Predicting breeding value of body weight at 6-month age using Artificial Neural Networks in Kermani sheep breed

• Autor(a) principal: Ghotbaldini, Hamidreza
• Data de Publicação: 2019
• Outros Autores: Mohammadabadi, Mohammadreza, Nezamabadi-pour, Hossein, Babenko, Olena Ivanivna, Bushtruk, Maryna Vitaliivna, Tkachenko, Serhii Vasyliovych
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Acta Scientiarum. Animal Sciences (Online)
• Texto Completo: https://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/45282
• topic: estimate; genetic parameters; growth traits; lamb.

The present study aimed to apply artificial neural networks to predict the breeding values of body weight in 6-month age of Kermani sheep. For this purpose, records of 867 lambs including lamb sex, dam age, birth weight, weaning weight, age at 3-month (3 months old), age at 6-month (6 months old) and body weight at 3 months of age were used. Firstly, genetic parameters of the animals were estimated using ASReml software. The data was then pre-processed for using in MATLAB software. After initial experiments on the appropriate neural network architecture for body weight at 6-month age, two networks were examined. A feed-forward backpropagation multilayer perceptron (MLP) algorithm was used and 70% of all data used as training data, 15% as testing data and 15% as validating data, to prevent over-fitting of the artificial neural network. Results showed that the both networks capable to predict breeding values for body weight at 6 month-age in Kermani sheep. It can be concluded that artificial neural network has a good ability to predict growth traits in Kermani sheep with an acceptable speed and accuracy. Therefore, this network, instead of commonly-used procedures can be used to estimate the breeding values for productive and reproductive traits in domestic animals.