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| Registros recuperados : 92 | |
| 4. |  | DEL PONTE, E. M.; YANG, X. B.; GODOY, C. V. A chegada aos EUA. Cultivar: grandes culturas, Pelotas, v. 6, n. 68, p. 30,32,34,36, dez./jan. 2004/2005.| Biblioteca(s): Embrapa Soja. |
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| 5. | | DEL PONTE, E. M.; GHINI, R.; HAMADA, E.; ROSSI, P. Análise de risco de epidemias de ferrugem-asiática da soja sob cenário de mudança climática no Brasil. In: Summa Phytopathologica, Botucatu, v.34, supl. p.S42, 2008. Resumos do 21. Congresso Paulista de Fitopatologia, Campinas, 2008.| Biblioteca(s): Embrapa Meio Ambiente. |
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| 13. | | MAIA, A. de H. N.; DEL PONTE, E. M.; ESKER, P. D.; GODOY, C. V. Análise exploratória e seleção de ensaios para meta-análise de coeficientes de regressão linear. In: REUNIÃO ANUAL DA REGIÃO BRASILEIRA DA SOCIEDADE INTERNACIONAL DE BIOMETRIA - RBRAS, 54.; SIMPÓSIO DE ESTATÍSTICA APLICADA À EXPERIMENTAÇÃO AGRONÔMICA - SEAGRO, 13., 2009, São Carlos, SP. Anais.... São Carlos: UFSCar: Embrapa Pecuária Sudeste, 2009. 1 CD-ROM. N. 438. 5 p.| Biblioteca(s): Embrapa Meio Ambiente. |
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| 19. | | NICOLLI, C. P.; SPOLTI, P.; TIBOLA, C. S.; FERNANDES, J. M. C.; DEL PONTE, E. M. Fusarium head blight and trichothecene production in wheat by Fusarium graminearum and F. meridionale applied alone or in mixture at post-flowering. Tropical Plant Pathology, Brasília, DF, v. 40, N. 2, p. 134-140, 2015.| Biblioteca(s): Embrapa Trigo. |
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| Registros recuperados : 92 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Soja. |
|
Data corrente: |
04/04/2007 |
|
Data da última atualização: |
13/12/2011 |
|
Autoria: |
DEL PONTE, E. M.; GODOY, C. V.; CANTERI, M. G.; REIS, E. M.; YANG, X. B. |
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Título: |
Models and applications for risk assessment and prediction of Asian soybean rust epidemics. |
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Ano de publicação: |
2006 |
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Fonte/Imprenta: |
Fitopatologia Brasileira, Brasília, DF, v.31, n. 6, p. 533-544, Nov./Dec. 2006. |
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Idioma: |
Inglês |
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Conteúdo: |
Asian rust of soybean [Glycine max (L.) Merril] is one of the most important fungal diseases of this crop worldwide. The recent introduction of Phakopsora pachyrhizi Syd. & P. Syd in the Americas represents a major threat to soybean production in the main growing regions, and significant losses have already been reported. P. pachyrhizi is extremely aggressive under favorable weather conditions, causing rapid plant defoliation. Epidemiological studies, under both controlled and natural environmental conditions, have been done for several decades with the aim of elucidating factors that affect the disease cycle as a basis for disease modeling. The recent spread of Asian soybean rust to major production regions in the world has promoted new development, testing and application of mathematical models to assess the risk and predict the disease. These efforts have included the integration of new data, epidemiological knowledge, statistical methods, and advances in computer simulation to develop models and systems with different spatial and temporal scales, objectives and audience. In this review, we present a comprehensive discussion on the models and systems that have been tested to predict and assess the risk of Asian soybean rust. Limitations, uncertainties and challenges for modelers are also discussed. |
|
Palavras-Chave: |
Soybean. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/50136/1/27131.pdf
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|
Marc: |
LEADER 01860naa a2200181 a 4500
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100 1 $aDEL PONTE, E. M.
245 $aModels and applications for risk assessment and prediction of Asian soybean rust epidemics.
260 $c2006
520 $aAsian rust of soybean [Glycine max (L.) Merril] is one of the most important fungal diseases of this crop worldwide. The recent introduction of Phakopsora pachyrhizi Syd. & P. Syd in the Americas represents a major threat to soybean production in the main growing regions, and significant losses have already been reported. P. pachyrhizi is extremely aggressive under favorable weather conditions, causing rapid plant defoliation. Epidemiological studies, under both controlled and natural environmental conditions, have been done for several decades with the aim of elucidating factors that affect the disease cycle as a basis for disease modeling. The recent spread of Asian soybean rust to major production regions in the world has promoted new development, testing and application of mathematical models to assess the risk and predict the disease. These efforts have included the integration of new data, epidemiological knowledge, statistical methods, and advances in computer simulation to develop models and systems with different spatial and temporal scales, objectives and audience. In this review, we present a comprehensive discussion on the models and systems that have been tested to predict and assess the risk of Asian soybean rust. Limitations, uncertainties and challenges for modelers are also discussed.
653 $aSoybean
700 1 $aGODOY, C. V.
700 1 $aCANTERI, M. G.
700 1 $aREIS, E. M.
700 1 $aYANG, X. B.
773 $tFitopatologia Brasileira, Brasília, DF$gv.31, n. 6, p. 533-544, Nov./Dec. 2006.
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