Conventional models of energy utilization by animals, based on partitioning metabolizable energy (ME) intake or net energy (NE), are reviewed. The limitations of these methods are discussed, including various experimental, analytical and conceptual problems. Variation in the marginal efficiency of utilizing energy can be attributed to various factors: diet nutrient composition; animal effects on diet ME content; diet and animal effects on ME for maintenance (MEm); experimental methodology; and important statistical issues. ME partitioning can account for some of the variation due to animal factors, but not that related to nutrient source. In addition to many of the problems associated with ME, problems with NE pertain to: estimation of NE for maintenance (NEm); experimental and analytical methodology; and an inability to reflect variation in the metabolic use of NE. A conceptual framework is described for a new model of energy utilization by animals, based on representing explicit flows of the main nutrients and the important biochemical and biological transformations associated with their utilization. Differences in energetic efficiency from either dietary or animal factors can be predicted with this model.
Modelling: Energy utilization: Nutrient flow representationMathematical models can integrate theories and observations into a coherent framework that can be useful for both conceptual and computational purposes. Animal models have been developed for a variety of species and applications: pig growth (Whittemore & Fawcett, 1976;Black et al. 1986; Moughan et al. 1987;Pomar et al. 1991a; Technisch Model Varkensvoeding, 1991); reproducing sows (Pomar et al. 1991b;Pettigrew et al. 1992); poultry production (Zoons et al. 1991;Hruby et al. 1994); growing sheep (Gill et al. 1984); growing fish (Machiels & Henken, 1986;; growing and reproducing beef cattle (Buchanan-Smith & Fox, 2000); and dairy cattle (Baldwin et al. 1987). Some of these models are based exclusively on empirical observations, such as direct relationships between daily lysine and energy intake, and average daily gain and backfat thickness in growing pigs, established using multiple linear regression (Carr et al. 1979). Application of such empirical models is limited to animal, environmental, and management conditions similar to those used in the trials on which they are based. Furthermore, this approach to representing animal production offers little insight into the mechanistic biological principles of which the measured performance is a consequence.In contrast to the empirical approach, highly complex mechanistic biochemical models have been developed to simulate nutrient metabolism at the level of individual tissues, using differential equations to represent (noncausally) relationships between the various metabolite flow rates. These mechanistic models are most useful for demonstrating biological and biochemical principles, especially at the cellular and inter-cellular levels. Wholeanimal models of this type have been developed, for example in mon...