Published online by Cambridge University Press: 02 September 2010
A nucleus dairy population using multiple ovulation and embryo transfer (MOET) was stochastically modelled with overlapping generations. The aim was to investigate the feasibility of controlling inbreeding in MOET breeding schemes using more realistic parameters for embryo recovery and best linear unbiased prediction (BLUP) for genetic evaluation. Four different cases (involving the culling of donors, more donors and the use of organized progeny testing of nucleus bulls) were studied in combination with nested and factorial designs. Further studies involved modifications of the selection index, including subtracting parental breeding values, inflating the genetic variance in the BLUP evaluation and penalizing inbred animals; these options were examined both with and without organized progeny testing. The effects of applying these schemes on both genetic response and rate of inbreeding were investigated. The results stressed the importance of incorporating progeny testing into MOET schemes for value of reducing inbreeding whilst maintaining genetic progress. There was no significant difference between nested and factorial designs. In the absence of progeny testing the inflation of genetic variance was more effective than subtracting parental breeding values at controlling inbreeding; however incorporating progeny testing made the latter strategy more potent and the superiority of inflating the genetic variance was in this case much smaller and non-significant.