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Large clonal planting is a practice already established by the timber companies. However, statistical models, the plot size used in selection of superior clones is still a topic of discussion between forest breeders. Based on 11 trials containing plots similar to commercial plantations and 63 clones, this study aimed to evaluate the use of pedigree information, genetic heterogeneity between environments and the possibility of plot reduction in order to optimize the predictive accuracies of the mean annual increment (MAI) performing cross-validation between environments. All trials showed high narrow-sense heritabilities (from 0.65 to 0.95) and a strong change of clonal rankings was verified. It was observed that the inclusion of pedigree information and particular genetic variances for each trial on model is an effective procedure to increase the predictive accuracies. Moreover, between 4-16 trees evaluated per plot is a reliable size for the prediction of forest stands.

Acurácia preditiva de testes clonais de Eucalyptus spp. utilizando efeitos aditivos do parentesco e validação cruzada