Causal reasoning applied to sensory analysis: the case of the Italian wine

In this paper, a structure learning algorithm is applied to the sensory analysis field to study the factors that have an influence on the quality of Italian wines. Directed acyclic graphs, involving chemical as well as sensory variables, will be proposed to suggest hypotheses about causal connections between these variables and the Altroconsumo’s Global Score of Quality, given by the Italian independent consumer’s association Altroconsumo in its annual publication Guida Vini (Wines’ Guide). The analysis is performed considering all types of wine included in the database, as well as red and white wines separately.