Academy of National Food and Strategic Reserves Administration, No.11 Baiwanzhuang Str, Xicheng District, Beijing 100037, China.
Wageningen Food Safety Research, Akkermaalsbos 2, 6708 WB Wageningen, The Netherlands.
Food Chem. 2023 Mar 30;405(Pt A):134727. doi: 10.1016/j.foodchem.2022.134727. Epub 2022 Oct 26.
Deoxynivalenol (DON) in wheat is one of the major food safety concerns worldwide. In this study, 70 characteristic precursive factors associated with environment and 6 agronomic practicing factors were explored, using historical data of 479 wheat fields in the Huang-Huai-hai, China. Results showed that DON concentrations influenced by air temperature, relative humidity, precipitation, and sunshine duration in the period from 17 days before flowering to 10 days before harvest. Rice crop rotation, straw returning, larger density of sowing, and lower latitude planting increased DON risk. Furthermore, an empirical model of DON prediction was established. The classification accuracy of internal and external validation were 87.73% (R = 0.62) and 80.21% (R = 0.60), respectively. This model is the first large-scale prediction of mycotoxin contamination in grain at harvest in China. It can be used to predict the risk of DON contamination for nearly 14 % of the global wheat supply.
脱氧雪腐镰刀菌烯醇（DON）是小麦中存在的主要食品安全问题之一。本研究使用中国黄淮海地区 479 个麦田的历史数据，探讨了与环境相关的 70 个特征前驱因素和 6 个农业实践因素。结果表明，从开花前 17 天到收获前 10 天，DON 浓度受空气温度、相对湿度、降水和日照时间的影响。稻茬轮作、秸秆还田、播种密度增大和种植纬度降低会增加 DON 的风险。此外，还建立了 DON 预测的经验模型。内部和外部验证的分类准确性分别为 87.73%（R = 0.62）和 80.21%（R = 0.60）。这是中国首次对收获时粮食中霉菌毒素污染进行的大规模预测。该模型可用于预测全球近 14%小麦供应的 DON 污染风险。
