Artificial neural networks for predicting the genetic value of Eucalyptus progenies.

The main goal of researchers in genetic breeding programs is to select superior genotypes and recommend varieties through effective selection methods. Thus, the objective of this study was to evaluate the performance of Artificial Neural Networks (ANN) in predicting genetic values for progeny selection of Eucalyptus sp. For the training of ANN, 64 experiments were simulated that varied among means (5, 10, 15 and 20), heritability (10, 20, 30 and 40%) and coefficient of variation (10, 20, 30 and 40%). For validation of ANN, data from a progeny test of Eucalyptus camaldulensis was used.