寒地玉米大斑病预警诊断系统研究

发布时间：2018-03-28 04:29

本文选题：寒地玉米　切入点：大斑病　出处：《山东农业大学》2015年硕士论文

【摘要】：我国玉米种植历史从明朝末期开始,由于玉米本身极强的适应性,当前我国玉米种植地域范围极广。在2012年玉米成为我国第一大粮食作物,在我国粮食生产中占有重要地位;而以东北地区为主的寒地玉米种植区是我国最主要玉米产区之一。由于种植面积不断增加、区域化种植、跨区收割和重茬种植严重等因素,导致病虫源基数逐年累积;加上一些不合理的种植、栽培方式和多变的气候条件,玉米病虫害的发生面积逐年扩大,发生程度逐年加重。这种情况在东北寒地玉米种植区表现为:以玉米大斑病为代表的病虫害连年发生。在玉米种植面积逐年增加与病虫害频发重发的背景下,对病虫害的发生发展做出预报预警就显得尤为重要。本文主要通过参考相关文献资料和黑龙江农垦北安管局红星、赵光农场的实地调研结论,了解寒地玉米大斑病的发生条件和发病规律,通过分析不同气象因子与寒地玉米大斑病病情的相关性,确立寒地玉米大斑病的预警因子;从而实现了通过预警模型结合实地调查信息的综合预警机制;同时通过分析玉米病害的病症特点、发病部位和发病时期等信息,确立了寒地玉米病害的诊断机制。在此基础上,通过数据库技术、网络技术、物联网技术等,对寒地玉米大斑病预警诊断系统进行设计;实现了玉米地块实时环境数据的获取与显示,初步实现了寒地玉米大斑病的实时预警和寒地玉米病害的快速诊断。系统主要具有以下几个功能:田间环境数据查询功能,利用部署在田间的气象数据采集设备,通过无线传感器网络监测田间气象信息,使用户可以在系统中查看田间实时环境数据和田间历史环境数据;寒地玉米大斑病实时预警功能,利用气象数据采集设备采集的田间实时环境数据,通过预警模型库中的预警模型进行预警,同时结合用户自主调查的信息,增加预警结果的准确性,初步实现了寒地玉米大斑病的实时预警;寒地玉米病害诊断功能,用户通过匹配玉米病害的病症特点、发病部位、发病时期和标准图像,可以实现寒地玉米病害的快速诊断;寒地玉米病害查询功能,用户可以通过病害名称查询病害的病源信息、发病部位、发病时期等详细信息。系统的设计符合了寒地玉米种植区的基本需求,能够满足用户的业务需求,操作简单、数据直观。最后,系统通过寒地玉米种植区连续两年的病虫害调查记录和气象数据记录进行测试,结果表明,系统对寒地玉米大斑病的实时预警效果良好,对玉米病害可以进行快速诊断,同时实现了通过无线传感网获取玉米地块实时环境参数,对玉米生长环境的有效监控。
[Abstract]:The history of maize planting in China began at the end of Ming Dynasty. Because of the strong adaptability of maize itself, the growing area of maize in China is very wide at present. In 2012, maize became the largest food crop in China and played an important role in the grain production of our country. The cold corn planting area in Northeast China is one of the most important maize producing areas in China. Due to the increasing planting area, regional planting, cross-region harvesting and heavy cropping, the base number of diseases and pests is accumulated year by year. With some unreasonable planting, cultivation methods and changeable climate conditions, the occurrence area of maize diseases and insect pests has been expanding year by year. The degree of occurrence is increasing year by year. In the northeast cold region of maize planting area, the disease and insect pests, which are represented by the large spot disease of maize, occur year after year, and under the background of increasing planting area year by year and frequent occurrence of diseases and insect pests, It is particularly important to predict the occurrence and development of diseases and insect pests. This paper mainly refers to the relevant literature and the field investigation conclusions of Hongxing and Zhaoguang Farm of Heilongjiang Agricultural Reclamation Administration Bureau of Bei'an. By analyzing the correlation between different meteorological factors and the disease condition of maize leaf spot in cold region, the early warning factors of maize leaf spot disease in cold region were established. Therefore, a comprehensive early-warning mechanism combining field investigation information with early-warning model is realized. At the same time, the diagnosis mechanism of maize disease in cold region is established by analyzing the disease characteristics, location and period of maize disease. Through database technology, network technology, Internet of things technology and so on, the early warning diagnosis system of maize spot disease in cold region is designed, and the real-time environmental data of maize field are acquired and displayed. The system has the following main functions: the field environment data query function, the meteorological data acquisition equipment deployed in the field. Through wireless sensor network monitoring field meteorological information, users can view field real time environment data and field historical environment data in the system. The field real time environmental data collected by meteorological data acquisition equipment is used to carry out early warning through the early warning model in the early warning model database. At the same time, the accuracy of the early warning result is increased by combining the information of the user's independent investigation. The diagnosis function of maize disease in cold region can be realized by matching the disease characteristics, disease location, onset period and standard image of maize disease in cold region, and the rapid diagnosis of maize disease in cold region can be achieved by matching the disease characteristics, disease location, onset period and standard image. The query function of maize disease in cold region, the user can search the disease source information, disease location, disease period and so on through the disease name. The design of the system accords with the basic demand of maize planting area in cold region. The system can meet the business needs of users, easy to operate, intuitive data. Finally, the system through two consecutive years of cold corn planting area survey records and meteorological data records to test, the results show that, The system has a good effect on real time early warning of maize spot disease in cold region. It can diagnose maize disease quickly. At the same time, it can obtain real time environmental parameters of maize plot through wireless sensor network, and effectively monitor the growth environment of maize.
【学位授予单位】：山东农业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：S435.131.4;S126

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