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- Title
Artificial neural networks for adaptability and stability evaluation in alfalfa genotypes.
- Authors
Nascimento, Moysés; Peternelli, Luiz Alexandre; Cruz, Cosme Damião; Campana Nascimento, Ana Carolina; Paula Ferreira, Reinaldo de; Bhering, Leonardo Lopes; Salgado, Caio Césio
- Abstract
The purpose of this work was to evaluate a methodology of adaptability and phenotypic stability of alfalfa genotypes based on the training of an artificial neural network considering the methodology of Eberhart and Russell. Data from an experiment on dry matter production of 92 alfalfa genotypes (Medicago sativa L.) were used. The experimental design constituted of randomized blocks, with two repetitions. The genotypes were submitted to 20 cuttings, in the growing season of November 2004 to June 2006. Each cutting was considered an environment. The artificial neural network was able to satisfactorily classify the genotypes. In addition, the analysis presented high agreement rates, compared with the results obtained by the methodology of Eberhart and Russell
- Subjects
BRAZIL; ALFALFA varieties; ARTIFICIAL neural networks; GROWING season; BAYESIAN analysis
- Publication
Crop Breeding & Applied Biotechnology, 2013, Vol 13, Issue 2, p152
- ISSN
1518-7853
- Publication type
Article
- DOI
10.1590/s1984-70332013000200008