Chemometric Approach Using ComDim and PLS-DA for Discrimination and Classification of Commercial Yerba Mate (Ilex paraguariensis St. Hil.)

Abstract

Yerba mate samples from three different states of Brazil were evaluated in order to discriminate them regarding the presence of sugar and geographic origin. High-performance liquid chromatography (HPLC), phytochemical compounds, in vitro antioxidant activity, visible and near-infrared (NIR) spectroscopy, colorimetry, and electronic nose were used in tandem with chemometric methods. The multiblock exploratory analysis (ComDim) was able to discriminate the samples containing sugar; however, it was not possible to discriminate them by geographical origin. Furthermore, ComDim results showed the NIR spectra presented the best discriminating capacity. Partial least square discriminant analysis (PLS-DA) models constructed using NIR spectra classified the samples assertively according to the presence of sugar (100% of sensitivity and specificity for the prediction set), and reasonable models were also obtained for the geographic classification (80% of sensitivity and 93% of specificity for the prediction set). The multiblock approach allowed an overall evaluation of the data collected through different analytical methods. In addition, among the methods applied, NIR spectroscopy was faster and cheaper and allowed for better sample discrimination.