For selection purposes and the prediction of breeding progress estimates of efficiencies are necessary for individual animals. Estimates of such efficiencies cannot be obtained by the conventional multiple regression procedures due to the high correlation between protein and fat deposition in individual animals. The present approach avoids this problem of collinearity by transforming the estimation procedure from multiple regression to straightforward bivariate regression by adjoining assumptions on the energy partitioning between protein and lipid deposition as well as its control. The simplest realistic assumptions are that the proportions of growth energy devoted to protein and lipid deposition are proportional to the energetic proportions of body protein and lipid respectively and that the activities of enzymes responsible for the control of protein and lipid deposition vary with powers of the size of these chemical components. It will be shown that these assumptions lead to bivariate regression estimates of protein and lipid deposition efficiencies in agreement with multiple regression results.
Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume 2002. Session 10, , 10.04, 2002
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