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Estimation of genetic parameters using health, fertility and production data from a management recording system for dairy cattle

Published online by Cambridge University Press:  02 September 2010

J. E. Pryce
Affiliation:
Genetics and Reproduction Department, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG
R. J. Esslemont
Affiliation:
Department of Agriculture, Earley Gate, University of Reading RG6 6AT
R. Thompson
Affiliation:
Statistics Department, Institute of Arable Crops Research (IACR), Rothamsted, Harpenden AL5 2JQ
R. F. Veerkamp
Affiliation:
Genetics and Reproduction Department, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG
M. A. Kossaibati
Affiliation:
Department of Agriculture, Earley Gate, University of Reading RG6 6AT
G. Simm
Affiliation:
Genetics and Reproduction Department, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG
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Abstract

The Dairy Information System (DAISY) was developed to record fertility and health information for use in research and to help farmers manage their farms. Data from 33 herds recording health and fertility over a 6-year period were used to study genetic relationships of several health, fertility and production traits. There were 10 569 records from 4642 cows of all parities. These were used to estimate genetic parameters for health: mastitis, lameness and somatic cell score (SCS), for fertility: calving interval, days to first service, conception to first service and for production: 305-day milk, butterfat and protein yields. Heritabilities for these traits were also estimated for the first three lactations. (Co)variances were estimated using linear, multitrait restricted maximum likelihood (REML) with an animal model. Mastitis and lameness were treated as all-or-none traits. The incidence of these diseases increased with lactation number, which may lead to variance component estimation problems, as the mean is linked to the variance in binomial distributions. Therefore, a method was used to fix the within-lactation variance to one in all lactations while maintaining the same mean. The heritability for SCS across lactations was 0·15. Heritabilities for other health and fertility traits were low and ranged between 0·013 and 0·047. All genetic correlations with the production traits were antagonistic implying that selection for yield may have led to a deterioration in health and fertility. The genetic correlation between SCS and mastitis was 0·65 indicating that indirect selection for improvements in mastitis may be achieved using somatic cell counts as a selection criterion. The potential use of linear type scores as predictors of the health traits was investigated by regressing health traits on sire predicted transmitting abilities for type. The results indicate that some type traits may be useful as future selection criteria.

Type
Research Article
Copyright
Copyright © British Society of Animal Science 1998

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References

Ali, A. K. A. and Shook, G. E. 1980. An optimum transformation for somatic cell count concentration in milk. Journal of Dairy Science 63:487490.CrossRefGoogle Scholar
Arendonk, J. A. M. van, Hovenier, R. and Boer, W. de. 1989. Phenotypic and genetic association between fertility and production in dairy cows. Livestock Production Science 21: 112.Google Scholar
Banos, G. 1996. Survey on genetic evaluation procedures for functional traits in cattle in various countries. Proceedings of an international workshop on genetic improvement of functional traits in cattle, Gembloux, Belgium (ed. Groen, A. F., Solkner, J., Strandberg, E. and Gengler, N.). Interbull Bulletin 12: 1124.Google Scholar
Boelling, D. and Pollott, G. 1997. The genetics of feet, legs and locomotion in cattle. Animal Breeding Abstracts 65: 111.Google Scholar
Brotherstone, S. 1994. Genetic and phenotypic correlations between linear type traits and production traits in HolsteinFriesian dairy cattle. Animal Production 59: 183188.Google Scholar
Brotherstone, S. and Hill, W. G. 1986. Heterogeneity of variance amongst herds for milk production. Animal Production 42: 297303.Google Scholar
Brotherstone, S. and Hill, W. G. 1991. Dairy herd life in relation to linear type traits and production. 1. Phenotypic and genetic analyses in pedigree type classified herds. Animal Production 53: 279287.Google Scholar
Emanuelson, U. 1988. Recording of production diseases in cattle and possibilities for genetic improvement: a review. Livestock Production Science 20: 89106.CrossRefGoogle Scholar
Eriksson, J. A. and Wretler, E. 1990. Sire evaluation for diseases in Sweden. World Review of Animal Production 25: 2932.Google Scholar
Esslemont, R. J. 1993. The development of decision support systems in agriculture: DAISY — The dairy information system. University of Reading, study no. 30.Google Scholar
Esslemont, R. J. and Kossaibati, M. A. 1997. Culling in 50 dairy herds in England. Veterinary Record 140: 3639.CrossRefGoogle ScholarPubMed
Forshell, K. P., Osteras, O., Aagaard, K. and Kulkas, L. 1995. Disease recording and cell count data in 1993 in Sweden, Norway, Denmark and Finland. The third international mastitis seminar, 29 May-1 June 1995, Tel Aviv, Israel.Google Scholar
Groeneveld, E. 1996. REML VCE a multivariate multi model restricted maximum likelihood (co)variance component estimation package version 3.2 user's guide. Federal Research Centre of Agriculture, Mariensee, Germany.Google Scholar
Hoekstra, J., Lugt, A. W. van der, Werf, J. H. J. van der and Ouweltjes, W. 1994. Genetic and phenotypic parameters for milk production and fertility traits in upgraded dairy cattle. Livestock Production Science 40: 225232.CrossRefGoogle Scholar
Holstein Friesian Society of Great Britain and Ireland. 1995. Focus on type. Holstein Friesian Journal 77: 6471.Google Scholar
Kossaibati, M. A. and Esslemont, R. J. 1995. Wastage in dairy herds. DAISY report no. 4, University of Reading.Google Scholar
Lawes Agricultural Trust. 1993. Genstat 5, version 5.3 reference manual. Clarendon Press, London.Google Scholar
Lund, T., Miglior, F., Dekkers, J. C. M. and Burnside, E. B. 1994. Genetic relationships between clinical mastitis, somatic cell count and udder conformation in Danish Holsteins. Livestock Production Science 39: 243251.CrossRefGoogle Scholar
Lyons, D. T., Freeman, A. E. and Kuck, A. L. 1991. Genetics of health traits. Journal of Dairy Science 74: 10921100.CrossRefGoogle ScholarPubMed
Mrode, R. A., Swanson, G. J. T. and Winters, M. S. 1995. Genetic parameters for somatic cell counts (SCC) for three dairy breeds in the United Kingdom. Animal Science 60: 545 (abstr.).Google Scholar
Oltenacu, P. A., Frick, A. and Lindhe, B. 1991. Relationship of fertility to milk yield in Swedish cattle. Journal of Dairy Science 71: 264268.CrossRefGoogle Scholar
Peeler, E. J., Otte, M. J. and Esslemont, R. J. 1994. Inter-relationships of periparturient diseases in dairy cows. Veterinary Record 5: 129132.CrossRefGoogle Scholar
Philipsson, J., Ral, G. and Berglund, B. 1995. Somatic cell count as a selection criterion for mastitis resistance in dairy cattle. Livestock Production Science 41: 195200.CrossRefGoogle Scholar
Poso, J. and Mantysaari, E. A. 1996a. Relationships between clinical mastitis, somatic cell score, and production for the first three lactations of Finnish Ayrshire. Journal of Dairy Science 79: 12841291.CrossRefGoogle ScholarPubMed
Poso, J. and Mantysaari, E. A. 1996b. Genetic relationships between reproductive disorders, operational days open and milk yield. Livestock Production Science 46: 4148.CrossRefGoogle 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: 353360.CrossRefGoogle Scholar
Robertson, A. and Lerner, I. M. 1949. The heritability of allor-none traits: liability of poultry. Genetics 34: 395411.CrossRefGoogle Scholar
Rogers, G. W., Hargrove, G. L. and Cooper, J. B. 1995. Correlations among somatic cell scores of milk within and across lactations and linear type traits of Jerseys. Journal of Dairy Science 78: 914920.CrossRefGoogle ScholarPubMed
Rogers, G. W., Hargrove, G. L., Lawlor, T. J. and Ebersole, J. L. 1991. Correlations among linear type traits and somatic cell counts. Journal of Dairy Science 74: 10871091.CrossRefGoogle ScholarPubMed
Schutz, M. M. 1994. Genetic evaluation of somatic cell counts for United States dairy cattle. Journal of Dairy Science 77: 21132129.CrossRefGoogle ScholarPubMed
Shearer, J. K., Schmidt, R. H. and Reneau, J. K. 1992. Monitoring milk quality and udder health. In Large dairy herd management (ed. Horn, H. H. Van and Wilcox, C. J.), pp. 475486. American Dairy Science Association, USA.Google Scholar
Solbu, H. and Lie, O. 1990. Selection for disease resistance in dairy cattle. Proceedings of the fourth world congress on genetics applied to livestock production, Edinburgh, vol. XVI, pp. 445448.Google Scholar
Strandberg, E., Groen, A. F. and Solkner, J. 1996. General introduction. Proceedings of an international workshop on genetic improvement of functional traits in cattle, Gembloux, Belgium (ed. Groen, A. F., Solkner, J., Strandberg, E. and Gengler, N.). Interbull Bulletin 12: 510.Google Scholar
Uribe, H. A., Kennedy, B. W., Martin, S. W. and Kelton, D. F. 1995. Genetic parameters for common health disorders of Holsteins. Journal of Dairy Science 78: 421430.CrossRefGoogle Scholar
Veerkamp, R. F., Hill, W. G., Stott, A. W., Brotherstone, S. and Simm, G. 1995. Selection for longevity and yield in dairy cows using transmitting abilities for type and yield. Animal Science 61: 189198.CrossRefGoogle Scholar