Output Energy Modilling of Broiler Chicken Breeding Units by Artificial Neural Network (Case Study: Mazandaran Province)

Document Type : Research Paper

Authors

1 Sari Agricultural College, Mazandaran Technical University, Iran

2 Animal and Poultry Nutrition Faculty, Animal Science Faculty, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Golestan, Iran

3 Kerman

Abstract

The poultry industry is very important in terms of supplying a significant portion of the country's food and protein needs. In this research, the energy consumption of broiler chickens has been evaluated. For this purpose, information was collected from 45 broiler chicken producers randomly collected in Mazandaran province. In this study, energy consumption and energy indices were calculated first and then, using artificial neural network, output energy modeling was considered as a function. The results of this study showed that total input and output energy in broiler chicken meat production was 153.79 and 27.45 GJ per 1000, respectively. In broiler chickens, the highest inputs were consumed with 61.48%. The energy ratio in the production of this product was also calculated to be 0.18. The artificial neural network results showed that the best structure for estimating the energy consumption of broiler chicken meat was estimated to be 5-12-1. The coefficient of explanation for the best structure for broiler chicken production was 0.99 for training data. Therefore, this model was selected as the best method for estimating the output energy based on input energy in the study area. In assessing the effectiveness of inputs on the outputs, the fossil fuel showed the highest sensitivity among the production inputs that reveals the needs for revision of the energy resources more than ever.

Keywords

References

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Animal Sciences Journal
Volume 32, Issue 124
December 2019
Pages 183-196

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