DECISION MAKING OF SELECTION USING GGE BIPLOT

Application of GGE biplot graphs in multi-environment trials on selection of forest trees

In the studies on selection and population genetics of forest trees that include the analysis of genotype × environment interaction (GE), the use of biplot graphs is relatively rare. This article describes the models and analytic methods useful in the biplot graphs, which enable the analyses of mega-environments, selection of the testing environment, as well as the evaluation of genotype stabil...

Bayesian GGE biplot models applied to maize multi-environments trials.

The additive main effects and multiplicative interaction (AMMI) and the genotype main effects and genotype x environment interaction (GGE) models stand out among the linear-bilinear models used in genotype x environment interaction studies. Despite the advantages of their use to describe genotype x environment (AMMI) or genotype and genotype x environment (GGE) interactions, these methods have ...

Evaluation of soybean lines and environmental stratification using the AMMI, GGE biplot, and factor analysis methods.

In the final phases of new soybean cultivar development, lines are cultivated in several locations across multiple seasons with the intention of identifying and selecting superior genotypes for quantitative traits. In this context, this study aimed to study the genotype-by-environment interaction for the trait grain yield (kg/ha), and to evaluate the adaptability and stability of early-cycle so...

Evaluation of Genotype × Environment Interaction for Seed Yield of Sunflower Hybrids using GGE Biplot Method

Extended Abstract Introduction and Objective: The sunflower is one of the most important oilseed plants in the world and its oil has nutritional and high economic value. Identification and selection of high-yielding genotypes with desirable characteristics are especially important in this plant. Evaluating sunflower genotypes under different environmental conditions would be useful to identify...

A hybrid decision making system using DEA and fuzzy models for supplier selection in the presence of multiple decision makers