Neural networks for predicting breeding values and genetic gains

Scientia Agricola

Gabi Nunes Silva²  Rafael Simões Tomaz¹  Isabela De Castro Sant'anna¹  Moysés Nascimento²  Leonardo Lopes Bhering¹  Cosme Damião Cruz² 

[1] ,Federal University of Viçosa - Dept. of Applied Statistics and Biometrics Viçosa MG ,Brazil

关键词: genetic value;    statistics;    simulation;    artificial intelligence;    training strategy;   

DOI  :  10.1590/0103-9016-2014-0057

来源: SciELO

【 摘 要 】

Analysis using Artificial Neural Networks has been described as an approach in the decision-making process that, although incipient, has been reported as presenting high potential for use in animal and plant breeding. In this study, we introduce the procedure of using the expanded data set for training the network. Wealso proposed using statistical parameters to estimate the breeding value of genotypes in simulated scenarios, in addition to the mean phenotypic value in a feed-forward back propagation multilayer perceptron network. After evaluating artificial neural network configurations, our results showed its superiority to estimates based on linear models, as well as its applicability in the genetic value prediction process. The results further indicated the good generalization performance of the neural network model in several additional validation experiments.

【 授权许可】

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