Abstract. Stochastic simulation was used to analyse the effect of missing sire information (MSI) on different parameters of genetic evaluation. Eighty proven bulls producing 100 progeny and 40 test bulls producing 50 progeny were simulated. The proportion of MSI was varied in four steps from 10 to 40%. Analyses were carried out for h² = 0.10 and h² = 0.25. A sire model was used for simulation and evaluation. The variance of DYD increased with increasing proportion of MSI. Variances of sire breeding values as well as rank correlations decreased with increasing proportion of MSI. The probability that the simulated Top5 and Top10 bulls were placed under the estimated Top5 and Top10 bulls, respectively, decreased with increasing percentage of MSI. The same holds true for the probability of ranking a bull with 10 to 40% MSI under the 5% best bulls with complete pedigree. The loss of response to selection increased up to 8.6% for proven bulls and up to 12.6% for test bulls.
FERN – a Java framework for stochastic simulation and evaluation of reaction networks
