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A serial slaughter trial was carried out to examine the developmental change of physical and chemical body composition in pigs highly selected for lean content. A total of 48 pigs (17 females and 31 castrated males) were serially slaughtered and chemically analysed. Eight pigs were slaughtered at 20, 30, 60, 90, 120 and 140 kg live weight, (LW) respectively. The carcass was chilled and the left carcass side was dissected into the primal carcass cuts ham, loin, shoulder, belly and neck. Each primal carcass cut was further dissected into lean tissue, bones and rind. Additionally, the physical and chemical body composition was obtained for the total empty body as well as for the three fractions soft tissue, bones and viscera. Viscera included the organs, blood, empty intestinal tract and leaf fat. The relationship between physical or chemical body composition and empty body weight (EBWT) at slaughter was assessed using allometric equations (log10y=log10a+b log10 EBWT). Dressing percentage increased from 69·4 to 85·2% at 20 to 120 kg and then decreased to 83·1% at 140 kg LW, whereas percentage of soft tissue, bones and viscera changed from 23·5 to 33·0%, 10·1 to 6·3% and 14·7 to 10·3%, respectively, during the entire growth period. Substantial changes in proportional weights of carcass cuts on the left carcass side were obtained for loin (10·5 to 17·5%) and belly (11·3 to 13·8%) during growth from 20 to 140 kg. Soft tissue fraction showed an allometric coefficient above 1 ( b=1·14) reflecting higher growth rate in relation to the total empty body. The coefficients for the fractions bones and viscera were substantially below 1 with b=0·77 and 0·79, respectively, indicating substantial lower growth relative to growth of the total empty body. Lean tissue allometric growth rate of different primal cuts ranged from b=1·02 (neck) to 1·28 (belly), whereas rates of components associated with fat tissue growth rate ranged from b=0·62 (rind of belly) to 1·79 (backfat). For organs, allometric growth rate ranged from b=0·61 (liver) to 0·90 (spleen). For the entire empty body, allometric accretion rate was 1·01, 1·75, 1·02 and 0·85 for protein, lipid, ash and water, respectively. Extreme increase in lipid deposition was obtained during growth from 120 to 140 kg growth. This was strongly associated with an increase in backfat and leaf fat in this period. Interestingly, breeds selected for high leanness such as Piétrain sired progeny showed an extreme increase in lipid accretion at a range of LW from 120 to 140 kg, which indicates that selection has only postponed the lipid deposition to an higher weight compared with the normally used final weight of 100 kg on the performance test. The estimates obtained for allometric growth rates of primal carcass cuts, body tissue and chemical body composition can be used to predict changes in weight of carcass cuts, determine selection goals concerning lean tissue growth, food intake capacity, etc. and generally as input parameters for pig growth models that can be used to improve the efficiency of the entire pig production system for pigs highly selected for lean content.
The amount of a bulky food that an animal can eat depends on its capacity for bulk and the bulk content of the food. For pigs between 12 and 40kg the capacity for food bulk was found to be directly proportional to liveweight (Kyriazakis and Emmans, 1995). The way in which the capacity for bulky foods changes with weight above 40 kg is not clear; there is no a priori reason to assume that the scaling rule proposed for young pigs will hold in heavier pigs. The applicability of the work in young pigs for use in more mature pigs needs investigation, to develop predictive equations for the whole relevant weight range. An experiment was designed to determine how the capacity for bulk changed with weight; the objective was to develop a relationship between the capacity for food bulk and liveweight.
We need to improve our understanding of the factors that are important for the control of food intake on high bulk foods. The study of short term feeding behaviour (STFB) may help to do this. The objective of this experiment was to study the effects of giving foods differing in bulk content on the STFB of growing pigs. It was expected that the foods would result in different levels of daily intake and that this would be reflected as differences in STFB between the foods. Two hypotheses were developed based on ideas about the way in which a physical constraint to intake could arise. H1; there would be less diurnal variation in feeding on high bulk foods that limit intake. H2; feeding patterns on bulky foods would be less flexible than those on a control food when feeding time is limited by reducing time of access to the feeder.
A review of work reported in the literature was used to present quantitative descriptions of protein use in the growing pig. These are detailed in the text, which also points to preferred values, and to anomalies and lacunae. The review was prepared with the objective of allowing from its content the inclusive and quantitative modelling of amino acid requirement. Requirement was approached as the sum of the component factors: maintenance and protein retention. Ileal true digestible protein and amino acid requirements are presented in a form consistent with that forwarded for energy. Thus both energy and protein elements can be conceptualized within a single coherent framework. Priority uses for absorbed amino acids were assumed to be (a) to support endogenous protein losses resultant from the passage of food and incomplete re-absorption prior to the terminal ileum, (b) to replace lost hair and skin, and (c) to cover the basic maintenance losses which will occur as a result of minimal protein turn-over even when protein retention is zero. The bulk of the protein requirement was directly linked to the daily rate of protein retention, for which the linear-plateau response was accepted. For determination of the maximum rate of protein retention the Gompertz function was proposed, although the use of a single value throughout the growth period was not dismissed. The balance of amino acids for protein retention is specified as different from that for maintenance. Central to the approach was the proposal that the inefficiency of use of ileal digested ideal protein, even when not supplied in excess, was an expression of protein losses occurring as a result of protein turn-over. The requirement for the satisfaction of the losses from protein turn-over occurring as a consequence of protein retention, and therefore additional to the requirements for maintenance, was identified. Quantification was attempted with sufficient success to warrant its inclusion into requirement estimation. It was concluded that this element addressed previously inadequately explained protein utilization inefficiencies. Algorithms are presented based upon protein turn-over which appear to be consistent with empirical findings.
The objective of this experiment was to provide a severe test of the two frameworks currently available for understanding and predicting voluntary food intake. Framework 1 predicts that an animal will eat at a level that will allow potential performance to be achieved subject to its capacity to deal with a constraint, such as the bulk content of the food, not being exceeded. In framework 2 intake is seen as that which will allow some biological efficiency, such as the ratio of net energy intake per litre of oxygen consumed, to be maximised (Tolkamp and Ketelaars, 1992). The frameworks differ in their prediction of the effect that a period of prior feeding on a high bulk food (severely limiting) will have upon the subsequent intake of foods of differing bulk content. Framework 1 predicts that the intake of a low bulk food, that is non limiting, but not that of a moderate bulk food, that is limiting, will be increased under such circumstances. Framework 2 predicts that intake will be increased regardless of the type of food being fed as long as the Metabolisable Energy of that food is utilised more efficiently.
Currently there are two theoretical frameworks for the prediction of feed intake of animals. The first considers feed intake to be a consequence of the animal eating to achieve its genetic potential (Kyriazakis and Emmans, 1999). When potential performance is not achieved it is because feed intake is being constrained, for example through the bulkiness of the feed or the hotness of the environment. The second framework considers feed intake to be an outcome of some process of optimisation so that intake is that which allows the maximisation of biological efficiency (Tolkamp and Ketelaars, 1992). The two frameworks differ in their predictions of the effect of temperature on the intake of bulky feeds. In the first, feed intake on bulky feeds is seen as a function of the type of feed; in the second, feed intake is a function of both the type of feed and the environment. The first framework predicts that in the cold the intake of low, but not high, bulk feeds will increase. The second framework predicts that in the cold intake will be increased regardless of the type of feed offered. This experiment was designed to provide a severe test of the two feed intake theories.
A dynamic model for simulation of growth in pigs was extended by a module to assess maximum and minimum heat loss (HLcold, HLhot) for a given pig, to compare these figures to heat production (HP), and to take thermoregulatory action when HP < HLcold (cold conditions) or HP > HLhot (hot conditions).
HLcold and HLhot were largely determined according to algorithms obtained from the literature, hut HLcold was made dependent on body fat depth through tissue insulation. Data to establish the relation (Ύ = 0.05 + 0.002 x X) between cold tissue insulation (Ύ in °C.m2 per W) and backfat depth (X in mm) independent of body weight were obtained from the literature. The same data showed that HLhot is not related to backfat depth in pigs.
Cold thermoregulatory action included an increase of ad libitum food intake. Hot thermoregulatory action included reduction of physical activity, increase of body temperature, wetting of a proportion of the skin and reduction of dia libitum food intake.
A sensitivity analysis showed that the model’s output in terms of ãd libitum food intake, HP, protein deposition (Pdep) and lipid deposition (Ldep) is strongly sensitive to the characterization of the genotype being simulated. The model was used to simulate trials from the literature. Although the model does not explicitly calculate lower and upper critical temperatures, these could be adequately predicted from its output. Comparison of model output with experimental data revealed an adequate prediction of ad libitum food intake and of the partitioning of ad libitum ingested metabolizable energy (ME) into HP, Pdep and Ldep in cold, thermoneutral and hot conditions. At restricted ME intake, and especially in cold conditions, the model tends to overestimate HP and underestimate Ldep, probably because it does not take account of long-term acclimatization.
Available technology allows pig breeding companies to automate feed intake recording during performance test. This provides data on ‘average daily feed intake’ as recorded with more traditional manual systems. It also results in feed intake curves, i.e. the relationship between ‘days on test’ and ‘daily feed intake’. This information can be used in different ways. The feed intake curve may be described using sophisticated linear or non-linear models; these may describe the feed intake curve accurately, but model parameters cannot be used easily in genetic/economic evaluation in the context of a breeding programme. A simple method to describe feed intake curves is used in this paper, allowing for easy interpretation of the results. The objective is to study the impact of existing selection procedures on the feed intake curve and the utilisation of variation in its shape in pig breeding.
Performance test data of 1331 boars of a Large White based line, collected from November 1990 to March 1993 were analysed. Boars are tested over a 12 week period, starting at approximately 30 kg. Feed intake data are recorded with the Hunday FIRE system.
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