Breeding values were predicted by iterating on data using reduced animal model. Body weight at 35 days of age from two lines of meat-type chickens was measured in two generations and data file was consisted on 1044 parents (base population), 829 progeny parents and 9039 progeny non-parents. The number of iterative rounds and processing time for mixed model equations solutions via iterating on data were evaluated using seven convergence criteria (10¹ to 10-5). A total of six rounds of iteration and 9 s of time and 158 rounds and 5 min and 38 s were required to reach the solutions for 10¹ and 10-5 convergence criteria, respectively. The correlation between predicted breeding values were perfect (r=1,00) and there were no significant differences between estimated genetic trends using 10-1 to 10-5 as a convergence criteria. Based on these results, it was concluded that iterating on data could be efficiently used for animal genetic evaluation in microcomputer without great computational requirements.
genetic evaluation; iteration on data; mixed model
