Effect of enhanced hygiene on transmission of Staphylococcus aureus, Streptococcus agalactiae, and Streptococcus dysgalactiae in dairy herds with automatic milking systems.

The objective of the study was to evaluate the effect of hygiene measures in automatic milking units on the transmission of 3 mastitis pathogens considered to be mainly or partly transmitted from cow to cow during milking events. Two studies were conducted as within-herd experimental trials in 2 Danish commercial dairy herds (A and B) with automatic milking systems. Interventions to enhance hygiene were implemented on the automatic milking units. The 2 studies evaluated separate interventions. In herd A, the hygiene interventions were manual wash with the Lely foam unit and adjustments on the brush-mediated teat cleaning procedure. In herd B, the hygiene intervention included automatic disinfection spray on the upper surface of the brush motor and daily change of brushes. Composite milk samples were collected longitudinally at 3- or 4-wk intervals from all lactating cows. Additional milk samples were taken from cows entering or leaving the study groups. Milk samples were analyzed with quantitative PCR. A hidden Markov model implemented within a Bayesian framework was used to estimate the transmission probability. For analysis, 701 samples from 156 cows were used for herd A, and 1,349 samples from 390 cows were used for herd B. In the intervention group in herd B, transmission of Streptococcus agalactiae was reduced to 19% (95% posterior credibility interval: 0.00-64%) of the transmission in the control group, whereas transmission of Streptococcus dysgalactiae was reduced to 17% (95% posterior credibility interval: 0.00-85%) of transmission in the control group. This suggests that automatic spray on the upper surface of the brush motor with disinfectant along with daily change of brushes collectively reduced transmission of Strep. agalactiae and Strep. dysgalactiae. Results on Staphylococcus aureus in herd B and results on manual foam cleaning and brush-mediated teat cleaning adjustments in herd A were inconclusive.

Monitoring individual cow udder health in automated milking systems using online somatic cell counts.

This study presents and validates a detection and monitoring model for mastitis based on automated frequent sampling of online cell count (OCC). Initially, data were filtered and adjusted for sensor drift and skewed distribution using ln-transformation. Acceptable data were passed on to a time-series model using double exponential smoothing to estimate level and trends at cow level. The OCC levels and trends were converted to a continuous (0-1) scale, termed elevated mastitis risk (EMR), where values close to zero indicate healthy cow status and values close to 1 indicate high risk of mastitis. Finally, a feedback loop was included to dynamically request a time to next sample, based on latest EMR values or errors in the raw data stream. The estimated EMR values were used to issue 2 types of alerts, new and (on-going) intramammary infection (IMI) alerts. The new alerts were issued when the EMR values exceeded a threshold, and the IMI alerts were issued for subsequent alerts. New alerts were only issued after the EMR had been below the threshold for at least 8d. The detection model was evaluated using time-window analysis and commercial herd data (6 herds, 595,927 milkings) at different sampling intensities. Recorded treatments of mastitis were used as gold standard. Significantly higher EMR values were detected in treated than in contemporary untreated cows. The proportion of detected mastitis cases using new alerts was between 28.0 and 43.1% and highest for a fixed sampling scheme aiming at 24h between measurements. This was higher for IMI alerts, between 54.6 and 89.0%, and highest when all available measurements were used. The lowest false alert rate of 6.5 per 1,000 milkings was observed when all measurements were used. The results showed that a dynamic sampling scheme with a default value of 24h between measurements gave only a small reduction in proportion of detected mastitis treatments and remained at 88.5%. It was concluded that filtering of raw data combined with a time-series model was effective in detecting and monitoring mastitis status in dairy cows when based on IMI alerts, and by using a dynamically adjusting sampling scheme almost full performance was still obtainable. However, results were less desirable when based on new alerts most likely because of the used gold standard for mastitis, which may not necessarily reflect the onset of and IMI case in contrast to a new alert.

Effects of combined liver and udder biopsying on the acute phase response of dairy cows with experimentally induced E. coli mastitis.

A minimally invasive biopsy technique was evaluated for udder tissue collection in dairy cows with Escherichia coli mastitis. Meanwhile, the effect of taking repeated liver and udder biopsies on the systemic and local acute phase response (APR) of the dairy cows was investigated during the disease. The cows were divided into a biopsy group (B) (n = 16) and a no-biopsy group (NB) (n = 16) and were sampled in the acute disease stage and in the recovery stage. The cows' pre-disease period served as a control period for establishing baseline values for the investigated parameters. A total of 32 Holstein-Friesian cows were inoculated with 20 to 40 colony-forming units (cfu) of E. coli in one front quarter at 0 hour. Liver biopsies were collected at -144, 12, 24 and 192 h, and udder biopsies were collected at 24 and 192 h post E. coli inoculation (PI) using a minimally invasive biopsy technique. Effects of combined biopsying were investigated by recording production traits, clinical response, and measuring inflammatory milk and blood parameters: E. coli, somatic cell count, milk amyloid A (MAA) levels, white blood cell count, polymorphonuclear neutrophilic leukocyte numbers and serum amyloid A levels at several time points. E. coli inoculation changed all production parameters and the clinical and inflammatory response in all cows except one that was not infected. Combined biopsying had no constant or transient effect on the daily feed intake, the clinical responsiveness or the blood parameters, but affected the daily milk yield and some milk parameters transiently, that is, the presence of blood in milk, increased E. coli counts and MAA levels during the acute disease stage. Combined biopsying had no effect on the parameters in the recovery stage apart from the presence of blood in the milk. In conclusion, although, a minimally invasive biopsy technique was used, tissue damages could not be avoided when biopsying and they transiently affected the inflammatory parameters in the mammary gland. Nevertheless, we believe combined biopsying of liver and udder is as an acceptable approach to study the systemic and local APR in dairy cows during E. coli mastitis, if the timing of biopsying and other types of sampling is planned accordingly.

Effects of Bos taurus autosome 9-located quantitative trait loci haplotypes on the disease phenotypes of dairy cows with experimentally induced Escherichia coli mastitis.

Several quantitative trait loci (QTL) affecting mastitis incidence and mastitis-related traits such as somatic cell score exist in dairy cows. Previously, QTL haplotypes associated with susceptibility to Escherichia coli mastitis in Nordic Holstein-Friesian (HF) cows were identified on Bos taurus autosome 9. In the present study, we induced experimental E. coli mastitis in Danish HF cows to investigate the effect of 2 E. coli mastitis-associated QTL haplotypes on the cows' disease phenotypes and recovery in early lactation. Thirty-two cows were divided in 2 groups bearing haplotypes with either low (HL) or high (HH) susceptibility to E. coli. In addition, biopsies (liver and udder) were collected from half of the cows (n=16), resulting in a 2 × 2 factorial design, with haplotype being one factor (HL vs. HH) and biopsy being the other factor (biopsies vs. no biopsies). Each cow was inoculated with a low E. coli dose (20 to 40 cfu) in one front quarter at time 0 h. Liver biopsies were collected at -144, 12, 24, and 192 h; udder biopsies were collected at 24h and 192 h post-E. coli inoculation. The clinical parameters: feed intake, milk yield, body temperature, heart rate, respiration rate, rumen motility; and the paraclinical parameters: bacterial counts, somatic cell count (SCC), and milk amyloid A levels in milk; and white blood cell count, polymorphonuclear neutrophilic leukocyte (PMNL) count, and serum amyloid A levels in blood were recorded at different time points post-E. coli inoculation. Escherichia coli inoculation changed the clinical and paraclinical parameters in all cows except one that was not infected. Clinically, the HH group tended to have higher body temperature and heart rate than the HL group did. Paraclinically, the HL group had faster PMNL recruitment and SCC recovery than the HH group did. However, we also found interactions between the effects of haplotype and biopsy for body temperature, heart rate, and PMNL. In conclusion, when challenged with E. coli mastitis, HF cows with the specific Bos taurus autosome 9-located QTL haplotypes were associated with differences in leukocyte kinetics, with low-susceptibility cows having faster blood PMNL recruitment and SCC recovery and a tendency for a milder clinical response than the high-susceptibility cows did.

Enzyme activity and acute phase proteins in milk utilized as indicators of acute clinical E. coli LPS-induced mastitis.

The importance of non-visual and on-line monitoring of udder health increases as the contact between humans and animals decreases, for example, in robotic milking systems. Several indicator systems have been introduced commercially, and a number of techniques are currently in use. This study describes the kinetics of seven indigenous milk parameters for monitoring udder inflammation in an Escherichia coli lipopolysaccharide (LPS, endotoxin)-induced mastitis model. Proportional milk from LPS-infused quarters was compared with milk from parallel quarters, which were placebo-treated with sterile 0.9% NaCl solution. Somatic cell counts (SCCs), the acute phase proteins (APP), that is, milk amyloid A (MAA) and haptoglobin (Hp), and the enzymes N-acetyl-ß-D-glucosaminidase (NAGase), lactate dehydrogenase (LDH), alkaline phosphatase (AP) and acid phosphatase (AcP) were measured at fixed intervals during the period from -2 to +5 days after LPS and NaCl infusions. All parameters responded significantly faster and were more pronounced to the LPS infusions compared with the NaCl infusions. All parameters were elevated in the proportional milk collected at the first milking 7 h after infusion and developed a monophasic response, except Hp and MAA that developed biphasic response. SCC, LDH, NAGase and Hp peaked at 21 h followed by AP, AcP and MAA peaking at 31 h with the highest fold changes seen for MAA (23 780×), LDH (126×), NAGase (50×) and Hp (16×). In the recovery phase, AP, AcP and Hp reached base levels first, at 117 h, whereas LDH, NAGase and MAA remained elevated following the pattern of SCC. Minor increases of the milk parameters were also seen in the neighboring (healthy) quarters. Distinction between inflamed and healthy quarters was possible for all the parameters, but only for a limited time frame for AP and AcP. Hence, when tested in an LPS mastitis model, the enzymes LDH, NAGase and AP in several aspects performed equally with SCC and APP as inflammatory milk indicators of mastitis. Furthermore, these enzymes appear potent in the assessment of a valuable time sequence of inflammation, a necessary ingredient in modeling of programs in in-line surveillance systems.

Cytokine and acute phase protein gene expression in repeated liver biopsies of dairy cows with a lipopolysaccharide-induced mastitis.

A minimally invasive liver biopsy technique was tested for its applicability to study the hepatic acute phase response (APR) in dairy cows with Escherichia coli lipopolysaccharide (LPS)-induced mastitis. The hepatic mRNA expression profiles of the inflammatory cytokines, tumor necrosis factor alpha (TNF-alpha), IL-1beta, IL-6, and IL-10, and the acute phase proteins serum amyloid A isoform 3 (SAA3), haptoglobin (Hp), and alpha(1)-acid glycoprotein (AGP) were determined by real-time reverse transcription-PCR. Fourteen primiparous cows in mid lactation were challenged with 200 microg of LPS (n = 8) or NaCl solution (n = 6) in 1 front quarter. Six repeated liver biopsies were collected at -22, 3, 6, 9, 12, and 48 h relative to LPS challenge in 4 LPS-infused cows and 3 NaCl-infused cows. The remaining cows had 3 liver biopsies taken at -22, 9, and 48 h. Production data and clinical signs were recorded and white blood cell counts and somatic cell counts (SCC) were analyzed to investigate the effect of repeated liver biopsies and verify the LPS model. Plasma concentrations of TNF-alpha, SAA3, Hp, and AGP were determined for comparison with the liver expression data. Repeated liver biopsies had no effects on the production data, clinical signs, or APR of dairy cows. Compared with the NaCl-infused cows the LPS-infused cows responded to the LPS treatment by increased body temperature (38.6 +/- 0.1 vs. 39.4 +/- 0.1 degrees C), short-term leukopenia followed by leukocytosis (6.44 +/- 0.4 vs. 5.69 +/- 0.3 x 10(6) cells/mL), an increased SCC (log(10) 2.1 +/- 0.1 vs. log(10) 2.8 +/- 0.1 x 10(3) cells/mL), heart rate (76 +/- 1 vs. 93 +/- 1 beats/min), and respiratory rate (32 +/- 2 vs. 36 +/- 1 breaths/min) in the acute phase of the disease. The LPS treatment upregulated the hepatic expression of TNF-alpha (103 +/- 24 vs. 255 +/- 18 units), IL-1beta (37 +/- 23 vs. 296 +/- 18 units), IL-6 (8 +/- 17 vs. 122 +/- 12 units), and IL-10 (130 +/- 66 vs. 541 +/- 50 units), and SAA3 (64 +/- 36 vs. 128 +/- 28 units) and Hp (9 +/- 82 vs. 762 +/- 65 units) reaching maximum levels at 3 to 6 h and 9 to 12 h postinfusion, respectively. Plasma concentrations of TNF-alpha (nondetectable vs. 1.9 +/- 0.3 ng/mL), SAA (19.8 +/- 19.4 vs. 149.7 +/- 15.5 microg/mL) and Hp (71.4 +/- 143.7 vs. 1,013.8 +/- 111.5 microg/mL) were elevated in the LPS-infused cows at 4 to 12 h, 8 to 120 h, and 24 to 120 h postinfusion, respectively. The hepatic expression of AGP and the AGP plasma concentration remained unaltered in LPS-induced cows. In conclusion, a minimally invasive liver biopsy technique can be used for studying the hepatic APR in diseased cattle. Lipopolysaccharide-induced mastitis resulted in a time-dependent production of inflammatory cytokines and SAA and Hp in the liver of dairy cows.

Improved detection of reproductive status in dairy cows using milk progesterone measurements.

This study tested a model for predicting reproductive status from in-line milk progesterone ;measurements. The model is that of Friggens and Chagunda [Theriogenology 64 (2005) 155]. Milk progesterone measurements (n = 55 036) representing 578 lactations from 380 cows were used to test the model. Two types of known oestrus were identified: (1) confirmed oestrus (at which insemination resulted in a confirmed pregnancy, n = 121) and (2) ratified oestrus (where the shape of the progesterone profile matched that of the average progesterone profile of a confirmed oestrus, n = 679). The model detected 99.2% of the confirmed oestruses. This included a number of cases (n = 16) where the smoothed progesterone did not decrease below 4 ng/ml. These cows had significantly greater concentrations of progesterone, both minimum and average, suggesting that between cow variation exists in the absolute level of the progesterone profile. Using ratified oestruses, model sensitivity was 93.3% and specificity was 93.7% for detection of oestrus. Examination of false positives showed that they were largely associated with low concentrations of progesterone, fluctuating around the 4 ng/ml threshold. The distribution of time from insemination until the model detected pregnancy failure had a median of 22 days post-insemination. In this test, the model was run using limited inputs, the potential benefits of including additional non-progesterone information were not evaluated. Despite this, the model performed at least as well as other oestrus detection systems.

Estimating degree of mastitis from time-series measurements in milk: a test of a model based on lactate dehydrogenase measurements.

The aim of this study was to test a model for mastitis detection using a logic that allows examination of time-related changes and a progressive scale of mastitis state (i.e., not using specificity/sensitivity). The model produces a mastitis risk (MR) for individual cows on a scale from 0 (completely healthy) to 1 (full-blown mastitis). The main model input was lactate dehydrogenase (LDH; mumol/min per L) x milk yield. Test data containing 253 mastitis cases were used. Proportional samples were collected from each cow at each milking and analyzed for LDH and somatic cell count (SCC). The basis for the health definitions was veterinary treatment records. A refinement of the basic health definitions was made using systematic positive deviations in log(SCC) to indicate untreated infections. Two subsets of cows were identified: mastitic cows and cows completely free of mastitis (healthy controls). The time-profiles of these 2 groups in a 60-d window relative to day of veterinary treatment were examined. Model reliability throughout all stages of lactation and degrees of infection was examined using SCC as a continuous measure of degree of mastitis. The time-profile for the health controls was flat throughout the 60-d window with a median MR of 0.02. In contrast, the profile of the mastitic cows increased above the control cows' baseline from about -6 d, rising to a MR value of 0.20 at d 0, and declining to the control level after treatment. There were significant differences between mastitic and healthy cows from -4 to +2 d relative to veterinary treatment. When cases were time-aligned to peak of infection, rather than veterinary treatment, there was a much sharper peak to the time-profile of mastitic cows. The median MR at peak was 0.62 and the mean was 0.80. Using these data, the MR value of 0.62 had a <1% likelihood of actually coming from a healthy control. Testing against SCC, on the whole data set, showed that only 2.1% of all MR values had an error >0.7. These estimates of model reliability are comparable with the greatest values reported in the literature and, additionally, the model was able to detect significant differences between mastitic and healthy cows 4 d before treatment. It was also found that specificity/sensitivity calculations are inappropriate for evaluating time-related changes and a progressive scale of predicted mastitis state.

Influence of air intake on the concentration of free fatty acids and vacuum fluctuations during automatic milking.

The main objective of the study was to determine whether the amount of air intake during quarter milking influences the concentration of free fatty acids (FFA) and vacuum fluctuations at the teat end when milking automatically. Air intake in the teat cup was restricted from the normal inlet of 4.5 to 7 L/min to 1.7 and 0 L/min on 2 farms and experiments were carried out as half-udder studies with 40 cows. Blockage of the air inlet reduced FFA from 1.02 to 0.77 mEq/100 g of fat in one herd and from 1.50 to 1.17 mEq/100 g of fat in the other herd. Milk yield per milking was the most significant factor influencing FFA. Air intake accounted for <20% of the variation in FFA concentration. Characteristics of the cow explained the most variation, which could mainly be assigned to the effects of milk yield, fat percentage, fat globule size, and fat globule size distribution. The interval between milkings was not significant when adjusting for milk yields. Blockage of the air inlet caused vacuum fluctuations at the teat end to increase from 15.4 to 21.5 kPa for one model of an automatic milking system (AMS), but from 12.8 to 53.6 kPa for another model. Measurements made with a flow simulator and water revealed that the AMS model and water flow were the most important factors influencing vacuum fluctuations, and that interactions existed between the diameter of the short milk tube and air intake. Free fatty acids in bulk milk from 5,980 herds averaged 0.75 mEq/L of milk for conventional herds and varied from 0.77 to 0.94 mEq/L of milk for the 5 AMS models on the Danish market. Fault detection in 55 herds pointed out that the most frequent faults in conventional herds were air leakages and intake of too much air in the cluster, whereas AMS herds had problems with the cooling and stirring of milk. Correction of the cooling faults caused FFA to decrease by 0.52 mEq/L in the AMS herds. We concluded that air intake during automatic milking is not the most important factor in reducing FFA, whereas milk yield per milking matters the most. More attention should be paid to the cooling and stirring of milk. Reducing the air intake causes vacuum fluctuations during milking to increase significantly.

Detection of carryover in automated milk sampling equipment.

Equipment for sampling milk in automated milking systems may cause carryover problems if residues from one sample remain and are mixed with the subsequent sample. The degree of carryover can be estimated statistically by linear regression models. This study applied various regression analyses to several real and simulated data sets. The statistical power for detecting carryover milk improved considerably when information about cow identity was included and a mixed model was applied. Carryover may affect variation between animals, including genetic variation, and thereby have an impact on management decisions and diagnostic tools based on the milk content of somatic cells. An extended procedure is needed for approval of sampling equipment for automated milking with acceptable latitudes of carryover, and this could include the regression approach taken in this study.

Quarter health, milking interval, and sampling time during milking affect the concentration of milk constituents.

Eleven Danish Holstein cows were used to examine the effects of quarter health (healthy vs. unhealthy), milking interval (12 vs. 6 h), and sampling time during milking on the concentration of 8 milk constituents [acetone, beta-hydroxybutyrate (BHBA), N-acetyl-beta-D-glucosaminidase (NAGase), somatic cell count (SCC), urea, fat, protein, and lactose]. The selection criterion was that each cow should have 2 or 3 healthy and 1 or 2 unhealthy quarters. Foremilk was collected before attaching the teat cups of the milking machinery, and thereafter, milk samples were collected automatically from each quarter every 45 s during milking. Compared with milk from healthy quarters, milk from unhealthy quarters had a higher concentration of BHBA, NAGase, SCC, and protein during the entire milking, whereas urea was higher in the last part of the milking process. Healthy quarters had a higher content of acetone and lactose during the whole milking, whereas fat was higher in the first part of the milking process. When the cows were milked at the 6-h interval, all milk constituents except lactose and protein were higher during the whole (NAGase, SCC, and urea) or part of the milking (acetone, BHBA, and fat) compared with when cows were milked at the 12-h interval. Lactose was higher in the first part of the milking at the 12-h compared with the 6-h interval, whereas protein was not affected by milking interval. beta-Hydroxybutyrate, NAGase, SCC, and fat increased during the milking process, whereas acetone, urea, protein, and lactose decreased. Foremilk was remarkably different for all constituents, except acetone, and should not be used as a representative milk sample to achieve the true level of a milk constituent. If these milk constituents are to be used in an inline management system, these effects should be taken into account.

Milk quality on Danish farms with automatic milking systems.

The bulk-milk quality of 98 Danish farms with automatic milking systems was analyzed from 1 yr before introduction of automatic milking until 1 yr after. Bulk-milk total bacterial count, spores of anaerobes, somatic cell count (SCC), and freezing point increased when automatic milking was introduced and the frequency of milk-quality failures almost doubled. Milk-quality failures were most frequent in the first 3 mo after the start of automatic milking. The increase in spores of anaerobes indicated that the increase in total bacterial count originated partly from contamination of milk from the teat surface and partly from lack of cleaning of the milking equipment or cooling of the milk. The increase in bulk-milk SCC indicated that milk from clinically infected cows and cows with high cell counts was not diverted to the same degree, milking automatically rather than milking conventionally. A self-monitoring program including survey of the bulk-milk quality was established to help farmers in the transition period going from conventional to automatic milking. The program was introduced on 84 farms. Farms on the self-monitoring program reduced bulk-milk cell count. Application of the program did not reduce the frequency of high total bacterial counts and freezing points of the bulk milk to the level of conventional milking. However, the program reduced the overall frequency of milk-quality failures.