Construction of a Prediction Model for Taste of Miso (Japanese Fermented Soybean Paste) Using Metabolic Profiling and Quantitative Descriptive Analyses

Abstract

Various types of miso are manufactured in Japan, which results in diverse flavors. However, the number of miso engineers who understand the variety of miso tastes has decreased due to decreases in the miso market. To solve this problem, we examined the potential to characterize various miso tastes using mainly low-molecular-weight hydrophilic component data by metabolic profiling. Analysis was performed by orthogonal partial least squares analysis, the relative intensity data for annotated compounds as explanatory variables and the data obtained by sensory evaluation as objective variables. The OPLS prediction model of taste had high accuracy and stability, and the components important for each taste were reasonable. From the results of model construction, we also found galactose correlated to umami. These results suggested that sensory evaluations of various types of miso may be in part replaced with instrumental analyses in the future.