Research And Implementation Of Greenhouse Tomato Intelligent Management Information System

Tomato is an important fruit and vegetable crop in Shandong Province.It plays an irreplaceable role in food and medicine,and is in great demand every year.However,the current planting method of tomato is relatively backward,and the whole growing process of tomato is very strict to the growing environment and disease control,so it is easy to cause problems such as insufficient yield and low return rate of farmers.Therefore,in this paper,the Internet of things technology,artificial intelligence,image processing and other new information technologies are applied to the management of information related to greenhouse tomato planting and the identification and control of leaf diseases,the intelligent management information system of greenhouse tomato is studied and implemented,which can assist farmers to do a better job of increasing yield and good harvest and preventing and controlling diseases,and timely monitor the information of tomato growth environment changes,diseases and so on,improve the efficiency of tomato planting.The main research contents of this thesis include:1.Image recognition of tomato leaf diseases.First,the image of tomato leaf disease was collected in the experimental base,and the image was labeled manually.Then,the data set of tomato leaf disease was constructed by using Python language image processing method to enhance the image such as turning,denoising,cutting,etc.Finally,the Dense Convolutional neural Network(DenseNet)algorithm is used to train the image recognition model of tomato leaf disease,and the image recognition of tomato leaf disease is realized on Android mobile device.2.Construction of Knowledge Atlas of Tomato Pest.By means of Literature Review,Field Survey and Web crawler,the information of common pests of tomato,such as pest name,disease position and control method,was obtained,it visually shows the relationship between the information.3.Collection and monitoring of microenvironment data of tomato growth in greenhouse.The data of micro-environment(air temperature,air humidity,soil temperature,soil humidity and light intensity)in tomato greenhouse were collected,transmitted and stored by Internet of things system based on the environment of experimental base,the data set of microenvironment for tomato growth in greenhouse was constructed and the real-time monitoring of micro-environment was realized.4.Research and implementation of greenhouse tomato intelligent management information system.Through on-the-spot investigation and communication with experts and farmers,the intelligent management information system of greenhouse tomato was studied and realized.The system mainly includes: planting information,disease identification,greenhouse micro-environment monitoring,equipment monitoring,knowledge mapping and system background management modules.The system can assist the scientific researchers and farmers to grasp the information about the growth of tomatoes,management methods,growth environment and common diseases and insect pests more conveniently and efficiently,and realize scientific and effective management,the disease recognition function can also be used to quickly and accurately identify leaf diseases and provide corresponding disease control methods.