No nationwide studies of the incidence rate of clinical mastitis (IRCM) have been conducted in Canada. Because the IRCM and distribution of mastitis-causing bacteria may show substantial geographic variation, the primary objective of this study was to determine regional pathogen-specific IRCM on Canadian dairy farms. Additionally, the association of pathogen-specific IRCM with bulk milk somatic cell count (BMSCC) and barn type were determined. In total, 106 dairy farms in 10 provinces of Canada participated in the study for a period of 1 yr. Participating producers recorded 3,149 cases of clinical mastitis. The most frequently isolated mastitis pathogens were , , , and coagulase-negative staphylococci. Overall mean and median IRCM were 23.0 and 16.7 cases per 100 cow-years in the selected herds, respectively, with a range from 0.7 to 97.4 per herd. No association between BMSCC and overall IRCM was found, but and culture-negative IRCM were highest and IRCM was lowest in low and medium BMSCC herds. , , and IRCM were lowest in the Western provinces. and IRCM were highest in Québec. Cows in tie-stalls had higher incidences of , , coagulase-negative staphylococci, and other streptococcal IRCM compared with those in free-stalls, whereas cows in free stalls had higher spp. and IRCM than those in tie-stall barns. The focus of mastitis prevention and control programs should differ between regions and should be tailored to farms based on housing type and BMSCC.
Hristov, A. N., Hanigan, M., Cole, A., Todd, R., McAllister T. A., Ndegwa, P. and Rotz, A. 2011. Review: Ammonia emissions from dairy farms and beef feedlots. Can. J. Anim. Sci. 91: 1-35. Ammonia emitted from animal feeding operations is an environmental and human health hazard, contributing to eutrophication of surface waters and nitrate contamination of ground waters, soil acidity, and fine particulate matter formation. It may also contribute to global warming through nitrous oxide formation. Along with these societal concerns, ammonia emission is a net loss of manure fertilizer value to the producer. A significant portion of cattle manure nitrogen, primarily from urinary urea, is converted to ammonium and eventually lost to the atmosphere as ammonia. Determining ammonia emissions from cattle operations is complicated by the multifaceted nature of the factors regulating ammonia volatilization, such as manure management, ambient temperature, wind speed, and manure composition and pH. Approaches to quantify ammonia emissions include micrometeorological methods, mass balance accounting and enclosures. Each method has its advantages, disadvantages and appropriate application. It is also of interest to determine the ammonia emitting potential of manure (AEP) independent of environmental factors. The ratio of nitrogen to non-volatile minerals (phosphorus, potassium, ash) or nitrogen isotopes ratio in manure has been suggested as a useful indicator of AEP. Existing data on ammonia emission factors and flux rates are extremely variable. For dairy farms, emission factors from 0.82 to 250 g ammonia per cow per day have been reported, with an average of 59 g per cow per day (n = 31). Ammonia flux rates for dairy farms averaged 1.03 g m(-2) h(-1) (n = 24). Ammonia losses are significantly greater from beef feedlots, where emission factors average 119 g per animal per day (n = 9) with values as high as 280 g per animal per day. Ammonia flux rate for beef feedlots averaged 0.174 g m(-2) h(-1) (n = 12). Using nitrogen mass balance approaches, daily ammonia nitrogen losses of 25 to 50% of the nitrogen excreted in manure have been estimated for dairy cows and feedlot cattle. Practices to mitigate ammonia emissions include reducing excreted N (particularly urinary N), acidifying ammonia sources, or binding ammonium to a substrate. Reducing crude protein concentration in cattle diets and ruminal protein degradability are powerful tools for reducing N excretion, AEP, and whole-farm ammonia emissions. Reducing dietary protein can also benefit the producer by reducing feed cost. These interventions, however, have to be balanced with the risk of lost production. Manure treatment techniques that reduce volatile N species (e.g., urease inhibition, pH reduction, nitrification-denitrification) are also effective for mitigating ammonia emissions. Another option for reducing ammonia emissions is capture and treatment of released ammonia. Examples in the latter category include biofilters, permeable and impermeable covers, and manure incorporation into the soil for crop or pasture production. Process-level simulation of ammonia formation and emission provides a useful tool for estimating emissions over a wide range of production practices and evaluating the potential benefits of mitigation strategies. Reducing ammonia emissions from dairy and beef cattle operations is critical to achieving environmentally sustainable animal production that will benefit producers and society at large.
Occupational exposure to harmful bioaerosols in industrial environments is a real threat to the workers. In particular, dairy-farm workers are exposed to high levels of fungal bioaerosols on a daily basis. Associating bioaerosol exposure and health problems is challenging and adequate exposure monitoring is a top priority for aerosol scientists. Using only culture-based tools does not express the overall microbial diversity and underestimate the large spectrum of microbes in bioaerosols and therefore the extended fungal profile that farmers are exposed to. The aim of this study was to provide an in-depth characterization of fungal exposure at Eastern Canadian dairy farms using qPCR and high-throughput sequencing methods. Specific primers were used for the quantification of / and in dairy farms air samples. Illumina Miseq sequencing of the ITS1 region provided sequences for the diversity analyses. The minimum and maximum concentration of / ranged from 4.6 × 10 to 9.4 × 10 gene copies/m and from 1 × 10 gene copies/m to 4.8 × 10 gene copies/m for , respectively. Differences in the diversity profiles of the five dairy farms support the idea that the novel approach identifies a large number of fungal taxa. The most striking differences include , , , , , , , , and . The presence of a diverse portrait of fungi in air may represent a health risk for workers who are exposed on a daily basis. The broad spectrum of fungi detected in this study includes many known pathogens like , , and . Adequate monitoring of bioaerosol exposure is necessary to evaluate and minimize risks.
A survey was performed on 19 dairy farms in Manitoba representing a range of sizes, feeding, housing and management systems to identify factors that affect the utilization of dietary phosphorus (P) by lactating dairy cows. Each farm was visited once to collect milk, blood, feed and feces samples as well as production data from 10 early/peak, 10 mid-lactation, and 10 late lactation cows. Phosphorus content of feed (FEED P), feces (FECAL P), milk (MILK P), blood (BLOOD P) and calcium content of feed (Ca) were determined. Pearson correlation analysis among the various measures was conducted using SAS 9.4 software. The average P contents (DM basis) of FEED P, FECAL P, MILK P, and BLOOD P was 0.41% (0.34 and 0.53%), 0.76% (0.30 and 1.35%), 0.09% (0.05 and 0.12%) and 2.04 mmol/L (1.34 to 3.04 mmol/L), respectively. The output of P in milk (P OUT) which is obtained by multiplying MILK P with daily milk yield (MY), was positively correlated with the MILK P, FEED P, MY, Parity, Ca and negatively correlated with days in milk (DIM). But no correlation was observed with the BLOOD P and FECAL P. FEED P was positively correlated with the MILK P, FECAL P, MY, and negatively correlated with Ca and DIM. BLOOD P was positively correlated with Ca and DIM, but not correlated with any other measures (Table 1). Results show that the P content of diets, and feces vary considerably among cows and among farms, suggesting that the P contents in diets and feces can be reduced. Furthermore, more than 50% of the animals received diets which contain excess P levels than the NRC (2001) recommendations. The P content of blood was not indicative of P output in milk, nor the P contents of the diet or feces. The output of P in milk was highly correlated with the yield and P content of milk, but a 1% increase in the dietary P content lead to a 0.21% increase in P OUT. Better understanding of the dynamics between these dietary and cow factors can help to develop efficient P management strategies to improve P utilization and avoid excess P use.
Public concerns regarding the quality of life of farm animals are often focused on specific practices such as separating the cow and calf immediately after birth. The available scientific literature provides some evidence in support of this practice (including reduced acute responses to separation when it does occur), as well as evidence of disadvantages (such as increased risk of uterine disease in cows). The aim of this study is to systematically examine public views around this practice. Specifically, this study analyzes the views of American and German citizens to separation of cow and calf at birth using a quantitative segmentation approach. Although the majority of participants opposed early separation, a small proportion of our sample supported the practice. According to participants' preference for early and later separation and their evaluation of different arguments for both practices, three clusters were identified. US participants were more likely to support early separation compared to German participants. The arguments presented for and against both practices caused different reactions in the three clusters, but did not appear to sway the opinions of most participants. The results show considerable opposition to the practice of early separation in large parts of the sample and suggest that the dairy industry should consider approaches to address this concern.
Purpose This systematic literature review integrates the findings of existing studies regarding technical efficiency (TE) in dairy farms. The purpose of this paper is to offer a research framework that assembles TE descriptors, a classification of previous literature that provides the basis for the synthesis and research agenda. Design/methodology/approach This paper systematically reviews 86 survey research studies using rigorous and reproducible procedures. The review is applied to published survey research. Findings The framework relates context, inputs, outputs and metrics of TE. There is no agreement among the authors on the context and determinants of TE. The main determinants of TE are geographical location, farm size, investments in veterinary care, feeding and milking practice, TE model estimation techniques, public policy, and management-related variables. This paper offers ten propositions for future research on the controversial results on the determinants of TE. The authors also explore the reasons for the discrepant results based on the Debreu-Farrell’s definition of TE, the contingency theory and the resource-based view of the firm, elucidating the literature and serving as a basis for future investigation. Implications for dairy farmers and researchers close the review. Originality/value Meta-analysis and meta-regression studies were long at the forefront of reviews in the TE of dairy farms. This paper offers a novel qualitative research synthesis with frameworks and the classification of previous literature and a research agenda, which provides a new and different perspective for analysis, by innovating over the available quantitative procedures to combine statistical results.
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.
Freshwater use in agriculture is a matter of discussion due to rising concerns over water scarcity, availability and pollution. To make robust predictions of freshwater demand, a large dataset of agricultural data is needed to discern the relationships between production parameters and water demand. The objective of this research was to predict freshwater demand (L yr ) on Irish dairy farms based on a minimal set of farm data. A detailed water footprint (WF) was calculated for 20 dairy farms for 2014 and 2015, and the relationships between the WF and agricultural inputs explored via a mixed modelling procedure, to develop a minimal footprinting solution. The WF comprised of the consumption of soil moisture due to evapotranspiration (green water, GW) and ground and surface water (blue water, BW). The performance of the models was validated using an independent data set of five dairy farms. The GW model was applied to 221 dairy farms to establish the relationship between the GWF of milk and economic performance. The average total volumetric WF of the 20 farms was 778 L/kg fat and protein corrected milk (L/kg FPCM) (range 415–1338 L/kg FPCM). Freshwater for pasture production made up 93% of the GW footprint. Grass grown, imported forages and concentrates fed were all significant predictors of GW. The relative prediction error (RPE) of the GW model was 11.3%. Metered on-farm water and concentrates were both significant predictors of BW. The RPE of the BW model was 3.4%. When applied to 221 dairy farms ranked by net margin per hectare, there was a trend (P < 0.05) towards higher profitability as the GWF decreased, indicating that the GWF of dairy farms can be improved by implementing good management practices aligned with improving profitability.
Life Cycle Assessment (LCA) is often used for the environmental evaluation of agri-food systems due to its holistic perspective. In particular, the assessment of milk production at farm level requires the evaluation of multiple dairy farms to guarantee the representativeness of the study when a regional perspective is adopted. This article shows the joint implementation of LCA and Data Envelopment Analysis (DEA) in order to avoid the formulation of an average farm, therefore preventing standard deviations associated with the use of average inventory data while attaining the characterization and benchmarking of the operational and environmental performance of dairy farms. Within this framework, 72 farms located in Galicia (NW Spain) were subject to an LCA + DEA study which led to identify those farms with an efficient operation. Furthermore, target input consumption levels were benchmarked for each inefficient farm, and the corresponding target environmental impacts were calculated so that eco-efficiency criteria were verified. Thus, average reductions of up to 38% were found for input consumption levels, leading to impact reductions above 20% for every environmental impact category. Finally, the economic savings arising from efficient farming practices were also estimated. Economic savings of up to 0.13 € per liter of raw milk were calculated, which means extra profits of up to 40% of the final raw milk price. ► Computation of operational and environmental benchmarks for dairy farming. ► Operational reductions of up to 38%, leading to impact reductions above 20%. ► Lack of a consistent pattern linking operational efficiency to specific parameters. ► Quantification of the economic savings related to the move towards efficiency. ► Validation of LCA + DEA methodology.