基于多元统计学的青稞HPLC指纹图谱研究

为了筛选品质良好的青稞,选择不同产地的10批青稞样品,建立了青稞的高效液相指纹图谱,并进行了聚类分析和主成分分析,测定了儿茶素、表儿茶素和芦丁3种指标成分的含量.首先采用高效液相色谱法测得了10批青稞的色谱图,建立其共有模式,确定了11个共有峰,蓝青稞指标成分含量均高于白青稞.对共有峰数据进行聚类分析和主成分分析,10...

Study on HPLC fingerprint of hulless barley based onmultivariate statistics

In order to screen good quality hulless barley(Hordeum vulgare L.var.nudum Hook.f.),10 batches of hulless barley sample from different origins were selected,and high-performance liquid fingerprints of hulless barley were established.Cluster analysis and principal component analysis were performed,and contents of three index components(catechin,epicaechin and rutin)were determined.Firstly,the chromatograms of 10 batches of hulless barley were measured by high performance liquid chromatography,and a common mode was established.Eleven common peaks were determined.The content of the index components from blue hulless barley was higher than that of white hulless barley.Cluster analysis and principal component analysis were performed on the common peak data.Ten batches of hulless barley were divided into two categories.The principal component analysis obtained three principal components with a cumulative variance of 82.266%.The three samples with the highest comprehensive scores were S4,S3 and S1,which are the blue hulless barley in Tibet,and it was consistent with the results of the determination of the index component content.The combination of fingerprint analysis,clustering analysis and the principal components analysis provides a new method for index screening and comprehensive evaluation of hulless barley.