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 | Acceso al texto completo restringido a Biblioteca INIA La Estanzuela. Por información adicional contacte bib_le@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha actual : |
07/08/2019 |
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Actualizado : |
10/02/2020 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
MOSCHINI, R.C.; RODRIGUEZ, M.; MARTÍNEZ, M.I.; STEWART, S. |
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Afiliación : |
R. C. MOSCHINI, Instituto de Clima y Agua, CIRN INTA, Castelar, Nicolás Repetto y de los Reseros s/n, Buenos Aires, Argentina.; MARCELO JULIAN RODRIGUEZ ALONZO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; M. I. MARTÍNEZ, Instituto de Clima y Agua, CIRN INTA, Castelar, Nicolás Repetto y de los Reseros s/n, Buenos Aires, Argentina.; SILVINA MARIA STEWART SONEIRA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Weather-based predictive models for Diaporthe helianthi ascospore release in Uruguay. |
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Fecha de publicación : |
2019 |
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Fuente / Imprenta : |
Australasian Plant Pathology , 2019.[Online First]. |
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ISSN : |
0815-319 |
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DOI : |
10.1007/s13313-019-00655-x |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: 13 March 2019/Accepted: 22 July 2019/Published online: 1 August 2019. |
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Contenido : |
ABSTRACT.
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.
© 2019, Australasian Plant Pathology Society Inc. MenosABSTRACT.
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 ... Presentar Todo |
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Palabras claves : |
CANCRO DEL TALLO; LOGISTIC MODELS; STEM CANKER; SUNFLOWER; WEATHER VARIABLE. |
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Thesagro : |
GIRASOL; HELIANTHUS ANNUUS. |
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Asunto categoría : |
H20 Enfermedades de las plantas |
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Marc : |
LEADER 02563naa a2200277 a 4500
001 1059986
005 2020-02-10
008 2019 bl uuuu u00u1 u #d
022 $a0815-319
024 7 $a10.1007/s13313-019-00655-x$2DOI
100 1 $aMOSCHINI, R.C.
245 $aWeather-based predictive models for Diaporthe helianthi ascospore release in Uruguay.$h[electronic resource]
260 $c2019
500 $aArticle history: Received: 13 March 2019/Accepted: 22 July 2019/Published online: 1 August 2019.
520 $aABSTRACT. 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. © 2019, Australasian Plant Pathology Society Inc.
650 $aGIRASOL
650 $aHELIANTHUS ANNUUS
653 $aCANCRO DEL TALLO
653 $aLOGISTIC MODELS
653 $aSTEM CANKER
653 $aSUNFLOWER
653 $aWEATHER VARIABLE
700 1 $aRODRIGUEZ, M.
700 1 $aMARTÍNEZ, M.I.
700 1 $aSTEWART, S.
773 $tAustralasian Plant Pathology , 2019.[Online First].
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