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Journal of Analytical Methods in Chemistry
Volume 2013, Article ID 246986, 9 pages
Research Article

Comparative Analysis of the Volatile Components of Agrimonia eupatoria from Leaves and Roots by Gas Chromatography-Mass Spectrometry and Multivariate Curve Resolution

1School of Chemical and Material Engineering, Quzhou College, Quzhou 324000, China
2Changde Institute for Food and Durg Control, Changde 415000, China
3College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China

Received 10 June 2013; Revised 8 August 2013; Accepted 20 August 2013

Academic Editor: Shao-Nong Chen

Copyright © 2013 Xiao-Liang Feng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Gas chromatography-mass spectrometry and multivariate curve resolution were applied to the differential analysis of the volatile components in Agrimonia eupatoria specimens from different plant parts. After extracted with water distillation method, the volatile components in Agrimonia eupatoria from leaves and roots were detected by GC-MS. Then the qualitative and quantitative analysis of the volatile components in the main root of Agrimonia eupatoria was completed with the help of subwindow factor analysis resolving two-dimensional original data into mass spectra and chromatograms. 68 of 87 separated constituents in the total ion chromatogram of the volatile components were identified and quantified, accounting for about 87.03% of the total content. Then, the common peaks in leaf were extracted with orthogonal projection resolution method. Among the components determined, there were 52 components coexisting in the studied samples although the relative content of each component showed difference to some extent. The results showed a fair consistency in their GC-MS fingerprint. It was the first time to apply orthogonal projection method to compare different plant parts of Agrimonia eupatoria, and it reduced the burden of qualitative analysis as well as the subjectivity. The obtained results proved the combined approach powerful for the analysis of complex Agrimonia eupatoria samples. The developed method can be used to further study and quality control of Agrimonia eupatoria.