The research paper proposes a knowledge base framework for assuring the export quality of Indian Seafood. Fisheries sector plays an important role in India’s economic development by contributing 2% to the national GDP [Gross Domestic Production]. The good taste, high nutritional quality, medicinal property, and easy digestibility of fish make it a favorable food of almost all living organisms in the world. Processed fishery products are the country’s largest single foreign exchange earning item today because Indian Seafood is very popular in International Markets. Seafood exports from India during the year 2010 - 2011 reached an all-time high of US $ 2.857 billion compared to US $ 2.1 billion of the previous fiscal year - a growth of almost 35%. Competition in the International market is tough and quality standards insisted by the import countries, have become very stringent. Unfortunately, sometimes some consignments are rejected by the import countries, because of the poor quality of the product. This is very badly affecting this industry and as a result the name of the country in foreign trade is ruined.? Various quality assurance programmes like HACCP [Hazard Analysis Critical Control Point], TQM [Total Quality Management] etc. are aimed to ensure the quality of seafood. But still computer based intelligent software’s do not exist to ensure the quality of the product. This inter-disciplinary research proposes an intelligent system model based on knowledge-base to assure the quality of seafood in different levels of processing. Knowledge base is a special kind of database using knowledge management. Ontologies are used to build knowledge bases. Ontology can be defined as an explicit and specific description of domain knowledge. It describes the logical structure of a domain, its concepts and the relations between them. This kind of system is different from a database oriented system, which cannot predict the entire quality in an intelligent way. Ontologies are the back bone of our system and thus the quality is ensured. Our system can alert the technologist’s if there are any errors in the test results based on the past test results and can also make predictions about the quality of similar types of seafood purchased from a specific landing center.
展开▼
