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resumen

Resumen
Over the last 20 years, begomoviruses have emerged as devastating pathogens, limiting the production of different crops worldwide. Weather conditions increase vector populations, with negative effects on crop production. In this work we evaluate the relationship between the incidence of begomovirus and weather before and during the crop cycle. Soybean and bean fields from north-western (NW) Argentina were monitored between 2001 and 2018 and classified as [ver mas...]
dc.contributor.authorReyna, Pablo Gastón
dc.contributor.authorSuarez, Franco
dc.contributor.authorBalzarini, Mónica
dc.contributor.authorRodriguez Pardina, Patricia
dc.date.accessioned2023-03-03T10:22:19Z
dc.date.available2023-03-03T10:22:19Z
dc.date.issued2023-02-02
dc.identifier.issn1999-4915 (online)
dc.identifier.otherhttps://doi.org/10.3390/v15020462
dc.identifier.urihttp://hdl.handle.net/20.500.12123/14130
dc.identifier.urihttps://www.mdpi.com/1999-4915/15/2/462
dc.description.abstractOver the last 20 years, begomoviruses have emerged as devastating pathogens, limiting the production of different crops worldwide. Weather conditions increase vector populations, with negative effects on crop production. In this work we evaluate the relationship between the incidence of begomovirus and weather before and during the crop cycle. Soybean and bean fields from north-western (NW) Argentina were monitored between 2001 and 2018 and classified as moderate (≤50%) or severe (>50%) according to the begomovirus incidence. Bean golden mosaic virus (BGMV) and soybean blistering mosaic virus (SbBMV) were the predominant begomovirus in bean and soybean crops, respectively. Nearly 200 bio-meteorological variables were constructed by summarizing climatic variables in 10-day periods from July to November of each crop year. The studied variables included temperature, precipitation, relative humidity, wind (speed and direction), pressure, cloudiness, and visibility. For bean, high maximum winter temperatures, low spring humidity, and precipitation 10 days before planting correlated with severe incidence. In soybeans, high temperatures in late winter and in the pre-sowing period, and low spring precipitations were found to be good predictors of high incidence of begomovirus. The results suggest that temperature and pre-sowing precipitations can be used to predict the incidence status [predictive accuracy: 80% (bean) and 75% (soybean)]. Thus, these variables can be incorporated in early warning systems for crop management decision-making to reduce the virus impact on bean and soybean crops.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherMDPIes_AR
dc.rightsinfo:eu-repo/semantics/openAccesses_AR
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/es_AR
dc.sourceViruses 15 (2) : 462 (February 2023)es_AR
dc.subjectViroseseng
dc.subjectWeathereng
dc.subjectVirosises_AR
dc.subjectBegomoviruses_AR
dc.subjectArgentinaes_AR
dc.subjectTiempo Meteorológico
dc.subject.otherPathosystemeng
dc.subject.otherViral Diseaseseng
dc.subject.otherPredictive Modeleng
dc.titleInfluence of Climatic Variables on Incidence of Whitefly-Transmitted Begomovirus in Soybean and Bean Crops in North-Western Argentinaes_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.rights.licenseCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)es_AR
dc.description.origenInstituto de Patología Vegetales_AR
dc.description.filFil: Reyna, Pablo Gastón. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentinaes_AR
dc.description.filFil: Reyna, Pablo Gastón. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; Argentinaes_AR
dc.description.filFil: Suarez, Franco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentinaes_AR
dc.description.filFil: Suarez, Franco. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; Argentinaes_AR
dc.description.filFil: Balzarini, Monica. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentinaes_AR
dc.description.filFil: Balzarini, Monica. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Fitopatología y Modelización Agrícola (UFyMA); Argentinaes_AR
dc.description.filFil: Balzarini, Mónica. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; Argentinaes_AR
dc.description.filFil: Rodriguez Pardina, Patricia. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; Argentinaes_AR
dc.description.filFil: Rodriguez Pardina, Patricia. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Fitopatología y Modelización Agrícola (UFyMA); Argentinaes_AR
dc.subtypecientifico


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