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Title: Modelling the effects of the infectious environment on pig growth and intake
Author: Sandberg, Fredrik B.
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2007
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A core part of any animal growth model is how it predicts the partitioning of dietary protein and energy to protein and lipid retention for different genotypes at different degrees of maturity. Solutions proposed in the literature to the partitioning problem were described in detail and criticised in relation to their scope, generality and economy of parameters (Chapter 1). Partitioning rules that withstood qualitative criticisms were then tested against literature data and a general quantitative partitioning rule was concluded for that had two key parameters: the maximum marginal efficiency of protein retention and the energy to protein ratio at which the maximum efficiency is achieved (Chapter 2). A general rule was identified which was able to predict protein retention for both protein and energy limiting diets. In Chapter 3 a general model was developed for predicting effects of sub-clinical pathogen challenges of different doses and virulence on the relative feed intake (RFI) of animals. In Chapter 4 literature data was reviewed for different kinds of pathogen challenges of a range of hosts to identify reductions in growth beyond that caused by anorexia: these were host, dose and time dependent. In only some instances did anorexia fully explain the reductions in growth. Solutions were needed for describing the protein costs of innate and acquired immune responses and repair of damaged tissues. In Chapter 5 a framework is proposed that predicts the performance of different genotypes (growth potential and disease resistance) when challenged by different doses of pathogens and given access to different foods. A partitioning rule was developed for partitioning scarce resources between growth and immune responses.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available