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.
Evaluation across contrasting crop seasons is important for identifying rice (Oryza sativa L.) genotypes with stable performance under variable field conditions. In the present study, 16 rice genotypes were evaluated across three seasonal environments at Rudrur to assess grain yield stability, adaptability and genotype × environment interaction. The experiment was conducted under recommended agronomic practices and grain yield data were subjected to stability analysis using the additive main effects and multiplicative interaction (AMMI) model and the best linear unbiased prediction (BLUP) approach. Stability was further assessed using the weighted average of absolute scores from the BLUP(WAASB) index and the AMMI stability value (ASV). Significant differences were observed among genotypes, environments and genotype × environment interactions, indicating that the performance of genotypes varied considerably across seasonal conditions. The AMMI analysis effectively partitioned the interaction effects, with the first two interaction principal component axes explaining most of the genotype × environment interaction variation. Based on WAASB and ASV, the genotypes RDR5289, KNM1638 and JGL24423 exhibited high stability and consistent grain yield across the tested environments. Multi-trait stability analysis further identified KNM1638 as the most balanced genotype, combining stable grain yield with desirable expression of important agronomic traits. Among the test environments, kharif 2022 provided the most stable conditions for evaluating genotype performance. The identified stable genotypes can be utilised formultilocation testing, varietal recommendation and as valuable parental lines in rice breeding programmes aimed at developing high-yielding cultivars with broad adaptation and stable performance under diverse seasonal environments.
R. Ramya, K. Parimala, B. Soundharya et al.· Plant Science Today· 0 citations
Climate change and environmental variability pose major challenges to sustainable wheat production, highlighting the need for stable and high-yielding cultivars. This study evaluated fifteen bread wheat (Triticum aestivum L.) genotypes across twelve environments during two consecutive growing seasons using a randomized complete block design with three replications. Stability and performance were assessed using Additive Main Effects and Multiplicative Interaction (AMMI), Genotype main plus Genotype × Environment (GGE) biplot, and multi-trait stability index (MTSI). AMMI combined ANOVA indicated that both grain yield per plot and falling number were significantly affected by genotype, environment and their interaction (GEI). The GGE biplot revealed that the first two principal components together explained 86.92% of the total variation in grain yield per plot and 88.27% for falling number, demonstrating the reliability of the model in interpreting GEI patterns. AMMI and GGE biplot analyses consistently identified Sakha 95 (G1), Misr 4 (G3), Sakha Line#1 (G6), Sakha Line#2 (G7), Gemmeiza Line#2 (G14), and Gemmeiza Line#3 (G15) as high-yielding and stable genotypes across environments. In contrast, Sakha Line#4 (G9), Sakha Line#6 (G11), Sakha Line#7 (G12), and Gemmeiza Line#1 (G13) showed poor adaptation and low stability. MTSI further refined selection by integrating yield and quality traits, identifying Gemmeiza Line#3, Sakha Line#3, Sakha Line#2, and Giza 171 as superior genotypes at 25% selection intensity, characterized by low MTSI values. The identification of stable, high-performing genotypes with desirable grain quality can contribute to sustainable wheat production by improving yield reliability under diverse environmental conditions and supporting more efficient cultivar selection for climate-resilient wheat production. Overall, integrating AMMI, GGE biplot, and MTSI provided a robust framework for identifying stable and high-performing wheat genotypes, supporting selection decisions in multi-environment breeding programs.
M. Genedy, Mahmoud A. Hussein, A. R. Ibrahim et al.· Sustainability· 0 citations
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.
Zeleke Legesse, Fikadu Tadesse, Berhanu Diribsa et al.· American Journal of Bioscien...· 0 citations
Cotton (Gossypium hirsutum L.) is a major fibre crop underpinning the global textile industry; however, its productivity is increasingly threatened by climatic variability and the resurgence of sap-sucking insect pests. The interaction between genotype and environment (G × E) further complicates the identification of stable and high-yielding genotypes, particularly under rainfed conditions. The present study evaluated 7 cotton genotypes across 9 environments (three locations over 3 consecutive years: 2021–24) in Odisha, India, to assess G × E interaction for 14 quantitative traits related to yield and sucking pest resistance using advanced statistical approaches. Combined analysis of variance revealedhighly significant (p < 0.01) effects of genotypes, environments and G × E interaction for all traits studied. The interaction component was particularly significant for key traits, including seed cotton yield (SCY), lint yield (LY) and populations of major sucking pests, necessitating a comprehensive stability analysis. High broad-sense heritability coupled with moderate to high genetic advance for yield and pest resistance traits indicated the predominance of additive gene action. Stability analyses using the Eberhart and Russell model, additive main effects and multiplicative interaction (AMMI) and genotype plus genotype by environment (GGE) biplot consistently identified genotype BS 3-17 as superior, exhibiting the highest mean SCY (1978 kg ha-1) and LY (675 kg ha-1), along with the lowest mean populations of aphids (APH) (5.28 per 3 leaves) and jassids (JAS) (1.82 per 3 leaves) across environments. The multi-trait stability index (MTSI) further ranked BS 3-17 as the most desirable genotype (MTSI score = 5.51), indicating its closest proximity to the ideotype. Agronomic validation trials demonstrated that high-density planting (90 × 30 cm) combined with 125 % of the recommended dose of fertilisers significantly enhanced the yield potential of BS 3-17, achieving up to 3114 kg ha-1. These findings establish BS 3-17 as a climate-resilient, high-yielding genotype suitable for commercial cultivation and a promising donor parent for breeding programs targeting yield stability and sucking pest resistance.
D. Subhashree, S. N. Bhabani, R. Jyoti et al.· Plant Science Today· 0 citations
Eighteen promising single crosses of maize and two check varieties (BHM-9 and 981) were assessed for genotype environment interaction (GEI) and stability for the selection of promising one(s) in three agro-ecological zones of Bangladesh. The AMMI (additive main effects and multiplicative interaction) model was used to analyze the GEI over three locations to select desired hybrid having higher yield and other potential attributes. Both genotypes (G) and environment (E) exhibited significant variation for all the characters studied. The environment of Gazipur and Ishwardi were poor but Dinajpur was favorable for the tested maize hybrids. Considering the mean, bi and S2di value, all the genotypes showed differential response of adaptability under different environmental conditions. Hybrids E12 (BIL28 × BIL96) and E15 (BIL95 × BIL79) showed the higher yield as well as stable across locations regarding response and stability parameters.
Bangladesh J. Agril. Res. 48(3): 359-370, September 2023
A. Karim, Z. Talukder, R. Sultana et al.· Bangladesh Journal of Agricu...· 0 citations
Under conditions of climate variability and heterogeneity of agro-ecological environments, assessment of genotype × environment (G×E) interaction constitutes a fundamental basis for the selection of wheat genotypes exhibiting both stable yield performance and strong adaptability across diverse environments. Accordingly, the objective of this study was to evaluate yield variability and G×E interactions among winter wheat genotypes grown across multiple locations in the Republic of Serbia. Multilocational field trials involving 25 wheat varieties were conducted over a single growing season at five locations. Results revealed statistically significant variability in grain yield attributable to genotype, location, and their interaction-with the location effect being the most pronounced. Application of the AMMI (Additive Main Effects and Multiplicative Interaction) model enabled identification of genotypes combining high yield potential with satisfactory stability. Visualization of results via a genotype-environment biplot facilitated interpretation of response patterns, thereby clarifying the nature and magnitude of genotype-specific adaptability across the tested environments. The highest mean yields were recorded for the newly released varieties NS Supernova (8.08 t ha-¹), NS Eudora (8.07 t ha-¹), and NS Rajna (7.80 t ha-¹); all three demonstrated robust adaptability and consistently high yields across multiple locations. In contrast, varieties such as NS Igra, NS Lavica, and NS Kimera yielded values close to the overall site-mean across most locations, indicating relatively uniform responsiveness and broad adaptability under variable agro-ecological conditions. Novi Sad and Pančevo emerged as locations with comparatively favorable agro-ecological conditions, where even varieties possessing only moderate yield potential achieved high absolute yields. Based on these findings, a set of promising genotypes was identified, characterized by a favorable combination of high and stable yield, and recommended for advancement into subsequent breeding stages and multi-year, multi-environment testing.
Krstina Aleksić, Jovana Timić, B. Jocković et al.· Selekcija i Semenarstvo· 0 citations
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