Parameter estimation and sensitivity analysis of fat deposition models in beef steers using acslXtreme

Author(s)
McPhee, Malcolm John
Oltjen, Jim
Fadel, James
Mayer, David
Sainz, Roberto
Publication Date
2009
Abstract
The Davis Growth Model (a dynamic steer growth model encompassing 4 fat deposition models) is currently being used by the phenotypic prediction program of the Cooperative Research Centre (CRC) for Beef Genetic Technologies to predict P8 fat (mm) in beef cattle to assist beef producers meet market specifications. The concepts of cellular hyperplasia and hypertrophy are integral components of the Davis Growth Model. The net synthesis of total body fat (kg) is calculated from the net energy available after accounting for energy needs for maintenance and protein synthesis. Total body fat (kg) is then partitioned into 4 fat depots (intermuscular, intramuscular, subcutaneous, and visceral). This paper reports on the parameter estimation and sensitivity analysis of the DNA (deoxyribonucleic acid) logistic growth equations and the fat deposition first-order differential equations in the Davis Growth Model using acslXtreme (Hunstville, AL, USA, Xcellon). The DNA and fat deposition parameter coefficients were found to be important determinants of model function; the DNA parameter coefficients with days on feed >100 days and the fat deposition parameter coefficients for all days on feed. The generalized NL2SOL optimization algorithm had the fastest processing time and the minimum number of objective function evaluations when estimating the 4 fat deposition parameter coefficients with 2 observed values (initial and final fat). The subcutaneous fat parameter coefficient did indicate a metabolic difference for frame sizes. The results look promising and the prototype Davis Growth Model has the potential to assist the beef industry meet market specifications.
Citation
Mathematics and Computers in Simulation, 79(9), p. 2701-2712
ISSN
1872-7166
0378-4754
Link
Language
en
Publisher
Elsevier BV, North-Holland
Title
Parameter estimation and sensitivity analysis of fat deposition models in beef steers using acslXtreme
Type of document
Journal Article
Entity Type
Publication

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