HUBEI AGRICULTURAL SCIENCES ›› 2025, Vol. 64 ›› Issue (6): 128-135.doi: 10.14088/j.cnki.issn0439-8114.2025.06.021

• Chinese Herbal Medicines • Previous Articles     Next Articles

Chemical compositions,UPLC fingerprints and chemical pattern recognition evaluation of Yao medicine Galium aparine Linn. var. echinospermum (Wallr.) Cuf.

XIE Xian-li1, QING Li-ting1, LIANG Jian-li1, LIU Dan2, LI Yao-hua1   

  1. 1. Key Laboratory of Extraction, Purification and Quality Analysis of Traditional Chinese Medicine in Guangxi Universities / National Experimental Teaching Demonstration Center of Chinese Materia Medica, Guangxi University of Chinese Medicine, Nanning 530200,China;
    2. Faculty of Chinese Medicine Guangxi University of Chinese Medicine, Nanning 530200,China
  • Received:2024-12-30 Online:2025-06-25 Published:2025-07-18

Abstract: The chemical constituents of Galium aparine Linn. var. echinospermum (Wallr.) Cuf. were identified using UPLC-Q-Exactive-MS in combination with reference substance comparison. The mobile phase was methanol-0.1% formic acid with gradient elution, and the flow rate was set to 0.2 mL/min. The column temperature was maintained at 30 ℃. ACQUITY UPLC HSS-T3 C18 ( 150 mm × 3 mm, 1.8 μm ) column was used. The detection wavelengths were 260 nm and 340 nm. At the same time, UPLC fingerprint analysis was performed on 10 batches of Galium aparine samples from different producing areas, and chemical pattern recognition methods such as similarity evaluation, cluster analysis, and principal component analysis were used to comprehensively evaluate their quality. The results showed that 32 components in Galium aparine were successfully identified by UPLC-Q-Exactive-MS technology. The UPLC fingerprints of 10 batches of Galium aparine samples were established, and a total of 17 common peaks were calibrated, of which 3 chromatographic peaks were identified as phenolic acids. The similarity of 10 batches of samples was 0.897 ~ 0.996. The samples were divided into two categories by cluster analysis. The results of principal component analysis were consistent with cluster analysis. It was demonstrated that the high-resolution liquid-mass spectrometry technique combined with UPLC fingerprinting and chemical pattern recognition method could comprehensively and effectively evaluate the quality of Galium aparine.

Key words: Galium aparine Linn. var. echinospermum (Wallr.) Cuf., UPLC-Q-Exactive-MS, fingerprint, chemical pattern recognition, quality evaluation

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