Abstract:This chapter discusses possible types of data centering and the properties of the corresponding biplots. The dataset consists of the grain yield data of 18 winter wheat genotypes tested at four locati...This chapter discusses possible types of data centering and the properties of the corresponding biplots. The dataset consists of the grain yield data of 18 winter wheat genotypes tested at four locations in Ontario, Canada, in 1993. The chapter discusses five possible types of data centering: uncentered, grand mean-centered, environment-centered, double-centered and genotype-centered. The usefulness of a biplot type depends entirely on the research purpose. The most common purpose of variety trials is to identify genotypes that have superior performances in the whole target region or a subregion of it. Another key objective in variety data analysis is to identify test environments that are most suitable for testing genotypes. The GGE biplot is the only biplot type suitable for genotype evaluation and test environment evaluation. This conclusion has a sound theoretical basis, which is described in the chapter. Other types of biplots may be useful for a particular research objective.Read More
Publication Year: 2014
Publication Date: 2014-03-21
Language: en
Type: other
Indexed In: ['crossref']
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