Issue 28, 2023, Issue in Progress

Simultaneous determination of phenols in the four main original plants of the famous traditional Chinese medicine Shihu by pressurized capillary electrochromatography

Abstract

A rapid pressurized capillary electrochromatography (pCEC) method has been established for the simultaneous analysis of 11 phenols in the four main original plants of the famous traditional Chinese medicine (TCM) Shihu. The effects of wavelength, mobile phase, flow rate, pH value, concentration of buffer, and applied voltage were systematically studied. The investigated 11 phenols could be isolated in 35 min on a reversed-phase EP-100-20/45-3-C18 capillary column using the established method. To apply the established pCEC method, all phenols except tristin (11) were detected in the four Dendrobium plants. A total of 10 components were detected in D. huoshanense, 6 components in D. nobile, 3 components in D. chrysotoxum, and 4 components in D. fimbriatum. The consistent evaluation revealed that the similarities among the four original plants of Shihu were 38.2–86.0% based on the 11 polyphenols and 92.5–97.7% based on the pCEC fingerprints. These further suggested that the components of the four original plants of TCM Shihu might be significantly different. Further investigation should be conducted to confirm and evaluate if the four species could be used as the same medicine with the same amount according to Chinese Pharmacopoeia (ChP).

Graphical abstract: Simultaneous determination of phenols in the four main original plants of the famous traditional Chinese medicine Shihu by pressurized capillary electrochromatography

Article information

Article type
Paper
Submitted
06 Feb 2023
Accepted
09 Jun 2023
First published
27 Jun 2023
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2023,13, 19455-19463

Simultaneous determination of phenols in the four main original plants of the famous traditional Chinese medicine Shihu by pressurized capillary electrochromatography

X. Liu, C. Qin, N. Chen, J. Hao, S. Ma, M. Zhang, Y. Song, Y. Min, Y. Bu and S. Li, RSC Adv., 2023, 13, 19455 DOI: 10.1039/D3RA00761H

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