The knowledge of genetic variability and breeding techniques is crucial in crop improvement programs. This information is especially important in underutilized crops such as Bambara groundnut, which have limited breeding systems and genetic diversity information. Hence, this study evaluated the genetic variability and established the relationship between the yield and its components in Bambara groundnut based on seed weight using multivariate analysis. A field trial was conducted in a randomized complete block design with three replications on 28 lines. Data were collected on 12 agro-morphological traits, and a statistical analysis was conducted using SAS version 9.4 software, while the variance component, genotypic and phenotypic coefficient variation, heritability, and genetic advance values were estimated. A cluster analysis was performed using NT-SYS software to estimate the genetic relations among the accessions. The results showed significant variability among the accessions based on the yield and yield component characteristics. The evaluated lines were grouped into seven primary clusters based on the assessed traits using the UPGMA dendrogram. Based on the overall results, G5LR1P3, G1LR1P3, G4LR1P1, G2SR1P1 and G3SR1P4 performed the best for the yield and yield components. These improved lines are recommended for large-scale evaluation and utilization in future breeding programs to develop high-yield Bambara groundnut varieties.

Addressing genetic diversity and application of appropriate breeding strategies are imperative for Bambara groundnut (Vigna subterranea L.) improvement as a newly introduced legume in Malaysia. It has become a “miracle lucrative” legume for Asia and Africa because of its drought resilience, excellent nutritional profiles, and versatile uses. This crop’s progress has been limited owing to a lack of extensive research, marginalization, inadequate knowledge, and a lack of accessible funds, among other concerns. The expansion of this crop is reliant on the assessment and selection of unique and reliable breeding lines in various circumstances. Consequently, the goal of this work is to determine genetic diversity and the relationship between yield-contributing components in 44 Bambara groundnut accessions sourced from the Genebank of Institute of Tropical Agriculture and Food Security (ITAFoS) at Universiti Putra Malaysia (UPM). Three replications were used in the experiment, which was done using a randomized complete block design (RCBD). The data were subjected to ANOVA, PCA, correlation, and heat map cluster analysis; also, genetic parameters and broad-sense heritability estimation were carried out on recorded phenotypic descriptors. All of the investigated variables had a significant variance ( p ≤ 0.05 or 0.01) according to the ANOVA results. Yield per hectare showed a positively strong to perfect significant correlation ( 0.75 ≤ r ≤ 1.00 ; p ≤ 0.01 ) with the yield components viz. fresh pod weight, hundred seed weight, dry pod weight, and dry seed weight. Interestingly, these traits had heritability ≥ 60 % and genetic   gain ≥ 20 % , which can be beneficial for direct selection to this crop improvement. The UPGMA clustering revealed five distinct clusters in which genotypes under cluster I, cluster II, and cluster IV produce a greater yield of 5.96%, 7.12%, and 15.05%, respectively, than the grand mean yield of 1927.01 kg/ha. The PCA biplot estimated that PC1 (32.9%) and PC2 (12.9%) would cover 45.8% of the total variance. We discovered 30 promising lines that provide yields per hectare more than 1.8 ton/ha and might be used as parental lines in future breeding operations aimed at improving the grain yield in tropical areas or comparable agroecological zones.