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徐 敏1, 2*, 周晴晴3, 杨荣明4, 徐忆菲1, 高 苹1, 2.植保无人飞机喷雾防治小麦赤霉病雾滴沉积量的气象影响因子分析及预报模型构建[J].植物保护,2024,50(3):70-79.
植保无人飞机喷雾防治小麦赤霉病雾滴沉积量的气象影响因子分析及预报模型构建
Analysis of meteorological factors affecting the droplets deposition in the prevention and control of wheat scab by unmanned aerial vehicle and construction of deposition prediction models
投稿时间:2023-08-25  修订日期:2023-10-26
DOI:10.16688/j.zwbh.2023451
中文关键词:  气象条件  植保无人飞机  沉积量  覆盖率
英文关键词:meteorological conditions  unmanned aerial vehicle for plant protection  droplets deposition  coverage rate
基金项目:江苏省第六期“333人才”培养支持项目;江苏省气象局揭榜挂帅项目(KZ202302); 江苏省农业科技自主创新项目[CX(23)1002]
作者单位E-mail
徐 敏1, 2*, 周晴晴3, 杨荣明4, 徐忆菲1, 高 苹1, 2 1. 江苏省气候中心, 南京 210019
2. 金坛国家气候观象台, 常州 213200
3. 农业农村部南京农业机械化研究所, 南京 210014
4. 江苏省植物保护植物检疫站, 南京 210036 
amin0506@163.com 
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中文摘要:
      为阐明不同气象条件对植保无人飞机防治赤霉病过程中冠层雾滴沉积的影响规律, 采用大疆T40四轴八旋翼植保无人飞机在不同麦区进行喷雾施药处理, 利用诱惑红示踪剂、聚酯卡、水敏纸等采集雾滴, 计算雾滴沉积量和覆盖率, 并对实时记录的田间气象条件进行分级, 其中温度分为A1(10℃≤T<20℃)、A2(20℃≤T<30℃)、A3(30℃≤T<40℃)等级, 相对湿度分为B1(30%≤RH<50%)、B2(50%≤RH<70%)、B3(70%≤RH<90%)等级, 风速分为C1(0 m/s≤V<1.6 m/s)、C2(1.6 m/s≤V<3.4 m/s)、C3(3.4 m/s≤V<5.5 m/s)等级。应用方差分析、主效应多重比较等统计方法, 揭示不同气象等级组合条件对雾滴沉积量和覆盖率的影响趋势, 并基于气象因子构建沉积量和覆盖率的预报模型。结果表明:温度、相对湿度、风速对雾滴沉积量的有利程度按等级排序分别为:A1≥A2>A3、B3>B2>B1、C1≥C2>C3。不同气象等级对覆盖率的影响规律与对沉积量的影响规律基本一致, 其中相对湿度对雾滴覆盖率和沉积量影响显著, 温度和风速的交互作用对覆盖率也具有显著影响。基于气象因子构建的冠层上层雾滴沉积量和覆盖率预报模型准确率分别为88.15%、82.82%, 均方根误差分别为0.030 μL/cm2、1.33%, 具有较高的可信度, 可应用于植保飞防气象预报服务。研究结果对植保无人飞机适时开展药剂喷洒作业、提高防治效果、减轻农药对农田生态环境的污染具有参考作用。
英文摘要:
      To clarify the influence of different meteorological conditions on droplets deposition within the canopy in the prevention and control of wheat scab by unmanned aerial vehicle (UAV), the Dajiang T40 four-axis eight-rotor UAV was used to spray fungicides solution in the different wheat areas. The deposition amount and coverage rate of fungicide droplets were collected and calculated using allure red tracer, polyester card, water-sensitive paper, etc. Field meteorological factors were recorded in real-time and categorized as follows: temperatures were classified as A1 (10℃≤T<20℃), A2 (20℃≤T<30℃), A3 (30℃≤T<40℃); relative humidity was classified as B1 (30%≤RH<50%), B2 (50%≤RH<70%), B3 (70%≤RH<90%); wind speed was classified as C1 (0 m/s≤V<1.6 m/s), C2 (1.6 m/s≤V<3.4 m/s), and C3 (3.4 m/s≤V<5.5 m/s). Statistical methods such as analysis of variance and multiple comparisons of main effects were used to uncover the trends in the impact of different combinations of meteorological levels on droplets deposition and coverage rate. Prediction models for deposition amount and coverage rate were constructed based on meteorological factors. The results showed that the favorable order of different temperatures, relative humidity, and wind speed levels on droplets deposition was A1≥A2>A3, B3>B2>B1, C1≥C2>C3, respectively. The influence of different meteorological levels on coverage rate and deposition was basically consistent, with relative humidity having a significant impact on droplets coverage rate and deposition, and the interaction between temperature and wind speed also imposed a significant impact on coverage rate. The accuracies of the upper-layer droplets deposition amount and coverage rate predicted by the models constructed based on meteorological factors were 88.15%, 82.82%, with a root mean square error of 0.030 μL/cm2 and 1.33%, respectively. These models demonstrate high reliability and can be applied to meteorological forecasting services for plant protection using UAV. These research findings provide valuable guidance for the timely fungicide spraying operations by UAV for plant protection, enhancing prevention and control effects and reducing fungicide pollution in the agricultural ecological environment.
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