Influence of Climatic Variables on Incidence of Whitefly-Transmitted Begomovirus in Soybean and Bean Crops in North-Western Argentina
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...
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| Format: | info:ar-repo/semantics/artículo |
| Language: | Inglés |
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MDPI
2023
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| Online Access: | http://hdl.handle.net/20.500.12123/14130 https://www.mdpi.com/1999-4915/15/2/462 https://doi.org/10.3390/v15020462 |
| _version_ | 1855037067683168256 |
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| author | Reyna, Pablo Gastón Suarez, Franco Balzarini, Mónica Rodriguez Pardina, Patricia |
| author_browse | Balzarini, Mónica Reyna, Pablo Gastón Rodriguez Pardina, Patricia Suarez, Franco |
| author_facet | Reyna, Pablo Gastón Suarez, Franco Balzarini, Mónica Rodriguez Pardina, Patricia |
| author_sort | Reyna, Pablo Gastón |
| collection | INTA Digital |
| description | 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 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. |
| format | info:ar-repo/semantics/artículo |
| id | INTA14130 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | MDPI |
| publisherStr | MDPI |
| record_format | dspace |
| spelling | INTA141302023-03-03T10:27:48Z Influence of Climatic Variables on Incidence of Whitefly-Transmitted Begomovirus in Soybean and Bean Crops in North-Western Argentina Reyna, Pablo Gastón Suarez, Franco Balzarini, Mónica Rodriguez Pardina, Patricia Viroses Weather Virosis Begomovirus Argentina Tiempo Meteorológico Pathosystem Viral Diseases Predictive Model 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 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. Instituto de Patología Vegetal Fil: Reyna, Pablo Gastón. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Reyna, Pablo Gastón. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; Argentina Fil: Suarez, Franco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Suarez, Franco. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; Argentina Fil: Balzarini, Monica. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina Fil: Balzarini, Monica. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Fitopatología y Modelización Agrícola (UFyMA); Argentina Fil: Balzarini, Mónica. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; Argentina Fil: Rodriguez Pardina, Patricia. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; Argentina Fil: Rodriguez Pardina, Patricia. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Fitopatología y Modelización Agrícola (UFyMA); Argentina 2023-03-03T10:22:19Z 2023-03-03T10:22:19Z 2023-02-02 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/14130 https://www.mdpi.com/1999-4915/15/2/462 1999-4915 (online) https://doi.org/10.3390/v15020462 eng 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) application/pdf MDPI Viruses 15 (2) : 462 (February 2023) |
| spellingShingle | Viroses Weather Virosis Begomovirus Argentina Tiempo Meteorológico Pathosystem Viral Diseases Predictive Model Reyna, Pablo Gastón Suarez, Franco Balzarini, Mónica Rodriguez Pardina, Patricia Influence of Climatic Variables on Incidence of Whitefly-Transmitted Begomovirus in Soybean and Bean Crops in North-Western Argentina |
| title | Influence of Climatic Variables on Incidence of Whitefly-Transmitted Begomovirus in Soybean and Bean Crops in North-Western Argentina |
| title_full | Influence of Climatic Variables on Incidence of Whitefly-Transmitted Begomovirus in Soybean and Bean Crops in North-Western Argentina |
| title_fullStr | Influence of Climatic Variables on Incidence of Whitefly-Transmitted Begomovirus in Soybean and Bean Crops in North-Western Argentina |
| title_full_unstemmed | Influence of Climatic Variables on Incidence of Whitefly-Transmitted Begomovirus in Soybean and Bean Crops in North-Western Argentina |
| title_short | Influence of Climatic Variables on Incidence of Whitefly-Transmitted Begomovirus in Soybean and Bean Crops in North-Western Argentina |
| title_sort | influence of climatic variables on incidence of whitefly transmitted begomovirus in soybean and bean crops in north western argentina |
| topic | Viroses Weather Virosis Begomovirus Argentina Tiempo Meteorológico Pathosystem Viral Diseases Predictive Model |
| url | http://hdl.handle.net/20.500.12123/14130 https://www.mdpi.com/1999-4915/15/2/462 https://doi.org/10.3390/v15020462 |
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