Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/12421
Title: Genetics of Growth in Mice with Particular Reference to the Application of Nonlinear Models
Contributor(s): Parratt, Andrew Christopher (author); Barker, James S F  (supervisor)orcid 
Conferred Date: 1985
Copyright Date: 1983
Open Access: Yes
Handle Link: https://hdl.handle.net/1959.11/12421
Abstract: The primary aim of this study was to examine the ability of nonlinear models to describe the weight/age and feed intake/age growth patterns in mice. The objective underlying this examination was to investigate the possibility of utilising the parameters of these models as selection criteria to alter the shape of the growth curves. In association with this primary aim an investigation of the interrelationships between growth, feed intake and the efficiency of growth was undertaken. Phenotypic and genetic analyses for weight, measures of growth rate, fraction of maturity, feed intake and feed efficiency were presented. Marked differences were found for some estimates of heritabilities, genetic and phenotypic correlation when compared with those reported for other studies on mice. A possible explanation, in terms of the differences in fractions of maturity when comparisons are made at similar ages,was proposed. Heritabilities tended to decrease with age for all measures of growth that were considered. Predicted direct and correlated responses to selection for a single generation were examined and the results obtained were consistent with predictions from two genetic models of growth proposed in the literature. ... It was concluded that the parameters of nonlinear models could be used as alternative selection criteria to alter the shape of the growth patterns for mice and possibly domestic livestock species. However, the large amount of data necessary to make accurate predictions on growth, the statistical problems associated with fitting different models and the requirement of an estimate of mature weight prior to selection may make utilising parameters of nonlinear models as selection criteria an unviable proposition.
Publication Type: Thesis Doctoral
Rights Statement: Copyright 1983 - Andrew Christopher Parratt
HERDC Category Description: T2 Thesis - Doctorate by Research
Appears in Collections:Thesis Doctoral

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