Research On Pear Nutrition Diagnosis And Treatment System Based On Android System

It is recorded that pear trees have been planted for more than 3000 years in China.The planting area of pear trees ranks the third in the planting area of fruit trees in China,and the planting area is very extensive.In recent years,although the quality of pear industry is constantly improving in the process of development,at the same time,there are a variety of problems,nutritional deficiency is one of the major problems.It not only greatly affects the quality of pear fruit,but also makes many pear products unable to meet the market standard.According to the law of malnutrition,the causes of its symptoms are usually unsuitable environment,improper fertilization and lack of management experience.According to the relevant researchers,pear lack of certain elements will present unique symptoms,which enables people to roughly diagnose the missing nutrient elements of pear tree according to the different appearances of these symptoms.Then combined with the results of diagnosis,put forward and implement targeted control measures as early as possible,which can reduce the impact of the lack of nutrients on the growth and development of pear trees to the greatest extent,and ultimately ensure the quality and yield of pear fruit.On the basis of artificial intelligence and other computer technologies,according to the appearance of pear deficiency,this study designs a system of pear nutrition diagnosis and correction,which is presented in the form of Android system application software,so that farmers can quickly and accurately diagnose pear deficiency through smart phones,and obtain correction methods provided by experts at the same time,so as to make professional pears Tree planting information has been popularized to a large extent.In this paper,the following research is carried out:1)The establishment of pear nutrition diagnosis and treatment knowledge base.Through consulting the literature of pear deficiency syndrome and consulting the experts of fruit tree science,the knowledge of 13 kinds of pear deficiency syndrome was acquired.Then,the knowledge was divided into two categories: rule and data,and the knowledge was expressed in the computer by using process representation and frame method.Finally,the experts were simulated by using the method of forward reasoning through observation The process of pear shape diagnosis of pear deficiency.The appearance diagnosis process is mainly presented in the client interface in the form of question and answer.The user can match the answers according to the appearance diagnosis questions provided by the system,infer the results of the absence of elements step by step,and obtain the correction scheme provided by the experts.The successful establishment of knowledge base lays a data foundation for the construction of application software database.2)The establishment of image recognition model of pear deficiency syndrome.Based on the artificial intelligence technology,using the method of machine learning,using the algorithm of support vector machine(SVM)and the feature extraction technology of directional gradient histogram(HOG),the image of healthy pear leaf and deficiency pear leaf are studied and classified,and the pattern of pear nutrition diagnosis image recognition is established.Users can upload the pictures to the background server of the system in the form of on-site photos or local uploads.The system calls up the image recognition model algorithm and gives the diagnosis results.The recognition accuracy of the model is 97.62%.3)The realization of pear nutrition diagnosis and treatment app system.The server side of pear nutrition diagnosis and treatment system is realized by object-oriented Java language programming,and the data resources are mainly accessed by My SQL database.The client uses HTML,CSS,Java Script and other computer languages to design the layout of human-computer interaction interface,which makes the final design of APP interface simple and easy to operate.Pear nutrition diagnosis and treatment of the smartphone app,through the use of Android platform so that farmers can not leave home to get expert system knowledge,has a strong popularity.