尖尾风药材的HPLC指纹图谱建立及聚类分析和主成分分析

发布时间:2019-08-30 来源: 感恩亲情 点击:


  摘 要 目的:建立尖尾風药材的高效液相色谱(HPLC)指纹图谱,并进行聚类分析和主成分分析。方法:采用HPLC法。色谱柱为ECOSIL ODS-EXTEND C18,流动相为乙腈-0.2%磷酸溶液(梯度洗脱),流速为1.0 mL/min,检测波长为334 nm,柱温为30 ℃,进样量为20 μL。以毛蕊花糖苷为参照,绘制14批药材样品的HPLC图谱,采用《中药色谱指纹图谱相似度评价系统》(2012版)进行相似度评价,确定共有峰,并采用SPSS 22.0软件进行聚类分析和主成分分析。结果:14批药材样品的HPLC图谱有13个共有峰,相似度为0.674~0.996,表明14批药材样品相似度差异较大,部分批次相似度大于0.9(9批)。14批药材样品可聚为4类,S3、S5、S6、S11聚为一类,S1、S2、S4、S9、S10聚为一类,S7、S8、S13、S14聚为一类,S12为一类。经主成分分析,主成分1和主成分2是影响药材样品质量评价的主要因子,2个主成分的累积方差贡献率为90.32%,以S13的主成分综合得分最高。结论:所建指纹图谱以及聚类分析和主成分分析结果可为尖尾风药材的质量评价提供参考。
  关键词 尖尾风;高效液相色谱法;指纹图谱;聚类分析;主成分分析
  中图分类号 R284.1 文献标志码 A 文章编号 1001-0408(2018)16-2215-05
  ABSTRACT OBJECTIVE: To establish HLPC fingerprint of Callicarpae longsissimae, and to conduct cluster analysis and principal component analysis. METHODS: HPLC method was adopted. The determination was performed on ECOSIL ODS- EXTEND C18 column with mobile phase consisted of acetonitrile-0.2% phosphoric acid solution (gradient elution) at the flow rate of 1.0 mL/min. The detection wavelength was set at 334 nm, and the column temperature was 30 ℃. The sample size was 20 μL. Using acteoside as reference, HPLC fingerprints of 14 batches of C. longsissimae were determined. The similarity of 14 batches of samples was evaluated by TCM Chromatographic Fingerprint Similarity Evaluation System (2012 edition) to confirm common peak. Cluster analysis and principal component analysis were performed by using SPSS 22.0 software. RESULTS: There were 13 common peaks in HPLC chromatograms of 14 batches of sample, the similarity of which was 0.674-0.996, indicating the similarity of 14 batches of sample was great different, but the similarity of some batches was greater than 0.9 (9 batches). After validation, HPLC fingerprints of 14 batches of sample were in good agreement with control fingerprint. Fourteen batches of samples were clustered into 4 categories; S3,S5,S6 and S11 were clustered into one category; S1,S2,S4,S9 and S10 were clustered into one category;S7,S8,S13 and S14 were clustered into one category;S12 was clustered into one category. By principal component analysis, principal component 1 and principal component 2 were main influential factors of medcicinal material quality;accumulative variance contribution rate of them was 90.32%,and comprehensive score of S13 was the highest. CONCLUSIONS: Established fingerprint, the results of cluster analysis and principal component analysis can provide reference for quality evaluation of C. longsissimae.
  KEYWORDS Callicarpae longsissimae; HPLC; Fingerprint; Cluster analysis; Principal component analysis

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