Bacteriological outcomes following random allocation to quarter-level selection based on California Mastitis Test score or cow-level allocation based on somatic cell count for dry cow therapy

Intramammary infusion of antimicrobials at the end of lactation (dry cow therapy) has been a cornerstone of mastitis management for many years. However, as only a proportion of cows are infected at this time, treating only those cows likely to be infected is an important strategy to reduce antimicrobial usage and minimize risk of emergence of antimicrobial resistance. Such an approach requires the ability to discriminate between cows and quarters likely to be infected and uninfected. This study compared assignment of cows or quarters to antimicrobial treatment at the end of lactation based on cow composite somatic cell count (SCC; i.e., all quarters of cows with a maximum SCC across lactation >200,000 cells/mL received an antimicrobial; n = 891 cows, SCC-group) or assignment to quarter-level treatment based on a quarter level California Mastitis Test (CMT) score ≥ trace (n = 884 cows; CMT-group) performed immediately before drying off. All quarters of all cows also received an infusion of a bismuth-based internal teat sealant. Milk samples were collected for microbiology following the last milking, and again within 4 d of calving. Clinical mastitis records from dry off to 30 d into the subsequent lactation were collected. Multilevel, multivariable models were used to assess the effect of assignment to antimicrobial treatment. At drying off, a total of 575 (8.8%) and 147 (2.3%) of the 6,528 quarters had a minor, and a major intramammary infection (IMI), respectively. At drying off, 2089/3270 (63.9%) and 883/3311 (26.7%) of quarters were treated with dry cow therapy in the CMT and SCC-groups, respectively. Apparent bacteriological cure proportion for any IMI was higher in quarters assigned to the CMT than the SCC-group (349/368 (0.95, 95% CI 0.92-0.97) versus 313/346 (0.90, 95% CI 0.87-0.93)). New IMI proportion was lower among quarters assigned to the CMT than SCC-group [101/3,212 (0.032, 95% CI 0.025-0.038) versus 142/3,232 (0.044, 95% CI 0.036-0.051)]. The prevalence of any IMI postcalving was lower in quarters assigned to the CMT than SCC-group [119/3,243 (0.037, 95% CI: 0.030-0.044) versus 173/3,265 (0.054, 95% CI: 0.045-0.062)]. There was no difference in incidence of clinical mastitis between treatment groups. The total mass of antimicrobials used was 63% higher in the CMT-group than in the SCC-group (3.47 versus 2.12 mg/kg of liveweight). Selection of quarters for antimicrobial treatment at the end of lactation based on CMT resulted in greater proportion undergoing bacteriological cure, reduced risk of any new IMI and reduced post calving prevalence of any IMI compared with selection of cows based on SCC. However, CMT-based selection resulted in higher antimicrobial use compared with SCC-based selection, and further research is required to analyze the cost benefit and impact on risk of antimicrobial resistance of these 2 strategies.

Distribution of somatic cell count and udder pathogens in Norwegian dairy goats

Compared with dairy cows, goat somatic cell count (SCC) is higher and probably more affected by physiological factors such as parity, stage of lactation, and season. Thus, SCC is believed to be a less precise indicator of intramammary infections in dairy goats, and no consensus exists on SCC thresholds for considering goats as infected. The Norwegian Goat Recording System maintains individual goat production records and results from microbiological analyses of milk samples. In this retrospective observational study, we used recordings over a 10-yr period (2010 to 2020) to describe the association between individual goat SCC and noninfectious factors, as well as intramammary infections. The median SCC in the 1,000,802 milk recordings included in the study was 440,000 cells/mL, and the mode was 70,000 cells/mL. Somatic cell count increased with parity, days in milk, estrus, pasture season, and intramammary infections. The effect of parity and stage of lactation was significantly higher in infected compared with uninfected goats. Staphylococci dominated as causes of intramammary infections, with Staphylococcus aureus as the udder pathogen associated with highest SCC. The most prevalent non-aureus staphylococci were Staphylococcus warneri, Staphylococcus epidermidis, and Staphylococcus caprae. This study provides guidelines for interpretation of goat SCC at different parities and stages of lactations under Norwegian management conditions. We revealed a considerable variation in SCC associated with physiological factors, indicating that the cutoff for identifying infected goats should be a dynamic threshold adjusted for parity, stage of lactation, and season.

Novel ways to use sensor data to improve mastitis management

Current sensor systems are used to detect cows with clinical mastitis. Although, the systems perform well enough to not negatively affect the adoption of automatic milking systems, the performance is far from perfect. An important advantage of sensor systems is the availability of multiple measurements per day. By clearly defining the need for detection of subclinical mastitis (SCM) and clinical mastitis (CM) from the farmers' management perspective, detection and management of SCM and CM may be improved. Sensor systems may also be used for other aspects of mastitis management. In this paper we have defined 4 mastitis situations that could be managed with the support of sensor systems. Because of differences in the associated management and the epidemiology of these specific mastitis situations, the required demands for performance of the sensor systems do differ. The 4 defined mastitis situations with the requirements of performance are the following: (1) Cows with severe CM needing immediate attention. Sensor systems should have a very high sensitivity (>95% and preferably close to 100%) and specificity (>99%) within a narrow time window (maximum 12 h) to ensure that close to all cows with true cases of severe CM are detected quickly. Although never studied, it is expected that because of the effects of severe CM, such a high detection performance is feasible. (2) Cows with mastitis that do not need immediate attention. Although these cows have a risk of progressing into severe CM or chronic mastitis, they should get the chance to cure spontaneously under close monitoring. Sensor alerts should have a reasonable sensitivity (>80%) and a high specificity (>99.5%). The time window may be around 7 d. (3) Cows needing attention at drying off. For selective dry cow treatment, the absence or presence of an intramammary infection at dry-off needs to be known. To avoid both false-positive and false-negative alerts, sensitivity and specificity can be equally high (>95%). (4) Herd-level udder health. By combining sensor readings from all cows in the herd, novel herd-level key performance indicators can be developed to monitor udder health status and development over time and raise alerts at significant deviances from predefined thresholds; sensitivity should be reasonably high, >80%, and because of the costs for further analysis of false-positive alerts, the specificity should be >99%. The development and validation of sensor-based algorithms specifically for these 4 mastitis situations will encourage situation-specific farmer interventions and operational udder health management.

Detecting intramammary infection at the end of lactation in dairy cows

To reduce antimicrobial use, infusion of antimicrobials into only infected cows at the end of lactation (selective dry cow therapy) is preferable to infusion of every cow with antimicrobials. Use of selective dry cow antimicrobial therapy requires differentiation of probably infected from uninfected cows to enable treatment allocation. Milk somatic cell count (SCC) has been used to distinguish between cows with and without intramammary infection (IMI). However, SCC may be influenced by milk yield, stage of lactation, breed, and herd-level variables such as prevalence of infection. Cut points for SCC, to distinguish between cows with and without an IMI, may need to differ between cow age groups and breeds, or among herds. This study evaluated associations between SCC and major pathogen IMI in one or more quarters of 2,606 cows from 36 herds in 4 regions of New Zealand. In the last week of lactation, cows selected at random had milk samples collected from each quarter, and the teat-end condition and hygiene of the udder were scored. Herd- and cow-level data including age, breed, milk volume, and SCC at each production were recorded, and bulk tank milk SCC and volume of milk shipped were collated. At cow level, the association between average, maximum, and last cow-composite SCC, and presence of a major pathogen IMI in one or more quarters of cows, was examined using receiver operator curves. Predictive logistic regression models were then developed that included potential effect modifiers such as age, milk yield, and bulk tank milk SCC. The population average prevalence of major pathogen IMI was 7.2% of cows (95% confidence interval = 5.9-8.6), and this varied significantly between herds. The average, maximum, and last cow-composite SCC of lactation were all predictive of presence of a major pathogen IMI and did not differ in their ability to discriminate infected from uninfected cows. However, the optimal cut points for the last SCC, the maximum SCC, and average SCC were 108, 152, and 105 × 1,000 cells/mL, respectively. Inclusion of age, bulk tank SCC, and history of clinical mastitis improved overall model fit. However, inclusion of these variables did not improve the discriminatory power of maximum cow-composite SCC used alone. We conclude that cow-composite SCC on its own resulted in sensitivities and specificities of between 0.76 and 0.86, and 0.71 to 0.80, respectively, for determination of presence of major pattern IMI, and the predictive value was not improved by addition of other predictor variables.

Rumen and Hindgut Bacteria Are Potential Indicators for Mastitis of Mid-Lactating Holstein Dairy Cows

Mastitis is one of the major problems for the productivity of dairy cows and its classifications have usually been based on milk somatic cell counts (SCCs). In this study, we investigated the differences in milk production, rumen fermentation parameters, and diversity and composition of rumen and hindgut bacteria in cows with similar SCCs with the aim to identify whether they can be potential microbial biomarkers to improve the diagnostics of mastitis. A total of 20 dairy cows with SCCs over 500 × 10³ cells/mL in milk but without clinical symptoms of mastitis were selected in this study. Random forest modeling revealed that Erysipelotrichaceae UCG 004 and the [Eubacterium] xylanophilum group in the rumen, as well as the Family XIII AD3011 group and Bacteroides in the hindgut, were the most influential candidates as key bacterial markers for differentiating "true" mastitis from cows with high SCCs. Mastitis statuses of 334 dairy cows were evaluated, and 96 in 101 cows with high SCCs were defined as healthy rather than mastitis according to the rumen bacteria. Our findings suggested that bacteria in the rumen and hindgut can be a new approach and provide an opportunity to reduce common errors in the detection of mastitis.

Factors associated with milking-to-milking variability in somatic cell counts from healthy cows in an automatic milking system

Fully automated on-line analysis equipment is available for analysis of somatic cell count (SCC) at every milking in automatic milking systems. In addition to results from on-line cell counters (OCC), an array of additional cow-level and quarter-level factors considered important for udder health are recorded in these systems. However, the amount of variability in SCC that can be explained by available data is unknown, and so is the proportion of the variability that may be due to physiological or normal variability. Our aim was to increase our knowledge on OCC as an indicator for disturbances in udder health by assessing the variability in OCC in cows free from clinical mastitis. The first objective was to evaluate how much of the variability in OCC could be explained by different potential sources of variability, including intramammary infection (IMI) status (assessed by bacterial culture of quarter milk samples). The second objective was to evaluate the repeatability of the OCC sensor used in our study and the agreement between OCC values and SCC measured in a dairy herd improvement (DHI) laboratory. A longitudinal study was performed in the research herd of the Norwegian University of Life Sciences from January 5th 2016 to May 22nd 2017. Data from 62,471 milkings from 173 lactations in 129 cows were analyzed. We used ln-transformed OCC values (in 1000 cells/ml) as the outcome (lnOCC) in linear mixed models, with random intercepts at cow-level and lactation-level within cow. We were able to explain 15.0% of the variability in lnOCC with the following fixed effects: lactation stage, parity, milk yield, OCC in residual milk from the previous milking, inter-quarter difference between the highest and lowest conductivity, season, IMI status, and genetic lineage. When including the random intercepts, the degree of explanation was 55.2%. The individual variables explained only a small part of the total variability in lnOCC. We concluded that physiological or normal variability is probably responsible for a large part of the overall variability in OCC in cows without clinical mastitis. This is important to consider when using OCC data for research purposes or in decision-support tools. Sensor repeatability was evaluated by analyzing milk from the same sample multiple times. The coefficient of variation was 0.11 at an OCC level relevant for detection of subclinical mastitis. The agreement study showed a concordance correlation coefficient of 0.82 when comparing results from the OCC with results from a DHI laboratory.

Dynamics of somatic cell count patterns as a proxy for transmission of mastitis pathogens

Management of udder health is particularly focused on preventing new infections. Data from the DeLaval Online Cell Counter (DeLaval, Tumba, Sweden) may be used in forecasting to improve decision support for improved udder health management. It provides online cell counts (OCC) as a proxy for somatic cell counts from every milking at the cow level. However, these values are typically too insensitive and nonspecific to indicate subclinical intramammary infection (IMI). Our aim was to describe and evaluate use of dynamic transmission models to forecast subclinical IMI episodes using milk cultures or changes in OCC patterns over time. The latter was expressed by an elevated mastitis risk variable. Data were obtained from the dairy herd of the Norwegian University of Life Sciences (Oslo, Norway). In total, 173 cows were sampled monthly for bacteriological milk culture during a 17-mo study period and 5,330 quarter milk samples were cultured. Mastitis pathogens identified were assigned to 1 of 2 groups, Pat 1 or Pat 2. Pathogens from which a high cell count would be expected during a subclinical IMI episode were assigned to the Pat 1 group. Pathogens not in the Pat 1 group were assigned to the Pat 2 group. Staphylococcus epidermidis, Staphylococcus aureus, and Streptococcus dysgalactiae were the most common Pat 1 pathogens. Corynebacterium bovis, Staphylococcus chromogenes, and Staphylococcus haemolyticus were the most common Pat 2 pathogens. The OCC were successfully recorded from 82,182 of 96,542 milkings. The current study included 324 subclinical IMI episodes. None of the mastitis pathogens demonstrated a basic reproduction number (R₀) >1. Patterns of OCC change related to an episode of Pat 1 subclinical IMI at specificity levels of 80, 90, and 95% at sensitivity levels of 69, 59, and 48% respectively, demonstrated an R₀ >1. An existing infection was significant for transmission for several Pat 2 pathogens, but only for Staphylococcus aureus and Staphylococcus epidermidis among Pat 1 pathogens. Dynamic transmission models showed that patterns of OCC change related to an episode of Pat 1 subclinical IMI were significantly related to the same pattern occurring in susceptible cows at specificity levels of 80, 90, and 99% at sensitivity levels of 69, 48, and 8%, respectively. We conclude that changes in herd prevalence of subclinical IMI can be predicted using dynamic transmission models based on patterns of OCC change. Choice of specificity level depends on management goals and tolerance for false-positive alerts.

A cohort study of the effect of Streptococcus agalactiae on milk yield and somatic cell count in Norwegian dairy cows

The primary objective of the present study was to estimate the effect of Streptococcus agalactiae intramammary infection on milk production and somatic cell count (SCC) in Norwegian dairy cows. A secondary objective was to assess differences in the effect of common Strep. agalactiae sequence types (ST) found in Norwegian dairy herds. We performed a cohort study combining registry data with sequence-type data from Strep. agalactiae isolates. Herds in which Strep. agalactiae had been detected in individual animals (bacteriological culture or quantitative PCR) between 2012 and 2015 were included. We accessed monthly test-day milk yield records for the entire period to compare milk yield and SCC between cows that were Strep. agalactiae positive and all other cows, within each herd. The study sample consisted of 150 herds, 15,757 cows, 30,850 lactations, and 204,126 test days. We evaluated the effects of Strep. agalactiae on test-day milk yield and SCC using mixed linear regression models, controlling for clustering by herd, cow, and lactation. Multilocus sequence typing of Strep. agalactiae was available for isolates from 86 herds. Additional models were fit to a subset of herds (n = 59) in which ST1, ST23, ST103, and ST196 had been found, to compare the effects of ST on milk production and SCC. In the period 3 to 2 mo before diagnosis, Strep. agalactiae-positive cows produced an average of 1.3 kg more DIM-adjusted milk/d than their negative herd mates. At the time of diagnosis, production was on average 0.13 kg less DIM-adjusted milk/d in Strep. agalactiae-positive cows than in negative cows; 2 to 3 mo after diagnosis, they produced 1.24 kg less DIM-adjusted milk/d than negative cows. Losses persisted for the rest of the investigated period. Cows with ST23, ST103, and ST196 followed a similar pattern as the overall analysis with respect to milk production, whereas ST1-affected cows produced similar amounts of milk before diagnosis as the negative cows. Cows with ST1 experienced the largest milk loss 1 to 2 mo after diagnosis but then recovered to some extent; for cows with ST103, the severe milk loss persisted for the rest of the investigation period. The cow-associated ST103 elicited a lower response in peak SCC compared with ST23, ST103, and ST196. The results indicate an effect of Strep. agalactiae on milk production and SCC. Production was lowest 2 to 3 mo after a positive sample. Peak SCC was reached the month before diagnosis, with notable differences between sequence types.

The detection of intramammary infections using online somatic cell counts

Timely and accurate identification of cows with intramammary infections is essential for optimal udder health management. Various sensor systems have been developed to provide udder health information that can be used as a decision support tool for the farmer. Among these sensors, the DeLaval Online Cell Counter (DeLaval, Tumba, Sweden) provides somatic cell counts from every milking at cow level. Our aim was to describe and evaluate diagnostic sensor properties of these online cell counts (OCC) for detecting an intramammary infection, defined as an episode of subclinical mastitis or a new case of clinical mastitis. The predictive abilities of a single OCC value, rolling averages of OCC values, and an elevated mastitis risk (EMR) variable were compared for their accuracy in identifying cows with episodes of subclinical mastitis or new cases of clinical mastitis. Detection of subclinical mastitis episodes by OCC was performed in 2 separate groups of different mastitis pathogens, Pat 1 and Pat 2, categorized by their known ability to increase somatic cell count. The data for this study were obtained in a field trial conducted in the dairy herd of the Norwegian University of Life Sciences. Altogether, 173 cows were sampled at least once during a 17-mo study period. The total number of quarter milk cultures was 5,330. The most common Pat 1 pathogens were Staphylococcus epidermidis, Staphylococcus aureus, and Streptococcus dysgalactiae. The most common Pat 2 pathogens were Corynebacterium bovis, Staphylococcus chromogenes, and Staphylococcus haemolyticus. The OCC were successfully recorded from 82,182 of 96,542 milkings during the study period. For episodes of subclinical mastitis the rolling 7-d average OCC and the EMR approach performed better than a single OCC value for detection of Pat 1 subclinical mastitis episodes. The EMR approach outperformed the OCC approaches for detection of Pat 2 subclinical mastitis episodes. For the 2 pathogen groups, the sensitivity of detection of subclinical mastitis episodes was 69% (Pat 1) and 31% (Pat 2), respectively, at a predefined specificity of 80% (EMR). All 3 approaches were equally good at detecting new cases of clinical mastitis, with an optimum sensitivity of 80% and specificity of 90% (single OCC value).

Large-scale cross-sectional study of relationships between somatic cell count and milking-time test results in different milking systems

Milking-time testing (MTT) is a method for evaluating the vacuum conditions in the teatcup during milking. The purpose is to evaluate the possible impact of the milking and milking equipment on udder health and milk quality. The method is commonly implemented by herd health advisory services, but results are interpreted empirically due to lack of scientific documentation on relationships between MTT result variables and objective measures of udder health. The current study was conducted to increase our understanding of associations between cow-level differences in composite milk somatic cell count (CMSCC) and MTT results in dairy cows milked in 3 different milking systems; automatic milking systems (AMS), milking parlors, and pipeline milking systems. Data from 7069 cows (predominantly Norwegian Red breed) in 1009 herds were used in a cross-sectional study. Multilevel linear regression models with a random intercept at herd level were used to describe relationships between CMSCC (on logarithmic scale) and the following MTT explanatory variables: average vacuum level in the short milk tube and mouthpiece chamber in the main milking and overmilking periods, the duration of these two periods, and vacuum stability, measured by sudden vacuum drops in the short milk tube. The models were corrected for the herd effect, mastitis history and differences in milk yield, lactation stage and parity between cows. Separate models were run for AMS, milking parlors, and pipeline milking systems, because this approach allowed for comparison between systems and for evaluation of the herd effect independently of milking system. The models described 8-10 % of the variation in CMSCC, indicating that MTT could only explain a relatively small proportion of a large total variation in CMSCC. In most observations, vacuum levels in the short milk tube during main milking were within the range recommended by the International Organization for Standardization. The results from our multivariable models showed decreasing CMSCC with increasing vacuum level in the short milk tube during the main milking period in AMS and milking parlors. Similarly, decreasing CMSCC was also associated with increasing duration of the main milking period in all 3 systems. These relationships are important for the interpretation of MTT results under practical conditions; finding high vacuum levels and long milking durations in a MTT is not associated with elevated CMSCC. In AMS herds, we also found indications that the relationships were different for cows where a case of mastitis had been treated before the MTT.

Methods for Diagnosing Mastitis

A diagnosis of mastitis is based on clinical observations or direct/indirect measures of the inflammatory response to infection, whereas a diagnosis of an intramammary infection is based on identification of the infectious agent. Somatic cell count/somatic cell score are common diagnostic tests for the detection of subclinical mastitis. Culture and polymerase chain reaction can be useful in the diagnosis of an intramammary infection; however, both have their advantages and disadvantages. Diagnosing the bacterial agent causing the intramammary infection can help to determine treatment and prevention strategies on the farm, which in turn can help to reduce incidence and prevalence.

Relationship between intramammary infection prevalence and somatic cell score in commercial dairy herds

We examined consistency of the relationship between intramammary infection (IMI) and somatic cell score (SCS) across several classes of cow, herd, and sampling time variables. Microbial cultures of composite milk samples were performed by New York Quality Milk Production Services from 1992 to 2004. SCS was from the most recent Dairy Herd Improvement test before IMI sampling. Records were analyzed from 79,308 cows in 1,124 commercial dairy herds representing a broad range of production systems. Three binary dependent variables were presence or absence of contagious IMI, environmental IMI, and all IMI. Independent variables in the initial models were SCS, SCS², lactation number, days in milk, sample day milk yield, use of coliform mastitis vaccine, participant type (required by regulation or voluntary), production system (type of housing, milking system, and herd size), season of sampling, year of sampling, and herd; also the initial models included interactions of SCS and SCS² with other independent variables, except herd and milk yield. Interaction terms characterize differences in the IMI-SCS relationship across classes of the independent variables. Models were derived using the Glimmix macro in SAS (SAS Institute Inc., Cary, NC) with a logistic link function and employing backward elimination. The final model for each dependent variable included all significant independent variables and interactions. Simplified models omitted SCS² and all interactions with SCS. Interactions of SCS with days in milk, use of coliform mastitis vaccine, participant type, season, and year were not significant in any of the models. Interaction of SCS with production system was significant for the all IMI model, whereas interaction of SCS with lactation number was significant for the environmental and all IMI models. Each 1-point increase in SCS (or doubling of somatic cell count) was associated with a 2.3, 5.5, and 9.1% increase in prevalence of contagious, environmental, and all IMI, respectively. Empirical receiver operator characteristic curves and areas under the curve were derived for final and simplified models. The areas under the curve for simplified and final models within each type of IMI differed by 0.009 or less. We concluded that the relationship of IMI with SCS was generally stable over time and consistent across seasons, production systems, and cow factors.

Prevalence of subclinical mastitis in Finnish dairy cows: changes during recent decades and impact of cow and herd factors

Background

The dairy industry has undergone substantial structural changes as intensive farming has developed during recent decades. Mastitis continues to be the most common production disease of dairy cows. Nationwide surveys of mastitis prevalence are useful in monitoring udder health of dairy herds and to study the impact of structural changes on the dairy industry. This survey on bovine subclinical mastitis was the first based on cow composite milk somatic cell count (SCC) data from the Finnish national health monitoring and milk recording database. A cow with composite milk SCC ≥200,000 cells/ml in at least one of the four test milkings during the year was considered to have subclinical mastitis and a cow with composite milk SCC ≥200,000 cells/ml in three or in all four test milkings during the year to have chronic subclinical mastitis. The aim of the study was to determine the prevalence of subclinical mastitis and chronic subclinical mastitis in Finland in 1991, 2001 and 2010 and to investigate cow and herd factors associated with elevated SCC.

Results

Prevalence of subclinical mastitis in Finland decreased over recent decades from 22.3% (1991) and 20.1% (2001) to 19.0% (2010). Prevalence of chronic subclinical mastitis was 20.4% in 1991, 15.5% in 2001 and 16.1% in 2010. The most significant cow and herd factors associated with subclinical mastitis or high milk SCC were increasing parity, Holstein breed, free-stalls with an automatic milking system and organic production. Milk SCC were highest from July to September. Main factors associated with chronic mastitis were increasing parity and Holstein breed.

Conclusions

Prevalence of subclinical mastitis in Finland decreased over recent decades, the greatest change taking place during the first decade of the study. Prevalence of chronic subclinical mastitis significantly decreased from 1991. The most significant factors associated with both types of mastitis were increasing parity and Holstein breed, and for subclinical mastitis also free-stalls with automatic milking. National surveys on mastitis prevalence should be carried out at regular intervals to monitor udder health of dairy cows and to study the impact of the ongoing structural changes in the dairy industry to enable interventions related to udder health to be made when needed.

Electronic supplementary material

The online version of this article (doi:10.1186/s13028-017-0288-x) contains supplementary material, which is available to authorized users.

Validity of somatic cell count as indicator of pathogen-specific intramammary infections

The objective of this study was to determine whether somatic cell count (SCC) was an effective test, with a sensitivity exceeding 85%, to determine species-specific bacterial infections. In addition, the relation between the SCC and various udder pathogen groups was investigated. SCC thresholds of greater than 200 000 cells/mL were used in quarter and greater than 150 000 cells/mL in composite milk samples. A retrospective study was conducted on a data set for 89 635 quarter and 345 467 composite cow milk samples. Eleven SCC threshold values were used to evaluate the diagnostic efficacy for the following bacteria: Gram-positive major pathogens: Staphylococcus aureus, Streptococcus agalactiae, Streptococcus dysgalactiae and Streptococcus uberis; Gram-negative major pathogens: Escherichia coli, Klebsiella pneumonia and Serratia spp.; minor pathogens: coagulase-negative staphylococci, Micrococcus spp., Staphylococcus pseudintermedius, Streptococcus pyogenes, Enterococcus faecalis, Enterococcus canis, Trueperella pyogenes and other Enterobacteriaceae. Sensitivity and specificity were calculated taking the effect of clustering into account with quarter milk samples. Most samples yielding major Gram-positive pathogens (88.9% in quarter and 79.9% in composite samples) and minor pathogens (61.4% in quarter and 51.7% in composite samples) had SCC greater than 200 000 cells/mL. Sensitivity of the SCC test to detect major pathogens at an SCC threshold of greater than 200 000 cells/mL in quarter samples and greater than 150 000 cells/mL in composite milk samples was 88.2% and 84.2%, respectively, but specificity was low (57.7% and 52.8%, respectively).

Somatic cell count and mastitis pathogen detection in composite and single or duplicate quarter milk samples

Abstract: The most acceptable criteria for diagnosing bovine intramammary infections include results of bacteriological culture and measures of inflammation. Therefore, information on the diagnostic characteristics of the procedures used to identify infected quarters is required. Thus, this study was designed to evaluate a set of criteria to classify the infectious status of an udder at the quarter (single and duplicate milk samples) and cow (composite milk sample) levels, and to compare the infectious status with somatic cell counts (SCCs) of the samples. Here, the SCC thresholds determined by receiver operating characteristic curve analysis had a higher Youden index using mammary quarter duplicate milk samples as the gold standard for testing compared with single quarter and composite milk samples, especially for samples for which at least one of the duplicates was microbiologically positive, regardless of the mastitis pathogen isolated. The kappa coefficient for bacteriological results of the single quarter milk samples (single S1 and S2) was 0.85±0.019, indicating that single quarter milk sampling can be useful in mastitis control programs. Therefore, the use of composite milk samples to detect mastitis pathogens may be limited to the detection of major pathogens, given their predictive values. Thus, our findings suggest that the milk SCCs and microbiological examinations, although regarded as the most reliable indicators of ongoing mastitis, should be used in an integrated manner in mastitis control programs. Furthermore, the accuracy of single, duplicate and composite microbiological analyses to diagnosis mastitis should be considered for its implications in mastitis control strategies.

Evaluation of the composite milk somatic cell count as a predictor of intramammary infection in dairy cattle

The objectives of this study were (1) to evaluate the test characteristics and predictive values of quarter-composite milk somatic cell count (quarter-cSCC) values based on either a single observation or the geometric mean of multiple recordings as a predictor of intramammary infection (IMI) in lactating dairy cows; and (2) to explore to what extent herd prevalence of IMI and cow factors such as parity and stage of lactation affect them. A total of 780 single-quarter milk samples were collected from 195 dairy cows for bacteriologic culture at a single cross-sectional herd screening performed at 21 different dairy herds as part of different research projects. Additionally, monthly quarter-cSCC milk samples at test day were available as part of the Dairy Herd Improvement program. Sensitivity (Se), specificity (Sp), positive predictive valu (PPV), and negative predictive value (NPV) were calculated to differentiate cows infected with any pathogen and cows infected with major pathogens from uninfected cows. Different threshold values for quarter-cSCC, ranging between 50,000 and 500,000 cells/mL, were evaluated for all animals in the study, as well as for high- and low-prevalence herds, heifers and multiparous cows, and cows in early, mid, and late lactation. The overall Se and Sp at a threshold of 200,000 cells/mL for a single quarter-cSCC observation obtained closest to the time of bacteriologic culture were 44.3 and 87.3%, respectively, for cows infected with any pathogen, and 65.1 and 73.0%, respectively, for cows infected with major pathogens. The overall PPV and NPV at a threshold of 200,000 cells/mL for a single quarter-cSCC observation obtained closest to the time of bacteriologic culture were 89.9 and 38.1%, respectively, for cows infected with any pathogen, and 40.6% and 88.1%, respectively, for cows infected with major pathogens. No major differences were observed between estimates of the test characteristics and predictive values of the quarter-cSCC criteria based on a single observation and the geometric mean of multiple observations. For IMI with any pathogen, the Se and PPV were higher in high-prevalence herds than in low-prevalence herds, particularly at thresholds of 50,000 and 100,000 cells/mL. For IMI with major pathogens, Sp was substantially higher in low-prevalence herds than in high-prevalence herds. Sensitivity was higher in multiparous cows than in heifers infected with any pathogen, more specifically at a threshold of 100,000 and 200,000 cells/mL. For cows in early and mid lactation infected with any pathogen, Sp was higher than for cows in late lactation using the single observation closest to the time of bacteriologic culture. The results suggest that the quarter-cSCC threshold value to select cows for bacteriologic culture to maximize the likelihood of finding the causative pathogen of IMI should depend on the group of pathogens one is interested in, the herd prevalence of subclinical mastitis, lactation stage, and the cow's parity.

Reproductive performance, udder health, and antibiotic resistance in mastitis bacteria isolated from Norwegian Red cows in conventional and organic farming

Background

The objectives of this study were to investigate whether there were differences between Norwegian Red cows in conventional and organic farming with respect to reproductive performance, udder health, and antibiotic resistance in udder pathogens.

Methods

Twenty-five conventional and 24 organic herds from south-east and middle Norway participated in the study. Herds were matched such that geographical location, herd size, and barn types were similar across the cohorts. All organic herds were certified as organic between 1997 and 2003. All herds were members of the Norwegian Dairy Herd Recording System. The herds were visited once during the study. The relationship between the outcomes and explanatory variables were assessed using mixed linear models.

Results

There were less > 2nd parity cows in conventional farming. The conventional cows had higher milk yields and received more concentrates than organic cows. Although after adjustment for milk yield and parity, somatic cell count was lower in organic cows than conventional cows. There was a higher proportion of quarters that were dried off at the herd visit in organic herds. No differences in the interval to first AI, interval to last AI or calving interval was revealed between organic and conventional cows. There was no difference between conventional and organic cows in quarter samples positive for mastitis bacteria from the herd visit. Milk yield and parity were associated with the likelihood of at least one quarter positive for mastitis bacteria. There was few S. aureus isolates resistance to penicillin in both management systems. Penicillin resistance against Coagulase negative staphylococci isolated from subclinically infected quarters was 48.5% in conventional herds and 46.5% in organic herds.

Conclusion

There were no large differences between reproductive performance and udder health between conventional and organic farming for Norwegian Red cows.