Cases of mastitis (CM) from 38,236 lactations belonging to 16,497 cows were recorded on seven farms in the Czech Republic from 1996 to 2014. Clinical mastitis was analyzed with linear animal model as an all-or-none trait for each recorded lactation (CM305) and separately for each trimester of lactation (CM1, CM2, and CM3). Bivariate linear animal models were used to estimate the genetic correlation between these CM traits and lactation means for somatic cell score (SCS305), the interval between calving and first insemination (INT) and days open (DO). Factors included in the linear model were parity, herd, year of calving, calving season, fixed linear and quadratic regression on age at first calving, fixed linear and quadratic regression on milk production in the corresponding parity, permanent environmental effect of the cow, and additive genetic effect of the cow. Estimated heritabilities of the CM traits ranged from 0.01 to 0.03. Permanent environmental effects accounted for approximately two-thirds of the phenotypic variance. Genetic correlations of SCS305 with CM traits were 0.85±0.029, 0.81±0.086, 0.82±0.087, and 0.67±0.088 for CM305, CM1, CM2, and CM3, respectively. Genetic correlations of INT with CM305, CM1, CM2, and CM3, respectively, were 0.22±0.065, 0.19±0.084, 0.20±0.121 and 0.15±0.121: and genetic correlations of DO and the four CM traits were 0.28±0.079, 0.26±0.101, 0.43±0.134, and 0.15±0.131. For the 140 sires in the dataset, Spearman rank correlations among breeding values for the four CM traits and for SCS305 were uniformly high at 0.99±0.001.
If the inline PDF is not rendering correctly, you can download the PDF file here.
Alam M., Cho C.I., Choi T.J., Park B., Choi J.G., Choy Y.H., Lee S.S., Cho K.H. (2015). Estimation of genetic parameters for somatic cell scores of Holsteins using multi-trait lactation models in Korea. Asian Australas. J. Anim. Sci., 28: 303–310.
Ali A.K.A., Shook G.E. (1980). An optimum transformation for somatic cell concentration in milk. J. Dairy Sci., 63: 487–490.
Buch L.H., Sorensen M.K., Lassen J., Berg P., Jakobsen J.H., Johansson K., Sorensen A.C. (2011). Udder health and female fertility traits are favourably correlated and support each other in multi-trait evaluations. J. Anim. Breed. Genet., 128: 174–182.
Carlén E., Strandberg E., Roth A. (2004). Genetic parameters for clinical mastitis, somatic cell score, and production in the first three lactations of Swedish Holstein cows. J. Dairy Sci., 87: 3062–3070.
Fetrow J. (2000). Mastitis: An economic consideration. Proc. Natl. Mastitis Counc. Mtg., Atlanta, GA. Natl. Mastitis Council, Verona, WI, pp. 3–47.
Fuerst C., Koeck A., Egger-Danner C., Fuerst-Waltl B. (2011). Routine genetic evaluation for direct health traits in Austria and Germany. Proc. Interbull Meeting, 26–28.08.2011, Stavanger, Norway.
Govignon-Gion A., Dassonneville R., Baloche G., Ducrocq V. (2016). Multiple trait genetic evaluation of clinical mastitis in three dairy cattle breeds. Animal, 10: 558–565.
Halasa T., Huijps J., Osteras O., Hogeveen H. (2007). Economic effects of bovine mastitis and mastitis management: A review. Vet. Q., 29: 18–31.
Heringstad B., Klemetsdal G., Ruane J. (2000). Selection for mastitis resistance in dairy cattle: A review with focus on the situation in the Nordic countries. Livest. Prod. Sci., 64: 95–106.
Heringstad B., Rekaya R., Gianola D., Klemetsdal G., Weigel K.A. (2003). Genetic change for clinical mastitis in Norwegian cattle: a threshold model analysis. J. Dairy Sci., 86. 369–375.
Heringstad B., Østerås O. (2013). More than 30 years of health recording in Norway. Proc. ICAR 2013 Health Data Conference: challenges and benefits of health data recording in the context of food chain quality, management and breeding. 30–31.05.2013, Århus, Denmark.
Jamrozik J., Schaeffer L.R. (2012). Test-day somatic cell score, fat-to-protein ratio and milk yield as indicator traits for sub-clinical mastitis in dairy cattle. J. Anim. Breed. Genet., 129: 11–19.
Jamrozik K., Koeck A., Miglior F. (2013). Genetic and genomic evaluation of mastitis resistance in Canada. Interbull Bulletin, 47: 23–26.
Jamrozik J., Koeck A., Kistemaker G.J., Miglior F. (2016). Multiple-trait estimates of genetic parameters for metabolic disease traits, fertility disorders, and their predictors in Canadian Holsteins. J. Dairy Sci., 99: 1990–1998.
Kadarmideen H., Thompson N.R., Simm G. (2000). Linear and threshold model genetic parameters for disease, fertility and milk production in dairy cattle. Anim. Sci., 71: 411–419.
Kadarmideen H., Thompson N.R., Coffey M.P., Kossaibati M.A. (2013). Genetic parameters and evaluations from single- and multiple-trait analysis of dairy cow fertility and milk production. Livest. Prod. Sci., 81: 183–195.
Madsen P., Jensen J. (2010). DMU – a package for analysing multivariate mixed models. Version 6, release 5.0. Aarhus University, Foulum, Denmark. Available from http://dmu.agrsci.dk accessed 1 June 2011.
Negussie E., Koivula M., Mäntysaari E.A. (2006). Genetic parameters and single versus multi-trait evaluation of udder health traits. Acta Agric. Scand, A-Anim. Sci., 56: 73–82.
Negussie E., Strandén I., Mäntysaari E.A. (2007). Genetic analysis of clinical mastitis during different risk periods in Finnish Ayrshire. Agr. Food Sci., 16: 115–123.
Negussie E., Strandén I., Mäntysaari E.A. (2008). Genetic associations of clinical mastitis with test-day somatic cell count and milk yield during first lactation of Finnish Ayrshire. J. Dairy Sci., 91: 1189–1197.
Pérez-Cabal M.A., Charfeddine N. (2013). Genetic relationship between clinical mastitis and several traits of interest in Spanish Holstein dairy cattle. Interbull Bulletin, 47: 77–81.
Pérez-Cabal M.A., delos Campos G., Vazquez A.I., Gianola D., Rosa G.J.M., Weigel K.A., Alenda R. (2009). Genetic evaluation of susceptibility to clinical mastitis in Spanish Holstein cows. J. Dairy Sci., 92: 3472–3480.
Sasaki O., Aihara M., Nishiura A., Takeda H., Satoh M. (2015). Genetic analysis of the cumulative pseudo-survival rate during lactation of Holstein cattle in Japan by using random regression models. J. Dairy Sci., 98: 5781–5795.
Sharma N., Singh N.K., Bhadwal M.S. (2011). Relationship of somatic cell count and mastitis: an overview. Asian Australas. J. Anim. Sci., 24: 429–438.
Sender G., Kakorwin-Kossakowska A., Pawlik A., Abdel Hameed K.G., Oprządek J. (2013). Genetic basis of mastitis resistance in dairy cattle – a review. Ann. Anim. Sci., 13: 663–673.
Vazquez A.I., Gianola D., Bates D., Weigel K.A., Heringstad B. (2009). Assessment of Poisson, logit and linear models for genetic analysis of clinical mastitis in Norwegian Red cows. J. Dairy Sci., 92: 739–748.
Wall E., Brotherstone S., Woolliams J.A., Banos G., Coffey M.P. (2003). Genetic evaluation of fertility using direct and correlated traits. J. Dairy Sci., 86: 4093–4102.
Wolf J., Wolfová M., Štípková M. (2010). A model for the genetic evaluation of number of clinical mastitis cases per lactation in Czech Holstein cows. J. Dairy Sci., 93: 1193–1204.
Wolfová M., Štípková M., Wolf J. (2006). Incidence and economics of clinical mastitis in five Holstein herds in the Czech Republic. Prev. Vet. Med., 77: 48–64.
Zavadilová L., Zink V. (2013). Genetic relationship of functional longevity with female fertility and milk production traits in Czech Holsteins. Czech J. Anim. Sci., 58: 554–565.
Zavadilová L., Štípková M., Šebková N., Svitáková A. (2015). Genetic analysis of clinical mastitis data for Holstein cattle in the Czech Republic. Arch. Anim. Breed., 58: 199–204.
Zink V., Lassen J., Štípková M., (2012). Genetic parameters for female fertility and milk production traits in first-parity Czech Holstein cows. Czech J. Anim. Sci., 57: 108–114.
Zink V., Zavadilová L., Lassen J., Štípková M., Vacek M., Štolc L. (2014). Analyses of genetic relationships between linear type traits, fat-to-protein ratio, milk production traits, and somatic cell count in first-parity Czech Holstein cows. Czech J. Anim. Sci., 59: 539–547.
Zwald N.R., Weigel K.A., Chang Y.M., Welper R.D., Clay J.S. (2006). Genetic analysis of clinical mastitis data from on-farm management software using threshold models. J. Dairy Sci., 89: 330–336.