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目的:建立不同产地高乌头药材的HPLC指纹图谱,并测定其中2种主要生物碱成分含量,为高乌头药材质量控制提供参考依据。方法:采用HPLC-DAD技术,以Dikma spursil C18色谱柱(4.6 mm×250 mm,5μm),乙腈-0.05 mol·L~(-1)磷酸二氢钠水溶液为流动相梯度洗脱,建立高乌头药材的指纹图谱并进行含量测定;采用中药指纹图谱相似度评价系统(2012版)对10批样品进行共有峰确认及相似度评价;通过SPSS 21.0统计软件采用主成分分析(PCA)和聚类分析(CA)对HPLC指纹图谱进行模式识别分析。结果:建立了高乌头药材指纹图谱,10批高乌头药材的相似度均>0.90;标定共有峰11个,并对其中2主要成分(高乌甲素、冉乌头碱)进行含量测定;聚类分析法(CA)将所有批次高乌头药材共分为4类,反映了10个批次不同地区高乌头药材的质量特征;主成分分析法(PCA)筛选出累计贡献率达到89.748%的4个主成分,得到决定高乌头药材质量5个化学成分。结论:建立的HPLC指纹图谱结合含量测定,PCA,CA方法,可以客观、有效、全面地用于高乌头药材的质量评价。
OBJECTIVE: To establish the HPLC fingerprints of A. officinalis from different areas and to determine the contents of two main alkaloids in them, and provide a reference for the quality control of A. officinalis. Methods: HPLC-DAD was used to elute the mobile phase of Dikma spursil C18 column (4.6 mm × 250 mm, 5 μm) and acetonitrile-0.05 mol·L -1 sodium dihydrogen phosphate aqueous solution. The fingerprint of the head herbs was determined and the content was determined. The common peak identification and similarity evaluation of ten batches of samples were carried out by using the Chinese medicine fingerprint similarity evaluation system (2012 version). The principal components analysis (PCA) and clustering Analysis (CA) Pattern recognition analysis of HPLC fingerprints. Results: The fingerprint of Radix Aconiti Kusnezoffii was established. The similarity of all the ten batches of Radix Aconiti Preparatum was> 0.90. The total number of peaks was 11, and the contents of two major components (lappaconitine and ranconitine) were determined. Cluster analysis method (CA) was used to classify all batches of A. officinalis into four groups, which reflected the quality characteristics of A. officinalis from 10 batches of different regions. The principal component analysis (PCA) screened the cumulative contribution rate Achieve 89.748% of the four main components, to get the quality of the ingredients of A. officinalis 5 chemical composition. Conclusion: The established HPLC fingerprint combined with content determination, PCA, CA method can be used objectively, effectively and comprehensively for the quality evaluation of A. officinalis.