Authentication of Specialty Coffees from the Fluminense Northwest and Caparaó Regions (Brazil) Using UV-Vis Spectroscopy and Synthetic Samples Partial Least Square Discriminant Analysis (SS-PLS-DA)

Abstract

Caparaó and the Fluminense northwest regions are nationally recognized by the important contribution on coffee production and exportation. Adulterations involving specialty coffees result in a decrease in the quality of the final product. However, obtaining many different samples from the same region is unfeasible in some cases, needing strategies to work with a limited number of samples for pattern recognition. Thus, this work is the first to use the construction of synthetic samples (SS) for analysis of coffees, and its objective is to identify adulterations in specialty coffees with bark, straw and low-quality beans, using UV-Vis spectroscopy, associated with chemometric methods. The synthetic samples partial least square discriminant analysis (SS-PLS-DA) showed better specificity, sensitivity and reliability rates than the Hard PLS-DA models. One-class methods (soft independent modeling of class analogy (SIMCA) and data driven soft independent modeling of class analogy (DD-SIMCA)) showed low specificity and reliability. The discriminant methods together with the synthetic samples proved to be adequate to identify adulterations in specialty coffees.