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 +/- 1,138 kg 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 > or = 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.

The single most important factor affecting somatic cell count in milk is mammary gland infection status. In comparison, all other factors are minor. Consideration needs to be given to diurnal effects on Dairy Herd Improvement a.m.-p.m. sampling schemes. Somatic cell count linear score of 5 (283,000) appears to be a good choice of threshold for mastitis control applications. A greater understanding of the nonbacteriological factors affecting somatic cell count is needed so that relative thresholds could be used to improve the clarity of somatic cell count interpretation. Linear score loss estimates are effective educational tools providing motivation for mastitis control implementation. Infection status or milk loss estimates based on single somatic cell count tests on individual cows are weak. A lactational average linear score on individual cows or linear score compilations across a herd provide credible estimates. Treatment of subclinical mastitis based on somatic cell count levels is not economically beneficial and is not recommended. Usefulness of Dairy Herd Improvement somatic cell count data as a mastitis management tool requires measures of mastitis level, new infection rate, and mastitis pattern within the herd over time.

Results suggest that the hygiene scoring system was repeatable, accurate, and easy to use. However, only hygiene scores for the udder and hind limbs and the udder-hind limb composite score were significantly associated with SCS.

This study evaluates the changes in milk production (yield; MY) and milk electrical conductivity (MEC) before and after disease diagnosis and proposes a cow health monitoring scheme based on observing individual daily MY and MEC. All reproductive and health events were recorded on occurrence, and MY and MEC were collected at each milking from January 2004 through November 2006 for 587 cows. The first 24 mo (January 2004 until December 2005) were used to investigate the effects of disease on MY and MEC, model MY and MEC of healthy animals, and develop a health monitoring scheme to detect disease based on changes in a cow's MY or MEC. The remaining 11 mo of data (January to November 2006) were used to compare the performance of the health monitoring schemes developed in this study to the disease detection system currently used on the farm. Mixed model was used to examine the effect of diseases on MY and MEC. Days in milk (DIM), DIM x DIM, and ambient temperature were entered as quantitative variables and number of calves, parity, calving difficulty, day relative to breeding, day of somatotropin treatment, and 25 health event categories were entered as categorical variables. Significant changes in MY and MEC were observed as early as 10 and 9 d before diagnosis. Greatest cumulative effect on MY over the 59-d evaluation period was estimated for miscellaneous digestive disorders (mainly diarrhea) and udder scald, at -304.42 and -304.17 kg, respectively. The greatest average daily effect was estimated for milk fever with a 10.36-kg decrease in MY and 8.3% increase in MEC. Milk yield and MEC was modeled by an autoregressive model using a subset of healthy cow records. Six different self-starting cumulative sum and Shewhart charting schemes were designed using 3 different specificities (98, 99, and 99.5%) and based on MY alone or MY and MEC. Monitoring schemes developed in this study issue alerts earlier relative to the day of diagnosis of udder, reproductive, or metabolic problems, are more sensitive, and give fewer false-positive alerts than the disease detection system currently used on the farm.

This study investigates whether dry matter (DM) or water intake is affected by the presence of disease or estrus in dairy cows and whether water intake can serve as an accurate substitute for monitoring changes in DM intake (DMI). A combined cumulative sum (CUSUM) and Shewhart monitoring scheme is proposed to detect DMI changes and emerging disease or estrus. Daily readings from 35 inline water meters for 35 water cups in a tie-stall barn at the University of Minnesota were collected from September 2005 until June 2006. Two cows were assigned to each water cup. Individual DMI were recorded for each of the 70 cows on the study. All drug or hoof treatments administered to the cows along with breeding and calving events were also recorded and classified as 1 of the following 6 event categories: estrus, calving, mastitis, fever, hoof treatment, and other. Analysis of covariance was used to identify factors significantly changing intake. Only the first 150 d in milk (DIM) were considered in the analysis. Six event categories plus DIM, ambient temperature, relative humidity, and parity were entered as independents into the model. Calving, primiparity, and health events categorized as "other" were associated with decreased DM and water intake. Mastitis decreased DMI and fever negatively affected water intake. Both intakes increased with DIM, and water intake decreased with increase in humidity. Covariance analysis was used to investigate the relationship between DMI and water intake. In model 1, analysis was done for a pair of cows, whereas model 2 modeled DMI of the whole group of 70 cows. Water intake, ambient temperature, humidity, and DIM were entered as independents in both models and parity was entered in model 1. Polynomial models and 2-way interactions were also considered. Water intake, ambient temperature, DIM, and DIM(2) were kept in final models 1 and 2, and parity was kept in model 1. Final models for cow pairs and a group of 70 cows resulted in R(2) of 0.50 and 0.82, respectively. The proposed CUSUM-Shewhart DMI monitoring scheme successfully detected emerging disease even in the first week of lactation. Monitoring water intake can serve as an alternative to measurements of DMI for groups of cows and has the potential of predicting change in individual cow health and estrus status.