Prediction of yerba mate caffeine content using near infrared spectroscopy.

Abstract

There is a commercial and beneficial interest of producing yerba mate leaves into different grades of caffeine. This work uses a handheld and bench near infrared spectroscopy to compare and predict, using partial least squares regression, the amount of caffeine in yerba mate leaves. Standards of pure caffeine were compared, using high-performance liquid chromatography, with extracts of yerba mate. The bench spectroscopy gave a strong confidence model of caffeine prediction, whereas the handheld related to a fair model. For first detection and initial separation of yerba mate in the field, the modelling proposed can be used to predict caffeine intensity.