文献类型：期刊文献

英文题名：Multivariate statistical analysis based on a chromatographic fingerprint for the evaluation of important environmental factors that affect the quality of Angelica sinensis

作者：Song, Xin-Yue[1,3];Jin, Ling[2];Shi, Yan-Ping[1];Li, Ying-Dong[2];Chen, Juan[1]

第一作者：Song, Xin-Yue

通信作者：Li, YD[1]

机构：[1]Chinese Acad Sci, Lanzhou Inst Chem Phys, Key Lab Nat Med Gansu Prov, Key Lab Chem Northwestern Plant Resources, Lanzhou 730000, Peoples R China;[2]Gansu Coll Tradit Chinese Med, Lanzhou 730000, Peoples R China;[3]Univ Chinese Acad Sci, Beijing 100039, Peoples R China

第一机构：Chinese Acad Sci, Lanzhou Inst Chem Phys, Key Lab Nat Med Gansu Prov, Key Lab Chem Northwestern Plant Resources, Lanzhou 730000, Peoples R China

通信机构：[1]corresponding author), Gansu Coll Tradit Chinese Med, Lanzhou 730000, Peoples R China.|[10735]甘肃中医药大学;

年份：2014

卷号：6

期号：20

起止页码：8268

外文期刊名：ANALYTICAL METHODS

收录：;EI(收录号：20144100084654);Scopus(收录号：2-s2.0-84907542657);WOS:【SCI-EXPANDED(收录号:WOS:000342989400026)】；

基金：This work was supported by the National Key Technology Research and Development Program of China (no. 2011BAI05B02) and the National Natural Science Foundation of China (no. 21105106).

语种：英文

外文关键词：Chromatographic analysis - Discriminant analysis - Electron emission - Factor analysis - Least squares approximations - Liquid chromatography - Medicine - Multivariant analysis - Plant extracts

摘要：Multiple components in traditional Chinese medicines (TCMs) have a synergistic action on the therapeutic effects of TCMs and their contents may vary substantially with environmental changes. In this study, an ultra-performance liquid chromatographic (UPLC) fingerprint was established to choose the optimum environmental conditions for the cultivation of Angelica sinensis (A. sinensis). Optimum separation was achieved on a C-18 column (50 x 2.1 mm i.d., 1.7 mu m particles) with a 25 min gradient. The method was applied to establish the chromatographic fingerprint of A. sinensis by analyzing 109 samples cultivated under controlled environmental conditions. A representative standard fingerprint chromatogram was obtained using professional software, in which 30 common peaks were marked. The common peaks for all samples were subjected to principal component analysis with partial least squares discriminant analysis to screen out the peaks related to specific environmental factors. Peaks with areas that showed significant differences under different environmental conditions were screened out and used to obtain the optimum environmental conditions. Our method of integrating the advantages of chromatographic fingerprinting and multivariate statistical analysis can reveal the integral characteristics of herbal medicines. Consequently, it is a comprehensive, scientific method that provides a technical safeguard for the cultivation of herbal medicines.