不同产地黑果腺肋花楸叶指纹图谱的建立及化学模式识别
Establishment of fingerprint and chemistry pattern recognition of Aronia melanocarpca leaves from different habitats
王琪瑶 1史锐 1丛龙娇 1刘斯文 1黄晓彤 1吴俊英1
作者信息
摘要
目的:建立不同产地10批黑果腺肋花楸叶的HPLC指纹图谱,结合化学模式识别法进行质量评价.方法:采用AgilentTC-C18色谱柱,以乙腈-0.45％甲酸水溶液为流动相,梯度洗脱,检测波长280nm,流速1.0mL/min,采用中药指纹图谱相似度评价系统建立指纹图谱,结合化学模式识别方法对数据进行处理,分析10批黑果腺肋花楸叶的相似性及差异性.结果:10批黑果腺肋花楸叶相似度为0.175～0.921,标定了 17个共有峰,指认出没食子酸、绿原酸、矢车菊素-3-O-葡萄糖苷、表儿茶素等4个共有峰.10批样品聚类分析可分为两类,主成分分析得到4个主成分的累计方差贡献率为88.726％,能有效区分不同产地黑果腺肋花楸叶,确定出4种影响其质量的差异性成分.结论:建立了黑果腺肋花楸叶的指纹图谱,本方法科学、准确、稳定,为该药材的质量控制和资源开发提供了科学依据.
Abstract
Objective:To establish HPLC fingerprint of 10 batches of Aronia melanocarpa leaves in different origin and evaluate quality with chemical pattern identification.Methods:Using Agilent TC-C18 column with acetonitrile-0.45％formic acid solution as the mobile phase,gradient elution,the wavelength of 280 nm.Combined with the chemical pattern identification method to analyze the similarity and differences of 10 batches of leaves.Results:The leaf similarity of 10 batches of Aronia melanocarpca leaves was 0.175～0.921,and 17 common peaks were identified,referring to the recognition of four common peaks including gallic acid,chlorogenic acid,comabin-3-O-glucoside and epicatechin.The cluster analysis of 10 batches of samples can be divided into two categories.The principal component analysis found that the cumulative variance contribution rate of the four principal components was 88.726％,which could effectively distinguish the leaves of different origins and identify four different components that affect their quality.Conclusion:The fingerprint of the method is scientific and accurate,which provides scientific basis for its quality control and resource development.
关键词
黑果腺肋花楸叶/指纹图谱/高效液相/化学模式识别/主成分分析Key words
Aronia melanocarpca leaves/Fingerprint/High performance liquid phase/Chemical pattern recognition/Principal component analysis引用本文复制引用
出版年
2024
NETL
NSTL
万方数据