Abstract
Phenolic compounds play a major role in the intensity and characteristics of wine astringency. However, studies involving commercial wine samples are still scarce. The aim of the present work was to study the relationship between astringency and phenolic composition of commercial Uruguayan Tannat wines using boosted regression trees (BRT), a novel predictive method. Forty commercial Tannat wines were evaluated by a trained sensory panel (9 members), who assessed their total astringency intensity using time-intensity (TI) and described their astringency sub-qualities using a check-all-that-apply (CATA) question composed of sixteen terms. The polyphenolic profiles of the wines were determined by HPLC-MS and conventional oenological parameters were also obtained. Fifty BRT models with different partitions of the data in training and test sets were built for astringency maximum intensity (Imax) and for the frequency of use of the 16 astringency sub-qualities considered in the CATA question. As predictor variables, 84 phenolic compounds and oenological parameters were considered for all BRT models. Both strong and weak predictive models were obtained for each response variable. Predictive accuracy was much higher for astringency intensity than for the frequency of mention of astringency sub-qualities. Still, the BRT models allowed to point out to some compositional variables most likely involved in wine astringency perception. Total tannin concentration (chemically determined) was the most relevant explanatory variable for sensory astringency, while flavan-3-ols were the individual phenolic compounds with the highest contribution to astringency, particularly some dimers, trimers and the sum of non-galloylated tetramers. However, the effect of these predictors differed according to the astringency sub-quality considered as response. As expected, non-linear relationships between phenolic compounds and astringency were found. These results contribute to the understanding of the influence of phenolic composition on wine astringency and stress the potential of BRT models for identifying the compounds responsible for this complex sensory characteristic.
Published Version
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