Predicting breeding value of body weight at 6-month age using Artificial Neural Networks in Kermani sheep breed
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) an...
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| Published in | Acta scientiarum. Animal sciences Vol. 41; no. 1; pp. 45282 - e45282 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English Portuguese |
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Maringa
Editora da Universidade Estadual de Maringá - EDUEM
2019
Editora da Universidade Estadual de Maringá (Eduem) |
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| Abstract | 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. |
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| AbstractList | 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. 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 back propagation 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. |
| Author | Babenko, Olena Ivanivna Tkachenko, Serhii Vasyliovych Bushtruk, Maryna Vitaliivna Nezamabadi-pour, Hossein Ghotbaldini, Hamidreza Mohammadabadi, Mohammadreza |
| AuthorAffiliation | Bila Tserkva National Agrarian University Shahid Bahonar University of Kerman |
| AuthorAffiliation_xml | – name: Shahid Bahonar University of Kerman – name: Bila Tserkva National Agrarian University |
| Author_xml | – sequence: 1 givenname: Hamidreza surname: Ghotbaldini fullname: Ghotbaldini, Hamidreza – sequence: 2 givenname: Mohammadreza orcidid: 0000-0002-1268-3043 surname: Mohammadabadi fullname: Mohammadabadi, Mohammadreza – sequence: 3 givenname: Hossein surname: Nezamabadi-pour fullname: Nezamabadi-pour, Hossein – sequence: 4 givenname: Olena Ivanivna surname: Babenko fullname: Babenko, Olena Ivanivna – sequence: 5 givenname: Maryna Vitaliivna surname: Bushtruk fullname: Bushtruk, Maryna Vitaliivna – sequence: 6 givenname: Serhii Vasyliovych surname: Tkachenko fullname: Tkachenko, Serhii Vasyliovych |
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| SubjectTerms | Age Algorithms Animals Artificial neural networks Back propagation Back propagation networks Birth weight Body weight Breeding Computer architecture Computer programs Domestic animals estimate genetic parameters growth traits lamb Multilayer perceptrons Neural networks Parameter estimation Sheep Software VETERINARY SCIENCES Weaning |
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| Title | Predicting breeding value of body weight at 6-month age using Artificial Neural Networks in Kermani sheep breed |
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