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Seed coat metabolite profiling of cowpea (Vigna unguiculata L. Walp.) accessions from Ghana using UPLC-PDA-QTOF-MS and chemometrics
Authors:Armelle Tontsa Tsamo  Haruna Mohammed  Mustapha Mohammed  Peter Papoh Ndibewu  Felix Dapare Dakora
Institution:1. Department of Chemistry, Tshwane University of Technology, Pretoria, South Africa;2. Department of Organic Chemistry, University of Yaoundé I, Yaounde, Cameroon;3. armelletsamo@yahoo.fr TsamoTontsaA@tut.ac.za;5. Department of Crop Sciences, Tshwane University of Technology, Pretoria, South Africa;6. CSIR-Savanna Agricultural Research Institute, Tamale, Ghana
Abstract:Abstract

Cowpea (Vigna unguiculata L. Walp.) is an important grain legume in Africa exhibiting high morpho-genetic diversity. However, not much information exists on the phytochemical profiles of its hulls. This study explored the metabolite profiles of seed-coats from thirteen cowpea accessions of varying phenotypes using UPLC-QTOF-MS and chemometric analysis. A total of 34 secondary metabolites were identified, which comprised phenolic acids, flavonoids, anthocyanins, sphingolipids and fatty acids. Quantification of selected phenolic compounds revealed marked variations among the cowpea accessions. The chemical profiles of the test accessions were distinguished by multivariate analysis, and the results revealed a marked influence of seed-coat pigmentation on the observed differences in their metabolite profiles. Moreover, delphinidin (traces to 2257.6 µg/g), catechin glucoside (traces to 2840.6 µg/g), catechin (traces to 2089.2 µg/g) and epicatechin (26.3 to 3222.7 µg/g) contributed to the segregation amongst the studied samples. The concentrations of the discriminant metabolites were greater in the dark seeded cowpeas compared to their lighter seeded counterparts. The findings represent a useful contribution to the literature on cowpea seed coat metabolites, and also reveal their potential for use in the development of food and pharmaceutical products.
Keywords:Vigna unguiculata L  Walp  chemical composition  UHPLC-qTOF-MS  principal component analysis  hierarchical clustering analysis
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