Genotype x environment (G x E) interaction is one of the most crucial issues in plant breeding progress and has to be perfectly examined based on figures from multi environment experiments. The present study was anticipated to analyze the magnitude of GxE interaction and evaluate the adaptability and stability of open pollinated maize genotypes for grain yield, using AMMI (Additive Main Effects and Multiplicative Interaction) model. The field experiment was conducted for two consecutive years during the off seasons of 2016/17 and 2017/18 at three locations namely, Awra, Dalifage and Dubti. The experiment in each location was laid out using Completely Randomized Block Design (RCBD) with three replications. The pooled analysis of variance over environments for A MMImodel were highly significant (P<0.01). The results revealed the existence of considerable variation among the genotypes and the environments for grain yield, indicating the differential performance of genotypes across the environments. Based on the AMMI model genotypes Melkassa-2 and Melkassa-7were the most stable varieties with lower Interaction (IPCA) score and smallest AMMI Stability Value (ASV). Genotypes Melkassa-3 and Melkassa-4 had shown specific adaptation to environment Awra and Dalifage, respectively; indicating that these genotypes were more interactive or sensitive to environmental changes and have better adaptation for specific locations. The results of AMMI biplots were also in agreement with the results of ASV. Thus, the whole analysis generally suggested that maize grain yield was highly influenced by environments and G x E interaction, which contributed more to the phenotypic disparity. Further testing of these open pollinated maize varieties in more seasons and locations could enhance breeding efficiency with respect to genotypic stability and adaptation across environments.
Mohammed Abate. Genotype by environment interaction and yield stability analysis of open pollinated maize varieties using ammi model in afar regional state, Ethiopia. Int. J. Agric. Nutr. 2019;1(1):01-06.