NATURAL PRODUCT RESEARCH AND DEVELOPMENT ›› 2018, Vol. 30 ›› Issue (9): 1543-1547.doi: 10.16333/j.1001-6880.2018.9.012

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Comparative Study on Volatile Constituents of  Radix Adenophorae Based on Principal Component Analysis and Cluster Analysis

ZHOU Kun1,JIANG Han-mei2*,XU Jia-qi2,GUO Yu2   

  1. 1Affiliated Mental Health Center Department of Pharmacy,tongji Medicial College of Huazhong University of Science & Technology,Wuhan 430022,China ; 2Hubei University of Chinese Medicine Department of Pharmaceutical Engineering & Teaching,Wuhan 430065,
  • Online:2018-10-08 Published:2018-10-10

Abstract: The volatile constituents were extracted from Radix Adenophorae by solid phase micro extraction,and were qualitified by gas-chromatography mass-spectrometry,and content of each component of volatile constituents were calculated by peak area normalization method.by SPSS 18.0 software,principal component analysis and cluster analysis were used to statistical analysis.41 kinds of constituents were determind in Radix Adenophorae which come from different habitats,the main components are alkylic acid,olefine acid,aldehydes and alcohols; Radix Adenophorae which come from different habitats were contains isovaleraldehyde,hexanal,α-pinene and suet aldehyde; Radix Adenophorae which come from Jiangsu and Hubei were contain more terpenoids. Radix Adenophorae which come from different habitats can be divided into five categories by cluster analysis.the study established a rapid analysis method of the volatile components of Radix Adenophorae and contributed the patterns of characteristics distribution and origin information of volatile components from Radix Adenophorae,the method is simple and fast.principal component analysis and cluster analysis method can effectively distinguish  Radix Adenophorae which come from different areas.the results can provide evaluation method for the species and quality comparison of Radix Adenophorae.

Key words: Radix Adenophorae, solid phase micro extraction, gas-chromatography-mass spectrometry, volatile components, cluster analysis, principal component analysis

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