Title
Disease diagnosis on short-cycle and perennial crops: An approach guided by ontologies.
Abstract
It is extremely important that farmers regularly monitor their crop looking for symptoms that may reveal the presence of diseases. However, sometimes farmers have no access to information that helps them to respond to questions such as: what is wrong with their crop? and what can they do to deal with the problem? This situation could cause them to lose their crops, which in turn represents economic losses. Nowadays, there are solutions focused on the automatic diagnosis of diseases, including human diseases and diseases of specific crops such as maize. However, there is a lack of solutions focused on the diagnosis of diseases of short-cycle and perennial crops. In this sense, we propose an ontology-based solution for helping farmers to diagnose disease of such kind of crops from a set of symptoms perceived by farmers. For this purpose, our solution implements a rule-based engine that can diagnose a disease from the symptoms provided. The ontology and rule-based engine were designed in conjunction with a group of experts in plant pathology. Our proposal was evaluated in conjunction with farmers from the Costa Region of Ecuador achieving encouraging results.
Year
DOI
Venue
2017
10.1007/978-3-319-62410-5_24
DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE
Keywords
Field
DocType
ontology,plant disease diagnosis,crop
Ontology (information science),Ontology,Disease,Crop,Computer science,Knowledge management,Access to information,Distributed computing
Conference
Volume
ISSN
Citations 
620
2194-5357
0
PageRank 
References 
Authors
0.34
9
5