Herd-level variables associated with delayed milk ejection in Michigan dairy herds

The objective of this study was to determine which herd-level variables were associated with delayed milk ejection (bimodal milk let-down) in 64 Michigan dairy herds. Median herd size was 294 cows (range 59 to 2,771 cows). For each herd, milking protocols were observed and milk flow dynamics were estimated by use of digital vacuum recorders. Surveys were also administered to the producers to measure mastitis management practices and attitudes. Milk flow dynamics were recorded for a total of 3,824 cow milkings, with a mean of 60 milkings per herd (range of 11 to 154). Backward multivariable analysis was used to determine which of the 47 herd-level milking and management variables were associated with delayed milk ejection (cows with milk let-down periods between milking cluster attachment and the incline phase of milk flow of >30 s). Delayed milk ejection occurred in an average of 25% of the cows in each herd (range 0 to 75%). A multivariable model found that the proportion of cows in a herd with delayed milk ejection was negatively associated with mean total time of tactile stimulation during premilking routines and positively associated with herd size.     

Association between bovine leukemia virus, production, and population age in Michigan dairy herds

The objective of this study was to determine the herd-level effect of bovine leukemia virus (BLV) infection on dairy production, culling, and cow longevity. During routine herd testing, Dairy Herd Improvement Association technicians collected milk samples from about 40 cows from each of 104 randomly selected Michigan dairy herds averaging ≥120 milking cows and 11,686 kg of milk/yr. Milk samples were analyzed for the presence of anti-BLV antibodies by ELISA, and herd- and lactation-specific estimates of BLV prevalence were computed to determine which were the most predictive of herd milk production, culling rate, and cow longevity (proportion of cows in their third or greater lactation). On this basis, the herd BLV index (an unweighted mean BLV prevalence rate for lactation number 1, 2, 3, and ≥4) was selected as the measure of BLV prevalence that was the most highly associated with BLV economic impact. Step-down multivariate analysis was used to determine the extent to which any of 19 herd-level management variables may have confounded the association of BLV index and measures of herd economic impact (milk production and cow longevity). The BLV index was not associated with the 12-mo culling rate, but was negatively associated in the final multivariable model with the proportion of cows that were ≥third lactation, and was negatively associated with herd milk production. In summary, increased prevalence of BLV within Michigan dairy herds was found to be associated with decreased herd milk production and decreased cow longevity. Our results provide evidence that BLV infection is associated with herd-level economic impacts in high-performing dairy herds.     

Farm-level factors associated with lameness prevalence,productivity, and milk quality in farms with automated milking systems

Impaired locomotion (lameness) may negatively affect the ability and desire of cows to milk voluntarily, which is a key factor in success of automated milking systems (AMS). The objective of this study was to identify factors associated with herd-level lameness prevalence and associations of lameness and other farm-level factors with milking activity, milk yield, and milk quality in herds with AMS. From April to September 2019, 75 herds with AMS in Ontario, Canada, were visited, and data on barn design and farm management practices were collected. Data from AMS were collected, along with milk recording data, for the 6-mo period before farm visits. Farms averaged 98 ± 71 lactating cows, 2.3 ± 1.5 robot units/farm, 43.6 ± 9.4 cows/robot, 36.4 ± 4.9 kg/d of milk, a milking frequency of 3.01 ± 0.33 milkings/d, and a herd average geometric mean SCC of 179.3 ± 74.6 (× 1,000) cells/mL. Thirty percent of cows/farm (minimum of 30 cows/farm) were scored for body condition (1 = underconditioned to 5 = over conditioned) and locomotion (1 = sound to 5 = lame; clinically lame ≥3 out of 5 = 28.3 ± 11.7%, and severely lame ≥4 out of 5 = 3.0 ± 3.2%). Clinical lameness (locomotion score ≥3) was less prevalent on farms with sand bedding, with increased feed bunk space per cow, and on farms with non-Holstein breeds versus Holsteins, and tended to be less prevalent with lesser proportion of underconditioned cows (with body condition score ≤2.5). Severe lameness occurrence (farms with any cows with locomotion score ≥4) was associated with a greater proportion of underconditioned cows and in farms with stalls with greater curb heights. Herd average milk yield/cow per day increased with lesser prevalence of clinical lameness (each 10-percentage-point decrease in clinical lameness prevalence was associated with 2.0 kg/cow per day greater milk yield) and greater milking visit frequency per day, and tended to be greater with increased feed push-up frequency. Lesser herd average somatic cell count was associated with lesser clinical lameness prevalence, herd average days in milk, and proportion of overconditioned cows, and somatic cell count tended to be lesser for farms with sand bedding versus those with organic bedding substrates. The results highlight the importance of minimizing lameness prevalence, using of sand bedding, ensuring adequate feed access and feed bunk space, and maintaining proper cow body condition to optimize herd-level productivity and milk quality in AMS herds.     

Retrospective cohort study of management procedures associated with dairy herd-level eradication of Streptococcus agalactiae in the Danish surveillance program

The aim of this observational retrospective cohort study was to identify management procedures that are associated with herd-level eradication of Streptococcus agalactiae in dairy herds. The objective was to compare herds that recovered from Strep. agalactiae with herds that remained infected with Strep. agalactiae on the basis of specific management procedures. Data from the Danish surveillance program for Strep. agalactiae, where all milk delivering dairy herds are tested yearly, were used to identify study herds. One hundred ninety-six herds that were classified in the program as infected with Strep. agalactiae, in both January 2013 and January 2014, were identified as study herds. These were followed until January 2017. One hundred forty-four herds remained infected every year until January 2017. Forty-six herds recovered from Strep. agalactiae after January 2014 (were tested negative continuously after January 2015, January 2016, or January 2017 and remained noninfected in the program from recovery until January 2017). Herd characteristics and management procedures were obtained through the Danish Cattle Database. Herd characteristics included herd size, yield, milking system, and bulk milk somatic cell count (SCC). Management procedures included the proportion of cows culled within 100 d after calving due to mastitis, the extent of diagnoses relative to the extent of mastitis treatments, the proportion of cows treated for mastitis during lactation, the proportion of cows treated for mastitis early in lactation, the proportion of cows treated at dry-off, and the median length of the dry period for cows receiving dry cow treatment. All variables were calculated on herd level. Multivariable logistic regression was used to analyze the association between herd infection status and management procedures. A higher proportion of culling due to mastitis within 100 d from calving was associated with a higher probability of herd-level recovery from Strep. agalactiae in herds with conventional milking system. For example, herds with conventional milking, a bulk milk SCC of 260,000 cells/mL, and 10% early culling due to mastitis had a recovery probability of 0.13, whereas similar herds with 20% early culling due to mastitis had a recovery probability of 0.15. A higher proportion of mastitis treatments within 250 d postcalving was associated with a higher probability of herd-level recovery for herds with a relatively high bulk milk SCC. For example, herds with conventional milking, a bulk milk SCC of 260,000 cells/mL, and 10% lactational mastitis treatments had a recovery probability of 0.12, whereas similar herds with 20% lactational mastitis treatments had a recovery probability of 0.15. Herds with a low bulk milk SCC (<220,000 cells/mL) combined with a low proportion of lactational treatments (<0.2) had a relatively high probability of herd-level recovery (>0.2). Additional variables, including the proportion of dry cow treatments, were not associated with herd-level recovery from Strep. agalactiae.     

Dairy management practices associated with incidence rate of clinical mastitis in low somatic cell score herds in France

An epidemiological prospective study was carried out in French dairy herds with Holstein, Montbéliarde, or Normande cows and with low herd somatic cell scores. The objective was to identify dairy management practices associated with herd incidence rate of clinical mastitis. The studied herds were selected on a national basis, clinical cases were recorded through a standardized system, and a stable dairy management system existed. In the surveyed herds, mean milk yield was 7420 kg/cow per yr and mean milk somatic cell score was 2.04 (132,000 cells/mL). Overdispersion Poisson models were performed to investigate risk factors for mastitis incidence rate. From the final model, the herds with the following characteristics had lower incidence rates of clinical mastitis: 1) culling of cows with more than 3 cases of clinical mastitis within a lactation; 2) more than 2 person-years assigned to dairy herd management; 3) balanced concentrate in the cow basal diet. Moreover, herds with the following characteristics had higher incidence rates of clinical mastitis: 1) milking cows loose-housed in a straw yard; 2) no mastitis therapy performed when a single clot was observed in the milk; 3) clusters rinsed using water or soapy water after milking a cow with high somatic cell count; 4) 305-d milk yield >7435 kg; 5) herd located in the South region; 6) herd located in the North region; 7) cows with at least 1 nonfunctional quarter; and 8) premilking holding area with a slippery surface. The underlying mechanisms of some highlighted risk factors, such as milk production level and dietary management practices, should be investigated more thoroughly through international collaboration.     

Short communication: Herd-level variables associated with overmilking in Michigan dairy herds

The objective of this study was to determine the herd-level variables that are associated with overmilking in 64 Michigan dairy herds with a mean herd size of 451 cows (range: 59–2,771 cows). Participating producers completed surveys to indicate their mastitis management practices and attitudes. Additionally, milking protocols were observed and milk flow dynamics for 3,824 cows were estimated using digital vacuum recorders. The median duration of overmilking was 47 s (95% confidence interval, CI: 38.6 to 55.9 s), with a mean of 55% (95% CI: 49.5 to 61.1%) of cows within each herd overmilked by at least 30 s. Median milking time for all herds was 324 s (95% CI: 302 to 346 s) and was found to be positively correlated with median duration of overmilking (r = 0.670). Backward multivariate analysis was used to determine which of 45 herd-level milking and management variables were associated with median duration of overmilking. Median duration of overmilking was negatively associated with the duration of time needed to complete 1 milking for the entire herd (adjusted R² = 0.13). Herds that operate milking facilities below maximum daily capacity may be prone to overmilking. Given the low coefficient of determination, variables unaccounted for in this study, such as equipment function or manual detachment by milking operators, are likely the most important risk factors for overmilking.     

Decreased milk yield is associated with delayed milk ejection

To determine whether individual cow milking vacuum (within the short milk tube and the liner mouthpiece) could be substituted for milk flow technology to identify delayed (bimodal) milk ejection, and the possible relationship between bimodal milk flow and milk yield, we recorded milking data from 663 Holstein cows on a 3,600-cow Michigan dairy that milked 3 times per day. Overall, delayed milk ejection occurred in 45.6% of the milkings, and 98% of the cows with delayed milk ejection also had bimodal flow. Multivariable analysis revealed that milk yield during each individual cow milking was positively associated with increasing lactation number but negatively associated with increasing days in milk and delayed milk ejection. As the time between unit attachment and the estimated milk letdown (the lag period) increased, milk yield decreased; relative to a lag of <30 s, milk yield decreased by 1.8 and 3.1 kg for lags of 30–59 and ≥60 s, respectively. The final multivariate model had an adjusted coefficient of determination of 0.27. The negative association between delayed milk ejection and decreased milk yield in this study suggested that milking vacuum parameters from individual cows could serve as a useful tool to qualitatively estimate milk flow within a herd and that this information may be used to enhance herd productivity.     

Influence of provision of concentrate at milking on voluntary cow traffic in a pasture-based automatic milking system

The success of an automatic milking system is generally reliant upon the voluntary movement of cows around the farm system and the correct management of incentives to achieve a targeted level of cow traffic. The present study investigated the effect of providing a small feed reward as an incentive at milking on the premilking voluntary waiting time of cows milked on a prototype robotic rotary in an Australian pasture-based dairy. The 2 treatments were “feed on” (concentrate offered at milking) and “feed off” (no concentrate offered at milking), with data from a single herd of 168 lactating dairy cows collected over 16 d. A survival analysis with time-varying covariates was used to model the voluntary waiting times of cows in the premilking yard. The median time cows spent waiting before milking was 129 min and after 4 h just over 70% of the cows had exited the yard (volunteered for milking). When feed was provided, cows were faster to exit the premilking yard (shorter time spent waiting) and waited just over half the time (0.53×) they did during the “feed off” treatment. Heifers exited the premilking yard more rapidly than cows in later lactations, with older cows spending at least 1.40 times longer in the yard before milking. Average daily milk yield along with stage of lactation and fetching cows from the paddock also influenced cow traffic in the premilking yard. As the number of cows in the premilking yard increased, voluntary waiting time also increased. At a queue length of 20 or more cows, the negative effect on waiting time of an additional cow entering the yard was less than that when fewer than 20 cows were present. Results demonstrated that feeding a small reward on the robotic rotary platform can reduce the time cows spend in the premilking yard, leading to a potential reduction in the risk of congestion at the dairy, particularly during times of high demand. Minimizing congestion will likely benefit multiple aspects of the voluntary milking operation, including a potential improvement in robot utilization, a reduction in unnecessary time spent off pasture by cows in the milking herd, promoting cow welfare through reducing the risk of lameness, and enhancing productivity. Targeting strategies to minimize queue length to less than the threshold length, which in this study was 20 cows, could result in reduced time spent in the premilking yard.     

Benchmarking of farms with automated milking systems in Canada and associations with milk production and quality

The objective of this study was to benchmark the herd-level housing and management strategies of automated milking system (AMS) farms across Canada and assess the associations of these herd-level housing factors and management practices with milk production and quality. Canadian AMS farms (n = 197; Western Canada: n = 50, Ontario: n = 77, Quebec: n = 59, Atlantic Canada: n = 11) were each visited once from April to September 2019, and details were collected related to barn design and herd management practices. Milk-recording data for the 6 mo before farm visits were collected. Farms averaged (± standard deviation) 110 ± 102 lactating cows, 2.4 ± 1.9 AMS units/farm, 47.5 ± 14.9 cows/AMS, 36.7 ± 5.0 kg/d of milk, 4.13 ± 0.34% fat, 3.40 ± 0.16% protein, and a herd-average somatic cell count of 186,400 ± 80,800 cells/mL. Farms mainly used freestall housing systems (92.5%), organic bedding substrates (73.6%), and free flow cow traffic systems (87.8%); farms predominantly milked Holsteins (90.4%). Multivariable regression models were used to associate herd-level housing factors and management practices with milk production and quality. At the herd level, feed push-up frequency (mean = 12.8 ± 8.3 times per day) and feed bunk space (mean = 64 ± 21.5 cm/cow) were positively associated with milk yield. Greater milk yield was associated with herds using inorganic (sand) versus organic bedding, milking Holsteins versus non-Holsteins, and using a form of mechanical ventilation versus natural ventilation alone. Milk fat and milk protein content were only associated with breed. Herds with lower somatic cell counts had more frequent alley cleaning (mean = 12.1 ± 7.5 times per day), wider lying alleys (mean = 304.5 ± 40.0 cm), and sand bedding. The results highlight the importance of using sand bedding, using mechanical ventilation, keeping feed pushed up, ensuring alleys are clean, and ensuring adequate space at the feed bunk for maintaining herd-level productivity and milk quality in farms with AMS.     

Modeling milk production and labor efficiency in modernized Wisconsin dairy herds

The 1999 Wisconsin Dairy Modernization Project was conducted to examine variation in milk production and labor efficiency among herds that had recently expanded. Data were obtained from a sample of Wisconsin herds that expanded between 1994 and 1998. Using rolling herd average milk production in 1998 as the dependent variable in the milk production model, milking frequency, bovine somatotropin use, sprinkler use, average linear somatic cell score, average age at first calving, average days dry, and rolling herd average milk production in 1994 predicted 69% of the variation in milk production. Milking three times daily, using bovine somatotropin, using sprinklers to cool cows, and decreasing linear somatic cell score, age at first calving, and days dry were associated with increased milk production. Each of these variables supports previous research from designed experiments with on-farm results. Variation in milk production is determined primarily by differences in management ability and management practices employed by the dairy producer. Using cows per full-time equivalent as the dependent variable in the labor efficiency model, acres per cow, number of people involved in the milking operation, milking system type, herd size, and interactions between milking system types and herd size predicted approximately 43% of the variation in labor efficiency. As expected, labor efficiency increased with larger herd sizes, fewer acres per cow, and fewer people involved in the milking process. Parallel milking parlors were associated with the highest cows per full-time equivalent followed by herringbone parlors, flat barns, and stall barns.     

Manageable risk factors associated with bacterial and coliform counts in unpasteurized bulk milk in Flemish dairy herds

Associations between herd management practices and both bacterial counts (BC) and coliform counts (CC) from 254 and 242 dairy herds in Flanders (Belgium), respectively, were studied. Data were analyzed using multivariable, multilevel linear regression analysis, allowing variance components analyses. Both BC and CC fluctuated throughout the year, although the milk quality parameters followed an opposite pattern. Bacterial count values decreased with each increase of the cleaning frequency of the cubicles (once per week, once per day, twice per day, or more than twice per day) between January and March. Herds with a conventional milking parlor had substantially lower BC than herds where the cows were milked using an automatic milking system. Lower BC were observed when the milking parlor was equipped with an automatic cluster removal system, when premilking teat disinfection was applied, when the dry cows were supplemented with a mix of minerals and vitamins, and when the teats were prepared either first wet and dried or via an automatic milking system. Milking cows with a high-pipeline milking parlor setup or with an automatic milking system was associated with substantially higher CC values. Herds where prepartum heifers were often treated with antimicrobials before calving had a lower CC than farms where heifers were either not or only rarely treated. Most variation in BC and CC resided at the herd level rather than at the observation level, indicating that management is important in the control of both BC and CC. Still, only a small proportion of the total variance was explained by factors capturing information related to the milking, herd health, and dry cow management, which suggests that the bacteriological milk quality and, in particular, CC is primarily driven by other factors than the ones included in this study.     

Factors affecting milk flow traits in dairy cows: results of a field study

The study of milk flow curves provides useful information for enhancing milking efficiency and protecting udder health by adapting milking machine and milking procedures to the physiological requirements of the cow. The aim of this experiment was to investigate, using field data, the relationships among traits of the milk flow curves, their sources of variation, and milking performances in terms of milk production, machine-on time, and udder health. A total of 2,486 milk flow curves of the whole udder were collected in 82 Italian Holstein-Friesian dairy herds in the Lombardy region of Italy. Approximately one-third (35.1%) of milk flow curves were classified as bimodal. Most flow characteristics were influenced by lactation number, days in milk, and peak flow but also strongly affected by premilking operations. Proper udder preparation, including forestripping and predipping, resulted in better milking performances compared with poor preparation, with greater milk yield per milking, shorter milking time, and lesser bimodality. Premilking delay time, between the start of teat stimulation and cup attachment, affected milking time significantly: The shortest milking time was obtained for a range of delay time between 1 and 60 s. As the delay time increased, the percentage of bimodality dropped significantly. Increasing the number of clusters per operator led to greater percentages of bimodal curves. The greater somatic cell count of cows with bimodal curves supports the hypothesis of the negative effect of bimodality on udder health and indicates the importance of avoiding its occurrence using proper pre-milking procedures.     

Premilking teat disinfection: Is it worthwhile in pasture-grazed dairy herds?

A controlled trial was conducted in 5 pasture-grazed commercial dairy herds in Australia in 2012 to determine whether premilking teat disinfection and drying of teats reduces clinical mastitis incidence during early lactation by at least 50%. A 50% reduction was estimated to be the minimum required to justify additional costs of labor, disinfectants, and other resources if premilking teat disinfection was implemented in a 500-cow herd averaging 8 clinical cases per 100 cow-months. A secondary aim was to determine whether this premilking teat disinfection routine reduces incidence of new udder infections. Treatment was applied in each herd for approximately 60 d (range of 59.5 to 61 d), commencing in each herd soon after the start of the herd's main or only calving period. Within each herd, cows were allocated to either the treatment (premilking disinfection) or the control (no premilking disinfection) group based on their herd identity number. During the trial period, any cow having a new case of clinical mastitis or an individual cow cell count greater than 250,000 cells/mL of milk (when preceded by individual cow cell counts of 250,000 cells/mL of milk or below) was deemed to have had a new infection. Overall, neither clinical mastitis incidence nor new infection rate differed significantly between treatment and control groups. Over the whole study period, 98 of the 1,029 cows in the premilking disinfection group and 97 of the 1,025 cows in the control group had clinical mastitis. Total cow-days at risk of clinical mastitis were similar in each group. However, clinical incidence rates were markedly lower in treatment cows in one herd (herd 3; incidence rate ratio = 0.34) and there was some evidence that new infection incidence rates were lower in treated cows in this herd (incidence rate ratio = 0.42). Rainfall during the study period was below long-term district average in all 5 study herds. Cows’ teats were less dirty than in previous, wetter years for the 4 herds where no significant clinical mastitis response was detected but some teat soiling was observed in herd 3 during the study period. Routine application of premilking teat disinfection in pasture-grazed herds is unlikely to produce a worthwhile (economic) reduction in the number of clinical mastitis cases when teats are relatively clean and dry and the clinical mastitis incidence is low. However, premilking disinfection might be worthwhile during periods when teats are heavily soiled and the incidence of clinical mastitis due to environmental pathogens is high.     

Effects of duration of udder stimulation on milking dynamics and oxytocin release

For effects of varying duration of premilking manual udder massage on milking performance and oxytocin release, five Holstein cows were subjected to a) no stimulation, b) stimulation by manual udder massage before machine attachment for 15 s, c) for 30 s, d) for 60 s, and e) for 120 s. Milk yield, fat, protein, and somatic cell content were not affected by treatments. The 30-, 60-, and 120-s treatments resulted in higher peak milk flow rate as compared to no stimulation. Stimulation for 60 or 120 s did not achieve higher peak milk flow rates than 15 or 30 s. Average milk flow rate increased with duration of stimulation, and no stimulation differed from 30-, 60-, and 120-s treatments. Machine-on time decreased with increasing stimulation. However, differences in average flow rates and machine-on times became nonsignificant when premilking stimulation time was added to machine-on time. No differences were significant between treatments and mean oxytocin concentrations. The marked difference in milk flow variables and machine-on time suggested a small yet finite threshold concentration of oxytocin leads to milk ejection. Udder massage of 30 s prior to machine attachment is more than adequate for preparing cows for milking with machine stripping.     

Comparison of modeled sampling strategies for estimation of dairy herd lameness prevalence and cow-level variables associated with lameness

Monitoring herd lameness prevalence has utility for dairy producers and veterinarians in their efforts to reduce lameness, for animal welfare assessment programs, and for researchers. Locomotion scoring is a method used to quantify lameness and calculate prevalence. Because of the time necessary to locomotion score each cow in large dairy herds, a sampling strategy to determine herd lameness prevalence that allows scoring of fewer cows would be useful. Such a sampling strategy must be validated for accuracy compared with the lameness prevalence when all cows in a herd are locomotion scored. The purpose of this study was to assess 3 previously suggested methods of estimating lameness prevalence by strategic sampling of dairy herds. Sampling strategies tested included (1) sampling a calculated number of cows in the middle third of the milking parlor exit order for each pen, (2) sampling a calculated number of cows weighted across pens and distributed evenly within each pen, and (3) sampling all cows in the high production, low production, and hospital pens. Lactating cows on 5 dairy farms in Washington and Oregon (n = 4,422) were locomotion scored using a 5-point scale to determine herd-level lameness prevalence (percentage with locomotion score ≥3). Milking parlor exit order, order in headlocks at the feed bunk within each pen, and breed were recorded for each cow. The number of days in lactation, milk production, and parity were collected from farm computer records. Pen grouping strategy for each farm was obtained by interview with farm management. Sampling strategies were modeled using the locomotion score data set for each herd. Estimates of lameness prevalence obtained from the milking parlor exit order sample and the sample distributed across pens were within 5 percentage points of the whole herd prevalence. The third strategy estimated the lameness prevalence within 5 percentage points on 4 farms, but overestimated prevalence on 1 farm. Pen-level prevalence obtained by locomotion score of all cows in the pen was variable and not reliably predictive of herd-level prevalence. Cows of Holstein breed, parity >1, and exiting the milking parlor in the last 20% of the pen had greater odds of lameness compared with other breeds, parities, and milking parlor exit order groups in a multivariate analysis. This study indicates that the sampling strategies using the middle of milking parlor exit order and a calculated sample distributed across the herd may be used to obtain an estimate of herd lameness prevalence.     

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.     

Evaluation of milk ELISA fordetection of Mycobacterium avium subspecies paratuberculosis indairy herds and association with within-herd prevalence

Cow-level milk ELISA results can be used to determine herd Mycobacterium avium ssp. paratuberculosis (MAP) status. Milk sample collection is minimally invasive and ELISA results can be obtained quickly and economically. The objectives were to evaluate the herd-level test characteristics of 3 commercial milk ELISA, and to determine the impact of within-herd MAP prevalence on the performance of the milk ELISA herd test. A total of 32 purposively selected herds with a median herd size of 66 milking cows were used in this 2-yr project. Fecal and milk samples were collected from all milking cows at 6-mo intervals. Fecal samples were pooled by cow age, with 5 cow samples per pool; individual fecal culture was completed on cow samples from positive pools. Herd MAP status was defined as MAP positive if, at any point during the longitudinal study, a pooled fecal culture from the herd was positive. Milk samples were analyzed using each of 3 commercial milk ELISA kits; a cow-level result from each ELISA was classified as positive following the respective manufacturer’s recommended threshold for a positive result. Herd-level milk ELISA test characteristics were estimated using generalized estimating equations logistic models, which accounted for repeated measurements. Using a cutoff of 2% milk ELISA-positive cows, milk ELISA herd sensitivity relative to a herd MAP status based on all pooled fecal culture results collected during the study was as follows: ELISA A: 59% [95% confidence interval (CI): 36–78%), ELISA B: 56% (95% CI: 32–77%), and ELISA C: 63% (95% CI: 41–81%). Herd specificity for ELISA A, B, and C was 80% (95% CI: 71–88%), 96% (95% CI: 89–98%), and 92% (95% CI: 86–96%), respectively. The remainder of the analyses focused on results from ELISA B. Herd sensitivity of ELISA B increased as MAP prevalence increased. In herds with a mean MAP prevalence ≤5%, the herd sensitivity of the milk ELISA was low, ranging from 11% when MAP prevalence was 1%, to 62% when MAP prevalence was 5%. Categorical likelihood ratios based on milk ELISA within-herd prevalence predicted that herds with milk ELISA prevalence above 0 but <2% had a similar likelihood to be MAP positive or MAP negative, whereas herds with a milk ELISA prevalence between 2 and 4% were 3.7 times more likely to be MAP positive than MAP negative. All herds with a milk ELISA prevalence >4% were MAP positive. Although milk ELISA B worked well to establish herd MAP status in high-prevalence herds, interpretation was unreliable in MAP-negative and low-prevalence herds.     

Factors associated with productivity on automatic milking system dairy farms in the Upper Midwest United States

The objective of this study was to identify housing and management factors associated with productivity on automatic milking system (AMS) dairy farms measured as daily milk yield/AMS and daily milk yield/cow. Management, housing, and lameness prevalence data were collected from 33 AMS farms in Minnesota and Wisconsin during a farm visit. All farms in the study used free-flow cow traffic. Mixed model analysis of cross-sectional data showed that farms with automatic feed push-up via a robot produced more milk per AMS/day and per cow/day than farms where feed was pushed up manually. New versus retrofitted facility, freestall surface, manure removal system, and the number of AMS units/pen were not associated with daily milk yield per AMS or per cow. Cow comfort index (calculated as number of cows lying down in stalls divided by total number of cows touching a stall) was positively associated with daily milk yield/cow. Prevalence of lameness and severe lameness, number of cows per full-time employee, depth of the area in front of the AMS milking station, and length of the exit lane from the AMS milking station were not associated with daily milk yield per AMS or per cow. Multivariable mixed model analysis of longitudinal AMS software data collected daily over approximately an 18-mo period from 32 of the farms found a positive association between daily milk yield/AMS and average age of the cows, cow milking frequency, cow milking speed, number of cows/AMS, and daily amount of concentrate feed offered/cow in the AMS. Factors negatively associated with daily milk yield/AMS were number of failed and refused cow visits to the AMS, treatment time (the time spent preparing the udder before milking and applying a teat disinfectant after milking), and amount of residual concentrate feed/cow. Similar results were also found for daily milk yield on a per cow basis; however, as it would be expected, average days in milk of the herd were also negatively associated with daily milk yield/cow. These findings indicate that several management and cow factors must be managed well to optimize AMS productivity.     

Milking parlour size, pre-milking routine and stage of lactation affect efficiency of milking in single-operator herringbone parlours

Efficient milking systems, in terms of labour demand, capital investment and cow udder health are critical to successful dairy herd expansion. The objective of this study was to establish the effect of two primary influencing factors on efficient milking performance, i.e. parlour size (number of milking units) and pre-milking routine (full and nil) of spring-calved cows, in a single-operator side-by-side, swing-over milking parlour. Efficiency parameters investigated in a 5 × 2 factorial design included milk-flow and yield, row time, over-milking duration and operator idle time. Five combinations of parlour size (14, 18, 22, 26 and 30 milking units) each with two different pre-milking routines (Full: spray, strip, wipe, attach clusters, and Nil: attach clusters) were examined with one milking operator. The trial was carried out over 40 milking sessions and cows (up to 120) were randomly assigned to groups (n = 14, 18, 22, 26 or 30) before each milking session. Row within a milking session was the experimental unit. The experiment was carried out at both peak and late lactation. The data were analysed with a mixed model using GenStat 13.2. The full pre-milking routine reduced time to milk let-down and milking time, increased average flow rate but did not affect milk yield. As milking unit number increased, the duration of over-milking (defined as time at milk flow rate < 0·2 kg/min) increased more with a full compared with nil routine. Thus, the use of pre-milking preparation decreased milking time per cow but as parlour size increased, milking row times, as well as the proportion of cows that were over-milked, also increased, thereby reducing overall efficiency. These results have implications for milking management in single-operator swing-over, tandem and rotary parlours with seasonally calved herds.     

Effects of cleaning duration and water temperature on oxytocin release and milk removal in an automatic milking system

Four different methods of teat preparation during milking in an automatic milking system were studied in 2 experiments on Red Holstein/German Fleckvieh cross-breed cows. Milking routines used were milking: 1) without premilking teat preparation; 2) with one cleaning cycle (58 to 60 s) with cold (13 to 15 degrees C) water; 3) with one cleaning cycle with warm water (30 to 32 degrees C); or 4) with 2 cleaning cycles (122 s) with warm water. In experiment 1, milking characteristics were evaluated and milking routines were randomly assigned to 62 cows during 3 measuring periods of 24 h each. In experiment 2, 10 randomly selected cows were assigned to the same milking routines during 4 d and blood samples for oxytocin (OT) determination were taken during milking in addition to milk flow recording. Milk production, peak flow rate, total, and quarter milk yields showed no differences among treatments. Premilking preparation with cold water compared with warm water showed no differences in OT release, milk yield, peak flow rate, main milking time, average flow rate, or time until main milk flow. Baseline OT concentrations were consistently low. At the start of teat cup attachment without premilking teat preparation OT concentrations remained on the basal level but were elevated in all other treatments. By 30 s from the start of milking, OT concentrations were markedly increased in all treatments and were no longer different between treatments. In conclusion, the teat cleaning device used in the automatic milking system, either with warm or cold water, was suitable to induce milk ejection in cows before the start of milking.