Correlation between sensory evaluation scores of Japanese sake and metabolome profiles

Abstract

The aim of this study was to explore the association between taste and metabolite profiles of Japanese refined sake. Nontarget metabolome analysis was conducted using capillary electrophoresis mass spectrometry. Zatsumi, an unpleasant not clear flavor, and sweetness, bitterness, and sourness were graded by four experienced panelists. Regression models based on support vector regression (SVR) were used to estimate the relationships among sensory evaluation scores and quantified metabolites and visualized as a nonlinear relationship between sensory scores and metabolite components. The SVR model was highly accurate and versatile: the correlation coefficients for whole training data, cross-validation, and separated validation data were 0.86, 0.73, and 0.73, respectively, for zatsumi. Other sensory scores were also analyzed and modeled by SVR. The methodology demonstrated here carries great potential for predicting the relevant parameters and quantitative relationships between charged metabolites and sensory evaluation in Japanese refined sake.