Application of Principle Component Analysis and Hierarchical Cluster Analysis in HPLC Fingerprint of Lagerstroemia Specious L

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外文摘要：Principle component analysis (PCA)， and hierarchical cluster analysis (HCA) were introduced for quality assessment of total triterpenes in HPLC fingerprint of Lagerstroemia specious 。The fingerprint was developed by analyzing 10 samples from different growing areas。 Eight chromatographic peaks were selected as characteristic peaks and their relative peak areas (RPA) were calculated for quantitative expression of the HPLC fingerprints。 Four principal components have been extracted by PCA。 The scores of the samples showed that the samples could be clustered reasonably into different groups corresponding to different growing areas。 Therefore， HPLC fingerprint in combination with HCA and PCA provide a very flexible and reliable method for quality assessment of traditional Chinese medicines。

外文关键词：

FingerprintPrinciple component analysisHierarchical cluster analysis

作者：

F.Xing、J.X.Guo、Y.Wang、Y.Chen

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作者单位：

ZONG Wei@School of Food and Biological Engineering ,Zhengzhou University of Light Industry, P.R.China,450002--LI Bo@College of Food Engineering ,Henan Institute of Science and Technology, P.R.China, 453003--

会议名称：

International Conference on Informationization, Automation and Electrification in Agriculture;IAEA

会议地点：

Zhengjiang(CN);Zhengjiang(CN)

会议母体文献：

Informationization, Automation and Electrification in Agriculture

页码：

527-530

出版时间：

2008