目的 基于HPLC指纹图谱、多成分定量与化学计量学相结合的方法建立不同产地三棱质量评价方法。方法 采用中药色谱指纹图谱相似度评价系统（2004A版）对7省12批不同产地的三棱药材的HPLC指纹图谱进行相似度评价；通过对照品比对指认9种化学成分，并测定样品中9种成分含量；使用SPSS 20.0软件进行聚类分析和主成分分析。结果 选取了12个色谱峰作为指纹图谱共有峰，12批样品的相似度计算结果均大于0.800，说明各产地的药材有较好的一致性；测定了5-羟甲基糠醛、香草酸、阿魏酸、对羟基苯甲醛、对羟基苯甲酸、香兰素、原儿茶酸、对香豆酸、异阿魏酸9种成分的含量；通过聚类分析可将12批样品聚为4类；主成分分析用4个主成分对三棱药材进行综合评价，综合得分结果显示，河南新乡、江苏镇江、河北沧州、湖南岳阳、浙江金华、河南郑州的三棱药材在所有样品中的综合得分位于前6名；12批饮片主成分综合得分与含量测定结果存在相关性。结论 建立的三棱质量评价方法操作简便、重复性好、结果可靠，可用于全面评价三棱药材的质量。

Objective To establish a combinative method based on HPLC fingerprint, multi-component assay, and pattern recognition for quality evaluation of Sparganii Rhizoma. Methods The similarity analyzed with "Similarity Evaluation System for Chromatographic Fingerprint of Chinese Materia Medica 2004A", Nine kinds of components were identified by comparison with reference substances and their content in samples were determined and hierarchical clustering analysis (HCA) and principal component analysis (PCA) were performed by SPSS 20.0. Results There were 12 common peaks, and the similarity degrees of 12 batches of samples were more than 0.800, which showed that all the samples from different origins were of good consistency. Nine of them were identified as 5-hydroxymethylfurfural, vanillic acid, ferulic acid, p-hydroxybenzaldehyde, p-hydroxybenzoic acid, vanillin, protocatechuic acid, p-coumaric acid, and isoferulic acid; The samples were divided into four clusters by HCA. The result of PCA showed, the quality of samples could be evaluated basically. According to the composite score, the quality of Sparganii Rhizoma from different origins, Henan Xinxiang, Jiangsu Zhenjiang, Hebei Cangzhou, Hunan Yueyang, Zhejiang Jinhua, and Henan Zhengzhou were better than others. There was a correlation between the scores of the main components of the 12 batches of decoction pieces and the results of the content determination. Conclusion The method is simple, reproducible, and reliable, it can be used for quality control and evaluation of Sparganii Rhizoma from different origins.

R282.2

山东省中医药科技发展计划项目（2017-165）；山东省自然科学基金项目（ZR2015HL117）；山东省重点研发计划项目（2017CXGC1308）；山东省泰山学者工程专项（ts201511107）