Genotype × Environment Interaction and Selection of High Yielding Wheat Genotypes for Different Wheat-growing Areas of Ethiopia

Alemu, Gadisa; Dabi, Alemu; Geleta, N; Duga, Ruth; Solomon, Tafesse; Zegaye, Habtemariam; Getamesay, Abebe; Delesa, Abebe; Asnake, Dawit; Asefa, Bayisa; Shewaye, Yewubdar; Abeyo, Bekele; Badebo, Ayele

doi:10.11648/j.ajbio.20210902.15

Cited by 7 publications

(5 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The GGE biplot is a data visualization tool that allows an evaluation of environments due to the discriminative ability and representativeness of the GGE view, which is an advantage over the AMMI biplot analysis [39]. The GGE biplot analysis is the most effective way for a precise and useful interpretation of genotype-environment interactions as well as interrelationships among various test environments and genotypes and identifies the best line of each environment [40].…”

Section: Discussionmentioning

confidence: 99%

Genotype by Environment Interaction Analysis for Grain Yield of Wheat (Triticum aestivum (L.) em.Thell) Genotypes

et al. 2022

View full text Add to dashboard Cite

Genotype environment interaction and stability performance were investigated on grain yield per plot in eight environments during Rabi (here, rabi means that a crop has been grown in Rabi season: crops that are sown in winter and harvested in spring in the Indian subcontinent) 2019–2020 and 2020–2021 using 100 diverse wheat genotypes. Research was conducted at Chaudhary Charan Singh Haryana Agricultural University, Hisar, Haryana in India. The analysis of variance revealed that genotype, environment and their interaction had a highly significant effect on the yield as reflected in Eberhart and Russel model and The Eberhart and Russell model indicated the suitability of the genotypes WH 1142, PBW 661, PBW 475 and DBW 17 with high mean, bi > 1 and non-significant deviation from regression to favorable environment, whereas the genotypes UP 2660 and DBW 88 with high mean, bi < 1 and non-significant deviation from regression were found suitable for poor environment. The Additive Main Effects and Multipicative Interaction (AMMI) analysis of variance for grain yield per plot across the environments showed that 26.41% of the total variation was attributed to genotypic effects, 70.22% to environmental effects and 3.37% to genotype × environment interaction effects. AMMI biplot study indicated the genotypes PBW 750, DPW 621-50, WH 542, PBW 486, PBW 661 and WH 1192 stable across the environments as they did not exert strong interactive forces; hence, they were selected as potential candidates for possible release in the study areas. Furthermore, the which-won–where model indicated the adaptation of genotypes PBW 706, PBW 769, DBW 116, WH 1157, WH 789 and WH1186 to first mega-environment and genotypes DBW 16, WH 1152, WH 1105 and PBW 503 in the second. These genotypes could be utilized in breeding programs to improve grain yield in bread wheat and may be used as stable breeding material for commercial cultivation.

show abstract

Section: Discussionmentioning

confidence: 99%

Genotype by Environment Interaction Analysis for Grain Yield of Wheat (Triticum aestivum (L.) em.Thell) Genotypes

et al. 2022

View full text Add to dashboard Cite

show abstract

“…The substantial variability attributed to environmental factors indicates high differences among the tested environmental conditions, and also emphasises the predominant role of environmental factors in shaping the grain yield of wheat genotypes. Tulu & Wondimu (2019); Alemu et al (2021); and Kedir et al (2022) have also reported significant environmental effects, stressing the necessity of breeding program to focus on specific adaptation.…”

Section: Resultsmentioning

confidence: 99%

Assessing drought tolerance in advance wheat genotypes using stress tolerance indices

Rijal,

Bashyal,

Yadav

et al. 2024

Arch. Agric. Environ. Sci.

View full text Add to dashboard Cite

Wheat, an important crop of Nepal, is significantly affected by drought, leading to severe yield losses. Thus, an experiment was conducted to assess effect of drought on wheat traits and to identify drought resilient genotypes comparing stress tolerance indices. Altogether seventy-two genotypes including checks were evaluated under drought and non-stress condition in an alpha-lattice design with two replications at the research block of National Rice Research Program, Hardinath, Nepal during winter of 2019/20. Analysis of variance revealed significant genotypic differences (p<0.01) in traits such as days to heading, anthesis, and maturity, plant height, flag leaf area, spike length, grains per spike, 1000-grain weight, and grain yield under both conditions. The combined analysis of variance showed that genotype, environment, and their interaction significantly influenced most traits. The environment was the dominant factor, accounting for 86.2% of the variation in grain yield, followed by genotype (9.5%) and genotype-environment interaction (4.3%). Among the nine quantitative traits assessed, grain yield was most severely affected due to drought, experiencing a substantial reduction of 63%. To assess drought tolerance, six indices (TOL, SSI, MP, GMP, HMP, and STI) were calculated based on grain yield data. Most indices identified genotypes NL1373, NL1308, NL1407, BL4868, and BL4947 as highly drought-tolerant. Among the indices, MP, STI, and GMP were the most reliable for measuring stress tolerance due to their strong positive correlation with yield under both conditions. These identified genotypes are promising candidates for breeding programs aimed at developing drought-resilient wheat varieties, thereby enhancing food security in drought-affected regions.

show abstract

“…Despite this potential, Ethiopia remains a net importer of wheat due to the huge gap between production and consumption (Abate, 2018;Brasesco et al, 2019) emanating from very low national yield (Haile et al, 2013a(Haile et al, , 2013b and increased demand for wheat (Zegeye et al, 2020). The mean productivity of wheat in Ethiopia is 3 tons per hectare (t/ha) (CSA 2021) which is below the attainable yield for the crop which can be up to 5 t/ha (Alemu et al, 2019;Zegeye et al, 2020;Nigus et al, 2022). Hence, low productivity continues to be the major challenge facing wheat production in Ethiopia (Alemu et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…The mean productivity of wheat in Ethiopia is 3 tons per hectare (t/ha) (CSA 2021) which is below the attainable yield for the crop which can be up to 5 t/ha (Alemu et al, 2019;Zegeye et al, 2020;Nigus et al, 2022). Hence, low productivity continues to be the major challenge facing wheat production in Ethiopia (Alemu et al, 2019). Accordingly, continuous enhancement of wheat yield is crucially needed.…”

Section: Introductionmentioning

confidence: 99%

Genetic variation, genetic advance, heritability and correlation analysis of phenotypic traits in tetraploid wheat (Triticum turgidum spp.) landraces and some improved cultivars of Ethiopia

Fufa,

Gedebo,

Leta

et al. 2024

Plant Genet. Resour.

View full text Add to dashboard Cite

Tetraploid wheat species from Ethiopia hold ample genetic variation, which could provide a source for improvement of wheat. A total of 196 Ethiopian tetraploid wheat (Triticum turgidum spp.) accessions, including 174 landraces and 22 improved cultivars, were evaluated at Sinana and Debrezeit to assess morphological variation, genetic advance, heritability and correlation based on 11 phenotypic traits. Except for spike length, highly significant variation (P < 0.001) among genotypes for all traits was observed. The observed mean and range values of the phenotypic traits revealed high variability in the accessions. Phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) values were high for grain yield, biomass yield and harvest index. Seed yield showed highly significant (P < 0.001) negative correlation with days to booting and days to maturity and positive correlation with all traits. The estimates of heritability (H2) for grain yield and the number of spikelets per spike respectively ranged from 41.78 to 84.62%. The genetic advance as a percentage of mean was low for the number of seeds per spikelet, days to booting and days to maturity; intermediate for plant height, thousand kernel weight and spike length and high for the number of spikelets per spike, the number of effective tillers per plant, grain yield, biomass yield and harvest index, respectively. The number of spikelets per spike gave a high value of genetic advance and heritability implying high genetic gain from its selection.

show abstract

Genotype × Environment Interaction and Selection of High Yielding Wheat Genotypes for Different Wheat-growing Areas of Ethiopia

Cited by 7 publications

References 15 publications

Genotype by Environment Interaction Analysis for Grain Yield of Wheat (Triticum aestivum (L.) em.Thell) Genotypes

Genotype by Environment Interaction Analysis for Grain Yield of Wheat (Triticum aestivum (L.) em.Thell) Genotypes

Assessing drought tolerance in advance wheat genotypes using stress tolerance indices

Genetic variation, genetic advance, heritability and correlation analysis of phenotypic traits in tetraploid wheat (Triticum turgidum spp.) landraces and some improved cultivars of Ethiopia

Contact Info

Product

Resources

About