A revised model of energy transactions and body composition in sheep

Abstract

<p>A mechanistic, dynamic model was developed to calculate body composition in growing lambs by calculating heat production (HP) internally from energy transactions within the body. The model has a fat pool (<i>f</i>) and three protein pools: visceral (<i>v</i>), nonvisceral (<i>m</i>), and wool (<i>w</i>). Heat production is calculated as the sum of fasting heat production, heat of product formation (HrE), and heat associated with feeding (HAF). Fasting heat production is represented as a function of visceral and nonvisceral protein mass. Heat associated with feeding (HAF) is calculated as ((1 − <i>k_m</i>) x MEI), where <i>k_m</i> is partial efficiency of ME use for maintenance, and MEI = metabolizable energy intake) applies at all levels above and below maintenance. The value of <i>k_m</i> derived from data where lambs were fed above maintenance was 0.7. Protein change (dp/dt) is the sum of change in the <i>m</i>, <i>v</i>, and <i>w</i> pools, and change in fat is equal to net energy available for gain minus d<i>p</i>/d<i>t</i>. Heat associated with a change in body composition (HrE) is calculated from the change in protein and fat with estimated partial efficiencies of energy use of 0.4 and 0.7 for protein and fat, respectively. The model allows for individuals to gain protein while losing fat or vice versa.</p> <p>When evaluated with independent data, the model performed better than the current Australian feeding standards (Freer et al., 2007) for predicting protein gain in the empty body but did not perform as well as for gain of fat and fleece-free empty body weight. Models performed similarly for predicting clean wool growth. By explicit representation of the major energy using processes in the body, and through simplification of the way body composition is computed in growing animals, the model is more transparent than current feeding systems while achieving similar performance. An advantage of this approach is that the model has the potential for wider applicability across different growth trajectories and can explicitly account for the effects of systematic changes on energy transactions, such as the effects of selective breeding, growth manipulation, or environmental changes.</p>