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Aims: An extensive source investigation was conducted on a dairy farm with neurolisteriosis and subclinical mastitis cases to identify infection source and potential transmission routes of Listeria monocytogenes. Methods and Results: A total of 36 L. monocytogenes isolates were obtained from animal clinical cases (neurolisteriosis and udder infection) and the farm environment (silage, faeces, water). Isolates were typed using pulsed‐field gel electrophoresis (PFGE) and whole‐genome sequencing (WGS). Their virulence potential was assessed using the gentamicin protection assay and WGS‐based identification of virulence genes. PFGE and WGS revealed a high genetic diversity of L. monocytogenes. An epidemiological link was confirmed for isolates from (i) several subclinical mastitis cases, (ii) silage and subclinical mastitis cases and (iii) different water sources. The neurolisteriosis isolate belonged to clonal complex (CC) 1, but infection source was not identified. A high occurrence (9/47 cows; 19·1%) of subclinical mastitis was observed with isolates belonging to CC2, CC4 and CC11. Conclusions: The dairy farm environment was contaminated with diverse L. monocytogenes strains, including genotypes associated with human disease. Several isolates harboured genetic determinants associated with increased infectious potential in humans. Significance and Impact of the Study: Results suggest that subclinical listerial mastitis should not be neglected as a potential source of milk contamination. The presence of hypervirulent CCs in subclinical mastitis cases calls for the implementation of improved mastitis detection. [ABSTRACT FROM AUTHOR]

Aim: The present study was carried out to determine load of total bacteria, Escherichia coli and Salmonella spp. in dairy farm and its environmental components. In addition, the antibiogram profile of the isolated bacteria having public health impact was also determined along with identification of virulence and resistance genes by polymerase chain reaction (PCR) under a one-health approach. Materials and Methods: A total of 240 samples of six types (cow dung - 15, milk - 10, milkers' hand wash - 10, soil - 10 water - 5, and vegetables - 10) were collected from four dairy farms. For enumeration, the samples were cultured onto plate count agar, eosin methylene blue, and xylose-lysine deoxycholate agar and the isolation and identification of the E. coli and Salmonella spp. were performed based on morphology, cultural, staining, and biochemical properties followed by PCR. The pathogenic strains of E. coli stx1, stx2, and rfbO157 were also identified through PCR. The isolates were subjected to antimicrobial susceptibility test against 12 commonly used antibiotics by disk diffusion method. Detection of antibiotic resistance genes ereA, tetA, tetB, and SHV were performed by PCR. Results: The mean total bacterial count, E. coli and Salmonella spp. count in the samples ranged from 4.54±0.05 to 8.65±0.06, 3.62±0.07 to 7.04±0.48, and 2.52±0.08 to 5.87±0.05 log colony-forming unit/g or ml, respectively. Out of 240 samples, 180 (75%) isolates of E. coli and 136 (56.67%) isolates of Salmonella spp. were recovered through cultural and molecular tests. Among the 180 E. coli isolates, 47 (26.11%) were found positive for the presence of all the three virulent genes, of which stx1 was the most prevalent (13.33%). Only three isolates were identified as enterohemorrhagic E. coli. Antibiotic sensitivity test revealed that both E. coli and Salmonella spp. were found highly resistant to azithromycin, tetracycline, erythromycin, oxytetracycline, and ertapenem and susceptible to gentamycin, ciprofloxacin, and imipenem. Among the four antibiotic resistance genes, the most observable was tetA (80.51-84.74%) in E. coli and Salmonella spp. and SHV genes were the lowest one (22.06-25%). Conclusion: Dairy farm and their environmental components carry antibiotic-resistant pathogenic E. coli and Salmonella spp. that are potential threat for human health which requires a one-health approach to combat the threat. [ABSTRACT FROM AUTHOR]

Abstract This study was carried out to determine the occurrence and characteristics of enteropathogenic Escherichia coli (EPEC) and Shiga toxin-producing E. coli (STEC) strains in cow's milk, cheese and dairy cattle farm environments, and to estimate distribution of antimicrobial resistance. A collection of 18 atypical EPEC -aEPEC, 14 STEC, and one E. albertii was obtained and characterized from 502 samples. Occurrence of aEPEC in cow's milk was high (>6%) whereas non-O157 STEC was isolated in ca. 2% of milk samples. Detection of these diarrheagenic E. coli was absent in more than 100 cheese samples obtained from raw milk. This is the first report identifying E. albertii (O69:HNM) in a dairy cattle farm. Nearly one-third of aEPEC strains showed antimicrobial resistance, mostly presenting a multidrug resistance pattern. One clonal complex (ST20 Cplx) containing aEPEC strains from milk and faecal samples was determined. Two STEC strains belonged to serotypes with importance in human disease (O91:H21 and O55:H8) and were isolated from air samples which suggests a high dissemination potential. Spanish bulk tank cow's milk can constitute an important source of aEPEC strains besides STEC, bearing multiple antimicrobial resistance and with high diversity of both serotypes and genetic features linked to potential human infection. Highlights • In cows' milk, occurrence is high (>6%) for aEPEC whereas ca. 2% for STEC. • No detection of diarrheagenic E. coli in cheese obtained from raw cows' milk. • Spanish cows' milk is source of high-diverse aEPEC with multiple antibiotic resistance. • Milk and farm environment are sources of non-O157 STEC with clinical importance. • Isolation of the emerging human enteropathogen E. albertii in a dairy cattle farm. [ABSTRACT FROM AUTHOR]

Plant extracts have been proposed as substitutes for chemical feed additives due to their potential as rumen fermentation modifiers and because of their antimicrobial and antioxidant activities, possibly reducing methane emissions. This study aimed to evaluate the use of oregano (OR), green tea extracts (GT), and their association as feed additives on the performance and methane emissions from dairy between 28 and 87 d of lactation. Thirty-two lactating dairy cows, blocked into 2 genetic groups: 16 Holstein cows and 16 crossbred Holstein-Gir, with 522.6 ± 58.3 kg of body weight, 57.2 ± 20.9 d in lactation, producing 27.5 ± 5.0 kg/cow of milk and with 3.1 ± 1.8 lactations were evaluated (means ± standard error of the means). Cows were allocated into 4 treatments: control (CON), without plant extracts in the diet; oregano extract (OR), with the addition of 0.056% of oregano extract in the dry matter (DM) of the diet; green tea (GT), with the addition of 0.028% of green tea extract in the DM of the diet; and mixture, with the addition of 0.056% oregano extract and 0.028% green tea extract in the DM of the diet. The forage-to-concentrate ratio was 60:40. Forage was composed of corn silage (94%) and Tifton hay (6%); concentrate was based on ground corn and soybean meal. Plant extracts were supplied as powder, which was previously added and homogenized into 1 kg of concentrate in natural matter, top-dressed onto the total mixed diet. No treatment by day interaction was observed for any of the evaluated variables, but some block by treatment interactions were significant. In Holstein cows, the mixture treatment decreased gross energy and tended to decrease the total-tract apparent digestibility coefficient for crude protein and total digestible nutrients when compared with OR. During the gas measurement period, GT and OR increased the digestible fraction of the ingested DM and decreased CH4 expressed in grams per kilogram of digestible DMI compared with CON. The use of extracts did not change rumen pH, total volatile fatty acid concentration, milk yield, or most milk traits. Compared with CON, oregano addition decreased fat concentration in milk. The use of plant extracts altered some milk fatty acids but did not change milk fatty acids grouped according to chain length (short or long), saturation (unsaturated or saturated), total conjugated linoleic acids, and n-3 and n-6 contents. Green tea and oregano fed separately reduced gas emission in cows during the first third of lactation and have potential to be used as feed additives for dairy cows. [ABSTRACT FROM AUTHOR]

Since the 2014 release of the International Standards Organization’s (ISO’s) international water footprint standard (ISO 14046), the subject of water footprint assessment based on life cycle assessment has gained increased attention in research communities. In this study, a dairy farm and five processing plants in a large Chinese enterprise’s dairy industrial chain were selected for a comprehensive water footprint assessment using ISO 14046. Results indicate that the water scarcity footprint at the plants was not only related to total freshwater consumption and production, but also closely related to the scarcity of water resources in the watershed basin or area. The water footprint assessment focused on volume but ignored environmental impacts, which are prone to errors and deviations. For the dairy farm, the indirect water scarcity footprint accounted for more than 92% of the total water footprint and was much larger than its direct water scarcity footprint. In the dairy industry chain, cow breeding had a larger contribution to environmental water scarcity, while dairy processing was the main contributor to the water degradation footprint. The results of the water degradation footprint composition show that impact from water eutrophication pollution (NH 3 -N, TP and TN) was greater than that of organic pollution (COD). Furthermore, in terms of the water eutrophication footprint, nitrogen pollutants contributed to a much greater extent than phosphorus pollutants. Finally, the results highlight that the water footprint of the dairy industrial chain could be greatly reduced by increasing the water efficiency of each production process, improving wastewater treatment capacity, reducing the water footprint of the supply chain, and considering the water sustainability of the river basin. [ABSTRACT FROM AUTHOR]

Quantification of the environmental performance of dairy farms should allow comparisons between farms. We assess whether IPCC Tier 1 methodology for emissions from soil management is sufficiently precise to analyse and differentiate the carbon footprint of milk production between practical dairy farms and whether we can correctly identify which farms have the lowest and the highest GHG emissions per product unit, respectively. We used data from 20 Norwegian dairy farms which are very similar in structure, but differ in organic/non-organic management and the share of peat soil of their farmland. We assessed the uncertainty of the carbon footprint by running Monte Carlo simulations with the uncertainty ranges given in Tier 1 of the IPCC guidelines. The carbon footprint is considered different when 95% of all Monte Carlo iterations assume that one farm has higher product-related GHG emissions than the farm in comparison. The uncertainty of results in the single farms, expressed as two-times the standard deviation divided by the median result, ranges between 4.2% and 15.3%. This means that 95% of values in the resulting distribution of one farm are within a range of 4–16% of the median of that farm. Farms can be differentiated when the variation of the carbon footprint is higher than the uncertainty of farm-related emissions. From all 190 direct comparisons of two farms in the study, 78% are significantly different. For this uncertainty assessment, it must be established that background processes, especially the datasets for import feed, can be judged covariant in order to prohibit them from influencing the comparison between farms. Secondly, the uncertainty ranges used for the calculation must be appropriate for the assessed systems. We were able to confirm the hypothesis that a significant differentiation of the milk carbon footprint between farms is possible with an IPCC Tier 1 approach for a majority of our comparisons, and found a difference of above 8.7% sufficient to establish significance. [ABSTRACT FROM AUTHOR]

The Irish agricultural policy ‘Food Harvest 2020’ is a roadmap for sectoral expansion and Irish dairy farming is expected to intensify, which could influence the environmental and economic performance of Irish milk production. Evaluating the total environmental impacts and the real cost of Irish milk production is a key step towards understanding the possibility of sustainable production. This paper addresses two main issues: aggregation of environmental impacts of Irish milk production by monetization, to understand the real cost of Irish milk production, including the environmental costs; and the effect of the agricultural policy ‘Food Harvest 2020’ on total cost (combining financial cost and environmental cost) of Irish milk production. This study used 2013 Irish dairy farming as a baseline, and defined ‘bottom’, ‘target’ and ‘optimum’ scenarios, according to the change of elementary inputs required to meet agricultural policy ambitions. The study demonstrated that the three monetization methods, Stepwise 2006, Eco-cost 2012 and EPS 2000, could be used for aggregating different environmental impacts into monetary unit, and to provide an insight for evaluating policy related to total environmental performance. The results showed that the total environmental cost of Irish milk production could be greater than the financial cost (up to €0.53/kg energy corrected milk). The dairy expansion policy with improved herbage utilization and fertilizer application could reduce financial cost and minimize the total environmental cost of per unit milk produced. [ABSTRACT FROM AUTHOR]

Dairy cattle farms are continuously developing more intensive systems of management which require higher utilization of durable and not-durable inputs. These inputs are responsible of significant direct and indirect fossil energy requirements which are related to remarkable emissions of CO2. This study aims to analyze direct energy requirements and the related carbon footprint of a large population of conventional dairy farms located in the south of Italy. A detailed survey of electricity, diesel and Liquefied Petroleum Gas (LPG) consumptions has been carried out among on-farm activities. The results of the analyses showed an annual average fuel consumption of 40 kg per tonne of milk, while electricity accounted for 73 kWh per tonne of milk produced. Expressing the direct energy inputs as primary energy, diesel fuel results the main resource used in on-farm activities, accounting for 72% of the total fossil primary energy requirement, while electricity represents only 27%. Moreover, larger farms were able to use more efficiently the direct energy inputs and reduce the related emissions of carbon dioxide per unit of milk produced, since the milk yield increases with the herd size. The global average farm emissions of carbon dioxide equivalent, due to all direct energy usages, accounted for 156 kg CO2-eq per tonne of Fat and Protein Corrected Milk (FPCM), while farms that raise more than 200 heads emitted 36% less than the average value. In this two-part series, the total energy demand (Part 1 + Part 2) per farm is mainly due to agricultural inputs and fuel consumption, which have the largest quota of the annual requirements for each milk yield class. These results also showed that large size farms held lower CO2-eq emissions when referred to the mass of milk produced. [ABSTRACT FROM AUTHOR]

The objectives of this study were to compare estimates of greenhouse gas emissions (GHG) as CH4 (enteric-manure), N2O (manure), and CO2 (fuel and energy use), the use of water and soil, the excretion of nutrients in manure, and feed efficiency from Mexican intensive dairy farms. Data from 26 dairy farms were analysed with a multivariable cluster analysis. Three grades of intensifications were identified (low, medium and high). Mathematical models were used to estimate GHG. Feed efficiency (kg milk per kg DMI) was better in high intensive production systems. Enteric methane was identified as the major source of GHG in all types of systems. High intensive dairies generated the lowest emissions of CH4, N2O and CO2 equivalent by unit of product, 18.6 g, 0.12 g and 828 g, respectively. Water footprint was lower in low intensive dairies using 427 L of water/L of milk. Cropland was highest in intensive systems but milk yield per area was better (30,938 kg/ha). Excretions of N, P, and K were lower in intensive dairies per kg of milk, at 13.2, 2.4, and 6.4 g, respectively. As intensification in the dairy system increased feed efficiency (kg milk/kg DMI) was better. Per unit of product (kg of milk), dairies with the highest intensification generated the lowest GHG emissions, nutrient excretion values and land and water use as compared to dairies with medium and low intensification. Increasing intensification and therefore feed efficiency of Mexican dairy systems could help to decrease GHG emissions, natural resources use and nutrient excretion. [ABSTRACT FROM AUTHOR]

Dairy farms have been widely acknowledged as a source of greenhouse gas (GHG) emissions. The need for a more environmentally friendly milk production system will likely be important going forward. Whereas methane (CH 4 ) enteric emissions can only be reduced to a limited extent, CH 4 manure emissions can be reduced by implementing mitigation strategies, such as the use of an anaerobic digestion (AD). Furthermore, implementing a photovoltaic (PV) electricity generation system could mitigate the fossil fuels used to cover the electrical needs of farms. In the present study to detect the main environmental hotspots of milk production, a Life Cycle Assessment was adopted to build the Life Cycle Inventory according to ISO 14040 and 14044 in a conventional dairy farm (1368 animals) provided by AD and PV systems. The Intergovernmental Panel on Climate Change tiered approach was adopted to associate the level of emission with each item in the life cycle inventory. The functional unit refers to 1 kg of fat-and-protein-corrected-milk (FPCM). In addition to milk products, other important co-products need to be considered: meat and renewable energy production from AD and PV systems. A physical allocation was applied to attribute GHG emissions among milk and meat products. Renewable energy production from AD and PV systems was considered, discounting carbon credits due to lower CH 4 manure emissions and to the minor exploitation of fossil energy. The CF of this farm scenario was 1.11 kg CO 2 eq/kg FPCM. The inclusion of AD allowed for the reduction of GHG emissions from milk production by 0.26 kg CO 2 eq/kg FPCM. The PV system contribution was negligible due to the small dimensions of the technology. The results obtained in this study confirm that integrating milk production with other co-products, originated from more efficient manure management, is a successful strategy to mitigate the environmental impact of dairy production. [ABSTRACT FROM AUTHOR]

Safe dairy food production starts at the farm level, with the presence of pathogens on farms potentially impacting the downstream food supply. Studies often commence with looking for pathogens in fecal material of farm animals, predominantly cows; however, pathogens may arise from other on-farm sources. In Australia, few studies have looked at the broader farm environment, particularly in relation to Escherichia coli and Salmonella. The present study characterized the genetic similarity of these pathogens from bovine, ovine, and caprine dairy farm environments and related this to the stx1, stx2, eae, or ehx virulence markers in E. coli and antibiotic resistance in Salmonella. E. coli isolates with indistinguishable genetic profiles and at least one of the virulence factors were found in multiple samples on the farms, although profiles were unique to each farm. E. coli O26 with stx1 from one bovine farm had a different fingerprint type than all of the other E. coli O26 isolates, which lacked the Shiga toxin genes. They were from a separate bovine farm and were themselves closely related. No antibiotic resistance was detected among Salmonella isolates to the 17 antibiotics tested. Three Salmonella serotypes were identified: Orion, Infantis, and Zanzibar. The published PCR serotyping method used misidentified Salmonella Zanzibar as Salmonella Javiana, which was revealed after conventional antisera-based serotyping; this illustrates the need for caution when using PCR techniques for Salmonella serotype identification. Of the three serotypes, Salmonella Orion was most prevalent and was potentially resident on the farm. This article describes the previously unreported genetic diversity of potentially pathogenic E. coli and Salmonella serotypes from the farm environments of three dairy animal species in Victoria, Australia. [ABSTRACT FROM AUTHOR]

Double cropping and increasing crop diversity could improve dairy farm economic and environmental sustainability. In this experiment, corn silage was partially replaced with 2 alternative forages, brown midrib-6 brachytic dwarf forage sorghum (Sorghum bicolor) or fall-grown oat (Avena sativa) silage, in the diet of lactating dairy cows. We investigated the effect on dry matter (DM) intake, milk yield (MY), milk components and fatty acid profile, apparent total-tract nutrient digestibility, N utilization, enteric methane emissions, and income over feed cost. We analyzed the in situ DM and neutral detergent fiber disappearance of the alternative forages versus corn silage and alfalfa haylage. Sorghum was grown in the summer and harvested in the milk stage. Oats were grown in the fall and harvested in the boot stage. Compared with corn silage, neutral detergent fiber and acid detergent fiber concentrations were higher in the alternative forages. Lignin content was highest for sorghum silage and similar for corn silage and oat silage. The alternative forages had less than 1% starch compared with the approximately 35% starch in the corn silage. Ruminal in situ DM effective degradability was similar, although statistically different, for corn silage and oat silage, but lower for sorghum silage. Diets with the alternative forages were fed in a replicated 3 x 3 Latin square design experiment with three 28-d periods and 12 Holstein cows. The control diet contained 44% (DM basis) corn silage. In the other 2 diets, sorghum or oat silages were included at 10% of dietary DM, replacing corn silage. Sorghum silage inclusion decreased DM intake, MY, and milk protein content but increased milk fat and maintained energy-corrected MY similar to the control. Oat silage had no effect on DM intake, MY, or milk components compared to the control. The oat silage diet increased apparent total-tract digestibility of dietary nutrients, except starch, whereas the sorghum diet slightly decreased DM, organic matter, crude protein, and starch digestibility. Cows consuming the oat silage diet had higher milk urea N and urinary urea N concentrations. Milk N efficiency was decreased by the sorghum diet. Diet did not affect enteric methane or carbon dioxide emissions. This study shows that oat silage can partially replace corn silage at 10% of the diet DM with no effect on MY. Brown midrib sorghum silage harvested at the milk stage with <1% starch may decrease DM intake and MY in dairy cows. [ABSTRACT FROM AUTHOR]

Particulate matter emissions from agricultural livestock operations contain both chemical and biological constituents that represent a potential human health hazard. The size and composition of these dusts, however, have not been well described. We evaluated the full size distribution (from 0 to 100 ?m in aerodynamic diameter) and chemical/biological composition of inhalable dusts inside several Colorado dairy parlors. Four aerodynamic size fractions (<3, 3-10, 10-30, and >30 ?m) were collected and analyzed using a combination of physiochemical techniques to understand the structure of bacterial communities and chemical constituents. Airborne particulate mass followed a bimodal size distribution (one mode at 3 ?m and a second above 30 ?m), which also correlated with the relative concentrations of the following microbiological markers: bacterial endotoxin, 3-hydroxy fatty acids, and muramic acid. Sequencing of the 16S-rRNA components of this aerosol revealed a microbiome derived predominantly from animal sources. Bacterial genera included Staphlyococcus, Pseudomonas, and Streptococcus, all of which have proinflammatory and pathogenic capacity. Our results suggest that the size distribution of bioaerosols emitted by dairy operations extends well above 10 ?m in diameter and contains a diverse mixture of potentially hazardous constituents and opportunistic pathogens. These findings should inform the development of more effective emissions control strategies. [ABSTRACT FROM AUTHOR]

Silage on dairy farms can emit large amounts of volatile organic compounds (VOCs), a precursor in the formation of tropospheric ozone. Because of the challenges associated with direct measurements, process-based modeling is another approach for estimating emissions of air pollutants from sources such as those from dairy farms. A process-based model for predicting VOC emissions from silage was developed and incorporated into the Integrated Farm System Model (IFSM, v. 4.3), a whole-farm simulation of crop, dairy, and beef production systems. The performance of the IFSM silage VOC emission model was evaluated using ethanol and methanol emissions measured from conventional silage piles (CSP), silage bags (SB), total mixed rations (TMR), and loose corn silage (LCS) at a commercial dairy farm in central California. With transport coefficients for ethanol refined using experimental data from our previous studies, the model performed well in simulating ethanol emission from CSP, TMR, and LCS; its lower performance for SB could be attributed to possible changes in face conditions of SB after silage removal that are not represented in the current model. For methanol emission, lack of experimental data for refinement likely caused the underprediction for CSP and SB whereas the overprediction observed for TMR can be explained as uncertainty in measurements. Despite these limitations, the model is a valuable tool for comparing silage management options and evaluating their relative effects on the overall performance, economics, and environmental impacts of farm production. As a component of IFSM, the silage VOC emission model was used to simulate a representative dairy farm in central California. The simulation showed most silage VOC emissions were from feed lying in feed lanes and not from the exposed face of silage storages. This suggests that mitigation efforts, particularly in areas prone to ozone non-attainment status, should focus on reducing emissions during feeding. For the simulated dairy farm, a reduction of around 30% was found if cows were housed and fed in a barn rather than in an open lot, and 23% if feeds were delivered as four feedings per day rather than as one. Reducing the exposed face of storage can also be useful. Simulated use of silage bags resulted in 90% and 18% reductions in emissions from the storage face and whole farm, respectively. [ABSTRACT FROM AUTHOR]

The objective of the study was to isolate potential Bacillus cereus sensu lato ( B. cereus s.l.) from a range of farm environments. Samples of tap water, milking equipment rinse water, milk sediment filter, grass, soil and bulk tank milk were collected from 63 farms. In addition, milk liners were swabbed at the start and the end of milking, and swabs were taken from cows' teats prior to milking. The samples were plated on mannitol egg yolk polymyxin agar (MYP) and presumptive B. cereus s.l. colonies were isolated and stored in nutrient broth with 20% glycerol and frozen at -80 °C. These isolates were then plated on chromogenic medium (BACARA) and colonies identified as presumptive B. cereus s.l. on this medium were subjected to 16S ribosomal RNA (rRNA) sequencing. Of the 507 isolates presumed to be B. cereus s.l. on the basis of growth on MYP, only 177 showed growth typical of B. cereus s.l. on BACARA agar. The use of 16S rRNA sequencing to identify isolates that grew on BACARA confirmed that the majority of isolates belonged to B. cereus s.l. A total of 81 of the 98 isolates sequenced were tentatively identified as presumptive B. cereus s.l. Pulsed-field gel electrophoresis was carried out on milk and soil isolates from seven farms that were identified as having presumptive B. cereus s.l. No pulsotype was shared by isolates from soil and milk on the same farm. Presumptive B. cereus s.l. was widely distributed within the dairy farm environment. [ABSTRACT FROM AUTHOR]

Farm nutrient management has been identified as one of the most important factors determining the economic and environmental performance of dairy cattle ( Bos taurus) farming systems. Given the environmental problems associated with dairy farms, such as emissions of greenhouse gases (GHG), and the complex interaction between farm management, environment and genetics, there is a need to develop robust tools which enable scientists and policy makers to study all these interactions. This paper describes the development of a simple model called NUTGRANJA 2.0 to evaluate GHG emissions and nitrogen (N) and phosphorus (P) losses from dairy farms. NUTGRANJA 2.0 is an empirical mass-balance model developed in order to simulate the main transfers and flows of N and P through the different stages of the dairy farm management. A model sensitivity test was carried out to explore some of the sensitivities of the model in relation to the simulation of GHG and N emissions. This test indicated that both management (e.g. milk yield per cow, annual fertiliser N rate) and site-specific factors (e.g. % clover ( Trifolium) in the sward, soil type, and % land slope) had a large effect on most of the model state variables studied (e.g. GHG and N losses). [ABSTRACT FROM AUTHOR]

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The aim of this paper is to assess the eco-efficiency of dairy farms in Spain. To do so, we use data from a survey carried out in 2010 for the specific purpose of analysing the environmental performance of 50 dairy farms in the Spanish region of Asturias. The survey contains information on nutrients balances and greenhouse gas emissions which is used to calculate environmental pressure indicators. Eco-efficiency is measured using data envelopment analysis. We analyse the influence of farmers' socio-economic characteristics and attitudes in explaining these eco-efficiency scores using truncated regression and bootstrapping procedures. On average, the dairy farms are found to be highly eco-inefficient. Among our results, farmers that are younger, that plan to continue in operation in the foreseeable future and that participate more in training schemes are found to be more eco-efficient. Self-reported positive environmental habits are also reflected in actual eco-efficient performance. We quantify these potential gains in eco-efficiency through a simulation analysis based on the estimated model's coefficients. [ABSTRACT FROM AUTHOR]

The study was conducted to find out the prevalence of sub-clinical mastitis (SCM) and antibiogram of the causative bacteria in dairy cows at the Sylhet govt. Dairy Farm (SGDF) and Local Farms of Sylhet (LFS) during the period of July2014 to June2015. These farms were selected to assess the predominant types of bacteria involved in causing sub-clinical mastitis and to know the in vitro antibiotic sensitivity spectrum of these bacterial isolates against the commonly used antibiotics and to study the economic effects due to SCM. Use of California Mastitis Test (CMT) for the detection of sub-clinical mastitis showed 42out of 100 samples were test positive, among which +(Trace) 22.0%, ++(Distinct) 12.0%, +++(Strong) 3.0%, ±(Doubtful) 5.0%. Bacteriological examination of milk samples of 100 milch cows (400 quarters) revealed that 42 cows (42.0%) had suffering from SCM with different bacterial infection with 95% confidence limit was 32.1574-51.8426. Among 42 positive samples31 (31.0%) cows had mono-bacterial infection and 11 (11.0%) cows had mixed bacterial infections. Statistical analysis of the result of single and mixed bacterial infections in the milk of apparently healthy milch cows revealed that the single infection was significantly (P < 0.05) higher than mixed bacterial infection. Of the 31 mono-bacterial isolates, of which 23 (23.0%) isolates were Staphylococci, 3 (3.0%) isolates were Escherichia coli, 5 (5.0%) isolated Streptococcus spp. The 11 cows had mixed infection, of which 5 had Staphylococcus spp. + Streptococcus spp., 3 had E. coli + Staphylococcus spp., and 3 had Streptococcus spp. + E. coli. Of 42 positive cases of SCM Staphylococcus spp. isolated from 23 samples. Among these 23 positive samples 13 obtained from SGDF (37.14%) and 10 obtained from LFS (15.38%). Escherichia coli isolated from 3 samples. Among these 3 positive samples 3 obtained from LFS (4.62%). Streptococcus spp. isolated from 5 samples. Among these 5 positive samples 1 obtained from SGDF (2.86%) and 4 obtained from LFS (6.15%). Ceftriaxone, ciprofloxacin and gentamicin were the best drug for treating sub-clinical mastitis. [ABSTRACT FROM AUTHOR]

The aim of this study was to estimate the environmental impact of organic and conventional small-scale dairy farms in mountain areas. Sixteen farms rearing the dual-purpose Rendena breed were assessed for global warming potential, acidification and eutrophication impacts through the Life Cycle Assessment method in two scenarios: the Baseline Scenario based on the actual farm data and the Milk-Beef production system Scenario assuming that calves exceeding the culling rate were fattened directly on-farm. Three different emissions allocation methods were considered: No allocation; Physical allocation, which also accounted for the co-product beef; and Economic allocation, which also accounted for the ecosystem services provided by the farms and were estimated on the basis of agri-environmental payments. Furthermore, two functional units were used: fat and protein corrected milk (FPCM) and utilizable agricultural land (UAL). Within the Baseline Scenario and with FPCM as the functional unit, performing No allocation, the mean values obtained for the global warming potential, acidification and eutrophication were 1.43 kg CO 2 -eq/kg FPCM, 25.84 g SO 2 -eq/kg FPCM and 3.99 g PO 4 3 − - eq / kg FPCM, respectively. The organic farms had a significantly lower eutrophication impact than the conventional farms considering all three allocation methods. Conversely, if UAL was used as the functional unit, the mean values obtained for the global warming potential, acidification and eutrophication were 0.80 kg CO 2 -eq/m 2 , 14.28 g SO 2 -eq/m 2 and 2.32 g PO 4 3 − - eq / m 2 , respectively. The Milk-Beef production system Scenario increased emissions per m 2 of UAL, but it reduced the emissions apportioned to 1 kg of FPCM, with stronger trends in the organic farms because of the increased added value of the meat production. This study highlights how strengthening beef production in dual-purpose breeds reduced the emissions apportioned to milk and suggests an approach to acknowledge multi-functionality considering some of the ecosystem services provided by the farms. [ABSTRACT FROM AUTHOR]

Dairy production leads to significant environmental impacts and increased production will only be feasible if the environmental performance at farm level permits a sustainable milk supply. Lameness is believed to become more prevalent and severe as herd sizes increase, and can significantly reduce milk output per cow while not influencing other attributes of the production system. The objective of this work was to quantify the effect of lameness on the environmental performance of a typical grazed grass dairy farm and evaluate the theoretical value of sensor-based real-time lameness management. Life cycle assessment was used to compare a typical baseline farm with scenarios assuming increased lameness severity and prevalence. It was found that lameness could increase the farm level global warming potential, acidification potential, eutrophication potential and fossil fuel depletion by 7–9%. As increased herd sizes will increase cow: handler ratio, this result was interpreted to suggest that the use of sensors and information and communication technology for lameness detection could improve management on dairy farms to reduce the adverse impact on environmental performance that is associated with lameness. [ABSTRACT FROM AUTHOR]

The aim of the study was to assess, through a cradle to farm gate Life Cycle Assessment, different mitigation strategies of the potential environmental impacts of milk production at farm level. The environmental performances of a conventional intensive dairy farm in Northern Italy (baseline scenario) were compared with the results obtained: from the introduction of the third daily milking and from the adoption of anaerobic digestion (AD) of animal slurry in a consortium AD plant. The AD plant, fed only with animal slurries coming also from nearby farms. Key parameters concerning on-farm activities (forage production, energy consumptions, agricultural machines maintenance, manure and livestock management), off-farm activities (production of fertilizers, pesticides, bedding materials, purchased forages, purchased concentrate feed, replacement animals, agricultural machines manufacturing, electricity, fuel) and transportation were considered. The functional unit was 1 kg fat and protein corrected milk (FPCM) leaving the farm gate. The selected environmental impact categories were: global warming potential, acidification, eutrophication, photochemical oxidation and non-renewable energy use. The production of 1 kg of FPCM caused, in the baseline scenario, the following environmental impact potentials: global warming potential 1.12 kg CO 2 eq; acidification 15.5 g SO 2 eq; eutrophication 5.62 g PO 4 3 − eq; photochemical oxidation 0.87 g C 2 H 4 eq/kg FPCM; energy use 4.66 MJ eq. The increase of milking frequency improved environmental performances for all impact categories in comparison with the baseline scenario; in particular acidification and eutrophication potentials showed the largest reductions (− 11 and − 12%, respectively). In anaerobic digestion scenario, compared to the baseline one, most of the impact potentials were strongly reduced. In particular the most important advantages were in terms of acidification (− 29%), global warming (− 22%) and eutrophication potential (− 18%). The AD of cow slurry is confirmed as an effective strategy to mitigate the environmental impact of milk production at farm level. [ABSTRACT FROM AUTHOR]

The rainfall-induced release of pathogens and microbial indicators from land-applied manure and their subsequent removal with runoff and infiltration precedes the impairment of surface and groundwater resources. It has been assumed that rainfall intensity and changes in intensity during rainfall do not affect microbial removal when expressed as a function of rainfall depth. The objective of this work was to test this assumption by measuring the removal of Escherichia coli , enterococci, total coliforms, and chloride ion from dairy manure applied in soil boxes containing fescue, under 3, 6, and 9 cm h − 1 of rainfall. Runoff and leachate were collected at increasing time intervals during rainfall, and post-rainfall soil samples were taken at 0, 2, 5, and 10 cm depths. Three kinetic-based models were fitted to the data on manure-constituent removal with runoff. Rainfall intensity appeared to have positive effects on rainwater partitioning to runoff, and removal with this effluent type occurred in two stages. While rainfall intensity generally did not impact the parameters of runoff-removal models, it had significant, inverse effects on the numbers of bacteria remaining in soil after rainfall. As rainfall intensity and soil profile depth increased, the numbers of indicator bacteria tended to decrease. The cumulative removal of E. coli from manure exceeded that of enterococci, especially in the form of removal with infiltration. This work may be used to improve the parameterization of models for bacteria removal with runoff and to advance estimations of depths of bacteria removal with infiltration, both of which are critical to risk assessment of microbial fate and transport in the environment. [ABSTRACT FROM AUTHOR]

Environmental and economic impacts of feeding strategies in Costa Rican dairy farms. The aim of this study was to analyze feeding practices in Costa Rica’s dairy farms and their influence on greenhouse gas emissions (GHG). Methane (CH4), nitrous oxide (N2O), and income over feed cost (IOFC) were evaluated. This study was carried out at 104 dairy farms, which were distributed within a range of altitude from 1000 to 2400 meters above sea level. Using cluster analysis based on type of feed, grazing period, areas of forage and pastures; four feeding strategies were identified, which included different proportions of feed categories in daily rations. Emissions expressed as carbon dioxide equivalent per kilo of fat and protein corrected milk (CO2eq/FPCM) were higher for forage feeding strategies and lower for farms found in higher altitudes. Concentrate feed accounted for the higher cost in all feeding strategies, and represented more than 50% in the intensive concentrate based production system, whereas the costs of fertilizers were higher in pasture based feeding strategies. Income from milk sales was higher for the concentrate based feeding strategy. However, IOFC was the same for all feeding strategies in spite of the large differences in daily milk production. Feeding strategies influenced GHG emissions and feeding costs. Feeding strategies associated with lower GHG emissions within the farm were more dependent from external inputs. [ABSTRACT FROM AUTHOR]

Mitigating greenhouse gas (GHG) emissions per unit of milk or the carbon footprint (CF) of milk is a key issue for the European dairy sector given rising concerns over the potential adverse effects of climate change. Several strategies are available to mitigate GHG emissions, but producing milk with a low CF does not necessarily imply that a dairy farm is economically viable. Therefore, to understand the relationship between the CF of milk and dairy farm economic performance, the farm accountancy network database of a European Union nation (Ireland) was applied to a GHG emission model. The method used to quantify GHG emissions was life cycle assessment (LCA), which was independently certified to comply with the British standard for LCA. The model calculated annual on- and off-farm GHG emissions from imported inputs (e.g., electricity) up to the point milk was sold from the farm in CO2-equivalent (CO2-eq). Annual GHG emissions computed using LCA were allocated to milk based on the economic value of dairy farm products and expressed per kilogram of fat- and protein-corrected milk (FPCM). The results showed for a nationally representative sample of 221 grass-based Irish dairy farms in 2012 that gross profit averaged €0.18/L of milk and €1,758/ha and gross income was €40,899/labor unit. Net profit averaged €0.08/L of milk and €750/ha and net income averaged €18,125/labor unit. However, significant variability was noted in farm performance across each financial output measure. For instance, net margin per hectare of the top one-third of farms was 6.5 times higher than the bottom third. Financial performance measures were inversely correlated with the CF of milk, which averaged 1.20 kg of CO2-eq/kg of FPCM but ranged from 0.60 to 2.13 kg of CO2-eq/kg of FPCM. Partial least squares regression analysis of correlations between financial and environmental performance indicated that extending the length of the grazing season and increasing milk production per hectare or per cow reduced the CF of milk and increased farm profit. However, where higher milk production per hectare was associated with greater concentrate feeding, this adversely affected the CF of milk and economic performance by increasing both costs and off-farm emissions. Therefore, to mitigate the CF of milk and improve economic performance, grass-based dairy farms should not aim to only increase milk output, but instead target increasing milk production per hectare from grazed grass. [ABSTRACT FROM AUTHOR]

A total number of 947 calving records from 613 Holstein Friesian cows raised at a private dairy farm in Kelkit, Turkey, from 2004 to 2006 were used to study the effect of non-genetic factors on calving difficulty and stillbirth rate using CHAID algorithm. The mean calf birth weight was 41.0±0.19 kg. The overall incidence of calving difficulty and stillbirths in the Holstein Friesian herd were 9.1% and 9.4%, respectively. Calf birth weight, birth type and calving season had the greatest impact on calving difficulty. The increase in calf birth weight was associated with a significant increase in calving difficulties (P<0.01). The calving difficulty risk in twins (18.9%) was higher than in singleton calves (5.0%). The main environmental variables affecting the stillbirth rate were parity number, calf birth weight, sex of calf, calving season and calving difficulty. Parity number was statistically the most relevant factor affecting the stillbirth rate, which was also higher in primiparous (18.7%) than in muciparous cows (5.4%). As the calf birth weight increased, a significant increase was also in the stillbirth rate (P<0.01).The stillbirth rate in winter (19.7%) was higher than in other seasons (3.6%) (P<0.01). Calving assistance was associated with an increased risk of stillbirth (P<0.05). As a result, calf birth weight, birth type and calving season had the greatest impact variables on calving difficulty, however, parity, calf birth weight, sex, calving season and calving difficulty were the most effective variables on stillbirth in Holstein Friesian Cattle. [ABSTRACT FROM AUTHOR]

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This study used the Integrated Farm System Model to simulate the whole farm performance of a representative Wisconsin dairy farm and predict its economic and environmental outputs based on 25 yr of daily local weather data (1986 to 2010). The studied farm, located in southern Wisconsin, had 100 milking cows and 100 ha of cropland with no replacement heifers kept on the farm. Sensitivity analyses were conducted to test the effect of management strategies on energy-corrected milk production (ECM; 4.0% fat and 3.5% protein), net return to management, and greenhouse gas (GHG; including biogenic CO2) emission. The management strategies included (1) target milk production, for which the model optimized available resources to attain, and (2) herd structure, represented by the percentage of first-lactation cows. Weather conditions affected the outputs by changing the farm quantity and the quality of produced feed resources. As expected, when target milk production increased, the ECM increased positively and linearly to a certain level, and then it increased nonlinearly at a decreasing rate, constrained by available feed nutrients. Thereafter, the ECM reached the maximum potential milk production and remained flat regardless of higher target milk production input. Greenhouse gas emissions decreased between 3.4 and 7.3% at different first-lactation cow percentages. As the first-lactation cow percent increased from 15 to 45% in 5% intervals, GHG increased between 9.4 and 11.3% at different levels of target milk production. A high percentage of first-lactation cows reduced the maximum potential milk production. Net return to management had a similar changing trend as ECM. As the target milk production increased from 9,979 to 11,793 kg, the net return to management increased between 31 and 46% at different first-lactation cow percentages. Results revealed a win-win situation when increasing milk production or improving herd structure, which concurrently increased farm net return to management and decreased GHG emissions. [ABSTRACT FROM AUTHOR]

A recent increase in plasmid-mediated quinolone resistance ( PMQR) has been detected among Salmonella isolated from humans in the United States, and it is necessary to determine the sources of human infection. We had previously isolated Salmonella from dairy farm environmental samples collected in Texas, and isolates were tested for anti-microbial susceptibility. Two isolates, serotyped as Salmonella Muenster, showed the discordant pattern of nalidixic acid susceptibility and intermediate susceptibility to ciprofloxacin. For this project, whole-genome sequencing of both isolates was performed to detect genes associated with quinolone resistance. The plasmid-mediated qnrB19 gene and IncR plasmid type were identified in both isolates. To our knowledge, this is the first report of PMQR in Salmonella isolated from food animals or agricultural environments in the United States. [ABSTRACT FROM AUTHOR]

Greenhouse gas (GHG) emissions from dairy farms are a major concern. Our objectives were to assess the effect of mitigation strategies on GHG emissions and net return to management on 3 distinct farm production systems of Wisconsin. A survey was conducted on 27 conventional farms, 30 grazing farms, and 69 organic farms. The data collected were used to characterize 3 feeding systems scaled to the average farm (85 cows and 127 ha). The Integrated Farm System Model was used to simulate the economic and environmental impacts of altering feeding and manure management in those 3 farms. Results showed that incorporation of grazing practices for lactating cows in the conventional farm led to a 27.6% decrease in total GHG emissions [-0.16 kg of CO2 equivalents (CO2eq)/kg of energy corrected milk (ECM)] and a 29.3% increase in net return to management (+$7,005/yr) when milk production was assumed constant. For the grazing and organic farms, decreasing the forage-to-concentrate ratio in the diet decreased GHG emissions when milk production was increased by 5 or 10%. The 5% increase in milk production was not sufficient to maintain the net return; however, the 10% increase in milk production increased net return in the organic farm but not on the grazing farm. A 13.7% decrease in GHG emissions (-0.08 kg of CO2eq/kg of ECM) was observed on the conventional farm when incorporating manure the day of application and adding a 12-mo covered storage unit. However, those same changes led to a 6.1% (+0.04 kg of CO2eq/kg of ECM) and a 6.9% (+0.06 kg of CO2eq/kg of ECM) increase in GHG emissions in the grazing and the organic farms, respectively. For the 3 farms, manure management changes led to a decrease in net return to management. Simulation results suggested that the same feeding and manure management mitigation strategies led to different outcomes depending on the farm system, and furthermore, effective mitigation strategies were used to reduce GHG emissions while maintaining profitability within each farm. [ABSTRACT FROM AUTHOR]

Purpose: With land application of farm effluents from cows during housing or milking as an accepted practice, there are increasing concerns over its effect on nitrogen (N) loss through ammonia (NH) volatilization. Understanding the relative extent and seasonal variation of NH volatilization from dairy effluent is important for the development of management practices for reducing NH losses. The objectives of this study were to determine potential NH losses from application of different types of dairy effluent (including both liquid farm dairy effluent (FDE) and semi-solid dairy farm manure) to a pasture soil during several contrasting seasons and to evaluate the potential of the urease inhibitor (UI)-N-(n-butyl) thiophosphoric triamide (NBTPT, commercially named Agrotain) to reduce gaseous NH losses. Material and methods: Field plot trials were conducted in New Zealand on an established grazed pasture consisting of a mixed perennial ryegrass ( Lolium perenne L.)/white clover ( Trifolium repens L.) sward. An enclosure method, with continuous air flow, was used to compare the effects of treatments on potential NH volatilization losses from plots on a free-draining volcanic parent material soil which received either 0 (control) or 100 kg N ha as FDE or manure (about 2 and 15 % of dry matter (DM) contents in FDE or manure, respectively) with or without NBTPT (0.25 g NBTPT kg effluent N). The experiment was conducted in the spring of 2012 and summer and autumn of 2013. Results and discussion: Results showed that application of manure and FDE, both in fresh and stored forms, potentially led to NH volatilization, ranging from 0.6 to 19 % of applied N. Difference in NH losses depended on the season and effluent type. Higher NH volatilization was observed from both fresh and stored manure, compared to fresh and stored FDE. The difference was mainly due to solid contents. The losses of NH were closely related to NH-N content in the two types of manure. However, there was no relationship between NH losses and NH-N content in either type of FDE. There was no consistent seasonal pattern, although lower NH losses from fresh FDE and stored FDE applied in spring compared to summer were observed. Potential NH losses from application of fresh FDE or manure were significantly ( P < 0.05) reduced by 27 to 58 % when NBTPT was added, but the UI did not significantly reduce potential NH volatilization from stored FDE or manure. Conclusions: This study demonstrated that NH losses from application of FDE were lower than from manure and that UIs can be effective in mitigating NH emissions from land application of fresh FDE and manure. Additionally, reducing the application of FDE in summer can also potentially reduce NH volatilization from pasture soil. [ABSTRACT FROM AUTHOR]

Dairy farms control an important share of the agricultural area of Northern Italy. Zero grazing, large maize-cropped areas, high stocking densities, and high milk production make them intensive and prone to impact the environment. Currently, few published studies have proposed indicator sets able to describe the entire dairy farm system and their internal components. This work had four aims: i) to propose a list of agro-environmental indicators to assess dairy farms; ii) to understand which indicators classify farms best; iii) to evaluate the dairy farms based on the proposed indicator list; iv) to link farmer decisions to the consequent environmental pressures. Forty agro-environmental indicators selected for this study are described. Northern Italy dairy systems were analysed considering both farmer decision indicators (farm management) and the resulting pressure indicators that demonstrate environmental stress on the entire farming system, and its components: cropping system, livestock system, and milk production. The correlations among single indicators identified redundant indicators. Principal Components Analysis distinguished which indicators provided meaningful information about each pressure indicator group. Analysis of the communalities and the correlations among indicators identified those that best represented farm variability: Farm Gate N Balance, Greenhouse Gas Emission, and Net Energy of the farm system; Net Energy and Gross P Balance of the cropping system component; Energy Use Efficiency and Purchased Feed N Input of the livestock system component; N Eco-Efficiency of the milk production component. Farm evaluation, based on the complete list of selected indicators demonstrated organic farming resulted in uniformly high values, while farms with low milk-producing herds resulted in uniformly low values. Yet on other farms, the environmental quality varied greatly when different groups of pressure indicators were considered, which highlighted the importance of expanding environmental analysis to effects within the farm. Statistical analysis demonstrated positive correlations between all farmer decision and pressure group indicators. Consumption of mineral fertiliser and pesticide negatively influenced the cropping system. Furthermore, stocking rate was found to correlate positively with the milk production component and negatively with the farm system. This study provides baseline references for ex ante policy evaluation, and monitoring tools for analysis both in itinere and ex post environment policy implementation. [Copyright &y& Elsevier]

In the western United States where dairy wastewaters are commonly land applied, there are concerns over individuals being exposed to airborne pathogens. In response, a quantitative microbial risk assessment (QMRA) was performed to estimate infectious risks after inhalation exposure of pathogens aerosolized during center pivot irrigation of diluted dairy wastewaters. The dispersion of pathogens (Campylobacter jejuni, Escherichia coli 01S7:H7, non-0157 E. coli, Listeria monocytogenes, and Salmonella spp.) was modeled using the atmospheric dispersion model, AERMOD. Pathogen concentrations at downwind receptors were used to calculate infectious risks during one-time (1, 8, and 24 h) and multiday (7 d at 1 h d-1) exposure events using a β-Poisson dose-response model. This assessment considered risk of infection in residential populations that were 1 to 10 km from a center pivot operation. In the simulations, infectious risks were estimated to be the greatest in individuals closest to the center pivot, as a result of a higher pathogen dose. On die basis of the results from this QMRA, it is recommended that wastewaters only be applied during daylight hours when inacrivation and dilution of airborne pathogens is highest. Further refinement of the dispersion and dose-response models should be considered to increase die utility of this QMRA. [ABSTRACT FROM AUTHOR]

Riparian zones adjacent to cropped lands are effective at reducing nitrate (NO3-) loads to receiving water bodies primarily through plant assimilation and denitrification. Denitrification represents a permanent removal pathway and a greenhouse gas source, converting NO3- to inert N2 gas or nitrous oxide (N2O), and has been the subject of many studies in agricultural landscapes. Despite the prevailing notion that riparian zones can be areas of enhanced denitrification, there is a lack of in situ denitrification measurements from these areas that buffer streams and rivers from NO3- originating in upland cropped soils, especially over time scales that capture seasonal dynamics. We measured in situ groundwater denitrification rates in two riparian zones of an intensive dairy farm located in the headwaters of the Susquehanna River. Denitrification rates determined monthly over a 1-yr period with the 15N-NO3 push-pull method ranged from 0 to 4177 µgN kg soil-1 d-1 (mean, 830 ± 193 µg N kg soil-1 d-1). Denitrification showed a distinct seasonal pattern, with highest rates observed in the spring and summer, concomitant with warmer temperatures and decreasing dissolved oxygen. We estimate an annual N loss of 470 ± 116 kg yr-1 ha-1 of riparian zone via denitrification in the shallow saturated zone, with the potential for > 20% of this amount occurring as N2O. Total denitrification from shallow groundwater in the riparian zone was equivalent to 32% of manure N spread on the adjacent upland field, confirming the importance of riparian zones in agricultural landscapes at controlling N loads entering downstream waters. [ABSTRACT FROM AUTHOR]

The New Zealand dairy industry produces approximately 17% of this country's total greenhouse gas emissions (GHG-e) and it is also this nation's largest export industry. The industry needs to reduce GHG-e under proposed policy directives and for ongoing market security. Given these pressures, there is the need to identify cost-effective management strategies to reduce on-farm GHG-e. The objective of this study was to investigate how the management of dairy farms in the Waikato region of New Zealand could change to minimise the abatement costs associated with GHG-e mitigation. Three typical farm systems importing low (less than 10%), medium (10–20%), and high (more than 20%) amounts of supplement are modelled using a non-linear optimisation model. A reduction in nitrogen fertiliser application was the production factor that changed the most to achieve the cap in all of the simulated systems, followed by a reduction in stocking rate. With the prices used in this study, decreasing farming intensity by reducing nitrogen fertiliser by 21–42% and stocking rate by 8–10% represented a cost of $68–$119/ha and a production reduction of 54–117 kg MS/ha for the three systems studied. Improving reproductive performance proved to be effective in reducing GHG-e, allowing for fewer replacement cows to be supported. However, it did not have a significant effect on profit when emissions were unconstrained. Nitrification inhibitors and stand-off pads were not identified as useful mitigation options, given their high cost relative to de-intensification. [Copyright &y& Elsevier]

The objectives of the study were to compare the climate conditions of 7 dairy farms with the climate recorded at the closest official meteorological station. Specifically, we set out to compare the ambient temperature, relative humidity, and the resulting temperature-humidity index (THI) from 7 different barns with those data obtained from the closest official meteorological stations and to compare the climate conditions between 4 different locations within 1 barn. Measures of correlation and agreement demonstrated that climate conditions differ significantly between the barn and the corresponding official meteorological stations as well as between 4 different locations inside 1 barn. The ambient temperature was higher (6.4 ± 3.6°C) in the barn than at the official meteorological station. The relative humidity was higher at the official meteorological station (0.2 ± 7.2%) than in the barn. The THI was higher (11.1 ± 6.5) in the barn than at the official meteorological station. Days with an average THI ≥ 72 were 64 and 4 out of 756 experimental d in the barn and at the official meteorological station, respectively. Also, in a comparison of 7 different barns, ambient temperature and THI were significantly higher than at the closest corresponding official meteorological station. These results indicate that climate conditions should be obtained from on-farm measurements to evaluate potential heat stress and to develop effective measures to abate heat stress of dairy cows. [ABSTRACT FROM AUTHOR]

A new ammonia (NH3) analyzer was developed based on off-axis integrated cavity output spectroscopy. Its feasibility was demonstrated by making tropospheric measurements in flights aboard the Department of Energy Gulfstream-1 aircraft. The ammonia analyzer consists of an optical cell, quantum-cascade laser, gas sampling system, control and data acquisition electronics, and analysis software. The NH3 mixing ratio is determined from high-resolution absorption spectra obtained by tuning the laser wavelength over the NH3 fundamental vibration band near 9.67 μm. Excellent linearity is obtained over a wide dynamic range (0-101 ppbv) with a response rate (1/e) of 2 Hz and a precision of ±90 pptv (1σ in 1 s). Two research flights were conducted over the Yakima Valley in Washington State. In the first flight, the ammonia analyzer was used to identify signatures of livestock from local dairy farms with high vertical and spatial resolution under low wind and calm atmospheric conditions. In the second flight, the analyzer captured livestock emission signals under windy conditions. Our results demonstrate that this new ammonia spectrometer is capable of providing fast, precise, and accurate in situ observations of ammonia aboard airborne platforms to advance our understanding of atmospheric compositions and aerosol formation. [ABSTRACT FROM AUTHOR]

The big dairy in farms in Albania are getting more complex than before. They have started to be more concentrated in last years with breeds that produce higher yields of milk and very depended on purchase feed outside the farm. The economic factor and environmental impact are very much related with nutrient balance of whole farm. Therefore strategies and software to manage and calculate these balance are important tools in controlling the impact to the environment and the overall performance of dairy farms in Albania. Relation between the nutrient balance and utilization of nutrient in dairy farms are not fully understood from dairy farm operators in Albania and it seems that is new concept. The dairy farms are not requested management plan to control the manure and wastewater as well as a yearly plan of nutrient management. These two plans should be an important objectives in coming years according to the request of a effective management plan of discharges for every dairy farms in Albania. The research on whole farm dairy nutrient balance in central part of Albania is in its initial stages and it aim to provide an overview of whole farm nutrient balance situation and used its findings as an indicator to overall performance and environment impact of Albanian dairy farms. This article provides information of the present situation of dairy farms in relation with nutrient balance and compare it with other international findings. All the calculation of nitrogen ustilization express the balance as proportion. So the information of nutrient balances of diferent farms target evaluated in the study (only based on the information collected direct from target farms in central part of Albania) result on inbalances and direct losses of nitrogen ranging from 62% -89%. [ABSTRACT FROM AUTHOR]

Little consideration has been given to how farm management, specifically tactics used to implement the management strategy, may influence the carbon footprint (CF) and land use for milk produced on commercial farms. In this study, the CF and land use of milk production from 18 Irish commercial dairy farms were analyzed based on foreground data from a 12-mo survey capturing management tactics and background data from the literature. Large variation was found in farm attributes and management tactics; for example, up to a 1.5-fold difference in fertilizer nitrogen input was used to support the same stocking density, and up to a 3.5-fold difference in concentrate fed for similar milk output per cow. However, the coefficient of variation for milk CF between farms only varied by 13% and for land use by 18%. The overall CF and overall land use of the milk production from the 18 dairy farms was 1.23 ± 0.04 kg of CO2 Eq and 1.22 ± 0.05 m² per kilogram of energy-corrected milk. Milk output per cow, economic allocation between exports of milk and liveweight, and on-farm diesel use per ha were found to be influential factors on milk CF, whereas the fertilizer N rate, milk output per cow, and economic allocation between exports of milk and liveweight were influential on land use. Effective sward management of white clover within a few farms appeared to lower the CF but increased on-farm land use. It was concluded that a combination of multiple tactics determines CF and land use for milk production on commercial dairy farms and, although these 2 measures of environmental impact are correlated, a farm with a low CF did not always have low land use and vice versa. [ABSTRACT FROM AUTHOR]

Abstract: Six dairy farms with the same on-farm area and milk production were compared. One farm (G-No) used grass as the sole forage for a herd of Normande cows, a dual-purpose breed. Three farms, with Holstein cows, varied forage for the herd from grass only (G-Ho) to low (G/LM-Ho) or high (G/HM-Ho) proportion of maize silage in the total forage area. Finally, two farms based on G/LM-Ho and G/HM-Ho systems aimed to increase omega-3 fatty acids in the winter diets of cows (G/LM/O3-Ho, G/HM/O3-Ho). Allocation methods (biophysical, protein, economic allocation) and system expansion applied for co-product (milk and meat) handling were examined. The impact categories considered were climate change, climate change including the effects of land use and land use change (CC/LULUC), cumulative energy demand, eutrophication, acidification and land occupation. The impacts per kg of fat-and-protein-corrected milk (FPCM) of G-No were highest, followed by those of G-Ho, G/LM-Ho and G/HM-Ho, regardless co-product handling methods and impact categories (except for eutrophication). CC/LULUC per kg FPCM of G/LM/O3-Ho and G/HM/O3-Ho were both 1% and 3% lower than those of G/LM-Ho and G/HM-Ho, respectively, but other impacts were higher. With system expansion, impacts per kg FPCM were lower than when allocation methods were used. Enteric fermentation was the greatest contributor (45–50%) to CC/LULUC, while grass production was the most important contributor to other impacts. The highest CC/LULUC (for G-No) can be explained by (1) G-No having the lowest milk yield/cow (though it produced the most meat) and (2) the fact that grass required more N fertiliser, but had lower yields than silage maize, even though grassland sequestered C. Among Holstein systems, increasing cow productivity by increasing feed intake (including maize silage and supplementing with concentrate) decreased impacts of milk. Reducing replacement rate and age of first calving also decreased impacts of milk. Increasing cow productivity reduced the amount of on-farm area required to produce a given amount of milk. Thus, the “liberated” on-farm area of Holstein systems was used to produce cash crops, and total impacts of these systems were lower than those of G-No (except for eutrophication and land occupation). [Copyright &y& Elsevier]

Inverse dispersion models are useful tools for estimating emissions from animal feeding operations, waste storage ponds, and manure application fields. Atmospheric stability is an important input parameter to such models. The objective of this study was to compare emission rates calculated with a backward Lagrangian stochastic (bLS) inverse-dispersion model (WindTrax) using three different methods for calculating atmospheric stability: sonic anemometer, gradient Richardson number, and Pasquill-Gifford (P-G) stability class. Ammonia and methane emission data from a compost yard at a 10,000-cow dairy were used for the comparisons. Overall, average emission rates were not significantly different among the stability methods. Emission rates correlated well between the sonic and other methods (r² > 0.79, p < 0.001). The slopes of the regression lines between the sonic and Richardson methods were 0.95 and 1.0 for CH4 and NH3, respectively. The regression line slopes for the P-G method were about 1.9 for CH4 and 1.6 for NH3, which means emission rates predicted with the P-G method tended to be 50% to 100% greater than rates predicted with sonic anemometer data. Based on this limited data set, using the gradient Richardson method to represent atmospheric stability resulted in emission rates that more closely matched emission rates from the sonic method. Considering the amount of variability inherent in emissions calculations, a three-dimensional sonic anemometer should be used, if possible, to directly provide the necessary data to calculate parameters representing wind properties, rather than inferring values from other stability classification methods. [ABSTRACT FROM AUTHOR]

Biofiltration, whereby CH4 is oxidized by methanotrophic bacteria, is a potentially effective strategy for mitigating CH4 emissions from anaerobic dairy effluent lagoons/ponds, which typically produce insufficient biogas for energy recovery. This study reports on the effectiveness of a biofilter cover design at oxidizing CH4 produced by dairy effluent ponds. Three substrates, a volcanic pumice soil, a garden-waste compost, and a mixture of the two, were tested as media for the biofilters. All substrates were suspended as 5 cm covers overlying simulated dairy effluent ponds. Methane fluxes supplied to the filters were commensurate with emission rates from typical dairy effluent ponds. All substrates oxidized more than 95% of the CH4 influx (13.9 g CH4 m-3 h-1) after two months and continued to display high oxidation rates for the remaining one month of the trial. The volcanic soil biofilters exhibited the highest oxidation rates (99% removal). When the influx CH4 dose was doubled for a month, CH4 removal rates remained >90% for all substrates (maximum = 98%, for the volcanic soil), suggesting that biofilters have a high capacity to respond to increases in CH4 loads. Nitrous oxide emissions from the biofilters were negligible (maximum = 19.9 mg N2O m-3 h-1) compared with CH4 oxidation rates, particularly from the volcanic soil that had a much lower microbial-N (75 mg kg-1) content than the compost-based filters (>240 mg kg-1). The high and sustained CH4 oxidation rates observed in this laboratory study indicate that a biofilter cover design is a potentially efficient method to mitigate CH4 emissions from dairy effluent ponds. The design should now be tested under field conditions. [ABSTRACT FROM AUTHOR]

Wastewater from concentrated animal feeding operations (CAFOs) frequently contains high concentrations of steroid estrogenic hormones. Release of these hormones into the environment may occur when CAFO wastewater is applied to agricultural lands as a nutrient and water source for crop production. To assess the potential risk of hormone contaminants derived from animal wastewater, we investigated the transformation kinetics and mechanisms of three natural estrogenic hormones (17α-estradiol, 17β-estradiol, and estrone) in aqueous solutions blended with dairy lagoon water under anaerobic conditions. Initial transformations of the three hormones in the dairy lagoon water were dominated by biodegradation and the degradation rates were temperature-dependent. The total amounts of hormones (initial concentration at 5 mg L-1) remaining in the solution after 52 days at 35 °C accounted for approximately 85%, 78%, and 77% of the initial amounts of 17α-estradiol, 17β-estradiol, and estrone, respectively. This observation suggests that these hormones are relatively stable over time and may accumulate in anaerobic or anoxic environments and anaerobic CAFO lagoons. A racemization reaction between 17α-estradiol and 17β-estradiol via estrone was observed in aqueous solutions in the presence of CAFO wastewater under anaerobic conditions. The initial hormone concentrations did not affect this degradation mechanism. A reversible reaction kinetic model was applied to fit the observed transformation dynamics. The degradation and regeneration of the parent hormone and its metabolites were successfully simulated by this model. The information in this study is useful for assessing the environmental risk of steroid hormones released from CAFO wastewater and to better understand why these hormone contaminants persist in many aquatic environments. [ABSTRACT FROM AUTHOR]

Background, aim and scope: Studies on the contribution of milk production to global greenhouse gas (GHG) emissions are rare (FAO 2010) and often based on crude data which do not appropriately reflect the heterogeneity of farming systems. This article estimates GHG emissions from milk production in different dairy regions of the world based on a harmonised farm data and assesses the contribution of milk production to global GHG emissions. Materials, methods and results: The methodology comprises three elements: (1) the International Farm Comparison Network (IFCN) concept of typical farms and the related globally standardised dairy model farms representing 45 dairy regions in 38 countries; (2) a partial life cycle assessment model for estimating GHG emissions of the typical dairy farms; and (3) standard regression analysis to estimate GHG emissions from milk production in countries for which no typical farms are available in the IFCN database. Across the 117 typical farms in the 38 countries analysed, the average emission rate is 1.50 kg CO equivalents (CO-eq.)/kg milk. The contribution of milk production to the global anthropogenic emissions is estimated at 1.3 Gt CO-eq./year, accounting for 2.65% of total global anthropogenic emissions (49 Gt; IPCC, Synthesis Report for Policy Maker, Valencia, Spain, 2007). Discussion and conclusion: We emphasise that our estimates of the contribution of milk production to global GHG emissions are subject to uncertainty. Part of the uncertainty stems from the choice of the appropriate methods for estimating emissions at the level of the individual animal. [ABSTRACT FROM AUTHOR]

The article presents a study which depicts the use of a dispersion model to compute whole-farm emissions of methane (CH4) from three dairy farms in Alberta. The model used in conjunction with stability of the air and field measurements of CH4 concentration during three sequential campaigns carried out in November 2004 and May and July 2005. The dairy farms had different manure handling operations and ranged in herd size from 208 to 351 cows. The approach to recognize the farm-to-farm differences in CH4 emissions as affected by manure management, animal type and diet is important when using whole-farm emission measurements for inventory and mitigation applications.

Understanding the ecology of methanogens in natural and engineered environments is a prerequisite to predicting or managing methane emissions. In this study, a novel high-throughput fingerprint method was developed for determining methanogen diversity and relative abundance within environmental samples. The method described here, designated amplicon length heterogeneity PCR of the mcrA gene ( LH-mcr A), is based on the natural length variation in the mcrA gene. The mcrA gene encodes the alpha-subunit of the methyl-coenzyme M reductase, which is involved in the terminal step of methane production by methanogens. The methanogenic communities from stored swine and dairy manures were distinct from each other. To validate the method, methanogenic communities in a plug flow-type bioreactor ( PFBR) treating swine manure were characterized using LH-mcr A method and correlated to mcrA gene clone libraries. The diversity and relative abundance of the methanogenic groups were assessed. M ethanobrevibacter, M ethanosarcinaceae, M ethanoculleus, M ethanogenium, M ethanocorpusculum and one unidentified group were assigned to particular LH-mcr A amplicons. Particular phylotypes related to M ethanoculleus were predominant in the last compartment of the PFBR where the bulk of methane was produced. LH-mcr A method was found to be a reliable, fast and cost-effective alternative for diversity assessment of methanogenic communities in microbial systems. [ABSTRACT FROM AUTHOR]

Abstract: Environmental contamination with Mycobacterium avium subsp. paratuberculosis (MAP) is thought to be one of the primary sources of infection for dairy cattle. The exact link between fecal shedding of MAP by individual cows and environmental contamination levels at the herd level was explored with a cross-sectional analysis of longitudinally collected samples on 3 dairy farms. Composite samples from multiple environmental sites in 3 commercial dairy herds in the Northeast US were cultured quarterly for MAP, providing 1131 samples (133 (11.8%) were culture-positive), and all adult animals in the herds were tested biannually by fecal culture (FC), for 6 years. Of the environmental sites sampled, manure storage areas and shared alleyways were most likely to be culture-positive. Environmental sample results were compared to FC results from either the concurrent or previous sampling date at both the herd and the pen level. At the herd level, a 1log unit increase in average fecal shedding increased the odds of a positive non-pen environmental sample by a factor of 6 and increased the average amount of MAP in non-pen samples by 2.9cfu/g. At the pen level, a 1log unit increase in average fecal shedding in the pen increased the odds of a positive environment by a factor of 2.4 and the average amount of MAP was increased by 3.5cfu/g. We were not able to model the relationship between non-pen environmental sample status and the distance between shedding animals and the sample''s location, and neighboring pens did not significantly affect the results of the pen-level analysis. The amount of MAP in pen-level samples and the probability of a pen testing positive for MAP were both positively but non-significantly correlated with the number of animals in the pen shedding >30cfu/g of MAP. At least 6 environmental samples met the criteria for the U.S. Voluntary Bovine Johne''s Disease Control Program on 47 of the 72 sampling dates; of these, 19 of the 47 FC-positive sampling dates were positive by the 6-sample environmental testing method, resulting in a herd sensitivity of 0.40 (95% CI: 0.26–0.54). None of the 3 FC-negative sampling dates produced positive environmental samples. Although environmental sampling can be used as a tool in understanding the level of MAP infection in a herd or pen, it did not appear to be a sensitive diagnostic method for herd positivity in these low prevalence herds, and its use may require caution. [Copyright &y& Elsevier]

The purpose of this study was to compile and evaluate relationships between feed nitrogen (N) intake, milk urea N (MUN), urinary urea N (UUN), and ammonia (NH3) emissions from dairy farms to aid policy development. Regression relationships between MUN, UUN, and NH3 emissions were compiled from studies conducted in Wisconsin, California, and the Netherlands. Relative reductions in NH3 emissions were calculated as percentage decreases in NH3 emissions associated with a baseline MUN level of 14 mg/dL (prevailing industry average). For 3 studies with cows in stanchion barns, relative NH3 emission reductions of 10.3 to 28.2% were obtained when MUN declined from 14 to 10 mg/dL. Similarly, analyses of 2 freestall studies provided relative NH3 emission reductions of 10.5 to 33.7% when MUN levels declined from 14 to 10 mg/dL. The relative reductions in NH3 emissions from both stanchion and freestall barns can be associated directly with reductions in UUN excretion, which can be determined using MUN. The results of this study may help create new awareness, and perhaps eventual industry-based incentives, for management practices that enhance feed N use efficiency and reduce MUN, UUN, and NH3 emissions from dairy farms. [ABSTRACT FROM AUTHOR]