Weather-based predictive models for Diaporthe helianthi ascospore release in Uruguay

Autores
Moschini, Ricardo Carlos; Rodríguez, M.J; Martinez, Malvina Irene; Stewart, S.
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Stem canker (SC), caused by Diaporthe helianthi, is the most serious sunflower disease in Uruguay. Yield losses have been estimated up to 75%. Chemical control is one of the strategies used to manage this disease, but fungicide application should be done before symptoms are visible. Ascospores are the primary source of inoculum, they are produced in perithecia which develop in infected stubble and are dispersed by wind to infect plants. As in other monocyclic diseases, quantifying primary inoculum is essential to predict an epidemic. In this study, ascospores were trapped on microscope slides with solid petroleum jelly which were placed on top of flat open cages filled with natural infected stubble. Cages were placed outdoors, slides where replaced twice a week and stained ascospores were counted under the microscope. Our objective was to develop weather-based models to predict ascospore release levels of D. helianthi from infected stubble. Explanatory weather variables were calculated during the seven-day periods prior to each field weekly ascospore count using daily weather station data from La Estanzuela, Uruguay. Then, logistic models were fit to estimate probabilities of having severe or moderate to light levels of ascospore counts. The best models included variables associated to the precipitation and dew-induced wetness frequency, combinated with the simultaneous occurrence of high relative humidity or low thermal amplitude records. Estimating the evolution of ascospore release through the weather-based models might help to guide preventive fungicide applications to control stem canker in Uruguay
Fil: Moschini, Ricardo Carlos. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Rodríguez, M.J. Instituto Nacional de Investigaciones Agropecuarias (INIA), La Estanzuela. Sección Protección Vegetal; Uruguay
Fil: Martinez, Malvina Irene. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Stewart, S. Instituto Nacional de Investigaciones Agropecuarias (INIA), La Estanzuela. Sección Protección Vegetal; Uruguay
Fuente
Austrasian plant pathology 48 (5) : 519-527.(September 2019)
Materia
Logit Analysis
Weather
Helianthus Annuus
Diaporthe Helianthi
Uruguay
Stem Canker
Sunflower
Logistic Models
Nivel de accesibilidad
acceso restringido
Condiciones de uso
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/6117
Acceder
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oai_identifier_str oai:localhost:20.500.12123/6117
network_acronym_str INTADig
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network_name_str INTA Digital (INTA)
spelling Weather-based predictive models for Diaporthe helianthi ascospore release in UruguayMoschini, Ricardo CarlosRodríguez, M.JMartinez, Malvina IreneStewart, S.Logit AnalysisWeatherHelianthus AnnuusDiaporthe HelianthiUruguayStem CankerSunflowerLogistic ModelsStem canker (SC), caused by Diaporthe helianthi, is the most serious sunflower disease in Uruguay. Yield losses have been estimated up to 75%. Chemical control is one of the strategies used to manage this disease, but fungicide application should be done before symptoms are visible. Ascospores are the primary source of inoculum, they are produced in perithecia which develop in infected stubble and are dispersed by wind to infect plants. As in other monocyclic diseases, quantifying primary inoculum is essential to predict an epidemic. In this study, ascospores were trapped on microscope slides with solid petroleum jelly which were placed on top of flat open cages filled with natural infected stubble. Cages were placed outdoors, slides where replaced twice a week and stained ascospores were counted under the microscope. Our objective was to develop weather-based models to predict ascospore release levels of D. helianthi from infected stubble. Explanatory weather variables were calculated during the seven-day periods prior to each field weekly ascospore count using daily weather station data from La Estanzuela, Uruguay. Then, logistic models were fit to estimate probabilities of having severe or moderate to light levels of ascospore counts. The best models included variables associated to the precipitation and dew-induced wetness frequency, combinated with the simultaneous occurrence of high relative humidity or low thermal amplitude records. Estimating the evolution of ascospore release through the weather-based models might help to guide preventive fungicide applications to control stem canker in UruguayFil: Moschini, Ricardo Carlos. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Rodríguez, M.J. Instituto Nacional de Investigaciones Agropecuarias (INIA), La Estanzuela. Sección Protección Vegetal; UruguayFil: Martinez, Malvina Irene. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Stewart, S. Instituto Nacional de Investigaciones Agropecuarias (INIA), La Estanzuela. Sección Protección Vegetal; UruguaySpringer2019-10-15T18:17:46Z2019-10-15T18:17:46Z2019-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://link.springer.com/content/pdf/10.1007%2Fs13313-019-00655-x.pdfhttp://hdl.handle.net/20.500.12123/61171448-6032https://doi.org/10.1007/s13313-019-00655-xAustrasian plant pathology 48 (5) : 519-527.(September 2019)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología AgropecuariaengUruguay (nation)info:eu-repo/semantics/restrictedAccess2025-09-04T09:48:13Zoai:localhost:20.500.12123/6117instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-04 09:48:13.417INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Weather-based predictive models for Diaporthe helianthi ascospore release in Uruguay
title Weather-based predictive models for Diaporthe helianthi ascospore release in Uruguay
spellingShingle Weather-based predictive models for Diaporthe helianthi ascospore release in Uruguay
Moschini, Ricardo Carlos
Logit Analysis
Weather
Helianthus Annuus
Diaporthe Helianthi
Uruguay
Stem Canker
Sunflower
Logistic Models
title_short Weather-based predictive models for Diaporthe helianthi ascospore release in Uruguay
title_full Weather-based predictive models for Diaporthe helianthi ascospore release in Uruguay
title_fullStr Weather-based predictive models for Diaporthe helianthi ascospore release in Uruguay
title_full_unstemmed Weather-based predictive models for Diaporthe helianthi ascospore release in Uruguay
title_sort Weather-based predictive models for Diaporthe helianthi ascospore release in Uruguay
dc.creator.none.fl_str_mv Moschini, Ricardo Carlos
Rodríguez, M.J
Martinez, Malvina Irene
Stewart, S.
author Moschini, Ricardo Carlos
author_facet Moschini, Ricardo Carlos
Rodríguez, M.J
Martinez, Malvina Irene
Stewart, S.
author_role author
author2 Rodríguez, M.J
Martinez, Malvina Irene
Stewart, S.
author2_role author
author
author
dc.subject.none.fl_str_mv Logit Analysis
Weather
Helianthus Annuus
Diaporthe Helianthi
Uruguay
Stem Canker
Sunflower
Logistic Models
topic Logit Analysis
Weather
Helianthus Annuus
Diaporthe Helianthi
Uruguay
Stem Canker
Sunflower
Logistic Models
dc.description.none.fl_txt_mv Stem canker (SC), caused by Diaporthe helianthi, is the most serious sunflower disease in Uruguay. Yield losses have been estimated up to 75%. Chemical control is one of the strategies used to manage this disease, but fungicide application should be done before symptoms are visible. Ascospores are the primary source of inoculum, they are produced in perithecia which develop in infected stubble and are dispersed by wind to infect plants. As in other monocyclic diseases, quantifying primary inoculum is essential to predict an epidemic. In this study, ascospores were trapped on microscope slides with solid petroleum jelly which were placed on top of flat open cages filled with natural infected stubble. Cages were placed outdoors, slides where replaced twice a week and stained ascospores were counted under the microscope. Our objective was to develop weather-based models to predict ascospore release levels of D. helianthi from infected stubble. Explanatory weather variables were calculated during the seven-day periods prior to each field weekly ascospore count using daily weather station data from La Estanzuela, Uruguay. Then, logistic models were fit to estimate probabilities of having severe or moderate to light levels of ascospore counts. The best models included variables associated to the precipitation and dew-induced wetness frequency, combinated with the simultaneous occurrence of high relative humidity or low thermal amplitude records. Estimating the evolution of ascospore release through the weather-based models might help to guide preventive fungicide applications to control stem canker in Uruguay
Fil: Moschini, Ricardo Carlos. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Rodríguez, M.J. Instituto Nacional de Investigaciones Agropecuarias (INIA), La Estanzuela. Sección Protección Vegetal; Uruguay
Fil: Martinez, Malvina Irene. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Stewart, S. Instituto Nacional de Investigaciones Agropecuarias (INIA), La Estanzuela. Sección Protección Vegetal; Uruguay
description Stem canker (SC), caused by Diaporthe helianthi, is the most serious sunflower disease in Uruguay. Yield losses have been estimated up to 75%. Chemical control is one of the strategies used to manage this disease, but fungicide application should be done before symptoms are visible. Ascospores are the primary source of inoculum, they are produced in perithecia which develop in infected stubble and are dispersed by wind to infect plants. As in other monocyclic diseases, quantifying primary inoculum is essential to predict an epidemic. In this study, ascospores were trapped on microscope slides with solid petroleum jelly which were placed on top of flat open cages filled with natural infected stubble. Cages were placed outdoors, slides where replaced twice a week and stained ascospores were counted under the microscope. Our objective was to develop weather-based models to predict ascospore release levels of D. helianthi from infected stubble. Explanatory weather variables were calculated during the seven-day periods prior to each field weekly ascospore count using daily weather station data from La Estanzuela, Uruguay. Then, logistic models were fit to estimate probabilities of having severe or moderate to light levels of ascospore counts. The best models included variables associated to the precipitation and dew-induced wetness frequency, combinated with the simultaneous occurrence of high relative humidity or low thermal amplitude records. Estimating the evolution of ascospore release through the weather-based models might help to guide preventive fungicide applications to control stem canker in Uruguay
publishDate 2019
dc.date.none.fl_str_mv 2019-10-15T18:17:46Z
2019-10-15T18:17:46Z
2019-08-01
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 https://link.springer.com/content/pdf/10.1007%2Fs13313-019-00655-x.pdf
http://hdl.handle.net/20.500.12123/6117
1448-6032
https://doi.org/10.1007/s13313-019-00655-x
url https://link.springer.com/content/pdf/10.1007%2Fs13313-019-00655-x.pdf
http://hdl.handle.net/20.500.12123/6117
https://doi.org/10.1007/s13313-019-00655-x
identifier_str_mv 1448-6032
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
eu_rights_str_mv restrictedAccess
dc.format.none.fl_str_mv application/pdf
dc.coverage.none.fl_str_mv Uruguay (nation)
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv Austrasian plant pathology 48 (5) : 519-527.(September 2019)
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
_version_ 1842341372025110528
score 12.623145

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