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| 1. |  | MEDEIROS, R. D. de; SOARES, A. A.; GUIMARAES, R. M. Compactacao do solo e manejo da agua.I efeitos sobre a absorcao de N, P, K, massa seca de raizes e parte aerea de plantas de arroz. Ciencia e Agrotecnologia, Lavras, v. 29, n. 5, p. 940-947, set.out. 2005.| Biblioteca(s): Epagri-Sede. |
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| 7. | | BARBERENA, DI. da S.; MEDEIROS, R. D. de; BARBOSA, G. F. Desenvolvimento e produtividade de arroz irrigado em resposta a diferentes doses de fósforo e potássio, em várzea de primeiro ano, no estado de Roraima. Ciência e Agrotecnologia, Lavras, MG, v. 35, n. 3, p. 462-470, maio/jun. 2011.| Biblioteca(s): Epagri-Sede. |
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| 8. | | MOREIRA, M. A. B.; MEDEIROS, R. D.; OLIVEIRA JUNIOR, J. O. L. de. Ocorrencia de plantas nativas e daninhas como hospedeiros alternativos da mosca branca, Bemisia argentifolii (Bellows & Perring, 1994), (Hemiptera: Aleyrodidae), no Rio Grande do Norte, Brasil. Revista Cientifica Rural, Bage, v. 6, n. 2, p.77-83, 2001.| Biblioteca(s): Epagri-Sede. |
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| 9. | | MEDEIROS, R. D. de; OLIVEIRA, J. A.; GUIMARAES, R. M.; SOARES, A, A,; EVANGELISTA, J. R. E. Efeito do teor de agua no solo sobre a emergencia e desenvolvimento de plantulas de arroz. Revista Ciencia Agronomica, Fortaleza, v. 37, n. 1, p. 55-58, 2006.| Biblioteca(s): Epagri-Sede. |
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Registro Completo
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Biblioteca(s): |
Epagri-Sede. |
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Data corrente: |
30/09/2022 |
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Data da última atualização: |
30/09/2022 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
MALLMANN, G.; FERNANDES, J. M. C.; MONTEIRO, F. P.; LINS JÚNIOR, J. C.; FELTRIM, A. L.; WAMSER, A. F.; VALMORBIDA, J. |
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Título: |
Evaluation of a generic model to predict garlic rust on San Valentim cultivar in Caçador, SC. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
In: WORKSHOP BRASILEIRO DE EPIDEMIOLOGIA DE DOENÇAS DE PLANTAS, 6., 2022, Chapecó, SC. Resumos... Brasília: Sociedade Brasileira de Fitopatologia, 2022. p. 32 |
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Idioma: |
Inglês |
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Conteúdo: |
Garlic rust caused by the fungus Puccinia porri, is a disease of widespread occurrence in
all regions of the world and, during the cultivation of susceptible plants, there are
environmental conditions favorable to their progress. The objective of this work was to
validate a generic model for the prediction of garlic rust. An agrometeorological station
was used to collect the meteorological data that were inserted in the model used to predict
the occurrence of rust. For the development of the model, the life of a pathogen was taken
as a basis, creating an easily parameterizable structur. All processing takes place through
the exchange of data on the number of organs created and the available area of each one
(healthy area) at that moment and through information on the area that the disease take
place (infected area). From the combination of temperature, relative humidity (≥90%) and
precipitation (input data) variables, the model performs the simulation and provides as
output data the amount of spores present in the environment. Field experiments were
carried out with cultivar San Valentim, in the 2019, 2020 and 2021 harvests, at the
Experimental Station of Caçador (Epagri). The inoculation of plants with the fungus P.
porri occurred naturally in the field. From the cloves differentiation phase, the weekly
evaluations of incidence and severity of rust in the field began. To assess severity, a
diagrammatic scale was used. Data collected in the field were compared with simulated
data to validate the model. It was verified by the simulated and observed data that the
years 2019 and 2020 were quite epidemic for garlic rust. In the 2021 harvest, there was
less severity compared to previous years. The simulated and observed data showed a
similar trend in the rust epidemic, indicating that the generic model is correctly predicting
rust. The garlic rust prediction model could be a useful tool for technicians and producers,
in the decision making of the ideal moment to carry out the disease control. MenosGarlic rust caused by the fungus Puccinia porri, is a disease of widespread occurrence in
all regions of the world and, during the cultivation of susceptible plants, there are
environmental conditions favorable to their progress. The objective of this work was to
validate a generic model for the prediction of garlic rust. An agrometeorological station
was used to collect the meteorological data that were inserted in the model used to predict
the occurrence of rust. For the development of the model, the life of a pathogen was taken
as a basis, creating an easily parameterizable structur. All processing takes place through
the exchange of data on the number of organs created and the available area of each one
(healthy area) at that moment and through information on the area that the disease take
place (infected area). From the combination of temperature, relative humidity (≥90%) and
precipitation (input data) variables, the model performs the simulation and provides as
output data the amount of spores present in the environment. Field experiments were
carried out with cultivar San Valentim, in the 2019, 2020 and 2021 harvests, at the
Experimental Station of Caçador (Epagri). The inoculation of plants with the fungus P.
porri occurred naturally in the field. From the cloves differentiation phase, the weekly
evaluations of incidence and severity of rust in the field began. To assess severity, a
diagrammatic scale was used. Data collected in the field were compared with sim... Mostrar Tudo |
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Thesagro: |
disease; Epidemiology; severity. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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Marc: |
LEADER 02804naa a2200229 a 4500
001 1132474
005 2022-09-30
008 2022 bl uuuu u00u1 u #d
100 1 $aMALLMANN, G.
245 $aEvaluation of a generic model to predict garlic rust on San Valentim cultivar in Caçador, SC.$h[electronic resource]
260 $c2022
520 $aGarlic rust caused by the fungus Puccinia porri, is a disease of widespread occurrence in all regions of the world and, during the cultivation of susceptible plants, there are environmental conditions favorable to their progress. The objective of this work was to validate a generic model for the prediction of garlic rust. An agrometeorological station was used to collect the meteorological data that were inserted in the model used to predict the occurrence of rust. For the development of the model, the life of a pathogen was taken as a basis, creating an easily parameterizable structur. All processing takes place through the exchange of data on the number of organs created and the available area of each one (healthy area) at that moment and through information on the area that the disease take place (infected area). From the combination of temperature, relative humidity (≥90%) and precipitation (input data) variables, the model performs the simulation and provides as output data the amount of spores present in the environment. Field experiments were carried out with cultivar San Valentim, in the 2019, 2020 and 2021 harvests, at the Experimental Station of Caçador (Epagri). The inoculation of plants with the fungus P. porri occurred naturally in the field. From the cloves differentiation phase, the weekly evaluations of incidence and severity of rust in the field began. To assess severity, a diagrammatic scale was used. Data collected in the field were compared with simulated data to validate the model. It was verified by the simulated and observed data that the years 2019 and 2020 were quite epidemic for garlic rust. In the 2021 harvest, there was less severity compared to previous years. The simulated and observed data showed a similar trend in the rust epidemic, indicating that the generic model is correctly predicting rust. The garlic rust prediction model could be a useful tool for technicians and producers, in the decision making of the ideal moment to carry out the disease control.
650 $adisease
650 $aEpidemiology
650 $aseverity
700 1 $aFERNANDES, J. M. C.
700 1 $aMONTEIRO, F. P.
700 1 $aLINS JÚNIOR, J. C.
700 1 $aFELTRIM, A. L.
700 1 $aWAMSER, A. F.
700 1 $aVALMORBIDA, J.
773 $tIn: WORKSHOP BRASILEIRO DE EPIDEMIOLOGIA DE DOENÇAS DE PLANTAS, 6., 2022, Chapecó, SC. Resumos... Brasília: Sociedade Brasileira de Fitopatologia, 2022. p. 32
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