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农学学报 ›› 2016, Vol. 6 ›› Issue (8): 50-53.doi: 10.11923/j.issn.2095-4050.cjas16040015

所属专题: 园艺 智慧农业

• 农业信息 农业气象 • 上一篇    下一篇

基于物联网技术的日光温室黄瓜白粉病预警系统的研究

王晓蓉,吕雄杰,贾宝红   

  1. 天津市农业科学院,天津市农业科学院信息研究所,天津市农业科学院信息研究所
  • 收稿日期:2016-04-13 修回日期:2016-06-24 接受日期:2016-06-24 出版日期:2016-08-23 发布日期:2016-08-23
  • 通讯作者: 吕雄杰 E-mail:wxr276
  • 基金资助:
    天津市科技支撑计划资助项目“基于物联网技术的设施蔬菜病害预警与诊断研究”(15ZCZDNC00120)。

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

  • Received:2016-04-13 Revised:2016-06-24 Accepted:2016-06-24 Online:2016-08-23 Published:2016-08-23

摘要: 运用物联网技术实现对日光温室黄瓜的生长环境(空气温湿度和土壤温湿度)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: 夏玉米, 夏玉米, 干旱胁迫, 权重, 灰色关联, 综合评价

Abstract: In 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 environment 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 incidence probability of cucumber powdery mildew in solar greenhouse. And it was feasible to construct cucumber powdery mildew warning system in solar greenhouse with internet of things.

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