Identification of constitutive herbs in an herbal product is critical for ensuring its quality and efficacy. However, current identification methods often lack universality, entail long durations, and involve complex procedures. Therefore, there is an urgent need to develop innovative methods for identifying constitutive herbs. This paper aims to propose a more refined, universal, simple, rapid, and eco-friendly method for identifying more constitutive herbs in herbal products, significantly enhancing the precision and efficiency of quality control method of herbal products. Leveraging UHPLC‒Q‒TOF‒MS (ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry) data of herbs and the R language, we devised algorithms to find exclusive ions and diagnostic ions of each herb. An open platform named IdenHerb for identifying constitutive herbs of herbal products was established. Using IdenHerb, exclusive ions of 94 herbs were found, and from these exclusive ions, their diagnostic ions were screened out. These diagnostic ions were successfully applied to identify constitutive herbs of two mixtures of herbal powders and eight Chinese patent medicines. Furthermore, this methodology was evaluated using three commonly encountered adulterants as test cases. After incorporating the LC‒MS data of these adulterants into the comprehensive LC‒MS database of all herbs, this approach demonstrated excellent discriminatory capabilities. Compared to the Chinese Pharmacopoeia (2020 edition), IdenHerb is capable of identifying a greater number of constituent herbs, thereby enhancing the level of quality control for the herbal products. This strategy deserves further research and wide application.
Keywords: Chinese patent medicines; Constitutive herb identification; Exclusive ions; Herbal products; Large-scale data; R language; UHPLC‒Q‒TOF‒MS.
Copyright © 2025 Elsevier B.V. All rights reserved.