Construction of Cucumber Powdery Mildew Early Warning System in Solar Greenhouse Based on Internet of Things  

基于物联网技术的日光温室黄瓜白粉病预警系统研究（英文）

作　　者：吕雄杰[1] 王晓蓉[2] 贾宝红[1] 

机构地区：[1]天津市农业科学院信息研究所,天津300192 [2]天津市农业科学院,天津300192

出　　处：《Agricultural Science & Technology》2016年第12期2873-2876,2884,共5页农业科学与技术（英文版）

基　　金：Supported by the Science and Technology Support Program of Tianjin(15ZCZDNC00120)~~

摘　　要：ln order to explore the design and construction of cucumber powdery mildew warning system in solar greenhouse, internet of things technology was used to conduct the real-time dynamic monitoring of the incidence of cucumber powdery mildew and cucumber growth environment in solar greenhouse. The growth environ-ment included temperature and humidity of air and soil. Logistic regression model was used to construct cucumber powdery mildew warning model. The results showed that humidity characteristic variable （maximum air humidity） and temperature characteristic variable （maximum air temperature） had significant effects on the inci-dence probability of cucumber powdery mildew in solar greenhouse. And it was fea-sible to construct cucumber powdery mildew warning system in solar greenhouse with internet of things.运用物联网技术实现对日光温室黄瓜的生长环境包括空气温湿度与土壤温湿度和白粉病发病状况进行了实时动态监测和采集,并采取Logistic回归模型建立日光温室黄瓜白粉病预警模型,以期探索基于物联网技术的日光温室黄瓜白粉病预警系统的设计与构建。研究结果表明:湿度特征变量(最大空气湿度)、温度特征变量(最大空气温度)对日光温室黄瓜白粉病的发病概率均有显著影响,且基于物联网技术构建日光温室黄瓜白粉病预警系统是可行的。

关 键 词：Solar Greenhouse CUCUMBER Powdery Mildew lnternet of Things Warning Model 

分 类 号：S436.421.12[农业科学—农业昆虫与害虫防治] S126[农业科学—植物保护]