Construction of a Regression Model for a Coffee Sensory Evaluation Through the Comprehensive Analysis of Metabolites

Eight types of coffee beans were ground, roasted, and extracted under the same conditions and subjected to sensory evaluation. Metabolites were then extracted from each coffee bean type and measured using GC-MS/MS analysis. Using the results of the sensory evaluation as response variables and the processed values of the detected peak areas of metabolites as explanatory variables, a partial least squares (PLS) regression model of the relationship between these variables was constructed. The components that affect the taste were then examined using the results of the PLS regression model.