Wisconsin Dairy Farms Research Articles

Sensitivity of dairy calf Salmonella enterica serotype Cerro isolates to infection-relevant stressors.

Salmonella enterica serotype Cerro (S. Cerro) is an emerging Salmonella serotype isolated from cattle, but the association of S. Cerro with disease is not well understood. While comparative genomic analyses of bovine S. Cerro isolates have indicated mutations in elements associated with virulence, the correlation of S. Cerro fecal shedding with clinical disease in cattle varies between epidemiologic studies. The primary objective of this study was to characterize the infection-relevant phenotypes of S. Cerro fecal isolates obtained from neonatal calves born on a dairy farm in Wisconsin, USA. The S. Cerro isolates varied in biofilm production and sensitivity to the bile salt deoxycholate. All S. Cerro isolates were sensitive to sodium hypochlorite, hydrogen peroxide, and acidic shock. However, S. Cerro isolates were resistant to nitric oxide stress. Two S. Cerro isolates were unable to compete with S. Typhimurium during infection of calf ligated intestinal loops, indicating decreased fitness in vivo. Together, our data suggest that S. Cerro is sensitive to some innate antimicrobial defenses present in the gut, many of which are also used to control Salmonella in the environment. The observed phenotypic variation in S. Cerro isolates from a single farm suggest phenotypic plasticity that could impact infectious potential, transmission, and persistence on a farm.IMPORTANCESalmonella enterica is a zoonotic pathogen that threatens both human and animal health. Salmonella enterica serotype Cerro is being isolated from cattle at increasing frequency over the past two decades; however, its association with clinical disease is unclear. The goal of this study was to characterize infection-relevant phenotypes of S. Cerro isolates obtained from dairy calves from a single farm. Our work shows that there can be variation among temporally related S. Cerro isolates and that these isolates are sensitive to killing by toxic compounds of the innate immune system and those used for environmental control of Salmonella. This work contributes to our understanding of the pathogenic potential of the emerging pathogen S. Cerro.

Validation of an on-farm portable blood analyzer for quantifying blood analytes in dairy cows

The periparturient period for dairy cows is a metabolically dynamic time period where the cow is adjusting from gestation to the onset of lactation. Metabolic disorders such as ketosis, hypocalcemia, and fatty liver occur during this time; however, tools to diagnose these diseases on-farm is limited. The need for compact metabolite quantification devices that can quantify metabolites on farm from whole blood samples is warranted. The purpose of this study was to validate a portable blood analyzer (PBA) by analyzing metabolites on privately owned dairy farms in southcentral Wisconsin. Additional tests were completed to determine if plasma metabolite quantification was similar to whole-blood quantification. Two phases were conducted on two separate farms to complete these analyses and data were analyzed by Bland-Altman plot and correlations. Metabolites quantified from whole blood samples included albumin, alanine and aspartate aminotransferases, β-hydroxybutyrate, blood urea nitrogen, total calcium, cholesterol, creatinine kinase, γ-glutamyl transferase, glucose, magnesium, nonesterified fatty acids, phosphorous, and total protein and were analyzed in the lab after plasma separation to determine gold-standard laboratory concentrations. Across Phase 1 and 2, whole-blood PBA metabolite concentrations resulted in similar results compared to the laboratory assays. For plasma analyzed on the PBA, overall results were positively correlated, but robustness was dependent upon initial validation results indicating some metabolites are suitable for plasma quantification on the device. These results indicate that the PBA is a viable on-farm metabolite quantification tool that will be valuable for on-farm diagnosis of metabolic stress and dysfunction in transition dairy cows.

Dairy farmers’ preferences for immediate versus late calf separation

The practice of separating calves from their dams right after birth is one of the main dairy cattle welfare concerns among the public. Farmer perceptions about the practice and the available alternative contact systems in the US are however, not well understood. Using data from a sample of Wisconsin dairy farmers, the study examines farmer preferences for different prolonged (relative to immediate separation) contact systems and the potential role of farm structural and individual-level specific factors. Four alternative hypothetical systems - free dam, half day, foster cow, and restricted suckling systems – differing on the basis of calf access to dam-were considered. The analysis controls for farm size, production system (conventional, organic, grazing), farmer socio-demographic characteristics in addition to farm animal welfare (FAW) perceptions. The findings indicate that amongst the set of alternative practices considered, foster cow system is most preferred alternative to the conventional early separation practised by most farmers. This is followed by restricted suckling systems. The least ranked alternative system is free calf-dam contact. The analyses further indicate that calf contact duration is negatively associated with herd size. Relative to conventional farms, calf-dam pairs on grazing, organic and mixed farms are less likely to be separated immediately after birth. Prolonged calf-dam contact is also prevalent amongst older farmers. Overall, the findings imply that farming system and structural considerations may be the key drivers of transition to prolonged contact systems in dairy production. Foster cow systems may offer the most feasible pathway for achieving this objective.

Variation in partial direct costs of treating clinical mastitis among 37 Wisconsin dairy farms

The objective of this observational study was to describe variations in partial direct costs of clinical mastitis (CM) treatments among 37 dairy herds using data obtained from herd management records. Animal health and drug purchase records were retrospectively collected from 37 Wisconsin dairy herds for a period of 1 yr. Each farm was visited to verify case definitions, recording accuracy, and detection criteria of CM cases. Descriptive statistics were used to summarize cost of drugs and milk discard. Differences in costs among protocols, intramammary (IMM) products, parities, days in milk, and recurrence were analyzed using ANOVA. Of 20,625 cases of CM, 31% did not receive antimicrobial treatment. The average cost of drugs and milk discard (including cases that were not treated) was $192.36 ± 8.90 (mean ± SE) per case and ranged among farms from $118.13 to $337.25. For CM cases treated only with IMM antimicrobials, milk discard accounted for 87% of total costs and was highly influenced by duration of therapy. Differences in costs were observed among parities, recurrence, and stage of lactation at case detection. Eight different treatment protocols were observed, but 64% of cases were treated using only IMM antimicrobials. Treatment costs varied among protocols; however, cases treated using both IMM and injectable antimicrobials as well as supportive therapy had the greatest costs as they were also treated for the longest duration. Ceftiofur was used for 82% of cases that received IMM antimicrobials while ampicillin was used for 51% of cases treated using injectable antimicrobials. With the exception of ceftiofur and pirlimycin IMM products, many IMM products were given for durations that exceeded the maximum labeled duration. For cases treated using only IMM therapy, as compared with observed costs, we estimated that partial direct costs could be reduced by $65.20 per case if the minimum labeled durations were used. Overall, partial direct costs per case varied among herds, cow factors, and treatment protocols and were highly influenced by the duration of therapy.

The role of animal breeding in productivity growth: Evidence from Wisconsin dairy farms

AbstractWe examine the relationship between investments in animal breeding and productivity growth on Wisconsin dairy farms using a control function approach. We incorporate farm‐level annual investment in breeding and genetics into the law of motion of productivity as in De Loecker (2013) to test the relationship between these investments and realized productivity. Our unique dataset also allows us to look at the effect of choosing bulls with high milk yield potential on productivity. Our results indicate that breeding investments made 3 years prior are associated with higher productivity of the current cohort. However, the farms with the highest level of productivity reap the lowest benefits from breeding investments, suggesting that there are diminishing returns to investing in genetics. When milk output is not quality adjusted, the contribution of breeding to productivity is undetectable, suggesting that breeding and investments in milk quality are related. We conclude that investments in breeding and genetics significantly contribute to dairy farm productivity, especially in terms of milk quality.

Effectiveness of local regulations on nonpoint source pollution: Evidence from Wisconsin dairy farms

AbstractAlthough the Clean Water Act's regulation of point source pollution has had a significant effect on water quality, nonpoint sources of pollution, especially animal agriculture, remain a leading unevenly regulated source of water pollution in the United States. This work studies the effectiveness of local manure management regulations on dairy farms in Wisconsin. Wisconsin represents a unique policy experiment in the delegation of nonpoint agricultural pollution policy in a state with economically important small, nonpoint, dairy farms. Using hand collected regulatory data from Wisconsin counties we estimate the effects of changes in local regulations on water quality outcomes. The results demonstrate that a few easily implemented and verifiable regulations such as nutrient management plans have significant short‐term effects on water quality, whereas other less observable and difficult to implement regulations have no discernible effects in the short term. The work points to a number of potential policy levers to improve the Management of nonpoint pollution, as well as the challenges of nonpoint source regulatory policies on slow‐moving hydrologic processes.

Survival of bovine-associated serotypes of Salmonella enterica in bedding sand

Cattle persistently infected with bovine-adapted serotypes of Salmonella enterica are an important animal health and food safety issue. One possible mechanism by which infection is sustained in a dairy herd is by survival of Salmonella in sand used as bedding material. In this study we assessed the survival of 107 to 108 cfu bovine-associated serotypes of Salmonella enterica (sv. Cerro, Dublin, and Heidelberg) in sterile sand, recycled bedding sand, and gray water collected from a Wisconsin dairy farm. All 3 serotypes persisted at relatively high numbers (>106 cfu/g) for at least 28 d in sterile sand, with Salmonella sv. Dublin decreasing less than 1 log10 over 70 d. To our surprise, when low numbers of Salmonella sv. Dublin (103 cfu) were inoculated into sterile sand, the organism multiplied within 3 d to approximately 106 cfu/g sand and persisted at that level for 28 d. When we inoculated Salmonella sv. Dublin into recycled bedding sand or sand taken directly from cow pens, we observed a significant decrease in colony-forming units by d 7. In contrast, we observed a significant increase in colony-forming units when Salmonella sv. Dublin was inoculated into gray water from the sand recycling system. These data demonstrate that Salmonella can persist for extended periods of time in bedding sand, although this is limited to some extent by the native microbiota in recycled bedding sand.

Incidence and Treatments of Bovine Mastitis and Other Diseases on 37 Dairy Farms in Wisconsin.

The aim of this research was to describe the incidence and treatments of mastitis and other common bovine diseases using one year of retrospective observational data (n = 50,329 cow-lactations) obtained from herd management software of 37 large dairy farms in Wisconsin. Incidence rate (IR) was defined as the number of first cases of each disease divided by the number of lactations per farm. Clinical mastitis (CM) remains the most diagnosed disease of dairy cows. Across all herds, the mean IR (cases per 100 cow-lactations) was 24.4 for clinical mastitis, 14.5 for foot disorders (FD), 11.2 for metritis (ME), 8.6 for ketosis (KE), 7.4 for retained fetal membranes (RFM), 4.5 for diarrhea (DI), 3.1 for displaced abomasum (DA), 2.9 for pneumonia (PN) and 1.9 for milk fever (MF). More than 30% of cows that had first cases of CM, DA, RFM, DI, and FD did not receive antibiotics. Of those treated, more than 50% of cows diagnosed with PN, ME and CM received ceftiofur as a treatment. The IR of mastitis and most other diseases was greater in older cows (parity ≥ 3) during the first 100 days of lactation and these cows were more likely to receive antibiotic treatments (as compared to younger cows diagnosed in later lactation). Cows of first and second parities in early lactation were more likely to remain in the herd after diagnosis of disease, as compared to older cows and cows in later stages of lactation. Most older cows diagnosed with CM in later lactation were culled before completion of the lactation. These results provide baseline data for disease incidence in dairy cows on modern U.S. dairy farms and reinforce the role of mastitis as an important cause of dairy cow morbidity.

Predicting daily milk yield for primiparous cows using data of within-herd relatives to capture genotype-by-environment interactions

This study develops and illustrates a hybrid k-medoids, random forest, and support vector regression (K-R-S) approach for predicting the lactation curves of individual primiparous cows within a targeted environment using monthly milk production data from their dams and paternal siblings. The model simulation and evaluation were based on historical test-day (TD) milk production data from 2010 to 2016 for 260 Wisconsin dairy farms. Data from older paternal siblings and dams were used to create family units (n = 6,400) of individual calves, from which their future performance was predicted. Test-day milk yield (MY) records from 2010 to 2014 were used for model training, whereas monthly milk production records of Holstein calves born in 2014 were used for model evaluation. The K-R-S hybrid approach was used to generate MY predictions for 5 randomly selected batches of 320 primiparous cows, which were used to evaluate model performance at the individual cow level by cross-validation. Across all 5 batches, the mean absolute error and the root mean square error of the K-R-S predictions were lower (by 24.2 and 23.4%, respectively) than that of the mean daily MY of paternal siblings. The K-R-S predictions of TD MY were closer to actual values 74.2 ± 2.0% of the time, as compared with means of paternal siblings'. The correlation between actual TD MY and K-R-S predictions was greater (0.34 ± 0.01) than the correlation between the actual yield and the mean of paternal siblings (0.08 ± 0.01). The results of this study demonstrate the effectiveness of the K-R-S hybrid approach for predicting future first-lactation MY of dairy calves in management applications, such as milk production forecasting or decision-support simulation, using only monthly TD yields of within-herd relatives and in the absence of detailed genomic data.

Pharmacy leader reflects on pharmacy reaching its full potential

Pharmacy leader reflects on pharmacy reaching its full potential

Assessing the microbiota of recycled bedding sand on a Wisconsin dairy farm

BackgroundSand is often considered the preferred bedding material for dairy cows as it is thought to have lower bacterial counts than organic bedding materials and cows bedded on sand experience fewer cases of lameness and disease. Sand can also be efficiently recycled and reused, making it cost-effective. However, some studies have suggested that the residual organic material present in recycled sand can serve as a reservoir for commensal and pathogenic bacteria, although no studies have yet characterized the total bacterial community composition. Here we sought to characterize the bacterial community composition of a Wisconsin dairy farm bedding sand recycling system and its dynamics across several stages of the recycling process during both summer and winter using 16S rRNA gene amplicon sequencing.ResultsBacterial community compositions of the sand recycling system differed by both seasons and stage. Summer samples had higher richness and distinct community compositions, relative to winter samples. In both summer and winter samples, the diversity of recycled sand decreased with time drying in the recycling room. Compositionally, summer sand 14 d post-recycling was enriched in operational taxonomic units (OTUs) belonging to the genera Acinetobacter and Pseudomonas, relative to freshly washed sand and sand from cow pens. In contrast, no OTUs were found to be enriched in winter sand. The sand recycling system contained an overall core microbiota of 141 OTUs representing 68.45% ± 10.33% SD of the total bacterial relative abundance at each sampled stage. The 4 most abundant genera in this core microbiota included Acinetobacter, Psychrobacter, Corynebacterium, and Pseudomonas. Acinetobacter was present in greater abundance in summer samples, whereas Psychrobacter and Corynebacterium had higher relative abundances in winter samples. Pseudomonas had consistent relative abundances across both seasons.ConclusionsThese findings highlight the potential of recycled bedding sand as a bacterial reservoir that warrants further study.

Nontraditional credit in the Wisconsin dairy industry

PurposeThe purpose of this article is to document and evaluate patterns of nontraditional credit use among Wisconsin dairy farmers. Using a survey-based case study approach, this article analyzes farmer and farm characteristics, farmers’ utilization of credit and farmers’ perceptions of nontraditional lenders. The findings are connected to ongoing structural change in the dairy sector and economic theories of trade credit.Design/methodology/approachData were collected using an incentivized online survey of Wisconsin dairy farmers distributed through existing university and industry networks. A total of 16 farmers completed the survey. The sample is treated as a focus group case study, and participants’ responses are examined using summary statistics and correlational analyses to describe emergent patterns in the industry.FindingsAmong survey respondents who utilize agricultural credit, nearly 80% (11 of 14) borrow from at least one nontraditional lender, and nontraditional credit comprises 17% of their total borrowing, on average. Much of this borrowing occurs through the financial arm of a vendor and is used to finance equipment or machinery purchases. Despite widespread use of nontraditional credit, no surveyed farmers preferred nontraditional lenders over traditional lenders.Originality/valueThis is the first study to analyze the use of nontraditional credit specifically among Wisconsin dairy farmers. Dairy farming is a capital-intensive endeavor, and recent structural change in the sector has increased surviving dairy farmers' demand for credit.

Transnational health protection strategies and other health-seeking behavior among undocumented and indigenous dairy workers in a rural new immigrant destination

Latin American immigrants in new immigrant destinations (NIDs) experience numerous barriers that negatively impact their access to healthcare. Yet the wide range of health-seeking behaviors deployed in response to these barriers–particularly among those who are undocumented and indigenous–are not well understood. Further, studies of immigrant health in NIDs tend to take place in those locations, rather than using a multi-sited design. Building on NID scholarship, the transnational social protection literature, and work on structural vulnerability, this study uses a multi-sited research design to examine the health-seeking behaviors that undocumented and indigenous immigrant workers exhibit in a rural NID. Data consist of interviews conducted intermittently from 2010 to 2017 in Mexico and the U.S. with 56 individuals from indigenous villages in Veracruz who worked on dairy farms in Wisconsin and Minnesota, as well as expert interviews. We found numerous barriers to healthcare that together constituted a limited resource environment for undocumented dairy workers. This accentuated their structural vulnerability and influenced responses to health problems. Strategies among undocumented and indigenous immigrant dairy workers in a rural NID included: self-care, delaying care, relying on local ties, cross-border health consultation, cross-border health packages, and returning home for health. Furthermore, we found that women in the family or community often facilitated cross-border health activity, and that traditional folk medicine was common. We argue that these workers' health protection strategies not only serve to secure their individual status as productive workers, but on a larger scale, they play an important part in preserving the migrant labor regime in this rural NID. Further, we argue that the indigenous knowledge that is transmitted largely by women via immigrants’ informal social networks is an important yet often invisible part of the carework that maintains this relatively new labor force.

COVID-19 Awareness and Preparedness of Minnesota and Wisconsin Dairy Farms

ABSTRACT Dairy farms that had participated in previous and ongoing projects with the National Farm Medicine Center (NFMC), Migrant Clinicians Network (MCN), and Upper Midwest Agricultural Safety and Health Center (UMASH) were asked to participate in a 17-question survey by phone or email to investigate biosecurity principles on Minnesota and Wisconsin dairy farms in response to COVID-19 and the effects of the pandemic on the dairy industry. Three additional farms were recruited via a press release published in agricultural newsletters. Of 76 farms contacted, 37 chose to participate in this study from June to July 2020. In response to the COVID-19 pandemic, dairies have implemented or increased biosecurity measures and COVID-19 precautions. Dairies reported adequate personal protective equipment for their workers, though face masks were not required on most dairies (n = 32, 86%). Producers were concerned about the safety of their families, maintaining a healthy workforce, and keeping their farms profitable. Access to healthcare was not perceived to be an issue for their workers. One-quarter of dairies reported COVID-19 infections on their farms. Even though the majority had an isolation protocol in place if someone on the farm were to become ill, less than half of respondents felt their farm was protected against COVID-19. Two-thirds of producers have not had to decrease production, and a majority of operations have not furloughed or terminated employees due to COVID-19. Our data suggest that dairy farms in Minnesota and Wisconsin have implemented biosecurity and safety measures in response to COVID-19. These measures can be improved. Farms would benefit from additional guidance and education on implementation of personal protective measures and disease prevention strategies to keep workers employed and safe.

Examining the Relationship between Social Inefficiency and Financial Performance. Evidence from Wisconsin Dairy Farms

Although social sustainability is an important component of sustainable agricultural production, little research has been conducted to assess social sustainability performance at the farm level. This study measures farmers’ social sustainability performance using (in)efficiency measures derived from a non-parametric dynamic directional distance function approach. It further examines the relationship between social (in)efficiency and financial performance measured by profitability, which is crucial to understand the financial impact of engaging in socially responsible activities. The empirical application focuses on a sample of Wisconsin dairy farms over the period 2007–2017. Results show that sample farms could have (decreased/)increased their social (in)efficiency by an average of 14%. Social (in)efficiency was found to be (negatively/)positively related to farm profitability, implying that social objectives can be achieved in tandem with economic goals.

Dairy Woes in Wisconsin: What about the Amish?

Wisconsin has steadily lost dairy farms for decades, yet the number of Amish dairy herds grew both numerically and proportionately into early 2018. Facing low milk prices, the overall rate of loss of dairy farms in Wisconsin accelerated since then. During 2019, the state lost over 1% of its dairy herds monthly, losing two to three herds daily. The expansion of Amish dairying also ended. Between April 1, 2018, when Wisconsin had 1,160 Amish dairy herds or 12.9% of the state's total, and November 1, 2019, the state lost 165 Amish herds. Losses are continuing.This paper focuses on the impact of the departure of many Amish farms from dairying, relying on examination of dairy producer licenses and a survey of bishops and ministers in Wisconsin's Amish church districts. The loss of Amish herds of dairy cows is greater than the overall departure of the Amish from dairying, inasmuch as the Amish have nearly doubled their milk goat herds over the past five years. Those settlements producing milk transported in cans have been more likely to leave dairying unless their community operates its own cheese factory. Yet dairying is declining in most Amish communities, other than in several recently established settlements. Expanding involvement in growing produce and in woodworking were seen.

Carbon footprint of milk from Holstein and Jersey cows fed low or high forage diet with alfalfa silage or corn silage as the main forage source

Our objective was to determine the cradle-to-farmgate carbon footprint of fat-and-protein corrected milk (FPCM) for four diets fed to two breeds using measured enteric methane and greenhouse gas emissions during manure storage and after field application. The diets were formulated as 2 × 2 factorial with forage neutral detergent fiber at two levels (19 and 24% of diet dry matter referred to as low forage and high forage diets, respectively) from two sources (70:30 or 30:70 ratio of alfalfa silage and corn silage). Measured emissions were incorporated in a modeled Wisconsin dairy farm with a herd consisting of 118 lactating cows (primiparous), 22 dry cows, and 119 heifers. Emissions were allocated between milk and meat using biophysical allocation, and a sensitivity analysis was performed to determine the impact of alternative allocation methods. Overall, carbon footprint was 1.43 kg CO2-e/kg FPCM for biophysical allocation, and 1.50 and 1.60 kg CO2-e/kg FPCM for economic and no allocation (100% allocated to milk), respectively. Forage source did not influence results. However, low forage-fed cows had 10% greater carbon footprint than high forage-fed cows (1.49 vs. 1.35 kg CO2-e/kg FPCM). Assuming similar herd structure, milk carbon footprint for Holsteins was 4.4% greater than for Jerseys (1.47 vs. 1.41 kg CO2-e/kg FPCM). Accounting for differences in fertility and replacement rate increased the difference in milk carbon footprint between breeds to 10%. Under our study conditions, differences in milk carbon footprint due to enteric fermentation were minimal but the differences became substantial when combining the effects of cow (enteric CH4) and manure (CH4 and N2O) emissions. These differences were exacerbated even further when accounted for the emissions associated with on-farm feed production and purchased feed (CO2 and N2O). This study highlights the need for an integrated approach to assess the effects of dietary manipulations on milk carbon footprint.

Quantification of antimicrobial usage in adult cows and preweaned calves on 40 large Wisconsin dairy farms using dose-based and mass-based metrics

Use of antimicrobials in animal agriculture is under increasing scrutiny, but the quantity of antimicrobials used on large US dairy farms has not been evaluated using data from large farms and different metrics. This study investigated total antimicrobial usage (AMU) in adult dairy cows and preweaned calves (PWC) and contrasted 2 metrics used for measurement of AMU. Wisconsin dairy farms were eligible if they had >250 lactating cows, maintained computerized animal health records, and were willing to allow researchers access to treatment records. Animal health data for a 1-yr period was retrospectively collected from computerized records, and a farm visit was performed to verify case definitions and recording accuracy. Both dose-based (animal daily doses; ADD) and mass-based (total mg of antimicrobials per kg of body weight; BW) metrics were calculated at the herd, cow, and PWC levels. Descriptive statistics for AMU were examined for both age groups. Mean AMU was compared among active ingredients and route of usage using ANOVA models that included farm as a random variable. At enrollment, farms (n = 40) contained approximately 52,639 cows (mean: 1,316 ± 169; 95% CI: 975, 1657) and 6,281 PWC (mean: 180 ± 33; 95% CI: 112, 247). When estimated using ADD, total herd AMU was 17.2 ADD per 1,000 animal-days (95% CI: 14.9, 19.5), with 83% of total herd-level AMU in adult cows. When estimated using the mass-based metric, total herd AMU was 13.6 mg of antimicrobial per kilogram of animal BW (95% CI: 10.3, 17.0), with 86% of total AMU used in adult cows. For cows, 78% of total ADD (15.8 ADD per 1,000 cow-d) was administered as intramammary (IMM) preparations. In contrast, when AMU was estimated using a mass-based metric, IMM preparations represented only 24% of total AMU (12.1 mg of antimicrobial/kg of cow BW). For cows, ceftiofur was the primary antimicrobial used and accounted for 53% of total ADD, with 80% attributed to IMM and 20% attributed to injectable treatments. When estimated using a mass-based metric, ampicillin was the predominant antimicrobial used in cows and accounted for 33% of total antimicrobial mass per kilogram of BW. When AMU was estimated for PWC using ADD, injectable antimicrobials represented 79% of total usage (28.3 ADD per 1,000 PWC-d). In contrast, when AMU was estimated for PWC using a mass-based metric, injectable products represented 42% of total AMU, even though more farms administered antimicrobials using this route. When AMU in PWC was summarized using ADD, penicillin represented 32% of AMU, and there were no significant differences in ADD among ampicillin, oxytetracycline or enrofloxacin. When a mass-based metric was used to estimate AMU in PWC, oral products (sulfadimethoxine and trimethoprim-sulfa) represented more than half of the total AMU given to this group. Overall, these results showed that choice of metric and inclusion of different age groups can substantially influence interpretation of AMU on dairy farms.

Farm Profitability as a Driver of Spatial Spillovers: The Case of Somatic Cell Counts on Wisconsin Dairies

AbstractWe hypothesize that spatial spillovers among neighboring farms are not only driven by spatial proximity, but also by farm profitability considerations. This hypothesis is tested by examining the role of spatial spillovers in shaping somatic cell counts (SCC) on Wisconsin dairy farms. Results show that neighborhood links defined both in terms of geographic proximity and farm profitability give rise to spatial spillovers that affect SCC. Significant differences in the estimated spatial spillovers are observed when defining the neighborhood space in terms of both farm profitability and geographic proximity as opposed to geographic proximity alone, with the data favoring the former specification.

A generalized true random-effects model with spatially autocorrelated persistent and transient inefficiency

This study extends the generalized true random-effects model to account for spatial dependence in persistent and transient inefficiency. For this purpose, a model with spatially autocorrelated persistent and transient inefficiency components is specified. Additionally, spatial dependence is also modeled in the noise component to account for uncontrolled spatial correlations. The proposed model is applied to a panel dataset of Wisconsin dairy farms observed between 2009 and 2017 and estimated using Bayesian techniques. Apart from the traditional output-input quantities, the utilized dataset also contains information on the exact location of farms based on their latitude and longitude coordinates as well as on environmental factors. The empirical findings suggest low levels of both persistent and transient inefficiency for farms. Additionally, all components exhibit spatial dependence with its magnitude being more than double for persistent inefficiency.