Organ Modeling Of Corn Growth And Computer Simulation Study

This research take maize as object, in the current study, based on productivity for maize production in the light, water requirements, nutrient supply, cultivation and management, planting density field management process, Decompose single maize plant according to organs, use 3 times of B-spline, Bezier curve, surface algorithms to construct the growing calculating models of maize organs. Fuzzy recognition, evolutionary algorithm is applied to the optimization model. It adopts the object-oriented methods to instantiate and combines various organs'models. Meanwhile pay attentions to model fitting and balanced calculation, realize the maize single shape's simulation based on java3D. And also carry out the maize community's simulation through recycling of examples, individual's rotation and translation. It designs simulation software based on B/S structure.Maize production systems is a complex and unique multi-factor dynamic system, by weather, soil, varieties, cultivation techniques, pests and other various factors, revealed very significant regional and temporal variability, making it difficult for corn production management expert taken into account to consider interaction of many factors, predict the growth trend, quantitative cultivation technical measures. Based on crop physiology, ecology theories, used the system analysis theories and the mathematical modeling technology, it analyzes the light productivity, the temperature moisture management and the nutrient supply, cultivation management level etc. It establishes a maize production target model. According to the field potential moisture evaporation, the effective rainfall, it establishes a maize moisture requirement dynamic model. It studies the knowledge representation system of maize cultivation management, constructs maize production target, moisture requirement, application etc pivotal technology. It digitalizes the information stream of maize growth. Designed simulation software based on B/S structure, take Mathematical model as the calculation basis, through real-time data analysis and simulation, implementation and management control of maize production forecast for corn production methods and means to implement dynamic decision-making, it makes moisture requirement and production information from qualitative analysis to quantitative analysis, from concept model to digital model, from expert experiment to optimization decision-making. Introducing sub-species competition model, fuzzy recognition, evolutionary algorithm is applied to the optimization model. It improves the accuracy of the model and descript maize growth and the management of the actual situation truly.