Architecture of a harmonized model of the growing pig for the determination of dietary net energy and protein requirements and of excretions into the environment (IMS Pig)

Abstract

The model incorporates, amongst its novel components, variable efficiency coefficients in the simulation of the responses of growing pigs to nutrient inputs, and thereby increases the accuracy and efficacy of control of feeding and nitrate excretion. The model determines (rather than is presented with) net energy and required amino acid level and balance. The estimation of protein turn-over as a function of rate of protein retention, protein mass and the maturity of the pig was found to be central to both the energy (ATP) and protein economy. Protein turn-over varied from around 0·14 to 0·08 of the protein mass depending upon the size of the pig. Efficiencies of energy yield from lipid, starch (and sugar), protein and (fibre-derived) volatile fatty acids were calculated to be 0·98, 0·86, 0·56 and 0·58 for ATP production and 0·90, 0·70, 0·50, and 0·44 for lipid retention, respectively. The maximum efficiency of use of ileal digestible amino acids was determined as around 0·85. The energy cost of protein synthesis was equivalent to 4·2 MJ metabolizable energy (ME) per kg, and the efficiency of use of ME for protein retention varied from 0·55 to 0·40 depending on the protein mass of the pig. The components of the model and the biochemical drivers are described in detail, and proof of principle of the main elements is presented. The model is different in its architecture to other published simulation models, and is considered to add to the present knowledge base in this discipline.

Effects of feeding levels on growth performance, feed utilization, body composition and apparent digestibility coefficients of nutrients for juvenile Chinese sucker,Myxocyprinus asiaticus

“…Quantitative information on rates of nutrient deposition has found several applications in animal nutrition. Assessing rates of nutrient deposition, mostly PD and LD, represent a comprehensive way of examining efficiency of utilization of feed components for growth, effects of genetics, nutrition and environment on the composition of the growth response, dietary requirements, and waste outputs from farmed animals (Black, Davies, Bray, Giles & Chapple 1995; Schinckel & de Lange 1996; Green & Whittemore 2003). Because growth and PD are associated, amino acid profile of deposited protein can serve in approximating amino acid requirements of growing animals (Möhn & de Lange 1998).…”

Development of sustainable precision farming systems for swine: Estimating real-time individual amino acid requirements in growing-finishing pigs

“…However, these methods are deterministic as they do not consider inter-or intraanimal variability (Pomar et al, 2009). Because of the complexity of animal responses and the many factors modulating these responses, mathematical models are proposed to simulate growth and estimate nutrient requirements of animals (Green and Whittemore, 2003;van Milgen et al, 2008). These models must be properly calibrated in relation to a reference population to ensure that the concentration of nutrients that will optimize animal responses are accurately estimated.…”

Partitioning of limiting protein and energy in the growing pig: testing quantitative rules against experimental data

“…However, it was recognised that the value could be lower (Whittemore, 1995). Green & Whittemore (2003) state that the value of (L:P) min is likely to be dependent on genotype, but did not give the values. Green & Whittemore (2003) also have an absolute minimum fatness defined as 0•05W.…”

“…Green & Whittemore (2003) state that the value of (L:P) min is likely to be dependent on genotype, but did not give the values. Green & Whittemore (2003) also have an absolute minimum fatness defined as 0•05W. Wellock et al (2003a) stated 'that an animal cannot lose lipid that is not present, and must have some minimum lipid content (L min ) necessary for survival'.…”