Title of article :
Prediction of the Weight and Number of Eggs in Mazandaran Native Fowl Using Artificial Neural Network
Author/Authors :
Semsarian ، Soudabeh M.sc. student and faculty member of Agricultural Science University of Zanjan , Pasha Eskandari Nasab ، Morad M.sc. student and faculty member of Agricultural Science University of Zanjan , Zarehdaran ، Saeed - University of Gorgan , Dehghani ، Amir Ahmad - Gorgan University of Agricultural Sciences and natural Resources
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
Keywords :
Egg number , Egg weight , Neural network , prediction
Journal title :
International Journal of Advanced Biological and Biomedical Research
Journal title :
International Journal of Advanced Biological and Biomedical Research
