Distinguishing Ontario Ginseng Land Races and Ginseng Species using NMR-based Metabolomics.

Yuk, J., McIntyre, K.L., Fischer, C., Hicks, J.B., Colson, K.L., Lui, E., Brown, D.C.W., and Arnason, J.T. (2013). "Distinguishing Ontario Ginseng Land Races and Ginseng Species using NMR-based Metabolomics.", Analytical and Bioanalytical Chemistry, 405(13), pp. 4499-4509. doi : 10.1007/s00216-012-6582-6  Access to full text

Abstract

The use of 1H-NMR-based metabolomics to distinguish and identify unique markers of five Ontario ginseng (Panax quinquefolius L.) landraces and two ginseng species (P. quinquefolius and P. ginseng) was evaluated. Three landraces (2, 3, and 5) were distinguished from one another in the principal component analysis (PCA) scores plot. Further analysis was conducted and specific discriminating metabolites from the PCA loadings were determined. Landraces 3 and 5 were distinguishable on the basis of a decreased NMR intensity in the methyl ginsenoside region, indicating decreased overall ginsenoside levels. In addition, landrace 5 was separated by an increased amount of sucrose relative to the rest of the landraces. Landrace 2 was separated from the rest of the landraces by the increased level of ginsenoside Rb1. The Ontario P. quinquefolius was also compared with Asian P. ginseng by PCA, and clear separation between the two groups was detected in the PCA scores plot. The PCA loadings plot and a t-test NMR difference plot were able to identify an increased level of maltose and a decreased level of sucrose in the Asian ginseng compared with the Ontario ginseng. An overall decrease of ginsenoside content, especially ginsenoside Rb1, was also detected in the Asian ginseng’s metabolic profile. This study demonstrates the potential of NMR-based metabolomics as a powerful high-throughput technique in distinguishing various closely related ginseng landraces and its ability to identify metabolic differences from Ontario and Asian ginseng. The results from this study will allow better understanding for quality assessment, species authentication, and the potential for developing a fully automated method for quality control.

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