Publisher : The Korean Society of Analytical Science
DOI : 10.5806/AST.2016.29.1.1
Title & Authors
Discrimination model of cultivation area of Corni Fructus using a GC-MS-Based metabolomics approach Leem, Jae-Yoon;
It is believed that traditional Korean medicines can be managed more scientifically through the development of logical criteria to verify their region of cultivation, and that this could contribute to the advancement of the traditional herbal medicine industry. This study attempted to determine such criteria for Sansuyu. The volatile compounds were obtained from 20 samples of domestic Corni fructus (Sansuyu) and 45 samples of Chinese Sansuyu by steam distillation. The metabolites were identified in the NIST Mass Spectral Library via the obtained gas chromatography/mass spectrometer (GC/MS) data of 53 training samples. Data binning at 0.2 min intervals was performed to normalize the number of variables used in the statistical analysis. Multivariate statistical analyses, such as principle component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) were performed using the SIMCA-P software package. Significant variables with a variable importance in the projection (VIP) score higher than 1.0 were obtained from OPLS-DA, and variables that resulted in a p-value of less than 0.05 through one-way ANOVA were selected to verify the marker compounds. Finally, among the 11 variables extracted, 1-ethylbutyl-hydroperoxide (9.089 min), nonadecane (20.170 min), butylated hydroxytoluene (25.319 min), 5β,7βH,10α-eudesm-11-en-1α-ol (25.921 min), 7,9-bis(2-methyl-2-propanyl)-1-oxaspiro[4.5]deca-6,9-diene-2,8-dione (34.257 min), and 2-decyldodecyl-benzene (54.717 min) were selected as markers to indicate the origin of Sansuyu. The statistical model developed was suitable for the determination of the geographical origin of Sansuyu. The cultivation areas of four Korean and eight Chinese Sansuyu samples were predicted via the established OPLS-DA model, and it was confirmed that 11 of the 12 samples were accurately classified.
Corni Fructus;Sansuyu, gas chromatography/mass spectrometer;metabolomics;multivariate analysis;orthogonal partial least squares discriminant analysis;
H. W. Lee, J. H. Choi, S. Y. Park, B. K. Choo, J. M. Chun, A. Y. Lee and H. K. Kim, Korean J. Med. Crop Sci., 16, 168-172 (2008).
A. Zhang, H. Sun, Z. Wang, W. Sun, P. Wang and X. Wang, Planta Med.., 76, 2026-2035 (2010).
O. Fiehn, Plant Mol. Biol., 48, 155-171 (2002).
J. C. Lindon, E. Holmes and J. K. Nicholson, FEBS J., 274, 1140-51 (2007).
V. Arbona, D. J. Iglesias, M. Talon and A. Gomez-Cadenas, J. Agric. Food Chem.., 57, 7338-7347 (2009).
W. M. Claudino, P. H. Goncalves, A. di Leo, P. A. Philip and F. Sarkar, Crit. Rev. Oncol. Hematol., 84, 1-7 (2012).
S. O. Yang, S. W. Lee, Y. O. Kim, S. W. Lee, N. H. Kim, H. K. Choi, J. Y. Jung, D. H. Lee and Y. S. Shin, Korean J. Med. Crop Sci., 22, 17-22 (2014).
R. C. H. De Vos, S. Moco, A. Lommen, J. J. B. Keurentjes, R. J. Bino and R. D. Hall, Nat. Protoc., 2, 778-791 (2007).
H. Kanani, J. Chromatogr. B., 871, 191-201 (2008).
A. Kende, D. Portwood, A. Senior, M. Earll, E. Bolygo and M. Seymour, J. Chromatogr. A, 1217, 6718-6723 (2010).
E. Fukusaki and A. Kobayashi, J. Biosci. Bioeng., 100, 347-354 (2005).
G. Özek, F. Demirci, T. Özek, N. Tabanca, D. E. Wedge, S. I. Khan, K. Hüsnü, C. Baser, A. Duran and E. Hamzaoglu, J. Chromatogr. A, 1217, 741-748 (2010).
M. Bylesjo, M. Rantalainen, O. Cloarec, J. K. Nicholson, E. Holmes and J. Trygg, J. Chemom., 20, 341-351 (2006).
J. A. Westerhuis, E. J. J. van Velzen, H. C. J. Hoefsloot and A. K. Smilde, Metabolomics, 6, 119-128 (2010).
Y. S. Hong, J. Korean Soc. Food Sci. Nutr., 43, 179-186 (2014).
Y. A. Jung, Y. S. Jung and G. S. Hwang, J. Korean Magn. Reson. Soc., 15, 90-103 (2011).
S. Wiklund, E. Johansson, L. Sjöström, E. J. Mellerowicz, U. Edlund, J. P. Shockcor, J. Gottfries, T. Moritz and J. Trygg, Anal. Chem., 80, 115-122 (2008).