Seven populations with different genetic means and different data structures resulting from replacing 0, 10, 25, 50, 75, 90 and 100% of sires simulated by GENESYS program were used to compare the mixed-model methodology (MMM) with the GenSys methodology, according to the accuracies and predicted error variances (PEV) of the breeding values, estimated under a sire or an animal model. Under the sire model, lower accuracy and greater PEV for both methodologies were observed as selection intensity increased, due to the reduced accuracy of estimation of the fixed effects and the reduced average number of progenies per sire. The superiority of MMM under the sire model was due to increase in the accuracy of the estimated fixed effects. Under the animal model, the tendencies were different. For the MMM, accuracy increased and PEV remained practically constant, as selection intensity increased, whereas for the GenSys methodology, reduced accuracy and an increase on the PEV as selection intensity increased were observed. Greater accuracies for MMM were due to the increased number of genetic ties, whereas the reduced accuracy for GenSys was due to the lower accuracy of the estimation of the fixed effects. The superiority of MMM was a result of the greater accuracy of the levels of fixed effect estimates and the use of the full relationship matrix, which included a base-population of unrelated, non-endogamic and non-selected individuals. The MMM was superior to GenSys according to the accuracy and PEV, for this structure of simulated selected data, mainly under the animal model.
animal model; GenSys; mixed-model; sire model
