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Intestinal broiler microflora estimation by artificial neural network

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Abstract

Microflora population of poultry was affected by various factors. Many methods and techniques were developed to study microflora population. But, most of them confronted some problems. Moreover, being costly, laborious, and time-consuming made it impossible to measure microflora population several times. In this study, we tried to estimate intestinal microflora population using artificial neural network (ANN). Lactic acid bacteria were used as model of microflora population. Time and lactic acid bacteria were used as input and output variables, respectively. The best model of ANN was determined based on coefficient of determination, root mean square error, and mean absolute error criteria. The results of current study have shown that ANN is appropriate, cheap, and reliable tools to estimate intestinal microflora population (lactic acid bacteria) of broiler at different ages.

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Acknowledgments

Our special thanks of Bu-Ali Sina University for providing facilities and financial support of this study. We also wish to thank to the staff of the Department of Animal Science of this university for their excellent scientific collaboration.

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Authors and Affiliations

  1. Faculty of Agriculture, Department of Animal Science, Bu-Ali Sina University, P Box 651783131, 65175, Hamaden, Iran

    Hamid Reza Hemati Matin, Ali Asghar Saki, Hasan Aliarabi, Mojtaba Shadmani & Hamid Zare Abyane

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  1. Hamid Reza Hemati Matin
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  2. Ali Asghar Saki
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  3. Hasan Aliarabi
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  4. Mojtaba Shadmani
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Correspondence to Ali Asghar Saki.

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Hemati Matin, H.R., Saki, A.A., Aliarabi, H. et al. Intestinal broiler microflora estimation by artificial neural network. Neural Comput & Applic 21, 1043–1047 (2012). https://doi.org/10.1007/s00521-011-0553-2

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  • DOI: https://doi.org/10.1007/s00521-011-0553-2

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