小麦赤霉病物联网实时监测预警技术试验评估

Experimental evaluation of real-time monitoring and early warning technology for Fusarium head blight based on Internet of Things

2017—2019年,在长江流域及黄淮沿淮麦区6个县(市)开展小麦赤霉病物联网实时监测预警技术试验,结果表明,应用小麦赤霉病物联网实时监测预警技术对小麦赤霉病病穗率和发生程度的平均预测准确率分别为79.9%和67.1%。其中,对赤霉病发生程度的预测准确率在黄淮沿淮麦区平均为84.3%,高于长江流域的50%;对病穗率的预测准确率在黄淮麦区平均为86.8%,高于长江流域的73.0%。模型对黄淮及沿淮麦区小麦赤霉病的短期预测效果较好。

From 2017 to 2019,experiments of mo nitoring and early warning technology of wheat Fusarium head blight were carried out in 6 counties in the Yangtze River Valley and Huanghuai wheat planted area.The results showed that the average accuracy of forecasting the diseased ears rate and the epidemic level of Fusarium head blight were 79.9%and74.5%,respectively.The average forecast accuracy of the epidemic level in the Huanghuai wheat planted area was 84.3%,which was higher than that of 67.1%in the Yangtze River valley.The average forecast accuracy of the diseased ears rate was 86.8%in the Huanghuai wheat planted area,which was also higher than that of 73.0%in the Yangtze River valley.The model has a good short-term early warning effect on Fusarium head blight in the Huanghuai wheat planted area.