Animal production for efficient phosphate utilization: from optimized feed to high efficiency livestock

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Highlights? Group feeding animals according to their physiological state will reduce P consumption. ? Reducing P in feed and precision feeding of P will increase efficiency of P utilization by livestock. ? Addition of phytase enzyme will increase P availability especially in swine and poultry. ? Transgenic plants and animals offer a way for efficient phosphate uptake. ? Nutritional genomics is expected to improve efficiency of P utilization in livestock.     

Models for predicting enteric methane emissions from dairy cows in North America,Europe, and Australia and New Zealand

There are several models in the literature for predicting enteric methane (CH₄) emissions. These models were often developed on region or country‐specific data and may not be able to predict the emissions successfully in every region. The majority of extant models require dry matter intake (DMI) of individual animals, which is not routinely measured. The objectives of this study were to (i) evaluate performance of extant models in predicting enteric CH₄ emissions from dairy cows in North America (NA), Europe (EU), and Australia and New Zealand (AUNZ) and (ii) explore the performance using estimated DMI. Forty extant models were challenged on 55, 105, and 52 enteric CH₄ measurements (g per lactating cow per day) from NA, EU, and AUNZ, respectively. The models were ranked using root mean square prediction error as a percentage of the average observed value (RMSPE) and concordance correlation coefficient (CCC). A modified model of Nielsen et al. (Acta Agriculturae Scand Section A, 63 , 2013 and 126) using DMI, and dietary digestible neutral detergent fiber and fatty acid contents as predictor variables, were ranked highest in NA (RMSPE = 13.1% and CCC = 0.78). The gross energy intake‐based model of Yan et al. (Livestock Production Science, 64 , 2000 and 253) and the updated IPCC Tier 2 model were ranked highest in EU (RMSPE = 11.0% and CCC = 0.66) and AUNZ (RMSPE = 15.6% and CCC = 0.75), respectively. DMI of cows in NA and EU was estimated satisfactorily with body weight and fat‐corrected milk yield data (RMSPE < 12.0% and CCC > 0.60). Using estimated DMI, the Nielsen et al. (2013) (RMSPE = 12.7 and CCC = 0.79) and Yan et al. (2000) (RMSPE = 13.7 and CCC = 0.50) models still predicted emissions in respective regions well. Enteric CH₄ emissions from dairy cows can be predicted successfully (i.e., RMSPE < 15%), if DMI can be estimated with reasonable accuracy (i.e., RMSPE < 10%).     

A comparison of the Schumacher with other functions for describing growth in pigs

This study was undertaken to introduce the Schumacher equation and compare it with established functions for describing growth in pigs. The relationship between live weight (LW) and cumulative feed intake was also investigated. A database was constructed from three independent trials in which LW, age and intake were measured from birth to 937 days. Three growth functions were used for analysis of growth versus age: Gompertz, Schumacher and Weibull; and the Richards and monomolecular equations were used for analysis of cumulative feed intake versus LW. The growth functions have different points of inflexion. Liveweight at inflexion is W_f/e for the Gompertz, where W_f is the final weight, W_f/e² for the Schumacher, and W_f − (W_f − W₀) exp[−(n − 1)/n] for the Weibull, where W₀ is initial body weight and n is a shape parameter. Meta-analysis of the data using mixed model and nonlinear regression procedures was conducted to identify the most appropriate growth function. Functions were compared using F-tests or Bayesian Information Criteria, which give a value based on best fit and number of parameters in the model. The three equations were fitted to five individual pig growth profiles and to the composite data. Although the Weibull had a lower residual mean square, it did not significantly improve the fit compared to the simpler models and appears to be over-parameterised. The results suggest that model selection should be based on the type and amount of data available for analysis. Residuals plot showed that Schumacher and Weibull better predict the initial growth phase, however, all models showed largest magnitude of residuals towards the end of the growth profile. The monomolecular equation was most appropriate for describing LW against cumulative feed intake and may be used to formulate diets based on the efficiency of conversion of feed to LW at various stages of the animal's life span.     

Prediction of enteric methane emissions from cattle

Agriculture has a key role in food production worldwide and it is a major component of the gross domestic product of several countries. Livestock production is essential for the generation of high quality protein foods and the delivery of foods in regions where animal products are the main food source. Environmental impacts of livestock production have been examined for decades, but recently emission of methane from enteric fermentation has been targeted as a substantial greenhouse gas source. The quantification of methane emissions from livestock on a global scale relies on prediction models because measurements require specialized equipment and may be expensive. The predictive ability of current methane emission models remains poor. Moreover, the availability of information on livestock production systems has increased substantially over the years enabling the development of more detailed methane prediction models. In this study, we have developed and evaluated prediction models based on a large database of enteric methane emissions from North American dairy and beef cattle. Most probable models of various complexity levels were identified using a Bayesian model selection procedure and were fitted under a hierarchical setting. Energy intake, dietary fiber and lipid proportions, animal body weight and milk fat proportion were identified as key explanatory variables for predicting emissions. Models here developed substantially outperformed models currently used in national greenhouse gas inventories. Additionally, estimates of repeatability of methane emissions were lower than the ones from the literature and multicollinearity diagnostics suggested that prediction models are stable. In this context, we propose various enteric methane prediction models which require different levels of information availability and can be readily implemented in national greenhouse gas inventories of different complexity levels. The utilization of such models may reduce errors associated with prediction of methane and allow a better examination and representation of policies regulating emissions from cattle.     

Impact of Nutrition and Salinity Changes on Biological Performances of Green and White Sturgeon

Green and white sturgeon are species of high conservational and economic interest, particularly in the San Francisco Bay Delta (SFBD) for which significant climate change-derived alterations in salinity and nutritional patterns are forecasted. Although there is paucity of information, it is critical to test the network of biological responses underlying the capacity of animals to tolerate current environmental changes. Through nutrition and salinity challenges, climate change will likely have more physiological effect on young sturgeon stages, which in turn may affect growth performance. In this study, the two species were challenged in a multiple-factor experimental setting, first to levels of feeding rate, and then to salinity levels for different time periods. Data analysis included generalized additive models to select predictors of growth performance (measured by condition factor) among the environmental stressors considered and a suite of physiological variables. Using structural equation modeling, a path diagram is proposed to quantify the main linkages among nutrition status, salinity, osmoregulation variables, and growth performances. Three major trends were anticipated for the growth performance of green and white sturgeon in the juvenile stage in the SFBD: (i) a decrease in prey abundance will be highly detrimental for the growth of both species; (ii) an acute increase in salinity within the limits studied can be tolerated by both species but possibly the energy spent in osmoregulation may affect green sturgeon growth within the time window assessed; (iii) the mechanism of synergistic effects of nutrition and salinity changes will be more complex in green sturgeon, with condition factor responding nonlinearly to interactions of salinity and nutrition status or time of salinity exposure. Green sturgeon merits special scientific attention and conservation effort to offset the effects of feed restriction and salinity as key environmental stressors in the SFBD.     

Primary open-angle glaucoma patients have reduced levels of blood docosahexaenoic and eicosapentaenoic acids

The aetiology of primary open-angle glaucoma (POAG), which is the commonest cause of non-remediable blindness and visual impairment, is not well understood. Nevertheless, increased intraocular pressure, and vascular factors such as ocular blood flow deficits are thought to be risk factors. There is evidence of decreased optic nerve blood velocity and increased red blood cell aggregability in POAG. These factors are influenced by fatty acids. We have investigated if glaucoma patients have abnormal blood fatty acid composition. Patients with POAG (n=10) and their healthy siblings (n=8) were enrolled. Compared with their healthy siblings, the glaucoma patients had reduced eicosapentaenoic (EPA, P<0.01), and docosahexaenoic (DHA, P<0.05) fatty acids and total omega3 long-chain polyunsaturated fatty acids (LCPUFA) (P<0.05) in red cell choline phosphoglycerides (CPG); decreased EPA (P<0.05) in ethanolamine phosphoglycerides (EPG); lower EPA (P<0.05) and total omega3 LCPUFA (P<0.05) in serine phosphoglycerides (SPG). Similarly, they had reduced EPA, DHA and total omega3 LCPUFA in plasma CPG (P<0.005) and triglycerides (P<0.05). These findings may be significant, since EPA and DHA could modulate impaired systemic microcirculation and ocular blood flow and optic neuropathy, which are the main physiological changes associated with glaucoma.     

Plasma fatty acids of neonates born to mothers with and without gestational diabetes

Women with gestational diabetes mellitus (GDM) and their neonates have lower levels of arachidonic (AA) and docosahexaenoic (DHA) acids in red cell membranes. It is not clear if this abnormality is restricted to red cells or is a generalised problem. We have investigated plasma fatty acids of neonates (venous cord) of GDM (n=37), and non-diabetic (n=31) women. The GDMs had lower levels of dihomogamma-linolenic (20:3n-6, DHGLA) acid, summation operator n-6 metabolites, DHA and summation operator n-3 metabolites (p<0.05) in choline phosphoglycerides (CPG). They also had lower levels of AA (-4.5%), adrenic acid (22:4n-6, -13%), osbond acid (22:5n-6, -7%) and summation operator n-6 (-2.5%). There was a similar pattern in triglycerides (TG) and cholesterol esters (CE). Mead acid, a marker of generalised shortage of derived and parent essential fatty acids, was higher in CPG and TG of the GDM group by 73% and 76%. The adrenic/osbond acid (22:4n-6/22:5n-6) ratio, a biochemical marker of DHA insufficiency, was reduced in CPG (-4.5%), TG (-63%) and CE (-75%) of the GDM group. These findings, which are consistent with the previous red cell data, suggest that the neuro-visual and vascular development and function of the offspring of GDM women may be adversely affected if the levels of AA and DHA are compromised further by other factors, pre- or post-natally. Studies are required to elucidate the underlying mechanism for the reduction of the two fatty acids and to evaluate the developmental and health implications.     

Effects of phosphorus intake on phosphorus flow in growing pigs: application and comparison of two models

A comparison of the models of Vitti et al. (2000, J. Anim. Sci. 78, 2706-2712) and Fernández (1995c, Livest. Prod. Sci. 41, 255-261) was carried out using two data sets on growing pigs as input. The two models compared were based on similar basic principles, although their aims and calculations differed. The Vitti model employs the rate:state formalism and describes phosphorus (P) flow between four pools representing P content in gut, blood, bone and soft tissue in growing goats. The Fernández model describes flow and fractional recirculation between P pools in gut, blood and bone in growing pigs. The results from both models showed similar trends for P absorption from gut to blood and net retention in bone with increasing P intake, with the exception of the 65 kg results from Date Set 2 calculated using the Fernández model. Endogenous loss from blood back to gut increased faster with increasing P intake in the Fernández than in the Vitti model for Data Set 1. However, for Data Set 2, endogenous loss increased with increasing P intake using the Vitti model, but decreased when calculated using the Fernández model. Incorporation of P into bone was not influenced by intake in the Fernández model, while in the Vitti model there was an increasing trend. The Fernández model produced a pattern of decreasing resorption in bone with increasing P intake, with one of the data sets, which was not observed when using the Vitti model. The pigs maintained their P homeostasis in blood by regulation of P excretion in urine.     

Oxicams Bind in a Novel Mode to the Cyclooxygenase Active Site via a Two-water-mediated H-bonding Network

Oxicams are widely used nonsteroidal anti-inflammatory drugs (NSAIDs), but little is known about the molecular basis of the interaction with their target enzymes, the cyclooxygenases (COX). Isoxicam is a nonselective inhibitor of COX-1 and COX-2 whereas meloxicam displays some selectivity for COX-2. Here we report crystal complexes of COX-2 with isoxicam and meloxicam at 2.0 and 2.45 angstroms, respectively, and a crystal complex of COX-1 with meloxicam at 2.4 angstroms. These structures reveal that the oxicams bind to the active site of COX-2 using a binding pose not seen with other NSAIDs through two highly coordinated water molecules. The 4-hydroxyl group on the thiazine ring partners with Ser-530 via hydrogen bonding, and the heteroatom of the carboxamide ring of the oxicam scaffold interacts with Tyr-385 and Ser-530 through a highly coordinated water molecule. The nitrogen atom of the thiazine and the oxygen atom of the carboxamide bind to Arg-120 and Tyr-355 via another highly ordered water molecule. The rotation of Leu-531 in the structure opens a novel binding pocket, which is not utilized for the binding of other NSAIDs. In addition, a detailed study of meloxicam·COX-2 interactions revealed that mutation of Val-434 to Ile significantly reduces inhibition by meloxicam due to subtle changes around Phe-518, giving rise to the preferential inhibition of COX-2 over COX-1.     

Estimation of the stoichiometry of volatile fatty acid production in the rumen of lactating cows

The purpose of this study was to improve the prediction of the quantity and type of Volatile Fatty Acids (VFA) produced from fermented substrate in the rumen of lactating cows. A model was formulated that describes the conversion of substrate (soluble carbohydrates, starch, hemi-cellulose, cellulose, and protein) into VFA (acetate, propionate, butyrate, and other VFA). Inputs to the model were observed rates of true rumen digestion of substrates, whereas outputs were observed molar proportions of VFA in rumen fluid. A literature survey generated data of 182 diets (96 roughage and 86 concentrate diets). Coefficient values that define the conversion of a specific substrate into VFA were estimated meta-analytically by regression of the model against observed VFA molar proportions using non-linear regression techniques. Coefficient estimates significantly differed for acetate and propionate production in particular, between different types of substrate and between roughage and concentrate diets. Deviations of fitted from observed VFA molar proportions could be attributed to random error for 100%. In addition to regression against observed data, simulation studies were performed to investigate the potential of the estimation method. Fitted coefficient estimates from simulated data sets appeared accurate, as well as fitted rates of VFA production, although the model accounted for only a small fraction (maximally 45%) of the variation in VFA molar proportions. The simulation results showed that the latter result was merely a consequence of the statistical analysis chosen and should not be interpreted as an indication of inaccuracy of coefficient estimates. Deviations between fitted and observed values corresponded to those obtained in simulations.