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.

Bulk tank somatic cell counts analyzed by statistical process control tools to identify and monitor subclinical mastitis incidence.

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.

Characterizing biosecurity, health, and culling during dairy herd expansions.

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.

Risk factors for twinning in dairy cows.

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.

Factors affecting reproductive performance in Ontario dairy herds.

Data were collected on reproductive, health and production events in 45 dairy herds in southwestern and eastern Ontario, Canada, from July 1990 to July 1993. Mean and median days in milk at first estrus, at first service, and at conception were 85.1 and 83.9, 94.0 and 88.9, and 126.3 and 115.5 d, respectively. The mean estrus detection rate was 48.3%, with a minimum of 28.4% and a maximum of 64.2%. The mean overall conception rate was 46.7%, with a minimum of 29.8% and a maximum of 70.7%. The most commonly used used therapeutic agents were GnRH (11.5% lactational incidence risk) and PG (13.1% lactational incidence risk). Estrus management accounted for the largest portion of PG use in the herds studied (69.4%). Results of a two sample t-test indicated no significant difference in reproductive performance among herds housed in free-stall compared with those housed in tie-stall barns. Multivariate linear regression models of 3 reproductive performance measures indicated that cows with ovarian cysts and/or increased peak milk production had significantly longer calving-to-first estrus and calving-to-conception intervals as well as lower conception rates than average producing cows without cysts. Cows with metritis were found to have significantly shorter calving-to-conception intervals but no detectable difference in conception rate or calving-to-first estrus interval than their herdmates. As lactation number increased reproductive performance improved. Cows that were observed in estrus earlier conceived earlier. Animals receiving uterine infusions had significantly longer calving-to-conception intervals and lower conception rates than their herdmates. There was no detectable difference in reproductive performance for cows treated with GnRH or PG compared with the nontreated cows. An increased estrus detection rate was associated with shorter calving-to-conception intervals and lower conception rates. Based on the range of performance in the study herds, the factors with the greatest potential influence on calving-to-conception interval in the average herd were the estrus detection rate and conception rate.

Vitreous humor analysis for selected biochemical parameters from cervids in Idaho.

Vitreous humor and liver samples were collected from hunter-harvested elk (Cervus elaphus) and mule deer (Odocoileus hemionus) 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 < or = 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.

Relationship of production to reproductive performance in Ontario dairy cows: herd level and individual animal descriptive statistics.

Data were collected on reproductive, health and production events in 45 dairy herds distributed throughout southwestern and eastern Ontario. The data were collected between July 1990 and July 1993. The herds were serviced by 11 different veterinary practices. Herd size ranged from 19 to 231 lactating cows, but 90% of the herds consisted of fewer than 125 milking cows. Mean and median actual milk yields per cow per day were 46.0 and 52.3 lbs, respectively, with a minimum of 21.3 and maximum of 67.8 lbs. Mean and medium adjusted corrected milk yields were 56.0 and 62.3 lbs, reflecting mean and median average days in milk of 199.0 and 198.5 d, respectively. Mean and median days in milk at the first estrus were 85.1 and 83.9 d, respectively, at first service 94.0 and 88.9 d, and at conception 126.3 and 115.5 d. Mean and median percentages of days open > 120 were 27.7 and 23.1%, respectively. The mean estrus detection rate was 48.3%, with a minimum of 28.4% and a maximum of 64.2%. The mean first service conception rate was 48.2%, with a minimum of 27.0% and maximum of 72.1%. The mean overall conception rate was 46.7%, with a minimum of 29.8% and a maximum of 70.7%. Mean and median lactation lengths were 341.1 and 338.5 d and the mean and median average dry days were 62.0 and 67.0, respectively. The mean lactational removal rate was 20.6%, with a range of 4.3 to 40.5%. Reasons for culling were available for 1381 cows. Low production accounted for 23.7 % of the cullings; reproductive reasons, 20.6 %; dairy sales, 13.4%; mammary problems, 12.8%; and lameness, 9.9%. Lactational incidence rates for diseases were lower than previously reported for Ontario dairy herds. The most commonly used therapeutic agents were GnRH (10.5%) and PGF (11.7%).

Evaluation of the benefits of the timing of pregnancy testing by transrectal palpation in dairy cattle.

OBJECTIVE: To determine the benefits that were associated with pregnancy testing by use of transrectal palpation during the period 30 to 65 days after unsuccessful insemination of dairy cows. DESIGN: Nonconcurrent, cohort study. ANIMALS: Cows in 15 dairy herds in the United States and Canada. PROCEDURE: Reproductive records of cows (n = 713) that did not calve within 294 days of first-service insemination and that had been evaluated for pregnancy 30 to 65 days after first-service insemination were examined. Records were analyzed to determine the day of parturition or date of culling and to determine if the probability of a cow being culled or the interval to parturition was related to the number of days after insemination that pregnancy testing was performed. RESULTS: For cows that calved more than 294 days after first-service insemination, the interval from first-service insemination until parturition was associated significantly with herd, season, and treatment on the day of pregnancy testing with prostaglandin F2 alpha or one of its analogues. Cows treated with prostaglandin F2 alpha on the day of pregnancy testing were less likely to be culled than nontreated cows. For cows pregnancy tested 30 to 65 days after insemination, each additional day after day 30 before pregnancy testing was performed resulted in an increase of 1.09 days in the interval until parturition. CLINICAL IMPLICATIONS: Pregnancy testing by means of transrectal palpation as soon as possible after day 30 after insemination can result in shorter calving intervals.

Options in dairy data management.

A great deal of progress has been made in the development of dairy herd management software in the last few years. At the same time, the speed, capacity, and portability of computer hardware have increased, while costs have decreased, thus encouraging use by veterinarians,dairy herd managers, and other industry support groups. A review of the literature indicates that an increasing number of producers, veterinarians, and other dairy industry service personnel are using computers and dairy herd management software in the delivery of their services (1-3,5,9-11,26-30,38,39). Wider adoption will occur if information generated through the use of these systems is directed towards the improvement of the profitability of dairy production. The quality of a decision is only as good as the information used to make it. In the past, the limited availability of reliable herd data has restricted our understanding of factors that influence herd performance. In essence, we must define what is normal before we can determine what is abnormal. More importantly, we must define what management practices are profitable and to what extent they increase revenue (3 1,32). Improved record keeping will benefit the dairy industry by allowing producers and dairy consultants to make profitable decisions based on more accurate and complete information. The ability to merge biological, management,and economic data may prove valuable in the evaluation of intervention at the herd and individual animal level. The impact of interventions is often as much a function of the unique combination of management factors on a dairy, as the biological effect that can be evaluated in a clinical trial. For example, the use of gonadotrophin-releasing hormone therapy at the time of service has been shown to be more successful in herds with better than average conception rates than in herds with poor conception rates. This difference in efficacy may be due to nutritional and other herd level management factors. Sophisticated dairy information management systems provide valuable herd specific management information, which allows more comprehensive understanding of the complex interaction of pharmaceutical,biological, and management factors that ultimately determine the profitability of veterinary intervention strategies. The use of electronic transfer of data will become essential in order to increase efficiency of use of information through data sharing. This will decrease transfer time and cost of information exchange between dairy herd managers and support industries.

Pregnancy attrition associated with pregnancy testing by rectal palpation.

The objective of this study was to estimate the effect on calving risk of interval from AI date until scheduled date of pregnancy examination. First AI (n = 7105) from 65 dairy herds in the United States and Canada were followed for 294 d to determine whether cows calved. Calving was modeled as a function of the number of days in the interval, herd, season, and breeding at PGF2 alpha-induced estrus by multivariate logistic regression. The main effects of herd and AI following PGF2 alpha-induced estrus were significantly associated with calving rate from first AI. The main effects of interval and season were not significantly associated with calving.

The prevalence of Escherichia coli O157.H7 in dairy and beef cattle in Washington State.

Escherichia coli O157.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 O157.H7. E. coli O157.H7 was also isolated from 10 of 1412 (0.71%) faecal samples from pastured beef cattle in 4 of 25 (16%) herds. The prevalence of E. coli O157.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 O157.H7 suggests the possibility that human E. coli O157.H7 exposure may be reduced by cattle management procedures.

Investigating perinatal calf mortality in beef herds.

This article summarizes the information presented in this issue to identify the reasons for a perinatal calf mortality (PCM) problem through a risk-factor-evaluation approach. The benefits of necropsies in PCM investigations are discussed, and the gross lesions of the major causes of PCM are described. The use of 2 x 2 tables to calculate odds ratios and the Chi-square method to test the validity of the odds ratios are presented as methods to determine suspected risk factors. The article concludes with a discussion of the management plan used to solve a PCM problem.