A multidimensional analytical framework for the selection of soft wheat varieties for dryland environments based on agronomic productivity, stability, nitrogen use efficiency and economic parameters

Wheat production in arid and semi-arid regions is constrained by environmental variability and limited input availability, especially nitrogen. The use of a novel multidimensional analytical framework is proposed to permit the selection of the most suitable bread wheat varieties for Afghanistan, optimizing the aforementioned constraints. The objective was to (i) evaluate 33 varieties across 6 environments, and (ii) to develop a novel robust analytical framework integrating agronomic performance, nitrogen use efficiency (NUE), stability metrics, and economic return for the identification of the most stable, high-performing varieties. Environmental factors explained over 80 % of the variance in grain yield (GY) and straw yield (SY). Significant genotype × environment interactions enabled the identification of broadly adapted genotypes. Varieties 28 and 32 exceeded 4.0 t ha⁻¹ GY with high stability across environments. Nitrogen uptake efficiency (Nt/Ns) ranged from 0.41 to 0.72, with varieties 11, 19 and 20 combining high NUE traits with consistent performance. Protein content was mostly environment-driven, with variety 15 showing exceptional stability and quality. The Net Nitrogen-adjusted Margin (NNaM), an economic index combining yield, NUE, and grain protein, was significantly associated with Nt/Ns and SY. A linear regression model explained 96.5 % of NNaM variability, highlighting the value of integrating physiological and economic traits. The derived composite index allowed for multi-trait ranking. From this, only varieties 28, 32 and 15 emerged as optimal candidates. This integrative framework facilitates the selection of productive, resource-efficient wheat varieties for Afghanistan farming and offers a scalable approach for breeding programs in arid and semi-arid agro-ecosystems.