A Decision Support System For Cropping System

The knowledge model for cropping system can provide new quantitative tool and method for digital and intelligent cropping system design. With optimal use of agricultural natural resource as the basis, this research focused on applying the system analysis principle and mathematical modeling technique to study of knowledge expression for cropping system. Based on collecting and analyzing literature, expert knowledge and experience in cropping system, relationships of cropping system indices to ecological conditions, crop types and social economical levels were quantified and integrated, for development of the knowledge model for cropping system design. With the method of component-based programming design, a knowledge model-based decision support system for cropping system n (CSDSS) was established on the platform of Visual C++. In addition, case studies on the system were carried out with different data sets under varied conditions. This work would help make cropping system design more scientific, quantitative and informational.1. Taking optimal resource use as research goal, and based on summarizing cropping system literature, and expert knowledge and experience, and on integrating the knowledge of multi-disciplines as agronomy, crop ecology, crop cultivation, agricultural meteorology, resource and agricultural economics, the dynamic relationships of cropping system indices to ecological conditions, crop types, social and economical levels were quantified with system engineering principle and mathematical modeling technique, and then the knowledge model for cropping system design was developed. The knowledge model overcomes the shortcomings of traditional expert system for cropping system, such as large knowledge base and narrow applicability.2. The knowledge model for cropping system includes submodels of crop combination, dynamic optimization of crop structure and crop distribution design. The submodel of crop combination includes crop ecological adaptability evaluation, year-round cropping number design. The submodel of crop structural dynamic optimization was developed based on the price estimation of agricultural products and53dynamic linear programming model, and the submodel of crop distribution was based on the economical, ecological and social benefits.3. On the basis of the knowledge model for cropping system , a decision support system for cropping system design (CSDSS) was developed on the platform of Visual C++ by fully using the component traits of no correlation between programming languages, reusability, and brief and shortcut system maintenance. In addition, the framework, contents, main functions and development flows of the system were established.4. Testing of the system with the data sets of different eco-sites and crop combinations indicated a good performance of the system in explanation and application.