摘要
为建立番茄病毒病与环境条件的深层次关联分析模型,根据农业物联网传感技术采集设施番茄病毒病发生前15 d的生长环境数据,利用SPSS Statistics Subscription初步建立了设施番茄病毒病预警模型,模型检验效果良好。该预警模型的建立,充分探索了空气温度和湿度与番茄病毒病发生几率之间的关系,并为番茄病虫害预警体系的建立奠定了基础,为实现现代农业精准化管理进行了一次探索。
In order to establish the deep correlation analysis model between tomato virus disease and environmental conditions,the growth environment data was collected by means of agricultural internet of things sensing technology 15 days before the occurrence of tomato virus disease in greenhouse,and the early warning model of greenhouse tomato virus disease was established by SPSS Studies Subscript.The model test results were good.The establishment of this early warning model fully explored the relationship between air temperature,humidity and the occurrence probability of tomato virus disease,laid the foundation for the establishment of tomato pest warning system,and carried out an exploration for the realization of modern agricultural precision management.
作者
杨英茹
黄媛
高欣娜
李瑜玲
段鹏鑫
李海杰
武猛
YANG Ying-ru;HUANG Yuan;GAO Xin-na;LI Yu-ling;DUAN Peng-xin;LI Hai-jie;WU Meng(Shijiazhuang Academy of Agriculture and Forestry Sciences,Shijiazhuang 050041,China;Shijiazhuang Agricultural Informatization Engineering Technology Research Center,Shijiazhuang 050041,China;Hebei University of Business and Economics,Shijiazhuang 050041,China)
出处
《河北农业科学》
2019年第5期91-94,共4页
Journal of Hebei Agricultural Sciences
基金
河北省科技厅重点研发计划项目“基于物联网的设施蔬菜智能测控、病虫害预警与云平台构建研究”(18226920D)
关键词
番茄病毒病
农业物联网
LOGISTIC回归分析
预警模型
Tomato virus disease
Agricultural internet of things
Logistic regression analysis
Early warning model
