Artificial neural networks compared with Bayesian generalized linear regression for leaf rust resistance prediction in Arabica coffee

Artificial neural networks compared with Bayesian generalized linear regression for leaf rust resistance prediction in Arabica coffee

Abstract: The objective of this work was to evaluate the use of artificial neural networks in comparison with Bayesian generalized linear regression to predict leaf rust resistance in Arabica coffee (Coffea arabica). This study used 245 individuals of a F2 population derived from the self-fertilizat...

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Bibliographic Details
Main Authors: Gabi Nunes Silva, Moysés Nascimento, Isabela de Castro Sant’Anna, Cosme Damião Cruz, Eveline Teixeira Caixeta, Pedro Crescêncio Souza Carneiro, Renato Domiciano Silva Rosado, Kátia Nogueira Pestana, Dênia Pires de Almeida, Marciane da Silva Oliveira
Format: Article
Language:English
Published: Embrapa Informação Tecnológica 2017-03-01
Series:Pesquisa Agropecuária Brasileira
Subjects:
Coffea arabica
Hemileia vastatrix
artificial intelligence
molecular markers
prediction
Online Access:http://www.scielo.br/pdf/pab/v52n3/1678-3921-pab-52-03-00186.pdf

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http://www.scielo.br/pdf/pab/v52n3/1678-3921-pab-52-03-00186.pdf

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