Decision support for grape crop protection using ontology

Abstract

Weather based decision support for managing pests and diseases of crops requires use of information technology. This paper details a system developed using ontology, semantic web rule language and image processing techniques for management of pests and diseases on wines, particularly in hot tropical region of India. It aims at minimising use of pesticides and fungicides by forecasting pests and diseases occurrence using information about meteorological conditions and it's relation with pest and disease occurrence. It is named as PDMGrapes. For system knowledge base, knowledge available in different formats on grape pests and diseases is converted to ontology. Favourable meteorological conditions for pest and disease occurrences are mentioned by SWRL rules. Grapes disease identification is done using image processing techniques. The system helps grape growers to minimise side effects of pesticides on environment. The developed system is validated and verified for accuracy and performance.