Field Survey of Clinical Mastitis in Low Somatic Cell Count Herds

Hogan, J.S.; Smith, Kenneth L.; Hoblet, Kent H.; Schoenberger, P.S.; Todhunter, D.A.; Hueston, William D.; Pritchard, Dave; Bowman, G. L.; Heider, Lawrence E.; Brockett, B. L.; Conrad, H.R.

doi:10.3168/jds.s0022-0302(89)79266-3

Cited by 208 publications

(120 citation statements)

References 13 publications

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“…Preventive programs that address all important udder health components are necessarily complex and dynamic. These programs will need to include components of the standard mastitis prevention plan (milking technique and milking machine performance, post-milking teat disinfection, culling policy for chronically infected animals, antibiotic treatment at dry-off and clinical events) [32], but additionally address hygiene, nutrition, housing and cow comfort, air and water quality, antibiotic use, health monitoring, breeding policy, and cow characteristics such as immunologic competence, cow conformation (teat and udder) and milk production level [21,41,48,61]. In each of these categories, a number of critical issues should be defined, and included into a comprehensive control scheme.…”

Section: Resultsmentioning

confidence: 99%

Monitoring udder health and milk quality using somatic cell counts

et al. 2003

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-In this article the use of somatic cell counts for monitoring udder health and milk quality is discussed. Somatic cell count dynamics at quarter, cow, herd and population level are discussed and illustrated with examples. Quarter and cow somatic cell counts directly represent the inflammatory status of the mammary gland. Herd and population somatic cell count are related to the inflammatory process in individual cows but much more reflect the udder health status of the herd and the quality of the raw milk in the herd and the population. Application of monitoring tools in herd health management are illustrated using a case study. Understanding infection dynamics requires precise longitudinal data. Monitoring tools are required to find the areas of risk in the herd. It is inevitable that more complete udder health programs and monitoring systems are to be developed and implemented. These programs are necessarily dynamic and complex. Implementation of complete udder health programs should be accompanied by research efforts to further fine-tune these complete udder health control and monitoring programs. somatic cell count / mastitis / milk quality / monitoring / epidemiology

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Section: Resultsmentioning

confidence: 99%

Monitoring udder health and milk quality using somatic cell counts

et al. 2003

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“…A high percentage of I.M. infections present at parturition also develop into clinical mastitis during the first 60 to 70 days of lactation [104]. The early postpartum period is a period of high risk for severe clinical mastitis because of extreme sensitivity for a number of animals for I.M.…”

Section: Stage Of Lactationmentioning

confidence: 99%

Severity of E. coli mastitis is mainly determined by cow factors

et al. 2003

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-Intramammary infections of dairy cows with Gram-positive bacteria such as Staphylococcus aureus (major cause of mastitis) have received a lot of attention because of their major economic impact on the dairy farm through production losses induced by an increase in somatic cell count. Management strategies, including greater awareness for efficient milking and hygienic measures, have limited the spread of Gram-positive bacteria and resulted in a significant decrease of proportion of S. aureus isolates and subclinical mastitis worldwide. Other organisms such as coliform subspecies and Streptococcus uberis, both environmental bacteria that cause clinical mastitis, have received less attention. Escherichia coli causes inflammation of the mammary gland in dairy cows around parturition and during early lactation with striking local and sometimes severe systemic clinical symptoms. This disease affects many high producing cows in dairy herds and may cause several cases of death per year in the most severe cases. It is well known that bacterial, cow and environmental factors are interdependent and influence mastitis susceptibility. Many studies, executed during the last decade, indicate that the severity of E. coli mastitis is mainly determined by cow factors rather than by E. coli pathogenicity. During E. coli mastitis, the host defense status is a cardinal factor determining the outcome of the disease. Today, we know that the neutrophil is a key factor in the cows' defense against intramammary infection with E. coli. Effective elimination of the pathogen by neutrophils is important for the resolution of infection and the outcome of E. coli mastitis. This review is a compilation of some major findings over the last 15 years concerning mainly host factors that modulate and influence neutrophil function and the mammary inflammatory reaction. The individual chapters address: virulence factors of E. coli strains, how neutrophils kill E. coli, connection between endotoxins, tumor necrosis factor-a and nitric oxide, severity classification of E. coli mastitis, lifespan of neutrophils, host factors that influence severity, tissue damage and production loss.

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“…These findings indicate that different genes operate at different parts of lactation. Pathogen-specific differences in the mastitis incidence over the course of lactation have been reported (Hogan et al, 1989). Different pathogens might initiate different defense mechanisms, resulting in differences in genetic correlations of CM across the lactation.…”

Section: Random Regression Models For Clinical Mastitismentioning

confidence: 99%

Random regression models for genetic evaluation of clinical mastitis in dairy cattle

Carlén

Grandinson

Emanuelson

et al. 2009

Animal

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A genetic analysis of longitudinal binary clinical mastitis (CM) data recorded on about 90 000 first-lactation Swedish Holstein cows was carried out using linear random regression models (RRM). This method for genetic evaluation of CM has theoretical advantages compared to the method of linear cross-sectional models (CSM), which is currently being used. The aim of this study was to investigate the feasibility and suitability of estimating genetic parameters and predicting breeding values for CM with a linear sire RRM. For validation purposes, the estimates and predictions from the RRM were compared to those from linear sire longitudinal multivariate models (LMVM) and CSM. For each cow, the period from 10 days before to 241 days after calving was divided into four 1-week intervals followed by eight 4-week intervals. Within each interval, presence or absence of CM was scored as '1' or '0'. The linear RRM used to explain the trajectory of CM over time included a set of explanatory variables plus a third-order Legendre polynomial function of time for the sire effect. The time-dependent heritabilities and genetic correlations from the chosen RRM corresponded fairly well with estimates obtained from the linear LMVM for the separate intervals. Some discrepancy between the two methods was observed, with the more unstable results being obtained from the linear LMVM. Both methods indicated clearly that CM was not genetically the same trait throughout lactation. The correlations between predicted sire breeding values from the RRM, summarized over different time periods, and from linear CSM were rather high. They were, however, less than unity (0.74 to 0.96), which indicated some re-ranking of sires. Sire curves based on the time-specific breeding values from the RRM illustrated differences in intercept and slope among the best and the worst sires. To conclude, a linear sire RRM seemed to work well for genetic evaluation purposes, but was sensitive for estimation of genetic parameters.Keywords: dairy cattle, genetic evaluation, clinical mastitis, random regression model ImplicationsLinear random regression models (RRM) were used as a new longitudinal approach for genetic evaluation of clinical mastitis data in dairy cattle. This approach has theoretical advantages compared to the method of linear cross-sectional models (CSM) currently used. The estimated genetic parameters and predicted breeding values from the RRM were in good agreement with the results from linear longitudinal multivariate and linear CSM. However, the RRM approach was sensitive to parameter estimation in the current setting.

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Field Survey of Clinical Mastitis in Low Somatic Cell Count Herds

Cited by 208 publications

References 13 publications

Monitoring udder health and milk quality using somatic cell counts

Monitoring udder health and milk quality using somatic cell counts

Severity of E. coli mastitis is mainly determined by cow factors

Random regression models for genetic evaluation of clinical mastitis in dairy cattle

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