基于冠层温湿度模型的日光温室黄瓜霜霉病预警方法

利用温室环境参数构建室内微环境模拟模型，并结合温室病害模型进行预警，便于开展病害生态防治，以减少农药使用，从而保护温室生态环境和保证农产品质量安全.本文利用温室内能量守恒原理和水分平衡原理，构建了日光温室冠层叶片温度和空气相对湿度模拟模型.叶片温度模拟模型考虑了温室内植物与墙体、土壤、覆盖物之间的辐射热交换，以及室内净辐射、叶片蒸腾作用引起的能量变化；相对湿度模拟模型综合了温室内叶片蒸腾、土壤蒸发、覆盖物与叶面的水汽凝结引起的水分变化.将温湿度估计模型输出值作为参数，输入黄瓜霜霉病初侵染和潜育期预警模型中，估计黄瓜霜霉病发病日期，并与田间观测的实际发病日期比较.试验选取2014年9月和10月的温湿度监测数据进行模型验证，冠层叶片温度实际值与模拟值的均方根偏差（RMSD)分别为0.016和0.024 ℃，空气相对湿度实际值与模拟值的RMSD分别为0.15%和0.13%.结合温湿度估计模型结果表明，黄瓜病害预警系统预测黄瓜霜霉病发病日期与田间调查发病日期相吻合.本研究可为黄瓜日光温室病害预警模型及系统构建提供微环境数据支持.

An early warning method of cucumber downy mildew in solar greenhouse based on canopy temperature and humidity modeling.

The greenhouse environmental parameters can be used to establish greenhouse mirco-climate model, which can combine with disease model for early warning, with aim of ecological controlling diseases to reduce pesticide usage, and protecting greenhouse ecological environment to ensure the agricultural product quality safety. Greenhouse canopy leaf temperature and air relative humidity models were established using energy balance and moisture balance principle inside the greenhouse. The leaf temperature model considered radiation heat transfer between the greenhouse crops, wall, soil and cover, plus the heat exchange caused by indoor net radiation and crop transpiration. Furthermore, the water dynamic balance in the greenhouse including leaf transpiration, soil evaporation, cover and leaf water vapor condensation, was considered to develop a relative humidity model. The primary infection and latent period warning models for cucumber downy mildew (Pseu doperonospora cubensis) were validated using the results of the leaf temperature and relative humidity model, and then the estimated disease occurrence date of cucumber downy mildew was compared with actual disease occurrence date of field observation. Finally, the results were verified by the measured temperature and humidity data of September and October, 2014. The results showed that the root mean square deviations (RMSDs) of the measured and estimated leaf temperature were 0.016 and 0.024 ℃, and the RMSDs of the measured and estimated air relative humidity were 0.15% and 0.13%, respectively. Combining the result of estimated temperature and humidity models, a cucumber disease early warning system was established to forecast the date of disease occurrence, which met with the real date. Thus, this work could provide the micro environment data for the early warning system of cucumber diseases in solar greenhouses.