Ontology Based Monitoring Of Seafood Quality And Modeling Of Acceptance Criteria Of Seafood Using Semantic Web Rule Language

Abstract

The export of seafood is extremely important in many countries' economic situations. Most of the developed fish-importing countries have implemented stringent quality and sanitary standards for fishery goods. To preserve consumer safety and health, strong food control procedures are required. But most of the seafood enterprises use manual quality assessment techniques to evaluate and maintain the safety and quality of their products. As a result, we propose a computer-based system that would store the quality assessment guidelines and test values in ontology and then employ acceptance criteria for tests encoded in ontology language to meet food safety requirements. Semantic Web Rule Language (SWRL) is used to model the acceptance criteria of seafood quality tests. The ontology is implemented using Protégé 5.5.0. The Pellet Reasoner is used to infer new information from the ontology. The paper concludes by demonstrating the classification of different instances (samples) of Crustaceans into Accepted/Not_Accepted classes automatically by the reasoner.