Title: Expert system for coffee rust detection based on supervised learning and graph pattern matching
Authors: Emmanuel Lasso; Thiago Toshiyuki Thamada; Carlos Alberto Alves Meira; Juan Carlos Corrales
Addresses: Telematics Engineering Group, University of Cauca, Popayán, Colombia ' University of Campinas, Campinas, São Paulo, Brazil ' Embrapa Agricultural Informatics, Campinas, São Paulo, Brazil ' University of Cauca, Popayán, Colombia
Abstract: Diseases in agricultural production systems represent one of the main reasons of losses and poor-quality products. For coffee production, experts in this area suggest that weather conditions and crop physical properties are the main variables that determine the development of coffee rust. This paper proposes an extraction of rules to detect coffee rust from induction of decision trees and expert knowledge. In order to obtain a model with greater expressiveness and interpretability, a graph-based representation is proposed. Finally, the extracted rules are evaluated using an expert system supported on graph pattern matching.
Keywords: graph pattern matching; expert system; decision tree; rules; plant disease; Hemileia vastatrix; agriculture.
International Journal of Metadata, Semantics and Ontologies, 2017 Vol.12 No.1, pp.19 - 27
Received: 17 Sep 2016
Accepted: 14 Feb 2017
Published online: 25 Oct 2017 *