Multivariate calibration applied to study of volatile predictors of arabica coffee quality.

The chemical complexity of coffee influences the sensory evaluation of the beverage, the main method used to define the quality of the coffee. In view of the subjectivity that method offers, we propose the association of an instrumental method with multivariate calibration (PLS and GA-SVR) to predict the quality of arabica coffee as support for sensory analysis. Arabica coffee samples were submitted to sensory evaluation using the Specialty Coffee Association (SCA) protocol and HS-SPME-GC/MS analysis. The models presented RMSEp results from 0.20 to 0.25, within the evaluation range the quality levels of sensory attributes (0.25). For the fragrance/aroma attribute, a value of Rp equal to 0.8503 was reached. 15 volatile compounds were identified as responsible for predicting the quality of arabica coffee, among which, 1-nonadecene was first reported as an impact compound in the prediction of important sensory attributes.