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Pimacao is a traditional Chinese folk medicine and is the main component of the famous Chinese herbal remedy “Yunnan Baiyao” for its significant analgesic activity in the treatment of wounds. Due to increases in consumption, its wild population is now difficult to find, and adulterant from the same genus has occurred. However, this is challenging to distinguish the species of  Veratrum  in Pimacao using dried roots and rhizomes or medicinal powder. ITS2 sequences and steroidal alkaloids by the non-targeted and pseudo-targeted metabolomics methods were taken advantage of establishing an effective identification method. Based on the ITS2 sequence, metabolite profiling of steroidal alkaloids and morphological characteristics, the classification of two distinct subspecies in  V. mengzeanum  has been reinforced. In addition, the new subspecies  V. mengzeanum  subsp.  phuwae  was collected in China for the first time. The ITS2 sequence could be used in the identification of  V. taliense ,  V. mengtzeanum ,  V. stenophyllum , and  V. nigrum , but is insufficient for intraspecific identification. Simultaneously, 147 variables were labeled by non-targeted analysis accomplished utilizing an ultra-high-performance liquid chromatography electrospray ionization orbitrap tandem mass spectrometry (UPLC-ESI-QE-Orbitrap-MS) system consisting of an Orbitrap QE HF-X. Followed by a pseudo-targeted analysis method developed for the Qtrap 6500-plus mass spectrometry system coupled with an ESI source, 29 labeled steroidal alkaloids detected by the MRM mode could distinguish between four species. Notably, 25 labeled steroidal alkaloids could distinguish between three closely related species. These have the potential to be used as markers for identification. Furthermore, there were several variables with statistical differences between two subspecies of  V. mengtzeanum  and populations of  V. taliense ,  V. mengtzeanum , and  V. stenophyllum .

Identification of Veratrum Species in Pimacao Based on ITS2 Sequences and Steroidal Alkaloids by a Pseudo-Targeted Metabolomics Method