Mastitis control in Swedish dairy herds

The aim of this study was to investigate which preventive measures targeting mastitis are implemented in Swedish dairy herds with different housing and milking systems. Data were collected through a self-administered postal questionnaire sent to 898 dairy farmers, stratified by housing and milking system, in May 2011. The questionnaire contained general questions about the herd and the person responsible for the udder health of the cows, and specific questions about perceived udder health and the implementation of preventive measures. The response rate was 48%. The median herd size of participating herds was 80 cows, and the median herd average milk yield per cow was 9,586 kg of milk. External validity was assessed by comparing participating herds with nonresponders in respect to key performance indicators in the Swedish official milk recording system; no significant differences were found. When herds with combined systems had been removed, 400 herds with tiestalls and pipeline milking, freestalls and parlor milking, and freestalls with an automatic milking system remained. Differences between herd types were analyzed using the Kruskal-Wallis test and Fisher’s exact test. The results showed that herd types differed in their rates of implementation of different preventive measures. Freestall herds with milking parlors implemented more preventive measures related to milking hygiene and milking routines than did tiestall herds. A milking order based on the udder health status of the cows was frequently implemented in tiestall herds, but not in most herds with an automatic milking system or most freestall herds with milking parlors. Irrespective of herd type, the proportion of herds in which cows were kept standing for at least 30 min after milking was low. A substantial proportion of herds ignored the udder health status of lactating cows when grouping them, and few herds grouped dry cows according to udder health status, although this occurred more frequently in tiestall herds. A large proportion of herds, especially those with tiestalls, did not allow cows and heifers to calve in single pens that were cleaned between animal occupations. These findings can be used to tailor advice on mastitis specifically to different herd types and thus improve the efficiency of mastitis control.     

A survey on the incidence of Prototheca mastitis in dairy herds in Lublin province,Poland

Prototheca mastitis has recently become an emerging disease; although its incidence is increasing steadily, its epidemiology remains largely understudied. The aim of this work was to investigate the prevalence of Prototheca spp. in dairy cows and their environment in Lublin province, covering most of southeastern Poland. Between December 2015 and July 2016, a total of 172 milking cows from 10 dairy farms were inspected for mastitis using clinical examination and the California Mastitis Test (CMT). Quarter milk samples (QMS, n = 179) and body site swabs (n = 151) from CMT-positive cows were collected for microbiological culture. In addition, we evaluated QMS and body site swabs from 23 healthy cows, along with 91 environmental samples. Of 100 CMT-positive cows, 71 had at least one QMS positive for microbial growth. In 8 (11.3%) of these cows, originating from 7 dairy farms, Prototheca spp. were cultured. The average somatic cell count of the Prototheca-containing milk was 4.02 × 10⁶ cells/mL compared with 0.13 × 10⁶ cells/mL of the Prototheca-free milk (collected from control animals). No significant differences were observed between mastitis and control cows with respect to counts of total white blood cells, lymphocytes, neutrophils, and eosinophils. Half of the cows with Prototheca spp. in their milk did not yield the algae from other anatomical sites. Eight cows were negative for the presence of Prototheca spp. in their milk but positive for the algae in swabs from anatomical sites. Among the environmental sources that were positive for Prototheca growth were watering troughs, manure, feed, and mud. All (45) Prototheca isolates recovered in this study were subjected to species- and genotype-level molecular identification. All QMS and most of the animal swabs (90%) yielded Prototheca zopfii genotype (gen.) 2. Of the animal samples, P. zopfii gen. 1 and Prototheca blaschkeae were isolated only from feces and rectum. Environmental samples grew either P. zopfii gen. 2 (67%) or P. zopfii gen. 1 (33%). This study demonstrates that P. zopfii gen. 2 is the third most common pathogen of mastitis in cattle in southeast Poland, with an overall incidence of 4.6%. Finding Prototheca spp., including P. zopfii gen. 1 and 2 and P. blaschkeae, in stool and rectal swabs from healthy animals may suggest their role as nonpathogenic microflora of bovine gut.     

A stochastic model simulating the feeding-health-production complex in a dairy herd

A dynamic, stochastic, and mechanistic Monte Carlo model, simulating a dairy herd with focus on the feeding-health-production complex is presented. By specifying biological parameters at cow level and a management strategy at herd level, the model can simulate the technical and economic consequences of scenarios at herd level. The representation of the feeding-health-production complex is aimed to be sufficiently detailed, to include relationships likely to cause significant herd effects, and to be sufficiently simple to enable a feasible parameterization of the model and interpretation of the results from the model. Consequently, diseases are defined as four disease types: two metabolic disease types, an udder disease type, and a reproductive disease type. Risk factors for the diseases were defined as parity, yield capacity, disease recurrence, disease interrelationships, lactation stage, and season. Direct effects of the diseases were defined according to milk yield, feed intake, feed utilization, conception, culling, involuntary removal, and death. Scenarios differing in base risks of milk fever and ketosis, heat detection rate, and culling strategy were simulated for describing the model behavior. Annual milk yield per cow was decreased by increased risk of ketosis and by increased risk of milk fever, even though no direct effect of milk fever on milk yield was modeled at the cow level. The indirect effect from milk fever is a consequence of increased replacement rate (relatively lower milk yield from younger cows). By ignoring the history of milk fever in insemination and replacement decisions, a significantly reduced net income per cow was found in some herds. We concluded that important benefits from using such a herd model are the capability of accounting for herd management factors and the advantage of avoiding to double count the indirect effects from disease, such as increased risk of other diseases, poorer reproduction results, and increased risk of culling and death.     

Pathogen-specific incidence rate of clinical mastitis in Flemish dairy herds,severity, and association with herd hygiene

A one-year survey on clinical mastitis was conducted on 50 randomly selected commercial Flemish dairy herds to estimate the pathogen-specific incidence rate of clinical mastitis (IRCM). The severity of the cases and the potential associations with herd hygiene were studied. Participating producers sampled 845 cases and 692 dairy cows. The mean and median IRCM was estimated at 7.4 and 5.3 quarter cases per 10,000 cow-days at risk, respectively. A large between-herd variation was observed (range of 0–21.3). In general, the IRCM was lower in heifers compared with multiparous cows (2.9 vs. 11.0 quarter cases per 10,000 cow-days at risk). However, the overall IRCM in the first week after calving was higher in heifers compared with cows (43.4 vs. 31.6 quarter cases per 10,000 cow-days at risk). Streptococcus uberis (18.2% of the cases) and Escherichia coli (15.5%) were the most frequently isolated pathogens and no growth was observed in 19.9% of the cases. The majority of the cases (63.1%) were mild (only clots in milk). Moderate (hard quarter without general signs) and severe symptoms (systemic illness) were observed in 29.9 and 7.0% of the cases, respectively. Isolation of E. coli (vs. any other culture result) was more likely in moderate and severe cases compared with mild cases. Overall IRCM and E. coli IRCM were higher in dirty compared with clean herds based on udder hygiene scores (9.0 and 1.7 vs. 6.0 and 0.6 quarter cases per 10,000 cow-days at risk, respectively). This study broadens the knowledge on clinical mastitis in Flemish dairy herds and underlines the high risk of CM in early-lactation heifers, the role of the so-called environmental pathogens, and herd hygiene.     

Does clinical mastitis in the first 100 days of lactation 1 predict increased mastitis occurrence and shorter herd life in dairy cows?

The objectives of this study were to estimate the direct effects of clinical mastitis (CM) occurring in early productive life (defined as the first 100 d of the first lactation) of Holstein dairy cows on the future rate of CM occurrence and on the length of total productive lifetime. Information on CM cases and other data occurring in 55,144 lactations in 24,831 cows in 5 New York State Holstein herds was collected from January 2004 until February 2014. For the first objective, a generalized linear mixed model with a Poisson distribution was used to study the effects of CM cases occurring in the first 100 d of a cow's first lactation, as well as farm indicator and number of days in the cow's lifetime, on the future lifetime rate of CM. Only cows that had completed their productive life [i.e., all had been culled (or sold) or had died; n = 14,440 cows] were included in this analysis. For the second objective, a Cox proportional hazards model was used to study the effects of CM cases occurring in the first 100 d of a cow's first lactation on the length of total productive lifetime. The model was stratified by farm. All 24,831 cows were included in this analysis with right censoring. Cows experienced between 0 and 4 CM cases in the first 100 d of lactation 1. Over their lifetime, cows experienced between 0 and 25 CM cases. During the study period, 10% of all cows died and nearly half of all cows were culled. The average length of productive life, including censored observations, was 2.0 yr after first calving. Compared with cows having no CM cases in the first 100 d of lactation 1, cows with 1 CM case in that time period had a 1.5 times higher rate of total number of CM cases over their lifetime. Cows with 2 (or 3 or more) CM cases in the first 100 d of lactation 1 had a 1.7 times (or 2.6 times) higher rate of total number of CM cases over their lifetime. For each additional CM case occurring in the first 100 d of lactation 1, the hazard rate of culling increased by 34%. Given economic conditions for preferentially culling mastitic cows, the study findings may help farmers make optimal decisions with regard to culling of such cows.     

Effect of pathogen-specific clinical mastitis on milk yield in dairy cows

Our objective was to estimate the effects of the first occurrence of pathogen-specific clinical mastitis (CM) on milk yield in 3071 dairy cows in 2 New York State farms. The pathogens studied were Streptococcus spp.,Staphylococcus aureus, Staphylococcus spp., Escherichia coli, Klebsiella spp., Arcanobacterium pyogenes, other pathogens grouped together, and "no pathogen isolated." Data were collected from October 1999 to July 2001. Milk samples were collected from cows showing signs of CM and were sent to the Quality Milk Production Services laboratory at Cornell University for microbiological culture. The SAS statistical procedure PROC MIXED, with an autoregressive covariance structure, was used to quantify the effect of CM and several other control variables (herd, calving season, parity, month of lactation, J-5 vaccination status, and other diseases) on weekly milk yield. Separate models were fitted for primipara and multipara, because of the different shapes of their lactation curves. To observe effects of mastitis, milk weights were divided into several periods both pre- and postdiagnosis, according to when they were measured in relation to disease occurrence. Another category contained cows without the type of CM being modeled. Because all pathogens were modeled simultaneously, a control cow was one without CM. Among primipara, Staph. aureus, E. coli, Klebsiella spp., and "no pathogen isolated" caused the greatest losses. Milk yield generally began to drop 1 or 2 wk before diagnosis; the greatest loss occurred immediately following diagnosis. Mastitic cows often never recovered their potential yield. Among older cows, Streptococcus spp., Staph. aureus, A. pyogenes, E. coli, and Klebsiella spp. caused the most significant losses. Many multipara that developed CM were actually higher producers before diagnosis than their nonmastitic herd-mates. As in primipara, milk yield in multipara often began to decline shortly before diagnosis; the greatest loss occurred immediately following diagnosis. Milk loss persisted until at least 70 d after diagnosis for Streptococcus spp., Klebsiella spp., and A. pyogenes. The tendency for higher producing cows to contract CM may mask its impact on cow health and production. These findings provide dairy producers with more information on which pathogen-specific CM cases should receive treatment and how to manage these cows, thereby reducing CM impact on cow well being and profitability.     

Genetic analysis of herd life in Canadian dairy cattle on a lactation basis using a Weibull proportional hazards model

The objectives of this study were to identify the most important factors that influence functional survival and to estimate the genetic parameters of functional survival for Canadian dairy cattle. Data were obtained from lactation records extracted for the May 2002 genetic evaluation of Holstein, Jersey, and Ayrshire breeds that calved between July 1, 1985 and April 5, 2002. Analysis was performed using a Weibull proportional hazard model, and the baseline hazard function was defined on a lactation basis instead of the traditional analysis of the whole length of life. The statistical model included the effects of stage of lactation; season of production; the annual change in herd size; type of milk recording supervision; age at first calving; effects of milk, fat, and protein yields calculated within herd-year-parity deviations; and the random effects of herd-year-season of calving and sire. All effects fitted in the model had a significant effect on functional survival of cows in all breeds. Milk yield was by far the most important factor influencing survival, and the hazard increased as the milk production of the cows decreased. The hazard also increased as the fat content increased compared with the average group. Heifers that were older at calving were at higher risk of being culled, and expanding herds were at lower risk of being culled compared with stable herds. More culling was found in unsupervised herds than in supervised herds. The heritability values obtained were 0.14, 0.10, and 0.09 for Holstein, Jersey, and Ayrshire, respectively. Rank correlation between estimated breeding values (EBV) obtained from the current national genetic evaluation of direct herd life and the survival kit used in this study ranged from 0.65 to 0.87, depending on the number of daughters per sire. Estimated genetic trend obtained using the survival kit was overestimated.     

Associations between herd characteristics and reproductive efficiency in dairy herds

Dairy herds worldwide are experiencing a decline in reproductive efficiency at the same time as management methods are changing. This study aimed to investigate the extent to which herd-level characteristics were associated with reproductive performance. Data from herds using artificial insemination (AI) in the Swedish Official Milk Recording Scheme that had more than 45 cows were included in the study (total of 2,728 herds). Reproductive performance was measured as the average for each herd for the calving interval, calving to first AI interval, calving to last AI interval, number of AI per animal submitted for AI, and culling attributed to reproductive problems. Herds with mainly Swedish Holstein cows had longer calving intervals, calving to first AI, and calving to last AI compared with herds with mainly Swedish Red and White cows. Large herds had shorter calving to first AI but a greater number of AI than small herds, whereas small herds had greater culling attributed to reproductive problems than large herds. Low-yielding herds had longer calving intervals, calving to first AI, and calving to last AI and had greater culling attributed to reproductive problems than high-yielding herds, whereas herds with high milk yields had a greater number of AI than low-yielding herds. Herds with automatic milking systems had shorter calving intervals, calving to first AI, and calving to last AI and had lesser odds for culling attributed to reproductive problems when compared with herds with ordinary pipeline milking systems. Herds that used Advanced Feed Advisory Services had shorter calving to first AI but a greater number of AI and greater culling attributed to reproductive problems. Herds using TMR had longer calving intervals and calving to last AI than herds that did not. Herds with tie stalls had longer calving intervals, calving to first AI, and calving to last AI, and organic herds had shorter calving intervals, calving to first AI, and calving to last AI compared with conventional herds. We found that herds with do-it-yourself inseminations had longer calving intervals and calving to first AI. Our study showed numerous associations between herd characteristics and reproductive performance. When allocating advisory service resources to improve reproductive performance, the focus should be on herd characteristics that are easy to influence, such as TMR and do-it-yourself inseminations.     

Effects of pathogen-specific clinical mastitis on probability of conception in Holstein dairy cows

The objective of this study was to estimate the effects of pathogen-specific clinical mastitis (CM), occurring in different weekly intervals before or after artificial insemination (AI), on the probability of conception in Holstein cows. Clinical mastitis occurring in weekly intervals from 6 wk before until 6 wk after AI was modeled. The first 4 AI in a cow’s lactation were included. The following categories of pathogens were studied: Streptococcus spp. (comprising Streptococcus dysgalactiae, Streptococcus uberis, and other Streptococcus spp.); Staphylococcus aureus; coagulase-negative staphylococci (CNS); Escherichia coli; Klebsiella spp.; cases with CM signs but no bacterial growth (above the level that can be detected from our microbiological procedures) observed in the culture sample and cases with contamination (≥3 pathogens in the sample); and other pathogens [including Citrobacter, yeasts, Trueperella pyogenes, gram-negative bacilli (i.e., gram-negative organisms other than E. coli, Klebsiella spp., Enterobacter, and Citrobacter), Corynebacterium bovis, Corynebacterium spp., Pasteurella, Enterococcus, Pseudomonas, Mycoplasma, Prototheca, and others]. Other factors included in the model were parity (1, 2, 3, 4 and higher), season of AI (winter, spring, summer, autumn), day in lactation of first AI, farm, and other non-CM diseases (retained placenta, metritis, ketosis, displaced abomasum). Data from 90,271 AI in 39,361 lactations in 20,328 cows collected from 2003/2004 to 2011 from 5 New York State dairy farms were analyzed in a generalized linear mixed model with a Poisson distribution. The largest reductions in probability of conception were associated with CM occurring in the week before AI or in the 2 wk following AI. Escherichia coli and Klebsiella spp. had the greatest adverse effects on probability of conception. The probability of conception for a cow with any combination of characteristics may be calculated based on the parameter estimates. These findings may be helpful to farmers in assessing reproduction in their dairy cows for more effective cow management.     

Use of herd solutions from a random regression test-day model for diagnostic dairy herd management

In a random regression test-day model, environmental effects in addition to individual animal factors can be included and analyzed. Moreover, instead of herd-year classification of the management groups, the herd-test-day classification within the model better accounts for month-to-month short-term environmental variation in production and somatic cell count (SCC) traits. The herd management levels of milk yield (milk deviation from whole-country mean, kilograms/day), protein and fat concentration (protein and fat deviation, %), and SCC (SCC deviation, 1,000 cells/mL) are used in the dairy herd management Web application “Maitoisa” (in English, “Milky”). This management tool helps to recognize several management problems. For recognition of systematic patterns and single unusual test-days, a monthly time-trend analysis was developed to smooth the random fluctuations and display the yearly production pattern. In addition to analyzing single test-day deviations from the mean, modeled herd solutions assist users in identifying repeated phenomena and enable the forecasting of the management pattern for the subsequent year. The solutions are displayed either as tables or graphs plotted by calendar months. In addition to management effects of the farmer's own herd, he or she can request country or region percentiles to be displayed in the graphs. The Web service has been offered to farmers and dairy advisors since 2001, and it has proved to be a powerful tool for herd monitoring and planning.     

Random herd curves in a test-day model for milk, fat, and protein production of dairy cattle in The Netherlands

With random regression models, genetic parameters of test-day milk production records of dairy cattle can be estimated directly from the data. However, several researchers that used this method have reported unrealistically high variances at the borders of the lactation trajectory and low genetic correlations between beginning and end of lactation. Recently, it has been proposed to include herd-specific regression curves in the random regression model. The objective was to study the effect of including random herd curves on estimated genetic parameters. Genetic parameters were estimated with 2 models; both included random regressions for the additive genetic and permanent environmental effect, whereas the second model also included a random regression effect for herd x 2-yr period of calving. All random regressions were modeled with fourth-order Legendre polynomials. Bayesian techniques with Gibbs sampling were used to estimate all parameters. The data set comprised 857,255 test-day milk, fat, and protein records from lactations 1, 2, and 3 of 43,990 Holstein cows from 544 herds. Genetic variances estimated by the second model were lower in the first 100 d and at the end of the lactation, especially in lactations 2 and 3. Genetic correlations between d 50 and the end of lactation were around 0.25 higher in the second model and were consistent with studies where lactation stages are modeled as different traits. Subsequently, estimated heritabilities for persistency were up to 0.14 lower in the second model. It is suggested to include herd curves in a random regression model when estimating genetic parameters of test-day production traits in dairy cattle.     

Effect of mastitis on milk perchlorate concentrations in dairy cows

Recent surveys have identified the presence of perchlorate, a natural compound and environmental contaminant, in forages and dairy milk. The ingestion of perchlorate is of concern because of its ability to competitively inhibit iodide uptake by the thyroid and to impair synthesis of thyroid hormones. A recent study established that milk perchlorate concentrations in cattle highly correlate with perchlorate intake. However, there is evidence that up to 80% of dietary perchlorate is metabolized in clinically healthy cows, thereby restricting the available transfer of ingested perchlorate into milk. The influence of mastitis on milk perchlorate levels, where there is an increase in mammary vascular permeability and an influx of blood-derived components into milk, remains unknown. The present study examined the effect of experimentally induced mastitis on milk perchlorate levels in cows receiving normal and perchlorate-supplemented diets. Over a 12-d period, cows were ruminally infused with 1 L/d of water or water containing 8 mg of perchlorate. Five days after the initiation of ruminal infusions, experimental mastitis was induced by the intramammary infusion of 100 μg of bacterial lipopolysaccharide (LPS). Contralateral quarters infused with phosphate-buffered saline served as controls. A significant reduction in milk perchlorate concentration was observed in the LPS-challenged glands of animals ruminally infused with either water or perchlorate. In control glands, milk perchlorate concentrations remained constant throughout the study. A strong negative correlation was identified between mammary vascular permeability and milk perchlorate concentrations in LPS-infused glands. These findings, in the context of a recently published study, suggest that an active transport process is operative in the establishment of a perchlorate concentration gradient across the blood-mammary gland interface, and that increases in mammary epithelial and vascular endothelial permeability lead to a net outflow of milk perchlorate. The overall finding that mastitis results in lower milk perchlorate concentrations suggests that changes in udder health do not necessitate increased screening of milk for perchlorate.     

Characterization of clinical mastitis occurring in cows on 50 large dairy herds in Wisconsin

In recent years, the US dairy industry has experienced significant demographic changes, with an increase in the number of large herds. The objectives of the present study were to characterize clinical mastitis occurring in cows on large dairy herds in Wisconsin. Participating herds (n = 50) were required to have a minimum of 200 lactating animals, participate in monthly DHI testing (including monthly individual cow somatic cell count), use computerized herd records, use a milking routine that included fore-stripping quarters for detection of mastitis, and use antimicrobials to treat affected cows. After study personnel visited the farm, each herd was instructed to enroll the next 17 cows that experienced clinical mastitis, regardless of severity. At detection of clinical mastitis and 14 to 21 d after treatment ended, duplicate quarter milk samples were collected from all affected quarters and used for microbiological analysis. Treatments of affected cows were performed according to existing individual farm protocols. Cow level follow-up data was collected for 90 d after enrollment. Microbiological diagnoses at enrollment included gram-negative (35.6%), no growth (27.3%), gram-positive (27.5%), and other (9.6%). Of the 741 cases, the most prevalent pathogens were Escherichia coli (22.5%), followed by environmental streptococci (12.8%), Klebsiella spp. (6.9%), and coagulase-negative staphylococci (6.1%). Bacteriological cure was 75.0% for cases caused by gram-negative pathogens (n = 136), 50.8% for cases caused by gram-positive pathogens (n = 128), 47.5% for cases caused by other pathogens (n = 40), and 73.2% for cases which did not result in microbial growth (n = 123). Of the 583 cases with severity recorded, the distribution of mild, moderate, and severe symptoms was 47.8, 36.9, and 15.3%, respectively. The majority of cases presenting with severe symptoms were caused by gram-negative pathogens. Treatment cure was greater for gram-negative pathogens and cases for which no pathogens were recovered as compared with cases caused by other etiologies. Cows experiencing severe cases were more likely to receive multiple antimicrobial treatments.     

Cross-infection between cats and cows: origin and control of Streptococcus canis mastitis in a dairy herd

Group G streptococci in animals usually belong to the species Streptococcus canis and are most commonly found in dogs and cats. Occasionally, Strep. canis is detected in milk from dairy cows. An outbreak of Strep. canis mastitis in a dairy herd is described. Based on results from bacterial culture and ribotyping, a cat with chronic sinusitis was the most likely source of the outbreak. Subsequent cow-to-cow transmission of Strep. canis was facilitated by poor udder health management, including use of a common udder cloth and failure to use postmilking teat disinfection. Infected cows had macroscopically normal udders and milk, but significantly higher somatic cell counts than Strep. canis-negative herd mates. The outbreak was controlled through antibiotic treatment of lactating cows, early dry-off with dry cow therapy, culling of infected animals, and implementation of standard mastitis prevention measures. Cure was significantly more likely in dry-treated cows (87.5%) and cows treated during lactation (67%) than in untreated cows (9%). Whereas mastitis due to group G streptococci or Strep. canis in dairy cows is usually limited to sporadic cases of environmental (canine or feline) origin, this case study shows that crossing of the host species barrier by Strep. canis may result in an outbreak of mastitis if management conditions are conducive to contagious transmission. In such a situation, measures that are successful in control of Strep. agalactiae can also be used to control Strep. canis mastitis.     

Novel approaches to assess the quality of fertility data stored in dairy herd management software

Scientific journals and popular press magazines are littered with articles in which the authors use data from dairy herd management software. Almost none of such papers include data cleaning and data quality assessment in their study design despite this being a very critical step during data mining. This paper presents 2 novel data cleaning methods that permit identification of animals with good and bad data quality. The first method is a deterministic or rule-based data cleaning method. Reproduction and mutation or life-changing events such as birth and death were converted to a symbolic (alphabetical letter) representation and split into triplets (3-letter code). The triplets were manually labeled as physiologically correct, suspicious, or impossible. The deterministic data cleaning method was applied to assess the quality of data stored in dairy herd management from 26 farms enrolled in the herd health management program from the Faculty of Veterinary Medicine Ghent University, Belgium. In total, 150,443 triplets were created, 65.4% were labeled as correct, 17.4% as suspicious, and 17.2% as impossible. The second method, a probabilistic method, uses a machine learning algorithm (random forests) to predict the correctness of fertility and mutation events in an early stage of data cleaning. The prediction accuracy of the random forests algorithm was compared with a classical linear statistical method (penalized logistic regression), outperforming the latter substantially, with a superior receiver operating characteristic curve and a higher accuracy (89 vs. 72%). From those results, we conclude that the triplet method can be used to assess the quality of reproduction data stored in dairy herd management software and that a machine learning technique such as random forests is capable of predicting the correctness of fertility data.     

Assessment of the prevalence of Streptococcus uberis in dairy cow feces and implications for herd health

Streptococcus uberis is a major causative agent of bovine mastitis worldwide, negatively affecting both milk production and animal welfare. Mammary infections result from environmental reservoirs, with cattle themselves required to propagate the infection cycle. Two longitudinal studies were performed to investigate the prevalence of Streptococcus uberis within feces and to evaluate factors which may affect gastrointestinal carriage. Bacterial detection was confirmed using a PCR-based method directed against sub0888 that detected S. uberis at an analytical sensitivity of 12 cfu/g of bovine feces. The first study sampled an entire herd at 8-wk intervals, over a 10-mo period and identified that maintenance of S. uberis within the dairy cow environment was due to a high proportion of animals shedding S. uberis and not due to a low number of “super-shedding” cows within the herd. Seasonality influenced detection rates, with detection levels significantly higher for housed cattle compared with those at pasture. Multilevel logistic regression was used to identify significant factors that affected S. uberis detection; these included parity, stage of lactation, and body condition score. An additional study involved screening a smaller cohort of cows housed over a 4-wk period and identified an increased probability of detection if cows were housed in loose straw yards, compared those in straw cubicles. This study highlighted several cow and management related factors that affect both detection of S. uberis and future infection risks.     

Optimal insemination and replacement decisions to minimize the cost of pathogen-specific clinical mastitis in dairy cows

Mastitis is a serious production-limiting disease, with effects on milk yield, milk quality, and conception rate, and an increase in the risk of mortality and culling. The objective of this study was 2-fold: (1) to develop an economic optimization model that incorporates all the different types of pathogens that cause clinical mastitis (CM) categorized into 8 classes of culture results, and account for whether the CM was a first, second, or third case in the current lactation and whether the cow had a previous case or cases of CM in the preceding lactation; and (2) to develop this decision model to be versatile enough to add additional pathogens, diseases, or other cow characteristics as more information becomes available without significant alterations to the basic structure of the model. The model provides economically optimal decisions depending on the individual characteristics of the cow and the specific pathogen causing CM. The net returns for the basic herd scenario (with all CM included) were $507/cow per year, where the incidence of CM (cases per 100 cow-years) was 35.6, of which 91.8% of cases were recommended for treatment under an optimal replacement policy. The cost per case of CM was $216.11. The CM cases comprised (incidences, %) Staphylococcus spp. (1.6), Staphylococcus aureus (1.8), Streptococcus spp. (6.9), Escherichia coli (8.1), Klebsiella spp. (2.2), other treated cases (e.g., Pseudomonas; 1.1), other not treated cases (e.g., Trueperella pyogenes; 1.2), and negative culture cases (12.7). The average cost per case, even under optimal decisions, was greatest for Klebsiella spp. ($477), followed by E. coli ($361), other treated cases ($297), and other not treated cases ($280). This was followed by the gram-positive pathogens; among these, the greatest cost per case was due to Staph. aureus ($266), followed by Streptococcus spp. ($174) and Staphylococcus spp. ($135); negative culture had the lowest cost ($115). The model recommended treatment for most CM cases (>85%); the range was 86.2% (Klebsiella spp.) to 98.5% (Staphylococcus spp.). In general, the optimal recommended time for replacement was up to 5 mo earlier for cows with CM compared with cows without CM. Furthermore, although the parameter estimates implemented in this model are applicable to the dairy farms in this study, the parameters may be altered to be specific to other dairy farms. Cow rankings and values based on disease status, pregnancy status, and milk production can be extracted; these provide guidance when determining which cows to keep or cull.     

Treatments of clinical mastitis occurring in cows on 51 large dairy herds in Wisconsin

Antimicrobials are frequently used for treatment of bovine mastitis and few studies have examined modern treatment strategies on large US dairy farms. The objective of this study was to describe treatment practices for clinical mastitis occurring in cows on large dairy herds in Wisconsin. Treatments performed on 747 cows experiencing cases of mild, moderate, or severe symptoms of clinical mastitis were recorded on 51 Wisconsin dairy farms. Duplicate milk samples were collected from the affected quarter for microbiological analysis at the onset of clinical mastitis and 14 to 21 d after treatment ended. Cows were treated according to individual farm protocol. Drugs and doses used for treatments were recorded for each case. Among all herds, 5 intramammary (IMM) antimicrobials (amoxicillin, hetacillin, pirlimycin, ceftiofur, and cephapirin) were used to treat cows for clinical mastitis. Of 712 cows with complete treatment data, 71.6% were treated with IMM ceftiofur either solely or combined with other antimicrobials (administered either IMM or systemically). Of cows experiencing severe symptoms of clinical mastitis, 43.8% received IMM treatment concurrent with systemic antimicrobials. Of all cows treated, 23.1% received an additional secondary treatment (either IMM, systemic, or both) because of perceived lack of response to the initial treatment. The majority of IMM treatments were administered to cows with a microbiological diagnosis of no growth (34.9%) or Escherichia coli (27.2%). Half of the cows experiencing cases caused by E. coli were treated using systemic antimicrobials in contrast to only 6.8% of cows experiencing cases caused by coagulase-negative staphylococci. In conflict with FDA regulations, which do not allow extra-label treatments using sulfonamides, a total of 22 cows from 8 farms were treated with systemic sulfadimethoxine either solely or in combination with oxytetracycline. Antimicrobial drugs were used on all herds and many cows received extra-label treatments. Great opportunity exists to improve mastitis therapy on large dairy herds, but use of more diagnostic methodologies is necessary to guide treatments. Farmers and veterinarians should work together to create protocols based on the herd needs considering reduced inappropriate and excessive use of antimicrobials.     

Study of the efficacy of a Streptococcus uberis mastitis vaccine against an experimental intramammary infection with a heterologous strain in dairy cows

Streptococcus uberis is a worldwide pathogen that causes intramammary infections in dairy cattle. Nevertheless, commercial vaccines are currently not available and measures to control S. uberis mastitis are limited to the implementation of good management practices. The aim of the present study was to evaluate the efficacy of an S. uberis subunit vaccine against bovine mastitis (Laboratorios Hipra S.A., Amer, Spain) administered precalving against an experimental intramammary challenge with a heterologous S. uberis strain in dairy cows postcalving. With this objective, 25 gestating Holstein-Friesian heifers were randomly assigned to 1 of 2 groups: group 1 (n = 13), vaccinated by intramuscular route with the vaccine, and group 2 (n = 12), vaccinated by intramuscular route with phosphate-buffered saline as a control group. Both groups were immunized 60 and 21 d before the expected parturition date (75 and 36 d before challenge). Fourteen days after calving all cows were challenged by intramammary infusion of 100 colony-forming units of a heterologous S. uberis strain in 2 quarters per cow. Then, challenged quarters were monitored for clinical signs of mastitis, bacterial count, and somatic cell count for the following 21 d. Rectal temperature and daily milk yield per cow were also assessed. Results showed that all challenged quarters developed clinical mastitis. Nevertheless, vaccination significantly reduced the clinical signs of mastitis, bacterial count, rectal temperature, and daily milk yield losses after the intramammary infection and significantly increased the number of quarters with no bacterial isolation and somatic cell count <200,000 cells/mL at the end of the study (d 19, 20, and 21 after challenge). To confirm the efficacy of this vaccine, further studies under field conditions are needed.     

Economic values and expected effect of selection index for pathogen-specific mastitis under Danish conditions

The objectives of this study were 1) to estimate costs related to 5 different pathogen-specific mastitis traits (susceptibility to different pathogens causing mastitis in dairy cattle) and unspecific mastitis, and 2) to compare selection differentials for an udder health index consisting of 5 different pathogen-specific mastitis traits and lactation average somatic cell count from 5 to 170 d after first calving (LASCC170) with another index consisting of 1 unspecific mastitis trait and LASCC170. Economic values were estimated for mastitis caused by Staphylococcus aureus, Streptococcus dysgalactiae, Escherichia coli, coagulase-negative staphylococci, and Streptococcus uberis using a stochastic simulation model (SimHerd IV). Mastitis incidences for SimHerd IV were from incidences of mastitis treatments in primiparous Danish Holstein cows calving in 2007. Estimated costs ranged from €149 to €570 per mastitis case and were highest for contagious pathogens such as Staph. aureus and coagulase-negative staphylococci and lowest for Strep. dysgalactiae and Strep. uberis. The value for unspecific mastitis was €231 per case. Selection differentials (in €) were estimated for 4 different selection indices, including 1) unspecific mastitis, 2) unspecific mastitis and LASCC170, 3) 5 pathogen-specific mastitis traits and unspecific residual mastitis (unspecific mastitis treatments minus mastitis treatments caused by the 5 pathogens), and 4) as index 3 including LASCC170. The breeding goal was identical to selection index 3. Mastitis data from primiparous cows calving from 1998 to 2008 were used to estimate genetic parameters of the mastitis traits using linear models and AI-REML algorithm. These parameters were used for construction of the selection index equations. For the selection indices, information sources were measurements of mastitis treatments and LASCC170 from 50, 80, or 130 daughters of a bull as well as measurements of mastitis treatments from 1,000 progeny of the bull's sire and 1,000 daughters of his maternal grandsire. Differences in selection differentials were marginal among the 4 indices. Without considering LASCC170, the selection differential of an unspecific mastitis index was €0.4 (<1%) better than that of a pathogen-specific index. On the other hand, the selection differential of the pathogen-specific index was €0.3 (<1%) better than that of an unspecific index when LASCC170 was included in the indices. Reliabilities of the selection indices were 0.62 to 0.67 (80 daughters) and were proportional to the selection differential. Changing the number of daughters to 50 or 130 did not change ranking of the indices. Heritabilities of the pathogen-specific traits were very low (h² = 0.005-0.021) compared with unspecific mastitis (h² = 0.062), which may limit the selection differential of the pathogen-specific index.