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...
Factorial approaches to estimate energy requirements of growing pigs require estimation of maintenance energy requirements. Heat production (HP) during fasting (FHP) may provide an estimate of maintenance energy requirements. Six barrows were used to determine effects of feeding level on components of HP, including extrapolated plateau HP following a 24 h fast (FHPp). Based on a cross-over design, each pig was exposed to three feeding levels (1·55, 2·05 and 2·54 MJ metabolisable energy/kg body weight (BW) 0·60 per d) between 30 and 90 kg BW. Following a 14 d adaptation period, HP was estimated using indirect calorimetry on pigs housed individually. Dynamics of HP were recorded in pigs for 5 d during the fed state and during a subsequent 24 h fast. Metabolisable energy intake was partitioned between thermal effect of feeding (HPf), activity HP (HPa), FHPp and energy retention. Feeding level influenced (P,0·05) total HP during the fed state, HPf and activity-free FHPp (609, 644 and 729 (SE 31) kJ/kg BW 0·60 per d for low, medium and high ME intakes, respectively). The value of FHPp when expressed per kg BW 0·60 did not differ (P¼ 0·34) between the three subsequent experimental periods. Feeding level did not (P¼ 0·75) influence HPa. Regression of total HP during the fed state to zero metabolisable energy intake yielded a value of 489 (SE 69) kJ/kg BW 0·60 per d, which is a lower estimate of maintenance energy requirement than FHPp. Duration of adaptation of pigs to changes in feeding level and calculation methods should be considered when measuring or estimating FHPp, maintenance energy requirements and diet net energy content.
A computational framework to represent nutrient utilization for body protein and lipid accretion by growing monogastric animals is presented. Nutrient and metabolite flows, and the biochemical and biological processes which transform these, are explicitly represented. A minimal set of calibration parameters is determined to provide five degrees of freedom in the adjustment of the marginal input -output response of this nutritional process model for a particular (monogastric) animal species. These parameters reflect the energy requirements to support the main biological processes: nutrient intake, faecal and urinary excretion, and production in terms of protein and lipid accretion. Complete computational details are developed and presented for these five nutritional processes, as well as a representation of the main biochemical transformations in the metabolic processing of nutrient intake. Absolute model response is determined as the residual nutrient requirements for basal processes. This model can be used to improve the accuracy of predicting the energetic efficiency of utilizing nutrient intake, as this is affected by independent diet and metabolic effects. Model outputs may be used to generate mechanistically predicted values for the net energy of a diet at particular defined metabolic states. Modelling: Nutrient flows: Monogastric animals
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