The roots and rhizomes of several Glycyrrhiza species are widely used as sweetening and flavoring agents in food, as well as important ingredients in formulations of traditional medicines. Five Glycyrrhiza species, G. uralensis, G. glabra, G. inflata, G. echinata, and G. lepidota, often share the name "licorice roots" in the botanicals' marketplace. Unfortunately, misidentification/mislabeling is very common due to their similarities in morpho-anatomical features. Significant metabolite alterations among the different Glycyrrhiza species and their hybrids have been reported, suggesting that the biological activities could vary with the licorice roots or products derived from different species. Development of simple, effective methods for species identification and differentiation is of key importance. In this study, 78 licorice samples were investigated using HPTLC and NMR as analytical tools. Significant metabolite variations were observed between the five species. The species-specific fingerprint patterns for the five Glycyrrhiza species were determined with HPTLC and NMR; then applied to the sample identification and discrimination. The results obtained from these two orthogonal analytical methods agreed with each other. Furthermore, the NMR signals and the species-specific constituents that made significant contributions to the differentiation of the five Glycyrrhiza species were confirmed based on the multivariate analysis of the NMR spectral data. Using the established OPLS-DA models, the classification of hybrids was evaluated and confirmed. The developed methods, particularly the HPTLC method with its simplicity and low cost, could be used as a rapid and reliable approach for the authentication of licorice species and quality control of licorice raw material and products.
Keywords: Fingerprinting; Glycyrrhiza species; HPTLC; Licorice; Multivariate analysis; NMR.
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