Stability and adaptability analysis of rice (Oryza sativa L.) genotypes across contrasting seasonal environments using AMMI, WAASB and multi-trait stability indices
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.
Fine-grain rice is highly preferred by consumers due to its superior cooking quality and higher market price. Consequently, the Bangladesh Rice Research Institute (BRRI) has developed several fine-grain rice genotypes through its breeding programs. This study evaluated the yield performance and stability of nine advanced fine-grain rice lines along with two local cultivars and five released varieties across ten agro-ecological zones during the 2023–24 Boro season. Genotype–environment interaction (GEI) for grain yield (GY) and yield-related traits was analyzed using the Additive Main Effects and Multiplicative Interaction (AMMI) model, the Weighted Average of Absolute Scores and Yield (WAASBY) index, and the Multi-Trait Stability Index (MTSI). Combined analysis of variance revealed that genotype, environment, and GEI significantly influenced grain yield and its components. Most traits exhibited moderate to high heritability (0.74–0.97) with selection accuracy above 80%, indicating strong genetic control. Among the tested genotypes, BR17-23-8-2-7B (G6) recorded the highest mean yield, while Bhanga, Faridpur (E3) was identified as the most favorable environment. Stability analyses indicated that G6 ranked highest based on WAASBY (91.45), whereas BRH11-7-17-10B (G7) and BRH9-3-2B (G8) were identified as the most stable genotypes according to MTSI. Overall, G6, G7, and G8 showed superior performance compared with the local and released varieties, suggesting their potential for cultivation and use in breeding programs targeting diverse agro-ecological environments.
Bangladesh Rice J.29(1): 1-17, 2025
M. M. Hasan, M. H. R. Mukul, Shamsunnaher et al.· Bangladesh Rice Journal· 0 citations
Genotype × environment interaction is an important consideration in groundnut improvement because yield and related traits are strongly influenced by environmental conditions. The present study evaluated the stability and adaptability of 74 groundnut genotypes, including four standard checks, across six environments during the Kharif seasons of 2023 and 2024. The environments represented three locations: CTAE Instructional Farm, Udaipur; KVK, Rajsamand; and KVK, Chittorgarh. The experiment was conducted in an augmented block design, and observations were recorded for days to 50 per cent flowering, number of branches per plant, dry pod yield per plant, kernel yield per plant, and 100-seed weight. Stability analysis was performed using the Eberhart and Russell model based on mean performance, regression coefficient, and deviation from regression. Pooled analysis of variance showed significant effects of genotype, environment, and genotype × environment interaction for all studied traits, indicating differential responses of genotypes across environments. Several genotypes showed desirable mean performance and adaptation for yield-related traits. Based on dry pod yield, kernel yield, and associated stability parameters, PI-614, PI-1362, PI-1660, PI-1989, PI-2124, PI-2311, PI-2452, PI-2506, PI-2571, PI-2749, PI-1473, PI-1530, PI-1918, PI-2344, PI-2544, and PI-3132 were identified as promising genotypes. These genotypes may be useful in breeding programmes aimed at improving yield performance and adaptability in groundnut, subject to further validation across additional environments.
Sarita Choudhary, P. Singh, R. B. Dubey et al.· Journal of Advances in Biolo...· 0 citations
Barley is a crucial crop worldwide, but it faces significant production challenges due to limited adaptable varieties, poor management practices, and environmental factors. Food barley varieties often struggle in unfamiliar environments, leading to crop loss. To address this issue, a study was conducted to evaluating the adaptability, performance, and yield stability of released high-performing food barley varieties over two years across 17 diverse environments during the 2023–2024 cropping years.
A multi-environment trial (MET) involving 20 released food barley genotypes was conducted during the 2023–2024 main cropping years across 17 environments using a randomized complete block design with three replications. Grain yield data were analyzed using combined analysis of variance (ANOVA), Additive Main Effects and Multiplicative Interaction (AMMI), AMMI Stability Value (ASV), Yield Stability Index (YSI), and Genotype plus Genotype × Environment (GGE) biplot analyses to assess genotype performance, stability, adaptability, and test environment suitability.
Combined ANOVA and AMMI revealed highly significant (P < 0.0001) effects for all sources of variation. In the ANOVA, environment, year, genotype, environment × year, genotype × environment interaction (GEI), genotype × year, and genotype × environment × year accounted for 33.06%, 10.62%, 8.00%, 13.44%, 10.72%, 2.84%, and 6.40% of the total variation, respectively. Pooled AMMI showed 61.47%, 7.09%, and 16.58% of the total variation attributable to environment, genotype, and GEI, respectively. Environmental mean grain yield ranged from 1.44 t ha⁻¹ at Ambo to 3.17 t ha⁻¹ at Debre Markos. Genotype G2 produced the highest mean grain yield (3.28 t ha⁻¹), while G11 had the lowest (1.91 t ha⁻¹). GEI biplot grouped the seventeen test environments into three mega-environments. AMMI identified genotypes G8, G9, G14, and G15 as exhibiting favourable yield and stability performance across the evaluated environments. The GGE biplot further revealed three distinct mega-environments and identified Holeta (E11) as both highly discriminative and representative, making it a suitable core testing environment. Based on the Yield Stability Index (YSI), genotypes G8 and G14 exhibited the most favourable combination of grain yield and stability, followed by G9 and G15, whereas G2 combined the highest grain yield with comparatively lower stability. Overall, G8, G9, G14, and G15 demonstrated favourable yield performance and stability and are promising candidates for further validation and recommendation in Ethiopian barley-growing environments.
Genotypes G8, G9, G14, and G15 exhibited favourable combinations of grain yield and stability across the evaluated environments and are promising candidates for further validation and wider cultivation in Ethiopia, particularly across the cool sub-humid and humid Ethiopian highland barley-growing agro-ecologies represented by the test environments. These genotypes are also promising parental materials for developing broadly adapted, high-yielding, and stable food barley cultivars. Although G2 produced the highest mean grain yield, it is comparatively less stable than the most stable genotypes and is therefore particularly suited to favourable production environments where maximizing yield is the primary objective. However, its superior yield potential makes G2 a potential parent for improving grain-yield potential, particularly when combined with stable and broadly adapted genotypes. Thus, G2 may be exploited for specific adaptation to high-potential favourable environments, whereas G8, G9, G14, and G15 may be prioritized for broad adaptation across similar Ethiopian highland agro-ecologies. The identification of Holeta as an ideal testing environment will also help improve the efficiency of future national barley breeding and evaluation programs.
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
Barley production in the Ethiopian highlands is constrained by soil acidity and the lack of acid‐tolerant genotypes. This study evaluated the effects of environment, genotype, and their interaction on barley performance and identified suitable genotypes for acidic soils. Ten barley genotypes, including eight accessions, one local variety, and one released cultivar, were tested under acidic and lime‐treated soil conditions using a randomized complete block design. The results on the additive main effects and multiplicative interactions (AMMI) analysis showed that environment explained 60.45% of the total variation, genotype 32.38%, and genotype by environment interaction accounted for 7.18%. The first and the second interaction principal component axes were significant and cumulatively accounted for 80.59% of the total interaction variance. Analysis of the first two principal components showed that E7 and E8 in the Gumer district, representing fully limed and unlimed soils, respectively, contributed most to the genotype by environment interaction. In contrast, E5 and E6 in the Hulla district, representing unlimed and fully limed soils, respectively, contributed least, while E1–E4 had moderate effects. Grain yields in limed environments consistently exceeded the grand mean of 2.79 t ha−1, whereas the unlimed environments produced substantially lower yields across. The first two AMMI components identified genotypes G1, G3, G9, and G10 as superior performers, combining high yield with stability. Therefore, expanding the cultivation of improved variety, G9, and further evaluating genotype G1, G3 and G10, and lime application could improve barley production and food security in the southern highlands of Ethiopia.
Chigign Mengiste, W. Worku, Berhanu Abate et al.· Plant-Environment Interactio...· 0 citations
Ratoon rice production offers an opportunity to increase rice productivity by utilizing the regrowth of harvested plants, thereby reducing production costs and shortening the cropping cycle. This study evaluated the ratooning potential and yield stability of five rice (Oryza sativa L.) genotypes across two environments in Niger State, Nigeria. Field experiments were conducted during the wet season at Badeggi and Edozhigi using a randomized complete block design with three replications. The genotypes evaluated were FARO 44, FARO 67, MADU YANKPA, WALUYE, and YANDA GWASHE. Data were collected on phenological, growth, and yield-related traits for both the main and ratoon crops and analyzed using analysis of variance, while treatment means were separated using Fisher's Least Significant Difference (LSD) test at the 5% probability level.
Significant (P ≤ 0.05) genotypic differences were observed for most of the measured traits, indicating substantial genetic variability among the evaluated genotypes. Grain yield was consistently lower in the ratoon crop than in the main crop; however, the genotypes differed significantly in their ability to sustain productivity after harvest. FARO 67 produced the highest grain yield in both the main crop (3,207.20 kg ha⁻¹) and ratoon crop (822.25 kg ha⁻¹) and exhibited the greatest yield stability across environments. MADU YANKPA was the earliest flowering genotype, indicating its suitability for short-duration production systems. The significant genotype × environment interaction for grain yield demonstrated differential genotype responses across locations. Overall, FARO 67 combined superior grain yield, ratooning ability, and yield stability, making it a promising genotype for cultivation and for use in breeding programmed aimed at improving ratoon rice productivity.
H. G. Yusuf, M. Dangana, S. Audu et al.· African Journal of Sustainab...· 0 citations
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