Multivariate discrimination of selected taxa of the Fabaceae family

Abstract

Abstract. Abdulrahman MD. 2022. Multivariate discrimination of selected taxa of the Fabaceae family. Nusantara Bioscience 15: 227-232. Nigeria is among the most interesting and diversified countries globally regarding tropical vegetation and medicinal plants. The taxonomy of the Fabaceae family is not entirely clear, to organize species into manageable groups that are helpful for taxonomical, conservational, or pharmacognostic study. This study aimed to discriminate the leaves of Dialium guineense Willd., Detarium microcarpum Guill. & Perr, Tamarindus indica L, Acacia nilotica (L.) Willd. ex Delile, Abrus precatorius L., Senna occidentalis (L.) Link, Erythrina senegalensis DC. and Pterocarpus erinaceus Poir. based on the mineral elements contents coupled with multivariate analysis. Three samples of each wild-growing species were collected. Unsupervised multivariate analysis using SIMCA-P (V.14.1, Umetrics Sweden) was employed. Five model groups were formed based on their mineral element contents. The species were fully discriminated along the PC1, accounting for 39.3% of the variation. Evidence from this study showed that a combination of mineral element analysis and chemometrics yielded a powerful classification method. Taxonomic identification of plants through biological research combined with chemometrics is an excellent method for preventing the adulteration or consumption of plants with excessive contents or harmful ingredients. However, a mix of molecular and developmental datasets is still necessary to explicitly examine their connections.

Classification of Eugenia uniflora and E. punicifolia based on anatomical features and multivariate discrimination based on chemical composition.

“…For quantitatively classifying or subdividing plants into groups, a principal component analysis (PCA) score plot is a valuable tool. Based on their similarities and differences as well as the compounds responsible for the discrimination, the objective is to group them into distinct categories [33] . The Biplot plots scores and loadings together so that both can be seen and understood at the same time.…”