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Mathematical models in broiler raising

Published online by Cambridge University Press:  23 March 2009

J. Zoons ,
J. Buyse  and
E. Decuypere
J. Zoons
Affiliation:
Laboratory for Physiology of Domestic Animals, Faculty of Agricultural Sciences, Catholic University of Leuven, Kardinaal Mercierlaan 92, 3001 Herverlee, Belgium
J. Buyse
Affiliation:
Laboratory for Physiology of Domestic Animals, Faculty of Agricultural Sciences, Catholic University of Leuven, Kardinaal Mercierlaan 92, 3001 Herverlee, Belgium
E. Decuypere
Affiliation:
Laboratory for Physiology of Domestic Animals, Faculty of Agricultural Sciences, Catholic University of Leuven, Kardinaal Mercierlaan 92, 3001 Herverlee, Belgium
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Abstract

Among poultry scientists there is an increasing interest in model building because models are useful in the investigation of the economic consequences of management decisions and in identifying gaps in current knowledge of the biological processes involved in production. In addition to empirical formulae giving the relationship between one or two dependent and one or more independent variables, more mechanistic models are needed to solve problems which involve more detailed ‘what if’ questions, in particular, those that take into account interactions between several factors influencing growth and require a fundamental knowledge of growth processes. The advantage of these models is that they can be used in a broader range of circumstances than empirical models. The development of such mechanistic models serves to identify several remaining gaps in our fundamental knowledge of the causal mechanisms of growth. The mechanistic models described in this review can be seen as a collection of several empirical models, each representing a part of the total biological growth process.

It can be concluded that in future a more quantitative exploration of the causal mechanisms in growth and their interactions with the environment will be needed for the development of a mechanistic, stochastic and dynamic model of growth in a broiler population.

Keywords

Broilersgrowthmodels
Type
Reviews
Information
World's Poultry Science Journal , Volume 47 , Issue 3 , November 1991 , pp. 243 - 255
Copyright
Copyright © Cambridge University Press 1991

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References

Akiba, Y. (1988) Aspect and nutritional control of excess fat deposition in the broiler. In: Proceedings of XVIII World's Poultry Congress, pp. 192–195Google Scholar
Allison, J.R., Lane, O.E. and Amato, S.V. (1978) Broiler profit maximizing models. Poultry Science 57: 845–853CrossRefGoogle 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(3): 121–145Google Scholar
Burlacu, G.H., Burlacu, R., Columbeanu, I. and Alexandru, G. (1990) Mathematical model for energy and protein balance simulation in broilers. Archive of Animal Nutrition, Berlin 40(5/6): 469–484Google ScholarPubMed
Curnow, R.N. (1973) A smooth population response curve based on an abrupt threshold and plateau model for individuals. Biometrics 29: 1–10Google Scholar
Dijkhuizen, A.A. (1988) Modelling to support health programs in different species. In: Modelling of Livestock Production Systems. Kluwer Ac. Publishers, Dordrecht, pp. 125–132Google Scholar
Emmans, G.C. (1981) A model of growth and feed intake of ad libitum fed animals, particularly poultry. In: Computers in Animal Production, Occasional Publication No. 5, British Society of Animal Production, pp. 103–110Google Scholar
Emmans, G.C. (1984) An additive and linear energy scale. Animal Production 38: 538Google Scholar
Emmans, G.C. (1987) Growth, body composition and feed intake. World's Poultry Science Journal 43: 208–227CrossRefGoogle Scholar
Emmans, G.C. (1989) The growth of turkeys. In: Recent Advances in Turkey Science, Butterworths, London, pp. 135–166Google Scholar
Emmans, G.C. and Fisher, C. (1986). Problems in nutritional theory. In: Nutrient Requirements of Poultry and Nutritional Research (Eds. Fisher, C. and Boorman, K.N.), Butterworths, London, pp. 9–39Google Scholar
Emmans, G.C. and Oldham, J.D. (1987) Modelling of growth and nutrition in different species. EEC Animal Modelling Conference, Brussels, 04, 1987Google Scholar
Fisher, C. (1989) Use of models to describe biological function and to estimate nutrient requirements for poultry. In: Report of Proceedings of First European Symposium on EDP Applications in Poultry Management, WPSA Danish Branch, DSR Forlag, Copenhagen, pp. 52–63Google Scholar
Fisher, C., Morris, T.R. and Jennings, R.C. (1973) A model for the description and prediction of the response of laying hen to amino acid intake. British Poultry Science 14: 469–484CrossRefGoogle Scholar
France, J. and Thornley, J.H.M. (1984) Mathematical Models in Agriculture. A Quantitative Approach to Problems in Agriculture and Related Sciences, Butterworths, London, p. 335Google Scholar
Groenestein, G.M. and Van Ouwerkerk, E.N.J. (1990) Literatuuronderzoek naar de Energiebalans van Slachtkuikens, Instituut voor mechanisatie, arbeid en gebouwen, Netherlands. Internal note, 19 pp.Google Scholar
Hijink, J.W.F. and Meijer, A.B. (1987) Het koemodel, Proefstation voor de rundveehouderij, schapenhouderij en paarden houderij, Lelystad, Publikatie No. 50, 52 pp.Google Scholar
Howlider, M.A.R. and Rose, S.P. (1987) Temperature and the growth of broilers. World's Poultry Science Journal 43: 228–237CrossRefGoogle Scholar
Hurwitz, S., Talpaz, H. and Waibel, P.E. (1985) The use of simulation in the evaluation of economics and management of turkey production: dietary nutrient density, marketing age and environmental temperature. Poultry Science 64: 1415–1423CrossRefGoogle Scholar
Isariyodom, S., Tasaki, I., Okumura, J. and Muramatsu, T. (1988) Construction of a mathematical model for predicting broiler performance. Japanese Poultry Science 25: 191–200CrossRefGoogle Scholar
Kirchgessner, M., Maurus-Krukal, E.M. and Roth, F.X. (1989) Energy utilisation of broilers between 1500 and 3000 g liveweight. In: Energy Metabolism of Farm Animals, Pudoc, Wageningen, pp. 5–8Google Scholar
Koops, W.J. (1989) Multiphasic analysis of growth. PhD. Thesis, Wageningen, 121 pp.Google Scholar
Leclercq, B. and Saadoun, A. (1982) Selecting broilers for low or high abdominal weight: comparison of energy metabolism of the lean and fat lines. Poultry Science 61: 1799–1803CrossRefGoogle Scholar
Leenstra, F.R. (1986) Effect of age, sex, genotype and environment of fat deposition in broiler chickens – a review. World's Poultry Science Journal 42: 12–25Google Scholar
Moughan, P.J. (1985) Sensitivity analysis on a model simulating the digestion and metabolism of nitrogen in the growing pig. New Zealand Journal of Agricultural Research 28: 463–468Google Scholar
Moughan, P.J. and Smith, W.C. (1984a) Assessment of a balance of dietary amino acids required to maximise protein utilisation in the growing pig (20–80 kg liveweight). New Zealand Journal of Agricultural Research 27: 341–347CrossRefGoogle Scholar
Moughan, P.J. and Smith, W.C. (1984b) Prediction of dietary protein quality based on a model of the digestion and metabolism of nitrogen in the growing pig. New Zealand Journal of Agricultural Research 27: 501–507Google 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: 481–489CrossRefGoogle Scholar
Moughan, P.J. and Verstegen, W.A. (1988) The modelling of growth in the pig. Netherlands Journal of Agricultural Science 36: 145–166CrossRefGoogle Scholar
Parks, J.R. (1982) A Theory of Feeding and Growth of Animals, Springer-Verlag, 322 pp.Google Scholar
Pym, R.A.E., Nicholls, P.J., Thomson, E., Choice, A. and Farrell, D.J. (1984) Energy and nitrogen metabolism of broilers selected over ten generations for increased growth rate, food consumption and conversion of food to gain. British Poultry Science 25: 529–539Google Scholar
Scheele, C.W., Janssen, W.M.M. and Van Gils, L. (1977) Feeding criteria of growth and carcass composition. In: Growth and Poultry Meat Production, British Poultry Science Ltd, Edinburgh, pp. 249–259Google Scholar
Shanawany, M.M. (1988) Broiler performance under high stocking densities. British Poultry Science 29: 43–52Google Scholar
Spriet, J.A. and Vansteenkiste, G.C. (1982) Computer-aided Modelling and Simulation. Academic Press, London, 490 pp.Google Scholar
Talpaz, H., De La Torre, J.R. and Sharpe, P.J.H. (1986) Dynamic optimization model for feeding of broilers. Agriculture Systems 20: 121–132CrossRefGoogle Scholar
Talpaz, H., Hurwitz, S., De La Torre, J.R. and Sharpe, P.J.H. (1988) Economic optimization of a growth trajectory for broilers. American Journal of Agricultural Economics 70(2): 382–390Google Scholar
Thornley, J.H.M. and Johnson, I.R. (1990) A Mathematical Approach to Plant and Crop Physiology, Oxford Science Publications, 660 pp.Google Scholar
Toyomizu, M., Akiba, Y., Horiguchi, M. and Matsumoto, T. (1982) Multiple regression and response surface analysis of the effects of dietary protein, fat and carbohydrate on the body protein and fat gain in growing chicks. Journal of Nutrition 112: 886–896CrossRefGoogle ScholarPubMed
Tzeng, R. and Becker, W.A. (1981) Growth patterns of body and abdominal fat weights in male broiler chickens. Poultry Science 60: 1101–1106Google Scholar
Van Arendonk, J.A.M. (1985) Studies on the replacement policies in dairy cattle. PhD. Thesis, Wageningen, 126 pp.Google Scholar
Van Horne, P.L.M. (1988) Het optimale aflevergewicht in de slachtkuikenhouderij. Bij gemengde en gescheiden opzet van hanen en hennen. LEI-publikatie No. 3.138. Den Haag. 37 pp.Google Scholar
Wathes, C.M., Gill, B.D., Charles, D.R. and Back, H.L. (1981) The effect of temperature on broilers: a simulation model of the responses to temperature. British Poultry Science 22: 483–492CrossRefGoogle 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: 87–96Google Scholar
Zoons, J. (1987) Bepaling van het economisch optimaal vervangingsbeleid bij melkvee m.b.v. dynamisch programmeren. Student Thesis, Leuven, 86 pp.Google Scholar