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| Registros recuperados : 6 | |
| 4. |  | OLIVEIRA-PAIVA, C. A.; OLIVEIRA, M. C. de; MARRIEL, I. E.; GOMES, E. A.; CASTRO, C. S. P. DE; BRITO, M. A. V. P. e; COELHO, E. A.; MEIRELLES, W. C. L. Banco de competências: ferramenta de apoio à decisão de capacitação das coleções de microrganismos da Embrapa. Sete Lagoas: Embrapa Milho e Sorgo, 2015. 68 p. (Embrapa Milho e Sorgo. Documentos, 194).| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 5. | | PAIVA, C. A. O.; OLIVEIRA, M. C. de; MARRIEL, I. E.; GOMES, E. A.; CASTRO, C. S. P. DE; BRITO, M. A. V. P. e; COELHO, E. A.; MEIRELLES, W. C. L. Banco de competências: ferramenta de apoio à decisão de capacitação das coleções de microrganismos da Embrapa. Sete Lagoas: Embrapa Milho e Sorgo, 2015 68 p. (Embrapa Milho e Sorgo. Documentos, 194).| Biblioteca(s): Embrapa Gado de Leite. |
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| 6. | | MEIRELLES, W. C. L.; ANDRADE, C. de L. T. de; CARNEIRO, N. P.; RESENDE, A. V. de; OLIVEIRA, A. C. de; COELHO, A. M.; KARAM, D.; CRUZ, I.; VIANA, J. H. M.; GUIMARAES, L. J. M.; COTA, L. V.; GONTIJO NETO, M. M.; ALBUQUERQUE, P. E. P. de; GUIMARAES, P. E. de O.; NODA, R. W.; COSTA, R. V. da. Sistema de Integração e Gerenciamento de Dados Experimentais - SisIndex Sete Lagoas: Embrapa Milho e Sorgo, 2017. 75 p. (Embrapa Milho e Sorgo. Documentos, 213).| Biblioteca(s): Embrapa Milho e Sorgo. |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Milho e Sorgo. Para informações adicionais entre em contato com cnpms.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Milho e Sorgo. |
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Data corrente: |
13/03/2015 |
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Data da última atualização: |
27/09/2017 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
MEIRELLES, W. C. L.; ZARATE, L. E. |
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Afiliação: |
WANDERLEY CLARETE LANZA MEIRELLES, CNPMS. |
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Título: |
Data mining in the reduction of the number of places of experiments for plant cultivates. |
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Ano de publicação: |
2015 |
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Fonte/Imprenta: |
Computers and Electronics in Agriculture, New York, v. 113, p. 136-147, 2015. |
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DOI: |
10.1016/j.compag.2015.02.00 |
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Idioma: |
Inglês |
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Conteúdo: |
When a new plant cultivar is developed, it needs to be evaluated in relation to different environmental conditions before being commercially released. A set of experiments systematically was conducted at various locations with the purpose of evaluating the performance of the plants, in different soil, climate and elevation conditions. In these experiments, the plant culture development was monitored through-out the entire planting cycle. It is important to note that these experiments are very expensive and the aim of this work is to verify the possibility of reducing the number of places of the experiments without losing of representativeness in the evaluation of planted cultivars. To achieve this goal, the interaction among soil, climate and plant was modeled and the major components in each of these systems were considered. Neural computational models were also developed in order to estimate data regarding the relative air humidity. Using the partitioned clustering technique (k-medians), clusters (planting sites) were built in such a way that, according to the methodology proposed were similar in terms of soil, climate and plant behavior. The consistency of the formed clusters was evaluated by two criteria and the recommendation for reducing the cultivation sites was presented. By analyzing the results, it was possible to verify that the clustering process is not sufficient for deciding which planting locations should be omitted. It is necessary to count on complementary evaluation criteria associated with the production and cultivar ranking. In this work, the national competition experiments of maize cultivars in Brazil are considered as case study. MenosWhen a new plant cultivar is developed, it needs to be evaluated in relation to different environmental conditions before being commercially released. A set of experiments systematically was conducted at various locations with the purpose of evaluating the performance of the plants, in different soil, climate and elevation conditions. In these experiments, the plant culture development was monitored through-out the entire planting cycle. It is important to note that these experiments are very expensive and the aim of this work is to verify the possibility of reducing the number of places of the experiments without losing of representativeness in the evaluation of planted cultivars. To achieve this goal, the interaction among soil, climate and plant was modeled and the major components in each of these systems were considered. Neural computational models were also developed in order to estimate data regarding the relative air humidity. Using the partitioned clustering technique (k-medians), clusters (planting sites) were built in such a way that, according to the methodology proposed were similar in terms of soil, climate and plant behavior. The consistency of the formed clusters was evaluated by two criteria and the recommendation for reducing the cultivation sites was presented. By analyzing the results, it was possible to verify that the clustering process is not sufficient for deciding which planting locations should be omitted. It is necessary to count on complementary e... Mostrar Tudo |
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Palavras-Chave: |
Clustering; Mineração de dados; Rede neural artificial. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02281naa a2200181 a 4500
001 2011352
005 2017-09-27
008 2015 bl uuuu u00u1 u #d
024 7 $a10.1016/j.compag.2015.02.00$2DOI
100 1 $aMEIRELLES, W. C. L.
245 $aData mining in the reduction of the number of places of experiments for plant cultivates.$h[electronic resource]
260 $c2015
520 $aWhen a new plant cultivar is developed, it needs to be evaluated in relation to different environmental conditions before being commercially released. A set of experiments systematically was conducted at various locations with the purpose of evaluating the performance of the plants, in different soil, climate and elevation conditions. In these experiments, the plant culture development was monitored through-out the entire planting cycle. It is important to note that these experiments are very expensive and the aim of this work is to verify the possibility of reducing the number of places of the experiments without losing of representativeness in the evaluation of planted cultivars. To achieve this goal, the interaction among soil, climate and plant was modeled and the major components in each of these systems were considered. Neural computational models were also developed in order to estimate data regarding the relative air humidity. Using the partitioned clustering technique (k-medians), clusters (planting sites) were built in such a way that, according to the methodology proposed were similar in terms of soil, climate and plant behavior. The consistency of the formed clusters was evaluated by two criteria and the recommendation for reducing the cultivation sites was presented. By analyzing the results, it was possible to verify that the clustering process is not sufficient for deciding which planting locations should be omitted. It is necessary to count on complementary evaluation criteria associated with the production and cultivar ranking. In this work, the national competition experiments of maize cultivars in Brazil are considered as case study.
653 $aClustering
653 $aMineração de dados
653 $aRede neural artificial
700 1 $aZARATE, L. E.
773 $tComputers and Electronics in Agriculture, New York$gv. 113, p. 136-147, 2015.
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