In several parts of Africa, Securidaca longipenduculata Fresen is a medicinal plant that has become well-known in traditional medicine for its wide range of therapeutic uses. The first goal of this study was to establish a high-performance thin layer chromatography (HPTLC) chemical fingerprint for S. longipenduculata roots as a reference for quality control. Methanol was used to extract the root samples that were collected from seven distinct locations in the Vhembe area of the Limpopo Province, South Africa. To resolve the major compounds from the sample matrix, an HPTLC method was optimised. The developing solvent was chloroform: ethyl acetate: methanol: formic acid (90:5:30:1), while the derivatising agent used to view the plates was p-anisaldehyde/sulphuric acid. The developed HPTLC method was able to resolve the chemical constitutes from the root crude material to enable clear identification of six chemical markers. The second goal was to investigate Fourier transform infrared (FT-IR) functional groups information of the species in conjunction with multivariate statistical analysis. A web-based high throughput metabolomic program called MetaboAnalyst was used to build several chemometric models including principal component analysis (PCA), orthogonal projection to latent structures-discriminant analysis (OPLS-DA) and hierarchical cluster analysis (HCA). HCA analysis of data identified two clusters and additional analysis verified the quantitative differences between the samples. The FT-IR spectra of S. longipedunculata roots revealed a total of 15 metabolites that could be used as potential markers to differentiate between samples taken from the seven different locations.
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