Abstract
A simple, fast and eco-friendly methodology to determine quality parameters, such as moisture, total ashes and caffeine content, in yerba mate samples was developed using near-infrared (NIR) spectroscopy and chemometrics. The NIR spectra of the yerba mate samples were measured directly on the product contained in the packages, thus avoiding the need of previous pretreatments. In the present study, NIR spectroscopy was used combined with chemometric regression methods based on partial least squares (PLS) algorithm. Performance of the regression models was adequate with very good statistical results, the correlation coefficients (R2) were above 0.90 with a root mean square error of prediction (RMSEP) lower than 0.17% for the three quality control parameters studied. Besides, the quality of the proposed methodology was also evidenced on the basis of the relative error of prediction (REP), which was less than 6.97% in all cases, and the limit of detection (LOD), which ranged from 0.72 to 0.80% for moisture, from 0.74 to 0.76% for total ashes, and from 0.22 to 0.25% for caffeine. Overall, the results demonstrated that NIR spectroscopy with PLS analysis can be successfully applied as a rapid routine method to determine parameters of quality control in yerba mate samples.
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