Analysis and interpretation of genotype by environment interaction using cluster analysis

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In Agricultural Research, plant breeders conduct multi-environmental testing of genotypes to select the best genotype for farmers to grow on their farms. The genotype with relatively high mean yield across the test environments is usually considered as the best genotype to be selected. The problem with this selection is that some genotypes that might have performed well in some sites may have performed badly in some other sites. This phenomenon often referred to as genotype by environment (GE) interaction complicates the selection process. This thesis is therefore concerned with the analysis and interpretation of genotype by environment (GE) interaction which occurs when a wide range of genotypes are tested over a wide diversity of environmental conditions. Various statistical methods for the analysis of GE interaction have been proposed. One of the methods currently in use, Cluster analysis technique that is efficient at extracting information on genotype by environment (GE) interaction is of interest.
This dissertation is in partial fulfilment of a Masters program in Mathematics, 2005