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Modelling and optimising early performance for broiler chicks

Published online by Cambridge University Press:  22 November 2017

H Ahmadi  and
A Golian
H Ahmadi*
Affiliation:
Ferdowsi University of Mashhad, Mashhad, Khorasan, Islamic Republic of Iran
A Golian
Affiliation:
Ferdowsi University of Mashhad, Mashhad, Khorasan, Islamic Republic of Iran
*
Email: [email protected]
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Extract

Several methods have been introduced to estimate the optimum level of dietary nutrients such as metabolisable energy (ME), crude protein (CP), and lysine (Lys) in broiler chicken production. Performance optimisation is usually measured as maximising body weight gain and minimising adjusted feed conversion ratio (Adj FCR). One useful method is to model a system that requires an explicit mathematical input-output relationship. Group method of data handling-type neural network (GMDH-type NN) and genetic algorithm (GA) is used to model and optimise an output in an imprecise environment (Yao, 1999). The purpose of this study was to apply the GMDH-type NN and GA methods to provide an optimised formula for broiler chicken performance based on the dietary level of ME, CP, and Lys.

Type
Theatre Presentations
Information
Proceedings of the British Society of Animal Science , Volume 2009 , April 2009 , pp. 211
Copyright
Copyright © The British Society of Animal Science 2009

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References

Ahmadi, H., Mottaghitalab, M., Nariman-Zadeh, N., and Golian, A. 2008. British Poultry Science 49 (3), 315–320.Google Scholar
Nariman-Zadeh, N., Darvizeh, A., Jamali, A., and Moieni, A. 2005. Journal of Materials Processing Technology. 164-165, 1561–1571.CrossRefGoogle Scholar
Yao, X. 1999. Proceedings of the IEEE. 87 (9), 1423–1447.Google Scholar