Antimicrobial use on Canadian dairy farms

Antimicrobial use (AMU) data are critical for formulating policies for containing antimicrobial resistance. The present study determined AMU on Canadian dairy farms and characterized variation in AMU based on herd-level factors such as milk production, somatic cell count, herd size, geographic region and housing type. Drug use data were collected on 89 dairy herds in 4 regions of Canada, Alberta, Ontario, Québec, and the Maritime provinces (Prince Edward Island, New Brunswick, and Nova Scotia) for an average of 540 d per herd. Dairy producers and farm personnel were asked to deposit empty drug containers into specially provided receptacles. Antimicrobial use was measured as antimicrobial drug use rate (ADUR), with the unit being number of animal defined-daily doses (ADD)/1,000 cow-days. Antimicrobial drug use rates were determined at farm, region, and national level. Combined ADUR of all antimicrobial classes was 14.35 ADD/1,000 cow-days nationally. National level ADUR of the 6 most commonly used antimicrobial drug classes, cephalosporins, penicillins, penicillin combinations, tetracyclines, trimethoprim-sulfonamide combinations, and lincosamides were 3.05, 2.56, 2.20, 1.83, 0.87, and 0.84 ADD/1,000 cow-days, respectively. Dairy herds in Ontario were higher users of third-generation cephalosporins (ceftiofur) than in Québec. Alberta dairy herds were higher users of tetracyclines in comparison to Maritimes. Antimicrobial drug use rate was higher via systemic route as compared with intramammary and other routes of administration (topical, oral, and intrauterine). The ADUR of antimicrobials used intramammarily was higher for clinical mastitis treatment than dry cow therapy. For dry cow therapy, penicillin ADUR was greater than ADUR of first-generation cephalosporins. For clinical mastitis treatment, ADUR of intramammary penicillin combinations was greater than ADUR of cephapirin. Herd-level milk production was positively associated with overall ADUR, ADUR of systemically administered ceftiofur, cephapirin administered for dry cow therapy, and pirlimycin administered for clinical mastitis treatment. Herd size and ADUR of systemically administered ceftiofur were also positively associated. In conclusion, β-lactams were most commonly used on Canadian dairy farms. Among antimicrobials of very high importance in human medicine, the use of fluoroquinolones was rare, whereas third-generation cephalosporins and penicillin combinations containing colistin were used very frequently on Canadian dairy farms.     

Quantification of antibiotic use on dairy farms in Pennsylvania

Antibiotic use data are critical for drawing conclusions about the epidemiological connections between antibiotic use in farms animals, antibiotic resistance, animal health, and human health. The goal of this study was to quantitatively and qualitatively characterize antibiotic use on dairy farms in Pennsylvania, the state with second largest number of dairy farms nationally. A survey was sent to 10% of the 6,580 dairy farms registered in Pennsylvania and completed by 235 producers (response rate of 36%). Data on antibiotic use in the previous month and in the previous 6 mo were collected based on farmer self-report, using either recall or treatment records. Two metrics were used to quantify antibiotic consumption: animal-defined daily doses (ADD) and days of therapy (DOT), a metric used in human medicine for purposes of antimicrobial stewardship. Across all farms, 24,444 ADD and 19,029 DOT were reported, representing treatment incidences of 4.2 ADD/1,000 animal-days and 3.3 DOT/1,000 animal-days. These rates were generally lower than those found in other states and countries. The main indication for antibiotic use was mastitis, and first-generation cephalosporins were the most commonly used class of antibiotic for all indications, followed by penicillins and third-generation cephalosporins. Trends in use were similar for ADD and DOT, but the numbers of recorded DOT and associated treatment incidences were generally lower than the number of ADD and associated treatment incidences. Rates of treatment were significantly associated with herd size. This study is the first to quantify antibiotic use on dairy farms in Pennsylvania and the first to use the DOT metric in a dairy setting.     

Public perceptions of antibiotic use on dairy farms in the United States

There has been a global push for improved antimicrobial stewardship, including in animal agriculture, due to growing concerns about antimicrobial resistance. However, little is known about the general public's perceptions of antimicrobial use in animal agriculture. The aim of this study was to explore the US public's perceptions of antibiotic use in dairy farming and how these perceptions influence purchasing decisions. Data from the 2017 Cornell National Social Survey developed in collaboration with the Cornell Survey Research Institute were used to assess the public's perceptions. The Survey Research Institute of Cornell University (Ithaca, NY) administered the survey by telephone to a random sample of 1,000 adults in the continental United States. The survey collected information about perceptions of threat to human health posed by antibiotic use in cows on dairy farms and willingness to pay more for milk from cows raised without antibiotics, as well as several presumed explanatory variables, including respondents' knowledge of antibiotics, beliefs regarding cattle treatment in dairy farming, and 18 sociodemographic characteristics. Data were analyzed using logistic regression. Among respondents, 90.7% (n = 892/983) reported that antibiotic use on dairy farms posed some level of threat to human health and 71.5% (n = 580/811) indicated they would be willing to pay more for milk produced from cows raised without antibiotics. Respondents who believed that antibiotic use in dairy farming posed a moderate to high threat to human health were more likely to be female and report willingness to pay more for milk or not purchase milk. Additionally, consumers' willingness to pay more for milk from cattle raised without antibiotics was associated with the belief that antibiotic use posed some threat to human health, the belief that cows are treated better on organic dairy farms, an annual household income of $50,000 or greater, being born outside the United States, having a liberal social ideology, and being currently or formerly married. These results suggest that the general public's decisions as consumers of dairy products are associated with demographic factors in addition to perceptions of antibiotic use and cattle treatment in dairy farming. The rationale behind such perceptions should be further explored to facilitate consumers' informed decision making about antibiotic use in agriculture, links to cattle treatment, and associated willingness-to-pay attitudes.     

Measuring antimicrobial use on dairy farms: A method comparison cohort study

Antimicrobial use on UK dairy farms is measured for surveillance purposes, with veterinary sales data as a proxy for use. Two other methods of recording use have been used commonly on-farm: medicine waste bins and farm medicine records. However, none of these methods has been validated to measure antimicrobial use. The objective of this research was to assess agreement between the 3 most common methods for measuring on-farm antimicrobial use with a predetermined reference method on UK dairy farms. Antimicrobial use was measured prospectively on 26 UK dairy farms using medicine waste bins into which participants placed all discarded medicine packaging for a 12-mo period. At the end of 12 mo, farm medicine records and veterinary sales data were obtained retrospectively for participating farms. The reference method used was based on pre- and poststudy inventories combined with veterinary sales data. We investigated the systematic difference between the mean on-farm antimicrobial use measured by each of the 3 methods and a reference method, using one-way repeated-measures ANOVA models. Reliability and clinical relevance of the agreement between each pair of methods was quantified using the concordance correlation coefficient (CCC) and the Bland-Altman method, respectively. When compared with the reference method, veterinary sales data had excellent reliability for injectable antimicrobials and intramammary antimicrobials [95% confidence interval (CI) of CCC > 0.90] and moderate to excellent reliability for other antimicrobials (95% CI of CCC: 0.68–0.97). Medicine waste bins had good to excellent reliability for injectable (95% CI of CCC: 0.84–0.99), and intramammary products (95% CI of CCC: 0.78–0.94) and no agreement for other forms of antimicrobial. Farm medicine records did not agree for any form of antimicrobial when compared with the reference method. The use of veterinary sales data as a proxy for on-farm antimicrobial use in the UK represented excellent statistical reliability and offered clinically good agreement with the reference method when used to measure injectable antimicrobials. This study applies to the UK context and included a relatively small number of farms. However, these results have research and policy implications, both nationally and internationally, and are essential in accurately quantifying agricultural antimicrobial use to inform both animal and human health.     

Temporal and spatial water use on irrigated and nonirrigated pasture-based dairy farms

Robust information for water use on pasture-based dairy farms is critical to farmers' attempts to use water more efficiently and the improved allocation of freshwater resources to dairy farmers. To quantify the water requirements of dairy farms across regions in a practicable manner, it will be necessary to develop predictive models. The objectives of this study were to compare water use on a group of irrigated and nonirrigated farms, validate existing water use models using the data measured on the group of nonirrigated farms, and modify the model so that it can be used to predict water use on irrigated dairy farms. Water use data were collected on a group of irrigated dairy farms located in the Canterbury, New Zealand, region with the largest area under irrigation. The nonirrigated farms were located in the Manawatu region. The amount of water used for irrigation was almost 52-fold greater than the amount of all other forms of water use combined. There were large differences in measured milking parlor water use, stock drinking water, and leakage rates between the irrigated and nonirrigated farms. As expected, stock drinking water was lower on irrigated dairy farms. Irrigation lowers the dry matter percentage of pasture, ensuring that the amount of water ingested from pasture remains high throughout the year, thereby reducing the demand for drinking water. Leakage rates were different between the 2 groups of farms; 47% of stock drinking water was lost as leakage on nonirrigated farms, whereas leakage on the irrigated farms equated to only 13% of stock drinking water. These differences in leakage were thought to be related to regional differences rather than differences in irrigated versus nonirrigated farms. Existing models developed to predict milking parlor, corrected stock drinking water, and total water use on nonirrigated pasture-based dairy farms in a previous related study were tested on the data measured in the present research. As expected, these models performed well for nonirrigated dairy farms but provided poor predictive power for irrigated farms. Partial least squares regression models were developed specifically to simulate corrected stock drinking water, milking parlor water, and total water use on irrigated dairy farms.     

Assessment and promotion of judicious antibiotic use on dairy farms in Washington State

The aims of this study were to describe antibiotic use and biosecurity practices among Washington State dairy producers and to evaluate the effectiveness of a collaborative approach to promoting judicious antibiotic use on dairy farms. In collaboration with a statewide industry group, Washington State dairy producers participated in a written, self-administered survey in 2003. They were then provided several educational interventions followed by a second written survey in 2005. Sixty-five percent (381) of dairy producers completed the 2003 survey. The most commonly cited drugs used for disease treatment were penicillin, ceftiofur, and oxytetracycline. Participants also indicated significant preventive uses with 28% using medicated milk replacer. Most producers appeared to consider intramammary infusion at dry-off to be a treatment rather than a preventative practice. Twenty-three percent of initial respondents indicated at least one extra-label use of antibiotics, yet only half routinely consulted with a veterinarian when doing so. Most agreed that using written protocols for disease treatment could reduce errors, but less than one-third had protocols. After the educational intervention there was a tendency toward reduced use of antibiotic medicated milk replacer: 51% of producers who originally reported using medicated milk replacer discontinued this practice, whereas 12% of producers began using medicated milk replacer between the 2003 and 2005 surveys. Most reported that the resources and educational materials were useful. Areas where additional work is needed include reducing the use of medicated milk replacer, increasing veterinary involvement in antibiotic use decisions, implementing treatment protocols, enhancing biosecurity, and ensuring optimal cow and calf immunity.     

Whole-farm nitrogen balance on western dairy farms

Environmental legislation has made it necessary for livestock producers to be able to quantify and adjust the N balance on their farms. Whole-farm N balance and efficiencies were computed for 41 commercial dairies in Utah and Idaho using the University of Maryland Nutrient Balancer. The average N balance, or unaccounted for N, was 81 tonnes per year for the average herd size of 466 cows with 35.8% of the inputs accounted for in the outputs. The major inputs for farms that grew crops (n = 23, herd size = 284 total cows) were imported feed (57.4% of all inputs) and nitrogen fixation (30% of inputs). The major outputs were animal products (primarily milk and some meat, 80% of outputs). For farms that grew no crops (n = 18, herd size = 700 total cows), 98% of the inputs were from imported feed. Of the outputs, 57% of the N was in animal products and 42.9% in manure and compost. Whole-farm balance per product for those farms that grew crops was most affected by herd N utilization efficiency (kg feed N per kg product N), crop N utilization efficiency, and availability of manure N applied to crops, while manure N storage efficiency was of lesser importance. For farms that grew no crops, whole-farm N balance per product was most affected by herd N utilization efficiency and manure N storage efficiency. Maximizing conversion of feed N to product N was the best way to reduce whole-farm N balance.     

Whole-farm phosphorus balance on western dairy farms

Environmental concerns have focused attention on animal agriculture and its contribution to P accumulation in soils and runoff to surface waters. Monitoring P inputs and outputs on farms is a means of calculating the potential P build-up in farm soils. The objective of this study was to determine whole-farm P balance and the relative importance of the farm components (herd, manure storage, cropping systems) that contribute to it in dairies of the western United States. Whole-farm balances were computed for 41 commercial dairies in Utah and Idaho using the Maryland Nutrient Balancer. The average whole-farm P balance in the study was 6.6 tonne/yr with an average herd size of 466 cows. Imported feed made up 85.4% of the total P inputs and exported animal products (milk and meat), and manure and compost made up 53.1 and 45.9%, respectively, of the total P outputs. Farms were divided into those that grew crops and those that did not. Whole-farm balance (kg of P balance per animal) for farms that grew crops had more unaccounted for P (difference between P inputs and output) than farms that grew no crops. They also had more imported fertilizer and less imported feed and exported manure and compost. Multiple regression analysis of the relative effects of herd management, manure storage, and cropping system on whole-farm balance per product found that herd P utilization efficiency was the most important factor in determining whole-farm P balance on farms where crops were grown. Crop uptake of available P was the only other subsystem important for these farms. Increased conversion of feed P to P in product is an important way to decrease whole-farm P balance.     

Energy demand on dairy farms in Ireland

Reducing electricity consumption in Irish milk production is a topical issue for 2 reasons. First, the introduction of a dynamic electricity pricing system, with peak and off-peak prices, will be a reality for 80% of electricity consumers by 2020. The proposed pricing schedule intends to discourage energy consumption during peak periods (i.e., when electricity demand on the national grid is high) and to incentivize energy consumption during off-peak periods. If farmers, for example, carry out their evening milking during the peak period, energy costs may increase, which would affect farm profitability. Second, electricity consumption is identified in contributing to about 25% of energy use along the life cycle of pasture-based milk. The objectives of this study, therefore, were to document electricity use per kilogram of milk sold and to identify strategies that reduce its overall use while maximizing its use in off-peak periods (currently from 0000 to 0900 h). We assessed, therefore, average daily and seasonal trends in electricity consumption on 22 Irish dairy farms, through detailed auditing of electricity-consuming processes. To determine the potential of identified strategies to save energy, we also assessed total energy use of Irish milk, which is the sum of the direct (i.e., energy use on farm) and indirect energy use (i.e., energy needed to produce farm inputs). On average, a total of 31.73 MJ was required to produce 1 kg of milk solids, of which 20% was direct and 80% was indirect energy use. Electricity accounted for 60% of the direct energy use, and mainly resulted from milk cooling (31%), water heating (23%), and milking (20%). Analysis of trends in electricity consumption revealed that 62% of daily electricity was used at peak periods. Electricity use on Irish dairy farms, therefore, is substantial and centered around milk harvesting. To improve the competitiveness of milk production in a dynamic electricity pricing environment, therefore, management changes and technologies are required that decouple energy use during milking processes from peak periods.     

Production and feeding strategies for phosphorus management on dairy farms

Long-term accumulation of soil phosphorus (P) is becoming a concern on some watersheds heavily populated with animal feeding facilities, including dairy farms. Management changes in crop production and feeding may help reduce the accumulation of excess P, but farm profitability must be maintained or improved to assure adoption of such changes. Whole-farm simulation was used to evaluate the long-term effects of changes in feeding, cropping, and other production strategies on P loading and the economics of 100-cow and 800-cow dairy farms in southeastern New York. Simulated farms maintained a long-term P balance if the following occurred: 1) animals were fed to meet recommended minimum amounts of dietary P, 2) the cropping strategy and land base supplied all of the forage needed, 3) all animals were fed a high forage diet, and 4) replacement heifers were produced on the farm to utilize more forage. The most easily implemented change was to reduce the supplemental mineral P fed to that required to meet current NRC recommended amounts, and this provided an annual increase in farm profit of about $22/cow. Intensifying the use of grassland and improving grazing practices increased profit along with a small reduction in excess P. Conversion from dairy production to heifer raising or expansion from 100 cows to a 250-cow "state-of-the-art" confinement facility (with a 70% increase in land area) were also profitable options. These options provided a long-term P balance for the farm as long as the production and use of forage was maximized and minimum dietary P amounts were those recommended by the NRC. Thus, management changes can be made to prevent the long-term accumulation of soil P on dairy farms while improving farm profitability.     

Survey of work processes on German dairy farms

The objective of this study was to conduct a survey to gain insight into the organization of work processes on commercial German dairy farms analyzing the use of standard operating procedures (SOP). Practices and routines were surveyed regarding the existence, creation, and use of SOP. A total of 250 survey forms were returned, and 248 could be used for final analysis. The existence of SOP was indicated by 82% of all respondents, but only 54% stated that these SOP were written down. Existence of SOP correlated with farm size such that larger farms were more likely to implement SOP than smaller farms. However, many farmers lacked the time (41%) or ability (42%) to create SOP to provide the employees with detailed instructions on how to perform a specific task. The majority of respondents (59%) were interested in using ready-made SOP that could be adjusted to their farm. An obvious discrepancy exists between the motivation of the farmers to improve the performance on their farm and their expertise in attaining these goals and intentions.     

Daily and seasonal trends of electricity and water use on pasture-based automatic milking dairy farms

The objective of this study was to identify the major electricity and water-consuming components of a pasture-based automatic milking (AM) system and to establish the daily and seasonal consumption trends. Electricity and water meters were installed on 7 seasonal calving pasture-based AM farms across Ireland. Electricity-consuming processes and equipment that were metered for consumption included milk cooling components, air compressors, AM unit(s), auxiliary water heaters, water pumps, lights, sockets, automatic manure scrapers, and so on. On-farm direct water-consuming processes and equipment were metered and included AM unit(s), auxiliary water heaters, tubular coolers, wash-down water pumps, livestock drinking water supply, and miscellaneous water taps. Data were collected and analyzed for the 12-mo period of 2015. The average AM farm examined had 114 cows, milking with 1.85 robots, performing a total of 105 milkings/AM unit per day. Total electricity consumption and costs were 62.6 Wh/L of milk produced and 0.91 cents/L, respectively. Milking (vacuum and milk pumping, within-AM unit water heating) had the largest electrical consumption at 33%, followed by air compressing (26%), milk cooling (18%), auxiliary water heating (8%), water pumping (4%), and other electricity-consuming processes (11%). Electricity costs followed a similar trend to that of consumption, with the milking process and water pumping accounting for the highest and lowest cost, respectively. The pattern of daily electricity consumption was similar across the lactation periods, with peak consumption occurring at 0100, 0800, and between 1300 and 1600 h. The trends in seasonal electricity consumption followed the seasonal milk production curve. Total water consumption was 3.7 L of water/L of milk produced. Water consumption associated with the dairy herd at the milking shed represented 42% of total water consumed on the farm. Daily water consumption trends indicated consumption to be lowest in the early morning period (0300–0600 h), followed by spikes in consumption between 1100 and 1400 h. Seasonal water trends followed the seasonal milk production curve, except for the month of May, when water consumption was reduced due to above-average rainfall. This study provides a useful insight into the consumption of electricity and water on a pasture-based AM farms, while also facilitating the development of future strategies and technologies likely to increase the sustainability of AM systems.     

Survey of disbudding practice on Czech dairy farms

Disbudding is a routine practice in many dairy herds due to the effort to decrease the risk of injuries. Although the disbudding practice is regulated, it can vary among farms. The variation may be caused by many factors, such as herd size or type of breed, but also by farmers' perception of pain caused by disbudding. Hence, the aim of this study was to specify the disbudding practice on dairy farms in the Czech Republic and to assess these practices, including the use of pain mitigation medication, by breed, herd size, and sex of the disbudded calves. We analyzed data from 106 Czech dairy farms, which were collected by a trained interviewer at dairy meetings in 2014–2015. The farmers answered questions regarding the farm's basic characteristics, disbudding practice, and his/her attitude to the pain caused by disbudding. To test the influence of breed, herd size, and sex of disbudded calves on different variables, logistic regression models were used. Disbudding was performed in 92.5% of the surveyed farms; 63.3% of dairy calves were disbudded before 4 wk of age, and Czech Fleckvieh calves were 2.8 times more likely to be disbudded before 4 wk of age than Holstein calves. The hot-iron method was the most used method (69.4%). Calves were 4.5 times more likely to be disbudded by hot iron in herds where both heifers and bulls were disbudded than in herds where only heifers were disbudded. Most (>90%) surveyed farms did not use any pre- or post-procedure medication to mitigate the pain caused by disbudding. The disbudding procedure was performed mainly by farm personnel (94.9%), who were trained by a veterinarian or veterinary technician (46.9%) or by other farm personnel (37.8%) or were not trained (15.3%). Two-thirds of farmers observed behavioral changes in calves after disbudding. Most farmers estimated the pain caused by disbudding to be mild or moderate (20.4 or 45.9%, respectively) and 15.3% of farmers estimated it to be severe. Almost a quarter of interviewed farmers were unable to assess the duration of pain, 39.8% farmers estimated that the pain lasts only several minutes, and 20.4% estimated that the pain lasts up to 6 h. We detected a tendency that farmers of larger herds estimated pain duration to be shorter (odds ratio = 1.2). To improve calves' welfare, training is needed in disbudding practice, focusing on the advantage of pain mitigation.     

Prevalence of and risk factors for Listeria species on dairy farms

This cross-sectional study determined the prevalence of Listeria spp. in bulk-tank milk on dairy farms in the region of Galicia in northwest Spain. The aim was to identify management practices associated with the presence of Listeria spp. and possible effects on milk hygienic quality. A total of 98 farms was randomly selected on the basis of an expected prevalence of 6.5% for Listeria monocytogenes from 20,107 dairy farms in the region. Bulk-tank milk samples were obtained from 98 farms, fecal samples from lactating cows from 97 farms, and silage samples from 83 farms. Listeria monocytogenes was detected in 6.1, 9.3, and 6.0% of these samples, respectively. Statistical analyses confirmed the relationship between low silage quality (as indicated by high pH) and presence of Listeria spp. in silage (29.5 vs. 6.2% for pH above or below 4.5, respectively). Only milking system [tie-stall systems (28.6%) vs. parlor milking (10%)] and inadequately controlled milking order [yes (32.0%) vs. no (10.7%)] had statistically significant effects on management practices for increasing the risk of Listeria contamination of bulk-tank milk.     

Risk-based audit selection of dairy farms

Dairy farms are audited in the Netherlands on numerous process standards. Each farm is audited once every 2 years. Increasing demands for cost-effectiveness in farm audits can be met by introducing risk-based principles. This implies targeting subpopulations with a higher risk of poor process standards. To select farms for an audit that present higher risks, a statistical analysis was conducted to test the relationship between the outcome of farm audits and bulk milk laboratory results before the audit. The analysis comprised 28,358 farm audits and all conducted laboratory tests of bulk milk samples 12 mo before the audit. The overall outcome of each farm audit was classified as approved or rejected. Laboratory results included somatic cell count (SCC), total bacterial count (TBC), antimicrobial drug residues (ADR), level of butyric acid spores (BAB), freezing point depression (FPD), level of free fatty acids (FFA), and cleanliness of the milk (CLN). The bulk milk laboratory results were significantly related to audit outcomes. Rejected audits are likely to occur on dairy farms with higher mean levels of SCC, TBC, ADR, and BAB. Moreover, in a multivariable model, maxima for TBC, SCC, and FPD as well as standard deviations for TBC and FPD are risk factors for negative audit outcomes. The efficiency curve of a risk-based selection approach, on the basis of the derived regression results, dominated the current random selection approach. To capture 25, 50, or 75% of the population with poor process standards (i.e., audit outcome of rejected), respectively, only 8, 20, or 47% of the population had to be sampled based on a risk-based selection approach. Milk quality information can thus be used to preselect high-risk farms to be audited more frequently.     

Financial benchmarking on dairy farms: Exploring the relationship between frequency of use and farm performance

The importance of financial benchmarking has increased in recent years as European Union milk quota abolition has facilitated rapid change in the dairy sector. This study evaluates the association between usage frequency of a financial benchmarking tool [Profit Monitor (PM)] and farm changes on spring-calving pasture-based dairy farms. To this end, physical and financial data for 5,945 dairy farms, representing 20,132 farm years, for the years 2010 to 2018 were used. Farms were categorized by frequency of annual financial benchmarking over the 9-yr period into frequent PM users (7–9 yr), infrequent PM users (4–6 yr), low PM users (1–3 yr), and nonusers. We use a mixed model framework and econometric models to characterize farms and to explore characteristics and determinants of economic performance and user groups. The most frequent users of the financial benchmarking tool had the greatest increase in intensification (measured by change in farm stocking rate), productivity (measured by change in milk production per hectare), and financial performance (measured by change in farm gross output and net profit per hectare) across the study period. Infrequent and low PM users of the benchmarking tool were intermediate for all variables measured, whereas nonusers had the least change. Empirical results indicated that economic performance was positively associated with dairy specialization and pasture utilization for all groups. Despite considerable fluctuations over the observation period, the overall change in total farm net profit between 2010 and 2018 was greatest for the frequent PM users (an increase of 70%, or €37,639), followed by farms in the infrequent PM user category (a 71% increase corresponding to an increase of €28,008 in net profit); meanwhile, low PM user and nonuser categories showed increases of 69% (€26,270) and 42% (€10,977), respectively. The results of this study also clearly indicated the existence of a strong positive association between frequency of financial benchmarking and greater technical and financial efficiency. The econometric analysis revealed that financial benchmarking users are more likely than nonusers to have larger herds, and that regional differences exist in usage rates. Finally, the study concludes by suggesting that the development of simplified financial benchmarking technologies and their support are required to increase benchmarking frequency, which may also help to facilitate a more sustainable and resource efficient dairy industry.     

Incidence rate of clinical mastitis on Canadian dairy farms

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 Staphylococcus aureus, Escherichia coli, Streptococcus uberis, 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 E. coli and culture-negative IRCM were highest and Staph. aureus IRCM was lowest in low and medium BMSCC herds. Staphylococcus aureus, Strep. uberis, and Streptococcus dysgalactiae IRCM were lowest in the Western provinces. Staphylococcus aureus and Strep. dysgalactiae IRCM were highest in Québec. Cows in tie-stalls had higher incidences of Staph. aureus, Strep. uberis, coagulase-negative staphylococci, and other streptococcal IRCM compared with those in free-stalls, whereas cows in free stalls had higher Klebsiella spp. and E. coli 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.     

The profitability of automatic milking on Dutch dairy farms

Several studies have reported on the profitability of automatic milking based on different simulation models, but a data-based study using actual farm data has been lacking. The objective of this study was to analyze the profitability of dairy farms having an automatic milking system (AMS) compared with farms using a conventional milking system (CMS) based on real accounting data. In total, 62 farms (31 using an AMS and 31 using a CMS) were analyzed for the year 2003 in a case control study. Differences between the years 2002 and 2003 also were analyzed by comparing a subgroup of 16 farms with an AMS and 16 farms with a CMS. Matching was based on the time of investment in a milking system (same year), the total milk production per year, and intensity of land use (kg/ha). Results from 2003 showed that the farms with an AMS used, on average, 29% less labor than farms with a CMS. In contrast, farms using a CMS grew faster (37,132 kg of milk quota and 5 dairy cows) than farms with an AMS (−3,756 kg milk quota and 0.5 dairy cows) between 2002 and 2003. Dairy farmers with a CMS had larger (€7,899) revenues than those with an AMS. However, no difference in the margin on dairy production was detected, partly because of numerically greater (€6,822) variable costs on CMS farms. Dairy farms were compared financially based on the amount of money that was available for rent, depreciation, interest, labor, and profit (RDILP). The CMS farms had more money (€15,566) available for RDILP than the AMS farms. This difference was caused by larger fixed costs (excluding labor) for the AMS farms, larger contractor costs (€6,422), and larger costs for gas, water, and electricity (€1,549). Differences in costs for contractors and for gas, water, and electricity were statistically significant. When expressed per full-time employee, AMS farms had greater revenues, margins, and gross margins per full-time employee than did CMS farms. This resulted in a substantially greater (but not statistically significant) RDILP per full-time employee (€12,953) for AMS farms compared with CMS farms. Depreciation and interest costs for automatic milking were not available but were calculated based on several assumptions. Assuming larger purchase costs and a shorter depreciation time for AMS than for CMS, costs for depreciation and interest were larger for AMS farms than for CMS farms. Larger fixed costs should be compensated for by the amount of labor that has become available after introducing the milking robot. Therefore, farm managers should decide whether the extra time acquired by automatic milking balances against the extra costs associated with an AMS.     

Reliability of sampling strategies for measuring dairy cattle welfare on commercial farms

Our objective was to evaluate how the proportion of high-producing lactating cows sampled on each farm and the selection method affect prevalence estimates for animal-based measures. We assessed the entire high-producing pen (days in milk <100; range = 81–241 cows) on 10 California farms using measures from the Welfare Quality Protocol for Cattle. Cows were restrained in head locks and visually evaluated for body condition, dirtiness, skin alterations (hair loss, lesions, or swelling), discharge (ocular, nasal, vulvar), diarrhea, and impaired respiration. Lameness was scored upon release. Prevalence was calculated as a percentage of assessed cows. The most common conditions were dirty hindquarters (33.5 ± 10.7%, mean ± standard deviation) and lesions or swelling on the carpal joint (34.4 ± 7.0%) and hock (26.4 ± 16.7%). Diarrhea (8.0 ± 5.8%), lameness (moderate = 7.3 ± 4.7%, severe = 2.2 ± 2.2%), and neck (5.8 ± 12.6%), flank (4.5 ± 5.0%), or hindquarter alterations (5.5 ± 3.9%) were less common. Very fat cows, vulvar discharge, and impaired respiration were rare (≤1%) and were excluded from further analysis. Four sampling strategies were used to generate 20 estimates for each animal-based measure. The strategies were (1) selecting every 10th, 5th, 4th, 3rd, 2nd, 2 of 3, or 3 of 4 cows at the feed bunk (7 estimates/measure); (2) randomly selecting 7 matching proportions of the pen; (3) randomly selecting cows using 3 sample size calculations from the Welfare Quality Protocol; and (4) selecting the first, middle, or final third of cows exiting the milking parlor. Estimates were compared with true values using regression analysis and were considered accurate if they met 3 criteria: the coefficient of determination was ≥0.9 and the slope and intercept did not differ significantly from 1 and 0, respectively. All estimates met the slope and intercept criteria, whereas the coefficient of determination increased when more cows were sampled. All estimates were accurate for neck alterations, ocular discharge (22.2 ± 27.4%), and carpal joint hair loss (14.1 ± 17.4%). Selecting a third of the milking order or using the Welfare Quality sample size calculations failed to accurately estimate all measures simultaneously. However, all estimates were accurate when selecting at least 2 of every 3 cows locked at the feed bunk. Using restraint position at the feed bunk did not differ systematically from computer-selecting the same proportion of cows randomly, and the former may be a simpler approach for welfare assessments.     

Calf management risk factors on dairy farms associated with male calf mortality on veal farms

The objective of this cross-sectional herd-level study was to assess the association of calf management practices on source dairy farms with mortality risk on veal farms. From April to October 2016, 52 source dairy farms supplying male calves to 2 veal operations were visited once. A questionnaire was administered that covered all areas of calf management, calves between 1 and 10 d of age were examined using a standardized health scoring system, and blood was taken to evaluate passive transfer of immunoglobulins. The mortality risk for calves from each dairy farm was calculated based on the number of male calves sold from the dairy farm and that died during 2016 at the veal operations. The mean mortality risk was calculated for both veal farms and, based on the veal facility-adjusted mortality risk, dairy farms were classified as high- or low-mortality source farms. Using the information gathered at the 52 source dairy farms, a logistic regression model was used to assess factors associated with being a high-mortality source farm. Suppliers to veal farm 1 had a mean mortality risk of 9.6% and suppliers to veal farm 2 had a mean mortality risk of 4.2%. The lower mortality risk at veal farm 2 was partially influenced by a shorter period of observation. Of the 182 calves examined during the single visit to the source dairy farms, 41% of male calves and 29% of female calves had at least one identifiable health abnormality. The risk of failure of passive transfer on source dairy farms was low, with only 13% of calves tested having <10 mg of IgG/mL of serum. The subset of calves examined at the source dairy farm was not followed prospectively to the veal farms. Using a tube feeder or pail to feed colostrum, bedding male calves on wood shavings or chopped straw at the source dairy farm, and the herd veterinarian not routinely and actively inquiring about the health and performance of calves during regular herd visits were significantly associated with the farm being classified as a high-mortality source dairy farm. Checking the calving pen at an interval of every 3 h or more during the day was associated with a lower probability of being classified as a high-mortality source dairy farm. The results of this study suggest that there are management practices on the source farm that contribute to the risk of mortality on veal farms.