Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-24T12:55:47.940Z Has data issue: false hasContentIssue false

Predicting the effects of animal variation on growth and food intake in growing pigs using simulation modelling

Published online by Cambridge University Press:  02 September 2010

N. S. Ferguson
Affiliation:
Department of Animal Science and Poultry Science, University of Natal, PO Box 375, Pietermaritzburg, 3200, South Africa
R. M. Gous
Affiliation:
Department of Animal Science and Poultry Science, University of Natal, PO Box 375, Pietermaritzburg, 3200, South Africa
G. C. Emmans
Affiliation:
Genetics and Behavioural Sciences Department, Scottish Agricultural College Edinburgh, Kings Buildings, West Mains Road, Edinburgh EH9 3JC
Get access

Abstract

All pig nutrition models to date predict growth responses of either an individual animal or the average animal of a given population over time. Translating the predicted nutrient requirements from the average animal to the population introduces a number of errors as the cause-and-effect response of the average animal is different from the population response. To overcome the problem of estimating the requirements for a given population using models it is necessary to simulate a number of individuals representative of a population and then average these results. This approach however, requires a knowledge of those animal characteristics that vary between individuals and the nature of their distribution. In this paper a scaled growth rate constant (B*), protein weight at maturity (Pm) and the ratio of lipid to protein at maturity (LPRm) are the parameters used to define an individual animal. As no data existed from which the nature of the distribution of B*, Pm and LPRm can be estimated for pigs of different strains and sexes, and due to the impracticality of determining this variability by experimentation, a simulation model was used to estimate the variations within each parameter. In addition this paper quantifies the subsequent effects these distributions have on the genetic variability of average daily gains (ADG) and daily food intake (TI) over a live-weight range of 25 to 90 kg. Comparisons were made between the genetic variation determined by modelling and those published in the literature. The results indicated coefficients of variation for B*, Pm and LPRm of 0·01, 0·05 and 0·10, respectively. An increase in the variability of all three parameters resulted in an increase in the variation in ADG whilst only an increase in the variation of B* and LPRm affected the distribution of FI.

Type
Research Article
Copyright
Copyright © British Society of Animal Science 1997

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

Black, J. L., Campbell, R. G., Williams, I. H., James, K. J. and Davies, G. T. 1986. Simulation of energy and amino acid utilisation in the pig. Research and Development in Agriculture 3: 121145.Google Scholar
Black, J. L., Flemming, J. F. and Davies, G. T. 1989. Role of computer simulation in the application of knowledge to the animal industries. Proceedings of the 50th Minnesota nutrition conference, pp. 518.Google Scholar
Bridges, T. C., Turner, L. W., Smith, E. A., Stahly, T. S. and Loewer, O. J. 1986. A mathematical procedure for estimating animal growth and body composition. Transactions of the American Society of Agricultural Engineering 29: 13421347.CrossRefGoogle Scholar
Cameron, N. D. 1990. Comparison of Duroc and British Landrace pigs and the estimation of genetic and phenotypic parameters for growth and carcass traits. Animal Production 50: 141153.Google Scholar
Cameron, N. D. and Curran, M. K. 1994. Selection for components of efficient lean growth rate in pigs. 4. Genetic and phenotype parameter estimates and correlated responses in performance test traits with ad libitum feeding. Animal Production 59: 281291.Google Scholar
Cameron, N. D., Curran, M. K. and Thompson, R. 1988. Estimation of sire with feeding regime interactions in pigs. Animal Production 46: 8795.Google Scholar
Campbell, R. G. and Dunkin, A. C. 1983. The influence of protein nutrition in early life on growth and development of the pig. 1. Effects on growth performance and body composition. British Journal of Nutrition 50: 605618.CrossRefGoogle ScholarPubMed
Curnow, R. N. 1973. A smooth population response curve based on an abrupt threshold and plateau model for individuals. Biometrics 29: 110.Google Scholar
Ellis, M., Chadwick, J. P., Smith, W. C. and Laird, R. 1988. Index selection for improved growth and carcass characteristics in a population of Large White pigs. Animal Production 46: 265275.Google Scholar
Emmans, G. C. 1988. Genetic components of potential and actual growth. In Animal breeding opportunities. British Society of Animal Production, occasional publication no. 12, pp. 153181.Google Scholar
Emmans, G. C. and Fisher, C. 1986. Problems in nutritional theory. In Nutrient requirements of poultry and nutritional research (ed. Fisher, C. and Boorman, K. N.), pp. 939. Butterworths, London.Google Scholar
Ferguson, N. S. and Gous, R. M. 1993a. Evaluation of pig genotypes. 1. Theoretical aspects of measuring genetic parameters. Animal Production 56: 233243.Google Scholar
Ferguson, N. S. and Gous, R. M. 1993b. Evaluation of pig genotypes. 2. Testing experimental procedure. Animal Production 56: 245249.Google Scholar
Ferguson, N. S., Gous, R. M. and Emmans, G. C. 1994. Preferred components for the construction of a new simulation model of growth, feed intake and nutrient requirements of growing pigs. South African Journal of Animal Science 24: 1017.Google Scholar
Groebner, D. S. and Shannon, P. W. 1989. Business statistics. Nerrill Publishers, London.Google Scholar
McPhee, C. P., Brennan, P. J. and Duncalfe, F. 1979. Genetic and phenotypic parameters of Australian Large White and Landrace boars performance-tested when offered food ad libitum. Animal Production 28: 7985.Google Scholar
Minitab, . 1994. Minitab reference manual, release 10 for Windows. State College, Pennsylvania.Google Scholar
Moughan, P. J., Smith, W. C. and Pearson, G. 1987. Description and validation of a model simulating growth in the pig (20–90 kg liveweight). New Zealand Journal of Agricultural Research 30: 481490.CrossRefGoogle Scholar
Mrode, R. A. and Kennedy, B. W. 1993. Genetic variation in measures of food efficiency in pigs and their genetic relationships with growth rate and backfat. Animal Production 56: 225232.Google Scholar
Phillips, P. A. and MacHardy, F. V. 1982. Modelling protein and lipid gains in growing pigs exposed to low temperature. Canadian Journal ofAnimal Science 62: 109121CrossRefGoogle Scholar
Pomar, C., Harris, D. L. and Minvielle, F. 1991. Computer simulation model of swine production systems. I. Modeling the growth of young pigs. Journal of Animal Science 69: 14681488.CrossRefGoogle ScholarPubMed
Rinaldo, D. and Le Dividich, J. 1991. Assessment of optimal temperature for performance and chemical body composition of growing pigs. Livestock Production Science 29: 6174.CrossRefGoogle Scholar
Roux, C. Z. 1976. A model for the description and regulation of growth and production. Agroanimalia 8: 8394.Google Scholar
Standal, N. and Vangen, O. 1985. Genetic variation and covariation in voluntary feed intake in pig selection programmes. Livestock Production Science 12: 367377.CrossRefGoogle Scholar
Stewart, T. S. and Schinckel, A. P. 1989. Genetic parameters for swine growth and carcass traits. In Genetics of swine (ed. Young, L. D.), NC-103 research project, Roman Hruska Research Center, Clay Center, Nebraska, USA, pp. 77105.Google Scholar
Taylor, St C. S. 1968. Time taken to mature in relation to mature weight for sexes, strains and species of domesticated mammals and birds. Animal Production 10: 157169.Google Scholar
Whittemore, C. T. 1993. The science and practice of pig production. Longman Scientific and Technical, Essex, UK.Google Scholar
Whittemore, C. T. and Fawcett, R. H. 1976. Theoretical aspects of a flexible model to simulate protein and lipid growth in pigs. Animal Production 22: 8796.Google Scholar
Wyllie, D., Morton, J. R. and Owen, J. B. 1979. Genetic aspects of voluntary food intake in the pig and their association with gain and food conversion efficiency. Animal Production 28: 381390.Google Scholar