Models and applications for risk assessment and prediction of Asian soybean rust epidemics.
Autor(a) principal: | |
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Data de Publicação: | 2006 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
Texto Completo: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/469959 |
Resumo: | 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. |
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Models and applications for risk assessment and prediction of Asian soybean rust epidemics.SoybeanAsian 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.2011-12-14T00:01:33Z2011-12-14T00:01:33Z2007-04-0420062011-12-14T00:01:33Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleFitopatologia Brasileira, Brasília, DF, v.31, n. 6, p. 533-544, Nov./Dec. 2006.http://www.alice.cnptia.embrapa.br/alice/handle/doc/469959engDEL PONTE, E. M.GODOY, C. V.CANTERI, M. G.REIS, E. M.YANG, X. B.info:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2017-08-15T23:13:33Zoai:www.alice.cnptia.embrapa.br:doc/469959Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542017-08-15T23:13:33falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-08-15T23:13:33Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Models and applications for risk assessment and prediction of Asian soybean rust epidemics. |
title |
Models and applications for risk assessment and prediction of Asian soybean rust epidemics. |
spellingShingle |
Models and applications for risk assessment and prediction of Asian soybean rust epidemics. DEL PONTE, E. M. Soybean |
title_short |
Models and applications for risk assessment and prediction of Asian soybean rust epidemics. |
title_full |
Models and applications for risk assessment and prediction of Asian soybean rust epidemics. |
title_fullStr |
Models and applications for risk assessment and prediction of Asian soybean rust epidemics. |
title_full_unstemmed |
Models and applications for risk assessment and prediction of Asian soybean rust epidemics. |
title_sort |
Models and applications for risk assessment and prediction of Asian soybean rust epidemics. |
author |
DEL PONTE, E. M. |
author_facet |
DEL PONTE, E. M. GODOY, C. V. CANTERI, M. G. REIS, E. M. YANG, X. B. |
author_role |
author |
author2 |
GODOY, C. V. CANTERI, M. G. REIS, E. M. YANG, X. B. |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
DEL PONTE, E. M. GODOY, C. V. CANTERI, M. G. REIS, E. M. YANG, X. B. |
dc.subject.por.fl_str_mv |
Soybean |
topic |
Soybean |
description |
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. |
publishDate |
2006 |
dc.date.none.fl_str_mv |
2006 2007-04-04 2011-12-14T00:01:33Z 2011-12-14T00:01:33Z 2011-12-14T00:01:33Z |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
Fitopatologia Brasileira, Brasília, DF, v.31, n. 6, p. 533-544, Nov./Dec. 2006. http://www.alice.cnptia.embrapa.br/alice/handle/doc/469959 |
identifier_str_mv |
Fitopatologia Brasileira, Brasília, DF, v.31, n. 6, p. 533-544, Nov./Dec. 2006. |
url |
http://www.alice.cnptia.embrapa.br/alice/handle/doc/469959 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
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Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
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EMBRAPA |
institution |
EMBRAPA |
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Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
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Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
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Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
cg-riaa@embrapa.br |
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1794503356317696000 |