Prediction of the Weight and Number of Eggs in Mazandaran Native Fowl Using Artificial Neural Network

Authors

  • Amir Ahmad Dehghani Department of Water Engineering, Gorgan University of Agricultural Sciences and natural Resources, Gorgan, Iran
  • Morad Pasha Eskandari Nasab In order, M.sc. student and faculty member of Agricultural Science University of Zanjan, Zanjan, Iran
  • Saeed Zarehdaran Department of Animal Science, Faculty of Agriculture and Natural Resources, University of Gorgan, Iran
  • Soudabeh Semsarian In order, M.sc. student and faculty member of Agricultural Science University of Zanjan, Zanjan, Iran
Abstract:

Traditional poultry production has changed to a considerable industry after few decades. Now, poultry industry is one of the main sectors to obtain the required protein for human consumption. Prediction of the weight and number of eggs according to economic traits can improve the efficiency of production and the profit of producers. In present study, the weight and number of eggs in Mazandaran native fowl were predicted using artificial neural network (ANN). The information of BW at birth, 8 and 12 weeks of age, weight and age at sexual maturity and the polymorphism of prolactin gene were used for the prediction. The results showed that ANN is reliable method for predicting the weight and number of eggs based on available information

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Journal title

volume 5  issue Issue 3. pp. 108-159

pages  133- 137

publication date 2017-07-01

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