Voltammetric fingerprinting of aqueous infusion of chemically modified yerba mate leaves: ASCA model analysis and PLS-DA discrimination.

Yerba mate (Ilex Paraguariensis) is widely consumed and used in the food and cosmetics industries. Its benefits include controlling cholesterol and diabetes, improving digestion and concentration, and providing antioxidant effects. However, excessive consumption can cause nervousness and insomnia due to the presence of caffeine. This study proposes an alternative methodology for the quality control of plants with diverse chemical compositions, using cyclic voltammetry and ASCA (ANOVA-Simultaneous Component Analysis) modeling to evaluate genotype and shading levels in plants. It also employs PLS-DA (Partial Least Squares Discriminant Analysis) to differentiate between decaffeinated and highly caffeinated yerba mate. The results demonstrated 100 % sensitivity and specificity in the discrimination models, confirming genetic differences and the viability of a robust quality control model. The developed method is notable for being economical, fast, accurate, and environmentally friendly.