Characterization of pig genotypes for growth modeling

ABSTRACT The models dealt with herein are driven by descriptors of pig growth potential and environment, predicting growth from their interaction. Growth potential parameters relate to resource intake and partitioning to maintenance, protein (P) deposition (PD), and lipid (L) deposition (LD); these parameters quantify genotype (breed, etc.). Simulation of a pig's growth requires characterization of its potential in terms of the associated model parameters. This requires a set of parameters that fully describe the potential, measurement of resource input, and partitioning in a genotype, and using these measurements to quantify those parameters for that genotype. Resource partitioning is commonly covered by potential PD, required LD, and ME_m. Description of the first two features commonly requires three parameters. The ME_m here is restricted to a neutral environment without functions for coping with stressors, which would require extra parameters. Nutrient intake is best modeled as resulting from nutrient requirements and from constraints to physical uptake, be they external or genetic. Intake and partitioning observations must reflect potential; environmental load must be minimized. Repeatedly measuring whole-body P and L and ad libitum ME intake over a sufficiently wide maturity range (for example from 10 to 175 kg of BW) requires serial slaughter trials with chemical analysis or in vivo techniques such as ultrasound. The latter allow for the description of individual growth patterns and for quantification of variation in addition to mean levels. Parameters can be estimated in three ways. First, P and L observations can be fitted to P and L growth functions. Then, ME_m comes out as the remainder of the ME budget, given valid assumptions about PD and LD efficiency. Second, observed feed intake, growth, and body composition can be fitted to their simulations (parameter calibration, inverted modeling) to avoid P or L measurement. This requires serial data and iteration to match resource requirements to allowance. Third, differential nutrient restriction techniques can be used.

Implications

Simulation of the growth of pigs of a particular genotype with “potential deposition” models requires specification of the model parameters that drive body maintenance and potential growth of body protein and lipid. In stress-free nonlimiting environments this requires four to six parameters: maintenance metabolizable energy requirements, two to four parameters to describe potential protein and lipid growth, and one to describe effective feed intake capacity. These can be estimated by fitting observed body protein and lipid mass to growth functions or by inverted modeling, fitting observed feed intake, growth rate, and body composition to their simulated values by calibrating model parameters. In a stressful or limiting environment, more parameters will be needed to describe the coping strategies of a particular genotype. A model requires functions to deal with such parameters to allow for a proper fit of data measured in such environments and avoid biased estimates of the potential parameters.

Key Words: Genotypes, Growth, Models, Pigs

© 2003, by the American Society of Animal Science. All rights reserved.

J. Anim. Sci. 2003. 81(E. Suppl. 2):E187-E195