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11.
Jimmy Yuk Kristina L. McIntyre Christian Fischer Joshua Hicks Kimberly L. Colson Ed Lui Dan Brown John T. Arnason 《Analytical and bioanalytical chemistry》2013,405(13):4499-4509
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. Figure
Principal component analysis scores and loadings plot for differentiating between closely-related ginseng landraces in Ontario, Canada 相似文献
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Everette S. GardnerJr. Ed. McKenzie 《The Journal of the Operational Research Society》1988,39(9):863-867
Model identification has traditionally been ignored in forecasting via exponential smoothing. The usual practice is to apply the same model to every time-series in a collection. This paper develops a procedure for model identification in large forecasting applications based on an examination of variances of differences of the time-series. The order of differencing yielding minimum variance suggests an appropriate model for the series. Empirical results show that this procedure selects models that give reasonable ex ante forecast accuracy. 相似文献
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Some fundamental fixed point theorems are proved for locally convex spaces whose generating family of seminorms satisfies the parallelogram law. 相似文献