Effect of high-sugar grasses on methane emissions simulated using a dynamic model

High-sugar grass varieties have received considerable attention for their potential ability to decrease N excretion in cattle. However, feeding high-sugar grasses alters the pattern of rumen fermentation, and no in vivo studies to date have examined this strategy with respect to another environmental pollutant: methane (CH(4)). Modeling allows us to examine potential outcomes of feeding strategies under controlled conditions, and can provide a useful framework for the development of future experiments. The purpose of the present study was to use a modeling approach to evaluate the effect of high-sugar grasses on simulated CH(4) emissions in dairy cattle. An extant dynamic, mechanistic model of enteric fermentation and intestinal digestion was used for this evaluation. A simulation database was constructed and analysis of model behavior was undertaken to simulate the effect of (1) level of water-soluble carbohydrate (WSC) increase in dietary dry matter, (2) change in crude protein (CP) and neutral detergent fiber (NDF) content of the plant with an increased WSC content, (3) level of N fertilization, and (4) presence or absence of grain feeding. Simulated CH(4) emissions tended to increase with increased WSC content when CH(4) was expressed as megajoules per day or percent of gross energy intake, but when CH(4) was expressed in terms of grams per kilogram of milk, results were much more variable due to the potential increase in milk yield. As a result, under certain conditions, CH(4) (g/kg of milk) decreased. The largest increases in CH(4) emissions (MJ/d or % gross energy intake) were generally seen when WSC increased at the expense of CP in the diet and this can largely be explained by the representation in the model of the type of volatile fatty acid produced. Effects were lower when WSC increased at the expense of NDF, and intermediary when WSC increased at the expense of a mixture of CP and NDF. When WSC increased at the expense of NDF, simulated milk yield increased and, therefore, CH(4) (g/kg of milk) tended to decrease. Diminished increases of CH(4) (% gross energy intake or g/kg of milk) were simulated when DMI was increased with elevated WSC content. Simulation results suggest that high WSC grass, as a strategy to mitigate N emission, may increase CH(4) emissions, but that results depend on the grass composition, DMI, and the units chosen to express CH(4). Overall, this project demonstrates the usefulness of modeling for hypothesis testing in the absence of observed experimental results.

A Bayesian approach to analyze energy balance data from lactating dairy cows

The objective of the present investigation was to develop a Bayesian framework for updating and integrating covariate information into key parameters of metabolizable energy (ME) systems for dairy cows. The study addressed specifically the effects of genetic improvements and feed quality on key parameters in current ME systems. These are net and metabolizable energy for maintenance (NE(M) and ME(M), respectively), efficiency of utilization of ME for milk production (k(L)) and growth (k(G)), and efficiency of utilization of body stores for milk production (k(T)). Data were collated from 38 studies, yielding 701 individual cow observations on milk energy, ME intake, and tissue gain and loss. A function based on a linear relationship between milk energy and ME intake and correcting for tissue energy loss or gain served as the basis of a full Bayesian hierarchical model. The within-study variability was modeled by a Student t-distribution and the between-study variability in the structural parameters was modeled by a multivariate normal distribution. A meaningful relationship between genetic improvements in milk production and the key parameters could not be established. The parameter k(L) was linearly related to feed metabolizability, and the slope predicted a 0.010 (-0.0004; 0.0210) change per 0.1-unit change in metabolizability. The effect of metabolizability on k(L) was smaller than assumed in present feed evaluation systems and its significance was dependent on collection of studies included in the analysis. Three sets of population estimates (with 95% credible interval in parentheses) were generated, reflecting different degrees of prior belief: (1) Noninformative priors yielded 0.28 (0.23; 0.33) MJ/(kg(0.75)d), 0.55 (0.51; 0.58), 0.86 (0.81; 0.93) and 0.66 (0.58; 0.75), for NE(M), k(L), k(G), and k(T), respectively; (2) Introducing an informative prior that was derived from a fasting metabolism study served to combine the most recent information on energy metabolism in modern dairy cows. The new estimates of NE(M), k(L), k(G) and k(T) were 0.34 (0.28; 0.39) MJ/(kg(0.75)d), 0.58 (0.54; 0.62), 0.89 (0.85; 0.95), and 0.69 (0.60; 0.79), respectively; (3) finally, all informative priors were used that were established from literature, yielding estimates for NE(M), k(L), k(G), and k(T) of 0.29 (0.11; 0.46) MJ/(kg(0.75)d), 0.60 (0.54; 0.70), 0.70 (0.50; 0.88), and 0.80 (0.67; 0.97), respectively. Bayesian methods are especially applicable in meta-analytical studies as information can enter at various stages in the hierarchical model.

An extended model of phosphorus metabolism in growing ruminants

A major objective of this study was to extend the Vitti-Dias model used to describe P metabolism in ruminants, by adding 2 new pools to the original model to represent the rumen and saliva. An experiment was carried out using 24 male sheep, initial BW of 34.5 kg, aged 8 mo, fed a basal diet supplied with increasing amounts of dicalcium phosphate to provide 0.14, 0.32, 0.49, and 0.65% P in the diet. Sheep were individually housed indoors in metabolic cages and injected with a single dose of 7.4 MBq of (32)P into a jugular vein. Feed intake and total fecal and urinary outputs were recorded and sampled daily for 1 wk, and blood samples were obtained at 5 min, and 1, 2, 4, 6, 24, 48, 72, 96, 120, 144, and 168 h after (32)P injection. Saliva and rumen fluid samples were taken on d 6, 7, and 8. Then, animals were slaughtered and samples from liver, kidney, testicle, muscle, and heart (soft tissue) and bone were collected. Specific radioactivity and inorganic P were then determined in bone, soft tissue, plasma, rumen, saliva, and feces, and used to calculate flows between pools. Increased P intake positively affected total P (r = 0.97, P < 0.01) and endogenous P excretion in feces (r = 0.85, P < 0.01), P flow from plasma to saliva (r = 0.73, P < 0.01), from saliva to rumen (r = 0.73, P < 0.01), and from lower gastrointestinal tract to plasma (r = 0.72, P < 0.01). Urinary P excretion was similar for all treatments (P = 0.35). It was, however, related to plasma P (r = 0.63, P < 0.01) and to net P flow to bone (accretion - resorption; r = -0.64, P < 0.01). Phosphorus intake affected net P flow to soft tissue (P = 0.04) but not net P flow to bone (P = 0.46). Phosphorus mobilized from bone was directed toward soft tissue, as suggested by the correlations between P flow from bone to plasma and net P flow to soft tissue (r = 0.89, P < 0.01), and P flow from plasma to soft tissue and net P flow to bone (r = -0.76, P < 0.01). The lack of effect of dietary P on net P accretion in bone suggests that P demand for bone formation was low and surplus P was partially used by soft tissue. In conclusion, the model resulted in appropriate biological description of P metabolism in sheep and added knowledge of the effects of surplus dietary P on P metabolism. Additionally, the model can be used as a tool to assess feeding strategies aiming to mitigate P excretion into the environment.

Modeling the efficiency of phosphorus utilization in growing pigs

Microbial phytase has been used to reduce P excretion from swine to mitigate environmental pollution. The objective of the study was to quantify the effect of feeding a low-P phytase-supplemented diet on growth and P utilization in growing pigs using mathematical models. A total of 20 weaned piglets (BW = 6.5 kg) housed in metabolism cages were randomly assigned to a standard diet (STD) or P-amended diet containing reduced P content and supplemented with phytase (AMN) with 10 pigs/diet. Body weight and feed consumption were recorded weekly so complete growth and cumulative P intake (cPI) curves could be modeled. A function with fixed point of inflexion (Gompertz) and a variable point of inflexion (generalized Michaelis-Menten) were considered in determining bioequivalence by analyzing BW vs. age relationships, whereas the monomolecular function was used to describe BW vs. cPI. All functions were incorporated into a nonlinear mixed effects model, and a first-order autoregressive correlation structure was implemented to take into account repeated measures. There was no difference between the 2 groups in final BW when the Gompertz equation was fitted (176 vs. 178 kg with SE of 7 kg for the STD and AMN, respectively) or the rate parameter (0.0140 vs. 0.0139 with SE of 0.0004 for the STD and AMN, respectively). The generalized Michaelis-Menten equation also showed a similar trend. When BW was expressed as a function of cPI the derivative with respect to cPI represented P efficiency, so it was possible to analyze the expected difference of the 2 diets in using P for BW gain and express it as a continuous function of cPI. The analysis showed through the entire growth period the difference in P efficiency was different from zero. On average, 56 g of supplemented inorganic P was consumed by a pig fed the AMN to reach market weight. In contrast, 309 g of supplemented inorganic P was consumed by the group fed the STD to reach similar BW. It would depend on other factors, but feeding pigs the AMN can result in economic benefit. Pigs fed the AMN excreted 19% less P compared with those fed the STD. In conclusion, nonlinear mixed model analysis (with repeated measures) was suitable for growth and efficiency analysis and showed that pigs fed the AMN consumed less than 20% of the inorganic P and performed as well as those fed the traditional inorganic P supplemented diet. The implications for mitigating P pollution, especially in areas where P loading is already problematic, are substantial.

Predicting caloric and feed efficiency in turkeys using the group method of data handling-type neural networks

Neural networks (NN) are a relatively new option to model growth in animal production systems. One self-organizing submodel of artificial NN is the group method of data handling (GMDH)-type NN. The use of such self-organizing networks has led to successful application of the GMDH algorithm over a broad range of areas in engineering, science, and economics. The present study aimed to apply the GMDH-type NN to predict caloric efficiency (CE, g of gain/kcal of caloric intake) and feed efficiency (FE, kg of gain/kg of feed intake) in tom and hen turkeys fed diets containing different energy and amino acid levels. Involved effective input parameters in prediction of CE and FE were age, dietary ME, CP, Met, and Lys. Quantitative examination of the goodness of fit for the predictive models was made using R2 and error measurement indices commonly used to evaluate forecasting models. Statistical performance of the developed GMDH-type NN models revealed close agreement between observed and predicted values of CE and FE. In conclusion, using such powerful models can enhance our ability to predict economic traits, make precise prediction of nutrition requirements, and achieve optimal performance in poultry production.

A model on biological flow of phosphorus in growing pigs

Ten crossbred barrows weighting 20kg were allocated in five groups fed and on diets consisted of different total phosphorus (P) levels: 0.30%, 0.40%, 0.51%, 0.65%, and 0.73%. The animals were intravenously injected 7.4MBq of radioactive P (32P) and after seven days they were slaughtered for further analysis. The evaluated parameters were intake, excretion, specific activities, and flow of P in compartments (1-gut, 2-blood, 3-bone, and 4-soft tissue). Besides fecal losses, the kidneys played an import role in P regulation. The flows of P from tissue and gut to the blood were affected by P intake.

Development and evaluation of a dynamic model of calcium and phosphorus flows in layers

Phosphorus is an essential nutrient involved in most metabolic processes. Most of the interest in Ca metabolism relates to eggshell formation. Although the eggshell is composed of Ca carbonate, metabolism of both Ca and P is closely related such that a deficiency in one can interfere with proper utilization of the other. To understand Ca and P metabolism properly, modeling can be of paramount importance. A new dynamic and mechanistic model of P and Ca metabolism in layers has been developed to simulate diurnal changes in Ca and P and the hourly requirement of the layer for those minerals. The model consists of 8 state variables representing Ca and P pools in the crop, stomachs, plasma, and bone. The flow equations are described by Michaelis-Menten or mass action forms. An experiment that measured Ca and P uptake in layers fed different Ca concentrations during shell-forming days was used for model evaluation. The experiment showed that Ca retained in body and egg decreased from 62.5 to 50.5% of Ca intake when the Ca in diet was increased from 25 to 45 mg/g of feed. The model simulations were in agreement with the trend. Predictions of Ca retention in bone and egg were 63.2, 56.1, and 55.3% for low, medium, and high dietary Ca concentrations. The experimental results showed that P retention in body and egg increased significantly from 11.5% of absorbable P intake at the lowest Ca inclusion concentration to 24.1% at the highest. The model also predicted an increase in P retention in bone and egg from 8.4 to 25.4% of absorbable P intake at the lowest and highest concentration of Ca inclusion, respectively. The advantage of the model is that absorption and utilization can be monitored on an hourly basis and that adjustments can be made accordingly. The model successfully showed how the availability of one mineral affects the utilization of the other and is a useful tool to evaluate feeding strategies aimed at reducing P excretion to the environment in poultry manure.