S. Oluwafemi Oyamakin, M. Olalekan Durojaiye, RETRACTED: Monte Carlo Approach To Genotype By Environment Interaction Models, Journal of Model Based Research, Volume 1, Issue 1, 2020, Pages 26-33, ISSN 2643-2811, https://doi.org/10.14302/issn.2643-2811.jmbr-20-3237.
(https://oap-researcharticles.org/jmbr/article/1291)
Abstract: This article has been retracted on 10 February 2021. VIEW THE RETRACTION NOTICE (https://doi.org/10.14302/issn.2643-2811.jmbr-25-5847) Understanding the implication of Genotype-by-Environment (GXE) interaction structure is an important consideration in plant breeding programs. Traditional statistical analyses of yield trials provide little or no insight into the particular pattern or structure of the GXE interaction. In this study, efforts were made to solve these problems under different level of data occurrence. We employed the simulation process of Monte Carlo in generating since use of a real-life data may pose a serious difficulty. In this paper, we simulated for two data Types of Balance and Unbalance designs with different Levels of generations (3X3, 7X7, 10X10, and 3X7, 7X3, 7X10, 10X7 , , respectively). We therefore check the performance of GXE interaction on four different models (AMMI, FW, GGE and Mixed model), and also their stability and adaptability. The findings revealed that, when the assumption was maintained, AMMI outperformed Finlay-Wilkinson model, GGE Biplot model and Mixed model.
Keywords: Genotype-by-Environment Interaction; Plant breeding; stability and adaptability AMMI; FW; GGE and Mixed model; Monte Carlo Experiment