Unidad Ejecutora UFYMA-INTA-CONICET, Córdoba X5020ICA, Argentina.
Instituto Nacional de Tecnología Agropecuaria (INTA), Instituto de Patología Vegetal (IPAVE), Av. 11 de Septiembre, Córdoba 4755 X5014MGO, Argentina.
Viruses. 2023 Feb 7;15(2):462. doi: 10.3390/v15020462.
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.
在过去的 20 年中,双生病毒已成为具有破坏性的病原体,限制了全球不同作物的产量。天气条件会增加媒介种群,对作物生产产生负面影响。在这项工作中,我们评估了双生病毒与作物周期前后的天气之间的关系。在 2001 年至 2018 年间,对阿根廷西北部(NW)的大豆和豆类田进行了监测,并根据双生病毒的发病率将其分类为中度(≤50%)或严重(>50%)。豆黄花叶病毒(BGMV)和大豆疱斑病毒(SbBMV)分别是豆类和大豆作物中的主要双生病毒。将近 200 个生物气象变量是通过总结每个作物年 7 月至 11 月 10 天期间的气候变量来构建的。所研究的变量包括温度、降水、相对湿度、风速和风向、气压、云量和能见度。对于豆类来说,冬季最高温度高、春季湿度低以及种植前 10 天的降水与严重的发病率相关。对于大豆来说,冬季末和播种前的高温以及春季低降水被认为是双生病毒高发的良好预测指标。结果表明,温度和播种前的降水可以用来预测发病率[预测精度:80%(豆类)和 75%(大豆)]。因此,这些变量可以被纳入作物管理决策的早期预警系统中,以减少病毒对豆类和大豆作物的影响。