Separations (Oct 2024)

Identification of Ginseng Radix et Rhizoma, Panacis Quinquefolii Radix, Notoginseng Radix et Rhizoma, and Platycodonis Radix Based on UHPLC-QTOF-MS and “Matrix Characteristics”

  • Jiating Zhang,
  • Fangliang He,
  • Xianrui Wang,
  • Wenguang Jing,
  • Minghua Li,
  • Xiaohan Guo,
  • Xianlong Cheng,
  • Fudong An,
  • Feng Wei

DOI
https://doi.org/10.3390/separations11110304
Journal volume & issue
Vol. 11, no. 11
p. 304

Abstract

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Ginseng Radix et Rhizoma (GRR), Panacis Quinquefolii Radix (PQR), Notoginseng radix et rhizoma (NRR) and Platycodonis Radix (PR) are often confused in the material market because of similar appearances and characteristics. Moreover, chemical identification methods tend to characterize the whole herb with regard to a single or a few components, which is an inaccurate representation and does not demonstrate the effective utilization of unknown components, and the result is unconvincing. In order to strengthen quality control, improve identification efficiency, and realize digital identification at the individual level of traditional Chinese medicine (TCM), we have put forward the “matrix characteristics” of TCM, combined with a UHPLC-QTOF-MS analysis to explore and realize the digital identification of GRR, PQR, NRR, and PR. The mass spectrometry was quantized to extract common data from different batches of the same TCMs as their matrix characteristics, and the matching credibility (M) was given by matching the “matrix characteristics” with unknown Chinese medicines. The results show that within a reasonable parameter threshold range, the M of four TCMs was higher than 92.00% compared with their own “matrix characteristics”, which was significantly higher than the M ranked second. Furthermore, the digital identification of four TCMs can be successfully realized based on the UHPLC-QTOF-MS analysis and “matrix characteristics”. This has important reference significance for developing the digital identification of GRR at an individual level based on UPLC-QTOF-MS and “matrix characteristics”.

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