A one-class classification approach for authentication of specialty coffees by inductively coupled plasma mass spectroscopy (ICP-MS)

Abstract

Due to the lucrative nature of specialty coffees, there have been instances of adulteration where low-cost materials are mixed in to increase the overall volume, resulting in illegal profit. A widely used and recommended approach to detect possible adulteration is the application of one-class classifiers (OCC), which only require information about the target class to build the models. Thus, this work aimed to identify adulterations in specialty coffees with low-quality coffee using multielement analysis determined by ICP-MS and to evaluate the performance of one-class classifiers (dd-SIMCA, OCRF, and OCPLS). Therefore, authentic specialty coffee samples were adulterated with low-quality coffee in 25 % to 75 % (w/w) proportions. Samples were subjected to acid decomposition for analysis by ICP-MS. OCPLS method presented the best performance to detect adulterations with low-quality coffee in specialty coffees, showing higher specificity (SPE = 100 %) and reliability rate (RLR = 94.3 %).

Keywords: ICP-MS; OCPLS; Random Forest; Specialty coffee; dd-SIMCA.