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HPLC fingerprint combined with chemical pattern recognition for quality evaluation of poeny leaves from Henan province*

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  • 1. Henan Natural Product Biotechnology Co., Ltd, Henan Academy of Sciences, Zhengzhou 450002, China;
    2. Henan Bussiness Research Institute Co., Ltd, Henan Academy of Sciences, Zhengzhou 450011, China

Received date: 2022-02-24

  Online published: 2024-06-24

Abstract

Objective: To establish an HPLC method and chemical pattern recognition model of poeny leaves from Henan province, providing quality evaluation of poeny leaves. Methods: Analysis was performed on an Agilent C18 column (250 mm×4.6 mm, 5 μm) with acetonitrile-0.1% formic acid for gradient elution. The flow rate was 1.0 mL·min-1, the detection wavelength was set at 270 nm, and the column temperature was 35 ℃. “Similarity Evaluation System of Fingerprint of Tradition Chinese Medicine (2012 edition)” was adopted to establish reference fingerprint and to calculate the similarities of 21 batches of poeny leaves. Combining with principal component analysis and cluster analysis, the overall quality of poeny leaves was evaluated. Results: There were 18 common characteristic peaks in the fingerprints of the 21 batches of samples, 5 peaks were identified as gallic acid, ethylgallate, paeoniflorin, ellagic acid and luteoloside. Similarities of 21 batches of samples were between 0.907-0.979. Samples were clustered into 3 types by principal component analysis which consistented with cluster analysis result. Conclusion: The method combining HPLC fingerprint with chemical pattern recognition is simple and reliable, which can quickly evaluate the quality and consistency of different resources of poeny leaves from Henan province, and is suitable for the evaluation of the overall quality evaluation of poeny leaves.

Cite this article

NING Er-juan, CHEN Ling, WANG Xue-fang, ZHANG Li-xian, LI Xiao, ZHANG Li-pan, WANG Fa-yun . HPLC fingerprint combined with chemical pattern recognition for quality evaluation of poeny leaves from Henan province*[J]. Chinese Journal of Pharmaceutical Analysis, 2023 , 43(3) : 486 -493 . DOI: 10.16155/j.0254-1793.2023.03.16

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