Current genetic evaluations ignore dominance effects. However, their incorporation might result in gain of accuracy of breeding values depending on dominance variance and on the number of animals with dominance relationships (Misztal et al., 1995). Furthermore, dominance effets can be used to implement mating systems (DeStefano and Hoeschele, 1992; Varona and Misztal, 1999). With the development of algorithms for large datasets using models with nonadditive genetic components, rapid inversion of dominance relationship matrices, and Method ℜ for computation of variance components with large data sets, there has been an interest in dominance effects over the last years. This interest is also due to datasets that include more relationships (e.g. fullsibs) necessary for estimating nonadditive genetic effects. The objectives of this papers were to 1) discuss previously estimated variance components for dominance effects in dairy cattle and to 2) use these components to draw conclusions on the value of incorporating dominance effects in genetic evaluation of dairy cattle

%V 2002. Session 1 %P 1.44 %G eng