Total bacterial count and somatic cell count in bulk and individual goat milk around kidding: Two longitudinal observational studies.

Total bacterial count (TBC) and SCC are important quality parameters in goat milk. Exceeding the bulk milk TBC (BMTBC) thresholds leads to price penalties for Dutch dairy goat farmers. Controlling these milk quality parameters can be challenging, especially around kidding. First, we describe the variation and the peaks around kidding of TBC and SCC in census data on Dutch bulk milk over the last 22 yr. Second, to explore causes of these elevations, we studied the variation of TBC and SCC in individual goat milk from 3 wk before to 5 wk after kidding and their association with systemic response markers IFN-γ, calprotectin, BHB, BCS, and fecal consistency. We visited 4 Dutch dairy goat farms weekly for 10 to 16 wk around kidding. Some of the goats had been dried off; other goats were milked continuously throughout pregnancy. A total of 1,886 milk samples from 141 goats were collected for automated flow cytometric quantification of TBC and SCC measurement. IFN-γ, calprotectin, and BHB were determined twice in blood of the same goats; most samples were collected after kidding. The BCS and fecal consistency were scored visually before and after kidding. We found a strong correlation between TBC and SCC (Spearman's rho = 0.87) around kidding. Furthermore, in the third week before kidding, the average TBC (5.67 log10 cfu/mL) and SCC (6.70 log10 cells/mL) were significantly higher compared with the fifth week after kidding, where the average TBC decreased to 4.20 log10 cfu/mL, and the average SCC decreased to 5.92 log10 cells/mL. In multivariable linear regression models, farm and stage of lactation were significantly associated with TBC and SCC, but none of the systemic response markers correlated with TBC or SCC. In conclusion, TBC and SCC in dairy goats were high in late lactation and decreased shortly after parturition. For SCC, the dilution effect might have caused the decrease, but this was not plausible for TBC. Moreover, the excretion of bacteria and cells in goat milk was not associated with the selected systemic response markers that were chosen as a readout for general immunity status, intestinal health, and metabolic diseases. Therefore, we assume that the TBC increase before kidding and the decrease after parturition are caused by other systemic, possibly hormonal, processes. To reduce BMTBC and bulk milk SCC, it would be advisable to keep milk of goats with highest numbers of bacteria and cells in their milk out of the bulk milk during end lactation. Further studies are needed to investigate the effects of withholding this end-lactation milk from the bulk tank.

Dynamic microbial and metabolic changes during Apulian Caciocavallo cheesemaking and ripening produced according to a standardized protocol.

The microbiota of a cheese play a critical role in influencing its sensory and physicochemical properties. In this study, traditional Apulian Caciocavallo cheeses coming from 4 different dairies in the same area and produced following standardized procedures were examined, as well as the different bulk milks and natural whey starter (NWS) cultures used. Moreover, considering the cheese wheels as the blocks of Caciocavallo cheeses as whole, these were characterized at different layers (i.e., core, under-rind, and rind) of the block using a multi-omics approach. In addition to physical-chemical characterization, culturomics, quantitative PCR, metagenomics, and metabolomics analysis were carried out after salting and throughout the ripening time (2 mo) to investigate major shifts in the succession of the microbiota and flavor development. Culture-dependent and 16S rRNA metataxonomics results clearly clustered samples based on microbiota biodiversity related to the production dairy plant as a result of the use of different NWS or the intrinsic conditions of each production site. At the beginning of the ripening, cheeses were dominated by Lactobacillus, and in 2 dairies (Art and SdC), Streptococcus genera were associated with the NWS. The analysis allowed us to show that although the diversity of identified genera did not change significantly between the rind, under-rind, and core fractions of the same samples, there was an evolution in the relative abundance and absolute quantification, modifying and differentiating profiles during ripening. The real-time PCR, also known as quantitative or qPCR, mainly differentiated the temporal adaptation of those species originating from bulk milks and those provided by NWS. The primary starters detected in NWS and cheeses contributed to the high relative concentration of 1-butanol, 2-butanol, 2-heptanol, 2-butanone, acetoin, delta-dodecalactone, hexanoic acid ethyl ester, octanoic acid ethyl ester, and volatile free fatty acids during ripening, whereas cheeses displaying low abundances of Streptococcus and Lactococcus (dairy Del) had a lower total concentration of acetoin compared with Art and SdC. However, the subdominant strains and nonstarter lactic acid bacteria present in cheeses are responsible for the production of secondary metabolites belonging to the chemical classes of ketones, alcohols, and organic acids, reaffirming the importance and relevance of autochthonous strains of each dairy plant although only considering a delimited production area.

Economic losses caused by mastitis and the influence of climate variation on the occurrence of the disease in a dairy cattle farm in southern Brazil.

This study evaluated the economic impacts caused by mastitis in a small dairy farm with similar characteristics and production to most dairy farms in southern Brazil and investigated if climatic variations influenced mastitis occurrence in the region. A farm with, on average, 45 lactating Holstein cattle was monitored from November 2021 to October 2022, and data on mastitis cases, bulk tank milk somatic cell count, animal treatment costs, milk production, animal disposal costs, and production losses were collected. Monthly averages of temperature, relative humidity (RH), and rainfall in the region were obtained. The greatest loss was related to the drop in milk production, resulting in 63.8% of total losses, followed by animal disposal (29.5%), milk disposal (4.6%), and treating animals with mastitis (2.0%), totaling a 10.6% reduction in the annual gross income. There were negative correlations between the clinical mastitis rate and monthly RH and between subclinical mastitis and temperature; the occurrence of subclinical mastitis and average RH were positively correlated. Our findings showed that mastitis negatively impacted the economy and that climate influenced mastitis occurrence.

Factors affecting the microbiological quality and contamination of farm bulk milk by Staphylococcus aureus in dairy farms in Asella, Ethiopia.

BACKGROUND: The determination of the microbiological quality and safety of raw milk and the associated influencing factors at the farm level is very critical given that the quality or safety of subsequent products that are further produced depends on this. Therefore, this study aimed to determine the microbiological quality and safety of bulk milk and identify associated risk factors, and assess the presence/absence of S. aureus in bulk milk with potential contaminating sources in dairy farms in Asella, Ethiopia. RESULTS: The geometric means of bacterial counts in farm bulk milk were 5.25 log cfu/ml, 3.1 log cfu/ml and 2.97 log cfu/ml for total bacterial count (TBC), coliform count (CC) and coagulase-positive staphylococci count (CPS), respectively. Of the 50 dairy farms, 66, 88, and 32% had TBC, CC and CPS counts, respectively, that exceeded the standard international limits for raw cow's milk intended for direct human consumption. TBC tended to increase as CC increased in bulk milk (r = 0.5). In the final regression model, increased TBC, CC and the contamination of farm bulk milk by S. aureus were significantly associated with dirty barns, dirty cows and soiled udder and teats. TBC was higher during the rainy season than during the dry season. The reported practice of washing teats with warm water significantly decreased CC and CPS. The occurrence of S. aureus was significantly (p < 0.05) higher in bulk farm milk (42%) than in pooled udder milk (37.3%), teat swabs (22.5%), milkers' hand swabs (18%), bulking bucket swabs (16.7%), milking container swabs (14%), and water for cleaning of udder and milkers' hands (10%). The questionnaire survey result showed widespred raw milk consumption habits, low level of training and poor hygienic milking practices. CONCLUSIONS: This study revealed low-quality bulk farm milk with high bacterial counts and a high occurrence of S. aureus. This indicates the potential food safety risks due to consumption of raw milk or its products. This study suggests awareness creation to dairy farmers and the public on hygienic milk production and heat treatment of milk before consumption.

A scoping review of the testing of bulk milk to detect infectious diseases of dairy cattle: Diseases caused by bacteria.

Testing of bulk milk (BM) samples is a convenient, cost-effective strategy that can easily be implemented as part of disease surveillance programs on dairy farms. Here, we performed a scoping review to summarize the literature reporting on the testing of BM samples to detect infectious diseases of dairy cattle caused by bacteria. We also provide a non-exhaustive, albeit significant, list of diagnostic tests that are marketed for BM samples, as well as a list of disease surveillance activities that included testing of BM samples. A literature search was carried out in 5 databases, yielding 8,829 records from which 474 were retained. Overall, 575 eligible bacterial pathogens were screened for using BM samples, ranging from 1 to 6 individual pathogens per study. Staphylococcus aureus, including methicillin-resistant Staph. aureus, were the most studied bacteria (n = 179 studies), followed by Streptococcus agalactiae (86), Mycobacterium avium ssp. paratuberculosis (79), Coxiella burnetii (79), and Mycoplasma spp. (67). Overall, culture-based protocols, ELISA, real-time PCR, and PCR were the most commonly adopted methodologies to screen BM samples. Sensitivity of BM testing for bovine paratuberculosis was generally low and varied greatly according to the ELISA cut-offs adopted and herd-level definition of disease. In general, protocols had low to moderate sensitivities (<50%), which increased for herds with high within-herd seroprevalence. Specificity of BM testing for paratuberculosis was generally high. With respect to mastitis pathogens, BM testing demonstrated high sensitivity and specificity for Strep. agalactiae, in general. However, we observed inconsistency among studies with respect to the sensitivity of BM culture to detect infected herds, which was notably higher if enrolled herds were heavily infected or had history of clinical disease. Among Salmonella spp. pathogens, Salmonella Dublin was the most frequently studied bacterium for which BM testing has been validated. Specificity of BM ELISA was high, ranging from 89.0 to 99.4. In contrast, sensitivity varied greatly among studies, ranging from 50.6% to 100%. Our findings support that one of most important factors affecting sensitivity of BM ELISA for Salmonella Dublin is whether nonlactating cattle are considered in the definition of herd infection status. In general, protocols analyzed in this review suffered from very low sensitivities, which hardly justifies their use as part of disease surveillance as single testing. Nevertheless, test sensitivity can be increased by the adoption of more inclusive definitions of disease-free herds. Further, low-sensitivity and high-specificity methods can be valuable tools for surveillance when used repeatedly over time.

A scoping review of the testing of bulk tank milk to detect nonbacterial pathogens or herd exposure to nonbacterial pathogens in dairy cattle.

In this scoping review, we characterized the literature reporting on the testing of bulk milk samples to detect microorganisms other than bacteria that can cause diseases in dairy cattle, including viruses, helminths, algae, and protozoa. A search strategy was completed by screening databases, conference proceedings, animal health agency websites, disease surveillance program websites, and handbooks of cattle-related diagnostic tests for potentially relevant articles. Two reviewers independently screened articles in English, Portuguese, or Spanish; original studies reporting on the testing of farm-level, unprocessed bulk milk samples for presence of pathogens or specific antibodies against agents other than bacteria that can cause diseases in cows were retained. From all studies, we used spreadsheets to extract relevant information, including pathogen screened, test used, and country of origin of bulk milk samples. Additionally, for studies reporting sufficient data to estimate test characteristics, we extracted detailed information about herd eligibility, testing protocol, and herd-level infection definition. A total of 8,829 records were identified, from which 1,592 were retained and assessed for eligibility, and 306 were included. Bovine viral diarrhea virus, Fasciola hepatica, Ostertagia ostertagi, and bovine herpesvirus 1 were the most frequently screened agents, reported from 107, 45, 45, and 33 studies, respectively. Sensitivity of bulk milk ELISA to detect herds with animals infected by bovine herpesvirus 1 ranged from 2 to 100%, and was affected mostly by antigen selection, cut-off adopted, herd vaccination status, and seroprevalence of lactating cows. Bulk milk ELISA had very high specificity to detect herds free of bovine leukemia virus, and varying sensitivity to detect herds with infected animals, which depended on the within-herd seroprevalence of lactating cattle. As for bovine viral diarrhea virus, in general, the sensitivity of bulk milk ELISA was moderate to high (>80%) when infection status was defined based on presence of persistently infected cattle or a high proportion of seropositive lactating cattle. Nevertheless, bulk milk ELISA was not able to distinguish infected and noninfected herds based on presence of seropositive unvaccinated weanlings. The PCR or quantitative PCR protocols employed had very low sensitivities (<40%) and very high specificities (>95%) to classify bovine viral diarrhea virus infection status of dairy herds. Sensitivity and specificity of bulk milk ELISA to classify herds with regards to presence of F. hepatica- or O. ostertagi-parasitized cattle were generally high and driven mostly by the definition of herd infection status. Conversely, bulk milk ELISA demonstrated varying characteristics to detect herds with or without Dictyocaulus viviparus-parasitized cattle, depending primarily on the antigen selected and presence of cattle with clinical signs of lungworm infection.

Evaluation of national surveillance methods for detection of Irish dairy herds infected with Mycobacterium avium ssp. paratuberculosis.

The aim of this study was to evaluate the utility and cost-effectiveness of a range of national surveillance methods for paratuberculosis in Irish dairy herds. We simulated alternative surveillance strategies applied to dairy cattle herds for the detection of Mycobacterium avium ssp. paratuberculosis (MAP)-infected herds (case-detection) or for estimation of confidence of herd freedom from infection (assurance testing). Strategies simulated included whole-herd milk or serum serology, serology on cull cows at slaughter, bulk milk tank serology, environmental testing, and pooled fecal testing. None of the strategies evaluated were ideal for widespread national case-detection surveillance. Herd testing with milk or serum ELISA or pooled fecal testing were the most effective methods currently available for detection of MAP-infected herds, with median herd sensitivity >60% and 100% herd specificity, although they are relatively expensive for widespread use. Environmental sampling shows promise as an alternative, with median herd sensitivity of 69%, but is also expensive unless samples can be pooled and requires further validation under Irish conditions. Bulk tank milk testing is the lowest cost option and may be useful for detecting high-prevalence herds but had median herd sensitivity <10% and positive predictive value of 85%. Cull cow sampling strategies were also lower cost but had median herd sensitivity <40% and herd positive predictive values of <50%, resulting in an increased number of test-positive herds, each of which requires follow-up herd testing to clarify status. Possible false-positive herd testing results associated with prior tuberculosis testing also presented logistical issues for both cull cow and bulk milk testing. Whole-herd milk or serum ELISA testing are currently the preferred testing strategies to estimate confidence of herd freedom from MAP in dairy herds due to the good technical performance and moderate cost of these strategies for individual herd testing. Cull cow serology and bulk tank milk sampling provide only minimal assurance value, with confidence of herd freedom increasing only minimally above the prior estimate. Different testing strategies should be considered when deciding on cost-effective approaches for case-detection compared with those used for building confidence of herd freedom (assurance testing) as part of a national program.

Pestivirus infection in cattle dairy farms: E2 glycoprotein ELISA reveals the presence of bovine viral diarrhea virus type 2 in northwestern Italy.

BACKGROUND: Bovine viral diarrhea virus (BVDV) types 1 and 2 are members of the Pestivirus genus of the Flaviviridae family. This genus also includes the HoBi-like virus, tentatively classified as BVDV type 3. BVDV-1 is widely distributed in Italy despite the extensive use of BVDV-1-based vaccines, while BVDV-2 and HoBi-like Pestivirus have been detected occasionally. Monitoring the occurrence of sporadic or atypical pestiviruses is a useful approach to evaluate the need for additional vaccine strains that can be used in BVDV control programs. RESULTS: In this study we developed a multiwell antibody ELISA based on the recombinant E2 protein of the three bovine pestiviruses. We evaluated the assay's applicability for surveillance purposes using pooled milk samples, each prepared from a maximum of 35 lactating cows and collected from 176 dairy herds. As expected, the majority of the pooled samples reacted to a greater extent against the BVDV-1 E2 antigen. All three milk pools from a single farm reacted to the BVDV-2 antigen, however. Further analysis using spot tests, antigen detection, and sequence analysis of the 5'-UTR region confirmed the presence of five persistently infected calves carrying a BVDV-2a strain. CONCLUSIONS: This study highlights for the first time that sporadic circulation of BVDV-2 can be predicted by immunoenzymatic methods in the absence of specific vaccination.

Short communication: Weak associations between mastitis control measures and bulk milk somatic cell counts in Swedish dairy herds.

Despite the fact that control programs have been available for several decades, mastitis remains an important problem in dairy herds around the world. Possible reasons for this include poor uptake and application of recommended mastitis control measures; poor or variable compliance; or variability in the effects of these measures. The objective of this study was to evaluate the associations between implemented mastitis control measures and bulk milk somatic cell count (BMSCC) in Swedish dairy herds. Data for this study were collected primarily from an extensive self-administered postal questionnaire about the herds, the people responsible for udder health, and details of udder health and mastitis management. A total of 898 questionnaires were distributed, and 428 questionnaires were returned (overall response rate of 48%), but we used the information from only 395 herds in this study. For all herds, we collected data on herd size and geometric average calculated BMSCC from the Swedish Official Milk Recording Scheme. We used logistic regression to assess the association between mastitis control measures and BMSCC, dichotomized as low (<200,000 cells/mL) or high (>200,000 cells/mL). We investigated 21 measures that have been suggested for mastitis control, but found only 2 to be associated with udder health as measured by BMSCC. Not providing dry cows with a specialized mineral feed was significantly associated with increased risk of high BMSCC, and not using post-milking teat disinfectant tended to be associated with increased risk. The lack of association for all other measures was not likely due to low power (because most of these measures had variable implementation rates) but could be due to the relatively narrow range of BMSCC in our study (range 61,000-524,000 cells/mL). However, our results agreed well with those of other recent studies, supporting the call for a thorough review of the current knowledge of mastitis control and for wider application of intervention studies to verify the actual effects of suggested control measures.

Herd-level prevalence of selected endemic infectious diseases of dairy cows in Great Britain.

To implement appropriate and effective disease control programs at the national level, up-to-date and unbiased information on disease frequency is needed. The aim of this study was to estimate the prevalence of selected endemic infectious diseases in the population of dairy herds in Great Britain. Bulk milk tank (BMT) samples from 225 randomly selected dairy farms, stratified by region and herd size, were tested for antibodies against bovine viral diarrhea virus (BVDV), bovine herpesvirus type 1, Mycobacterium avium ssp. paratuberculosis, Leptospira Hardjo, Salmonella spp., Coxiella burnetii, Fasciola hepatica, Neospora caninum, and Ostertagia ostertagi. Furthermore, the presence of BVDV, C. burnetii, and Chlamydia-like organisms was determined by PCR. The apparent herd prevalence was estimated as a weighted proportion of positive herds. The true prevalence was calculated when a test was used with known test characteristics for the cut-off value used. Among unvaccinated herds, the true prevalence of BMT antibodies against BVDV was estimated at 66% [95% confidence interval (CI): 56-77%], M. avium ssp. paratuberculosis 68% (95% CI: 59-77%), bovine herpesvirus type 1 62% (95% CI: 52-73%), Leptospira Hardjo 47% (95% CI: 34-60%), and Salmonella spp. 48% (95% CI: 39-56%). The apparent prevalence of BMT antibodies against C. burnetii was 80% (95% CI: 75-85%), F. hepatica 55% (95% CI: 48-62%), N. caninum 46% (95% CI: 38-54%), and O. ostertagi 95% (95% CI: 91-98%). The BVDV, C. burnetii, and Chlamydia-like antigens were detected in 5 (95% CI: 2-9%), 29 (95% CI: 21-36%), and 31% (95% CI: 24-38%) of herds, respectively. Our results show that dairy cows across GB are frequently exposed to the studied pathogens, which are endemic at high levels with some geographical variations. These prevalence estimates provide a much-needed basis to assess whether nationwide control programs for the studied pathogens are justified by their potential economic, environmental, and public health implications. Should surveillance and control programs be initiated, the estimates presented here are a baseline against which progress can be assessed.

Comparison of bulk milk antibody and youngstock serology screens for determining herd status for Bovine Viral Diarrhoea Virus.

BACKGROUND: This paper examines the use of Bulk Milk antibody (BM Ab), Youngstock (YS) serology (Check Tests) and Bulk Milk PCR (BM PCR) for determining the presence or absence of animals persistently infected (PI) with Bovine Viral Diarrhoea Virus (BVDV) within a herd. Data is presented from 26 herds where average herd sizes were 343 and 98 animals for dairy and beef units respectively. Seventeen herds had sufficient data to analyse using Receiver Operating Characteristic (ROC) and probability curves enabling calculation of the sensitivity and specificity of BM Ab and YS Check tests for determining the presence of PI animals within herds in this dataset. RESULTS: Using BM Ab to screen a herd for the presence of PI animals, achieved a herd level sensitivity and specificity of 80.00 % (44.39-97.48 %) and 85.71 % (42.13-99.64 %) respectively (95 % confidence intervals quoted). Sensitivity and specificity of YS Check Tests at a cut off of 3/10 Ab positive YS were 81.82 % (48.22-97.72 %) and 66.67 % (22.28-95.67 %) respectively (95 % confidence interval). These results were achieved by comparing the screening tests to whole herd PI searches that took place 1-19 months after the initial screen with a mean interval of 8 months. Removal of this delay by taking BM samples on the day of a whole herd test and simulating a YS Check Test from the herd test data produced improvements in the reliability of the Check Tests. BM Ab sensitivity and specificity remained unchanged. However, the Check Test sensitivity and specificity improved to 90.9 % (58.72-99.77 %) and 100 % (54.07-100 %) respectively (95 % confidence interval) at a cut of off 2.5/10 Ab positive animals. Our limited BM PCR results identified 5/23 dairy farms with a positive BM PCR result; two contained milking PIs, two had non-milking PIs and another had no PIs identified. CONCLUSIONS: Delaying a PI search following an initial herd screen decreased the diagnostic accuracy and relevance of our results. With careful interpretation, longitudinal surveillance using a combination of the techniques discussed can successfully determine farm status and therefore allow changes in BVDV status to be detected early, thus enabling prompt action in the event of a BVDV incursion.

Risk-based audit selection of dairy farms.

Dairy farms are audited in the Netherlands on numerous process standards. Each farm is audited once every 2 years. Increasing demands for cost-effectiveness in farm audits can be met by introducing risk-based principles. This implies targeting subpopulations with a higher risk of poor process standards. To select farms for an audit that present higher risks, a statistical analysis was conducted to test the relationship between the outcome of farm audits and bulk milk laboratory results before the audit. The analysis comprised 28,358 farm audits and all conducted laboratory tests of bulk milk samples 12 mo before the audit. The overall outcome of each farm audit was classified as approved or rejected. Laboratory results included somatic cell count (SCC), total bacterial count (TBC), antimicrobial drug residues (ADR), level of butyric acid spores (BAB), freezing point depression (FPD), level of free fatty acids (FFA), and cleanliness of the milk (CLN). The bulk milk laboratory results were significantly related to audit outcomes. Rejected audits are likely to occur on dairy farms with higher mean levels of SCC, TBC, ADR, and BAB. Moreover, in a multivariable model, maxima for TBC, SCC, and FPD as well as standard deviations for TBC and FPD are risk factors for negative audit outcomes. The efficiency curve of a risk-based selection approach, on the basis of the derived regression results, dominated the current random selection approach. To capture 25, 50, or 75% of the population with poor process standards (i.e., audit outcome of rejected), respectively, only 8, 20, or 47% of the population had to be sampled based on a risk-based selection approach. Milk quality information can thus be used to preselect high-risk farms to be audited more frequently.

Short communication: Effectiveness of tools provided by a dairy company on udder health in Dutch dairy farms.

A Dutch dairy company initiated a quality system to support dairy farmers to improve sustainability on their farm. Improvement of udder health is defined by the dairy company as one of the sustainability items. A part of that quality system is to offer farmers 3 tools to improve the udder health status of the herd. The first tool is an Udder Health Workshop at which farmers make a farm-specific action plan to improve the udder health situation in their herd. The second tool is the Udder Health Navigator, which is an internet-based program to gain insight in the actual udder health situation at the farm. The third tool is the Udder Health Checklist, which is available on the internet and it identifies farm-specific risks for udder health problems. The aim of this study was to evaluate the effectiveness of these tools in improving udder health. The bulk milk somatic cell count (BMSCC) was used as the measure of herd udder health performance. In total, 605 farms attended the Udder Health Workshop, 988 farms completed the Udder Health Navigator, and 1,855 farms completed the Udder Health Checklist in 2012. Information on BMSCC records (2 records per month) was available for 12,782 Dutch dairy farms during the years 2011 and 2012. For every farm, the average BMSCC of all months during the years 2012 and 2011 were calculated. This resulted in 306,768 average monthly observations of the BMSCC. Subsequently, all months after the completion of one of the tools were assigned a 1, and all other months were assigned a 0. A statistical analysis was carried out to compare the average monthly BMSCC of the farms that completed one or more tools with farms that did not complete one of the tools. Both completing the Udder Health Navigator and the Udder Health Checklist had a significant association with a lower average monthly BMSCC. The effect of the Udder Health Navigator and Udder Health Checklist on the BMSCC were greater in herds with a BMSCC in 2011 of 200,000 to 250,000 cells/mL and even greater for herds with a BMSCC above 250,000 cells/mL compared with herds with a BMSCC in 2011 of 150,000 to 200,000 cells/mL or less than 150,000 cells/mL. It is difficult to draw conclusions on the effect of the Udder Health Workshop due to overlap in participation between the tools. The results suggest that completing the web tools is associated with a reduction in the BMSCC of the herd.

Do farm audits improve milk quality?

Milk quality is assessed using bulk milk analysis and by farm audits in the Netherlands. However, the extent of the effect that dairy farm audits have on milk quality is unknown. Data from over 13,000 audits performed on 12,855 dairy farms from February 2006 to April 2008 were merged with laboratory test results of 325,150 bulk milk samples collected 6 mo before and after the audit. A linear mixed model with the method of restricted maximum likelihood was conducted to study whether the total bacterial counts (TBC) of bulk milk were lower during the periods before and after the dairy farm audit. Results showed that TBC values were 2 to 6% lower (i.e., 0.010 to 0.026 log cfu/mL) for a period from 1.5 to at least 6 mo after an audit. Additionally, several variables were significantly associated with bulk milk TBC values: seasonality, total number of attention points (given if some checklist points were not appropriate), audit type, audit result, and the categories milking equipment maintenance, and utility room-tank maintenance. The TBC values increased with a higher level of attention points. Furthermore, the farms rejected based on the audit results had the highest average TBC values and the approved farms had the lowest values. If dairy farms had an overall negative audit assessment and consequently needed a re-audit in the following year, the TBC values of bulk milk were more likely to be higher. Auditing may provide dairy farmers the opportunity to receive advice about factors that influence bulk milk TBC values, for a period of at least 6 mo following the audit.

Manageable risk factors associated with bacterial and coliform counts in unpasteurized bulk milk in Flemish dairy herds.

Associations between herd management practices and both bacterial counts (BC) and coliform counts (CC) from 254 and 242 dairy herds in Flanders (Belgium), respectively, were studied. Data were analyzed using multivariable, multilevel linear regression analysis, allowing variance components analyses. Both BC and CC fluctuated throughout the year, although the milk quality parameters followed an opposite pattern. Bacterial count values decreased with each increase of the cleaning frequency of the cubicles (once per week, once per day, twice per day, or more than twice per day) between January and March. Herds with a conventional milking parlor had substantially lower BC than herds where the cows were milked using an automatic milking system. Lower BC were observed when the milking parlor was equipped with an automatic cluster removal system, when premilking teat disinfection was applied, when the dry cows were supplemented with a mix of minerals and vitamins, and when the teats were prepared either first wet and dried or via an automatic milking system. Milking cows with a high-pipeline milking parlor setup or with an automatic milking system was associated with substantially higher CC values. Herds where prepartum heifers were often treated with antimicrobials before calving had a lower CC than farms where heifers were either not or only rarely treated. Most variation in BC and CC resided at the herd level rather than at the observation level, indicating that management is important in the control of both BC and CC. Still, only a small proportion of the total variance was explained by factors capturing information related to the milking, herd health, and dry cow management, which suggests that the bacteriological milk quality and, in particular, CC is primarily driven by other factors than the ones included in this study.

Genotype-specific risk factors for Staphylococcus aureus in Swiss dairy herds with an elevated yield-corrected herd somatic cell count.

Bovine mastitis is a frequent problem in Swiss dairy herds. One of the main pathogens causing significant economic loss is Staphylococcus aureus. Various Staph. aureus genotypes with different biological properties have been described. Genotype B (GTB) of Staph. aureus was identified as the most contagious and one of the most prevalent strains in Switzerland. The aim of this study was to identify risk factors associated with the herd-level presence of Staph. aureus GTB and Staph. aureus non-GTB in Swiss dairy herds with an elevated yield-corrected herd somatic cell count (YCHSCC). One hundred dairy herds with a mean YCHSCC between 200,000 and 300,000cells/mL in 2010 were recruited and each farm was visited once during milking. A standardized protocol investigating demography, mastitis management, cow husbandry, milking system, and milking routine was completed during the visit. A bulk tank milk (BTM) sample was analyzed by real-time PCR for the presence of Staph. aureus GTB to classify the herds into 2 groups: Staph. aureus GTB-positive and Staph. aureus GTB-negative. Moreover, quarter milk samples were aseptically collected for bacteriological culture from cows with a somatic cell count ≥150,000cells/mL on the last test-day before the visit. The culture results allowed us to allocate the Staph. aureus GTB-negative farms to Staph. aureus non-GTB and Staph. aureus-free groups. Multivariable multinomial logistic regression models were built to identify risk factors associated with the herd-level presence of Staph. aureus GTB and Staph. aureus non-GTB. The prevalence of Staph. aureus GTB herds was 16% (n=16), whereas that of Staph. aureus non-GTB herds was 38% (n=38). Herds that sent lactating cows to seasonal communal pastures had significantly higher odds of being infected with Staph. aureus GTB (odds ratio: 10.2, 95% CI: 1.9-56.6), compared with herds without communal pasturing. Herds that purchased heifers had significantly higher odds of being infected with Staph. aureus GTB (rather than Staph. aureus non-GTB) compared with herds without purchase of heifers. Furthermore, herds that did not use udder ointment as supportive therapy for acute mastitis had significantly higher odds of being infected with Staph. aureus GTB (odds ratio: 8.5, 95% CI: 1.6-58.4) or Staph. aureus non-GTB (odds ratio: 6.1, 95% CI: 1.3-27.8) than herds that used udder ointment occasionally or regularly. Herds in which the milker performed unrelated activities during milking had significantly higher odds of being infected with Staph. aureus GTB (rather than Staph. aureus non-GTB) compared with herds in which the milker did not perform unrelated activities at milking. Awareness of 4 potential risk factors identified in this study guides implementation of intervention strategies to improve udder health in both Staph. aureus GTB and Staph. aureus non-GTB herds.

Milk as an indicator of dietary imbalance.

BACKGROUND: Milk provides a readily available diagnostic fluid collected daily or more frequently on an individual animal or herd basis. Milk, as an aggregated sample in bulk tank milk (BTM) represents the status of a herd instead of a single animal. In this review, we examine the potential for milk to predict risks to efficient production, reproductive success, and health on the individual cow and herd level. FINDINGS: For many conditions related to disorders of metabolism including hyperlipdaemia and ketonaemia, improved individual cow milk testing may allow a temporally useful detection of metabolic disorder that can target intervention. However, the extension of these tests to the BTM is made more difficult by the tight temporal clustering of disorder to early lactation and the consequent mixing of cows at even moderately different stages of lactation. Integrating herd recording demographic information with Fourier-transformed mid-infrared spectra (FT-MIR) can provide tests that are useful to identify cows with metabolic disorders. The interpretation of BTM urea and protein content provides useful indications of herd nutrition. These may provide indicators that encourage further investigations of nutritional influences on herd fertility but are unlikely to provide strong diagnostic value. The fat-to-protein ratio has a high specificity, but poor sensitivity for detection of fibre insufficiency and acidosis on an individual cow basis. Selenium, zinc, ß-carotene, and vitamin E status of the herd can be determined using BTM. CONCLUSIONS: There appears to be increasing potential for the use of milk as a diagnostic fluid as more in-parlour tests become available for individual cows. However, the BTM appears to have under-utilised potential for herd monitoring.

Occurrence of Methicillin-Resistant Staphylococcus aureus (MRSA) in Bovine Bulk Milk and Farm Workers in Smallholder Dairy Farming Systems in Northwestern Ethiopia.

Background and Purpose: Staphylococcus aureus is a common pathogen responsible for causing various human and animal infections and is well known for its ability to develop resistance to multiple antibiotics. This study aimed to evaluate the occurrence of methicillin-resistant Staphylococcus aureus (MRSA) in bulk milk and dairy farms in northwestern Ethiopia and to determine their phenotypic and genotypic antimicrobial susceptibility patterns. Methods: We collected 50 bulk milk samples from 50 dairy farms and 50 hand swabs from dairy milkers. The cefoxitin disk diffusion test and PCR-based assays were used to identify MRSA isolates. In addition, cefoxitin-resistant isolates were tested for susceptibility to other antibiotics using the Kirby-Bauer disk diffusion method. Results: The results showed that MRSA was detected in 8 samples: 6 from bulk milk samples (12%) and 2 from hand swabs (4%). All MRSA isolates exhibited a high resistance rate to penicillin (100%), followed by tetracycline (75%), ciprofloxacin (25%), chloramphenicol (25%), erythromycin (25%), gentamycin (12.5%), and trimethoprim-sulfamethoxazole (12.5%). Moreover, 72% of the isolates showed resistance to three or more antibiotic classes and were classified as multidrug-resistant. Conclusion: This study identified methicillin-resistant Staphylococcus aureus and multidrug-resistant MRSA in bulk milk and dairy farms in northwestern Ethiopia. These findings highlight the potential risk of transmission of these antibiotic-resistant bacteria to humans and the need for improved antibiotic stewardship in the dairy sector using the One Health approach.

Molecular evidence of sporadic Coxiella burnetii excretion in sheep milk, central Portugal.

Coxiella burnetii is the etiologic agent of Q fever, a worldwide zoonosis. Cattle, sheep and goats are considered the main reservoirs of the disease. Transmission to humans occurs mainly through the inhalation of infectious aerosols from milk, faeces, urine, and birth products from infected ruminants. In this study, a 2-year longitudinal approach was performed to ascertain the excretion of C. burnetii in bulk tank milk samples of sheep from a mountain plateau in central Portugal, with sampling conducted during the years 2015 and 2016. From a total of 156 bulk tank milk samples tested by qPCR, only one showed to be positive for C. burnetii (1.28% [95%CI: 0.03-6.94]), from 2015, the first year of collection. Bidirectional sequencing and phylogenetic analysis of IS1111 transposase partial region confirmed the presence of C. burnetii DNA. The presence of C. burnetii in raw milk samples highlights the necessity for additional research to determine if raw milk is a potential source for human infection. Animal health surveillance and prevention measures against this zoonotic disease should be considered.

Establishing a surveillance programme for Salmonella Dublin in Austrian dairy herds by comparing herd-level vs. individual animal detection methods.

Due to its increasing occurrence in cattle farms in various countries, leading to significant economic losses in affected livestock, Salmonella enterica subspecies enterica serovar Dublin (S. Dublin) has become a highly investigated pathogen in cattle production. In Austria, there have been occasional human cases of S. Dublin as well as an increase in laboratory-confirmed cases in cattle, indicating the need for a screening programme to determine the current status in Austria. The aims of this study were, firstly, to determine the seroprevalence of S. Dublin in dairy herds through bulk milk screenings in two federal states (Salzburg, Tyrol) of Austria. Secondly, the study aimed to identify the infection status of the herds through individual animal and herd level detection, comparing microbiological, molecular and serological detection methods. The results of the study will allow the development of a sampling strategy for a surveillance programme in Austria. A total of 6973 dairy farms were tested through serological bulk milk screening. The seroprevalence for the federal state of Tyrol was 14.8 % and for Salzburg it was 18.2 %, resulting in an average seroprevalence of 16.5 %. At an individual animal level, 205 (11.3 %) animals tested positive for shedding of S. Dublin in the faeces through microbiological detection, and 268 (17.0 %) animals had positive values (ct value ≤ 38) by qPCR. The association between microbiological and molecular detection was statistically significant (p < 0.001), with a calculated kappa value of 0.65 ± 0.27 (p ≤ 0.001), assuming a substantial level of agreement. In 17 herds, where an individual animal tested positive for shedding of S. Dublin, environmental sampling and testing were carried out. At a herd level 16 (94.1 %) out of the 17 participating herds, tested positive for S. Dublin either microbiologically or by molecular assay in boot swab samples. Bulk milk samples from 14 out of the 17 participating herds were analysed for antibodies to S. Dublin and 12 samples (85.7 %) were positive. In total 111 (18.9 %) out of 587 blood samples tested positive for S. Dublin antibodies, demonstrating a statistically significant correlation (p < 0.001) both with microbiological (κ = 0.32 ± 0.49; p ≤ 0.001) and molecular (κ=0.23 ± 0.06; p ≤ 0.001) findings. It was possible to identify S. Dublin by culture from boot swabs in 14 (82.4 %) out of 17 herds and by molecular assay using qPCR in 15 (88.2 %) out of 17 herds, indicating a suitable sample type for screening on a herd level-basis for acute infections, but not for identifying chronic infections or asymptomatic carriers. Other environmental samples, such as sponge-sticks, are only suitable to a limited extent for the detection of S. Dublin. The results of this study demonstrate a moderate S. Dublin prevalence in dairy herds in the selected Austrian regions, signalling further screening and management programmes for the future.