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Two strains of Lactobacillus combined with Baker's yeast (Saccharomyces cerevisiae) used as probiotics were evaluated to replace antibiotics in poultry flocks by reducing ammonia emissions in manure of broilers without comprising performance or health. One-day-old Cobb 500 broilers (600) were fed starter, grower, and finisher diets as control (CON); probiotic S. cerevisiae, inclusion rate at 4.26 × 106 CFU/kg of feed (SCY); probiotic L. plantarum and L. rhamnosus, inclusion rate at 4.35 × 108 CFU/kg of feed (LPR) for each; and a combination of Lactobacillus plantarum and L. rhamnosus at 4.35 × 108 CFU/kg of feed for each plus Saccharomyces cerevisiae and 4.26 × 106 CFU/kg of feed (SWL). The 4 treatments had 5 replicates (pens), each with 30 broilers. Performance was measured weekly as feed consumption, weight gain, BW, and feed conversion ratio (FCR) over a 6-wk grow-out period. Accompanying biochemical analyses included lipase activity of the pancreas, liver weight, and uric acid (UA) concentration in liver. Albumin, total protein, UA, ammonia, and blood urea nitrogen (BUN) were measured in serum. Ammonium (NH4+) in manure and apparent ileal digestibility from digesta were also measured. Significance was determined at P ≤ 0.05. Results showed that biochemical analyses had no significant treatment effect; however, there were significant temporal changes in performance measures for individual treatments. Feed consumption increased over time for all treatments (P = 2.00 × 10-16). CON had lower weight gain in wk 2 (P = 0.013) compared to all treatment and the lowest BW in wk 5 (P = 0.0008) and wk 6 (P = 0.0124) compared to SWL. Specific probiotic strains, with well-defined inclusion rates, and surrounding environmental analyses of present microbes are needed to ascertain effects of probiotics. Other important areas for investigation include 1) confirmation of probiotics present in the digesta/ceca and how they alter the microbiota within the gastrointestinal (GI) tract and 2) the serum heterophil:lymphocyte ratio to further examine potential immune responses to the probiotics.

Livestock production contributes to greenhouse gas (GHG) emissions. However, there is a considerable variability in the carbon footprint associated with livestock production. Site specific estimates of GHG emissions are needed to accurately focus GHG emission reduction efforts. A holistic approach must be taken to assess the environmental impact of livestock production using appropriate geographical scale. The objective of this study was to determine baseline GHG emissions from dairy production in South Dakota using a life cycle assessment (LCA) approach. A cradle-to-farm gate LCA was used to estimate the GHG emissions to produce 1 kg of fat and protein corrected milk (FPCM) in South Dakota. The system boundary was divided into feed production, farm management, enteric methane, and manure management as these activities are the main contributors to the overall GHG emissions. The production of 1 kg FPCM in South Dakota dairies was estimated to emit 1.23 kg CO2 equivalents. The major contributors were enteric methane (46%) and manure management (32.7%). Feed production and farm management made up 14.1 and 7.2%, respectively. The estimate is similar to the national average but slightly higher than the California dairy system. The source of corn used in the dairies influences the footprint. For example, South Dakota corn had fewer GHG emissions than grain produced and transported in from Iowa. Therefore, locally and more sustainably sourced feed input will contribute to further reducing the environmental impacts. Improvements in efficiency of milk production through better genetics, nutrition animal welfare and feed production are expected to further reduce the carbon footprint of South Dakota dairies. Furthermore, anaerobic digesters will reduce emissions from manure sources.

Manure N from cattle contributes to nitrate leaching, nitrous oxide, and ammonia emissions. Measurement of manure N outputs on commercial beef cattle operations is laborious, expensive, and impractical; therefore, models are needed to predict N excreted in urine and feces. Building robust prediction models requires extensive data from animals under different management systems worldwide. Thus, the study objectives were to 1) collate an international dataset of N excretion in feces and urine based on individual observations from beef cattle; 2) determine the suitability of key variables for predicting fecal, urinary, and total manure N excretion; and 3) develop robust and reliable N excretion prediction models based on individual observation from beef cattle consuming various diets. A meta-analysis based on individual beef data from different experiments was carried out from a raw dataset including 1,004 observations from 33 experiments collected from 5 research institutes in Europe (n = 3), North America (n = 1), and South America (n = 1). A sequential approach was taken in developing models of increasing complexity by incrementally adding significant variables that affected fecal, urinary, or total manure N excretion. Nitrogen excretion was predicted by fitting linear mixed models with experiment as a random effect. Simple models including dry matter intake (DMI) were better at predicting fecal N excretion than those using only dietary nutrient composition or body weight (BW). Simple models based on N intake performed better for urinary and total manure N excretion than those based on DMI. A model including DMI and dietary component concentrations led to the most robust prediction of fecal and urinary N excretion, generating root mean square prediction errors as a percentage of the observed mean values of 25.0% for feces and 25.6% for urine. Complex total manure N excretion models based on BW and dietary component concentrations led to the lowest prediction errors of about 14.6%. In conclusion, several models to predict N excretion already exist, but the ones developed in this study are based on individual observations encompassing larger variability than the previous developed models. In addition, models that include information on DMI or N intake are required for accurate prediction of fecal, urinary, and total manure N excretion. In the absence of intake data, equations have poor performance as compared with equations based on intake and dietary component concentrations.

The contribution of greenhouse gas (GHG) emissions from ruminant production systems varies between countries and between regions within individual countries. The appropriate quantification of GHG emissions, specifically methane (CH4), has raised questions about the correct reporting of GHG inventories and, perhaps more importantly, how best to mitigate CH4 emissions. This review documents existing methods and methodologies to measure and estimate CH4 emissions from ruminant animals and the manure produced therein over various scales and conditions. Measurements of CH4 have frequently been conducted in research settings using classical methodologies developed for bioenergetic purposes, such as gas exchange techniques (respiration chambers, headboxes). While very precise, these techniques are limited to research settings as they are expensive, labor-intensive, and applicable only to a few animals. Head-stalls, such as the GreenFeed system, have been used to measure expired CH4 for individual animals housed alone or in groups in confinement or grazing. This technique requires frequent animal visitation over the diurnal measurement period and an adequate number of collection days. The tracer gas technique can be used to measure CH4 from individual animals housed outdoors, as there is a need to ensure low background concentrations. Micrometeorological techniques (e.g., open-path lasers) can measure CH4 emissions over larger areas and many animals, but limitations exist, including the need to measure over more extended periods. Measurement of CH4 emissions from manure depends on the type of storage, animal housing, CH4 concentration inside and outside the boundaries of the area of interest, and ventilation rate, which is likely the variable that contributes the greatest to measurement uncertainty. For large-scale areas, aircraft, drones, and satellites have been used in association with the tracer flux method, inverse modeling, imagery, and LiDAR (Light Detection and Ranging), but research is lagging in validating these methods. Bottom-up approaches to estimating CH4 emissions rely on empirical or mechanistic modeling to quantify the contribution of individual sources (enteric and manure). In contrast, top-down approaches estimate the amount of CH4 in the atmosphere using spatial and temporal models to account for transportation from an emitter to an observation point. While these two estimation approaches rarely agree, they help identify knowledge gaps and research requirements in practice.

The stable nitrogen isotope ratio δ15N is used as a marker of dietary protein sources in blood. Crop fertilization strategies affect δ15N in plant foods. In a double-blinded randomized cross-over dietary intervention trial with 33 participants, we quantified the effect of fertilizer type (conventional: synthetic fertilizer and organic: animal or green manure) on δ15N in blood plasma. At study baseline, plasma δ15N was +9.34 ± 0.29‰ (mean ± standard deviation). After 12 days intervention with a diet based on crops fertilized with animal manure, plasma δ15N was shifted by +0.27 ± 0.04‰ (mean ± standard error) compared to synthetic fertilization and by +0.22 ± 0.04‰ compared to fertilization with green manure (both p < 0.0001). Accordingly, differences in the δ15N values between fertilizers are propagated to the blood plasma of human consumers. The results indicate a need to consider agricultural practices when using δ15N as a dietary biomarker.

AimsRecent foodborne disease outbreaks have caused farmers to re-evaluate their practices. In particular, concern that soil amendments could introduce foodborne pathogens onto farms and promote their survival in soils has led farmers to reduce or eliminate the application of animal-based composts. However, organic amendments (such as composts and cover crops) could bolster food safety by increasing soil microbial diversity and activity, which can act as competitors or antagonists and reduce pathogen survival.Methods and resultsLeveraging a study of a 27-year experiment comparing organic and conventional soil management, we evaluate the impacts of composted poultry litter and cover crops on soil chemistry, bacterial communities and survival of Salmonella enterica and Listeria monocytogenes. We found that bacterial community composition strongly affected pathogen survival in soils. Specifically, organic soils managed with cover crops and composts hosted more macronutrients and bacterial communities that were better able to suppress Salmonella and Listeria. For example, after incubating soils for 10 days at 20°C, soils without composts retained fourfold to fivefold more Salmonella compared to compost-amended soils. However, treatment effects dissipated as bacterial communities converged over the growing season.ConclusionsOur results suggest that composts and cover crops may be used to build healthy soils without increasing foodborne pathogen survival.Significance and impact of the studyOur work suggests that animal-based composts do not promote pathogen survival and may even promote bacterial communities that suppress pathogens. Critically, proper composting techniques are known to reduce pathogen populations in biological soil amendments of animal origin, which can reduce the risks of introducing pathogens to farm fields in soil amendments. Thus, animal-based composts and cover crops may be a safe alternative to conventional fertilizers, both because of the known benefits of composts for soil health and because it may be possible to apply amendments in such a way that food-safety risks are mitigated rather than exacerbated.

The dissemination of antibiotic resistance genes (ARGs) in the environment contributes to the global rise in antibiotic resistant infections. Therefore, it is of importance to further research the exposure pathways of these emerging contaminants to humans. This study explores commercially available garden products containing animal manure as a source of ARGs in a survey of 34 garden products, 3 recently landscaped soils, and 5 native soils. DNA was extracted from these soils and quantified for 5 ARGs, intI1, and 16S rRNA. This study found that both absolute and relative gene abundances in garden products ranged from approximately two to greater than four orders of magnitude higher than those observed in native soils. Garden products with Organic Materials Review Institute (OMRI) certification did not have significantly different ARG abundances. Results here indicate that garden products are important sources of ARGs to gardens, lawns, and parks.

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Manure from poultry operations is typically applied to nearby cropland and may affect nutrient loading and the spread of antibiotic resistance (ABR). We analyzed the concentrations of nitrogen and phosphorus and the occurrence of ABR in Escherichia coli (E. coli) and extra-intestinal pathogenic E. coli isolates from streams draining 15 small (

Manure from poultry operations is typically applied to nearby cropland and may affect nutrient loading and the spread of antibiotic resistance (ABR). We analyzed the concentrations of nitrogen and phosphorus and the occurrence of ABR in Escherichia coli (E. coli) and extra-intestinal pathogenic E. coli isolates from streams draining 15 small (

Food production including dairy has been associated with environmental impacts and resource use that has been steadily improving when adjusted per unit of product. The objective of this study was to conduct a cradle-to-farm gate environmental impact analysis and resource inventory of the California dairy production system to estimate the change in greenhouse gas emissions and water and land use over the 50-yr period between 1964 and 2014. Using a life cycle assessment according to international standards and the Food and Agriculture Organization of the United Nations guidelines, we analyzed contributions from dairy production in California to global environmental change. Production of 1 kg of energy- and protein-corrected milk (ECM) in California emitted 1.12 to 1.16 kg of CO2 equivalents (CO2e) in 2014 compared with 2.11 kg of CO2e in 1964, a reduction of 45.0 to 46.9% over the last 50 yr, depending on the model used. Greater reductions in enteric methane intensity (i.e., methane production per kilogram of ECM) were observed (reduction of 54.1 to 55.7%) compared with manure GHG (reduction of 8.73 to 11.9%) in 2014 compared with 1964. This was mainly because manure management in the state relies on lagoons for storage, which has a greater methane conversion factor than solid manure storage. Water use intensity was reduced by 88.1 to 89.9%, with water reductions of 88.7 to 90.5% in crop production, 55.3 to 59.2% in housing and milking, and 52.4 to 54% in free water intake. Improved crop genetics and management have contributed to large efficiencies in water utilization. Land requirements for crop production were reduced by 89.4 to 89.7% in 2014 compared with 1964. This was mainly due to dramatic increases in crop yields in the last 50 yr. The increases in milk production per cow through genetic improvements and better nutrition and animal care have contributed to reductions in greenhouse gas emissions and land and water usage when calculated per unit of production (intensity) basis.

Antimicrobial resistance is a global public health concern, and livestock play a significant role in selecting for resistance and maintaining such reservoirs. Here we study the succession of dairy cattle resistome during early life using metagenomic sequencing, as well as the relationship between resistome, gut microbiota, and diet. In our dataset, the gut of dairy calves serves as a reservoir of 329 antimicrobial resistance genes (ARGs) presumably conferring resistance to 17 classes of antibiotics, and the abundance of ARGs declines gradually during nursing. ARGs appear to co-occur with antibacterial biocide or metal resistance genes. Colostrum is a potential source of ARGs observed in calves at day 2. The dynamic changes in the resistome are likely a result of gut microbiota assembly, which is closely associated with diet transition in dairy calves. Modifications in the resistome may be possible via early-life dietary interventions to reduce overall antimicrobial resistance.

Livestock manures are potential sources of antibiotics in the environment. Sulfamethazine (SMZ), frequently used in veterinary medicine, can enter the environment by using manure as soil fertilizer due to its incomplete absorption in the animal gut and its unmetabolized excretion. The objective of this study was to evaluate the mineralization of 14C-labelled SMZ in manure under a new redox scenario provided by microbial electrochemical reactors, termed microbial electroremediating cells (MERC). These devices aim to overcome the electron acceptor limitation in bacterial oxidative metabolism by means of using electrodes to enhance the biodegradation of pollutants in the environment. Our results revealed that the total degradation of 14C-SMZ reached 43.5% in short term batch laboratory scale experiments under reducing conditions (-400 mV vs. Ag/AgCl). Actually, SMZ mineralization was enhanced up to 10-fold in the early stages (after 2 weeks) in comparison with an electrode-free natural attenuation assay. Moreover, mineralization showed a dependence on electrode potential, with negligible results for conditions set to +400 mV vs Ag/AgCl. The impact of merging electrodes and microorganisms for manure bioremediation suggests a promising future for this emerging technology to treat polluted livestock wastes and prevent soil and groundwater pollution.

Reported estimates of CH4 emissions from ruminants and manure management are up to 2 times higher in atmospheric top-down calculations than in bottom-up (BU) inventories. We explored this discrepancy by estimating CH4 emissions of 2 dairy facilities in California with US Environmental Protection Agency (US EPA) methodology, which is used for BU inventories, and 3 independent measurement techniques: (1) open-path measurements with inverse dispersion modeling (hereafter open-path), (2) vehicle measurements with tracer flux ratio method, and (3) aircraft measurements with the closed-path method. All 3 techniques were used to estimate whole-facility CH4 emissions during 3 to 6 d per farm in the summer of 2016. In addition, open-path was used to estimate whole-facility CH4 emissions over 13 to 14 d per farm in the winter of 2017. Our objectives were to (1) compare whole-facility CH4 measurements utilizing the different measurement techniques, (2) compare whole-facility CH4 measurements to US EPA inventory methodology estimates, and (3) compare CH4 emissions between 2 dairies. Whole-facility CH4 estimates were similar among measurement techniques. No seasonality was detected for CH4 emissions from animal housing, but CH4 emissions from liquid manure storage were 3 to 6 times greater during the summer than during the winter measurement periods. The findings confirm previous studies showing that whole-facility CH4 emissions need to be measured throughout the year to estimate and evaluate annual inventories. Open-path measurements for liquid manure storage emissions were similar to monthly US EPA estimates during the summer, but not during the winter measurement periods. However, the numerical difference was relatively small considering yearly emission estimates. Manure CH4 emissions contributed 69 to 79% and 26 to 47% of whole-facility CH4 emissions during the summer and winter measurement periods, respectively. Methane yields from animal housing were similar between farms (on average 20.9 g of CH4/kg of dry matter intake), but CH4 emissions normalized by volatile solids (VS) loading from liquid manure storage (g of CH4 per day/kg of VS produced by all cattle per day) at 1 dairy were 1.7 and 3.5 times greater than at the other during the summer (234 vs. 137 g of CH4/kg of VS) and winter measurement periods (78 vs. 22 g of CH4/kg of VS), respectively. We attributed much of this difference to the proportion of manure stored in liquid (anaerobic) form, and suggest that manure management practices that reduce the amount of manure solids stored in liquid form could significantly reduce dairy CH4 emissions.

The majority of seafood is farmed, with most finfish coming from freshwater ponds. Ponds are often fertilized to promote microbial productivity as a natural feed source to fish. To understand if pond fertilization with livestock manure induces a probiotic or prebiotic effect, we communally reared tilapia (Oreochromis shiranus), and North African catfish (Clarias gariepinus), for 4 weeks under seven manure treatments including layer chicken, broiler chicken, guinea fowl, quail, pig, cow, vs. commercial feed to evaluate microbial community dynamics of the manure, pond water, and fish feces using 16S and 18S rRNA marker genes along with metagenome sequencing. Catfish growth, but not tilapia, was positively associated with plankton abundance (p = 0.0006, R2  = 0.4887) and greatest in ponds fertilized with quail manure (ANOVA, p

Dairy farms generate a considerable amount of manure, which is applied in cropland as fertilizer. While the use of manure as fertilizer reduces the application of chemical fertilizers, the main concern with regards to manure application is microbial pollution. Manure is a reservoir of a broad range of microbial populations, including pathogens, which have potential to cause contamination and pose risks to public and animal health. Despite the widespread use of manure fertilizer, the change in microbial diversity of manure under various treatment processes is still not well-understood. We hypothesize that the microbial population of animal waste changes with manure handling used in a farm environment. Consequential microbial risk caused by animal manure may depend on manure handling. In this study, a reconnaissance effort for sampling dairy manure in California Central Valley followed by 16S rRNA analysis of content and diversity was undertaken to understand the microbiome of manure after various handling processes. The microbial community analysis of manure revealed that the population in liquid manure differs from that in solid manure. For instance, the bacteria of genus Sulfuriomonas were unique in liquid samples, while the bacteria of genus Thermos were observed only in solid samples. Bacteria of genus Clostridium were present in both solid and liquid samples. The population among liquid samples was comparable, as was the population among solid samples. These findings suggest that the mode of manure application (i.e., liquid versus solid) could have a potential impact on the microbiome of cropland receiving manure as fertilizers.

The transport of oxytetracycline, chlortetracycline, and ivermectin from manure was assessed via surface runoff on irrigated pasture. Surface runoff plots in the Sierra Foothills of Northern California were used to evaluate the effects of irrigation water application rates, pharmaceutical application conditions, vegetative cover, and vegetative filter strip length on the pharmaceutical discharge in surface runoff. Experiments were designed to permit the maximum potential transport of pharmaceuticals to surface runoff water, which included pre-irrigation to saturate soil, trimming grass where manure was applied, and laying a continuous manure strip perpendicular to the flow of water. However, due to high sorption of the pharmaceuticals to manure and soil, less than 0.1% of applied pharmaceuticals were detected in runoff water. Results demonstrated an increase of pharmaceutical transport in surface runoff with increased pharmaceutical concentration in manure, the concentration of pharmaceuticals in runoff water remained constant with increased irrigation flow rate, and no appreciable decrease in pharmaceutical runoff was produced with the vegetative filter strip length increased from 30.5 to 91.5 cm. Most of the applied pharmaceuticals were retained in the manure or within the upper 5 cm of soil directly beneath the manure application sites. As this study evaluated conditions for high transport potential, the data suggest that the risk for significant chlortetracycline, oxytetracycline, and ivermectin transport to surface water from cattle manure on irrigated pasture is low.

Nitrogen excreted in dairy manure can be potentially transformed and emitted as NH, which can create livestock and human respiratory problems and be an indirect source of NO. The objectives of this study were to: (i) investigate environmental factors influencing NH emissions from dairy housing; and (ii) identify key explanatory variables in the NH emissions prediction from dairy housing using a meta-analytical approach. Data from 25 studies were used for the preliminary analysis, and data from 10 studies reporting 87 treatment means were used for the meta-analysis. Season and flooring type significantly affected NH emissions. For nutritional effect analysis, the between-study variability (heterogeneity) of mean NH emission was estimated using random-effect models and had a significant effect ( < 0.01). Therefore, random-effect models were extended to mixed-effect models to explain heterogeneity regarding the available dietary and animal variables. The final mixed-effect model included milk yield, dietary crude protein, and dry matter intake separately, explaining 45.5% of NH emissions heterogeneity. A unit increase in milk yield (kg d) resulted in a 4.9 g cow d reduction in NH emissions, and a unit increase in dietary crude protein content (%) and dry matter intake (kg d) resulted in 10.2 and 16.3 g cow d increases in NH emissions, respectively, in the scope of this study. These results can be further used to help identify mitigation strategies to reduce NH emissions from dairy housing by developing predictive models that could determine variables with strong association with NH emissions.

It has been proposed that livestock production effluents such as wastewater, airborne dust and manure increase the density of antimicrobial resistant bacteria and genes in the environment. The public health risk posed by this proposed outcome has been difficult to quantify using traditional microbiological approaches. We utilized shotgun metagenomics to provide a first description of the resistome of North American dairy and beef production effluents, and identify factors that significantly impact this resistome. We identified 34 mechanisms of antimicrobial drug resistance within 34 soil, manure and wastewater samples from feedlot, ranch and dairy operations. The majority of resistance-associated sequences found in all samples belonged to tetracycline resistance mechanisms. We found that the ranch samples contained significantly fewer resistance mechanisms than dairy and feedlot samples, and that the resistome of dairy operations differed significantly from that of feedlots. The resistome in soil, manure and wastewater differed, suggesting that management of these effluents should be tailored appropriately. By providing a baseline of the cattle production waste resistome, this study represents a solid foundation for future efforts to characterize and quantify the public health risk posed by livestock effluents.

Mathematical models for predicting P excretions play a key role in evaluating P use efficiency and monitoring the environmental impact of dairy cows. However, the majority of extant models require feed intake as predictor variable, which is not routinely available at farm level. The objectives of the study were to (1) explore factors explaining heterogeneity in P output; (2) develop a set of empirical models for predicting P output in feces (Pf), manure (PMa), and milk (Pm, all in g/cow per day) with and without dry matter intake (DMI) using literature data; and (3) evaluate new and extant P models using an independent data set. Random effect meta-regression analyses were conducted using 190 Pf, 97 PMa, and 118 Pm or milk P concentration (PMilkC) treatment means from 38 studies. Dietary nutrient composition, milk yield and composition, and days in milk were used as potential covariates to the models with and without DMI. Dietary phosphorus intake (Pi) was the major determinant of Pf and PMa. Milk yield negatively affected Pi partitioning to Pf or PMa. In the absence of DMI, milk yield, body weight, and dietary P content became the major determinants of Pf and PMa. Milk P concentration (PMilkC) was heterogeneous across the treatment groups, with a mean of 0.92 g/kg of milk. Milk yield, days in milk, and dietary Ca-to-ash ratio were negatively correlated with PMilkC and explained 42% of the heterogeneity. The new models predicted Pf and PMa with root mean square prediction error as a percentage of observed mean (RMSPE%) of 18.3 and 19.2%, respectively, using DMI when evaluated with an independent data set. Some of the extant models also predicted Pf and PMa well (RMSPE%=19.3 to 20.0%) using DMI. The new models without DMI as a variable predicted Pf and PMa with RMSPE% of 22.3 and 19.6%, respectively, which can be used in monitoring P excretions at farm level. When evaluated with an independent data set, the new model and extant models based on milk protein content predicted PMilkC with RMSPE% of 12.7 to 19.6%. Although models using P intake information gave better predictions, P output from lactating dairy cows can also be predicted well without intake using milk yield, milk protein content, body weight, and dietary P, Ca, and total ash contents.

Manure nitrogen (N) from cattle production facilities can lead to negative environmental effects, such as contribution to greenhouse gas emissions, leaching and runoff to aqueous ecosystems leading to eutrophication, and acid rain. To mitigate these effects and to improve the efficiency of N use, accurate prediction of N excretion and secretions are required. A genetic algorithm was implemented to select models to predict fecal, urinary, and total manure N excretions, and milk N secretions from 3 classes of animals: lactating dairy cows, heifers and dry cows, and steers. Two tiers of model classes were developed for each category of animals based on model input requirements. A total of 6 models for heifers and dry cows and steers and an additional 2 models for lactating dairy cattle were developed. Evaluation of the models using K-fold cross validation based on all data and using the most recent 6 yr of data showed better prediction for total manure N and fecal N compared with urinary N excretion, which was the most variable response in the database. Compared with extant models from the literature, the models developed in this study resulted in a significant improvement in prediction error for fecal and urinary N excretions from lactating cows. For total manure production by lactating cows, extant and new models were comparable in their prediction ability. Both proposed and extant models performed better than the prediction methods used by the US Environmental Protection Agency for the national inventory of greenhouse gases. Therefore, the proposed models are recommended for use in estimation of manure N from various classes of animals.

Nutrient loading and air emissions from swine operations raise environmental concerns. The objective of the study was to describe and evaluate a mathematical model (Davis Swine Model) of nutrient partitioning and predict manure excretion and composition on a daily basis. State variables of the model were AA, fatty acids, and a central pool of metabolites that supplied substrate for lipid synthesis and oxidation. The model traced the fate of ingested nutrients and water through digestion and intermediary metabolism into body protein, fat, water, and ash, where body protein and fat represented the body constituent pools. It was assumed that fluxes of metabolites follow saturation kinetics, depending on metabolite concentrations. The main inputs to the model were diet nutrient composition, feed intake, water-to-feed ratio, and initial BW. First, the model was challenged with nutrient partitioning data and then with excretion data. The data had 48 different feeding regimes with contrasting energy and lysine intakes at 2 different stages of growth. The overall observed and predicted mean were 109 and 112 g/d for protein deposition and 132 and 136 g/d for lipid deposition respectively, suggesting minor mean bias. Root mean square prediction error (RMSPE) was used in evaluation of the model for its predictive power. The overall RMSPE was 2.2 and 4.1 g/d for protein and lipid deposition, respectively. The excretion database used for evaluation of the model was constructed from 150 digestibility trials using growing-finishing pig diets that had a wide range of nutrient chemical composition. Nutrient and water excretion were quantified using the principle of mass conservation. The average daily observed and predicted manure production was 3.79 and 3.99 kg/d, respectively, with a RMSPE of 0.49 kg/d. There was a good agreement between observed and predicted mean fecal N output (9.9 and 9.8 g/d, respectively). Similarly, the overall observed and predicted mean urine N output was 21.7 and 21.3 g/d, respectively, suggesting minor mean bias. The RMSPE was 1.9 and 4.1 g/d for fecal and urinary N, respectively. Evaluation of the model showed that the model predicts manure excretion and N content well and can be used to assess environmental mitigation options from swine operations.

Reliable estimates of fresh manure water output from dairy cows help to improve storage design, enhance efficiency of land application, quantify the water footprint, and predict nutrient transformations during manure storage. The objective of the study was to construct a mechanistic, dynamic, and deterministic mathematical model to quantify urinary and fecal water outputs (kg/d) from individual lactating dairy cows. The model contained 4 body water pools: reticulorumen (QRR), post-reticulorumen (QPR), extracellular (QEC), and intracellular (QIC). Dry matter (DM) intake, dietary forage, DM, crude protein, acid detergent fiber and ash contents, milk yield, and milk fat and protein contents, days in milk, and body weight were input variables to the model. A set of linear equations was constructed to determine drinking, feed, and saliva water inputs to QRR and fractional water passage from QRR to QPR. Water transfer via the rumen wall was subjected to changes in QEC and total water input to QRR. Post-reticulorumen water passage was adjusted for DM intake. Metabolic water production and respiratory cutaneous water losses were estimated with functions of heat production in the model. Water loss in urine was driven by absorbed N left after being removed via milk. Model parameters were estimated simultaneously using observed fecal and urinary water output data from lactating Holstein cows (n=670). The model was evaluated with data that were not used for model development and optimization (n=377). The observations in both data sets were related to thermoneutral conditions. The model predicted drinking water intake, fecal, urinary, and total fresh manure water output with root mean square prediction errors as a percentage of average values of 18.1, 15.6, 30.6, and 14.6%, respectively. In all cases, >97% of the prediction error was due to random variability of data. The model can also be used to determine saliva production, heat and metabolic water production, respiratory cutaneous water losses, and size of major body water pools in lactating Holstein cows under thermoneutral conditions.

Although livestock production accounts for a sizeable share of global greenhouse gas emissions, numerous technical options have been identified to mitigate these emissions. In this review, a subset of these options, which have proven to be effective, are discussed. These include measures to reduce CH4 emissions from enteric fermentation by ruminants, the largest single emission source from the global livestock sector, and for reducing CH4 and N2O emissions from manure. A unique feature of this review is the high level of attention given to interactions between mitigation options and productivity. Among the feed supplement options for lowering enteric emissions, dietary lipids, nitrates and ionophores are identified as the most effective. Forage quality, feed processing and precision feeding have the best prospects among the various available feed and feed management measures. With regard to manure, dietary measures that reduce the amount of N excreted (e.g. better matching of dietary protein to animal needs), shift N excretion from urine to faeces (e.g. tannin inclusion at low levels) and reduce the amount of fermentable organic matter excreted are recommended. Among the many 'end-of-pipe' measures available for manure management, approaches that capture and/or process CH4 emissions during storage (e.g. anaerobic digestion, biofiltration, composting), as well as subsurface injection of manure, are among the most encouraging options flagged in this section of the review. The importance of a multiple gas perspective is critical when assessing mitigation potentials, because most of the options reviewed show strong interactions among sources of greenhouse gas (GHG) emissions. The paper reviews current knowledge on potential pollution swapping, whereby the reduction of one GHG or emission source leads to unintended increases in another.

Environmental releases of antibiotics from concentrated animal feeding operations (CAFOs) are of increasing regulatory concern. This study investigates the use and occurrence of antibiotics in dairy CAFOs and their potential transport into first-encountered groundwater. On two dairies we conducted four seasonal sampling campaigns, each across 13 animal production and waste management systems and associated environmental pathways: application to animals, excretion to surfaces, manure collection systems, soils, and shallow groundwater. Concentrations of antibiotics were determined using on line solid phase extraction (OLSPE) and liquid chromatography-tandem mass spectrometry (LC/MS/MS) with electrospray ionization (ESI) for water samples, and accelerated solvent extraction (ASE) LC/MS/MS with ESI for solid samples. A variety of antibiotics were applied at both farms leading to antibiotics excretion of several hundred grams per farm per day. Sulfonamides, tetracyclines, and their epimers/isomers, and lincomycin were most frequently detected. Yet, despite decades of use, antibiotic occurrence appeared constrained to within farm boundaries. The most frequent antibiotic detections were associated with lagoons, hospital pens, and calf hutches. When detected below ground, tetracyclines were mainly found in soils, whereas sulfonamides were found in shallow groundwater reflecting key differences in their physicochemical properties. In manure lagoons, 10 compounds were detected including tetracyclines and trimethoprim. Of these 10, sulfadimethoxine, sulfamethazine, and lincomycin were found in shallow groundwater directly downgradient from the lagoons. Antibiotics were sporadically detected in field surface samples on fields with manure applications, but not in underlying sandy soils. Sulfadimethoxine and sulfamethazine were detected in shallow groundwater near field flood irrigation gates, but at highly attenuated levels.

The localization and intensification of the poultry industry over the past 50 years have incidentally created a largely ignored environmental management crisis. As a result of these changes in poultry production, concentrated animal feeding operations (CAFOs) produce far more waste than can be managed by land disposal within the regions where it is produced. As a result, alternative waste management practices are currently being implemented, including incineration and pelletization of waste. However, organic arsenicals used in poultry feed are converted to inorganic arsenicals in poultry waste, limiting the feasibility of waste management alternatives. The presence of inorganic arsenic in incinerator ash and pelletized waste sold as fertilizer creates opportunities for population exposures that did not previously exist. The removal of arsenic from animal feed is a critical step toward safe poultry waste management.