Herbal teas and other herbal preparations are becoming more and more popular, and it is essential to ensure their quality. Quality control methods that are simple, fast, and of low cost are needed by the producers and by inspections. Infrared spectroscopy coupled with multivariate mathematical methods has been shown to be useful for the identification and characterization of plant samples. In this work, we developed a method for the identification of herbal drugs in different herbal teas. 100 one-component herbal teas were first used to build an identification algorithm, which showed 100 % correct classification. In the next validation step, 13 samples from 7 herbal mixtures were analyzed, confirming high accurate results for classification. The influence of using different number of components in the principal component analysis is also explored. Infrared spectroscopy coupled with analysis of variance, principal component analysis, and discriminant analysis was shown to be highly applicable for quality control procedures.
Georg Thieme Verlag KG Stuttgart · New York.