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Doctor of Philosophy, (Animal Science)
Study Completed: 2010
College of Sciences
Use of decision science to aid selection of genetically superior animals
Mr Sherriff developed a model linking nutrient partitioning and additive genetic effects, random genetic effects, and environmental variations for micro-traits to simulate pig growth under different dietary regimes. Different non-linear optimization procedures (tabu search, genetic algorithm, simulated annealing) were applied to the model to find the optimal genotype for a given selection objective, based on macro-traits and under different dietary conditions. The genetic algorithm was found to be the most consistent and reliable non-linear optimization procedure. The research has shown that there is a single optimal genome for a particular diet and selection objective. Mr Sherriff’s work has also shown that this single optimal genome changes as the diet and selection objective change.
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Last updated on Tuesday 04 April 2017