Evaluation of the potential growth and body composition of the Cobb 700 genotype.

1. The potential growth of the chemical and physical components of males and females of the Cobb 700 strain was measured from hatch to 15 weeks of age.2. A four-phase ad libitum feeding programme was used to feed 200 chicks of each sex. All birds were weighed weekly. Ten birds per sex were sampled at 0, 7, 14, 28, 42, 56, 70, 84 and 105 d of age. They were weighed before and after plucking to determine the weight of feathers. Physical parts were measured on defeathered birds, whereafter these components were combined, minced, freeze dried to measure water content, and then analysed for protein, lipid and ash content.3. Mature body weights of males and females averaged 8.38 and 6.94 kg, respectively, mature body protein weights averaged 1.48 and 1.19 kg and mature body lipid contents averaged 1.08 and 1.54 kg, respectively.4. Rates of maturing of the empty feather-free body weights of males and females averaged 0.0417 and 0.0402/d, respectively. All chemical and physical components within a sex, other than feathers, had the same rate of maturing. The rate of maturing of feathers, calculated by iteration, in males was lower than in females (0.0324 vs. 0.0357/d) and the mature weight was higher (435 vs. 372 g).5. The ratios of the chemical components to feather-free body protein at maturity for males and females were, for water, 3.80 and 3.34; for lipid, 0.73 and 1.29; and for ash, 0.13 and 0.19, respectively. Separate equations were required for males and females to describe the allometric relationship between lipid and protein in the feather-free body.6. Mature body weights of broilers in this trial were considerably higher than those measured using the same protocol 28 years ago, whereas rates of maturing have remained the same.

The potential post-hatching growth of domestic birds is sufficiently described by the Gompertz function.

1. It has been hypothesised that, for post-hatching domestic birds reared under good conditions, the relative growth rate R = (dW/dt)/W = dlnW/dt is a linear function of lnW; W is body weight. It followed that dW/dt = B.W. ln(A/W), where A is mature weight, and, by integration, that weight over time is described by a Gompertz function: Wt = A.exp.(-exp(-(G0 - B.t)), where Wt is weight at time t d, B is the rate parameter d-1, and G0 = -ln(-ln(W0/A)).2. Where growth data published in the literature did not show this relationship, it was likely to have been caused by sub-optimal conditions for maximum growth, such as inadequate nutrition or other factors.3. Published data, which have been diligently examined from both sexes and nine species, over 400-fold range of degree of maturity, collected over nearly a century of data from four continents, strongly corroborated the hypothesis.4. The data were not in agreement with another functions using three parameters and made functions with four or more parameters superfluous. The relationship between R and lnW should be carefully examined before subjecting any data set to further analysis.

Index selection in terminal sires improves early lamb growth.

The use of terminal sires (TS) for crossbreeding is integral to the UK sheep industry where approximately 71% of market lambs are sired by TS rams. Early growth of these crossbred lambs affects profitability. The objectives of this study were i) to evaluate the effectiveness of index selection among TS on BW and ADG of their crossbred offspring; and ii) to compare the efficacy of that selection within TS breeds. The most widely used TS breeds in the United Kingdom are Charollais, Suffolk, and Texel. These participated in sire referencing schemes in which they were evaluated on a lean growth index designed to increase carcass lean weight at a given age. From 1999 to 2002, approximately 15 high and 15 low lean growth index rams per breed (93 in total, differing in index on average by 4.6 SD) were selected from within their sire referencing schemes and mated to Welsh and Scottish Mule ewes. Their crossbred offspring were reared commercially on 3 experimental farms in England, Scotland, and Wales. A total of 6,515 lambs were born between 2000 and 2003. Lambs were weighed at birth (BWT), 5 wk (5WT), and 10 wk (10WT), and their ADG from birth to 10 wk was calculated. Lambs sired by high index rams were on average, across breeds, heavier at all ages (P < 0.01) with 0.07 ± 0.03, 0.3 ± 0.1, and 0.4 ± 0.1 kg greater BWT, 5WT, and 10WT, respectively. Their ADG was 5.1 ± 1.9 g/d greater than low-index-sired lambs (P < 0.01). Suffolk-sired lambs were on average heavier at all ages, with greater ADG, whereas Charollais-sired lambs were lightest with smallest ADG. Overall, there was no significant interaction between sire index and sire breed (P > 0.10). Within Suffolk-sired lambs, there was little difference between high and low index sires for the traits studied (P > 0.3). High and low index Charollais-sired lambs differed in BWT (0.09 ± 0.04 kg) and 5WT (0.3 ± 0.1 kg), and Texel-sired lambs differed in 5WT (0.5 ± 0.1 kg), 10WT (0.9 ± 0.2 kg), and ADG (10.2 ± 3.3 g/d; P < 0.01). Lambs from Scottish Mule dams were heavier, with greater ADG, than lambs born to Welsh Mules (P < 0.01). Lambs reared in Scotland were heavier at all ages (P < 0.01). The results suggest that using index selection in TS can improve the growth of their commercial offspring reared on grass.

Feed intake of sheep as affected by body weight, breed, sex, and feed composition.

The hypotheses tested were that genetic size-scaling for mature BW (A, kg) would reduce variation in intake between kinds of sheep and that quadratic polynomials on u = BW/A with zero intercept would provide good descriptions of the relationship between scaled intake (SI, g/A(0.73) d) and degree of maturity in BW (u) across feeds of differing quality. Both sexes of Suffolk sheep from 2 experimental lines (n = 225) and from 3 breed types (Suffolk, Scottish Blackface, and their cross; n = 149) were recorded weekly for ad libitum feed intake and BW; recording of intake was from weaning through, in some cases, near maturity. Six diets of different quality were fed ad libitum. The relationship between intake and BW on a given feed varied considerably between kinds of sheep. Much, but not all, of that variation was removed by genetic size-scaling. In males, the maximum value of SI was greater than in females (P = 0.07) and was greater in Suffolk than in Scottish Blackface, with the cross intermediate (P = 0.025); there was no difference between the 2 Suffolk lines used (P = 0.106). The quadratic polynomial model, through the origin, was compared with a split-line (spline) regression for describing how SI varied with u. For the spline model, the intercept was not different from zero in any case (P > 0.05). The values of u at which SI achieved its maximum value (u* and SI*) were calculated. Both models fit the data well; the quadratic was preferred because it predicted that SI* would be achieved within the range of the long-run data, as was observed. On a high quality feed, for the spline regression, u* varied little around 0.434 (SD = 0.020) for the 10 different kinds of sheep used. For the quadratic, the mean value of 0.643 (SD = 0.066) was more variable, but there were no consistent effects of kind of sheep. The values of u* and SI* estimated using the quadratic model varied among the 6 feeds: 0.643 and 78.5 on high quality; 0.760 and 79.6 on medium protein content; 0.859 and 73.3 on low protein content; 0.756 and 112 on a low energy content feed; 0.937 and 107 on ryegrass; and 1 (forced, as the fitted value of 1.11 was infeasible) and 135 on Lucerne. The value of u* tended to increase as feed digestibility decreased. We conclude that genetic size-scaling of intake is useful and that a quadratic polynomial with zero intercept provides a good description of the relationship between SI and u for different kinds of sheep on feeds of different quality. Up to u congruent with 0.45, intake was directly proportional to BW.

Predicting tissue distribution and partitioning in terminal sire sheep using x-ray computed tomography.

The utility of x-ray computed tomography (CT) scanning in predicting carcass tissue distribution and fat partitioning in vivo in terminal sire sheep was examined using data from 160 lambs representing combinations of 3 breeds (Charollais, Suffolk, and Texel), 3 genetic lines, and both sexes. One-fifth of the lambs were slaughtered at each of 14, 18, and 22 wk of age, and the remaining two-fifths at 26 wk of age. The left side of each carcass was dissected into 8 joints with each joint dissected into fat (intermuscular and subcutaneous), lean, and bone. Chemical fat content of the LM was measured. Tissue distribution was described by proportions of total carcass tissue and lean weight contained within the leg, loin, and shoulder regions of the carcass and within the higher-priced joints. Fat partitioning variables included proportion of total carcass fat contained in the subcutaneous depot and intramuscular fat content of the LM. Before slaughter, all lambs were CT scanned at 7 anatomical positions (ischium, midshaft of femur, hip, second and fifth lumbar vertebrae, sixth and eighth thoracic vertebrae). Areas of fat, lean, and bone (mm(2)) and average fat and lean density (Hounsfield units) were measured from each cross-sectional scan. Areas of intermuscular and subcutaneous fat were measured on 2 scans (ischium and eighth thoracic vertebra). Intramuscular fat content was predicted with moderate accuracy (R(2) = 56.6) using information from only 2 CT scans. Four measures of carcass tissue distribution were predicted with moderate to high accuracy: the proportion of total carcass (R(2) = 54.7) and lean (R(2) = 46.2) weight contained in the higher-priced joints and the proportion of total carcass (R(2) = 77.7) and lean (R(2) = 55.0) weight in the leg region. Including BW in the predictions did not improve their accuracy (P > 0.05). Although breed-line-sex combination significantly affected fit of the regression for some tissue distribution variables, the values predicted were changed only trivially. Within terminal sire type animals, using a common set of prediction equations is justified. Tissue distribution and fat partitioning affect eating satisfaction and efficiency of production and processing; therefore, including such carcass quality measures in selection programs is increasingly important, and CT scanning appears to provide opportunities to do so.

The effects of pathogen challenges on the performance of naïve and immune animals: the problem of prediction.

Predictive frameworks for performance under both physical and social stressors are available, but no general framework yet exists for predicting the performance of animals exposed to pathogens. The aim of this paper was to identify the key problems that would need to be solved to achieve this. Challenges of a range of hosts by a range of pathogens were reviewed to consider reductions in growth beyond those associated with reductions in voluntary food intake (VFI). Pair-feeding and marginal response studies identified the extent and mechanisms of how further reductions in growth occur beyond those caused by reduced VFI. Further reductions in growth depended on the pathogen, the host and the dose and were time dependent. In some instances the reduction in VFI fully explained the reduction in growth. Marginal response experiments showed increased maintenance requirements during exposure to pathogens, but these were different for specific amino acids. There were no clear effects on marginal efficiency. Innate immune functions, repair of damaged tissue and expression of acquired immunity caused significant but variable increases in protein (amino acid) requirements. More resistant genotypes had greater requirements for mounting immune responses. The partitioning of protein (amino acids) was found to be different during pathogen challenges. Prediction of the requirements and partitioning of amino acids between growth and immune functions appears to be a crucial problem to solve in order to predict performance during pathogen challenges of different kinds and doses. The problems of accounting for reductions in performance during pathogen challenges that are described here provide a useful starting point for future modelling and experimental solutions.

Genetic selection, sex and feeding treatment affect the whole-body chemical composition of sheep.

Hypotheses on total body chemical composition were tested using data from 350 Suffolk sheep grown to a wide range of live weights, and fed in a non-limiting way, or with reduced amounts of feed, or ad libitum on feeds of reduced protein content. The sheep were from an experiment where selection used an index designed to increase the lean deposition rate while restricting the fat deposition rate. Ultrasound muscle and fat depths were the only composition measurements in the index. The animals were males and females from a selection (S) line and its unselected control (C). The protein content of the lipid-free dry matter was unaffected by live weight, sex or feeding treatment with only a very small effect of genetic line (0.762 kg/kg in S and 0.753 kg/kg in C; P < 0.05). The form of the relationship between water and protein was not affected by any of the factors; in the different kinds of sheep it was consistent with no effect other than through differences in mature protein weight. The water : protein ratio at maturity was estimated as 3.45. Over the whole dataset, lipid weight (L) increased with protein weight (P) according to L = 0.3135 × P1.850. Allowing for this scaling, fatness increased on low-protein feeds, was greater in females than in males and in C than in S (P < 0.001). Lipid content (g/kg fleece-free empty body weight) was reduced by restricted feeding only in males at the highest slaughter weight (114 kg). The lines differed in lipid content (P < 0.001) with means of 265.1 g/kg for C and 237.3 g/kg for S. Importantly, there was no interaction between line and feeding treatments. A higher proportion of total body protein was in the carcass in S than in C (0.627 v. 0.610; P < 0.001). For lipid, the difference was reversed (0.736 v. 0.744; P < 0.05). The total energy content increased quadratically with slaughter weight. At a particular weight, the energy content of gain was higher in females than in males and in C than in S. Genetic selection affected body composition at a weight favouring the distribution of protein to the carcass and lipid to the non-carcass. Once allowing for effects of genetic selection, sex and feeding treatment on fatness, simple rules can be used to generate the chemical composition of sheep.

Body fatness affects feed intake of sheep at a given body weight.

In a 1-yr experiment, nutritional treatments were used to produce different combinations of BW and BCS in lambs. The experiment served to quantify the effects of BW and BCS on ADFI by sheep. Ewe lambs (n = 78) were assigned to treatment groups that had ad libitum access to one feed at a time. Three feeds were used: a medium-quality chopped hay (L), a pelleted feed based on oat feed (M), and a pelleted feed based on barley (H). Three groups received only one of these feeds throughout. Two groups first received H and then were switched to M when they reached a BW of 45 or 65 kg. Two groups first received L and then were switched to M or H after reaching a BW of 45 kg. Three groups first received H or M but were switched to L after reaching a BW of 45, 65, or 95 kg. Daily feed intake, BW, and BCS were recorded, and ME content of the feeds was estimated in a separate digestibility experiment. The lambs consuming M ate more (P < 0.001) feed than lambs consuming H, but this had no significant effects on ME intake or gain in BW or BCS. Animals that had had access to L were lean for their BW when switched to H or M and showed compensatory intake and gain. Animals switched from M or H to L all lost BCS; BW change depended on the BW at the switch. The treatments produced different combinations of BW and BCS for animals with access to the same feed. The ADFI of a given feed varied systematically with BCS for animals of a given BW. The model ADFI = a x BW x [1 - (b x BCS)] gave a reasonable description of the data in all treatments. A model using BW, BCS, and their interaction gave a slightly better fit but explained little more of the variation in ADFI than the simpler model. The implications of the collected data are that BW alone is an insufficient descriptor of the animal to correctly predict feed intake and that intake predictions can be improved by taking BCS into account.

A model for predicting feed intake of growing animals during exposure to pathogens.

A general model is proposed for predicting the effects of subclinical pathogen challenges of different doses and virulence on the relative feed intake (RFI) of animals. The RFI is defined as the feed intake (FI, kg/d) of the animal challenged by a pathogen divided by its FI in the same state had it not been challenged. Actual FI can be predicted from the RFI and the animal's state. The RFI was assumed to be affected only when animals were naïve to a particular pathogen (i.e., had not previously experienced it) and when the challenge dose was above a predetermined threshold. The model is for the period from recognition of a pathogen through acquisition and subsequent expression of immunity. The way in which RFI changes with time is described by 5 main parameters and is based on data for RFI during different pathogen challenges of a range of hosts. Lag time (L, d) is the delay from a pathogen challenge until any effects on RFI are seen. Reduction time (R, d) describes the time it takes for the lowest value of RFI (lambda) to be achieved. The duration time (D, d) describes the time that lambda is maintained for, and rho (RFI/d) describes the rate of recovery of RFI until RFI = 1. There is no compensatory intake, and RFI is always < or = 1. The effects of host resistance on the values of the model parameters are proposed. Attempts were made to parameterize the model; when data were scarce, initial parameter values were derived on conceptual grounds. Predictions of the effects of pathogen dose, virulence, and host resistance are described and discussed. When comparing the responses in RFI for different genotypes, it is crucial to define the pathogen challenge (in terms of dose and virulence) and the degree of resistance of different hosts. Possible interactions between dose, virulence, and resistance were explored. Feed intake of healthy and challenged animals, at a time, may be different once the challenged animal has recovered (RFI = 1). The issue of reductions in FI during pathogen challenges is important for nutritionist and animal breeders. The large variation that has been observed for reductions in FI during pathogen challenges may be a viable point of selection. The points highlighted will aid selection strategies by quantifying the effects of pathogen dose and virulence, and time, on the FI of challenged animals. The proposed model may be integrated with other models of growth to predict animal performance during exposure to pathogens.

Modeling the effects of stressors on the performance of populations of pigs.

A simulation model that predicts the effect of the social, physical, and nutritional environments on pig food intake and performance was extended to deal with individual variation. The aim was to investigate the effect of between-animal variation on the performance of a population of growing pigs. Variation was generated in initial state, growth potential, and ability to cope when exposed to social "stressors" (EX). Variation in initial state is described by initial body weight (BW0), from which the chemical composition of the pig is calculated. Variation in growth potential is described by creating variation in the genetic growth descriptors. Variation in EX exists between genotypes, where it has been suggested that leaner, more modern genotype pigs tend to be less able to cope. It is expected that within a population or group that the social environment (i.e., position within the social hierarchy) also affects an individual's ability to cope. In the model, it is assumed that the larger, more dominant individuals are better able to cope when exposed to social stressors. Consequently, within a population, EX is correlated with body weight around the genotype mean. Model predictions showed that increasing the variation in BW0 and EX increased the variation in pig performance. This is an important practical consideration in commercial pig production, where the heterogeneity of the population at slaughter may affect the profitability of an enterprise. The way a stressor constrains performance determines whether the mean population response to a given stressor is the same as the average individual response. If all pigs in a group are affected at the same stressor intensity (e.g., all are either mixed or not), then the predicted average individual and mean population responses will be the same. If, however, the intensity of stressor at which performance becomes limiting differs between individuals (such as space allowance or temperature), differences between the individual and mean population responses will be predicted. Variation in the growth response of a population was determined to a greater extent by variation in EX and BW0 than by variation in growth potential, when pigs were housed in simulated conditions likely to be encountered in commercial environments. Consequently, decreasing the variation in initial body weight and improving ability of pigs to cope may be a better way of improving pig performance than selecting only for increased growth potential.

Prediction of body lipid change in pregnancy and lactation.

A simple method to predict the genetically driven pattern of body lipid change through pregnancy and lactation in dairy cattle is proposed. The rationale and evidence for genetically driven body lipid change have their basis in evolutionary considerations and in the homeorhetic changes in lipid metabolism through the reproductive cycle. The inputs required to predict body lipid change are body lipid mass at calving (kg) and the date of conception (days in milk). Body lipid mass can be derived from body condition score and live weight. A key assumption is that there is a linear rate of change of the rate of body lipid change (dL/dt) between calving and a genetically determined time in lactation (T') at which a particular level of body lipid (L') is sought. A second assumption is that there is a linear rate of change of the rate of body lipid change (dL/dt) between T' and the next calving. The resulting model was evaluated using 2 sets of data. The first was from Holstein cows with 3 different levels of body fatness at calving. The second was from Jersey cows in first, second, and third parity. The model was found to reproduce the observed patterns of change in body lipid reserves through lactation in both data sets. The average error of prediction was low, less than the variation normally associated with the recording of condition score, and was similar for the 2 data sets. When the model was applied using the initially suggested parameter values derived from the literature the average error of prediction was 0.185 units of condition score (+/- 0.086 SD). After minor adjustments to the parameter values, the average error of prediction was 0.118 units of condition score (+/- 0.070 SD). The assumptions on which the model is based were sufficient to predict the changes in body lipid of both Holstein and Jersey cows under different nutritional conditions and parities. Thus, the model presented here shows that it is possible to predict genetically driven curves of body lipid change through lactation in a simple way that requires few parameters and inputs that can be derived in practice. It is expected that prediction of the cow's energy requirements can be substantially improved, particularly in early lactation, by incorporating a genetically driven body energy mobilization.

Predicting the consequences of social stressors on pig food intake and performance.

The influence of social stressors on pig performance, although undeniable, is frequently underestimated, and in pig growth modeling is generally ignored. The aims here were to quantify the effects of the main social stressors (i.e., group size, space allowance, feeder space allowance, and mixing) on the performance of growing pigs and to incorporate these relationships into a general growth simulation model. Effects of the individual stressors were described by conceptual equations derived on biological grounds. Parameter values were estimated from experimental data, while taking steps to avoid the problems of using a strictly empirical approach. It was assumed that social stress decreases the capacity of the animal to attain its potential. This is equivalent to lowering the maximum rate of daily gain (ADGp, kg/d). Because it is generally assumed that animals eat to attain their potential, a decrease in ADGp necessarily leads to a decrease in intake. Genetic variation among genotypes in their ability to cope with social stressors was accounted for by introducing an extra genetic parameter (EX) into the model. The value of EX adjusts both the intensity of stressor at which the animal becomes effectively stressed and the extent to which stress decreases performance and increases energy expenditure at a given stressor intensity. Rather than using an empirical adjustment to predict values for the model output variables, such as intake and gain, the chosen functional forms were integrated into a general growth model as mechanistic equations. This allowed the effects of interactions that exist between social stressors and the other variables, such as the genotype, feed composition, and environment on pig intake and growth, to be explored and, at least in principle, predicted. The adapted model is able to predict the performance of pigs differing in both the potential and ability to cope with environmental stressors when raised under given dietary, physical, and social environmental conditions. The social stressor equations developed here can be incorporated into other pig growth simulation models.

Responses of broiler chickens to dietary protein: effects of early life protein nutrition on later responses.

1. A study was conducted with modern broiler chicks to test the effects of early life protein nutrition and sex on responses in growth and body composition to dietary protein at a later age. Effects on the incidence of metabolic disorders were also evaluated. 2. From 11 to 26 d of age (EXP1), birds were given 8 diets varying in balanced protein to energy ratio (BPE ratio) between 0.575 and 1.100 g digestible lysine per MJ AMEn. Birds from two treatment groups in EXP1 (BPE ratio of 0.725 and 1.025 g/MJ, respectively) were subsequently used in a test from 26 to 41 d of age (EXP2). In EXP2, 8 diets were used, varying in BPE ratio between 0.500 and 1.025 g/MJ. 3. Responses in weight gain and feed conversion to BPE ratio in EXP2 changed considerably when BPE ratio in EXP1 was modified, irrespective of sex. Up to 10% improvement in both weight gain and feed conversion in EXP2 was observed if BPE ratio in EXP1 was 0.725 compared with 1.025 g/MJ. With males, however, the effect of treatment in EXP1 on weight gain in EXP2 was present only at high BPE ratios. 4. For the relative gain of breast meat and abdominal fat, but not for carcase, the responses of male broilers to BPE ratio in EXP2 were altered by the BPE ratio in EXP1. With females, responses in composition of the gain to diet in EXP2 were independent of BPE ratio in EXP1. 5. The incidence of metabolic disorders was low, irrespective of treatment in EXP1. The lower BPE ratio in EXP1 increased mortality in EXP2 from 0.8 to 3.6%. 6. Our findings show that broiler responses to dietary protein depend on previous protein nutrition and sex. Effects of early life protein nutrition on incidence of metabolic disorders were not observed. The results strongly suggest that protein levels in grower and finisher diets should not be optimised independently, but simultaneously.

The way in which the data are combined affects the interpretation of short-term feeding behavior.

Short-term feeding behavior of pigs has been analyzed using random process models and log-normal models. Both were successful despite very different underlying assumptions relating to the theory of control. Feeder visits of growing pigs, housed individually from 17 to 52 kg live weight, were recorded electronically over a continuous period of 35 days. For the combined data, intervals between visits to the feeder greater than 30 min could be described well by the negative exponential model. The starting probability of a visit was constant at around 0.3, suggesting randomness. Disaggregating the data for individual pigs or for individual weeks did not change this conclusion. Intervals in the day were of a different nature to those at night, and disaggregation of the data into these two periods revealed that the negative exponential model was not satisfactory for either period. The starting probability for both periods increased with time since the last visit. This is consistent with the idea of satiety. Therefore, the apparent randomness in the data pooled across the day and night is an artefact caused by pooling itself, and is not in conflict with the satiety concept. The implications of data handling are discussed with reference to studies of the physiological control of food intake.

Analysis of the feeding behavior of pigs using different models.

Short-term feeding behavior is conventionally analysed using random process models. The assumption underlying these models have recently been questioned and this article describes the application of both random, and more biologically based, models to the feeding behavior of pigs. Feeder visits of 16 growing pigs, housed individually from 17 to 52 kg live weight, were recorded electronically over a continuous period of 35 days. Daily food intake increased linearly with time, but there was considerable individuality in the degree of order. Pigs made between 18.8 and 80.3 (mean 47.9) daily visits to the feeder. Intervals between visits could be described by two log-normal distributions. Two Gaussian density functions were fitted to the distribution of the log-transformed intervals. For the combined data from all animals the within- and between-meal intervals were 11.2 s and 100.1 min, respectively. A model with three Gaussian functions gave an improved fit to the interval distribution. The within and between meal intervals were then estimated to be 4.2 s and 93.9 min, respectively. The middle distribution of intervals ranged from 0.5 to 38.1 min. The intervals were also described by random process models; again, a three-process model gave an improved fit compared to a two-process model. The mean estimated number of meals per day from the three Gaussian model was 14.3, and from the three process random model, 16.3. A biological interpretation of the three types of interval suggests that: (1) pigs eat in meals separated by long intervals; (2) meals consist of clusters of eating bouts separated by shorter intervals, sometimes associated with drinking; (3) within each eating bout short intervals occur as pigs constantly move in and out of the feeder. It remains unclear what underlies the observed patterns of eating.

A model to predict water intake of a pig growing in a known environment on a known diet.

A model to predict voluntary water intake (WI) of a pig fed a known diet in a known environment is described. The daily retentions of protein, lipid, water and ash were estimated over time using a published pig growth model. Food intakes were estimated using published methods. WI was estimated by adding the amounts required for digestion (WD), faecal excretion (Wfec), growth (WG), evaporation (WE), urinary excretion (WU) and by then subtracting the water arising from feed (WF), from nutrient oxidation (WO) and synthesis of body constituents (WS). WD was predicted assuming an absorption of water of 0.10, 0.16 and 0.07 kg/kg digestible carbohydrate, crude protein and lipid respectively. Wfec was estimated taking into account the water associated with the undigested protein (0.86 kg/kg), diethyl ether extract (-12.11 kg/kg), crude fibre (1.86 kg/kg), ash (-0.42 kg/kg) and N-free extract (4.4 kg/kg). The basal level of WE was estimated from the heat production of the pig fed ad libitum (MJ/d) as: 0.25 x (metabolizable energy - energy retained as protein and lipid) x 0.4, where 0.25 is the assumed proportion of the insensible heat loss at the comfort temperature and 0.4 is the water lost per MJ dissipated heat. WE in a hot environment was predicted by assuming that evaporation increased up to three times the basal level to offset the decreased sensible heat loss. To predict WU a water requirement for renal excretion of 2.05 and 3.40 kg/osmol excreted N as urea and minerals respectively was assumed. The urinary load of N and minerals was predicted from the intake of digestible nutrients and their retention. From the oxidation of 1 kg carbohydrate, protein, and fat it was assumed that 0.6, 0.42 and 1.07 kg water (WO) were released respectively. WS was predicted by assuming a release of 0.16, 0.07 and 0.57 kg water per kg retained protein, retained lipid coming from digestible lipid, and retained lipid coming from digestible carbohydrate respectively. The model is strongly rooted in a theoretical structure. When its predictions were compared with data from suitable experiments, the results were not significantly different. Both the pattern and the magnitude of responses of the model to changes in body weight, feed intake and environmental temperature are sensible and it allows a fuller prediction of voluntary water intake than the methods currently available.

Evaluation of the parameters needed to describe the overall growth, the chemical growth, and the growth of feathers and breast muscles of broilers.

An experiment was carried out to collect data suitable for testing methods used to describe the potential growth and body composition curves of broilers. Males and females of two commercial broiler strain-crosses were grown to 16 wk of age with birds taken at 0, 2, 4, 6, 8, 12, and 16 wk of age for chemical analysis and for the measurement of feather weight and breast meat (Pectoralis major and Pectoralis minor) weight at these ages. The data were used to test the Gompertz growth equation and the assumption of chemical allometry, as well as to estimate the values of the growth parameters for the different genotypes. Feeding and environmental conditions were intended to be such that potential growth and body composition could be attained. The weights of the chemical components for each of the four genotypes were described in terms of the mature weight of these components, their rates of maturing, and the time taken to reach the maximum rate of growth of each component. Allometric relationships between the weights of the chemical components and that of body protein were estimated. The ratio of ash to protein was essentially constant. Water matured more slowly, and lipid faster, than protein. For males, and for females up to 8 wk, the models were satisfactory. For females after this age, lipid growth was faster than expected from the earlier period, probably in preparation for egg production. There were small, but important, differences in the values of some parameters between the strain-crosses. For each of the four genotypes the changes in weight of feathers and breast meat with time were described in terms of the Gompertz growth function, which described the data very well. The parameters of the function for each component and genotype-mature weight, rate of maturing, and the time taken to reach the maximum rate of growth B were evaluated. For the feathers, the value of the rate parameter was higher than that estimated for the body as a whole. For the two breast muscles, and for their total weight, the value of the rate parameter was similar to that for the body as a whole. There was a simple allometric relationship between the weights of the breast muscles and that of the whole body. As a consequence, the development of the yield of breast meat for a given genotype could be described by the values of the two parameters: mature yield and the allometric exponent. A description of each genotype of interest is seen as an essential first step in using a simulation model either to predict requirements, or to predict the effects of different feeding programs, and environmental conditions, on the performance of broilers.

Feed intake relative to stage of lactation for dairy cows consuming total mixed diets with a high or low ratio of concentrate to forage.

This experiment examined the effect of feed quality on the relationship between intake and stage of lactation in dairy cows. Two total mixed diets composed of grass silage and concentrate were formulated. The high concentrate total mixed diet was designed to meet energy requirements, and the low concentrate total mixed diet was designed to limit intake. Twenty-four Holstein-Friesian cows were offered the total mixed diets in a full 2 x 2 change-over design with control treatments. The changeover was at 153 d in milk (DIM). For the statistical analyses, two periods of 13 wk, one period before and one period after the changeover, were used. Dry matter intake (DMI), milk yield, body weight, and body condition score were significantly greater for cows fed the high concentrate total mixed diet than for cows fed the low concentrate total mixed diet. Significant interactions between total mixed diet and period were observed for DMI and milk yield. However, no significant residual effects of changing from one total mixed diet to the other were observed. The interactions were due to substantially different slopes of DMI and milk yield relative to DIM for cows fed the two different total mixed diets. For cows fed the low concentrate total mixed diet, there was no effect of stage of lactation on DMI; the slope was 0. For cows fed the high concentrate total mixed diet, there was a significant decline in DMI as lactation progressed.

Effects of feed composition and stage of lactation on the short-term feeding behavior of dairy cows.

Twenty Holstein-Friesian cows were assigned to one of four feeding groups throughout lactation in a full change-over experiment using two total mixed diets. The low concentrate total mixed diet contained 100 g of concentrate/kg of fresh matter, and the high concentrate total mixed diet contained 300 g of concentrate/kg of fresh matter. The remainder of the total mixed diet was grass silage. The two changeover groups switched total mixed diets at 153 d of lactation; the other two treatment groups remained on their assigned diets throughout lactation. For analysis of short-term feeding behavior, four periods of 3 wk each were identified. The midpoints of these periods were -102, -18, 18, and 102 d from the changeover. The concentrate content of the total mixed diet significantly affected dry matter intake and all short-term feeding behavior variables. Cows that consumed the high concentrate total mixed diet had fewer but longer visits to the feeders and ate more feed per visit than did cows consuming the low concentrate total mixed diet. With one exception, no significant effect of stage of lactation was detected for any of the short-term feeding behavior variables. Despite a highly significant decline in dry matter intake as lactation progressed for cows consuming the high concentrate total mixed diet, there were no interactions between total mixed diet and stage of lactation for any of the short-term feeding behavior variables. Large differences in feeding behavior were detected between cows consuming the same total mixed diet. These last two findings suggest that the use of short-term feeding behavior variables to predict daily intake is unlikely to be successful.