Ryan Sherriff

Doctor of Philosophy, (Animal Science)
Study Completed: 2010
College of Sciences

Citation

Thesis Title
Use of decision science to aid selection of genetically superior animals

Read article at Massey Research Online: MRO icon

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.

Supervisors
Professor Patrick Morel
Professor Graham Wood
Professor Hugh Blair

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