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The economics of fertility in the dairy herd

Published online by Cambridge University Press:  18 August 2016

A. W. Stott
Affiliation:
Management Division, Scottish Agricultural College, Craibstone Estate, Aberdeen AB21 9YA
R. F. Veerkamp*
Affiliation:
Animal Biology Division, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG
T. R. Wassell
Affiliation:
Food Systems Division, Scottish Agricultural College, Auchincruive, Ayr KA6 5HW
*
Present address: ID-DLO, PO Box 65, 8200 AB Lelystad, The Netherlands.
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Abstract

A method to establish the economic optimum (minimum) cost of fertility in the dairy herd is described and demonstrated. A Markov chain model is used iteratively to establish the gross margin of the herd in the long term at various levels of oestrous detection rate and under two different rebreeding strategies. These gross margins are required by the optimization methodology. Under the initial assumptions reflecting current commercial practice in the United Kingdom, gross margin was £806 per cow. This figure varied by proportionately 0·15 over the range of oestrous detection rates assumed (0·4 to 0·7) while delaying rebreeding by 20 days caused gross margin to drop by approximately 0·04. It was concluded that it is important to optimize fertility control as well as rebreeding strategy in order to establish the economic impact of fertility in the dairy herd.

The economic value of fertility was also expressed per unit of calving interval and adjusted calving interval (ACI). ACI was calculated by dividing calving interval by the proportion of cows not culled for reproductive failure. Under the assumptions made, the marginal value of calving interval at the optimum oestrous detection rate was £6·22 per day, rising to £7·44 per day if rebreeding was delayed. The corresponding figures for ACI were £1·57 per day and £1·24 per day. The range in marginal values at sub-optimal oestrous detection rates were £4·38 for calving interval and £0·61 for ACI. It was concluded that the lower variation in ACI at different levels of fertility may make it a more representative trait for inclusion in a selection index provided the necessary genetic parameters can be reliably estimated.

Type
Research Article
Copyright
Copyright © British Society of Animal Science 1999

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References

Agrawal, R. C. and Heady, E. O. 1972. Operations research methods for agricultural decisions. Iowa State University Press, Ames.Google Scholar
Amer, P. R. and Fox, G. C. 1992. Estimation of economic weights in genetic improvement using neoclassical production theory: an alternative to rescaling. Animal Production 54: 341350.Google Scholar
Arendonk, J. A. M. van. 1985. A model to estimate the performance, revenues and costs of dairy cows under different production and price situations. Agricultural Systems 16: 157189.CrossRefGoogle Scholar
Arendonk, J. A. M. van and Dijkhuizen, A. A. 1985. Studies on the replacement policies in dairy cattle. III. Influence of variation in reproduction and production. Livestock Production Science 13: 333349.CrossRefGoogle Scholar
Boehlje, M. D. and Eidman, V. R. 1984. Farm management. John Wiley and Sons, New York.Google Scholar
Boichard, D. 1990. Estimation of the economic value of conception rate in dairy cattle. Livestock Production Science 24: 187204.Google Scholar
Bright, G. 1991. Economic weights from profit equations: appraising their accuracy. Animal Production 53: 395398.Google Scholar
Collins, J. D. 1995. Animal welfare on dairy farms. Irish Veterinary Journal 48: 145147.Google Scholar
Darwash, A. O., Lamming, G. E. and Woolliams, J. A. 1997. The phenotypic association between the interval to post-partum ovulation and traditional measures of fertility in dairy cattle. Animal Science 65: 916.Google Scholar
Debertin, D. L. 1986. Agricultural production economics. Macmillan, New York.Google Scholar
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.Google Scholar
DeLorenzo, M. A., Spreen, T. H., Bryan, G. R., Beede, D. K. and Arendonk, J. A. M. van. 1992. Optimizing model: insemination, replacement, seasonal production, and cashflow, journal of Dairy Science 75: 885896.Google Scholar
Dijkhuizen, A. A., Stelwagen, J. and Renkema, J. A. 1986. A stochastic model for the simulation of management decisions in dairy herds, with special reference to production, reproduction, culling and income. Preventive Veterinary Medicine 4: 273289.CrossRefGoogle Scholar
Emmans, G. C. 1994. Effective energy: a concept of energy utilisation applied across species. British journal of Nutrition 71: 801821.Google Scholar
Esslemont, R. J. 1992. Measuring dairy herd fertility. Veterinary Record 131: 209212.Google Scholar
Esslemont, R. J. 1993. Relationship between herd calving to conception interval and culling rate for failure to conceive. Veterinary Record 133: 14.CrossRefGoogle ScholarPubMed
Esslemont, R. J. and Peeler, E. J. 1993. The scope for raising margins in dairy herds by improving fertility and health. British Veterinary journal 149: 537547.Google Scholar
Goodall, E. A. and McMurray, C. H. 1984. An integration of mathematical models for feeding and lactation with reproductive performance of the dairy cow. Animal Production 38: 341349.Google Scholar
Hady, P. J., Lloyd, J. W., Kaneene, J. B. and Skidmore, A. L. 1994. Partial budget model for reproductive programs of dairy farm businesses, journal of Dairy Science 77: 482491.CrossRefGoogle Scholar
Hazel, L. N. 1943. The genetic basis for constructing selection indexes. Genetics 28: 476490.Google Scholar
Jalvingh, A. W., Arendonk, J. A. M. van and Dijkhuizen, A. A. 1993a. Dynamic probabilistic simulation of dairy herd management practices. I. Model description and outcome of different seasonal calving patterns. Livestock Production Science 37: 107131.Google Scholar
Jalvingh, A. W., Arendonk, J. A. M. van, Dijkhuizen, A. A. and Renkema, J. A. 1993b. Dynamic probabilistic simulation of dairy herd management practices. II. Comparison of strategies in order to change a herd’s calving pattern. Livestock Production Science 37: 133152.Google Scholar
Kossaibati, M. A. and Esslemont, R. J. 1995. Wastage in dairy herds. Report no. 4, DAISY — The Dairy Information System. University of Reading, Reading, UK.Google Scholar
Kristensen, A. R. 1994. A survey of Markov decision programming techniques applied to the animal replacement problem. European Review of Agricultural Economics 21: 7393.CrossRefGoogle Scholar
McInerney, J. P. 1996. Old economics for new problems: livestock disease: presidential address. Journal of Agricultural Economics 47: 295314.Google 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: 14.Google Scholar
Mainland, D. D. 1994. A decision support system for dairy farmers and advisors. Agricultural Systems 45: 217231.Google Scholar
Plaizier, J. C. B. King, G. J., Dekkers, J. C. M. and Lissemore, K. 1997. Estimation of economic values of indices for reproductive performance in dairy herds using computer simulation. Journal of Dairy Science 80: 27752783.CrossRefGoogle ScholarPubMed
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.Google Scholar
Radostits, O. M. and Blood, D. C. 1985. Herd health: a textbook of health and production management of agricultural animals. Saunders, W. B., Philadelphia.Google Scholar
Scottish Agricultural College. 1996. Farm management handbook. Scottish Agricultural College, Edinburgh.Google Scholar
Sorensen, J. T., Kristensen, E. S. and Thysen, I. 1992. A stochastic model simulating the dairy herd on a PC. Agricultural Systems 39: 14.Google Scholar
Stott, A. W. 1996 Stochastic dynamic programming as a framework for decision support in dairy farming. In Livestock farming systems: research development socio-economics and the land manager. E AAP publication no. 79, pp. 315321.Google Scholar
Stott, A. W., Veerkamp, R. F. and Emmans, G. C. 1995. Assessing the economic value of longevity in the UK dairy cow. Scottish Agricultural Economics Review 8: 99106.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: 189198.CrossRefGoogle Scholar
Weiler, J. I. and Folman, Y. 1990. Effects of calf value and reproductive management on optimum days to first breeding. Journal of Dairy Science 73: 13181326.Google Scholar
Williams, M. E. and Esslemont, R. J. 1993. A decision support system using milk progesterone tests to improve fertility in commercial dairy herds. Veterinary Record 133: 503506.CrossRefGoogle Scholar
Wood, P. H. P. 1967. Algebraic model of the lactation curve in cattle. Nature, London 216: 14.Google Scholar
Woolliams, J. A. and Wilmut, I. 1989. Embryo manipulation in cattle breeding and production. Animal Production 48: 330.CrossRefGoogle Scholar
Yalcin, C., Stott, A. W., Gunn, J. and Logue, D. N. 1997. An economic assessment of the impacts of mastitis control procedures used in Scottish dairy herds. Proceedings of the Society for Veterinary Epidemiology and Preventive Medicine, Chester, 9-11 April 1997, pp. 208222.Google Scholar
Yates, C. M., Rehman, T. and Chamberlain, A. T. 1996. Evaluation of the potential effects of embryo transfer on milk production on commercial dairy herds: the development of a Markov chain model. Agricultural Systems 50: 6579.Google Scholar