Genetic improvement of some novel traits is challenging in conventional dairy cattle breeding programs, because measuring the performance of each individual in the breeding population is too expensive.
With a new breeding tool that relies on DNA information – genomic selection – the expensive measurements need to be performed only on a subset of the whole breeding population. To optimally use this reduced number of measurements, alternative approaches are required compared to conventional traits such as milk yield.
The results of this PhD-thesis showed that genomic selection for novel traits can be optimized through careful selection of animals whose performance is recorded, and using available information from commonly measured traits.
This was a collaborative project between Poznan University of Life Sciences and Wageningen University.