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

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

Background: As global warming accelerates, developing climate-resilient crops is critical for agricultural sustainability. Amid increasing climatic disruptions, fodder cowpea, a drought-adapted legume, remains an essential nutritional security crop for livestock feed. Quantifying its phenotypic stability across heterogeneous environments would be fundamental for any breeding program capable of withstanding such intensifying climatic stresses. Methods: This study evaluated twenty-three fodder cowpea germplasm lines and three popular varieties across three environments differing in temperature, moisture and soil fertility. The focus was on three major traits namely, green fodder yield per plant (GFY), crude fiber content (CFB) and crude protein content (CPR). We analyzed Genotype-by-environment interaction (GEI) using two models, Additive Main Effects and Multiplicative Interaction (AMMI) for individual trait evaluation and Multi-Trait Stability Index (MTSI) for simultaneous evaluation of all the three traits. Result: Significant GEI observation highlighted the need for environment-specific genotypes. Combined AMMI 1 and AMMI 2 biplot analyses found genotypes such as FD 1067 (G10), K-13-CP42 (G14) and CO (FC) 8 (G24) to be broadly stable performers for GFY, CPR and CFB across environments, while genotypes like GETC 40 (G21), GETC 41 (G22) and GETC 49 (G23) showed specific adaptation. The environments (E1-E3) exhibited distinct discriminative capacities depending on the trait, highlighting the value of multi-environment trials for reliable genotype selection.

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.

Dissecting Genotype x Environment Interaction and Adaptability for Grain Yield in Irrigated Rice Systems

Rice cultivation is widely adapted across diverse agro-climatic zones and serves as a global staple food, supplying up to 75% of caloric intake for nearly 3 billion people worldwide. In Bangladesh, evolving climate patterns are increasingly threatening rice productivity across diverse agro-ecological regions. Therefore, identifying stable, high-yielding genotypes across agro-climatic zones in Bangladesh is essential for sustaining national food security. This study evaluated the yield stability of 10 advanced inbred lines with 2 HYV as checks across 10 diverse agro climatic zones using AMMI and GGE models.  Eight yield-related traits were analyzed, including days to maturity, plant height, number of effective tillers, panicle length, number of filled grains, percent spikelet sterility, 1000-grain weight, and grain yield. Combined ANOVA revealed significant effects of genotype, environment, and GEI on all traits, which were significantly associated with yield. The first two PCs explained 29.8% and 23.5% of variation in AMMI, and 30.66% and 22.79% in GGE. Among the studied genotypes, we found genotype G6 (NGR750-1) was the most stable comparable to the check HYV BRRI dhan89. Stability analysis showed that GEI strongly affects grain yield and the selection of stable genotypes across environments. Further investigation is required to elucidate the adaptive mechanisms of the identified genotype, focusing on physiological and molecular determinants of grain yield across diverse environments. The identified genotype could be used further within the framework of the rice improvement program or released as a high-yielding cultivar following multi-location evaluation. Bangladesh Rice J.29(2): 17-24, 2025

Climate change impacts on global wheat ( Triticum aestivum L.) production: A comprehensive meta‐analysis of stressors, risks, and adaptation strategies

Climate change is exerting profound and multidimensional pressures on global wheat ( Triticum aestivum L.) production. Rising temperatures, higher vapor pressure deficit, and more frequent heatwaves reduce yields through strong, phenology‐dependent effects, with flowering and grain filling identified as the most vulnerable stages. Compound heat–drought events disproportionately depress grain number and weight, while erratic precipitation marked by prolonged dry spells, intense rainfall, and waterlogging further destabilizes yield and degrades soil fertility. Meta‐analytic evidence shows wheat yield reductions exceeding 50% under drought and ∼23% under waterlogging, with associated declines in grain quality. Elevated CO 2 enhances photosynthesis and biomass in optimal conditions but fails to compensate for warming or drought and often lowers grain protein and mineral concentrations. Soil degradation, salinity, and nutrient imbalance are intensifying, while warming accelerates pest survival, reproduction, and geographic expansion, increasing biotic stress risks. Despite these challenges, multiple adaptation pathways demonstrate strong effectiveness. Drought‐tolerant cultivars, optimized sowing dates, deficit irrigation, mulching, conservation agriculture, and soil restorative practices significantly improve resilience. Precision agriculture, unmanned aerial vehicle remote sensing, Internet of Things‐enabled monitoring, and artificial intelligence (AI)‐driven decision‐support tools enhance early stress detection and management precision. Economic evidence consistently shows high returns from climate‐smart interventions. Strengthening policy coherence, climate‐informed services, and agricultural financing is essential to scale adaptation and secure wheat production under a warming climate.

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

AMMI Analysis for Grain Yield Stability of Early Maturing Sorghum Genotypes in East Hararghe, Ethiopia

Sorghum (Sorghum bicolor (L.) Moench) is a critical staple cereal in semi-arid tropics, yet its productivity is highly constrained by genotype × environment interaction (GEI), which complicates variety selection and recommendation. This study aimed to estimate the magnitude of GEI, evaluate grain yield performance, and identify stable, high-yielding and early-maturing sorghum genotypes for potential release in East Hararghe, Ethiopia. Fourteen sorghum genotypes alongside two standard checks (Fadis 01 and Melkam) were tested across six environments, combining two locations (Fadis and Erer) over three consecutive main cropping seasons (2022–2024) using a randomized complete block design with three replications. Data on grain yield and agronomic traits were subjected to combined analysis of variance, Additive Main Effects and Multiplicative Interaction (AMMI) analysis, and Genotype Main Effect plus GEI (GGE) biplot analysis. Combined ANOVA revealed highly significant (P < 0.001) effects for genotype, environment, and GEI, confirming differential genotypic responses across testing environments. AMMI analysis partitioned the total grain yield variation, attributing 18.54% to genotype, 25.15% to environment, and 28.86% to GEI, indicating that environmental factors and their interaction with genotypes were the dominant sources of variation. The first two interaction principal component axes (IPCA1 and IPCA2) jointly explained 75.56% of the GEI variation, with IPCA1 contributing 52.6% and IPCA2 contributing 22.96%. Genotype G6 (ETSC14576-5-1) recorded the highest mean grain yield (4265 kg ha⁻¹) and demonstrated exceptional stability across environments, as evidenced by its proximity to the IPCA zero line in the AMMI1 biplot, favorable AMMI stability value, and low genotype selection index. GGE biplot analysis further ranked G6 closest to the ideal genotype, confirming its superior mean performance and stability. Polygon view identified three mega-environments, with G6 emerging as the winning genotype in one of them. Based on the integrated assessment using mean yield, AMMI parameters, and GGE biplot outputs, genotype ETSC14576-5-1 (G6) is identified as the most stable and high-yielding genotype across the tested environments. Therefore, this genotype is recommended for variety verification and subsequent release for cultivation in East Hararghe and similar agro-ecologies.