Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-24T14:01:22.217Z Has data issue: false hasContentIssue false
  • English
  • Français

Developing breeding objectives for beef cattle production 1. A bio-economic simulation model

Published online by Cambridge University Press:  02 September 2010

H. Hirooka ,
A. F. Groen  and
J. Hillers
H. Hirooka
Affiliation:
Faculty of Economics, Ryukoku University, 612–8577 Kyoto, Japan
A. F. Groen
Affiliation:
Department of Animal Breeding, Wageningen Institute of Animal Sciences, PO Box 338, 6700 AH Wageningen, The Netherlands
J. Hillers
Affiliation:
Department of Animal Sciences, Washington State University, Pullman 99164, USA
Get access

Abstract

A deterministic simulation model was constructed to develop breeding objectives and estimate biological and economic values. The model simulates life-cycle production of a breeding cow and growth performance of her offspring. Input variables are divided into four categories: animal traits, nutritional variables, management variables and economic variables. The economic variables assume typical beef cattle production in Japan. The outputs from the model include cow-calf performance, feedlot performance and biological and economic efficiency. The model's ability to simulate herd composition, food intake of cow and calves, cow body-weight changes, empty body and carcass composition of feedlot animals and production efficiencies is illustrated.

Keywords

beef cattlebody compositionbreeding objectivescarcass compositionsimulation models
Type
Research Article
Information
Animal Science , Volume 66 , Issue 3 , June 1998 , pp. 607 - 621
Copyright
Copyright © British Society of Animal Science 1998

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

Agricultural Research Council. 1980. The nutrient requirement of ruminant livestock. Commonwealth Agricultural Bureaux, Farnham Royal, Slough.Google Scholar
Azzam, S. M., Azzam, A. M., Nielsen, M. K. and Kinder, J. E. 1990a. Markov chains as a shortcut method to estimate age distributions in herds of beef cattle under different culling strategies, journal of Animal Science 68: 5–14.CrossRefGoogle ScholarPubMed
Azzam, S. M., Kinder, J. E. and Nielsen, M. K. 1990b. Modelling reproductive management systems for beef cattle. Agricultural Systems 34: 103–122.CrossRefGoogle Scholar
Bailie, J. H. 1982. The influence of breeding management efficiency on dairy herd performance. Animal Production 34: 315–323.Google Scholar
Berg, R. T. and Butterfield, R. M. 1976. New concepts of cattle growth. University of Sydney Press, Sydney.Google Scholar
Bond, J., Warwick, E. J., Oltjen, R. R., Putnam, P. A., Hiner, R. L., Kotula, A. W. and Weinland, B. T. 1982. Effects of feeding level on growth, composition of gain, carcass quality and mature body size in steers at ages up to six years. Growth 46: 388–403.Google ScholarPubMed
Bourdon, R. M. and Brinks, J. S. 1982. Genetic, environmental and phenotypic relationships among gestation length, birth weight, growth traits and age at first calving in beef cattle. Journal of Animal Science 55: 543–553.Google Scholar
Bourdon, R. M. and Brinks, J. S. 1987. Simulated efficiency of range beef production. I. Growth and milk production.Journal of Animal Science 65: 943–955.CrossRefGoogle ScholarPubMed
Brody, S. 1945. Bioenergetics and growth. Reinhold, New York. Cartwright, T. C. 1979. The use of systems analysis in animal science with emphasis on animal breeding. Journal of Animal Science 49: 817–825.Google Scholar
CSIRO. 1990. Feeding standards for Australian livestock: ruminant (ed. Corbett, J. L.). Standing Committee on Agriculture, Ruminant Sub-Committee, CSIRO, Melbourne.Google Scholar
Davis, K. C., Tess, M. W., Kress, D. D., Doornbos, D. E. and Anderson, D. C. 1994. Life cycle evaluation of five biological types of beef cattle in a cow-calf range production system. I. Model development. Journal of Animal Science 72: 2585–2590.CrossRefGoogle Scholar
Dent, J. B. and Blackie, J. R. 1979. Systems simulation in agriculture. Applied Science Publishers, London.CrossRefGoogle Scholar
Dickerson, G. E. 1970. Efficiency of animal production — molding the biological components. Journal of Animal Science 30: 849–859.CrossRefGoogle Scholar
Ferrell, C. L., Garrett, W. N. and Hinman, N. 1976. Estimation of body composition in pregnant and non-pregnant heifers, journal of Animal Science 42: 1158–1166.CrossRefGoogle Scholar
Fox, D. G. and Black, J. R. 1984. A system for predicting body composition and performance of growing cattle. Journal of Animal Science 58: 725–739.Google Scholar
Fukuhara, R., Moriya, K. and Harada, H. 1989. [Estimation of genetic parameters and sire evaluation for carcass characteristics with special reference to yield grade of the new beef carcass grading standards.] Japanese Journal of Zootechnical Science 60: 1128–1134.Google Scholar
Garrett, W. N. and Hinman, N. 1969. Re-evaluation of the relationship between carcass density and body composition of beef steers, journal of Animal Science 28: 1–5.Google Scholar
Garrett, W. N. and Johnson, D. E. 1983. Nutritional energetics of ruminants. Journal of Animal Science 57: (suppl. 2) 478–497.Google Scholar
Groen, A. F. 1989. Economic values in cattle breeding. I. Influence of production circumstances in situations without output limitations. Livestock Production Science 22: 1–16.CrossRefGoogle Scholar
Harris, D. L. 1970. Breeding for efficiency in livestock production: defining the economic objectives. Journal of Animal Science 30: 860–865.CrossRefGoogle Scholar
Harris, D. L., Stewart, T. S. and Arboleda, C. R. 1984. Animal breeding programs: a systematic approach to their design. AAT-NC-8, Agricultural Research Service, United States Department of Agriculture, Peoria, IL.Google Scholar
Hazel, L. N. 1943. The genetic basis for constructing selection indexes. Genetics 28: 476–490.Google Scholar
Hill, W. G. 1974. Predictions and evaluation of responses to selection with overlapping generations. Animal Production 18: 117–140.Google Scholar
Hirooka, H., Groen, A. F. and Hillers, J. 1998. Developing breeding objectives for beef cattle production. 2. Biological and economic values of growth and carcass traits in Japan. Animal Science 66: 623–633.CrossRefGoogle Scholar
Hirooka, H. and Yamada, Y. 1989. A comparison of simulation models based on ARC metabolizable energy system and NRC net energy system with special reference to growing steers. Asian-Australasian Journal of Animal Science 2: 599–605.Google Scholar
Hirooka, H. and Yamada, Y. 1990. A general simulation mode for cattle growth and beef production. Asian-Australasian Journal of Animal Science 3: 205–218.CrossRefGoogle Scholar
Hirooka, H., Yamada, Y., Dahlan, I. and Miyazaki, A. 1989. Between-breed differences of carcass composition in cattle. Asian-Australasian Journal of Animal Science 2: 607–613.Google Scholar
Johnson, M. H. and Notter, D. R. 1987. Simulation of genetic control of reproduction in beef cows. 1. Simulation model. Journal of Animal Science 65: 68–75.CrossRefGoogle ScholarPubMed
Kahn, H. E. 1982. The development of a simulation model and its use in the evaluation of cattle production systems. Ph.D. thesis, University of Reading.Google Scholar
Keele, J. W., Williams, C. B. and Bennett, G. L. 1992. A computer model to predict the effects of levels of nutrition on composition of empty body gain in beef cattle. 1. Theory and development. Journal of Animal Science 70: 841–857.CrossRefGoogle ScholarPubMed
Korver, S., Tess, M. W. and Johnson, T. 1988. A model of growth and growth composition for beef bulls of different breeds. Agricultural Systems 27: 279–294.CrossRefGoogle Scholar
Lamb, M. A., Tess, M. W. and Robison, O. W. 1992. Evaluation of mating systems involving five breeds for integrated beef production systems I. Cow-calf segment. Journal of Animal Science 70: 689–699.Google Scholar
Laster, D. B., Glimp, H. A., Cundiff, L. V. and Gregory, K. E. 1973. Factors affecting dystocia and the effects of dystocia on subsequent reproduction in beef cattle. Journal of Animal Science 36: 695.CrossRefGoogle ScholarPubMed
Lunt, D. K., Riley, R. R. and Smith, S. B. 1993. Growth and carcass characteristics of Angus and American Wagyu steers. Meat Science 34: 327–334.CrossRefGoogle ScholarPubMed
Ministry of Agricultural, Fisheries and Food. 1987. [Japanese feeding standards. Beef cattle.] Central Association of Livestock Industry, Tokyo.Google Scholar
Ministry of Agricultural, Fisheries and Food. 1993. [Livestock production survey 1992.] Tokyo.Google Scholar
Murray, D. M., Tulloh, N. M. and Winter, W. H. 1975. The effect of three different growth rates on the chemical composition of the dressed carcass of cattle and the relationships between chemical and dissected components. Journal of Agricultural Science, Cambridge 85: 309–314.CrossRefGoogle Scholar
National Research Council. 1984. Nutrient requirements of beef cattle, sixth edition. National Academic Press, Washington, DC.Google Scholar
Oltenacu, P. A., Milligan, R. A., Rounsaville, T. R. and Foote, R. H. 1980. Modelling reproduction in a herd of dairy cattle. Agricutural Systems 5: 193–205.Google Scholar
Oltjen, J. W., Bywater, A. C. and Baldwin, R. L. 1986. Development of a dynamic model of beef cattle growth and composition, journal of Animal Science 62: 86–97.Google Scholar
Ponzoni, R. W. 1986. Economic evaluation of breeding objectives in sheep and goats — summary and commentary. Proceedings of the third world congress on genetics applied to livestock production, Lincoln, vol. 9, pp. 465–469.Google Scholar
Ruvuna, F., Taylor, J. F., Walter, J. P., Turner, J. W. and Thallman, R. M. 1992. Bioeconomic evaluation of embryo transfer in beef production systems. 1. Description of a biological model for steer production. Journal of Animal Science 70: 1077–1083.CrossRefGoogle Scholar
Sanders, J. O. and Cartwright, T. C. 1979a. A general cattle production systems model. 1. Structure of the model. Agricultural Systems 4: 217–227.CrossRefGoogle Scholar
Sanders, J. O. and Cartwright, T. C. 1979b. A general cattle production systems model. 2. Procedures used for simulating animal performance. Agricultural Systems 4: 289–309.Google Scholar
Stewart, T. S. and Martin, T. G. 1983. Optimum mature size of Angus cows for maximum cow productivity. Animal Production 37: 179–182.Google Scholar
Taylor, St C. S. 1985. Use of genetic size-scaling in evaluation of animal growth. Journal of Animal Science 61: (suppl. 2) 118–143.CrossRefGoogle Scholar
Taylor, St C. S., Moore, A. J., Thiessen, R. B. and Bailey, C. M. 1985. Efficiency of food utilization in traditional and sex controlled systems of beef production. Animal Production 40: 401–440.Google Scholar
Tess, M. W., Bennett, G. L. and Dickerson, G. E. 1983. Simulation of genetic changes in life cycle efficiency of pork production. II. Effects of components on efficiency. Journal of Animal Science 56: 354–368.Google Scholar
Wagner, J. J., Lusby, K. S., Oltjen, J. W., Rakestraw, J., Wettemann, R. P. and Walters, L. E. 1988. Carcass composition in mature Hereford cows: estimation and effect on daily metabolizable energy requirement during winter, journal of Animal Science 66: 603–612.Google Scholar
Wang, C. T. and Dickerson, G. E. 1991. Simulation of life-cycle efficiency of lamb and wool production for genetic levels of component traits and alternative management options. Journal of Animal Science 69: 4324–4337.CrossRefGoogle Scholar
Williams, C. B., Bennett, G. L. and Keele, J. W. 1995. Simulated influence of postweaning production system on performance of different biological types of cattle. II. Carcass composition, retail product, and quality, journal of Animal Science 73: 674–685.Google Scholar
Wood, P. D. P. 1967. Algebraic model of the lactation curve in cattle. Nature, London 216: 164–165.CrossRefGoogle Scholar
Yamazaki, T. 1981. The effect of age and fatness on meat quality and quantity of beef cattle. Bulliten of Natural Grassland Research Institute 18: 69–77.Google Scholar
Yang, M., Mukai, F. and Sasaki, Y. 1985. [Estimation of heritability for growth and carcass traits and their genetic and phenotypic correlations in Japanese Black cattle.] Japanese Journal of Zootechnical Science 56: 193–198.Google Scholar