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
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/1226
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oai_identifier_str oai:localhost:20.500.12123/1226
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network_name_str INTA Digital (INTA)
spelling 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)2025-10-23T11:16:22Zoai: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:l2025-10-23 11:16:23.116INTA 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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