An energy system is described in which, in both single-stomached and ruminant animals, the heat increment of feeding is considered to be linearly related to five measurable quantities. For both kinds of animals three of the quantities, with their heat increments in parentheses, are urinary N (wu; kJ/g), faecal organic matter (wd; kJ/g) and positive protein retention (wp; kJ/g). In ruminants the other two, with their heat increments in parentheses, are CH, energy (wm; kJ/kJ) and positive lipid retention (wI; kJ/g); in single-stomached animals they are positive lipid retention from feed lipid (wu; kJ/g), and positive lipid retention not from feed lipid (wl; kJ/g). Data from suitable experiments on steers, pigs and chickens were used to test the system and to estimate w, 29.2, w, 3.80, wp 36.5, w, 0.616, wI 16.4 and wII 4.4. The values for w,, wd, w, and (wI-wII) allow an energy scale, called effective energy, to be defined for both single-stomached animals and ruminants. On this energy scale the values of wp and wI, together with the heats of combustion of protein and lipid of 23.8 and 39.6 kJ/g respectively, allow the energy requirement to be expressed as (MH + 50PR + 56LR) for both kinds of animal, where P R and LR are the rates of positive protein and lipid retention (g/d), and MH is the maintenance heat production (kJ/d) which can be estimated as 0.96 of the fasting heat production. The effective energy (EE) yielded to a ruminant animal by a feed ingredient can be estimated as EE (MJ/kg organic matter) = 1.15ME-3.84 -4,67DCP, where M E is the metabolizable energy value (MJ/kg organic matter) and DCP is the digested crude protein content (kg/kg organic matter) with both measured at maintenance. Alternatively, EE can be estimated as EE (MJ/kg) = GE (d -0.228) -4.67DCP, where GE is the gross energy (MJ/kg) and d is the energy digestibility (MJ/MJ) also measured at maintenance. The EE yielded to a single-stomached animal can be estimated as EE (kJ/g) = 1.17ME-4.2CP-2.44, where M E (kJ/g) is measured at, or corrected to, zero N-retention and CP (g/g) is the crude protein (N x 6.25) content of the feed ingredient. The system is simpler for ruminants, and more accurate for both kinds of animal, than those now in use. As effective energy values can be tabulated for ingredients, and are additive to the extent that M E values are additive, they can be used to formulate diets using linear programming.Effective energy : Metabolizable energy : Ruminants : Single-stomached animals 'The feed of an animal is, as far as we know, the sole source of the energy whose transformations constitute the essential phenomena of physical life. This energy is contained in the feed as chemical energy, and the maximum quantity which any substance can furnish for the vital activities by its oxidation in the body is measured by its heat of combustion.
A deterministic, dynamic pig growth model is described that predicts the effects of genotype and the thermal and nutritional environments on food intake, growth and body composition of growing pigs. From the daily potential for protein gain, as determined by pig genotype and current state, the potential gains of the other chemical components, including ‘desired’ lipid gain, are calculated. Unconstrained voluntary food intake is predicted from the current protein and lipid contents of the pig, and the composition of the food, as that which is needed to permit potential growth to be achieved. The model allows compensatory lipid gain. The composition of the food is described in terms of its digestible energy content (DEC), ideal digestible crude protein content (IDCPC) and bulkiness. Both energy and protein can be limiting resources and the bulk of the food may constrain intake. The animal’s capacity for bulk is a function of its size. The thermal environment is described by the ambient temperature, wind speed, floor type and humidity and sets the maximum (HLmax) and minimum (HLmin) values possible for heat loss. A comparison with heat production (HP) determines whether the environment is hot (HP > HLmax), cold (HP < HLmin) or thermoneutral (HLmin< HP < HLmax). A constraint on intake operates in hot environments, while in cold environments, there is an extra thermal demand. If conditions are thermoneutral no further action is taken. Daily gains of each of the chemical components are calculated by partitioning energy intake between protein and lipid gains according only to the energy to protein ratio of the food. The model builds on the work of others in the literature as it allows predictions on how changes in: (i) the kind of pig; (ii) the animal’s current state, which is particularly relevant in cases of compensatory growth; (iii) the dietary composition, and; (iv) the climatic environment, affect food intake and growth, whilst maintaining simplicity and flexibility.
This study assessed the efficacy of the n-alkane technique to estimate intake and diet composition in animals given single foods or a choice of two. In thefirst experiment intakes of pelleted ryegrassand lucerne, given eitheralone or as a choice, were measured in lambshoused indoors in individual pens. Each of the three feeding treatments was given to 12 lambs at two degrees of maturity (0.30 and 0·45 of estimated mature sizes). The 12 lambs were constituted as three replicates of the two sexes of each of two breeds. The measured intakes werecompared with those estimated using the n-alkanes C 31 andC 33 , found naturally in thefoods, and C 32 ' which was given as a dose. On the choice treatment diet composition was estimated using. a non-negative least squares procedure and data on C 31 and C 33 alone. The agreement between actualand predicted intakewas good: R2 ofO·938for log-linear regression with a residual standard deviation of 0·0845. Intake of lucerne when offered alone was slightly yet significantly overp redicted. The proportion of ryegrass in the diet was also accurately predicted (R2 of 0·950 and residual s.d. of 0.0398). Using the data on C 2l and C 29 , in addition to that on C 31 and C 33 , gave a poorer agreement with the observed diet compositions. The low and similar levels of e 2l in the two foods meant that ihisn-alkane provided little extra information that could be used to estimate diet composition. In a second experimentfaecal samples were collected every 4 hours over a 24-h period in six lambs on ad libitum, and in six lambs on a restricted quantity, of pel/eted ryegrass. There was no significant diurnal variation in the ratios of either C 31 or C 33 to C 32 on either ad libitum or restricted feeding. The time offaecal collection within a day should not therefore affect the reliability of the predictions. The study confirmed the value of using n-alkanes in methods to determine the intake of forages by sheep, and that the time of faecal collection within the day does not affect the reliability of these predictions. The results also confirm theuWity of the n-alkane method for estimating diet choice, at least with two-component mixtures.
A deterministic, dynamic pig growth model predicting the effect of genotype, and the thermal and nutritional environments on food intake, growth and body composition of growing pigs was tested and evaluated against experimental data from the literature. Four sets of experiments meeting the necessary requirement of feeding the pigs ad libitum and reporting sufficient information on trial conditions were chosen to test the model. The parameters used in the model to describe the kind of pig were protein weight at maturity (Pm) the Gompertz rate parameter (B) and the ratio of mature lipid weight (Lm) to Pm. Values for Pm and B used to apply to the pigs in the four experiments were selected as those which gave the maximum daily gains equal to those reported at thermoneutral temperatures on diets not limiting in protein. The value of Lm was chosen as that which gave a value for food conversion ratio close to that seen in the experiment, again at a thermoneutral temperature and on a non-limiting diet. The model was run for each of the experiments from the given start weight until slaughter weight was reached. All pigs were assumed to have their desired bodily composition at the start of the experimental period, which is determined by their genetic descriptors and weight. From the conditions of the experiments, average daily gain (ADG) average daily food intake (ADFI) food conversion ratio (FCR) final body weight, body composition, average daily gains of each of the chemical body components and heat production (HP) were predicted. Generally as temperature increased or the crude protein content of the food increased, ADFI, ADG and the fatness of the pig decreased, whilst protein content increased. Quantitative differences between the model predictions and the observations, were probably due to the greater sensitivity of the model to temperature. This is likely to reflect the omission of long-term adaptation and acclimatization, or to incorrect estimation of the wetness of the pig’s skin. However, model predictions were generally in good quantitative agreement with the observed data over the wide range of treatments tested. This gives support to the value and accuracy of the model for predicting pig performance when the thermal and nutritional environments are manipulated.
The term ‘negative energy balance’ (NEB) is used to describe the condition in early lactation when the energy available from food intake is lower than that of the energy used by the cow for milk output, maintenance and activity. Current selection objectives may be favouring cows that are genetically predisposed to mobilise body tissue. This may have consequences for fertility since cows appear to resume reproductive activity only after the nadir of NEB has passed (Veerkamp et al., 2000). Extreme NEB may be considered generally undesirable, as it is a precursor to health and fertility problems. The aims of this study were: 1) to predict genetic merit for sires for traits contributing to energy balance; 2) to combine those breeding values into an overall energy balance evaluation for bulls using either daily energy flux or body state changes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.