基于物联网的日光温室冠层特征温度时空变化规律分析

Spatio-temporal Variation of Canopy Characteristic Temperature in Solar Greenhouse

针对日光温室冬季反季节生产中冠层温度时空分布不均的问题,以典型西北日光温室为研究对象,建立了40通道PT100温度场监测系统,对冬季番茄冠层全天候动态温度数据进行采集,在此基础上,采用克里金插值算法进行冠层温度场建模,通过差分进化算法获取温度极值点,分析了不同天气条件下冠层特征温度的时空变化规律。结果表明,晴天、多云天、阴(雨)天插值验证的R^(2)均大于0.94,平均均方根误差分别为1.34、0.95、0.40℃,该算法更适用于阴(雨)天及夜间低温冠层温度场的插值;在不同天气条件下,温室冠层温度全天整体上呈现西高东低、内高外低的趋势,阴(雨)天温室内温度整体变化规律趋于一致,晴天、多云天气揭被后,受外界光辐射等因素影响室内温度分布差异性较大,晴天夜间温度的下降程度大于阴(雨)天;冠层极值点分布结果表明,在不同天气条件下,极值特征点在日光温室中分布区域基本相同,冠层最高温点主要位于温室中部[22.0 m,2.5 m]附近,最低温点主要位于温室东部外膜[4.0 m,5.48 m]附近。日光温室冠层极值特征点的获取为温室栽培、温度灾害监测与传感器部署等研究提供了理论基础。

Aiming to explore the pattern of crop canopy temperature change and spatial location distribution characteristics,so as to realize the reasonable deployment of the greenhouse temperature monitoring scheme to prevent the occurrence of local chilling injury of crops in solar greenhouses.A 40-channel high-precision temperature field monitoring system were deployed to collect the tomato canopy temperature in the winter in a northwest solar greenhouse.The Kriging interpolation algorithm was used to interpolate the collected data to obtain a temperature field model.And the temperature extreme value feature points of the temperature field model were obtained based on differential evolution(DE)algorithm.The spatio-temporal variations of canopy characteristic temperature under different weather conditions were analyzed.The results showed that the R^(2) values of interpolation in sunny,cloudy and overcast(rainy)days were more than 0.94,and values of the average root mean square error(RMSE)were 1.34℃,0.95℃and 0.40℃,respectively.The algorithm was more suitable for the interpolation of low temperature canopy temperature field in overcast(rainy)days and night.Under different weather conditions,the greenhouse canopy temperature showed a trend of higher west and lower east,higher inside and lower outside,and the overall change of the temperature in the greenhouse tended to be consistent in the overcast(rainy)days.After the exposure of sunny and cloudy weather,the indoor temperature distribution was quite different due to external light radiation,and the temperature decrease at night in sunny days was greater than that in overcast(rainy)days.The results of further analysis of the distribution of canopy extreme points showed that under different weather conditions,the distribution of extreme characteristic points in the solar greenhouse was basically the same,and the highest temperature points of the canopy mainly appeared near the middle of the greenhouse[22.0 m,2.5 m].The lowest temperature points mainly appeared near the outer film of the eastern part of the greenhouse[4.0 m,5.48 m].The acquisition of canopy extreme characteristic points in solar greenhouse provided a theoretical basis for greenhouse cultivation,temperature disaster monitoring and sensor deployment.