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Swine-Vet is a kind of a web-based expert system for swine disease diagnosis and has been promoted in north of China past 3years. The few issues relevant with low diagnosis efficiency and error have arisen during the system test and promotion due to the limitation of previous adopted reasoning techniques and immaturity of diagnosis domain knowledge. This paper proposes a hybrid multimodal reasoning mechanism to resolve the swine intercurrent diseases and improve the system diagnosis efficiency. The framework consists of two modules: one is the forward diagnosing module, information fusion method based on evidence theory is used to solve the barriers of syndrome in swine diagnosis field, and the other is the backward confirming module, set pair analysis (SPA) is adopted to resolve evidence conflict and distinguish uncertain and unknown symptom information during the process of diagnosis. Then, in order to demonstrate this model, a case study is given. Finally, the benefits and challenges of the hybrid multimodal reasoning application in expert system are discussed.

Fish disease is becoming the major factor damaging the sustainable development of aquaculture and the quality security of aquatic product in China. Many researchers provide assistances and advice in fish disease diagnosis and appropriate treatment measures. However, the risk of misdiagnosis, incorrectly treatment or over-treatment also exists due to carrying out after disease outbreaks. So it is necessary to develop an early warning system. Taking into account that fish disease outbreak is mainly caused by suboptimal water quality in north of China, the best way is to develop decision aids tool that can assess and early warning the risk of fish disease based on water quality management. This paper introduces a knowledge-based early warning system for fish disease via water quality management. The architecture, the process for knowledge engineering, main components and their functions, especially a series of water quality management mathematic models are described. At present, the system is in pilot in the city of Tianjin in China. The stage achievements in developing the intellectual system of fish disease early warning are summarized.

Fish disease and health management is becoming a key barrier and major problem that currently limits expanded production and sustainable development of aquaculture and bring out food-safety issues. There has been a marked growth of interest in developing expert system to aid fish disease/health management. The literature shows that a few have been used to any extent due to the lack of deep user requirement analysis and long-term support and maintenance. This paper presents the effort to apply evolutionary prototyping model in developing an intelligent decision support system for fish disease/health management. The paper describes in detail about the four evolution stages as the system development experienced, every stage including the system design and implementation, feedback and requirement from system evaluation, and system redevelopment until a blown system. At last the evolution process is concluded from three directions. The evolutionary prototyping benefits and challenges experienced during the development and promotion are also discussed from the project management perceptive.

When a pig shows disease symptoms, it is important to make an accurate diagnosis to support control strategies. Diagnosing diseases in pigs requires considerable expertise. Only a few experts have the ability to do this, and each expert has his own specific domain. To make it more generally accessible and reduce the waiting time, an expert system named Pig-Vet has been developed by China Agricultural University. Based on investigations, this paper analyzes users' needs and describes the architecture, main components, and their functions. The system has over 300 rules and 202 images and graphics for different types of diseases and symptoms. It can diagnose 54 types of common diseases of pigs. At present the system is in pilot in north of China. The stage achievements in developing the intellectual expert system of pig disease diagnosis are summarized.

Aquaculture plays a very important role in adjusting Agricultural structure and increasing farmers' income. But the technological advances in the production and storage of fishery products have exceeded the development of effective market demand over the past one decade. As a result, participants within the fishery industry have frequently found themselves facing increased variable and declining prices negatively affected the fishery industry. So it is desirable to provide decision aids to price forecasting to avoid such market imbalance. An aquatic products price forecasting support system (APPFSS) was developed by China agricultural University. Based on questionnaire and interviews, we analyze the decision problems and user needs. Then the architecture and development of APPFSS were described. At last we discussed on problems we had encountered during development and promotion.