Bayesian prediction of genetic parameters in Eucalyptus globulus CLONES UNDER WATER SUPPLY CONDITIONS

Abstract

A Bayesian analysis of genetic parameters for growth traits at twelve months after planting was carried out in twenty nine Eucalyptus globulus clones in southern Chile. Two different environmental conditions were considered: 1) Non-irrigation and; 2) Plants were irrigated with a localized irrigation system. The Bayesian approach was performed using Gibbs sampling algorithm in a clone-environment interaction model. Heritability values were high in the water supply condition (posterior mode: H2=0.41, 0.36 and 0.39 for height, diameter and sectional area, respectively), while in the environment without irrigation, the heritabilities were significantly lower, which was confirmed by the Bayesian credible intervals (95 % probability). The posterior mode of the genetic correlation between sites was positive and high for all traits (r=0.7, 0.65 and 0.8, for height, diameter and sectional area, respectively) and according to the credible interval, it was statistically different from zero, indicating a non-significant interaction.