Department of Soil and Environment, Swedish University of Agricultural Sciences, 532 23 Skara, Sweden.
Agroväst Livsmedel AB, 532 23 Skara, Sweden.
Toxins (Basel). 2021 Oct 20;13(11):737. doi: 10.3390/toxins13110737.
Fusarium head blight (FHB) is one of the most serious diseases of small-grain cereals worldwide, resulting in yield reduction and an accumulation of the mycotoxin deoxynivalenol (DON) in grain. Weather conditions are known to have a significant effect on the ability of fusaria to infect cereals and produce toxins. In the past 10 years, severe outbreaks of FHB, and grain DON contamination exceeding the EU health safety limits, have occurred in countries in the Baltic Sea region. In this study, extensive data from field trials in Sweden, Poland and Lithuania were analysed to identify the most crucial weather variables for the ability of to produce DON. Models were developed for the prediction of DON contamination levels in harvested grain exceeding 200 µg kg for oats, spring barley and spring wheat in Sweden and winter wheat in Poland, and 1250 µg kg for spring wheat in Lithuania. These models were able to predict high DON levels with an accuracy of 70-81%. Relative humidity (RH) and precipitation (PREC) were identified as the weather factors with the greatest influence on DON accumulation in grain, with high RH and PREC around flowering and later in grain development and ripening correlated with high DON levels. High temperatures during grain development and senescence reduced the risk of DON accumulation. The performance of the models, based only on weather variables, was relatively accurate. In future studies, it might be of interest to determine whether inclusion of variables such as pre-crop, agronomic factors and crop resistance to FHB could further improve the performance of the models.
镰刀菌穗腐病(FHB)是全球小粒谷物最严重的病害之一,可导致减产和谷物中脱氧雪腐镰刀菌烯醇(DON)毒素的积累。天气条件对镰刀菌感染谷物和产生毒素的能力有显著影响。在过去的 10 年中,波罗的海地区的一些国家发生了严重的 FHB 爆发和谷物 DON 污染超过欧盟健康安全限量的情况。在这项研究中,对瑞典、波兰和立陶宛田间试验的大量数据进行了分析,以确定对产生 DON 能力最重要的天气变量。针对瑞典燕麦、春大麦和春小麦收获时 DON 污染水平超过 200μg/kg,波兰冬小麦超过 1250μg/kg的情况,建立了 DON 预测模型。这些模型能够以 70-81%的准确率预测 DON 高水平。相对湿度(RH)和降水(PREC)被确定为对谷物中 DON 积累影响最大的天气因素,开花前后以及谷物发育和成熟过程中的高 RH 和 PREC 与 DON 水平升高相关。谷物发育和衰老期间的高温降低了 DON 积累的风险。仅基于天气变量的模型性能相对准确。在未来的研究中,确定是否可以包含作物前茬、农艺因素和作物对 FHB 的抗性等变量,以进一步提高模型的性能,可能会很有趣。