Study On The Simulated Model Of Peanut Leaf Spots And Expert System Of Peanut Diseases And Pests For Forecasting

By using Agronomic measures to change the source-sink, the relationship to the source-sink index and the dynamic development of peanut leaf spots is studied. The model with variables of source-sink index and physiology period is developed. In addition, summing up the results of previous research and literature, the method for diagnosis, prediction is developed combining the Visual Basic6.0 programming technology, Acesss2000 database technology with expert systems technology organically, the expert system for diagnosis, forecasting and planning programs to protect is developed.1,The dynamic simulation model of peanut leaf spotsIn full flowering stage, Using a new variety named shanhua 7, the treatment with different concentration of paclobutrazol, can inhibit the height of plant to change the source-sink index. Meanwhile, observing plant growth and leaf spots. Analysis showed that the source-sink index of peanut is closely related to peanut leaf spot. Source-sink index is better to indicate the rule, It is studied that the higher the source-sink index is, the lower the disease index is.In relation to analysis, leaf spot disease index developments with model of Y=Y0exp(Rd*td), which were used to establish its different treatment of the disease index of the dynamic, model,, access to disease index relative growth rate, 0.022974, 0.024686, 0.026292, 0.026973. In every growth of four treatment, the source-sink index as variable is to set up six periods disease index relative growth rate and source-sink index fitting equation Rd=PA+PB*Xi. By curve fitting, different physiology process PA=f(d)=0.03597+0.00019*d+-3.23815E-06*d^2 and PB = f(d)=-0.02445 *Exp(0.02089*d)and the period since the introduction of reproductive variables. Establish the conditions for the relative growth rate Rd=f(Xi,d) (d :reproductive period, Xi: source for the indicator), a simulation model. According to L=L0exp(R*t) Establishment of leaf spot of forecasting model L=f(d,Xi,t).After testing different models of forecast and observed values RMSE is 0.80% to 1.37%, reaching significant level..As the model used in the classic analysis of the growth principle, as long as the understanding of a particular period of the initial conditions index, According to the period can be the source of the indicators, forecasts every day (t) of the leaf spot disease index.2,Expert system of peanut diseases and pests for forecasting, diagnosis and protectingBy using theory of systems engineering, methods of knowledge engineering, summing up the existing research results of peanut diseases and pests, documentation, expert experience and expert problem-solving ideas roundly; colligating crop protect, pesticide protection, nutrition sort and other fields of knowledge; combining the Visual Basic6.0 programming technology, Acesss2000 database technology with expert systems technology organically, an expert system for diagnosis of diseases and pests in peanut is developed based on peanut disease model. The expert systems for diagnosis of diseases and pests can realize functions such as simulating and predicting peanut's diseases and pests, diagnosing peanuts diseases and pests, referring information, teaching knowledge about pesticide, etc. depends on different peanut-diseases areas, different natural climate, and different production conditions. Also the system can changes, adds or deletes records in databases and knowledge bases through manage and maintain system of knowledge bases. The system is visual, flexible and convenient because of using Windows interface, menu-driven and order driven buttons.It has taken the fashion of more routes and entrances on the choice of the diseases and insect diagnostic pattern. According to the searches table of the plant diseases and insect peas, the two-fork table diagnostic pattern put the messages into the datasheet, simulating the course of human search the two-fork table, coming true the flow of the two-fork searches by programme. With much agility and dependability more routes diagnostic pattern may avoid the misplay because of the unproper choice of the two-fork routes, by the course of search from anyone character choice. According to user's answers (choices) man-machine conversation pattern reduce the range of searches one by one question and educe the diagnostic result, enhance the diagnostic practicability and intelligence.Combining multimedia technology and database technology, the consultation and recognition system of the colored picture of plant diseases and insect pests has been structured and collected nearly 50 sheets of the colored picture of plant diseases and insect pests of plant, management and inquiry of database of mode has carried on according to different categories, this kind of search mode that combines picture and text has the characteristic with simple and direct image and received by user at the basic level favourably deeply, has supplemented the defect that the characters describe. Meanwhile, after receiving the result from the long-distance diagnosing, the colored picture of plant diseases and insect pests access relevantly through data base administration, users can tell whether the result is correct contrast to diagnosing.