Abstract

This paper describes a formalization of the essential organoleptic characteristics assessed in the wine evaluation process. A scalar quality metrics is associated and bound to 3 dimensions and 6 variables representing standard organoleptic wine features detected by mouth-tasting (visual-tasting and nose-tasting are not the subject of this work). The correlation existing between such wine characteristics is mathematically modelled by a matrix of operators’ values acting on the corresponding variables. An algebraic notation is developed to express the multi-dimensional nature of the wine quality and to provide a measurement tool for the still subjective evaluation of a wine. Probability distributions are computed, or deduced from frequency distributions, for the values measured on a sample of over 100 wines in order to test the metrics performance in terms of phase-space and bias. The statistical meaning of the empiric distributions obtained by applying such a wine evaluation metrics is analysed by benchmarking them versus known theoretical mathematical conditions: this reverse-engineering of the metrics allows the factorization of the intrinsic metrics features from the effects due to the interaction with the “observer” and his preferences. Finally, the relation between the independent and correlated quantities in the evaluation of the wines is emphasized, and a conditional probability model is proposed.