Genotype - Environment Interaction for Grain Yield In Wheat | ||||
| Annals of Agricultural Science, Moshtohor | ||||
| Article 4, Volume 60, Issue 4, December 2022, Page 1035-1044 PDF (718.05 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/assjm.2022.275849 | ||||
 View on SCiNiTO | ||||
| Author | ||||
Nafisa ALI 
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| Agronomy Department, Faculty of Agriculture, Benha University. | ||||
| Abstract | ||||
| Three field experiments were carried out at the Experimental Farm Station of the Faculty of Agriculture Moshtohor, Benha University, Kalubia Gavernorate, Egypt, during two successive winter seasons of 2017/2018 and 2018/2019 to investigate the effect of some folair application materials: [ascorbic acid (ASA) and potassium (K) on and genetic stability of wheat plants grown under different water stress levels. The treatments included the combination between three water treatments and 4 treatments of folair application spray with control. The treatments were arranged in split-split plot design with three replicates, the main plots were assigned to water stress levels, while five treatments of folair application spray were located in subplots and six varieties were arranged in sub-sub plot. Stability analysis of the 6 wheat genotypes was carried out for grain yield/plant across all studied environments.The effect of the interaction becomes more complex with the increase of number of factors with the same magnitude that have impact on genotype. Very often one prevalent environmental factor influences the genotype. In such cases linear regression models can comprise a good part of the sum of squares of the interaction and thus explain the stability of the genotype. With regard to AMMI analysis of grain yield/ m2, Results showed highly significant due to treatments, genotypes and environments this pointed out that all sources of variance are important in analysis, however genotypes contributed with (5.77%) in treatments variances, the environment contributed with (89.63%) in treatments variance also interaction principal component axis (IPCA) Pc1 and Pc2 accounted for (39.36% and 28.62%) respectively, were found to be highly significant, the (IPCA1 and IPCA2) together with had a total (67.98%) variances of the interaction. The genotype G5 is suitable to E3, E5, E11, E23 and E29. The genotype G6 is suitable to E12, E14 and E26. The polygon reflects that G2, G1 and G3 are high grain yielding and suitable to either of the environments. An important feature of the AMMI was also predicted. In mega-environment identification process, furthest genotypes are connected together to form a polygon, and perpendicular genotypes are drawn to form sectors which will make it easy to visualize the mega-environments. | ||||
| Keywords | ||||
| Genotype; Grain Yield; Ascorbic Acid (ASA) -Potassium (K); Stability | ||||
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