Stability and Climate Resilience Potential of Fodder Cowpea (Vigna unguiculata) Germplasm Across Diverse Environments

Stability of grain and fodder yields in extra-early cowpea genotypes in Southeastern Niger

Cowpea [Vigna unguiculata (L.) Walp.] is a vital food and fodder crop in Niger, but its productivity is constrained by drought, poor soils, striga and pest pressures. Developing extra-early dual-purpose varieties is essential for strengthening food and feed security in these fragile production zones. This study evaluated the effects of genotype, environment, and their interaction on the stability of grain and fodder yields in 21 cowpea genotypes tested across six environments using an alpha-lattice design with three replications. Stability was assessed through Shukla’s stability variance, the cultivar superiority index, Wricke’s ecovalence, GGE biplot, and the multi-trait genotype–ideotype distance index (MGIDI). Results revealed significant differences among genotypes, environments, and genotype × environment interactions for all traits; environmental effects had the highest mean squares for all traits (p < 0.001). Broad-sense heritability ranged from 0.77 (fodder yield) to 0.88 (days to 50% flowering), and genetic advance as percentage of mean was high for yield traits (GAM = 78.67% for pod yield, 81.80% for grain yield, 99.59% for fodder yield), indicating strong selection potential. Mean grain yield across all genotypes and environments was 1,394.32 kg ha ⁻ ¹, and the coefficient of variation ranged from 26.59% (GY) to 40.63% (FY). Notably, ten extra-early lines—BM22, BP02, BP15, MM142, 65B5080, BP18, BM21, BM13, MM141, and BM12—were identified as combining early maturity with high and stable grain and fodder yields. These lines should be further evaluated across diverse agroecological zones to confirm their adaptability and alignment with farmer preferences, prior to deployment as released varieties or as parents in cowpea improvement programs targeting climate-resilient, dual-purpose productivity in the Sahel.

Harnessing G × E interactions to improve durum wheat resilience: Evidence from irrigated and drought‐stressed trials

Durum wheat ( Triticum durum Desf.) is a critical staple and cash crop in semi‐arid regions, yet its productivity remains highly vulnerable to climate‐induced abiotic stresses, particularly drought and rising temperatures. This study leverages data from the 30th Elite Regional Durum Wheat Yield Trials conducted across 13 rainfed and irrigated environments in Iran (2022–2025) to dissect genotype × environment (G × E) interactions and identify high‐performing, stable genotypes for deployment under increasing climatic uncertainty. Using an integrative analytical framework—combining Additive Main Effects and Multiplicative Interaction (AMMI), Genotype plus genotype‐by‐environment (GGE) biplot, and Partial Least Squares (PLS) regression with 19 climatic covariates—we quantified the relative contributions of environment, genotype, and their interaction, delineated environmental groups, and identified key climatic drivers of yield variation. Results revealed that environment accounted for 81% of total yield variance, with terminal drought (low June rainfall) imposing a universal constraint. G × E interaction, though modest in magnitude (7.65%), was over six times larger than genotype main effects, underscoring its operational relevance for varietal recommendation. Breeding lines G12 (CIMMYT‐derived) and G24 (Iranian) emerged as top candidates: G12 featured among the top‐four performers in 10 of 13 environments and ranked first in 7, while G24 displayed exceptional stability and broad adaptability. PLS modelling identified February and April rainfall—coinciding with tillering to heading—as the strongest climatic predictors of yield, surpassing total seasonal precipitation in explanatory power; late‐season (May–June) temperature also significantly modulated G × E, particularly under terminal heat stress. Environment evaluation highlighted KD3 (Khorramabad) and KH3 (Kermanshah) as the most discriminative and representative test sites, whereas MN4 (Moghan) and IM5 (Ilam) served as effective stress filters. Collectively, our findings support an empirical framework that integrates pattern recognition (AMMI/GGE) with environmental modelling (PLS) to guide environment‐targeted selection—providing a foundation for developing durum wheat varieties with improved adaptation to Iran's heterogeneous rainfed agroecologies.

Harnessing phenotypic diversity in Triticum turgidum for climate-resilient durum wheat improvement

Genetic Variability and Correlation Analysis among Guar Genotypes for Fodder Yield and Quality Related Traits

Limited genetic variability remains a major constraint to genetic improvement in guar (Cyamopsis tetragonoloba L.) restricting both its productivity and cultivation in Pakistan. As a drought adapted legume with significant value as fodder, green manure, and a soil-enhancing nitrogen fixer, guar holds considerable untapped potential for sustainable agriculture. Enhancing its genetic base is therefore essential for developing high-yielding, nutritionally superior varieties suited to arid and semi-arid environments. To address this need, a field experiment was conducted in October 2022 at the University of Agriculture, Faisalabad, using a Randomized Complete Block Design (RCBD) with three replications to assess genetic variability and trait associations among 24 guar genotypes. Five plants per genotype were evaluated for agronomic traits (plant height, branches, tillers, leaves, leaf area, clusters plant⁻¹, pods cluster⁻¹, pods plant⁻¹, fresh and dry biomass) and forage quality attributes (crude protein, crude fiber, ash, moisture, NDF, and ADF), with quality traits quantified via Near Infrared Spectroscopy (NIRS). Significant phenotypic variability was recorded among genotypes. Plant height ranged from 78–141.2 cm, branches 2.16–10.06, leaves 44.87–330.33, fresh biomass 200–700 g, dry biomass 70–244 g, and crude protein 15.16–23.37%. Plant height showed strong positive correlations with fresh biomass, leaf area, and crude protein, whereas branches and clusters exhibited negative associations. Tillers were positively correlated with several yield components but not with leaf area or protein. Crude protein was positively associated with NDF, ash, and crude fiber. Superior genotypes identified included Guar-401 (plant height), Guar-303 and Guar-701 (number of branches), Guar-102 and Guar-701 (number of leaves), and Guar-103 and Guar-803 (protein). These high performing genotypes provide valuable genetic resources for developing improved guar cultivars with enhanced fodder yield and nutritional quality.

Stability of yield and its components in upland cotton hybrids across environments: an AMMI–GGE–WAASBY integration

Understanding genotype-environment interaction is crucial for optimizing cotton hybrid performance, facilitating consistent yield and stability in semi-arid regions. To address this challenge, a total of 45 hybrids were evaluated across three kharif seasons (2021–2023) at Punjab Agricultural University Regional Research Station, Abohar. The analysis integrated combined analysis of variance (ANOVA), additive main effects and multiplicative interaction (AMMI), and genotype + genotype × environment (GGE) biplot approaches, supplemented with stability indices such as AMMI stability value (ASV), genotype stability index (GSI), and the weighted average of absolute scores (WAASBY) index, to identify high-performing and stable hybrids. Seed-cotton yield ranged from 2 122 to 3 168 kg·ha−1, with environmental effects explaining the largest proportion of phenotypic variation. The significant genotype × environment interaction (GEI) indicated differential hybrid performance across seasons. AMMI and GGE analyses identified hybrids exhibiting both broad and specific adaptation. Stability indices (ASV, GSI, and WAASBY) consistently identified G7, G8, G17, G22, and G45 as both stable and high-yielding, with mean seed cotton yield (SCY) ranging from 2 625 to 2 996 kg·ha−1. For yield component traits, G35 and G21 showed the highest sympodia per plant, G20 and G41 exhibited superior boll weight, and G38 had the highest bolls per plant. GGE biplot analysis indicated that E1 was both discriminative and representative for SCY, whereas E2 and E3 were most informative for BW and BPP, respectively, reflecting pronounced seasonal variations. Overall, the integrated analytic pipeline (ANOVA → AMMI → GGE → ASV/GSI/WAASBY) effectively partitioned and interpreted complex GEI into robust selection decisions. This approach facilitated the identification of a refined set of hybrids exhibiting temporal stability, high yield potential, and suitability for both wide and season-specific adaptation.

Comparison of Yield & Agronomical Characteristics of four Local Mung Bean Varieties under Climatic Conditions of Kabul, Afghanistan

Mung bean (Vigna radiata L.) is an important pulse crop with considerable potential to enhance food and nutritional security, improve soil fertility, and increase farmers’ incomes in Afghanistan. However, its productivity remains constrained by the widespread use of low-yielding varieties and the challenges associated with semi-arid climatic conditions. This study evaluated the Agronomic performance and yield potential of four mung bean varieties under the Agro climatic conditions of Kabul, Afghanistan, where low annual precipitation, high summer temperatures, and climatic variability limit crop production. The experiment was conducted using a Randomized Complete Block Design (RCBD) consisting of four treatments: Helmandi (T1), Local (T2), 08 Certified (T3), and 07 Certified (T4), with six replications. Data were analysed using analysis of variance (ANOVA), and treatment means were compared using an appropriate mean separation test. The results demonstrated significant differences (P < 0.05) among the evaluated varieties. The 07 Certified variety (T4) produced the highest mean grain yield (1,833.77 kg ha⁻¹), followed by 08 Certified (T3) (1,720.72 kg ha⁻¹), Local (T2) (1,378.87 kg ha⁻¹), and Helmandi (T1) (643.56 kg ha⁻¹). Mean comparison analysis confirmed significant differences among all varieties, with the performance ranking as T4 > T3 > T2 > T1. The superior yield performance of the 07 Certified variety indicates its greater adaptability and productivity under the semi-arid conditions of Kabul. These findings highlight the importance of promoting improved certified mung bean varieties to enhance crop productivity, support climate resilient agricultural systems, and contribute to improved food security and rural livelihoods in Afghanistan. Further multi location and multi-season evaluations are recommended to assess the stability, adaptability, and potential for wider adoption of the 07 certified variety.