Adaptability and Stability of Coffea Canephora to Dynamic Environments Using Bayesian Approach

Abstract

The aim of the work was to use the Bayesian approach, modeling the interaction of coffee genotypes with the environment, using a bisegmented regression to identify stable and adapted genotypes. A group of 43 promising genotypes of Coffea canephora was chosen. The genotypes were arranged in a randomized block design with three replications of seven plants each. The experimental plot was harvested four years in the study period, according to the maturation cycle of each genotype. The proposed Bayesian methodology was implemented in the free program R using rstanarm and coda. After fine adjustments in the approach, it was possible to make inferences about the significant GxE interaction, and to discriminate the coffee genotypes regarding production, adaptability and stability.