Effect of more stringent convergence criterion of estimated breeding values on response to selection

Prediction of breeding values of individuals using an animal model BLUP eva luation takes substantial computing resources which can be a limiting facto r in simulation studies. When a large set of equations has to be solved ite ratively, computing time depends on the stringency of the convergence crite rion (CC). This study investigated the interaction between computing time a nd selection response as convergence was varied for single and multiple tra it (four traits) BLUP evaluation. Although the average true breeding values (TBV) of the top 2% of individuals improved with increasingly stringent CC , the gain in average TBV was not sufficient to justify the number of extra iterations needed at increasingly stringent CC with single trait BLUP and h(2)= 0.25. Under multiple trait BLUP evaluation, the TBV of the selected g roup and hence genetic response was more affected by CC. The proportion of animals (PA) that were In the final selected group at the most stringent CC was observed for all high values of the CC. PA was more dependent on CC, t han the average TBVs, indicating that animals entering and leaving the sele cted group as iterations proceed are those around the truncation point. Und er both single and multiple trait analysis, the BLUP subroutines took about 33 and 49% of total computing time respectively for 12 110 individuals, wh en the most stringent CC was used.