目的 建立不同产地荸荠Heleocharis dulcis的HPLC指纹图谱及同时测定绿原酸、咖啡酸、阿魏酸、木犀草素、棕矢车菊素的方法，并结合化学模式识别法对不同产地荸荠进行质量评价。方法 采用ZORBAX SB C₁₈（250 mm×4.6 mm，5 μm）色谱柱，以乙腈-0.1%磷酸水溶液作为流动相，梯度洗脱，建立荸荠HPLC指纹图谱。运用“中药色谱指纹图谱相似度评价系统（2012.130723版本）”软件进行相似度评价，使用SPSS27.0软件、SIMCA14.1软件，结合聚类分析（hierarchical cluster analysis，HCA）、主成分分析（principal component analysis，PCA）和正交偏最小二乘判别分析（orthogonal partial least squares discriminant analysis，OPLS-DA）来评价不同产地荸荠质量；同时测定其中5个成分的含量，运用化学模式识别和熵权TOPSIS法对结果进行综合评价。结果 26批荸荠HPLC指纹图谱匹配出15个共有峰，指认了绿原酸、咖啡酸、阿魏酸、木犀草素和棕矢车菊素5个成分，指纹图谱的相似度在0.865～0.995；HCA将26批荸荠聚为2类；PCA得到3个主成分的累积方差贡献率为83.283%；OPLS-DA筛选出木犀草素和绿原酸等4个成分是不同产地荸荠药材质量差异的标志性成分；26批荸荠中绿原酸、咖啡酸、阿魏酸、木犀草素、棕矢车菊素的质量分数分别为5.43～60.65 μg/g、0.44～2.27 μg/g、1.65～6.46 μg/g、2.58～59.94 μg/g、0.31～24.40 μg/g；PCA与熵权TOPSIS分析均表明湖北产地的荸荠质量较优。结论 建立的HPLC指纹图谱方法稳定、可靠、重复性好，结合化学模式识别可用于荸荠的质量评价，为荸荠质量控制与资源开发提供参考。

Objective To establish the HPLC fingerprint of Heleocharis dulcis and simultaneously determine the contents of chlorogenic acid, caffeic acid, ferulic acid, luteolin and jaceosidin, and to evaluate the quality of H. dulcis from different regions by chemical pattern recognition method, so that a reference can be provided for quality control of H. dulcis. Methods The fingerprint of H. dulcis was established on a ZORBAX SB C₁₈ (250 mm × 4.6 mm, 5 μm) column using acetonitrile-0.1% phosphoric acid solution as the mobile phase with gradient elution. the “Chinese medicine chromatographic fingerprint pattern similarity evaluation system”(2012.130723 edition) was used for similarity evaluation, SPSS27.0 and SIMCA14.1software was performed for hierarchical cluster analysis (HCA), principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were utilized to evaluate the quality of H. dulcis from diverse origins. The five chemical constituents were identified and content determined by comparison with the reference substance, and the results were synthesized using chemical pattern recognition and entropy weighted TOPSIS method. Results A total of 15 common peaks were matched to 26 batches of H. dulcis HPLC fingerprints, and five components including chlorogenic acid, caffeic acid, ferulic acid, luteolin and jaceosidin were identified. The similarity of fingerprints was between 0.865 and 0.995. The 26 batches of H. dulcis were clustered into two classes by HCA. PCA analysis yielded a cumulative variance contribution of 83.283% for the three primary constituents. Four components, including luteolin and chlorogenic acid, were screened by OPLS-DA as the indicator components for the quality difference of H. dulcis from different regions. The mass fractions of chlorogenic acid, caffeic acid, ferulic acid, luteolin and jaceosidin in 26 batches of H.dulcis were 5.43—60.65 , 0.44—2.27, 1.65—6.46, 2.58—59.94 and 0.31—24.40 μg/g, successively. Both PCA and entropy weighted TOPSIS results indicated that samples from Hubei Province exhibited the best quality. Conclusion The established HPLC fingerprinting method is characterised by its stability, reliability, and reproducibility. which can be used for the quality evaluation of H. dulcis in combination with chemical pattern recognition, and provides a reference for the quality control and resource development of H. dulcis.

R282.6

湖北省科技厅重点研发项目（2025BCB067）；湖北省科技厅重点研发大健康计划项目（2022BCE017）；湖北省卫生健康委员会中医药重点项目（ZY2023Z015）；湖北省科技厅自然科学基金项目（2025AFB805，2025AFB839，2025AFD301，2025AFD294，2023AFB600，2022CFB357，2022CFB427）；宜昌市医疗卫生研究项目（A22-2-059，A23-1-061）；湖北省卫生健康委员会科研资助项目（WJ2023M153）；湖北省功能性消化系统疾病中医临床医学研究中心开放基金（SXZ202303，SXZ202308，SXZ202311）