SUMMARY
Understanding genotype by environment interaction (GEI) is important for crop improvement because it aids in the recommendation of cultivars and the identification of appropriate production environments. The objective of this study was to determine the magnitude of GEI for the grain yield of wheat grown under rain-fed conditions in Zambia by using the additive main effects and multiplicative interaction (AMMI) model. The study was conducted in 2015/16 at Mutanda Research Station, Mt. Makulu Research Station and Golden Valley Agricultural Research Trust (GART) in Chibombo. During2016/17, the experiment was performed at Mpongwe, Mt. Makulu Research Station and GART Chibombo, Zambia. Fifty-five rain-fed wheat genotypes were evaluated for grain yield in a 5 × 11 alpha lattice design with two replications. Results revealed the presence of significant variation in yield across genotypes, environments, and GEI indicating the differential performance of genotypes across environments. The variance due to the effect of environments was higher than the variances due to genotypes and GEI. The variances ascribed to environments, genotypes, and GEI accounted for 45.79%, 12.96%, and 22.56% of the total variation, respectively. These results indicated that in rain-fed wheat genotypes under study, grain yield was more controlled by the environment than by genetics. AMMI biplot analysis demonstrated that E2 was the main contributor to the GEI given that it was located farthest from the origin. Furthermore, E2 was unstable yet recorded the highest yield. Genotype G47 contributed highly to the GEI sum of squares considering that it was also located far from the origin. Genotypes G12 and G18 were relatively stable because they were situated close to the origin. Their position indicated that they had minimal interaction with the environment. Genotype 47 was the highest-yielding genotype but was unstable, whereas G34 was the lowest-yielding genotype and was unstable.
Keywords: Genotype–environment interaction, additive main effects and multiplicative interaction analysis, genetics, stability, Triticum aestivum L.
DOI: https://doi.org/10.54910/sabrao2021.53.4.5