Abstract The consumption of yerba mate beverages is related to several health benefits. These desirable properties are mainly due to the bioactive compounds. However, the levels of those compounds are directly affected by factors such as geographical origin. This study aimed to use chemometrics to evaluate the antioxidant compounds of yerba mate (consumed as chimarrão) marketed in southern Brazil. Neochlorogenic acid and caffeine were the main bioactive compounds found in this type of yerba mate beverage (chimarrão). The dataset was analyzed by chemometrics, and principal component analysis using the first three principal components explained 61.30% of the total variance. Hierarchical cluster analysis suggested three clusters, with cluster 1 containing the majority of the samples from the states of Rio Grande do Sul and Paraná, with higher levels of phenolics, methylxanthines, and antioxidant activity. The supervised methods, soft independent modeling of class analogy (SIMCA) and partial least squares-discriminant analysis (PLS-DA), had similar predictability (≥75% of accuracy) in terms of classifying yerba mate according to different Brazilian regions. Therefore, the chemometric tools used in the current study was suitable to monitor and assess a large variation of the antioxidant composition of yerba mate from different southern Brazilian states.

Abstract The effect of the variety (Gala, Lis Gala and Fuji Suprema) and the ripening stage (unripe, ripe and senescent) of apples on the phenolic compounds (HPLC) and antioxidant capacity (FRAP and DPPH) of apple juices and ciders were evaluated. The phenolic content of the Gala and Lis Gala apple juices decreased from the unripe to ripe stages and increased from the ripe to the senescent stages, while in the case of Fuji Suprema these values decreased with senescence. Fermentation caused a reduction (17 to 50%) of phenolics and the most affected were hydroxycinnamic acids and flavanols. Principal component analysis confirmed the influence of variety, and the use of multivariate regression (PLS) made it possible to create significant models (p < 0.05) to predict the antioxidant activity. The phenolic composition of the juices at different ripening stages was related to the variety of apple, which influenced the effect of fermentation on these compounds.