Zhao Lu-hua, Wu Meng-hua, Xiang Bing-ren
Analytic Center, China Pharmaceutical University, Nanjing 210009, China.
Chem Pharm Bull (Tokyo). 2005 Aug;53(8):1054-7. doi: 10.1248/cpb.53.1054.
Application of multivariate data analysis has become a popular method in the last decades, mainly because it can provide information not otherwise accessible. The information includes classification, searching similarities, finding relationships, finding physical significance to principal components, etc. Twenty-two Chinese medicinal herbs containing twelve constituents were collected and determined by HPLC. The results were studied by hierarchical cluster analysis (HCA) and principal components analysis (PCA). It was shown that the samples could be clustered reasonably into three groups, hence corresponding with the typical habitats of Psoralea corylifolia L.
在过去几十年中，多元数据分析的应用已成为一种流行的方法，主要是因为它能够提供通过其他方式无法获得的信息。这些信息包括分类、寻找相似性、发现关系、找出主成分的物理意义等。收集了22种含有12种成分的中草药，并通过高效液相色谱法进行测定。采用层次聚类分析（HCA）和主成分分析（PCA）对结果进行研究。结果表明，这些样品可以合理地聚类为三组，因此与补骨脂的典型生境相对应。
