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SePeRe: Semantically-Enhanced System for Pest Recognition

  • Jesús Garcerán-Sáez
  • Francisco García-Sánchez
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 901)

Abstract

Organic agriculture shows several benefits, namely, it reduces many of the environmental impacts of conventional agriculture, it can increase productivity in small farmers’ fields, it reduces reliance on costly external inputs, and guarantees price premiums for organic products. However, its feasibility is often questioned due to the constraints in the use of chemical fertilizers and pesticides. For that reason, the general approach in organic agriculture is to deal with the causes of a problem (i.e., management practices aiming at preventing pests and diseases from affecting a crop) rather than treating the symptoms. In this work we propose a fully-fledged, integral, comprehensive technological solution for the early detection of plant diseases and pests, and the suggestion of organic agriculture-compliant treatments. A proof-of-concept prototype has been developed that identifies the presence of harmful conditions in the crop and lists appropriate treatments.

Keywords

Organic agriculture Pest recognition Ontology 

Notes

Acknowledgements

This work has been supported by the Spanish National Research Agency (AEI) and the European Regional Development Fund (FEDER/ERDF) through project KBS4FIA (TIN2016-76323-R).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of Computer Science, Department of Informatics and SystemsUniversity of MurciaMurciaSpain

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