Abstract
Rhodiola rosea is a broadly used medicinal plant with largely unexplored natural variability in secondary metabolite levels. The aim of this work was to develop a non-target procedure for ¹H NMR spectroscopic fingerprinting of rhizome extracts for pattern recognition analysis and identification of secondary metabolites responsible for differences in sample composition. To achieve this, plants from three different geographic areas (Swiss Alps, Finland, and Altai region in Siberia) were investigated. A sample preparation procedure was developed in order to remove polymeric polyphenols as the ¹H NMR analysis of low-molecular-weight metabolites was hampered by the presence of tannins. Principal component analysis disclosed tight clustering of samples according to population. PCA models based on the aromatic region of the spectra showed that the first two components reflected changes in the content of salidroside and rosavin, respectively, the rosavin content being negatively correlated to that of rhodiocyanoside A and minor aromatics. Score plots and non-parametric variance tests demonstrated population-dependent changes according to harvest time. Data consistency was assessed using score plots and box-and-whisker graphs. In addition, a procedure for presenting loadings of PCA models based on bucketed data as high-resolution plots, which are reminiscent of real ¹H NMR spectra and help to identify latent biomarkers, is presented. This study demonstrated the usefulness of the established procedure for multivariate non-target ¹H NMR metabolic profiling of Rhodiola rosea.
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