Agro-morphological diversity and breeding potential of Bambara groundnut (Vigna subterranea L. Verdc): Insights from recombinant inbred lines evaluation

Ruzive, Amanda; Govender, LaurenciaORCID logo; Mandizvo, TakudzwaORCID logo; Shayanowako, Admire Isaac; Musimwa, Tatenda; Chai, Hui HuiORCID logo; Massawe, Festo; Mayes, Sean; Sibiya, Julia; and Mabhaudhi, TafadzwanasheORCID logo (2025) Agro-morphological diversity and breeding potential of Bambara groundnut (Vigna subterranea L. Verdc): Insights from recombinant inbred lines evaluation. South African journal of botany, 185. pp. 315-330. ISSN 0254-6299 DOI: 10.1016/j.sajb.2025.07.061
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Bambara groundnut (BGN) is a nutritious, multi-stress-tolerant legume with potential to enhance food and nutrition security across Africa, particularly in regions vulnerable to climate change and resource scarcity. Its ability to thrive in harsh environments while providing a rich source of protein and essential nutrients makes it an invaluable crop for sustainable agriculture. Despite its proven resilience and benefits, BGN remains overlooked in mainstream agricultural development and research, leaving its full potential untapped. This study evaluated recombinant inbred lines (RILs) derived from hybridization of four genetically diverse parental lines to identify superior genotypes. This research aims to pinpoint elite lines with potential for enhancing future BGN breeding programs, focusing on key agro-morphological traits. The experiment followed a 90 × 5 augmented design, incorporating 21 check lines. Trait measurements adhered to the descriptors provided by the International Plant Genetic Resources Institute. Data analysis included analysis of variance (ANOVA), Pearson correlation coefficient, Principal Component Analysis (PCA) and diversity indices. Quantitative morphological traits (days to 50 % emergence (DE), days to 50 % flowering (DFF), internode length (IL), plant height (pH), and petiole length (PL)) exhibited significant variability among genotypes (p < 0.001). Multivariate analysis indicated that the first three principal components (PCs), each with eigenvalues ≥ 1, accounted for 80 % of the total variance. Key correlations include strong positive relationships between DE and DFF (r = 0.85; p = 0.017), pH (r = 0.75; p = 0.021) and PL (r = 0.75; p = 0.027). Petiole length was positively correlated with DFF (r = 0.89; p = 0.01) and pH (r = 0.86; p = 0.011). Grain yield per plot (GY) and grain yield per plant (GYP) varied significantly, which aided classification into four groups, namely: A (high-yielding g), B (moderately high yielding), C (moderate yielding) and D (low yielding). A total of 19 genotypes including; IITA686/LunT-419–324, S19/Ankpa4–339–266, IITA686/LunT-348–271, S19/Ankpa4–50–43, S19/Ankpa4–234–197, PONG-BR, S19/Ankpa4–1–1 and S19/Ankpa4–151–129 were grouped as high-yielding. The significant genotypic differences observed across most quantitative traits confirm the presence of sufficient genetic diversity, highlighting BGN's potential for selection and genetic enhancement.


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