Abstract
INTRODUCTION: Codonopsis Radix (CR), also known as Dangshen, is a renowned plant native to China, highly valued for its unique medicinal properties. However, due to the existence of numerous closely related origins and the similarities in their interspecies traits, microscopic characteristics, and physicochemical properties, different origins of CR have been circulating in the market, posing significant challenges for standardizing its medicinal use. Therefore, establishing an accurate identification method is crucial for advancing research on CR and ensuring its proper utilization. METHODS: In this study, a UHPLC-Q/TOF-MS analysis method was developed to identify differential metabolites among three origins of CR using one-way analysis of variance (ANOVA). The metabolites were distinguished based on the response ratios of the differential metabolites. Additionally, a neural network (NN) model was established to validate the classification capability. RESULTS: Metabolomic results revealed that among the 56 identified metabolites, 29 differential metabolites were screened out. Notably, the response ratios of codonopyrrolidium A, codonopyrrolidium D, tryptophan, and codonopsinol A against 3'-hydroxy codonopyrrolidium B exhibited significant differences among the three origins. Verification experiments demonstrated that the NN model achieved a prediction accuracy of 100%, with a confidence measure exceeding 0.98. DISCUSSION: This study established two methods for identifying the origins of CR: a simple and rapid ratio method, and a highly accurate NN model. It demonstrated the feasibility of identifying the origins of CR through cross-validation, providing new insights and methodologies for the origin identification of multi-origin traditional Chinese medicine.