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ORIGINAL RESEARCH article

Front. Pharmacol.

Sec. Ethnopharmacology

This article is part of the Research TopicInnovative approaches to authenticate multi-species traditional herbal productsView all articles

UHPLC-Q/TOF-MS-Based Differential Metabolite Screening and Origins Classification of Codonopsis Radix

Provisionally accepted
  • Shanghai University of Traditional Chinese Medicine, Shanghai, China

The final, formatted version of the article will be published soon.

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. 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. 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. 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.

Keywords: Codonopsis Radix, neural network model, Ratio method, UHPLC-Q/TOF-MS, untargeted metabolomics

Received: 21 Nov 2025; Accepted: 23 Jan 2026.

Copyright: © 2026 Xuchen, Zhang, Fang, Ding and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Tong Zhang

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