The use of principal component analyses and hierarchical cluster analyses in the quality evaluation of Salvia miltiorrhiza Bunge

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Y.Y. Jiang
G.C. Zhong
L. Wang
T. Wang
M. Wang
L. Zhang
Y.H. Zhou
C.B. Ding
R.W. Yang
X.L. Wang


hierarchical cluster analyses, principal component analyses, Salvia miltiorrhiza


Principal component analysis (PCA) and hierarchical cluster analysis (HCA) are quite useful chemometrics tools for the data analysis in many fields. In China P.R., Salvia miltiorrhiza Bunge is a traditional medicinal plant. Due to the unique action of its biologically active compounds in treating cardiovascular disease, S. miltiorrhiza was planted in many regions as the local economic crop. The roots, which are also called ‘Danshen’, were the original economical products. In this study, PCA and HCA were used to determine the quality of Danshen from two aspects, namely, agronomic traits and active compounds. PCA revealed that the first principal component cumulatively accounted for 50.1% of the total variance in the data set, while PC2 and PC3 explained 20.0 and 13.1%, respectively. The quality descending order of all samples obtained by PCA was as follows: tissue culture lobular Danshen, tissue culture broad leaf Danshen, short stalk and lobular leaf Danshen, broad leaf Danshen, lobular Danshen, and white leaf Danshen. Samples were classified into three main groups by HCA. Therefore, based on the provisions in the Chinese pharmacopoeia about the content of tanshinone IIA, ZD was considered the best line for the farmers. The research showed that PCA and HCA also could be used in the quality evaluation of medicinal crops.

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