Genotype - Environment Interaction Study in Corn Genotypes Using additive main effects and multiplicative interaction method and GGE- biplot Method

Document Type : Research Paper

Authors

1 Department of Agronomy and Plant Breeding, Karaj Branch, Islamic Azad University

2 Plant breeding Ph. D. student, Department of Agronomy and Plant Breeding, Young Researchers and Elite Club, Karaj Branch, Islamic Azad University, Karaj, Iran

Abstract

Background and objectives: The genotype- environment interaction is one of the most important factors causing constraints in breeding programs. The purpose of this study was genotype- environment interaction analyze for grain yield of corn in different weather conditions to identify adapted and stable cultivars for the studied environments based on the additive main effects and multiplicative interaction method and GGE biplot graphical method.
Materials and Methods: Twelve maize genotypes were evaluated for stability and adaptation in four environments (Arak, Birjand, Shiraz and Karaj). Experiment was conducted in a randomized complete block design with three replications in 2016. Stability analysis of AMMI and GGE biplot methods were used to analyze the effect of interaction between genotype and environment for grain yield.
Results: The results of ANOVA showed that the effect of environment and effect of genotype were significant at 1% probability level and the effect of genotype- environment interaction at the 5% probability level. The multiplicative effects analysis showed that only the first component of the genotype- environment interaction was significant at 1% probability level and alone accounts for about 63% of the genotype- environment interaction variance. Biplot was obtained from mean grain yield for genotypes and environments, and the first main component of the interaction effect was the superiority of genotype 6 due to its grain yield and high stability compared to other genotypes under study. The results obtained from the graphical GGE bipolar method showed that the main components of the first and second factors were 66.97% and 57.5%, respectively, and a total of 87.53% of the total variation in the grain yield data. Biplot analysis and comparison of the environments indicated a similar reaction in Arak, Birjand and Shiraz environments in terms of grain yield of genotypes. The polygon biplot comprised the environments under study in a mega-environment where only genotype 6 was stable. Based on the ideal genotype biplot, genotype 6 in terms of both stability and grain yield was more favorable than other genotypes and showed a high degree of adaptation in all studied environments.
Conclusion: The results of this study, using multivariate methods, showed that the effect of environment on grain yield in corn was significant. The genotypes showed significant genetic variation. The genetic variation between genotypes was so large that it was roughly twice the environmental factor in justifying the variance of the total. The results of both methods indicated genotype 6 (KSC704) as a stable genotype. This genotype was the best genotype in all four studied environments.

Keywords

References

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Journal of Crop Production
Volume 14, Issue 3
October 2021
Pages 1-12

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