Application of Principle Component Analysis and Hierarchical Cluster Analysis in HPLC Fingerprint of Lagerstroemia Specious L
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.
Fingerprint Principle component analysis Hierarchical cluster analysis
ZONG Wei LI Bo
School of Food and Biological Engineering ,Zhengzhou University of Light Industry, P.R.China,450002 College of Food Engineering ,Henan Institute of Science and Technology, P.R.China, 453003
国际会议
2008 International Conference on IAEA(2008农业信息化、自动化与电气化国际会议)
镇江
英文
527-530
2008-11-01（万方平台首次上网日期，不代表论文的发表时间）