Disease diagnosis on short-cycle and perennial crops: An approach guided by ontologies

  • Katty Lagos-OrtizEmail author
  • José Medina-Moreira
  • José Omar Salavarria-Melo
  • Mario An-drés Paredes-Valverde
  • Rafael Valencia-García
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 620)


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.


ontology plant disease diagnosis crop 


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Katty Lagos-Ortiz
    • 1
    Email author
  • José Medina-Moreira
    • 1
  • José Omar Salavarria-Melo
    • 1
  • Mario An-drés Paredes-Valverde
    • 2
  • Rafael Valencia-García
    • 2
  1. 1.Universidad Agraria del EcuadorGuayaquilEcuador
  2. 2.Facultad de InformáticaUniversidad de MurciaMurciaSpain

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