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To mitigate methane emission from urban natural gas distribution systems, it is crucial to understand local leak rates and occurrence rates. To explore urban methane emissions in cities outside the U.S., where significant emissions were found previously, mobile measurements were performed in 12 cities across eight countries. The surveyed cities range from medium size, like Groningen, NL, to large size, like Toronto, CA, and London, UK. Furthermore, this survey spanned across European regions from Barcelona, ES, to Bucharest, RO. The joint analysis of all data allows us to focus on general emission behavior for cities with different infrastructure and environmental conditions. We find that all cities have a spectrum of small, medium, and large methane sources in their domain. The emission rates found follow a heavy-tailed distribution, and the top 10% of emitters account for 60–80% of total emissions, which implies that strategic repair planning could help reduce emissions quickly. Furthermore, we compare our findings with inventory estimates for urban natural gas-related methane emissions from this sector in Europe. While cities with larger reported emissions were found to generally also have larger observed emissions, we find clear discrepancies between observation-based and inventory-based emission estimates for our 12 cities.

In this communication, Earth temperature series in air and soil are analyzed and features that become convoluted with the known earth cycles of day-night and its orbit around the sun are separated. Atmospheric carbon dioxide concentrations are also considered. Earth weather changes (e.g., cloud, wind, rain, polar jet streams, and atmospheric pressure) in real time affect daily temperatures in a complex manner. A statistical model that accounts for autocorrelation and linear trend is evaluated together with empirical description of the series. Further graphical analysis is used to enhance remaining features and extreme events. Gaussian bell-shaped curve modeling of each year's daily profile is described. Further, Gaussian parameter-based anomalies are introduced together with soil anomalies at 30cm depth. Semi-variogram components are shown along with folded percentile or mountain plots for data visualization. The Chow test is described for detection of any structural changes in data series. For much of the statistical analysis, temperatures observed daily are most appropriate because they carry variation due to earth, sea and sky weather over a single day-night earth rotation cycle. Also, the ever changing earth position along its orbital path captures a varying amount of solar energy, hence the shape of the temperature cycle as one sees it. Human activity and climate changing factors appear to affect temperature cycles within and over years. A double bell-shaped Gaussian curve fit can indicate climate changing effects of Earth life.

Natural levels of soil nutrients are spatio-temporally variable and insufficient for agricultural purposes. Artificial fertilizers are applied to achieve greater crop growth rates and yield. Mitscherlich's equation and Boule's fertilizer units are described and illustrated in relation to crop yield then applied to estimate the nitrogen (N)-pool fraction in the soil that contributes to a component of greenhouse gas (GHG) emission, specifically the nitrous oxide (N2O) flux. Mitscherlich (1909) proposed a diminishing returns model to extract information about soil N status for production responses. Mitscherlich's equation was generalized by Baule (1918) and modified by Bray (1945) to account for soil nutrient contributions for multiple fertilizers. These models are examined in this chapter. Their application results in the extraction of further information on soil nutrient variability and N2O emission across various geo-positions (specific global locations). It is concluded that Mitscherlich's equation and Boule's fertilizer units are useful tools to investigate soil-fertilizer interaction and compare soil fertility and GHG emission.

Atmospheric methane grew very rapidly in 2014 (12.7 ± 0.5 ppb/year), 2015 (10.1 ± 0.7 ppb/year), 2016 (7.0 ± 0.7 ppb/year), and 2017 (7.7 ± 0.7 ppb/year), at rates not observed since the 1980s. The increase in the methane burden began in 2007, with the mean global mole fraction in remote surface background air rising from about 1,775 ppb in 2006 to 1,850 ppb in 2017. Simultaneously the 13C/12C isotopic ratio (expressed as δ13CCH4) has shifted, has shifted, now trending negative for more than a decade. The causes of methane's recent mole fraction increase are therefore either a change in the relative proportions (and totals) of emissions from biogenic and thermogenic and pyrogenic sources, especially in the tropics and subtropics, or a decline in the atmospheric sink of methane, or both. Unfortunately, with limited measurement data sets, it is not currently possible to be more definitive. The climate warming impact of the observed methane increase over the past decade, if continued at >5 ppb/year in the coming decades, is sufficient to challenge the Paris Agreement, which requires sharp cuts in the atmospheric methane burden. However, anthropogenic methane emissions are relatively very large and thus offer attractive targets for rapid reduction, which are essential if the Paris Agreement aims are to be attained. The rise in atmospheric methane (CH4), which began in 2007, accelerated in the past 4 years. The growth has been worldwide, especially in the tropics and northern midlatitudes. With the rise has come a shift in the carbon isotope ratio of the methane. The causes of the rise are not fully understood, and may include increased emissions and perhaps a decline in the destruction of methane in the air. Methane's increase since 2007 was not expected in future greenhouse gas scenarios compliant with the targets of the Paris Agreement, and if the increase continues at the same rates it may become very difficult to meet the Paris goals. There is now urgent need to reduce methane emissions, especially from the fossil fuel industry. Atmospheric methane is rising; its carbon isotopic ratio has become more depleted in C‐13The possible causes of the change include an increase in emissions, with changing relative proportions of source inputs, or a decline in methane destruction, or bothIf this rise continues, there are significant consequences for the UN Paris Agreement

Observations by the Cloud Imaging and Particle Size (CIPS) instrument on the Aeronomy of Ice in the Mesosphere (AIM) satellite show an anomalous decline in Northern Hemisphere polar mesospheric clouds (PMCs) from 26 July to 6 August 2014. The decline is attributed to local warming associated with the quasi‐two‐day wave and interhemispheric coupling (IHC) triggered by planetary wave breaking in the Antarctic (winter) stratosphere. The results indicate that the IHC in 2014 occurred via a pathway that previous studies have not emphasized. Based on observations from the Aura Microwave Limb Sounder (MLS) and reanalyses from both the Modern‐Era Retrospective analysis for Research and Applications, Version 2 (MERRA‐2) and the Navy Global Environmental Model (NAVGEM), we argue that a strengthening of the summer easterly jet gave rise to enhanced meridional and vertical shear along its equatorward flank, which supported growth of the two‐day wave. The two‐day wave led to enhanced meridional mixing in northern midlatitudes and a weakening of the northern branch of the mesospheric residual circulation, reducing ascent and warming the polar summer mesopause. In 2014, the five‐day planetary wave modulated the response to IHC such that PMCs persisted in its cold phases even though zonal mean temperatures were too high to support PMCs, and were absent in the warm phases when zonal mean temperatures were low enough to support PMCs. Polar mesospheric cloud frequencies decline rapidly in July 2014 due to a two‐day wave‐driven warming of the mesopause regionWintertime planetary waves lead to anomalous temperatures at low latitudes, enhanced extratropical wind shear, and two‐day wave growthThe response of polar mesospheric clouds to the two‐day wave‐driven temperature increase is modulated by a large mesospheric five‐day wave

A new Cloud Imaging and Particle Size (CIPS) gravity wave (GW) variance data set is available that facilitates automated analysis of GWs entering the mesosphere. This work examines several years of CIPS GW variances from 50 to 55 km in the context of the Arctic and Antarctic polar vortices. CIPS observes highest GW activity in the vortex edge region where horizontal wind speeds are largest, consistent with previously published GW climatologies in the stratosphere and mesosphere. CIPS observes the well‐documented planetary wave (PW)‐1 patterns in GW activity in both hemispheres. In the Northern Hemisphere, maximum GW activity occurs over the North Atlantic and western Europe. In the Southern Hemisphere, maximum GW activity stretches from the Andes over the South Atlantic and Indian Oceans, as expected. In the NH, CIPS GW spatial patterns are highly correlated with horizontal wind speed. In the SH, CIPS GW patterns are less positively correlated with the winds due to increased zonal symmetry and orographic forcing. The Andes Mountains and Antarctic Peninsula, South Georgia Island, Kerguelen/Heard Islands, New Zealand, and Tasmania are persistent sources of orographic GWs. Atmospheric Infrared sounder observations of stratospheric GWs are analyzed alongside CIPS to explore vertical GW coherence and to infer GW propagation and sources. NH midlatitude GW activity is reduced during the January 2021 SSW, as expected. This reduction in GWs leads to a simultaneous reduction in traveling ionospheric disturbances (TIDs), providing more evidence that weak polar vortex events with weak GW activity leads to reduced daytime TID activity. A new satellite gravity wave (GW) variance data set is available that facilitates automated analysis of GWs entering the mesosphere. This work examines several years of GW variances from 50 to 55 km in the context of the Arctic and Antarctic polar vortices. Highest GW activity is observed in the vortex edge region where horizontal wind speeds are largest, consistent with previous work. Known planetary wave‐1 patterns are confirmed in the new data set. In the Northern Hemisphere, maximum GW activity occurs over the North Atlantic and western Europe. In the Southern Hemisphere, maximum GW activity stretches from the Andes over the South Atlantic and Indian Oceans. In the Arctic winter, GW spatial patterns are highly correlated with horizontal wind speed. In the Antarctic winter, GW patterns are less positively correlated with the winds due to smaller variations around a latitude circle and larger orographic forcing. We show that Arctic midlatitude GW activity is reduced during the January 2021 SSW, as expected. This reduction in GWs leads to a simultaneous reduction in traveling ionospheric disturbances (TIDs), providing more evidence that weak polar vortex events with weak GW activity leads to reduced daytime TID activity. This is the first work to present gravity waves (GWs) from 50 to 55 km observed by AIM CIPS with a focus on the winter polar vorticesDuring the 2020–2021 Arctic winter the longitude of maximum GW activity, maximum horizontal wind speed, and the polar vortex are co‐locatedReduced GW activity during the January 2021 SSW leads to simultaneous reductions in daytime traveling ionospheric disturbances This is the first work to present gravity waves (GWs) from 50 to 55 km observed by AIM CIPS with a focus on the winter polar vortices During the 2020–2021 Arctic winter the longitude of maximum GW activity, maximum horizontal wind speed, and the polar vortex are co‐located Reduced GW activity during the January 2021 SSW leads to simultaneous reductions in daytime traveling ionospheric disturbances

Tropical methane sources are an important part of the global methane budget and include natural wetlands, rice agriculture, biomass burning, ruminants, fossil fuels, and waste. δ13CCH4can provide strong constraints on methane source apportionment. For example, tropical wetlands in this study give δ13CCH4values between −61.5 ± 2.9‰ and −53.0 ± 0.4‰ and in general are more enriched in 13C than temperate and boreal wetlands. However, thus far, relatively few measurements of δ13CCH4in methane‐enriched air have been made in the tropics. In this study samples have been collected from tropical wetland, rice, ruminant, and biomass burning emissions to the atmosphere. Regional isotopic signatures vary greatly as different processes and source material affect methane signatures. Measurements were made to determine bulk source inputs to the atmosphere, rather than to study individual processes. These measurements provide inputs for regional methane budget models, to constrain emissions with better source apportionment. Methane δ13C isotopic signatures have been measured in the tropics for wetland, rice, ruminant, and biomass burningWetlands, rice, and ruminants are depleted in 13C, but it is difficult to distinguish between them; biomass burning values are enriched in 13CIsotopic measurements are essential in determining the causes of methane growth Tropical methane sources are an important part of the global methane budget and include natural wetlands, rice agriculture, biomass burning, ruminants, fossil fuels, and waste. Carbon isotopes in methane can provide strong constraints on methane source apportionment. However, thus far, relatively few measurements of carbon isotopes in methane‐enriched air have been made in the tropics. In this study samples have been collected from tropical wetland, rice, ruminant, and biomass burning emissions to atmosphere. Regional isotopic signatures vary greatly as different processes and source material affect methane signatures. Measurements were made to determine bulk source inputs to the atmosphere, rather than to study individual processes, to provide inputs for regional methane budget models, and to constrain emissions with better source apportionment.

Airborne measurements of a methane (CH4) plume over the North Sea from August 2013 are analyzed. The plume was only observed downwind of circumnavigated gas fields, and three methods are used to determine its source. First, a mass balance calculation assuming a gas field source gives a CH4emission rate between 2.5 ± 0.8×104and 4.6 ± 1.5×104kg h−1. This would be greater than the industry's reported 0.5% leak rate if it were emitting for more than half the time. Second, annual average UK CH4emissions are combined with an atmospheric dispersion model to create pseudo‐observations. Clean air from the North Atlantic passed over mainland UK, picking up anthropogenic emissions. To best explain the observed plume using pseudo‐observations, an additional North Sea source from the gas rigs area is added. Third, the δ13C‐CH4from the plume is shown to be −53‰, which is lighter than fossil gas but heavier than the UK average emission. We conclude that either an additional small‐area mainland source is needed, combined with temporal variability in emission or transport in small‐scale meteorological features. Alternatively, a combination of additional sources that are at least 75% from the mainland (−58‰) and up to 25% from the North Sea gas rigs area (−32‰) would explain the measurements. Had the isotopic analysis not been performed, the likely conclusion would have been of a gas field source of CH4. This demonstrates the limitation of analyzing mole fractions alone, as the simplest explanation is rejected based on analysis of isotopic data. In the study, we have analyzed aircraft data to try and identify the source of a plume of methane observed over the North Sea. The flight circuited North Sea gas fields with the aim of intercepting any fugitive methane. Initial analysis of the amount of methane present and its location suggested that the methane was being emitted from the gas field area, and this was supported by dispersion modeling of the case. However, analysis of carbon isotopes in methane revealed that fugitive gas could not have been the primary component of the plume. As methane is often measured without analysis of its carbon isotopes, the authors feel that this is an important cautionary tale. We present our analysis of this case study with recommendations for how best to conduct such analyses in the future to try and avoid potential misdiagnosis of methane plume sources. Three methods are used to analyze a methane plume observed over the North SeaOnly with use of all three methods can the source of the plume be understoodMeasurement of carbon isotopes is essential for source identification, given limitations to the model and the extent of the measurements

This paper describes a new data set from the Aeronomy of Ice in the Mesosphere (AIM) Cloud Imaging and Particle Size (CIPS) instrument, from which gravity waves (GWs) at an altitude of 50–55 km can be inferred. CIPS is sensitive to GWs with horizontal wavelengths from ~15 to 600 km and vertical wavelengths longer than 15 km. Several examples of GWs in CIPS observations are shown, including waves associated with the Andes Mountains, island topography, convection, the polar night jet, and the tropospheric jet stream. GW signatures in the CIPS data are shown to agree well with near‐coincident but lower altitude measurements from the Atmospheric Infrared Sounder (AIRS) in June of 2016. Results suggest the power of combining CIPS measurements with those from other instruments to investigate GW filtering and propagation. The CIPS data set opens new areas of inquiry, enabling comprehensive investigations of GWs in the middle atmosphere on a near‐global scale. New gravity wave data set from the Aeronomy of Ice in the Mesosphere Cloud Imaging and Particle Size satellite instrumentNear‐global coverage at 50–55 km altitude for waves with horizontal wavelength from 15 to 600 km and vertical wavelength longer than 15 kmNew data fill key spatial and temporal gaps in current record and are particularly relevant to vertical propagation of gravity waves This paper describes a new data set from the Cloud Imaging and Particle Size instrument on the NASA Aeronomy of Ice in the Mesosphere satellite. The data set can be used to infer atmospheric gravity waves at an altitude of 50‐55 km. Several examples of gravity waves are shown, including waves associated with the Andes Mountains, island topography, convection, the polar night jet, and the tropospheric jet stream. Gravity wave signatures in the new data set are shown to agree well with near‐coincident but lower altitude measurements from the satellite‐based Atmospheric Infrared Sounder. Results suggest the power of combining the new data with measurements from other instruments to investigate gravity wave filtering and vertical propagation. This data set opens new areas of inquiry, enabling comprehensive investigations of gravity waves in the middle atmosphere on a near‐global scale. Such studies are important because gravity waves drive the circulation in the middle and upper atmosphere, thereby impacting global atmospheric structure, composition, and variability.

From 2007 to 2013, the globally averaged mole fraction of methane in the atmosphere increased by 5.7?±?1.2?ppb?yr-1. Simultaneously, d13CCH4(a measure of the 13C/12C isotope ratio in methane) has shifted to significantly more negative values since 2007. Growth was extreme in 2014, at 12.5?±?0.4?ppb, with a further shift to more negative values being observed at most latitudes. The isotopic evidence presented here suggests that the methane rise was dominated by significant increases in biogenic methane emissions, particularly in the tropics, for example, from expansion of tropical wetlands in years with strongly positive rainfall anomalies or emissions from increased agricultural sources such as ruminants and rice paddies. Changes in the removal rate of methane by the OH radical have not been seen in other tracers of atmospheric chemistry and do not appear to explain short-term variations in methane. Fossil fuel emissions may also have grown, but the sustained shift to more 13C-depleted values and its significant interannual variability, and the tropical and Southern Hemisphere loci of post-2007 growth, both indicate that fossil fuel emissions have not been the dominant factor driving the increase. A major cause of increased tropical wetland and tropical agricultural methane emissions, the likely major contributors to growth, may be their responses to meteorological change. Atmospheric methane, which is a powerful greenhouse gas, is increasing rapidly. In the 20th century, methane growth was primarily driven by emissions from fossil fuel sources, such as the natural gas industry and coal mining. Then, in the early years of the 21st century, came a period of stability in methane. However, since 2007, growth has resumed, with especially strong growth in 2014. Evidence from carbon isotopes implies that the primary cause of the new growth is an increase in biogenic emissions, probably from wetlands and also agricultural sources, such as rice fields and cattle. The evidence presented in this research study, from a wide range of measurement sites both in the northern and southern hemispheres, suggests increased tropical emissions, for example from tropical wetlands, may be a principal cause of the global rise in methane. Contributions to the growth may also come from agricultural sources and perhaps some fossil fuel emissions also. Atmospheric methane is growing rapidlyIsotopic evidence implies that the growth is driven by biogenic sourcesGrowth is dominated by tropical sources

Current feeding systems for goats estimate the energy and protein requirements for pregnancy using data from sheep. The objective of this study was to predict the NE and net protein requirements for pregnancy in goats carrying single and twin fetuses and to compare these requirements with those of sheep. Data were compiled from 2 studies with dairy goats and 3 studies with sheep. These studies measured the energy content (EC) and protein content (PC) of the gravid uterus and of the mammary gland using the comparative slaughter technique. The current study was performed as a meta-analysis using an exponential model, comparing species (sheep versus goats) and litter size (single versus twin) from 50 to 140 d of pregnancy. Total EC and total PC in the gravid uterus were similar in goats and sheep carrying a single fetus. Energy and protein contents of the gravid uterus of sheep carrying twins were, on average, 29% greater than that of goats with twins from 80 to 140 d of pregnancy. During pregnancy, EC and PC of the mammary gland in goats carrying singles and twins were, on average, greater than those of sheep by 9 and 24%, respectively, for EC and by 25% for PC for both litter sizes. In conclusion, the gravid uterus and the mammary gland of goats and sheep require different amounts of energy and protein. Sheep carrying twins have the greatest daily NE and net protein requirements for pregnancy followed by goats carrying twins and both species carrying a single fetus. Therefore, it is inappropriate to adopt data from sheep to predict the net pregnancy requirements of goats, and the results found in this study could be relevant to the nutritional management of dairy goats.

Agriculture in India and other Asian countries is facing multiple and complex challenges which are expected to become more severe with the passage of time. Some of the major challenges are sustainability of natural resources, impact of climate change and decline in factor of productivity. Besides, the declining trend in size of land holding poses a serious challenge to the profitability and sustainability of farming. In view of the decline in per capita availability of land, it is imperative to develop strategies and agricultural technologies that enable adequate employment and income generation, especially for small-holders (farmers with <2.0ha of land) who constitute the vast majority of the farming community in the developing world. No single farm enterprise, such as a typical mono-cropping system, is likely to be able to sustain the small-holder farmer. Integrated farming systems (IFS) are less risky if managed efficiently, as they benefit from synergisms among enterprises, diversity in produce, and environmental soundness. On this basis, IFS have been suggested for the development of small and marginal farms across Asia, and researchers have developed strategies which have benefited small-holder farmers by providing additional income and employment and minimizing risk. However, these IFS have not been promulgated and promoted effectively. The present review helps to remedy this by providing comprehensive information on the concepts and advantages of IFS for small-holder farmers, which is lacking at present. The review covers the key literature on farming systems and allied aspects published over the period 1970–2015.

Three experiments were conducted with broiler chickens to evaluate the effects of digestible total sulphur amino acid (TSAA) on their performance at three different phases of starter (1–14 d), grower (15–28 d) and finisher (29–42 d). The measured traits included: average daily gain (ADG), feed intake, feed conversion ratio (FCR), carcass protein, body lipid (BL), feather weight gain, carcass plus feather protein, carcass TSAA deposition and nitrogen excretion (NE). A dilution technique was used to create seven diets (with eight replicates) increasing the TSAA content from 2.5 to 9.04 g/kg of diet for starter, 2.26 to 8.14 g/kg of diet for grower and 2.08 to 7.5 g/kg of diet for finisher. Data measured were imported to neural networks to predict the measured traits in response to dietary and intake levels of TSAA and find the optimal levels of TSAA that lead to the desired responses. Optimization results showed decreases in optimal dietary TSAA values with increasing age for all traits, while reverse was observed for intake values and requirements were increased as birds aged. The highest TSAA requirement (7.95, 7.2 and 6.6 g/kg and 283, 585 and 1150 mg/bird per d for starter, grower and finisher, respectively) were achieved for minimum BL and lowest (5.8, 5.2 and 4.9 g/kg and 201, 444 and 873 mg/bird per d for starter, grower and finisher, respectively) were suggested for minimum NE. Based on intake models, the optimal TSAA values for minimum FCR in phases 1–3 were 283, 585 and 1150 mg/bird per d while maximum ADGs were achieved with 201, 444 and 873 mg/bird per d of TSAA.

Four novel growth functions, namely, Pareto, extreme value distribution (EVD), Lomolino, and cumulative β-Pdistribution (CBP), are derived, and their ability to describe ostrich growth curves is evaluated. The functions were compared with standard growth equations, namely, the monomolecular, Michaelis-Menten (MM), Gompertz, Richards, and generalized MM (gMM). For this purpose, 2 separate comparisons were conducted. In the first, all the functions were fitted to 40 individual growth curves (5 males and 35 females) of ostriches using nonlinear regression. In the second, performance of the functions was assessed when data from 71 individuals were composited (570 data points). This comparison was undertaken using nonlinear mixed models and considering 3 approaches: 1) models with no random effect, 2) random effect incorporated as the intercept, and 3) random effect incorporated into the asymptotic weight parameter (Wf). The results from the first comparison showed that the functions generally gave acceptable values of R2and residual variance. On the basis of the Akaike information criterion (AIC), CBP gave the best fit, whereas the Gompertz and Lomolino equations were the preferred functions on the basis of corrected AIC (AICc). Bias, accuracy factor, the Durbin-Watson statistic, and the number of runs of sign were used to analyze the residuals. CBP gave the best distribution of residuals but also produced more residual autocorrelation (significant Durbin-Watson statistic). The functions were applied to sample data for a more conventional farm species (2 breeds of cattle) to verify the results of the comparison of fit among functions and their applicability across species. In the second comparison, analysis of mixed models showed that incorporation of a random effect into Wfgave the best fit, resulting in smaller AIC and AICcvalues compared with those in the other 2 approaches. On the basis of AICc, best fit was achieved with CBP, followed by gMM, Lomolino, and Richards functions, respectively. The exponential, MM, Pareto, and EVD equations produced negative values for initial weight (W0) if left unconstrained. The Gompertz equation, in spite of having a fixed inflection point and therefore being less flexible, gave accurate estimates of both W0and Wfand an acceptable goodness of fit favored by having fewer parameters than the other sigmoidal functions. Nevertheless, all the sigmoidal functions appeared appropriate in describing the growth trajectory of male and female ostriches to a reasonable level of accuracy.

The use of stable 15N as a marker to determine microbial contamination in nylon bag incubation residues to estimate protein degradability was investigated. Three methods using 15N were compared: 15N-labeled forage (dilution method, LF), 15N enrichment of rumen solids-associated bacteria (SAB), and 15N enrichment of rumen liquid-associated bacteria (LAB). Herbage from forages differing in protein and fiber contents (early-cut Italian ryegrass, late-cut Italian ryegrass, and red clover) were freeze-dried and ground and then incubated in situ in the rumen of 3 steers for 3, 6, 12, 24, and 48 h using the nylon bag technique. The 15N-labeled forages were obtained by fertilizing the plots where herbage was grown with 15NH415NO3. Unlabeled forages (obtained from plots fertilized with NH4NO3) were incubated at the same time that (15NH4)2SO4was continuously infused into the rumen of the steers, and then pellets of labeled SAB and LAB were isolated by differential centrifugation of samples of ruminal contents. The proportion of bacterial N in the incubation residues increased from 0.09 and 0.45 g bacterial N/g total N at 3 h of incubation to 0.37 and 0.85 g bacterial N/g total N at 48 h of incubation for early-cut and late-cut ryegrass, respectively. There were differences (P< 0.001) between uncorrected N degradability values and those corrected for microbial contamination with all of the methods. Apparent N degradability of the low-N, high-fiber forage (late-cut ryegrass) was 0.51, whereas the corrected values were 0.85, 0.84, and 0.77 for the LF, SAB, and LAB methods, respectively. With early-cut ryegrass and red clover, the differences between uncorrected and corrected values ranged between 6% and 13%, with small differences among the labeling methods. Generally, methods using labeled forage or labeled SAB and LAB provided similar corrected degradability values. The accuracy in estimating the extent of degradation of protein in the rumen from in situ disappearance curves is improved when values are corrected for microbial contamination of the bag residue.

In the present study, neural networks (NN) were developed to investigate the responses (average daily gain [ADG] and feed efficiency [FE]) of broiler chicks to protein and two amino acids (AA), namely methionine (Met) and tryptophan (Trp). Separate NN models were constructed for responses to protein and Met and protein and Trp. Comparisons between NN and response surface models revealed higher accuracy of prediction with the NN models. The relative importance of the input variables (protein and AA) on model output (ADG and FE) was assessed using a sensitivity analysis technique. Results indicated that dietary protein is a more important variable than AA (Met and Trp). Optimal values of the input variables (protein and AA) required to maximize ADG and FE in were obtained by subjecting all constructed NN to an optimization algorithm. The optimization algorithm for the protein and Met response models revealed that diets containing 216 g/kg of protein and 5.45 g/kg of Met lead to maximum ADG, whereas maximum FE is achieved with diets containing 222.6 and 5.85 g/kg of protein and Met, respectively. The optimization algorithm for protein and Trp responses showed that 234 g/kg of protein and 2.6 g/kg of Trp in the diet lead to maximum ADG, while maximum FE is achieved with diets containing 240 g/kg of protein and 3.1 g/kg Trp. The optimization results therefore suggest that protein and AA requirements for maximum FE are higher than for maximum ADG.

The minerals Cu, Mo, and S are essential for metabolic functions related to cattle health and performance. The interaction between Cu, Mo, and S can determine the utilization of each mineral, in particular Cu, by ruminants. A meta-analysis was performed to evaluate the effects of dietary Cu, Mo, and S and their interactions on plasma and liver Cu, ADG, and G:F in growing-finishing cattle. Data were collated from 12 published studies. The model with the best fit to data indicated plasma Cu was positively affected by dietary Cu (P< 0.01) and negatively affected by both dietary Mo (P< 0.01) and S (P< 0.01). Another model also indicated that plasma Cu concentration is positively related to Cu:Mo ratio in the diet (P< 0.01). Dietary Cu had a positive effect on liver Cu (P< 0.01), whereas Mo showed a negative effect (P< 0.05), and no effect of dietary S on liver Cu was observed (P> 0.05). Average daily gain was negatively affected by dietary Mo (P< 0.05) and S (P< 0.01) and positively affected by Cu:Mo ratio (P< 0.01), likely because an increased Cu:Mo ratio minimizes the antagonistic effect of Mo on Cu. The feed conversion ratio was negatively affected by Mo (P< 0.05) and S (P< 0.01), whereas effects of the Cu:Mo ratio and dietary Cu were not significant (P> 0.05). The interaction between S and Mo affected (P< 0.01) G:F, which was likely related to a positive response with the proper balance between these minerals. In conclusion, dietary Cu, Mo, and S and the Cu:Mo ratio caused changes in plasma Cu. Only dietary Mo and S led to a negative response in the performance of growing-finishing cattle, whereas the diet Cu:Mo ratio has a linear and quadratic effect on ADG. Nutritionists and producers need to consider with caution the supplementation of growing-finishing cattle diets with Mo and S because of their potentially adverse effects on animal performance. An appropriate Cu:Mo ratio is desirable to minimize the effects of an impaired supply of Mo on Cu metabolism and ADG.

A generic daily time-step model of animal growth and metabolism for cattle and sheep is described. It includes total BW as well as protein, water, and fat components, and also energy components associated with the growth of protein and fat, and activity costs. Protein decay is also incorporated, along with the energy costs of resynthesising degraded protein. Protein weight is taken to be the primary indicator of metabolic state, and fat is regarded as a potential source of metabolic energy for physiological processes such as the resynthesis of degraded protein. Normal weight is defined as maximum protein and the associated fat component so that if the BW of the animal exceeds the normal value, all excess weight is in the form of fat. It is assumed that the normal fat fraction increases from birth to maturity. There are relatively few parameters, all of which have a reasonable physiological interpretation, which helps simplify choosing parameters for different animal types and breeds. Simulations for growing and mature cattle and sheep in response to varying available ME are presented and comparisons with empirical curves reported in the literature for body composition are in excellent agreement.

Monensin is a common feed additive used in various countries, where 1 of the associated benefits for use in beef cattle is improved efficiency of energy metabolism by the rumen bacteria, the animal, or both. Modeling fermentation-altering supplements is of interest, and thus, it is the purpose of this paper to quantify the change in VFA profile caused by monensin dose in high-grain-fed beef cattle. The developmental database used for meta-analysis included 58 treatment means from 16 studies from the published literature, and the proportional change in molar acetate, propionate, and butyrate (mol/100 mol) as well as total VFA (mM) with monensin feeding dose (mg/kg DM, concentration in the feed) was evaluated using the MIXED procedure (SAS Inst. Inc., Cary, NC) with the study treated as a random effect. The mean monensin dose in the literature database was 30.9 ± 3.70 mg/kg DM and ranged from 0.0 to 88.0 mg/kg DM. Mean DMI was 7.8 ± 0.26 kg DM/d, mean concentrate proportion of the diet was 0.87 ± 0.01, and mean treatment period was 42 ± 5.6 d. Results produced the following equations: proportional change in acetate (mol/100 mol) = -0.0634 (± 0.0323) × monensin (mg/kg DM)/100 (P = 0.068), proportional change in propionate (mol/100 mol) = 0.260 (± 0.0735) × monensin (mg/kg DM)/100 (P = 0.003), and proportional change in butyrate (mol/100 mol) = -0.335 (± 0.0916) × monensin (mg/kg DM)/100 (P = 0.002). The change in total VFA was not significantly related to monensin dose (P = 0.93). The results presented here indicate that the shift in VFA profile may be dose dependent, with increasing propionate and decreasing acetate and butyrate proportions (mol/100 mol). These equations could be applied within mechanistic models of rumen fermentation to represent the effect of monensin dose on the VFA profile in high-grain-fed beef cattle.

The objective of this study was to develop a framework describing the milk production curve in sows as affected by parity, method of milk yield (MY) determination, litter size (LS), and litter gain (LG). A database containing data on LS, LG, dietary protein and fat content, MY, and composition measured on more than 1 d during lactation and method for determining MY from peer reviewed publications and individual sow data from 3 studies was constructed. A Bayesian hierarchical model was developed to analyze milk production data. The classical Wood curve was used to model time trends in MY during lactation, and it was re-parameterized expressing the natural logarithm of MY values at d 5, 20, and 30 as functional parameters. The model incorporated random effects of experiment, sow nested within experiment, and fixed effects of LS, LG, parity, and method through the functional parameters of the Wood curve. A second set of models were constructed to analyze milk composition data, including day in milk, LS, dietary protein, and fat contents. Four scenarios with different LG and LS were constructed using the framework to estimate the energy output in milk at different days during lactation. The estimated energy output was compared with energy output values calculated using the 1998 NRC method. Milk yield was underestimated by approximately 20% with the weigh-suckle-weigh technique compared with the deuterium oxide dilution technique (P < 0.001). The mean LG and LS for the dataset were 2.05 kg/d (1.0; 3.3) and 9.5 piglets (5; 14), respectively. The MY was affected by LS on d 5 and 20 (P < 0.001) and by LG on d 20 (P < 0.001) and d 30 (P = 0.004). The mean time to peak lactation was 18.7 d (SD = 1.06) postpartum and mean MY at peak lactation was 9.23 kg (SD = 0.14). The average protein, lactose, and fat content of milk was 5.22 (SD = 0.06), 5.41 (SD = 0.08), and 7.32% (SD = 0.17%), respectively. The NE requirement for lactation increased from d 5 to 20 because of increased MY. Requirements also increased with increasing LG and LS. The framework could be used to predict energy and protein requirements for lactation under different production expectations and can be incorporated into a whole animal model for determination of energy and nutrient requirements for lactating sows, which can optimize sow performance and longevity.

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 32P 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 32P 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.

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.

The objective of this study was to evaluate the relationships between chewing behavior, digestibility, and digesta passage kinetics in steers fed oat hay at restricted and ad libitum intakes. Four Hereford steers, with an initial average BW of 136 kg, were used in an experiment conducted as a balanced 4 × 4 Latin square with 4 treatments (levels of intake) and 4 periods. Animals were fed lopsided oat hay (Avena strigosaSchreb.) at 4 levels of intake (as a percentage of BW): 1.5, 2.0, 2.5, and ad libitum. Digestibility, chewing behavior, and digesta passage kinetic measurements were recorded during the experimental period. Chewing rates during eating and ruminating [(chews∙min−1)/g of DMI∙kg−1of BW∙d−1] decreased (P= 0.018 and P= 0.032, respectively) with increased DMI (g∙kg−1of BW∙d−1), whereas total chewing and total time spent on each chewing activity increased. Calculated total energy expended by the chewing activity was 4.2, 4.4, 5.2, and 5.3% of ME intake for DMI of 1.5, 2.0, and 2.5% of BW and ad libitum, respectively, indicating that adjustments in animal chewing behavior may be a mechanism of reducing energy expenditure when forages are fed at restricted intake. Hay digestibility decreased (P< 0.001) with increased DMI (r = −0.865). Digesta mean retention time (h) was strongly correlated with DMI (r = −0.868) and OM digestibility (r = 0.844). At reduced intake, hay digestibility was enhanced (P< 0.001) by extending digesta retention time and by increasing chewing efficiency, highlighting the relationship between chewing behavior and the digestive process. Fractional outflow rate of particulate matter from the reticulorumen (k1) was positively correlated with total chews, emphasizing that the decrease in particle size caused by chewing facilitates particle flow through the digestive tract. Increased hay intake also increased (P< 0.001) k1, whereas passage rate of the liquid phase, transit time, and rumen fill were not affected (P> 0.05). The latter was correlated with rumen volume (r = 0.803). In conclusion, the results of this study indicate that animals fed at restricted intake increased chewing rate when eating and ruminating, which, along with a longer digesta retention time, contributed to enhance feed digestibility.

Mathematical modeling techniques have been applied to study various aspects of the ruminant, such as rumen function, postabsorptive metabolism, and product composition. This review focuses on advances made in modeling rumen fermentation and its associated rumen disorders, and energy and nutrient utilization and excretion with respect to environmental issues. Accurate prediction of fermentation stoichiometry has an impact on estimating the type of energy-yielding substrate available to the animal, and the ratio of lipogenic to glucogenic VFA is an important determinant of methanogenesis. Recent advances in modeling VFA stoichiometry offer ways for dietary manipulation to shift the fermentation in favor of glucogenic VFA. Increasing energy to the animal by supplementing with starch can lead to health problems such as subacute rumen acidosis caused by rumen pH depression. Mathematical models have been developed to describe changes in rumen pH and rumen fermentation. Models that relate rumen temperature to rumen pH have also been developed and have the potential to aid in the diagnosis of subacute rumen acidosis. The effect of pH has been studied mechanistically, and in such models, fractional passage rate has a large impact on substrate degradation and microbial efficiency in the rumen and should be an important theme in future studies. The efficiency with which energy is utilized by ruminants has been updated in recent studies. Mechanistic models of N utilization indicate that reducing dietary protein concentration, matching protein degradability to the microbial requirement, and increasing the energy status of the animal will reduce the output of N as waste. Recent mechanistic P models calculate the P requirement by taking into account P recycled through saliva and endogenous losses. Mechanistic P models suggest reducing current P amounts for lactating dairy cattle to at least 0.35% P in the diet, with a potential reduction of up to 1.3 kt/yr. A model that integrates nutrient utilization and health has great potential benefit for ruminant nutrition research. Finally, whole-animal or farm level models are discussed. An example that used a multiple-criteria decision-making framework is reviewed, and the approach is considered to be appropriate in dealing with the multidimensional nature of agricultural systems and can be applied to assist the decision process in cattle operations.

Canada is committed to reducing its greenhouse gas emissions to 6% below 1990 amounts between 2008 and 2012, and methane is one of several greenhouse gases being targeted for reduction. Methane production from ruminants is one area in which the agriculture sector can contribute to reducing our global impact. Through mathematical modeling, we can further our understanding of factors that control methane production, improve national or global greenhouse gas inventories, and investigate mitigation strategies to reduce overall emissions. The purpose of this study was to compile an extensive database of methane production values measured on beef cattle, and to generate linear and nonlinear equations to predict methane production from variables that describe the diet. Extant methane prediction equations were also evaluated. The linear equation developed with the smallest root mean square prediction error (RMSPE, % observed mean) and residual variance (RV) was Eq. I: CH4, MJ/d = 2.72 (±0.543) + [0.0937 (±0.0117) × ME intake, MJ/d] + [4.31 (±0.215) × Cellulose, kg/d] − [6.49 (±0.800) × Hemicellulose, kg/d] − [7.44 (±0.521) × Fat, kg/d] [RMSPE = 26.9%, with 94% of mean square prediction error (MSPE) being random error; RV = 1.13]. Equations based on ratios of one diet variable to another were also generated, and Eq. P, CH4, MJ/d = 2.50 (±0.649) − [0.367 (±0.0191) × (Starch:ADF)] + [0.766 (±0.116) × DMI, kg/d], resulted in the smallest RMSPE values among these equations (RMSPE = 28.6%, with 93.6% of MSPE from random error; RV = 1.35). Among the nonlinear equations developed, Eq. W, CH4, MJ/d = 10.8 (±1.45) × (1 − e[−0.141 (±0.0381) × DMI, kg/d]), performed well (RMSPE = 29.0%, with 93.6% of MSPE from random error; RV = 3.06), as did Eq. W3, CH4, MJ/d = 10.8 (±1.45) × [1 − e{− [−0.034 × (NFC/NDF) + 0.228] × DMI, kg/d}] (RMSPE = 28.0%, with 95% of MSPE from random error). Extant equations from a previous publication by the authors performed comparably with, if not better than in some cases, the newly developed equations. Equation selection by users should be based on RV and RMSPE analysis, input variables available to the user, and the diet fed, because the equation selected must account for divergence from a “normal” diet (e.g., high-concentrate diets, high-fat diets).

The mammalian target of rapamycin (mTOR) plays key roles in cellular metabolism and hypertrophic-hyperplasic growth, and it acts as a central regulator of protein synthesis and ribosome biogenesis at the transcriptional and translational levels by sensing and integrating signals from mitogens and nutrients. Hormonal and stress factors can affect the mTOR-signaling pathway via their receptors and signal transduction pathways. Nutritional regulation of the mTOR-signaling pathway is mediated by their corresponding plasma membrane transporters, other unknown mechanisms, or both. Adenine monophosphate-activated protein kinase, an important cellular energy sensor, can interact with the mTOR-signaling pathway to maintain cellular energy homeostasis. Interactions of mTOR with regulatory-associated protein of TOR or rapamycin-insensitive companion of mTOR result in 2 mTOR complexes, with the former (mTOR complex-1) being the primary controller of cell growth and the latter (mTOR complex-2) mediating effects that are insensitive to rapamycin, such as cytoskeletal organization. Upstream elements of the mTOR-signaling pathway include Ras-homolog enriched in brain, and tuberous sclerosis complex 1 and 2, with tuberous sclerosis complex 2 as the linker between phosphatidylinositol 3-kinase/protein kinase B or Ras-Raf-mitogen-activated protein kinase-extracellular signal-regulated protein kinase pathways and the mTOR pathway. Ribosomal protein S6 protein kinase 1 and eukaryotic initiation factor 4E binding protein 1 are currently the 2 best-known downstream effectors of mTOR signaling. Hormonal factors, stressors, and nutrients can differentially mediate cellular metabolism and growth via the mTOR pathway with effectors specific to the organ or tissue types involved.

Success of pig production depends on maximizing return over feed costs and addressing potential nutrient pollution to the environment. Mathematical modeling has been used to describe many important aspects of inputs and outputs of pork production. This study was undertaken to compare 4 mathematical functions for the best fit in terms of describing specific data sets on pig growth and, in a separate experiment, to compare these 4 functions for describing of P utilization for growth. Two data sets with growth data were used to conduct growth analysis and another data set was used for P efficiency analysis. All data sets were constructed from independent trials that measured BW, age, and intake. Four growth functions representing diminishing returns (monomolecular), sigmoidal with a fixed point of inflection (Gompertz), and sigmoidal with a variable point of inflection (Richards and von Bertalanffy) were used. Meta-analysis of the data was conducted to identify the most appropriate functions for growth and P utilization. Based on Bayesian information criteria, the Richards equation described the BW vs. age data best. The additional parameter of the Richards equation was necessary because the data required a lower point of inflection (138 d) than the Gompertz, with a fixed point of inflexion at 1/e times the final BW (189 d), could accommodate. Lack of flexibility in the Gompertz equation was a limitation to accurate prediction. The monomolecular equation was best at determining efficiencies of P utilization for BW gain compared with the sigmoidal functions. The parameter estimate for the rate constant in all functions decreased as available P intake increased. Average efficiencies during different stages of growth were calculated and offer insight into targeting stages where high feed (nutrient) input is required and when adjustments are needed to accommodate the loss of efficiency and the reduction of potential pollution problems. It is recommended that the Richards and monomolecular equations be included in future growth and nutrient efficiency analyses.

Many studies have highlighted concerns over current methods of determining endogenous P losses and P requirements in growing pigs. Therefore, a database containing observations on 350 pigs was assembled from various studies. Four functions for analyzing P balance data were considered: 1) a straight line, 2) a diminishing returns function (monomolecular), 3) a sigmoidal function with a fixed point of inflection (Gompertz), and 4) a sigmoidal function with a flexible point of inflection (Richards). The nonlinear functions were specifically reparameterized to assign biological meaning to the parameters. Meta-analysis of the data was conducted to estimate endogenous P excretion, maintenance requirement, and efficiency of utilization. Phosphorus retention was regressed against either available P intake or total P intake [all variables scaled by metabolic BW (BW0.75)]. There was evidence of non-linearity in the data, and the monomolecular function provided the best fit to the data. The Richards equation did not fit the data well and appeared overparameterized. Estimates of endogenous P excretion of 14 and 17 mg/kg of BW0.75· d based on available and total P analysis, respectively, were predicted by the monomolecular equation, which were within the range reported in the literature. Maintenance requirement values of 15 mg of available P/kg of BW0.75· d and 37 mg of total P/kg of BW0.75· d were obtained, based on the monomolecular equation. Average efficiencies of conversion of dietary P to retained P were 65 and 36% for available and total P, respectively, with greater efficiency values calculated for low P intakes. Although the monomolecular equation fitted the data best, more observations at high P intakes/kg of BW0.75are required to determine conclusively whether P retention scaled by metabolic BW is linearly related to available or total P intake.

The objective of the study was to revise a model of P kinetics proposed by Vitti et al. (2000)and extend its use to study Ca flows in growing sheep. Twelve Santa Ines male sheep, 8 mo of age, with average BW of 31.6 kg were injected with 32P and 45Ca to trace the movement of P and Ca in the body. The original model had 4 pools representing the gut, plasma, soft tissues, and bone. In the revised model, instantaneous values rather than averages for pool derivatives were incorporated, and the model was extended to represent absorption and excretion of phytate P explicitly. The amendments improved the model, resulting in higher flows between plasma and bone than between plasma and tissue and, therefore, a more accurate representation of P metabolism. Phosphorus and Ca metabolism were then assessed conjointly using the revised model. The results showed that P and Ca metabolism are closely related as evidenced by the ratio of these minerals in the bidirectional flows between plasma and bone and between plasma and tissue. Phytate P digestibility was 47%, and P retention was negative (−1.4 g/d), suggesting that a feed characteristic impaired P utilization and led to P deficiency. The revised model provides an improved prediction of P and Ca metabolism that can be used to assess mineral requirements and to estimate losses to the environment.

Small-scale dairy systems play an important role in the Mexican dairy sector and farm planning activities related to resource allocation have a significant impact on the profitability of such enterprises. Linear programming is a technique widely used for planning and ration formulation, and partial budgeting is a technique for assessing the impact of changes on the profitability of an enterprise. This study used both methods to optimise land use for forage production and nutrient availability, and to evaluate the economic impact of such changes in small-scale Mexican dairy systems. The model showed satisfactory performance when optimal solutions were compared with the traditional strategy. The strategy using fresh ryegrass, maize silage and oat hay, and the strategy using a combination of alfalfa hay, maize silage, fresh ryegrass and oat hay appeared attractive options for providing a better nutrient supply and maintaining a higher stocking rate throughout the year than the traditional strategy.

The kidney is believed to play a major role in the clearance of apoA-I (apolipoprotein A-I) and HDL (high-density lipoprotein) particles from the bloodstream. Proximal tubule epithelial cells of the kidney appear to prevent the loss of these proteins in the urine by re-absorbing them from the urinary filtrate. Experiments were undertaken to investigate the factors that regulate the renal re-absorption of apoA-I and small HDL in a transformed human proximal tubule epithelial (HKC-8) cell line. Fluorescent microscopic studies show that HKC-8 cells can readily bind and take up HDL particles. Intracellular localization of fluorescently labelled native HDL shows its accumulation in endocytotic vesicles, in a perinuclear region after 1 h. Binding studies reveal a saturable cell association of 125I-HDL with the HKC-8 cell surface after 2 h. HKC-8 cells do not degrade apoA-I or other HDL-apoproteins. The specific cell association of lipid-free apoA-I is approx. 2-fold less than that observed for native HDL. Similarly, reconstituted HDL prepared from HDL-apoproteins and pure phospholipids also exhibits a low cell association with the HKC-8 cells. In contrast, reconstituted HDL prepared with the extracted lipids of HDL and pure apoA-I exhibits an even higher cell association than that observed with the native lipoprotein. A detailed characterization of the major lipid classes in reconstituted HDL shows that only cholesteryl ester increases the cell association of the recombinant particles. These results show that the cholesteryl ester content of HDL may play an important role in the re-absorptive salvage of HDL by the proximal tubule cells of the kidney.

A method is proposed to determine the extent of degradation in the rumen involving a two-stage mathematical modeling process. In the first stage, a statistical model shifts (or maps) the gas accumulation profile obtained using a fecal inoculum to a ruminal gas profile. Then, a kinetic model determines the extent of degradation in the rumen from the shifted profile. The kinetic model is presented as a generalized mathematical function, allowing any one of a number of alternative equation forms to be selected. This method might allow the gas production technique to become an approach for determining extent of degradation in the rumen, decreasing the need for surgically modified animals while still maintaining the link with the animal. Further research is needed before the proposed methodology can be used as a standard method across a range of feeds.

Improving N utilization in dairy cows and especially reducing N output in excreta is desirable due to global concerns of agricultural contribution of N to environmental pollution, particularly as ammonia. Data from five N balance experiments were used to develop a dynamic model that was evaluated with independent data. Model predictions of feces, urine, and milk outputs were close to observed values. Statistical analysis showed that 96% of mean square prediction error for feces and urine N output predictions was due to random variation. However, the model tends to overpredict milk N output, especially at higher N intake levels. Evaluation of model predictions for independent experimental observations from Agricultural Development Advisory Service at Bridgets (U.K.) showed good agreement between predicted and observed urine N output (95% due to random variation). However, there was a slight underprediction for fecal N output (14% mean square prediction error due to bias) and overprediction of milk N output (22% of mean square prediction error due to bias). The model predictions of N outputs in excreta were sensitive to changes in energy concentration of the diet. Dietary protein degradability had only a small influence on predicted fecal N output. However, the model was sensitive in its predictions of urine N when protein degradability was varied. Application of the model to assess reduction in ammonia emissions from dairy cows showed that increasing the energy concentration could potentially reduce ammonia emissions by up to 25% per cow. Similarly, reducing CP concentration in the diet to about 16% could reduce ammonia production by 20% and lower degradability of CP to match microbial requirement by 19% per cow. The model is a first step toward a mechanistic approach of nutrient modeling, and it is a valuable method for predicting N excretions and estimating N emissions from dairy systems.

Previous efforts to simulate mammary metabolism have focused on energy, mostly considering amino acids (AA) in aggregate. The main objective of this work was to build a model of mammary metabolism, based on data from arterio-venous difference studies, which considered AA in sufficient detail to predict yields of milk solids. The model contains 19 state variables and considers the removal of 37 metabolites from blood, including 22 AA. It is driven by blood flow and arterial concentrations, and outputs include milk protein, milk lactose, and three classes of milk fat (by chain length). The model was parameterized using a balance version of it and the mean observations from four arterio-venous difference experiments, with a limited number of assumptions, and evaluated against these experiments. In assembling the balance model, milk protein output was not predicted satisfactorily, as some essential AA were not present in quantities great enough to support the rates of milk protein synthesis observed experimentally. Tryptophan showed the greatest deficit, followed by tyrosine plus phenyl-alanine, methionine, and histidine. In addition, significant quantities of pyruvate were needed to synthesize serine, glycine, and alanine. The supply of α-ketoglutarate plus glutamate to synthesize proline and glutamine was provided in part by catabolism of arginine; the remainder was derived from catabolism of other AA and energetic substrates.

One of the major contributions to atmospheric pollution comes from nitrogen (N) derived from cattle and especially dairy cows. Although most estimates of ammonia volitilization are based on total N excretion, it has been repeatedly shown that urinary N is a much more important source of pollution than faecal N, specially under grazing conditions. A model was developed to predict the amount and form of N excreted under different production systems. Analysis of N pollution was based on data collected from Holstein/Friesian cows fed 30 different diet types consisting of 10 grass silages and 6 concentrates. While there was a strong correlation between N intake and N output in general, urinary N was exponentially correlated with N intake and the model predicted about 80% loss of N in urine for levels of N consumption above 500 g N/d. On the other hand, outputs of faecal and milk N increased by less than 20% per unit increase in N intake. Model predictions also agreed well with published data and provided reasonable estimates of the form in which N was excreted. Concentrate composition with respect to energy type and its degradation and protein degradability and silage type had significant effects on the amount and form of N excreted. It is concluded that N pollution may be ameliorated by using grass grown with moderate fertiliser application, and maize-based energy supplements, formulated to provide low degradable protein and with N intakes of less than 400 g/d for average yielding cows.

Dietary intervention to reduce methane emissions from lactating dairy cattle is both environmentally and nutritionally desirable due to the importance of methane as a causative agent in global warming and as a significant loss of feed energy. Reliable prediction systems for methane production over a range of dietary inputs could be used to develop novel dietary regimes for the limitation of feed energy loss to methane. This investigation builds on previous attempts at modeling methanogenesis and involves the development of a dynamic mechanistic model of wholerumen function. The model incorporates modifications to certain ruminal fermentation parameters and the addition of a postruminal digestive element. Regression analysis showed good agreement between observed and predicted results for experimental data taken from the literature (r2= 0.76, root mean square prediction error = 15.4%). Evaluation of model predictions for experimental observations from five calorimetry studies (67 observations) with lactating dairy cows at the Centre for Dairy Research, in Reading, U.K., shows an underprediction (2.1 MJ/d) of methane production (r2= 0.46, root mean square prediction error = 12.4%). Application of the model to develop diets for minimizing methanogenesis indicated a need to limit the ratio of lipogenic to glucogenic VFA in the rumen and hindgut. This may be achieved by replacing soluble sugars in the concentrate with starch or substituting corn silage for grass silage. On a herd basis, the model predicted that increasing dietary energy intake per cow can minimize the annual loss of feed energy through methane production. The mechanistic model is a valuable tool for predicting methane emissions from dairy cows.

To eliminate unnecessary feeding trials, a mechanistic model of sugarcane digestion was used in the search for suitable supplements to improve milk production. Milk production simulated by the model was compared with data observed in four feeding trials published in the tropical literature where crossbred dairy cows were fed sugarcane/urea diets with different types of supplements. The predicted effects of the supplements on the ruminal microbial population, concentrations of ammonia and volatile fatty acids were also compared with the published results in one experiment. The model indicated the nutrient most limiting milk production for the different feeding situations. The addtion of Leucaenato the basal sugarcane/urea improved the availability of amino acids and long-chain fatty acids, with energy becoming the limiting factor. Supplementation with rice bran increased the availability of energy and long-chain fatty acids, but amino acids then became the limiting factor. Supplementation with both Leucaenaand rice bran further improved the milk yield, but availability of energy now limited milk production. Supplementation with Leucaenaincreased milk production more than supplementation with king grass. The main reason for this increase was increased amino acid absorption due to increased microbial outflow. In all feeding situations, the average difference between the predicted milk production and that observed experimentally was 0.57 kg/d (ranging from 0.08 to 1 kg/d).

The effects of season of growth and monensin treatment on ruminal digestion of fresh-cut autumn and spring pasture were measured in a single group of ruminally fistulated castrated male sheep, housed indoors in metabolism crates. Responses were assessed in terms of ruminal volatile fatty acid molar proportions, ammonia concentration, pH, apparent digestibility of the pasture, and nitrogen balance of the animals. Blood plasma concentrations of insulin, glucose, beta-hydroxybutyrate, urea, and NEFA were also evaluated. Autumn pasture contained significantly lower proportions of water-soluble carbohydrate (P< 0.05), cellulose (P< 0.05), and lignin (P< 0.05) and increased pectin (P< 0.05), hemicellulose (P< 0.05), and crude protein (P< 0.10) concentrations when compared with spring pasture. Voluntary DMI by sheep of autumn pasture was lower (P< 0.01) than that of spring pasture and was significantly (P< 0.05) reduced by monensin treatment. Monensin treatment significantly decreased the ruminal molar proportions of acetic acid (P< 0.10) and butyric acid (P< 0.001) and increased the molar proportions of propionic acid (P< 0.001) and minor VFA (P< 0.01). Nitrogen retention of the sheep was significantly (P< 0.05) reduced by monensin treatment. Plasma glucose levels were increased (P< 0.10) by monensin treatment during the fourth 5-d collection period in both seasons. Chemical analysis suggested that the composition of autumn pasture was different from that of spring pasture and that this was manifested in vivo by increased DMI and digestibility of spring vs autumn pasture. Ruminal fermentation of autumn pasture also had an increased acetate-to-propionate ratio compared with spring pasture. Monensin treatment acted consistently across seasons by increasing the proportion of propionate and decreasing the proportion of acetate in ruminal fluid.

An experiment was conducted to examine the effect that various isoenergetic diets, containing different quantities of soluble carbohydrate and fiber and different types of starch, have on nitrogen (N) balances. Six lactating dairy cows in early to midlactation consuming grass silage diets with not less than 600 g/kg total DMI as forage were used in the experiment. Four concentrates were prepared that had higher amounts of either fiber, soluble sugars, corn (low degradable starch source), or barley (high degradable starch source). Overall N utilization by the cows was poor, rarely exceeding 0.30 g milk N/g of dietary N intake. Fecal N outputs accounted for more than half of total N excreted in all treatments except for diets supplemented with high degradable starch, in which urinary N excretion was significantly higher compared with the other treatments. Milk yield was unaffected by concentrate type, averaging 19.9 kg/d, but milk protein content decreased from 32.9 for starch-based diets to 30.9 and 30.0 g/kg for the soluble sugar- and fiber-based diets, respectively. The efficiency of N utilization improved in the low degradable starch treatment, which had lower N excretion (65%) and higher protein concentration in milk. Furthermore, feeding cows corn-based concentrates reduced urinary N excretion by almost 30% compared with barley-based concentrates; therefore, feeding corn-based diets is recommended for the reduction of nitrogen pollution in lactating dairy cows.