Metabolites Profiling for the Classification of Medicinal Plants

Medicinal plants have been increasingly used worldwide during the last few decades and the importance on quality control is well established. The overall quality of medicinal plants is dependent on many factors including geographical origins, species, ages, and various environmental factors. Adulteration and substitution of raw materials is another flaw to interfere correct and proper use of the medicinal plants. An ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QToF-MS) method was applied to study the metabolite profiling of Panax ginseng samples aged from 1 to 6 years. Multivariate statistical methods such as principal component analysis and hierarchical clustering analysis were used to compare the derived patterns among the samples. The data set was subsequently used with various metabolite selection methods for sophisticated classification with the optimal number of metabolites. The results showed variations in accuracy among the classification methods for the samples of different ages, especially for those aged 4, 5, and 6 years. This proposed analytical method coupled with multivariate analysis is fast, accurate, and reliable for discriminating the cultivation ages of P. ginseng samples. This approach with UPLC/Q-TOF MS successfully identified and classified the samples tested according to their origins.