SUMMARYEscherichia coli 0157. H7 was found in 10 of 3570 (0 28 %) faecal samples from dairy cattle in 5 of 60 herds (8-3%). Several tentative associations with manure handling and feeding management practices on dairy farms were identified. Faecal/urine slurry samples, bulk milk samples, and milk filters from dairy herds were negative for E. coli 0157. H7. E. coli 0157. H7 was also isolated from 10 of 1412 (0-71 %) faecal samples from pastured beef cattle in 4 of 25 (16%) herds. The prevalence ofE. coli 0157. H7 excretion in feedlot beef cattle was 2 of 600 (0 33 %). The identification of cattle management practices associated with colonization of cattle by E. coli 0157. H7 suggests the possibility that human E. coli 0157. H7 exposure may be reduced by cattle management procedures.

Records for 52,362 lactations over a 10-yr period from 260 dairy farms in North America that used a common commercial software for record keeping were evaluated for potential risk factors for twinning. Records were evaluated for the associations of reproductive disease, parity, production, drug therapy, and the occurrence of subsequent twins. The rate of twinning on these farms steadily increased over the observation period from 1.4% in 1983 to 2.4% in 1993. The rate of twinning also increased as parity of the cow increased, from 1.0% for cows in their first lactation to > 4.1% for cows in their fifth or higher lactation. No association between twinning and season of year was detected. A multivariate logistical regression analysis found that the rate of twinning increased with increases in milk production, incidence of cystic ovarian disease, and the use of common pharmaceuticals, including GnRH, PGF2 alpha, and antibiotics. Results of the regression model also indicated that the single most important reason for the recent increase in the rate of twinning was a concurrent increase in milk production.

The global dairy industry is composed of a multitude of countries with unique production practices and consumer markets. The global average number of cows per farm is about 1-2 cows; however, as a farm business model transitions from sustenance to market production, the average herd size, and subsequent labor force increases. Dairy production is unique as an agricultural commodity because milk is produced daily, for 365 days per year. With the introduction of new technology such as the milking parlor, the global industry trend is one of increasing farm sizes. The farm sizes are the largest in the United States; however, the European Union produces the most milk compared with other global producers. Dairy production is essential for economic development and sustainable communities in rural areas. However, the required capital investment and availability of local markets and labor are continued challenges. Due to farm expansion, international producers are faced with new challenges related to assuring food safety and a safe working environment for their workforce. These challenges exist in addition to the cultural and language barriers related to an increasing dependence on immigrant labor in many regions of the world. Continued success of the global dairy industry is vital. Therefore, research should continue to address the identification of occupational risk factors associated with injuries and illnesses, as well as develop cost-effective interventions and practices that lead to the minimization or elimination of these injuries and illnesses on a global scale, among our valuable population of dairy producers and workers.

Our objectives were to investigate strategies for biosecurity, expansion, and culling for expanding dairy herds in the Upper Midwest. Eighteen dairies in Iowa and Wisconsin were visited, and dairy managers and veterinarians were interviewed to characterize five biosecurity practices, herd culling practices, vaccines administered, and ensuing disease status for the herds. The majority of herds that were interviewed failed to employ comprehensive biosecurity programs for incoming cattle. Nearly 60% of herds obtained cattle from sources for which it was difficult to document genetic backgrounds and health histories, fewer than half required health testing for incoming cattle, and approximately 50% quarantined new cattle on arrival. Despite high rates of vaccination for bovine viral diarrhea, all herd owners and managers indicated that herd biosecurity was compromised as a result of expansion. Half of the interviewed herds indicated that bovine viral diarrhea and papillomatous digital dermatitis were notable disease problems. Herds that obtained cattle with unknown backgrounds and health status experienced the largest number of diseases. Before expansion, the most frequently cited reasons for culling were reproductively unsound; low milk production; mastitis, poor udder health, and high SCC; during expansion, the strategic decision to cull cows for low milk production was used less often. In addition, the stochastic simulation model, DairyORACLE, was used to evaluate economic outcomes for several expansion alternatives. Five model scenarios studied were: base scenario (herd size was maintained) and four expansion scenarios--all paired combinations of heifer quality (high, low) and voluntary culling (implemented, not implemented). Culling for low milk production yielded an additional $23.29 annually (6-yr annuity) per cow, but on the basis of purchased replacements, no voluntary culling was most profitable. Purchasing high versus low quality replacement heifers for expansions returned an additional $113.54 annually ($681.24 total net present value) per heifer purchased. Many opportunities exist to improve cattle-related factors for dairy herd expansions, including the use of comprehensive biosecurity programs, realistic planning and budgeting for cattle purchases, and cost effective purchase and culling practices.

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The objective of this study was to examine the relationship between monthly Dairy Herd Improvement (DHI) subclinical mastitis and new infection rate estimates and daily bulk tank somatic cell count (SCC) summarized by statistical process control tools. Dairy Herd Improvement Association test-day subclinical mastitis and new infection rate estimates along with daily or every other day bulk tank SCC data were collected for 12 mo of 2003 from 275 Upper Midwest dairy herds. Herds were divided into 5 herd production categories. A linear score [LNS = ln(BTSCC/100,000)/0.693147 + 3] was calculated for each individual bulk tank SCC. For both the raw SCC and the transformed data, the mean and sigma were calculated using the statistical quality control individual measurement and moving range chart procedure of Statistical Analysis System. One hundred eighty-three herds of the 275 herds from the study data set were then randomly selected and the raw (method 1) and transformed (method 2) bulk tank SCC mean and sigma were used to develop models for predicting subclinical mastitis and new infection rate estimates. Herd production category was also included in all models as 5 dummy variables. Models were validated by calculating estimates of subclinical mastitis and new infection rates for the remaining 92 herds and plotting them against observed values of each of the dependents. Only herd production category and bulk tank SCC mean were significant and remained in the final models. High R2 values (0.83 and 0.81 for methods 1 and 2, respectively) indicated a strong correlation between the bulk tank SCC and herd's subclinical mastitis prevalence. The standard errors of the estimate were 4.02 and 4.28% for methods 1 and 2, respectively, and decreased with increasing herd production. As a case study, Shewhart Individual Measurement Charts were plotted from the bulk tank SCC to identify shifts in mastitis incidence. Four of 5 charts examined signaled a change in bulk tank SCC before the DHI test day identified the change in subclinical mastitis prevalence. It can be concluded that applying statistical process control tools to daily bulk tank SCC can be used to estimate subclinical mastitis prevalence in the herd and observe for change in the subclinical mastitis status. Single DHI test day estimates of new infection rate were insufficient to accurately describe its dynamics.

Vitreous humor and liver samples were collected from hunter-harvested elk (Cervus elaphus) and mule deer (Odocoilens hernionus) in Idaho (USA). Concentrations of calcium, chloride, potassium, sodium, urea nitrogen and selenium were determined and evaluated according to species, age, gender, geographic location, and time elapsed following death. Vitreous humor analysis yielded reliable biochemical information for 96 hr subsequent to the death of the animal. Vitreous potassium concentration changes over time could be used to estimate the time that elapsed following death.

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.