Bulk Tank Somatic Cell Count Research Articles

Short communication: Effect of dry therapy using an intramammary infusion on bulk tank somatic cell count in sheep

A total of 3,141 records of bulk tank milk somatic cell counts (BTSCC) and bulk tank milk total bacterial counts (BTTBC) were obtained over 24 mo from 25 dairy flocks of Assaf ewes belonging to the Consortium for Ovine Promotion in Castilla-León, Spain, in which a complete dry therapy program was carried out in 10,313 ewes using an antibiotic infusion containing 100mg of penethamate hydriodide, 280mg of benethamine penicillin, and 100mg of framycetin sulfate. The selection criteria for all flocks were BTSCC mean values ≥1,000×103 cells/mL and absence of dry therapy before the start of this experiment. Significant effects on log BTSCC were detected for treatment, milking system, flock within milking system, month within flock by treatment, the interactions treatment by milking system and flock by treatment within milking system, and log BTTBC. After dry therapy was implemented, log BTSCC decreased significantly in machine-milked flocks (5.95±0.007) compared with values before antibiotic treatment (6.13±0.008). The effect was observed at the beginning of the second lactation posttreatment (5.98±0.013). However, dry therapy was not effective in hand-milked flocks, suggesting poor hygiene conditions. A significant relationship was found between BTSCC and BTTBC; therefore, programs for improving milk hygiene should be implemented for both BTSCC and BTTBC variables at the same time.

Evaluation of Effects of Milking Hygiene and Management Factor on Clinical Mastitis Incidence in Dairy Cows

Summary The aim of this study was to determine the prevalence of clinical mastitis and somatic cell count (SCC) in six dairy herds which had different milking management and hygiene conditions. Four - hundred thirty one Holstein - Friesian cows were used in the study. The herds were classifi ed to be good (Group 1, n=2), medium (Group 2, n=1) or bad (Group 3, n=3) according to milking management and hygiene. The study was carried out on these 3 groups. Diagnosis of clinical mastitis was based on pathological symptoms in quarters and abnormal changes in milk. Rates of clinical cases were 20.2%, 28.3% and 36.5% for good, medium and bad conditions. Individual (ISCC) and bulk tank (BTSCC) somatic cell count were categorized to be low, medium and high. Of the quarters, 82% had low ISCC (<200.000 cells mL -1 ) in herds with good milking hygiene. Average ISCC and BTSCC values were higher in bad conditions than others (P<0.05).

Prevalence of Pathogens Associated with Bovine Mastitis in Bulk Tank Milk in Mexico

Mastitis as cause of low milk production coupled with the use of medication to control it cause dairy farms to register large economic losses. Microorganisms' prevalence, and somatic cell counts (SCCs) were determined in 112 Holstein bovine herds in two bulk tank milk-screening assays. Detection of Staphylococcus aureus, Streptococcus agalactiae, and Mycoplasma spp. as microorganisms primarily responsible for clinical and subclinical mastitis and their relationship with SCCs was evaluated by Student's t-test and the kappa test. Prevalence of Mycoplasma was 55%; of S. aureus, 30%; of Streptococcus uberis, 37.5%; and of Staphylococcus coagulase-negative, 38.3%. The geometric mean of the SCC was 465,000 cells/mL. No significant differences were observed in the SCCs between the positive and negative samples of pathogens isolated (P > 0.5). There was a low kappa value of Mycoplasma correlation between samplings (kappa value = 0.10). This work aimed to understand the relationship between the prevalence of mastitis pathogens in bulk tank milk and SCCs in bovine herds in the central part of Mexico.

Management of mastitis on organic and conventional dairy farms1

This paper compares management of mastitis on organic dairy farms with that on conventional dairy farms. National standards for organic production vary by country. In the United States, usage of antimicrobials to treat dairy cattle results in permanent loss of organic status of the animal, effectively limiting treatment choices for animals experiencing bacterial diseases. There are no products approved by the US Food and Drug Administration that can be used for treatment of mastitis on organic dairy farms, and usage of unapproved products is contrary to Food and Drug Administration guidelines. In general, organic dairy farms tend to be smaller, produce less, and more likely to be housed and milked in traditional barns as compared with conventionally managed herds. It is difficult to compare disease rates between herds managed conventionally or organically because perception and detection of disease is influenced by management system. To date, no studies have been published with the defined objective of comparing animal health on organic dairy herds with that on conventional dairy herds in the United States. European studies have not documented significant differences in animal health based on adoption of organic management. Few differences in bulk tank somatic cell counts have been identified between organic and conventional herds. Farmers that have adopted organic management consistently report fewer cases of clinical mastitis, but organic farmers do not use the same criteria to detect clinical mastitis. European dairy farmers that adopt organic management report use of a variety of conventional and alternative therapies for treatment and control of mastitis. In the United States, organic farmers treat clinical mastitis using a variety of alternative therapies including whey-based products, botanicals, vitamin supplements, and homeopathy. Organic farmers in the United States use a variety of alternative products to treat cows at dry-off. Virtually no data are available that support the clinical efficacy of any of the alternative veterinary products used for treatment or prevention of mastitis. Some associations between organic management and antimicrobial susceptibility of gram-positive mastitis pathogens have been noted, but overall, few mastitis pathogens from both conventional and organic dairy herds demonstrate resistance to antibiotics commonly used for mastitis control.

Management practices associated with Mycobacterium avium subspecies paratuberculosis infection and the effects of the infection on dairy herds

During 2004, a survey of Mycobacterium avium subspecies paratuberculosis (map) was conducted in 101 randomly selected dairy herds to investigate associations between the infection status of the herds, different management...

The effect of estrus synchronization treatments on somatic cell count of transitional-anestrus Awassi ewes’ milk

Fifty-three transitional-anestrus Awassi ewes, randomly assigned to three groups: fluorogestone acetate (FGA, n = 18), FGA-Prostaglandin (FGA-PGF, n = 18) and control (n = 17), were used to examine the effect of estrus synchronization protocols and steroid hormones concentrations on milk somatic cell count (SCC). Intravaginal FGA sponge was inserted for 13 days and 600 IU equine chorionic gonadotropin was administered for ewes of FGA and FGA-PGF groups at the time of sponge removal (day 0). In addition, 10 mg was administered to ewes of FGA-PGF group on day 0. Blood and milk samples were collected from all ewes on days -13, -6, 0, 1, 2, 7 and 14. Estradiol had significant positive correlation with the SCC during the periods of sponge insertion (P = 0.015, r = 0.235) and within two days (P = 0.063 r = 0.23) after sponge removal with no correlation with SCC of both udder halves during the luteal phase. Progesterone concentrations, on the other hand, had a significant positive correlation (P < 0.001; r = 0.420) with the SCC of both udder halves during the luteal phase of the experiment, but not during the periods of sponge insertion and expected estrus. SCC returned under the influence of endogenous progesterone on days 7 and 14 to pre-synchronization values. In conclusion, sheep milk SCC is affected significantly with induction of estrus and steroid hormones concentrations. However, peak SCC recorded during estrus was far below the upper limit of the current standard for normal milk. With the current standards for SCC of 1,000,000/ml as legal limit for abnormal milk control programs in sheep, estrus synchronization programs and the estrus status should not be considered when bulk-tank milk SCC is being investigated, but should be considered during the process of setting new standards.

Influence of Variable Milk Quality Premiums on Observed Milk Quality

The objective of this study was to evaluate a premium program for very high quality milk in a US cooperative. Data were available on a monthly basis from a large US milk cooperative from April 1998 through December 2005. The data set consisted of 36,930 observations representing producer-months. The actual amount of the low bulk tank somatic cell count (BTSCC) premium varied from $0.15 per hundred pounds (cwt.) of milk to $1.00/cwt. with steps in between of $0.50 and $0.60 per cwt. of milk during the data collection period. Data analysis was done to evaluate the impact of the premium program on average BTSCC and on the probability of a producer to ship milk with <100,000 cells/mL in a given month. The results showed a strong effect of the premium program on both the average BTSCC and the probability of producing milk with very low BTSCC. On average, the BTSCC of all the milk in the cooperative was reduced by 22,000 cells during the high premium period. The probability of producing milk with BTSCC <100,000 doubled during some months of the high premium period from 4 to 8%, and an associated 10% increase in probability to produce milk below 200,000 cells/mL was observed. The data clearly indicate that premium offerings for very high quality milk affect the overall milk quality in the population affected by the premium. Producers responded to the high premiums and the overall impact on milk quality was substantial. We argue that the combination of a penalty program for high BTSCC milk with a premium program for very high quality milk (low BTSCC) provides a strong incentive for improvement of milk quality.

Record keeping, genetic selection, educational experience and farm management effects on average milk yield per cow, milk fat percentage, bacterial score and bulk tank somatic cell count of dairy farms in the Central region of Thailand

A study was conducted to estimate the record keeping, genetic selection, educational, and farm management effects on average milk yield per cow (AYC), milk fat percentage, bacterial score, and bulk tank somatic cell count (BTSCC) of dairy farms in the central region of Thailand. Farms were located in the provinces of Saraburi and Nakhon Ratchisima and were members of the Muaklek dairy cooperative. Records from individual animals were unavailable. Thus, farm records of milk yield, milk fat percentage, bacterial score, and BTCCC were collected from July 1, 2003 through June 30, 2006. Additional record keeping, genetic selection, education, and farm management information was collected through a questionnaire in May of 2006. Data from the Muaklek dairy cooperative and the questionnaire were then merged by a farm identification number. A single trait mixed model was used to analyze AYC, milk fat percentage, and BTSCC, while a log linear model was used to analyze bacterial score. Results showed that farms that kept records on individual animals had higher (P < 0.05) milk fat percentages and lower bacterial scores than farms that did not. Farms that used genetic information (EBV) and phenotypes when selecting sires were higher (P < 0.05) for milk fat percentage than farms that used only phenotypes and personal opinion. Farms milking cows with a single unit milking machine and by hand, had higher (P < 0.05) bacterial scores and BTSCC than farms using only a single or multi unit machine. Overall farms that kept individual animal records, used EBV when selecting sires, used a single method for collecting milk, and used family labor achieved higher performance from their herds than farms that did not.

Costs of mastitis: facts and perception

A model to calculate the economic losses of mastitis on an average Dutch dairy farm was developed and used as base for a tool for farmers and advisors to calculate farm-specific economic losses of mastitis. The economic losses of a clinical case in a default situation were calculated as euro210, varying from euro164 to euro235 depending on the month of lactation. The total economic losses of mastitis (subclinical and clinical) per cow present in a default situation varied between euro65 and euro182/cow per year depending on the bulk tank somatic cell count. The tool was used to measure perception of the total economic losses of mastitis on the farm and the farmers' assessment of the cost factors of mastitis on 78 dairy farms, of which 64 were used for further analyses. Most farmers (72%) expected their economic losses to be lower than those revealed by our calculation made with their farm information. Underestimating the economic losses of mastitis can be regarded as a general problem in the dairy sector. The average economic losses assessed by the farmers were euro78/cow per year, but a large variation was given, euro17-198/cow per year. Although the average assessment of the farmers of the different cost factors is close to the default value, there is much variation. To improve the adoption rate of advice and lower the incidence of mastitis, it is important to show the farmers the economic losses of mastitis on their farm. The tool described in this paper can play a role in that process.

Predicting Somatic Cell Count Standard Violations Based on Herd's Bulk Tank Somatic Cell Count. Part I: Analyzing Variation

The present study examines the relationship between the bulk tank somatic cell count (SCC) mean and sigma (an estimate of variation) and the probability of exceeding a SCC standard. Daily or every other day, bulk tank SCC data were collected for 24 mo from 1,501 herds. Mean and sigma were estimated for each herd monthly and were compared between months and herd production categories using Kruskal-Wallis nonparametric ANOVA. The effect of month on bulk tank SCC mean and sigma was significant, with estimates for all summer months and most of the spring and fall months being significantly greater than estimates of mean and sigma in December 2004. Logistic regression models were developed to examine the relationship between month and herd production and the odds of a herd exceeding a SCC standard. The odds of exceeding a bulk tank SCC standard were significantly greater in the summer months and for smaller herds. A grid was constructed determining the probability of exceeding any of 5 SCC standards (200,000 to 600,000 cells/mL, step 100,000 cells/mL) in the following month, based on the mean and sigma of the past month. The violation probability grid can be used to assess the prospect of meeting quality premium goals and to proactively encourage more consistent performance in all the processes affecting bulk tank SCC.

Predicting Somatic Cell Count Standard Violations Based on Herd's Bulk Tank Somatic Cell Count. Part II: Consistency Index

The present study examines the capability of 1,501 herds in the Upper Midwest and the performance of statistical process control charts and indices as a way of monitoring and controlling milk quality on the farm. For 24 mo, daily or every other day bulk tank somatic cell count (SCC) data were collected. Consistency indices for 5 different SCC standards were developed. The indices calculate the maximum variation allowed to meet a desired SCC level at a given mean bulk tank SCC and were used to identify herds not capable of meeting a specific SCC standard. Consistency index method was compared with a test identifying future bulk tank SCC standard violators based on herds’ past violations. The performance of the consistency index test and the past violation method was evaluated by logistic regression. The comparison focused on detection probability and certainty associated with a result. For the 5 SCC levels, detection probability and certainty associated with a result ranged from 51 to 98%. Detection probability of all violators and certainty associated with a negative result was greater for the consistency index across all 5 SCC levels (by 0.7 to 7.4% and 2.1 to 5.1%, respectively). Control charts were plotted and monthly consistency indices calculated for individual farms. Charts in combination with the consistency indices would warn from 66 to 80% of the herds about an upcoming violation within 30 d before it occurred. They offer a proactive approach to maintaining consistently high milk quality. By assessing process capability and distinguishing between significant changes and random variation in bulk tank SCC, tools presented in this article encourage fact-based decisions in dairy farm milk quality management.

Comparison of two milk pricing systems and their effect on milk price and milk revenue of dairy farms in the Central region of Thailand

A study was conducted to investigate determinates of how milk pricing system, farm location, farm size, and month and year affected farm milk price (FMP), farm milk revenue (FMR) and loss in FMR of dairy farms in the Central region of Thailand. A total of 58,575 milk price and 813,636 milk yield records from 1034 farms were collected from November of 2004 to June of 2006. Farms were located in the districts of Muaklek, Pak Chong, Wang Muang, and Kaeng Khoi. A fixed linear model was used to analyze milk price of farms. Two pricing systems were defined as 1 = base price plus additions/deductions for milk fat percentage, solids-non-fat, and bacterial score, and 2 = same as 1 plus bulk tank somatic cell count (BTSCC). Farm size (small, medium, and large) was based on the number of cows milked per day of farms. Results showed that FMP were lower (P < 0.05) in pricing system 1 than pricing system 2. Most small farms had higher (P < 0.05) milk prices than medium and large farms across both pricing systems. Large farms lost more milk revenue due to deductions from bacterial score and BTSCC than small and medium farms.

The effect of estrus synchronization treatment on somatic cell count of transitional-anestrus local-Damascus cross breed goats’ milk

An experiment was conducted to examine the effect of estrus synchronization protocols and steroid hormones concentrations on somatic cell count (SCC) of transitional-anestrus local-Damascus cross goats' milk. Fifty-six goats (2-4-year old) were randomly assigned to three groups: fluorogestone acetate (FGA, n = 19), FGA-Prostaglandin (FGA-PGF, n = 19) and control (n = 18) groups. Intravaginal sponge containing 40 mg FGA was inserted for 13 days and an injection of 600 IU equine chorionic gonadotropin (eCG) was administered for goats of FGA and FGA-PGF groups at the time of sponge removal (day 0). In addition, goats of FGA-PGF group were injected with 10 mg dinoprost tromethamine (PGF2alpha) on day 0. Five fertile local-Damascus cross bucks were turned-in with all goats on day 0. Blood and milk samples were collected from all goats on days -13 (beginning of experiment), -6, 0, 1, 2, 7, 13 and 20 (end of the experiment). Four-year old and second-parity goats had significantly higher (p < 0.05) SCC of both udder halves than 2- and 3-year old and first-parity goats, respectively. There was a significant effect (p < 0.05) for treatment and number of kids born in the last kidding season on SCC of both udder halves. Neither estradiol nor progesterone concentrations were correlated with SCC in goats in this experiment. The SCC of both udder halves and left udder halves in goats of the control and FGA groups, respectively, increased significantly (p < 0.05) after sponge removal and buck introduction when compared with day 0, with no differences in the FGA-PGF group. This increase in SCC of the control and FGA groups coincided with peak estrus behavior. However, SCC was far below the upper limit of the current standard for normal milk. In conclusion, induction of estrus with progestagen based programs and buck introduction may cause temporary significant increase in SCC. However, the SCC values during this period of temporary increase were still in the range of acceptable values for normal milk. With the current standards for SCC of 1,000,000/ml as legal limit for abnormal milk control programs in goats, estrus synchronization programs and the estrus status should not be considered when bulk-tank milk SCC is being investigated.

Factors affecting milk yield, milk fat, bacterial score, and bulk tank somatic cell count of dairy farms in the central region of Thailand

A study was conducted to determine the effects of season, farm location, and farm size on farm milk yield (FMY), average milk yield per cow (AYC), milk fat, bacterial score, and bulk tank somatic cell count (BTSCC) of dairy farms in the central region of Thailand. Farms were located in the districts of Kaeng Khoi, Muaklek, Pak Chong, and Wang Muang. Collection of data was at the farm level; individual animal records were unavailable. A total of 967,110 daily farm milk yield, 58,575 milk fat and bacterial score, and 24,109 BTSCC records from 1,034 farms were collected from July of 2003 to June of 2006. There were three seasons: rainy, summer and winter. Farms were categorized into small, medium, and large according to the number of cows milked per day. Results showed that FMY and AYC were higher (p<0.05) in winter and lower in the summer and rainy seasons. In addition, the majority of small size farms had higher (p<0.05) AYC and milk fat values, and lower bacterial score and BTSCC values than medium and large size farms.

Herd Management Practices and Their Association with Bulk Tank Somatic Cell Count on United States Dairy Operations

The objective of this study was to evaluate associations between bulk tank somatic cell count (BTSCC) and herd management practices using data collected in the National Animal Health Monitoring System Dairy 2002 study. Twenty-six percent and 17.8% of 1,013 operations reported a BTSCC <200,000 cells/mL and >400,000 cells/mL, respectively. Univariate analysis identified associations between management variables and BTSCC. The use of mattresses, sand, and newspaper as bedding were all associated with a lower BTSCC. Primary lactating cow housing facility, outside maternity housing area, flooring type cows walk or stand on, and use of automatic take-offs were also associated with BTSCC. Multivariate associations between management variables and BTSCC were determined by backward elimination ordinal logistic regression. The odds of an operation from the West, Midwest, and Northeast having a high BTSCC were lower than those from the Southeast. The odds of a higher BTSCC were 2 times greater for operations with a rolling herd average milk production <9,090 kg/cow per year compared with those with ≥9,090 kg/cow per year. Operations using composted manure were 2.9 times more likely to have a higher BTSCC than those not using composted manure. Finally, operations that reported not using a coliform mastitis vaccine were 1.7 times more likely to have a higher BTSCC than those using one. Future studies of the association between management practices and BTSCC should include an evaluation of the quality of management practice application and herd prevalence of contagious mastitis pathogens. Significant variables identified in this study dealt with housing, use of composted manure for bedding, and coliform mastitis vaccine use, suggesting the effect of environmental mastitis pathogens may be more influential on BTSCC than previously thought.

Bulk tank milk somatic cell count and sources of raw milk contamination with mastitis pathogens

The objective of this study was to probe the relationship between prevalence of selected principal mastitis pathogens and somatic cell counts in bulk tank milk samples. The sources of milk contamination were evaluated. The samples were collected from 298 dairy herds (with approximately 32 000 dairy cows). Only 48.3% of the bulk tank milk samples were free of contamination of pathogens of interest. Approximately 38.9% of the milk samples were contaminated with only one, 12.4% with two and 0.3% with three pathogens. The arithmetic mean of logarithmically transformed data of bulk tank milk somatic cell count rise in order: pathogen free, &lt;i&gt;Pseudomonas aeruginosa&lt;/i&gt;, &lt;i&gt;Streptococcus uberis&lt;/i&gt;, &lt;i&gt;Escherichia coli&lt;/i&gt; and &lt;i&gt;Staphylococcus aureus&lt;/i&gt; (5.381; 5.413; 5.495; 5.518; 5.563, respectively). The arithmetic mean differences between bulk tank milk somatic cell counts in pathogen-free and single-pathogen contaminated samples have revealed a significance for the &lt;i&gt;Escherichia coli&lt;/i&gt; and &lt;i&gt;Staphylococcus aureus&lt;/i&gt; groups (&lt;i&gt;P&lt;/i&gt; &amp;lt; 0.01). Using binary logistic regression, a statistically highly significant relationship (&lt;i&gt;P&lt;/i&gt; &amp;lt; 0.001) has been found between the number of contaminations of bulk tank milk samples with mastitis pathogens and bulk tank milk somatic cell counts. The relationship allows the determination of the probability of finding relevant mastitis pathogens in bulk tank milk samples with different levels of bulk tank milk SCC. A 63% probability can be defined at a cell count level of 400 000/ml and 20% at a cell count level of 100 000/ml. Analysis may reveal the potential sources of the bulk tank milk sample contamination, i.e. infected mammary glands or the environment. The presence of high levels of contamination along with a low bulk tank SCC may suggest an environmental source of contamination. The study clarified that a potential source of bulk tank milk contamination by relevant pathogens (the environment or the mammary gland) may be elucidated and the probability of the contamination of bulk tank milk samples with mastitis pathogens predicted by the analysis of relationship between the bulk tank milk somatic cell counts and the number of mastitis pathogen contaminations.

Dairy cow cleanliness and milk quality on organic and conventional farms in the UK

A subjective cow cleanliness scoring system was validated and used to assess the cleanliness score of dairy cows at different times in the year. A longitudinal study followed a number of farms from summer to winter, and a larger, cross-sectional study assessed a greater number of farms during the housed winter period. The scoring system was demonstrated to be both a repeatable and practical technique to use on-farm and showed that cows become dirtier in the transition from summer grazing to winter housing. Although farming system (organic or conventional) had no effect on cow cleanliness when cows were at grass, when housed in the winter, organic cows were significantly more likely to be cleaner. There was a link between cow cleanliness scores and milk quality, with herds having lower bulk tank somatic cell counts (BTSCC) tending to have a lower (cleaner) median cow cleanliness score; with this relationship strongest for the organic herds. There was no significant link between cleanliness score and Bactoscan (BS) count or clinical mastitis incidence. No major mastitis pathogens were cultured from bulk tank milk samples from the quartile of herds with the cleanest cows in contrast to the quartile of herds with the dirtiest cows, where significant mastitis pathogens were cultured. Based on this study, all farms, especially organic systems, should attempt to keep cows clean as part of subclinical mastitis control.

Performance and Welfare of Dairy Cows in an Alternative Housing System in Minnesota

The compost bedded pack dairy barn is an alternative housing system for lactating cows that has received increased attention in the last 2 yr. No descriptive data were available about this housing system. Therefore, a study of 12 compost dairy barns in Minnesota was conducted between late June 2005 and September 2005. The objectives of this study were to describe the housing system, identify management practices used in these herds, observe cow welfare, analyze herd performance and udder health prior to and following the change in housing system, and measure producer satisfaction with the system. Producers were interviewed on various aspects related to the housing system and herd management, samples of milk were collected, and cows were scored for locomotion, body condition, hygiene, and hock lesions. In addition, historical bulk tank information and Dairy Herd Improvement Association data were collected when available. At the time of the visit, the Dairy Herd Improvement Association somatic cell count (SCC) was 325,000±172,000 cells/mL, rolling herd average was 10,457±1,138kg per cow, and herd size was 73±35.5 lactating cows. The body condition score was 3.04±0.11, the cow hygiene score was 2.66±0.19, and 7.8% of all cows were clinically lame (locomotion score ≥3 on a 1 to 5 scale). No hock lesions were present on 74.9% of the cows; 24.1% of cows had a mild lesion (hair loss), and 1.0% had a severe lesion (swollen hock). Historical analysis of the bulk tank SCC showed that 3 out of the 7 herds analyzed had a significant reduction in bulk tank SCC when compared with the previous housing system. Mastitis infection rates decreased significantly by 12% on 6 of the 9 farms analyzed. Reproductive performance significantly improved for 4 out of the 7 herds analyzed, with 25.9 and 34.5% improvement in heat detection rates and pregnancy rates, respectively. The main reasons producers reported for building this type of housing system were for improved cow comfort, cow health and longevity, and ease of completing daily chores. The largest concern was the cost and availability of bedding, especially as additional compost barns are built. Overall, all producers were satisfied with their decision to build a compost barn.

Loser cows in Danish dairy herds: Risk factors

The objective of our study was to evaluate risk factors for the loser cow state in Danish dairy herds. A loser cow was defined on the basis of a clinical examination of the individual cow. Recordings of clinical signs were converted into a loser cow score and all cows with a loser cow score of 8 or more were defined as loser cows. We used correspondence analysis to give a first indication of the associations between the proportion of loser cows in the herd and potential risk factors. Risk factors were evaluated both at the herd level (39 herds) and at the cow level (6451 cows) using logistic regression. Conventional herds with a high average somatic cell count, hard cubicles and no grazing seem to be associated with a high proportion of loser cows. Odds ratio for the loser cow state was 4.18 in conventional herds compared to organic herds. Odds ratio for the loser cow state was 1.87 for an increase in average weighted mean bulk tank somatic cell count of 100,000 cells per ml. We found a statistically significant interaction between stall surface and the use of grazing. Odds ratio for the loser cow state in herds with soft cubicles and the use of grazing was 0.09 compared to herds with hard cubicles and no grazing. At the cow level, odds ratio for the loser cow state increases significantly with increasing parity. Odds ratios for the loser cow state were 1, 2.59 and 6.74 for parity 1, 2, and 3 or older, respectively. Odds ratio for the loser cow state was significantly higher (3.38) for cows giving birth to twins at the last calving before the scoring. Additionally, cows scored on pasture had a significantly lower odds ratio (0.26) for the loser cow state compared to cows scored in the barn.

Temporal Trends in Bulk Tank Somatic Cell Count and Total Bacterial Count in Irish Dairy Herds During the Past Decade

The objective of this study was to document temporal trends in bulk tank somatic cell count (SCC) and total bacterial counts (TBC) in Irish dairy herds during the years 1994 to 2004. Three milk processors participated in the study, providing data on 2,754,270 individual bulk tank SCC and 2,056,992 individual bulk tank TBC records from 9,113 herds. Somatic cell counts decreased during the years 1994 to 2000, followed by an annual increase thereafter of more than 2,000 cells/mL. A tendency existed for TBC to decrease over time. Across all years, bulk tank SCC were the lowest in April and highest in November; TBC were the lowest in May and highest in December. The significant seasonal pattern observed in herd SCC and TBC was an artifact of seasonal calving in Ireland. In general, herds selling more milk had lower bulk tank SCC and TBC. Herds having the highest SCC (i.e., >450,000 cells/mL) and the lowest SCC (i.e., ≤150,000 cells/mL) both contributed substantially to the mean SCC of the milk pool collected by the milk processors. Derived transition matrices showed that between adjacent years, herds had the greatest probability of remaining in the same annual mean SCC or TBC category.