Early Prediction of Shiraz Wine Quality Based on Small Volatile Compounds in Grapes

Abstract

Wine producers perform early wine quality prediction based on berry morphology, the taste of the berry and the measurement of basic chemical parameters. Incorporating analysis on grape and wine volatiles could potentially achieve a more accurate prediction of wine quality, but forming these models requires careful selection of grapes, controlled fermentations, and standardised quality assessment. Here, we present 3 models for the prediction of quality in Shiraz wine. Modelling was performed by general regression analysis with 4-fold cross-validation: Model 1 (R2 = 99.97% and 4-foldR2 = 97.61%) for prediction of wine quality from wine volatiles, Model 2 (R2 = 99.89% and 4-foldR2 = 98.42%) for early prediction of wine quality from free-bound and glycosidically bound grape volatiles, and Model 3 (R2 = 91.62% and 4-foldR2 = 80.21%) for the prediction of wine quality from free grape volatiles only. The accuracy of these models presents an advancement in the early prediction of wine quality and provides a valuable tool to assist grape growers and winemakers to support the understanding of quality in the vineyard to better direct scarce resources.