中文摘要：

为了对防虫网覆盖塑料大棚内空气温度和相对湿度进行预测,该文根据能量平衡和质量平衡原理,建立了以塑料大棚外气象要素（太阳辐射、温度、相对湿度、风速、气压）为驱动变量,以塑料大棚结构（容积、表面积、通风窗面积、棚内地表面积）、覆盖材料（塑料薄膜透光率、防虫网目数）、小白菜（叶宽、叶面积指数）等为参数的塑料大棚内温湿度模拟模型,并根据试验观测资料对模型进行了检验。结果表明：模型能较好地预测长江下游地区防虫网覆盖塑料大棚内温度和相对湿度。模型对该地区夏季晴天、多云天和阴天覆盖防虫网塑料大棚内温度预测值与实测值的决定系数（R2）分别为0.93、0.92和0.87,回归估计标准误差（RMSE）分别为1.3、1.4和0.9℃,相对误差（RE）分别为5.8%、6.5%和4.1%;夏季晴天、多云天和阴天大棚内相对湿度预测值与实测值的R2分别为0.91、0.90和0.89,RMSE分别为4.1%、4.7%和3.2%,RE分别为4.8%、5.6%和3.8%。模型的建立也为防虫网覆盖塑料大棚结构优化和管理提供参考。

英文摘要：

In order to forecast the air temperature and relative humidity inside a plastic tunnel with insect-proof nets,a model for simulating the air temperature and humidity inside a plastic greenhouse tunnel covered with insect-proof nets was developed based on the energy and mass balance analysis.Experiments were carried out in a plastic greenhouse tunnel covered with insect-proof nets located in Shanghai City to collect data to validate the model.The model can predict the air temperature and humidity inside the plastic greenhouse tunnel covered with insect-proof nets with such inputs as the outside hourly weather data（global radiation,temperature,relative humidity,wind speed,air pressure）,information of greenhouse structure（volume,cover surface area,area of vents,floor area）,transmittance of cover material and porosity of the insect-proof net material,and crop information（canopy leaf area index and leaf width）.The results showed that the simulated air temperature and relative humidity inside the plastic greenhouse tunnel agreed well with the measured data.The determination coefficient（R 2）between the simulation and measured air temperature inside the plastic greenhouse tunnel under sunny,cloudy,and overcast conditions was 0.93,0.92,and 0.87,respectively,and the root mean squared error（RMSE）was 1.3,1.4,and 0.9℃,respectively.The R2between the simulation and measured air relative humidity inside the plastic greenhouse tunnel under sunny,cloudy,and overcast conditions was 0.91,0.90,and 0.89,respectively,and the RMSE was 4.1%,4.7%,and 3.2%,SE was 4.8%,5.6%,and 3.8%,respectively.The model can be used for the optimisation of the greenhouse tunnel structure as well as for the improvement of greenhouse tunnel climate management.