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Parameter estimation and sensitivity analysis of fat deposition models in beef steers using acslXtreme
Authors:Malcolm McPhee  Jim Oltjen  James Fadel  David Mayer  Roberto Sainz
Affiliation:1. Cooperative Research Centre for Beef Genetic Technologies, Armidale, NSW 2351, Australia;2. NSW Department of Primary Industries Beef Industry Centre of Excellence, UNE, NSW 2351, Australia;3. Department of Animal Science, University of California, Davis, CA 95616, USA;4. Department of Primary Industries & Fisheries, Yeerongpilly, Qld 4105, Australia
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.
Keywords:Cattle  Fat deposition  Parameter estimation  Sensitivity analysis
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