Study On Wheat Growth Simulation And Decision Support System

The crop growth simulation model and decision support system (DSS) for cultural management are the core contents of informational and digital agriculture. The crop growth simulation model is mainly characterized with the functions of systemic integration and real-time prediction. The dynamic model on crop quality formation is much needed for quality prediction under various conditions. Also, the growth model-based DSS for crop management is helpful for conducting strategy analysis and practice evaluation through different simulation trials. On the basis of the wheat growth simulation model established by the author's laboratory, using the system analysis method and mathematical modeling technique, this study developed a a physiological process-based simulation model and a climate effectiveness-based prediction model on wheat grain quality through quantifying the dynamics of plant carbon and nitrogen flow and their relationships to environments. By further adopting the object-oriented programming and component technology, a comprehensive and component-based wheat growth simulation system (WGSS) was constructed for simulating wheat growth and development, yield and quality formation. Then, a growth model-based decision support system for wheat management (GMDSSWM) was developed with the function of decision-making support by combining the techniques of simulation experiments and strategy analysis. Finally, the growth model and web-based decision support system for wheat management (GMDSSWM~W) was further established on the platform of C#.net with the web application. This work has provided a basic platform for development of digital wheat farming system, and should be helpful for construction of DSS for other crop management. The main results of the present study are summarized as follows.Based on the literature and support experiments, the quantitative relationships of the variation in major quality traits of wheat (protein and starch contents) with environmental factors were fully analyzed, and a general ecological model was developed for predicting grain protein and starch contents of wheat under various climatic conditions. Major climatic factors were determined by stepwise regression and correlations analysis on relationshipbetween grain starch, protein content and climatic factors. Then, models were established based on these correlations. Wet gluten content, sedimentation value and falling number were simulated on the correlations between wet gluten content, sedimentation value and protein content and on the correlation between falling number and starch content. The model was tested by the different data from experiments of diverse eco-sites, genotypes and sowing dates. The results indicated a good fit between the simulated and observed values of grain starch, protein and wet gluten contents, sedimentation value and falling number. Thus, the present model could be used for predicting major quality traits of different winter wheat genotypes under diverse environments.The process-based simulation model on wheat grain quality proposed that the rate of individual grain N accumulation was determined by the N availability and the interaction of influencing factors as temperature, water and nitrogen conditions within plants over the time course. N availability of individual grain was the sum of N uptake and remobilization from vegetative parts post anthesis. Post anthesis N uptake exhibited an exponential relationship to grain weight and N accumulation at the time of anthesis which was determined by pre-anthesis N uptake. N remobilization from leaves was assumed to decrease with leaf area index (LAI). N remobilization from the stems and chaffs (spikes without grains) was dependent on the curvilinear or linear decrease of the N concentration and the weight of stems and chaffs during grain filling. It is proposed that the rate of individual grain starch accumulation (STR) was determined by the interaction of carbon availability, which exponentially related to STR, and ability of carbon translocation into starch (f(CUi)), w...