Hostname: page-component-76fb5796d-vvkck Total loading time: 0 Render date: 2024-04-26T07:50:23.552Z Has data issue: false hasContentIssue false

Including lameness and mastitis in a profit index for dairy cattle

Published online by Cambridge University Press:  09 March 2007

A. W. Stott*
Affiliation:
Animal Health Economics Team, Land Economy Group, Scottish Agricultural College, Bucksburn, Aberdeen AB21 9YA, UK
M. P. Coffey
Affiliation:
Sustainable Livestock Systems, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG, UK
S. Brotherstone
Affiliation:
Sustainable Livestock Systems, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG, UK
*
Get access

Abstract

The objective of this work was to establish economic values (EVs) of mastitis and lameness in order to enhance the current UK dairy profit index (£PLI) by including these health traits. The EVs of traits currently in £PLI were also re-evaluated to account for changes in costs/returns over time and to determine their sensitivity to changes in some of the basic assumptions used in their derivation.

Predicted transmitting abilities (PTAs) for mastitis are not available in the UK. Instead, PTAs for somatic cell count (SCC), which has a strong genetic correlation with clinical mastitis, were used to predict clinical mastitis. Similarly, PTAs for locomotion and (for bulls with no locomotion PTA) the ‘legs and feet’ composite were used to predict lameness.

The EV of mastitis was estimated at £0·83 per percent incidence, giving an index weight for SCC PTA of £0·20. The EV of lameness was estimated at £0·99 per percent incidence, giving an index weight for locomotion PTA of £1·28. The associated index weight for the ‘legs and feet’ composite was estimated to be £1·50. Economic values for all traits (production, lifespan, mastitis and lameness) were found to be sensitive to their associated price assumption but not to price assumptions of other traits in the index or to other production parameters in the model.

Better information is needed on the influence of cow age (parity) on incidence of disease and on the probability of involuntary culling to determine the appropriate balance between the EVs for longevity and health. Currently, 16% of the weight in £PLI is attributable to non-production traits. In our revised index this weight increased to 23%. Even so, selection using this index is still predicted to result in an increase in mastitis and lameness, albeit at a very low rate. This situation may be changed by the introduction of fertility into £PLI and through better information about health traits. Incorporation of consumer preference into £PLI may require traits associated with health and welfare of the cow to receive more weight than their EV would suggest in order to maintain or improve health traits in national selection programmes.

Type
Research Article
Copyright
Copyright © British Society of Animal Science 2005

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Arendonk, J. A. M. van. 1985 a. Studies on the replacement policies in dairy cattle. II. Optimum policy and in. uence of changes in production and prices. Livestock Production Science 13: 101121.CrossRefGoogle Scholar
Arendonk, J. A. M. van. 1985 b. A model to estimate the performance, revenues and costs of dairy cows under different production and price situations. Agricultural Systems 16: 157189.Google Scholar
Arendonk, J. A. M. van. 1990. Use of profit equations to determine relative economic value of dairy cattle herd life and production from field data. Journal of Dairy Science 74: 11011107.CrossRefGoogle Scholar
Bennett, R. M. 2003. The ‘direct’ costs of livestock disease: the development of a system of models for the analysis of 30 endemic livestock diseases in Great Britain. Journal of Agricultural Economics 54: 5572.CrossRefGoogle Scholar
Bennett, R. M., Christiansen, K. and Clifton-Hadley, R. S. 1999. Modelling the impact of livestock disease on production: case studies of non-notifiable diseases of farm animals in Great Britain. Animal Science 68: 681689.CrossRefGoogle Scholar
Bevan, K. 2003. OTMS decision deferred. SAC Monthly Economic Review 29(10): 45.Google Scholar
Brotherstone, S., Thompson, R. and White, I. M. S. 2004. Effects of pregnancy on daily milk yield of Holstein-Friesian dairy cattle. Livestock Production Science 87: 265269.Google Scholar
Clarkson, M. J., Downham, D. Y., Faull, W. B., Hughes, J. W., Manson, F. J., Merritt, J. B., Murray, R. D., Russell, W. B., Sutherst, J. E. and Ward, W. R. 1996. Incidence and prevalence of lameness in dairy cattle. Veterinary Record 138: 563567.Google Scholar
Cohen, S. S. 1985. Operational research. Edward Arnold, London.Google Scholar
Collard, B. L., Boettcher, P. J., Dekkers, J. C. M., Peticlerc, D. and Schaeffer, L. R. 2000. Relationships between energy balance and health traits of dairy cattle in early lactation. Journal of Dairy Science 83: 26832690.CrossRefGoogle ScholarPubMed
Dekkers, J. C. M. 1991. Estimation of economic values for dairy cattle breeding goals: bias due to sub-optimal management policies. Livestock Production Science 29: 131149.CrossRefGoogle Scholar
Forbes, D., Gayton, S. and McKeogh, B. 1999. Longevity report. Kingshay Farming Trust. Ref: 97/R1/12. Milk Development Council, Cirencester.Google Scholar
Garnsworthy, P. C. 2004. The environmental impact of fertility in dairy cows: a modelling approach to predict methane and ammonia emissions. Animal Feed Science and Technology 112: 211223.CrossRefGoogle Scholar
Groen, A. F. 1990. Influences of production circumstances on the economic revenue of cattle breeding programmes. Animal Production 51: 469480.Google Scholar
Groen, A. F., Steine, T., Colleau, J.-J., Pedersen, J., Pribyl, J. and Reinsch, N. 1997. Economic values in dairy cattle breeding, with special reference to functional traits. Report of an EAAP working group. Livestock Production Science 49: 121.CrossRefGoogle Scholar
Harvey, D. R. 1990. Agricultural sector modelling for policy development. In Systems theory applied to agriculture and the food chain(ed. Jones, J. and Street, P.), pp. 251304. Elsevier, London.Google Scholar
Hazel, L. N. 1943. The genetic basis for constructing selection in dexes. Genetics 28: 476490.CrossRefGoogle Scholar
Hirst, W., Murray, R., Ward, W. and French, N. 2002. Generalised additive models and hierarchical logistic regression of lameness in dairy cows. Preventive Veterinary Medicine 55: 3746.CrossRefGoogle ScholarPubMed
Juga, J., Mántysaari, E. A. and Pösö, J. 1999. Economic response to total merit selection in Finnish Ayrshire breeding. Proceedings of an international workshop on EU Concerted Action on Genetic Improvement of Functional Traits in Cattle, Wageningen, The Netherlands.Google Scholar
Kadarmideen, H. N. and Pryce, J. E. 2001. Genetic and economi crelationships between somatic cell count and clinical mastitis and their use in selection for mastitis resistance in dairy cattle. Animal Science 73: 1928.CrossRefGoogle Scholar
Kadarmideen, H. N., Rekaya, R. and Gianola, D. 2001. Genetic parameters for clinical mastitis in Holstein-Friesians in the United Kingdom: a Bayesian analysis. Animal Science 73: 229240.Google Scholar
Kennedy, J. O. S. 1986. Dynamic programming: applications to agriculture and natural resources. Elsevier Applied Science, London.CrossRefGoogle Scholar
Kossaibati, M. A. and Esslemont, R. J. 1995. Wastage in dairy herds, DAISY- The dairy information system. Report no. 4. University of Reading, Reading.Google Scholar
KPMG. 2003. Prices and profitability in the British Dairy Chain. Report to the Milk Development Council. Milk Development Council, Cirencester. http: //www. mdcdatum. org. uk/PDF/KPMG%20Report. pdfGoogle Scholar
McInerney, J. P. 1996. Old economics for new problems. Journal of Agricultural Economics 47: 295314.CrossRefGoogle Scholar
McInerney, J. P., Howe, K. S. and Schepers, J. A. 1992. A framework for the economic analysis of disease in farm livestock. Preventive Veterinary Medicine 13: 137154.CrossRefGoogle Scholar
Matthews, L. R. 1996. Animal welfare and sustainability of production under extensive conditions: A non-EU perspective. Applied Animal Behaviour Science 49: 4146.Google Scholar
Milk Development Council. 2002. Profitable life index-£PLI. MDC Evaluations Ltd, Cirencester. http: //www. mdcevaluations. co. uk/ publications/factsheetpli. htmGoogle Scholar
Milk Development Council. 2004. MDC datum market information service. Milk Development Council, Cirencester. http: //www. mdcdatum. org. uk/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: 569576.CrossRefGoogle Scholar
Offer, J. E., McNulty, D. and Logue, D. N. 2000. Observations of lameness, hoof conformation and development of lesions in dairy cattle over four lactations. Veterinary Record 147: 105109.CrossRefGoogle ScholarPubMed
Olesen, I., Groen, A. F. and Gjerde, B. 2000. Definition of animal breeding goals for sustainable production systems. Journal of Animal Science 78: 570582.CrossRefGoogle ScholarPubMed
Pedersen, J., Nielsen, U. S. and Aamand, G. P. 2002. Economic values in the Danish Total Merit Index. Proceedings of the 2002 Interbull Meeting, Interlaaken, Switzerland.Google Scholar
Policy Commission on the Future of Farming and Food. 2002. Farming and food: a sustainable future. Cabinet Office, London. http: //www. cabinet-of. ce. gov. uk/farming.Google Scholar
Rajala-Schultz, P. J., Gröhn, Y. T., McCulloch, C. E. and Guard, C. L. 1999. Effects of clinical mastitis on milk yield in dairy cows. Journal of Dairy Science 82: 12131220.Google Scholar
Rauw, W. M., Kanis, E., Noordhuizen-Stassen, E. N. and Grommers, F. J. 1998. Undesirable side effects of selection for high production ef. ciency in farm animals: a review. Livestock Production Science 56: 1533.Google Scholar
Robertson, A. and Rendel, J. M. 1950. The use of progeny testing with artificial insemination in dairy cattle. Journal of Genetics50: 2131.CrossRefGoogle ScholarPubMed
Rogers, G. W., Arendonk van, J. A. M. and McDaniel, B. T. 1988. Influence of involuntary culling on optimum culling rates and annualized net revenues. Journal of Dairy Science 71: 34633469.Google Scholar
Rowlands, J. G., Russell, A. M. and Williams, L. A. 1985. Effects of stage of lactation, month, age, origin and heart girth on lameness in dairy cattle. The Veterinary Record 117: 576580.CrossRefGoogle ScholarPubMed
Royal, M. D., Darwash, A. O., Flint, A. P. F., Webb, R., Woolliams, J. A. and Lamming, G. E. 2000. Declining fertility in dairy cattle: changes in traditional and endocrine parameters of fertility. Animal Science 70: 487501.Google Scholar
Rupp, R. and Boichard, D. 1999. Genetic parameters for clinical mastitis, somatic cell score, production, udder type traits, and milking ease in first lactation Holsteins. Journal of Dairy Science 82: 21982204.Google Scholar
Santarossa, J. M., Stott, A. W., Woolliams, J. A., Brotherstone, S., Wall, E. and Coffey, M. P. 2004. An economic evaluation of longterm sustainability in the dairy sector. Animal Science 79: 315325.Google Scholar
Schepers, J. A. and Dijhuizen, A. A. 1991. The economics of mastitis and mastitis control in dairy cattle: a critical analysis of estimates published since 1970. Preventive Veterinary Medicine 10: 213224.CrossRefGoogle Scholar
Scottish Agricultural College. 2002. Farm management handbook2002/3. SAC, EdinburghGoogle Scholar
Simm, G., 1998. Genetic improvement of cattle and sheep. CABI, Wallingford.Google Scholar
Smith, C. 1983. Effects of changes in economic weights on the efficiency of index selection. Journal of Animal Science 56: 10571064.CrossRefGoogle Scholar
Smith, C. 1985. Scope for selecting many breeding stocks of possible economic value in the future. Animal Production 41: 403412.Google Scholar
Stott, A. W. 1994. The economic advantage of longevity in the dairy cow. Journal of Agricultural Economics 45: 113122.Google Scholar
Tweddle, J. 2004. Milk-review of the year. SAC Monthly Economic Survey 30(12): 910.Google Scholar
Veerkamp, R. F., Dillon, P., Kelly, E., Cromie, A. R. and Groen, A. F. 2002. Dairy cattle breeding objectives combining yield, survival and calving interval for pasture-based systems in Ireland under different milk quota scenarios. Livestock Production Science 76: 137151.Google 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: 189197.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: 293298.CrossRefGoogle Scholar
Wall, E., Brotherstone, S., Woolliams, J. A., Banos, G. and Coffey, M. P. 2003. Genetic evaluation of fertility using direct and correlated traits. Journal of Dairy Science 86: 40934102.Google Scholar