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Index- and Pareto-based multi-trait selection identifies dual-purpose sorghum and pearl millet cultivars for arid agro-ecosystems of Saudi Arabia

Aug 2026 · Frontiers in Plant Science · Vol 17 · 0 citations · 39 references
Medicine

Abstract

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.

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