Descriptive screening and lexicon development of non-aged artisanal cachaça sensorial profile using principal component analysis and Kohonen artificial neural networks

Abstract

Cachaça is a distilled spirit made from sugarcane, exclusively produced in Brazil, and appreciated worldwide. This paper seeks to evaluate the sensory characteristics of 24 nonaged artisanal cachaça samples from Salinas (Minas Gerais, Brazil) through descriptive analysis, as well as chemometrically treat the obtained data based on principal components analysis (PCA) and Kohonen's neural network. The attributes (23) were divided between aroma (11) and flavor (12). PCA does not show good differentiation of nonaged cachaça samples. On the other hand, by using Kohonen's neural network it was possible to group samples according to their aroma and flavor characteristics in 9 and 10 distinct groups, respectively. A reduced number of descriptors could be used to describe the flavor of cachaça samples (alcohol, acidic, sweet, bitter, citric, tar, and burning), as significant correlations (R > 0.70, p