Discrimination of three Siegesbeckiae Herba species using UPLC-QTOF/MS-based metabolomics approach

Abstract The plant origin is one of the most important factors for the quality control of traditional Chinese medicines (TCMs) and highly affected on their safety and effectiveness in clinical applications. Multi-origin has been widely observed for many TCMs. Siegesbeckiae Herba (SH) is a traditional anti-rheumatic TCM which is originated from the plants of Siegesbeckia pubescens Makino (SP), S. orientalis L. (SO), and S. glabrescens Makino (SG). In the present study, an UPLC-QTOF/MS method were validated and successfully applied for the determination of the chemical profiles in the three SH species. The data were statistical analyzed with the OPLS-DA analysis and One-Way ANOVA F -test. Obvious differences in chemistry were observed in different SH species and 40 components were identified. Finally, 6 components were selected as potential chemical markers for the discrimination of SP, SO and SG based on the characteristic distribution in individual SH species.