Multi-trait multi-environment models for selecting high-performance and stable eucalyptus clones

Multi-trait multi-environment (MTME) models were fitted to eucalyptus breeding trials data assess residual variance structure, genetic stability and adaptability. To do so, 215 clones evaluated in a randomized complete block design with 30 replicates one plant per plot four environments. At 36 months of age, tree diameter at breast height (DBH) pilodyn penetration (PP) measured. Two MTME fitted, for which residuals considered homoscedastic heteroscedastic, the best model selected using Bayesian information criterion. The harmonic mean relative performance genotypic values (HMRPGV) was used determine Of two models, heteroscedastic had better fit provided greater accuracy. In addition, genotype-by-environment interaction complex, there low correlation between DBH PP. Rank by high but HMRPGV facilitated clone selection through simultaneous evaluation stability, adaptability, productivity. Thus, our results suggest that / can be efficiently applied clones.