|
|
Registros recuperados : 430 | |
Registros recuperados : 430 | |
|
|
Registro Completo
Biblioteca(s): |
Embrapa Pecuária Sudeste. |
Data corrente: |
19/10/2015 |
Data da última atualização: |
15/05/2023 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
B - 1 |
Autoria: |
NASCIMENTO, M.; PETERNELLI, L. A.; CRUZ, C. D.; NASCIMENTO, A. C. C.; FERREIRA, R. de P. |
Afiliação: |
MOYSÉS NASCIMENTO, UNIVERSIDADE FEDERAL DE VIÇOSA, VIÇOSA, MG; LUIZ ALEXANDRE PETERNELLI, UNIVERSIDADE FEDERAL VIÇOSA/ VIÇOSA, MG.; COSME DAMIÃO CRUZ, UNIVERSIDADE FEDERAL VIÇOSA/ VIÇOSA, MG.; ANA CAROLINA CAMPANHA NASCIMENTO, UNIVERSIDADE FEDERAL VIÇOSA/ VIÇOSA, MG.; REINALDO DE PAULA FERREIRA, CPPSE. |
Título: |
Artificial neural networks for adaptability and stability evaluation in alfalfa genotypes |
Ano de publicação: |
2013 |
Fonte/Imprenta: |
Crop Breeding and Applied Biotechnology, v. 13, n. 2, p. 152-156, jul. 2013. |
Idioma: |
Inglês |
Conteúdo: |
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. |
Palavras-Chave: |
Bioinformatic; Data simulation; Eberhart russell. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/131321/1/PROCI-2013.00300.pdf
|
Marc: |
LEADER 01410naa a2200205 a 4500 001 2026720 005 2023-05-15 008 2013 bl uuuu u00u1 u #d 100 1 $aNASCIMENTO, M. 245 $aArtificial neural networks for adaptability and stability evaluation in alfalfa genotypes$h[electronic resource] 260 $c2013 520 $aThe 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. 653 $aBioinformatic 653 $aData simulation 653 $aEberhart russell 700 1 $aPETERNELLI, L. A. 700 1 $aCRUZ, C. D. 700 1 $aNASCIMENTO, A. C. C. 700 1 $aFERREIRA, R. de P. 773 $tCrop Breeding and Applied Biotechnology$gv. 13, n. 2, p. 152-156, jul. 2013.
Download
Esconder MarcMostrar Marc Completo |
Registro original: |
Embrapa Pecuária Sudeste (CPPSE) |
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
Nenhum registro encontrado para a expressão de busca informada. |
|
|