One-class modeling for the authentication of a geographically certified Brazilian coffee based on atomic-molecular
Larissa Batista Dos Santos1, Rodinei Augusti1, Clésia Cristina Nascentes1
1Departamento de Química, Universidade Federal de Minas Gerais, Belo Horizonte, MG 31270-901, Brazil.
Abstract:
Coffee is among the most consumed beverages worldwide and holds great economic importance for Brazil. Cerrado Mineiro region has gained prominence for its green coffee beans, certified with the Protected Designation of Origin (PDO), ensuring their quality and uniqueness. This study developed classification models to characterize these beans using total reflection X-ray fluorescence (TXRF), mid-infrared spectroscopy (MIRS), and paper-spray mass spectrometry (PS-MS). SIMCA (soft independent modeling of class analogy) one-class modeling was applied to individual techniques and fused data. The data fusion model combining MIR, PS-MS, and TXRF achieved 97 % accuracy. The interpretation of this model allowed the detection of the variables that contribute most to the authentication, related to chlorogenic acids and alkaloids, alongside the elements Cu, Rb, and Cl. The soft foodomics strategy proposed in this study enabled the detailed chemical characterization of this food matrix and the classification of distinctive, high-quality coffees, thus assuring their geographical indication.
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