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Describing and predicting potential growth in the pig

Published online by Cambridge University Press:  18 August 2016

I. J. Wellock ,
G. C. Emmans  and
I. Kyriazakis
I. J. Wellock*
Affiliation:
Animal Health Research Group, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG, UK
G. C. Emmans
Affiliation:
Animal Health Research Group, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG, UK
I. Kyriazakis
Affiliation:
Animal Health Research Group, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG, UK
*
† E-mail: [email protected]
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Abstract

Most animal growth models contain an explicit growth function. It determines the pattern of growth over the lifetime of the animal and defines an upper limit to growth rate (the potential). The criterion of the ‘goodness-of-fit’ to one or more sets of data is frequently used to select a suitable growth function. Alternative criteria are described here that can be used to choose between forms that describe potential growth. Of the functions reviewed only a few fulfilled all of the proposed criteria. Of these the Logistic and Gompertz functions were favoured because of an economy of parameters and their ability to describe relative growth rate as a simple function of size. The Logistic function was rejected on the grounds of its numerical consequences for growth in pigs over a wide range of degrees of maturity, leaving the Gompertz function to be tested for its ability to make sensible predictions of potential growth. Pre-natal growth data, assumed to occur under non-limiting conditions as long as the mother is not subjected to extremely adverse nutritional conditions or incidence of infection, were used to estimate the values of the two Gompertz function parameters-the growth coefficient and the initial condition-given an estimate of mature size. The values were comparable with literature estimates based on post-natal growth and predictions of growth rate over a wide range of degree of maturity were thus sensible. On these grounds, and because it uses few parameters all with biological meaning, the Gompertz function is proposed as a suitable descriptor of potential growth.

Keywords

growthpigs
Type
Growth, development and meat science
Information
Animal Science , Volume 78 , Issue 3 , June 2004 , pp. 379 - 388
Copyright
Copyright © British Society of Animal Science 2004

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References

Bastianelli, D. and Sauvant, D. 1997. Modelling the mechanisms of pig growth. Livestock Production Science 51: 97–107.CrossRefGoogle Scholar
Bertalanffy, L. von. 1957. Quantitative laws for metabolism and growth. Quarterly Reviews of Biology 32: 217–232.Google Scholar
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: 121–145.Google Scholar
Black, J. L., Davies, G. T., Bray, H. R. and Chapple, R. P. 1995. Modelling the effect of genotype, environment and health on nutrient utilisation. Proceedings of the fourth international workshop on modelling nutrient utilisation in farm animals (ed. Danfaer, A. and Lescoat, P.), pp. 85–105. National Institute of Animal Science, Tjele, Denmark.Google Scholar
Bridges, T. C., Turner, L. W., Smith, E. M., Stahly, T. S. and Loewer, O. J. 1986 A mathematical procedure for estimating animal growth and body composition. Transactions of the American Association of Agricultural Engineers 29: 1342–1347.Google Scholar
Bridges, T. C., Turner, L. W., Stahly, T. S., Usry, J. L. and Loewer, O. J. 1992a. Modelling the physiological growth of swine. I. Model logic and growth concepts. Transactions of the American Association of Agricultural Engineers 35: 1019–1028.Google Scholar
Bridges, T. C., Turner, L. W., Stahly, T. S., Usry, J. L. and Loewer, O. J. 1992b. Modelling the physiological growth of swine. II. Validation of model logic and growth concepts. Transactions of the American Association of Agricultural Engineers 35: 1029–1033.Google Scholar
Brody, S. 1945. Bioenergetics and growth. Rheinhold Publishing, New York.Google Scholar
Bureau, D. P., Azevedo, P. A., Salazar, M. T. and Cuzon, G. 2000. Pattern and cost of growth and nutrient deposition in fish and shrimp: potential implications and applications. Avances en Nutrición Acuicola V, Mexico (abstr. ).Google Scholar
Campbell, R. G. and Taverner, M. R. 1988. Genotype and sex effects on the relationship between energy intake and protein deposition in growing pigs. Journal of Animal Science 66: 676–686.CrossRefGoogle ScholarPubMed
Chanter, N. 1976. Mathematical models in mushroom research and production. Ph. D. thesis, University of Sussex.Google Scholar
Coop, R. L. and Kyriazakis, I. 1999. Nutrition-parasite interaction. Veterinary Parisitology 84: 187–204.Google Scholar
Courtis, S. A. 1937. What is a growth cycle? Growth 1: 155–174.Google Scholar
Doornenbal, H. 1971. Growth, development and chemical composition of the pig. I. Lean tissue and protein. Growth 35: 281–295.Google ScholarPubMed
Doornenbal, H. 1972a. Growth, development and chemical composition of the pig. II. Fatty tissue and chemical fat. Growth 36: 185–194.Google Scholar
Doornenbal, H. 1972b. Growth, development and chemical composition of the pig. III. Bone, ash and moisture. Growth 39: 427–434.Google Scholar
Emmans, G. C. 1987. Growth, body composition and feed intake. World Poultry Science Journal 43: 208–227.Google Scholar
Emmans, G. C. 1988. Genetic components of potential and actual growth. In Animal breeding opportunities (ed. R. B. Land, G. Bulfield, and W. G. Hill, ), British Society of Animal Production occasional publication no. 12, pp. 153–181.Google Scholar
Emmans, G. C. 1989. The growth of turkeys. In Recent advances in turkey science (ed. R. B., Land Bulfield, G. and Hill, W. G.), Poultry Science symposium no. 21, pp. 153–181. British Society of Animal Production, Edinburgh.Google Scholar
Emmans, G. C. 1997. A method to predict the food intake of domestic animals form birth to maturity as a function of time. Journal of Theoretical Biology 186: 189–199.CrossRefGoogle Scholar
Emmans, G. C. and Kyriazakis, I. 1999. Growth and body composition. In A quantitative biology of the pig (ed. Kyriazakis, I.), pp. 181–197. CAB International, Wallingford.Google Scholar
Emmans, G. C. and Kyriazakis, I. 2000. Issues arising from genetic selection for growth and body composition characteristics in poultry and pigs. In The challenge of genetic change in animal production (ed. Hill, W. G. Bishop, S. C. McGuirk, B. McKay, J. C. Simm, G. and Webb, A. J.), British Society of Animal Science occasional publication no. 27, pp. 39–53.Google Scholar
Emmans, G. C. and Kyriazakis, I. 2001. Consequences of genetic change in farm animals on food intake and feeding behaviour. Proceedings of the Nutrition Society 60: 1–11.CrossRefGoogle ScholarPubMed
Erp-van der Kooij, E. V. van, Kuijpers, A. H., Schrama, J. W., Ekkel, E. D. and Tielen, M. J. M. 2000. Individual behavioural characteristics in pigs and their impact on production. Applied Animal Behaviour Science 66: 171–185.CrossRefGoogle Scholar
Ferguson, N. S. and Gous, R. M. 1993a. Evaluation of pig genotypes. 1. Theoretical aspects of measuring genetic parameters. Animal Production 56: 233–243.Google Scholar
Ferguson, N. S. and Gous, R. M. 1993b. Evaluation of pig genotypes. 2. Testing experimental procedure. Animal Production 56: 245–249.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: 10–17.Google Scholar
Fitzhugh, H. A. 1976. Analysis of growth curves and strategies for altering their shape. Journal of Animal Science 58: 903–912.Google Scholar
France, J., Dijkstra, J., Thornley, J. H. M. and Dhanoa, M. S. 1996. A simple but flexible growth function. Growth, Development and Aging 60: 71–83.Google Scholar
France, J. and Thornley, J. H. M. 1984. Mathematical models in agriculture. Butterworths, London.Google Scholar
Gall, G. A. E. and Kyle, W. H. 1968 Growth of the laboratory mouse. Theoretical and Applied Genetics 38: 304–311.Google Scholar
Gompertz, B. 1825. On nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies. Philosophical Transactions of the Royal Society 115: 513–585.Google Scholar
Hill, A. V. 1913. The combinations of haemoglobin with oxygen and with carbon monoxide. Biochemistry 7: 472–480.Google Scholar
Janoschek, A. 1957. Das reaktionskinetische Grundgesetz und seine Beziehungen zum Wachs-tums- und Ertragsgesetz. Stat. Vjschr 10: 25–37.Google Scholar
Knap, P. W. 2000. Variation in maintenance requirements of growing pigs in relation to body composition. A simulation study. Ph. D. thesis, University of Wageningen.Google Scholar
Koops, W. J. 1986. Multiphasic growth curve analysis. Growth 50: 169–180.Google Scholar
Koops, W. J. and Grossman, M. 1991. Applications of a multiphasic growth function to body composition in pigs. Journal of Animal Science 69: 3265–3273.Google Scholar
Kowalski, C. J. and Guire, K. E. 1974. Longitudinal data analysis. Growth 38: 131–169.Google Scholar
Kyriazakis, I. and Emmans, G. C. 1991. Diet selection in pigs: dietary choices made by growing pigs following a period of underfeeding with protein. Animal Production 52: 337–346.Google Scholar
Lange, C. F. M. de. 1995. Framework for a simplified model to demonstrate principles of nutrient partitioning for growth in the pig. In Modelling growth in the pig (ed. Moughan, P. J. Verstegen, M. W. A. and Visser-Reyneveld, M. I.) European Association for Animal Production publication no. 78, pp. 71–85. Wageningen Pers, The Netherlands.Google Scholar
Lawrence, T. L. J. and Fowler, V. R. 1997. Growth of farm animals. CAB International, Wallingford.Google Scholar
Lewis, R. M., Emmans, G. C., Dingwall, W. S. and Simm, G. 2002. A description of the growth of sheep and its genetic analysis. Animal Science 74: 51–62.Google Scholar
Lister, D., Cowen, T. and McCance, R. A. 1966. Severe undernutrition in growing and adult animals. 16. The ultimate results of rehabilitation: poultry. British Journal of Nutrition 20: 633–639.Google Scholar
Lister, D. and McCance, R. A. 1967. Severe undernutrition in growing and adult animals. 17. The ultimate results of rehabilitation: pigs. British Journal of Nutrition 21: 787–799.Google Scholar
Lopez, S., France. J., , Gerrits, W. J. J., Dhanoa, M. S., Humphries, D. J. and Dijkstra, J. 2000. A generalized Michaelis-Menton equation for the analysis of growth. Journal of Animal Science 78: 1816–1828.CrossRefGoogle Scholar
McCance, R. A. 1960. Severe undernutrition in growing and adult animals. 1. Production and general effects. British Journal of Nutrition 14: 59–72.Google Scholar
Mitchell, H. H., Carroll, W. E., Hamilton, T. S. and Hunt, G. E. 1931. Food requirements of pregnancy in swine. Bulletin, Illinois Agriculture Experiment Station, no. 375.Google Scholar
Moore, A. J. 1985. A mathematical equation for animal growth from embryo to adult. Animal Production 40: 441–453.Google Scholar
Moughan, P. J. 1995. Modelling protein metabolism in the pig-critical evaluation of a simple reference model. In Modelling growth in the pig (ed. Moughan, P. J. Verstegen, M. W. A. and Visser-Reyneveld, M. I.) European Association for Animal Production publication no. 78, pp. 103–112. Wageningen Pers, The Netherlands.Google Scholar
Moustgaard, J. 1962. Foetal nutrition in pigs. In Nutrition of pigs and poultry (ed. Morgan, J. T. and Lewis, D.), pp. 189–206. Butterworths, London.Google Scholar
Oijen, M. A. A. J. van, Koops, W. J., Zandstra, T. and Kemp, B. 1993. Modelling foetal growth in pigs. Animal Production 57: 447–453.Google Scholar
Palmer, G. Y., Schinckel, A. P. and Einstein, M. E. 1993. Evaluation of lean growth of seven genotypes of swine. Journal of Animal Science 71: 244.Google Scholar
Parks, J. R. 1965. Prediction and entropy of half-tone pictures. Behavioural Science 10: 436–445.Google Scholar
Parks, J. R. 1982. A theory of feeding and growth of animals. Springer-Verlag, Berlin.Google Scholar
Pomar, C., Harris, D. L. and Minviele, F. 1991. Computer simulation model of swine production systems. 1. Modelling the growth of young pigs. Journal of Animal Science 69: 1468–1488.Google Scholar
Richards, F. J. 1959. A flexible growth function for empirical use. Journal of Experimental Botany 10: 290–300.Google Scholar
Robertson, T. B. 1908. On the normal rate of growth of an individual and its biochemical significance. Archiv für Entwicklungsmechanik der Organismen 25: 581–614.Google Scholar
Robertson, T. B. 1923. The chemical basis of growth and senescence. In Monographs of experimental biology (ed. Lipincott, J. B.), Philadelphia, PA.Google Scholar
Robinson, J. J., Sinclair, K. D. and McEvoy, T. G. 1999. Nutritional effects on foetal growth. Animal Science 68: 315–331.Google Scholar
Schinckel, A. P. 1994. Nutrient requirement of modern pig genotypes. In Recent advances in animal nutrition (ed. Garnsworthy, P. C. and Cole, D. J. A.), pp. 133. University of Nottingham Press, Nottingham.Google Scholar
Schinckel, A. P. 1999. Describing the pig. In A quantitative biology of the pig (ed. Kyriazakis, I.), pp. 181–197. CAB International, Wallingford.Google Scholar
Schinckel, A. P. and Lange, C. F. M. de. 1996. Characterisation of growth parameters needed as inputs for pig growth models. Journal of Animal Science 74: 2021–2036.Google Scholar
Schnute, J. 1981. A versatile growth model with statistically stable parameters. Canadian Journal of Fisheries and Aquatic Sciences 38: 1128–1140.CrossRefGoogle Scholar
Stamataris, C., Kyriazakis, I. and Emmans, G. C. 1991. The performance and body composition of young pigs following a period of growth retardation by food restriction. Animal Production 53: 373–381.Google Scholar
St C. S., Taylor 1980. Genetic size-scaling rules in animal growth. Animal Production 30: 161–165.Google Scholar
Thorburn, W. M. 1915. Occam’s razor. Mind 24: 287–288.Google Scholar
Wan, X., Zhong, W. and Wang, M. 1998. New flexible growth function and its application to the growth of small mammals. Growth, Development and Aging 62: 27–31.Google Scholar
Wellock, I. J., Emmans, G. C. and Kyriazakis, I. 2003. Modelling the effects of thermal environment and dietary composition on pig performance: model logic and concepts. Animal Science 77: 255–266.Google Scholar
Whittemore, C. T. 1998. The science and practice of pig production. Blackwell Science, London.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: 87–96.Google Scholar
Whittemore, C. T., Tullis, J. B. and Emmans, G. C. 1988. Protein growth in pigs. Animal Production 46: 437–445.Google Scholar
Winsor, C. P. 1932. The Gompertz curve as a growth curve. Proceedings of the National Academy of Sciences of the United States of America 18: 1–8.Google Scholar
Wright, S. 1926. Book review. Journal of American Statisticians Association 21: 494–503.Google Scholar