.

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).

Palabras clave : Instrumental texture analysis; mechanical parameters; wine grape seeds; berry heterogeneity; varietal classification; extractable phenols prediction.

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