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Genetic and economic relationships between somatic cell count and clinical mastitis and their use in selection for mastitis resistance in dairy cattle

Published online by Cambridge University Press:  18 August 2016

H. N. Kadarmideen  and
J. E. Pryce
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Abstract

Clinical mastitis (CM) and monthly test-day somatic cell count (SCC) records on Holstein cows were used to investigate the genetic and economic relationship of lactation average (of natural logarithms of) monthly test-day SCC (LSCC) with CM. After editing, there were 23663 lactation records on 17937 cows from 257 herds. Three groups of herds were first identified as having low (L), medium (M) and high (H) incidences of CM from the original or pooled (P) data set. Genetic parameters were estimated for the original and three data sub-sets (derived from the three herd groups). Expected genetic responses to selection against CM were calculated using genetic parameters of each data set separately, with an adapted version of the UK national index (£PLI-profitable lifetime index). Indirect economic values of SCC (EVSCC) were calculated as the direct cost of CM per cow per lactation weighted by the genetic regression coefficient of CM lactation records on their sires’ predicted transmitting ability for SCC (PTASCC). All genetic regression analyses were based on linear and threshold-liability models. Heritabilities and repeatabilities, respectively, were 0034 and 0·111 for CM and 0120 and 0·347 for LSCC in the original data set. Genetic, permanent environmental, residual and phenotypic correlations between CM and LSCC for the original (pooled) data set were 0·70, 0·44, 013 and 0·20, respectively. Parameter estimates for the three herd groups differed, with magnitude of the estimates increasing with increase in incidence from L to H herd groups. The EVSCC per unit of PTASCC for L, M, H and P herd groups, respectively, were £004, £0·15, £0·33 and £018 on the observed and £0·86, £0·96, £1·22 and £110 on the underlying-liability scales. Selection for mastitis resistance, using SCC as an indicator trait in an extended version of £PLI, resulted in a selection response of 0·9, 21, 1·7 and 1·9 more cases per 100 cows after 10 years of selection in L, M, H and P herd groups, respectively. These results suggest that genetic responses to selection for CM resistance as well as the EVSCC are specific to herd incidence and hence would be appropriate for customized selection indexes. The increase in CM cases was greater when CM was excluded from the £PLI (2·8 v 1·9), hence it is recommended that CM should be included in the breeding goal in order to arrest further decline or to make improvement in genetic resistance to clinical mastitis.

Keywords

dairy cattleeconomic valuesgenetic parametersmastitissomatic cell count.
Type
Breeding and genetics
Information
Animal Science , Volume 73 , Issue 1 , August 2001 , pp. 19 - 28
Copyright
Copyright © British Society of Animal Science 2001

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References

Banos, G. 1999. From research to application: a summary of scientific developments and possible implementation to the genetic improvement for functional traits. Proceedings of the workshop on genetic improvement of functional traits (GIFT) meeting, 7 to 9 November 1999, Ede/Wageningen, The Netherlands.Google Scholar
Boettcher, P. J., Dekkers, J. C. M. and Kolstad, B. W. 1998. Development of an udder health index for sire selection based on somatic cell score, udder conformation, and milking speed. Journal of Dairy Science 81: 1157–1168.Google Scholar
Bowman, P. J., Visscher, P. M. and Goddard, M. E. 1996. Customized selection indices for dairy bulls in Australia. Animal Science 62: 393–403.Google Scholar
Brotherstone, S., Veerkamp, R. F. and Hill, W. G. 1998. Predicting breeding values for herd life of Holstein Friesian dairy cattle from lifespan and type. Animal Science 67: 405–412.CrossRefGoogle Scholar
Castillo-Juarez, H., Oltenacu, P. A., Blake, R. W., McCulloch, C. E. and Cienfuegos-Rivas, E.G. 2000. Effect of herd environment on the genetic and phenotypic relationships among milk yield, conception rate and somatic cell score in Holstein cattle. Journal of Dairy Science 83: 807–814.Google Scholar
Foulley, J. L. 1992. Prediction of selection response for threshold dichotomous traits. Genetics 132: 1187–1194.CrossRefGoogle ScholarPubMed
Gates, P., Johansson, K. and Danell, B. 1999. “Quasi-REML” correlation estimates between production and health traits in the presence of selection and confounding: a simulation study. Journal of Animal Science 77: 558–568.Google Scholar
Gianola, D. 1982. Theory and analysis of threshold characters. Journal of Animal Science 56: 1079–1096.Google Scholar
Gilmour, A. R., Cullis, B. R., Welham, S. J. and Thompson, R. 1998. ASREML user’s manual, October 1998. New South Wales Agriculture, Orange Agricultural Institute, Orange, NSW, Australia.Google Scholar
Heringstad, B., Klemetsdal, G. and Ruane, J. 1999. Clinical mastitis in Norwegian cattle: frequency, variance components, and genetic correlation with protein yield. Journal of Dairy Science 82: 1325–1330.CrossRefGoogle ScholarPubMed
Kadarmideen, H. N., Janss, L. L. G. and Dekkers, J. C. M. 2000a. Power of quantitative trait locus mapping for polygenic binary traits using generalized and regression interval mapping in multi-family half-sib designs. Genetical Research 76: 305–317.Google Scholar
Kadarmideen, H. N., Rekaya, R. and Gianola, D. 2000b. Genetic analysis of mastitis in dairy cattle with a Bayesian threshold model. Proceedings of the British Society of Animal Science, 2000, p. 16.Google Scholar
Kadarmideen, H. N., Rekaya, R. and Gianola, D. 2000c. Genetic analysis of repeated mastitis episodes with Bayesian longitudinal threshold models. Proceedings of the 51st annual meeting of the European Association for Animal Production (EAAP), 21-24 August 2000, The Hague, The Netherlands.Google Scholar
Kadarmideen, H. N., Thompson, R. and Simm, G. 2000d. Linear and threshold model genetic parameters for disease, fertility and milk production in dairy cattle. Animal Science 71: 411–419.CrossRefGoogle Scholar
Kossaibati, M. A. and Esslemont, R. J. 1997. Cost of production diseases in dairy herds in England. Veterinary Journal 154: 41–51.CrossRefGoogle ScholarPubMed
Lindhe, B. and Philipsson, J. 2001. The Scandinavian experience of including reproductive traits in breeding programmes. In Fertility in the high producing dairy cow (ed. Diskin, M. G.) British Society of Animal Science occasional publication no. 26, pp. 251–262.Google Scholar
Lund, M. S., Jensen, J. and Petersen, P. H. 1999. Estimation of genetic and phenotypic parameters for clinical mastitis, somatic cell production deviance, and protein yield in dairy cattle using Gibbs sampling. Journal of Dairy Science 82: 1045–1051.Google Scholar
Mrode, R. A. and Swanson, G. J. T. 1996. Genetic and statistical properties of somatic cell count and its suitability as an indirect means of reducing the incidence of CM in dairy cattle. Animal Breeding Abstracts 64: 847–856.Google Scholar
Mrode, R. A., Swanson, G. J. T. and Winters, M. S. 1998. Genetic parameters and evaluations for somatic cell counts and its relationship with production and type traits in some dairy breeds in the United Kingdom. Animal Science 66: 569–576.Google Scholar
Philipsson, J., Banos, G. and Arnason, T. 1994. Present and future uses of selection index methodology in dairy cattle. Journal of Dairy Science 77: 3252–3261.Google Scholar
Philipsson, J., Ral, G. and Berglund, B. 1995. Somatic cell count as a selection criterion for CM resistance in dairy cattle. Livestock Production Science 41: 195–200.Google Scholar
Pösö, J. and Mäntysaari, E. A. 1996. Relationship between clinical mastitis, somatic cell score, and production for the first three lactations of Finnish Ayrshire. Journal of Dairy Science 79: 1284–1291.Google Scholar
Pryce, J. E. and Brotherstone, S. 1999. Estimation of lifespan breeding values in the UK and their relationship with health and fertility traits. Proceedings of the workshop on genetic improvement of functional traits (GIFT) meeting, Paris, May 1999. Interbull Bulletin 21: 166–169.Google Scholar
Pryce, J. E., Coffey, M. P., Simm, G., Brotherstone, S., Hill, W. G. and Stott, A. W. 1999a. Sustainable breeding goals: genetic and economic aspects of selection for yield, reproduction and body tissue utilisation. In Scottish Agricultural College final report, September 1999, p. 35.Google Scholar
Pryce, J. E., Simm, G., Amer, P., Coffey, M. and Stott, A. 1999b. Returns from genetic improvement on indices that include production, longevity, CM and fertility in UK circumstances. Proceedings of the workshop on genetic improvement of functional traits (GIFT) meeting, 7 to 9 November 1999, Ede/Wageningen, The Netherlands.Google Scholar
Pryce, J. E., Veerkamp, R. F. and Simm, G. 1998. Expected correlated responses in health and fertility traits to selection on production in dairy cattle. Proceedings of the sixth world congress on genetics applied to livestock production, Armidale, Australia, January 1998, vol. 23, pp. 383–386.Google Scholar
Pryce, J. E., Veerkamp, R. F., Thompson, R., Hill, W. G. and Simm, G. 1997. Genetic aspects of common health disorders and measures of fertility in Holstein Friesian dairy cattle. Animal Science 65: 353–360.Google Scholar
Robertson, A. and Rendel, J. M. 1950. The use of progeny testing with artificial insemination in dairy cattle. Journal of Genetics 50: 21–31.Google Scholar
Rupp, R. and Boichard, D. 1999. Genetic parameters for CM, somatic cell score, production, udder type traits, and milking ease in first lactation Holsteins. Journal of Dairy Science 82: 2198–2204.Google Scholar
Shook, G. E. and Schutz, M. M. 1994. Selection on somatic cell score to improve resistance to mastitis in the United States. Journal of Dairy Science 77: 648–658.Google Scholar
Stott, A. W., Gunn, G., Humphry, R., Berry, R., Richardson, H. and Logue, D. 2000. The economic value of somatic cell counts. Proceedings of the British Society of Animal Science, 2000, p. 110.Google Scholar
Uribe, H. A., Kennedy, B. W., Martin, S. W. and Kelton, D. F. 1995. Genetic parameters of common health disorders of Holsteins. Journal of Dairy Science 78: 421–430.Google Scholar
Van Tassell, C. P., Van Vleck, L. D. and Gregory, K. E. 1999. Bayesian analysis of twinning and ovulation rates using multiple-trait threshold model and Gibbs sampling. Journal of Animal Science 76: 2048–2061.Google Scholar
Veerkamp, R. F., Stott, A. W., Hill, W. G. and Brotherstone, S. 1998. The economic value of somatic cell count payment schemes for UK dairy cattle breeding programmes. Animal Science 66: 293–298.Google Scholar
Weller, J. I. and Ezra, E. 1997. Genetic analysis of somatic cell score and female fertility of Israeli Holsteins with an individual animal model. Journal of Dairy Science 80: 586–593.CrossRefGoogle ScholarPubMed
Weller, J. L., Saran, A. and Zeliger, Y. 1992. Genetic and environmental relationships among somatic cell count, bacterial infection and clinical mastitis. Journal of Dairy Science 75: 2532–2540.Google Scholar