Determination of the age of dry red wine by multivariate techniques using color parameters and pigments

Vintage is a decisive factor for market price of commercial bottled dry red wines. Aim of this study was to use color parameters and pigments for the prediction of the age of dry red wine by means of partial least squares (PLS) and multiple linear regression (MLR). Both models allow the prediction of the age accurately, with high coefficients of determination (R2), and low enough root mean square error of cross-validation (RMSECV). Although less variables were required to obtain a successful MLR model, its prediction results were as accurate as the model obtained by PLS. The ratio of the first polymeric pigments (TFPP) and malvidin-3-glycoside was demonstrated to be a promising and practical chemical parameter for the rapid and simple age assessment of the dry red wines.

Automated summary

This study successfully predicted the age of dry red wines using color parameters and pigments through partial least squares (PLS) and multiple linear regression (MLR). Both models accurately predicted the age, with high coefficients of determination and low root mean square error of cross-validation. The ratio of the first polymeric pigments (TFPP) and malvidin-3-glycoside was identified as a promising chemical parameter for rapid and simple age assessment of dry red wines.