Research Project
Full description In crop and livestock breeding, combining numerous desirable alleles for important agronomic traits, such as disease resistance, drought and heat tolerance, end-use quality and high yield potential in the shortest possible time remains a major challenge. Because of the number of alleles that need to be considered for these traits, the number of possible mating combinations increases exponentially. This projects aims to develop novel strategies that enable breeders to design improved breeding programs via more efficient mate allocations, ultimately contributing to substantially increasing the rate of genetic gain. To address this, an integrated approach will be used that combines computer simulations with linear programming and evolutionary computing which are widely used for solving highly combinatorial problems. Using large scale public and commercial data sets we will evaluate the decrease in germplasm development time that can be achieved with this approach compared to traditional breeding approaches.