Construction And Application Research On Citrus Pest Information Ontology

In China, the prevention and control of citrus pests is a long-term and serious problem. In citrus growing region, pests occur annually frequent, and due to the lack of relevant knowledge and information, citrus growers can not be taken rapid and effective control measures for pest. A lot of negative impact has been brought to the local economy and the environment. In this paper, the ideas and methods of ontology is introduced into the field. We combine together ontology technology and traditional agricultural techniques to provide a knowledge and information-sharing platform for the planters. Through the platform, growers diagnose by morphological, distribution and damage symptoms of citrus pests, and they can access to basic information and control methods of pests. In this way, the efficiency and accuracy of regional pests prevention and mitigation will be improved greatly.In this paper, the organization and representation of pest diagnosis knowledge are based on citrus pest diagnosis ontology. On this basis, combined with ontology reasoning technology, an ontology-based citrus pest diagnostic system is built up. The main results include:1) The citrus pest diagnostic ontology is constructed. The paper discusses in detail about build tools and representation language of ontology. According to the seven-step method, an OWL-based pest diagnostic ontology is built by Protege"4.0.2. At the same time, the integrity of the morphological, distribution and damage symptoms of citrus pests is ensured. The ontology provides the general terminology within the field, which provide a reasonable solution to the problem of semantic heterogeneity, and a clear description of the hierarchical relationship between the knowledge and complex knowledge system.2) Based on citrus pest diagnostic ontology, a knowledge base of ontology is constructed. In this paper, we collect the morphological, distribution and damage symptoms of citrus pests, covering a total of two classes,11orders,52families and187species of insects. The above information is classified and established the citrus pest ontology knowledge base.3) Based on the ICTCLAS segmentation system and Jena inference engine, combined with user input information and diagnostic rules, the citrus pests diagnostic reasoning is initially realized. Results based on semantic ontology reasoning are better than general text retrieval in theory.