Study On Winter Wheat And Summer Maize Annual Decision Support System

The research and application of crop growth simulation model and decision-making support system would have an important theoretical and practical significance for facilitating development of informational and digital agriculture. After decades of research and development, hundreds of crop growth simulation models have been constructed up to now. But the vast majority of growth simulation models only considered the influence of single crop, with little consideration of the impact of the former crop on growing crop and the growing crop on the succeeding crop, so it is still inadequate for practical application. This study took the planting pattern of winter wheat and summer maize continuous cropping system in northern China as subject, and established the winter wheat and summer maize annual management decision support system which is significant for improving the practicality of model and promoting informational agricultural production.The main results are as follows:1. The cropping pattern of winter wheat and summer maize was selected and corresponding variety selection was decided according to annual active accumulated temperature, number of days available for maize growing and developing and the temperature requirement for maize completing the normal growth and development.2. The relation between air temperature and soil temperature under different soil moisture conditions was studied. Under the same soil depth, the lower the soil moisture, the more the soil temperature was impacted by air temperature. The difference among the soil temperature of different soil moisture in the same depth soil decreased with the increase of soil depth. It was analyzed respectively that the relation between the 0-10cm or 0-15cm soil average temperature and air temperature. The results showed that 0～10 cm soil average temperature had good relation with air temperature. The regression coefficients of 0-10 cm soil average temperature under different soil moisture treatments which were 55%～65%, 65%～75% and 75%～85% and air temperature all reached more than 0.8. It is feasible that air temperature forecasted 0～10cm soil average temperature.3. Optimum seeding time is one of the key conditions for the success of wheat interplanting corn. Before emergence the growth of corn is mainly controlled by soil temperature and soil moisture. The model established for corn sowing to emergence according to soil temperature and soil moisture water is mechanism, which is significant for simulating accurately emergence stage of intercropping corn. Simulating corn sowing to emergence by soil moisture and soil temperature forecasted, the results showed that the model can simulate accurately corn emergence stage. The suitable intercropping sowing date can be achieved by backstepping against model according to wheat harvest time and corn being three leaf age.4. Coupling water balance model with the growth and development simulation model of wheat and maize, the parameters needed for simulating water moisture of succeeding season crop can be called according to the sowing time and harvest time of crop, realizing integral simulation of soil moisture, which lays the foundation for the water integrated management. Finally, the winter wheat and summer maize annual decision support system was constructed based on above research work, further increasing the practicality of the model. The system includes five parts: model base, database, model dictionary, man-machine interface and user interface with the function of data management, adjustment of parameters, variety selection, normal decision-making, current decision-making and so on.Testing the system with the measured growing data of wheat and maize which were in the pattern of sole cropping and intercropping, the results showed that winter wheat and summer maize annual decision support system can simulate perfectly the growth and development of wheat and maize in the different cropping pattern.