The study of genetic diversity is essential for understanding population structure and optimizing breeding programs. To support cowpea breeding efforts, we conducted a diversity study on a panel of 185 accessions, including 125 newly collected accessions from Niger and additional accessions provided by research institutions in Nigeria, Burkina Faso, Senegal and Niger. This study aimed to analyse cowpea population structure and genomic diversity and to provide a preliminary assessment of phenotypic variation across genomic clusters. Genotyping-by-sequencing generated 20,918 single nucleotide polymorphisms (SNPs), which were used to assess population structure and genetic diversity. Population structure was inferred using a Bayesian approach (ADMIXTURE), and the resulting clustering pattern was corroborated by a multivariate method (DAPC). Seven genetic clusters were identified (A1–A7). Accessions from Niger were predominantly assigned to clusters A1, A2, A3 and A5; those from Senegal were mainly assigned to A4, whereas accessions from Nigeria were predominantly assigned to A7. Strong genetic differentiation was observed between accessions from Nigeria and those from Niger. The evaluation of phenological traits and yield components revealed marked differences among clusters. Most clusters showed low and multimodal grain and husk yield distributions, whereas cluster A5 consistently combined early maturity, high haulm yield and superior reproductive performance, highlighting its breeding potential. Overall, this study generated a large SNP marker dataset and provided integrated genomic and preliminary phenotypic information for a diverse cowpea germplasm panel. These resources will be useful for further studies of population genetics, breeding and association mapping in cowpea, an important legume crop for Sahelian countries.
Hadiara Hamadou Hamidou, A. Saïdou, Abdou Harou et al.· Plant genetic resources· 0 citations
Background Rainfed cereal production in southwestern Saudi Arabia depends largely on farmer-saved landraces, creating an important opportunity to strengthen grain and fodder productivity in mixed crop-livestock systems exposed to heat and variable rainfall. This study evaluated introduced dual-purpose sorghum and pearl millet germplasm under contrasting arid, supplemental-irrigated rainfed environments, and applied complementary quantitative approaches to identify high-performing, stable candidates that balance grain yield and green-fodder production while accounting for genotype × environment interaction (G×E). Methods Twenty-seven sorghum and 15 pearl millet entries were evaluated in alpha-lattice trials at the contrasting Jazan lowland and Abha highland sites across four site × season/sowing-window environments. Linear mixed models quantified environment, genotype, and G×E effects and estimated entry-mean reliability. Stability and adaptation patterns were evaluated using the weighted average of absolute scores from BLUPs (WAASB) and GGE biplots. Dual-purpose performance was assessed using a standardized 50:50 grain-yield-fresh-biomass index as a transparent baseline in the absence of validated local economic or farmer-preference weights. Pareto-frontier analysis was used to identify non-dominated genotypes representing efficient grain-green-fodder trade-offs. Results The trials revealed substantial genetic variation and contrasting genotype responses across environments, demonstrating considerable scope for improving grain and green-fodder productivity. Selection reliability was very high for sorghum fresh biomass and pearl millet grain yield, and high for pearl millet fresh biomass, providing a strong basis for prioritizing selection candidates within the target production environments. Sorghum grain yield showed lower reliability because only two grain-evaluable environments were available and G×E variance was large, highlighting a clear priority for expanded grain testing. SSV 74, WM 89/90#1615, and 89WM 5003 achieved the highest sorghum DualIndex values, while ICSV 15021 combined the highest mean fresh biomass with the lowest WAASB, identifying it as a particularly promising forage-oriented candidate. In pearl millet, LCICMV-1 (SOSAT-C-88) and ICMV 91450 displayed favorable grain-green-fodder profiles, ICMV 221 recorded the highest mean grain yield, and LCICMV-4 (Jirani) showed promising grain-yield performance under Jazan-associated conditions. Conclusions The study identified a valuable portfolio of sorghum and pearl millet candidates addressing complementary production objectives, including high green-fodder productivity, balanced grain-fodder performance, high grain yield, and targeted environmental adaptation. By integrating mixed-model reliability, stability analysis, a transparent grain-green-fodder index, and Pareto-frontier assessment, the study provides a rigorous and practical framework for converting early multi-environment data into evidence-based advancement decisions. The identified genotypes provide a strong foundation for expanded multi-location and participatory on-farm validation, standardized fodder-quality assessment, and staged seed-system development. Collectively, these findings advance the development of productive and resilient dual-purpose cereal options capable of strengthening grain and fodder security in southwestern Saudi Arabia and comparable arid mixed crop-livestock systems.
Ephrem Habyarimana, A. Alhendi, Kakoli Ghosh et al.· Frontiers in Plant Science· 0 citations
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