The Grand Selection
Selecting the best plants from large populations is one of the most important processes in the plant breeding practice. The selection process to obtain the best genotype typically spans multiple rounds of selection in successive plant populations. This combination of iteration and the stochastic element of mendelian allele segregation makes the result of even a relative simple selection process surprisingly difficult to predict.
For a plant breeder, it would be of large benefit, if an optimal selection process could be determined in advance, as growing and selecting large populations of plants is costly. In the context of a challenging research program in collaboration with three breeding companies, KeyGene is developing and testing algorithms to predict optimized breeding strategies.
Within this research program, there is room for research topics for a MSc student Scientific computing/Bioinformatics/Mathematics. Depending on skills and preferences, his or her assignment will concentrate on:
• Further development of optimization algorithms based on stochastic optimization, dynamic programming or genetic algorithms
• Exploration of the effect of different types of selection processes through modeling and/or simulation
• Exploration of patterns in breeding scenario outline (containing multiple selection rounds) and parameter choice in relation to the selection result
• Sensitivity analysis of the many possible parameters in a breeding scenario
The research will be carried as an internship at Keygene’s Wageningen facilities. For more information contact Dr. Jaap Buntjer (firstname.lastname@example.org) or Prof. Dr. Marcel Reinders (M.J.T.Reinders@tudelft.nl).