Soybean frogeye leaf spot [Cercospora sojina] : first weather-based prediction models developed from weather station and satellite data
- Autores
- Sepulcri, Maria Gabriela; Moschini, Ricardo Carlos; Carmona, Marcelo Anibal
- Año de publicación
- 2015
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- In Argentina, soybean frogeye leaf spot occurs sporadically. However, particularly in the Pampas Region, the incidence and severity of this fungal disease have significantly increased in the last years. In the present study, its epidemic progress was evaluated in six sites of the Pampas region during the 2009/2010 soybean season. Also, meteorological variables were calculated during the nine days previous to each field observation of disease occurrence for each site, using weather station and satellite data. Rain occurrence was obtained from the 3B42 TRMM product and temperature images were taken from NOAA-AVHRR. Then, logistic models were used to estimate probabilities of having severe or moderate to null disease. The stepwise procedure used to select the best model included the interaction (product) between wetness frequency (WF) and sum of days without precipitation (DwP) as a variable. Estimations from the resulting model agreed with the observed epidemiological curve for one of the sites studied (El Trébol, Santa Fe) during the 2010/2011 soybean season and coincided with the low disease presence recorded during the 2011/2012 soybean season. These new results could be useful as support for rational fungicide application.
Fil: Sepulcri, Maria Gabriela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Moschini, Ricardo Carlos. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Carmona, Marcelo Anibal. Universidad de Buenos Aires. Facultad de Agronomía. Cátedra de Fitopatología; Argentina - Fuente
- Advances in applied agricultural science 3 (6) : 1-13. (2015)
- Materia
-
Enfermedades de las Plantas
Plant Diseases
Forecasting
Remote Sensing
Climatic Data
Weather Forecasting
Soybeans
Técnicas de Predicción
Teledetección
Datos Climatológicos
Pronóstico del Tiempo
Soja
Cercospora Sojina
Modelos Logísticos
Logistic Models
Epidemiological Curve - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Instituto Nacional de Tecnología Agropecuaria
- OAI Identificador
- oai:localhost:20.500.12123/1226
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Soybean frogeye leaf spot [Cercospora sojina] : first weather-based prediction models developed from weather station and satellite dataSepulcri, Maria GabrielaMoschini, Ricardo CarlosCarmona, Marcelo AnibalEnfermedades de las PlantasPlant DiseasesForecastingRemote SensingClimatic DataWeather ForecastingSoybeansTécnicas de PredicciónTeledetecciónDatos ClimatológicosPronóstico del TiempoSojaCercospora SojinaModelos LogísticosLogistic ModelsEpidemiological CurveIn Argentina, soybean frogeye leaf spot occurs sporadically. However, particularly in the Pampas Region, the incidence and severity of this fungal disease have significantly increased in the last years. In the present study, its epidemic progress was evaluated in six sites of the Pampas region during the 2009/2010 soybean season. Also, meteorological variables were calculated during the nine days previous to each field observation of disease occurrence for each site, using weather station and satellite data. Rain occurrence was obtained from the 3B42 TRMM product and temperature images were taken from NOAA-AVHRR. Then, logistic models were used to estimate probabilities of having severe or moderate to null disease. The stepwise procedure used to select the best model included the interaction (product) between wetness frequency (WF) and sum of days without precipitation (DwP) as a variable. Estimations from the resulting model agreed with the observed epidemiological curve for one of the sites studied (El Trébol, Santa Fe) during the 2010/2011 soybean season and coincided with the low disease presence recorded during the 2011/2012 soybean season. These new results could be useful as support for rational fungicide application.Fil: Sepulcri, Maria Gabriela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Moschini, Ricardo Carlos. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Carmona, Marcelo Anibal. Universidad de Buenos Aires. Facultad de Agronomía. Cátedra de Fitopatología; Argentina2017-09-14T17:50:48Z2017-09-14T17:50:48Z2015-06-30info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/12262383-4234Advances in applied agricultural science 3 (6) : 1-13. (2015)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-09-29T13:44:10Zoai:localhost:20.500.12123/1226instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-29 13:44:10.933INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse |
dc.title.none.fl_str_mv |
Soybean frogeye leaf spot [Cercospora sojina] : first weather-based prediction models developed from weather station and satellite data |
title |
Soybean frogeye leaf spot [Cercospora sojina] : first weather-based prediction models developed from weather station and satellite data |
spellingShingle |
Soybean frogeye leaf spot [Cercospora sojina] : first weather-based prediction models developed from weather station and satellite data Sepulcri, Maria Gabriela Enfermedades de las Plantas Plant Diseases Forecasting Remote Sensing Climatic Data Weather Forecasting Soybeans Técnicas de Predicción Teledetección Datos Climatológicos Pronóstico del Tiempo Soja Cercospora Sojina Modelos Logísticos Logistic Models Epidemiological Curve |
title_short |
Soybean frogeye leaf spot [Cercospora sojina] : first weather-based prediction models developed from weather station and satellite data |
title_full |
Soybean frogeye leaf spot [Cercospora sojina] : first weather-based prediction models developed from weather station and satellite data |
title_fullStr |
Soybean frogeye leaf spot [Cercospora sojina] : first weather-based prediction models developed from weather station and satellite data |
title_full_unstemmed |
Soybean frogeye leaf spot [Cercospora sojina] : first weather-based prediction models developed from weather station and satellite data |
title_sort |
Soybean frogeye leaf spot [Cercospora sojina] : first weather-based prediction models developed from weather station and satellite data |
dc.creator.none.fl_str_mv |
Sepulcri, Maria Gabriela Moschini, Ricardo Carlos Carmona, Marcelo Anibal |
author |
Sepulcri, Maria Gabriela |
author_facet |
Sepulcri, Maria Gabriela Moschini, Ricardo Carlos Carmona, Marcelo Anibal |
author_role |
author |
author2 |
Moschini, Ricardo Carlos Carmona, Marcelo Anibal |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Enfermedades de las Plantas Plant Diseases Forecasting Remote Sensing Climatic Data Weather Forecasting Soybeans Técnicas de Predicción Teledetección Datos Climatológicos Pronóstico del Tiempo Soja Cercospora Sojina Modelos Logísticos Logistic Models Epidemiological Curve |
topic |
Enfermedades de las Plantas Plant Diseases Forecasting Remote Sensing Climatic Data Weather Forecasting Soybeans Técnicas de Predicción Teledetección Datos Climatológicos Pronóstico del Tiempo Soja Cercospora Sojina Modelos Logísticos Logistic Models Epidemiological Curve |
dc.description.none.fl_txt_mv |
In Argentina, soybean frogeye leaf spot occurs sporadically. However, particularly in the Pampas Region, the incidence and severity of this fungal disease have significantly increased in the last years. In the present study, its epidemic progress was evaluated in six sites of the Pampas region during the 2009/2010 soybean season. Also, meteorological variables were calculated during the nine days previous to each field observation of disease occurrence for each site, using weather station and satellite data. Rain occurrence was obtained from the 3B42 TRMM product and temperature images were taken from NOAA-AVHRR. Then, logistic models were used to estimate probabilities of having severe or moderate to null disease. The stepwise procedure used to select the best model included the interaction (product) between wetness frequency (WF) and sum of days without precipitation (DwP) as a variable. Estimations from the resulting model agreed with the observed epidemiological curve for one of the sites studied (El Trébol, Santa Fe) during the 2010/2011 soybean season and coincided with the low disease presence recorded during the 2011/2012 soybean season. These new results could be useful as support for rational fungicide application. Fil: Sepulcri, Maria Gabriela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina Fil: Moschini, Ricardo Carlos. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina Fil: Carmona, Marcelo Anibal. Universidad de Buenos Aires. Facultad de Agronomía. Cátedra de Fitopatología; Argentina |
description |
In Argentina, soybean frogeye leaf spot occurs sporadically. However, particularly in the Pampas Region, the incidence and severity of this fungal disease have significantly increased in the last years. In the present study, its epidemic progress was evaluated in six sites of the Pampas region during the 2009/2010 soybean season. Also, meteorological variables were calculated during the nine days previous to each field observation of disease occurrence for each site, using weather station and satellite data. Rain occurrence was obtained from the 3B42 TRMM product and temperature images were taken from NOAA-AVHRR. Then, logistic models were used to estimate probabilities of having severe or moderate to null disease. The stepwise procedure used to select the best model included the interaction (product) between wetness frequency (WF) and sum of days without precipitation (DwP) as a variable. Estimations from the resulting model agreed with the observed epidemiological curve for one of the sites studied (El Trébol, Santa Fe) during the 2010/2011 soybean season and coincided with the low disease presence recorded during the 2011/2012 soybean season. These new results could be useful as support for rational fungicide application. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-06-30 2017-09-14T17:50:48Z 2017-09-14T17:50:48Z |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/20.500.12123/1226 2383-4234 |
url |
http://hdl.handle.net/20.500.12123/1226 |
identifier_str_mv |
2383-4234 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
Advances in applied agricultural science 3 (6) : 1-13. (2015) reponame:INTA Digital (INTA) instname:Instituto Nacional de Tecnología Agropecuaria |
reponame_str |
INTA Digital (INTA) |
collection |
INTA Digital (INTA) |
instname_str |
Instituto Nacional de Tecnología Agropecuaria |
repository.name.fl_str_mv |
INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria |
repository.mail.fl_str_mv |
tripaldi.nicolas@inta.gob.ar |
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1844619117190971392 |
score |
12.559606 |