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CropPestO: An Ontology Model for Identifying and Managing Plant Pests and Diseases

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Book cover Technologies and Innovation (CITI 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1309))

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Abstract

Organic agriculture practices have the potential to improve soil fertility and biodiversity while ensuring a more sustainable development. However, given that no chemicals can be used in crop cultivation, fighting against harmful plant pests and diseases becomes an even greater challenge. According to the organic agriculture principles, prevention and avoidance constitute the first line of defense against pests and diseases. There are many guides, manuals and codes of practice available relating to all aspects of organic agriculture scattered throughout the Web. The challenge is providing farmers with the information that they need to confront potential risks, improve yields and reduce insect damage. Semantic technologies can be useful assisting in the process of data gathering, integration and exploitation to provide insightful recommendations. Ontologies constitute the necessary bedrock for Semantic Web-based applications to work properly. In this work, we describe the process to build an ontology to model the plant pests and diseases application domain. This ontology is expected to allow the development of a knowledge base to enable a decision support system for farmers interested in applying organic agriculture practices.

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Acknowledgements

This work has been partially supported by the Seneca Foundation-the Regional Agency for Science and Technology of Murcia (Spain)-through project 20963/PI/18, the Spanish National Research Agency (AEI) and the European Regional Development Fund (FEDER/ERDF) through projects KBS4FIA (TIN2016-76323-R) and LaTe4PSP (PID2019-107652RB-I00), Research Talent Attraction Program by the Comunidad de Madrid with grants references 2017-T2/TIC-5664, and Young Researchers R+D Project. Ref. M2173 – SGTRS (co-funded by Rey Juan Carlos University).

Author information

Authors and Affiliations

  1. Department of Computer Sciences, Universidad Rey Juan Carlos, Madrid, Spain

    Miguel Ángel Rodríguez-García

  2. Dept. Informática y Sistemas, Universidad de Murcia, 30071, Murcia, Spain

    Francisco García-Sánchez

Authors
  1. Miguel Ángel Rodríguez-García
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  2. Francisco García-Sánchez
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Corresponding author

Correspondence to Francisco García-Sánchez .

Editor information

Editors and Affiliations

  1. Universidad de Murcia, Espinardo, Murcia, Spain

    Rafael Valencia-García

  2. Universidad de Castilla la Mancha, Toledo, Toledo, Spain

    Gema Alcaraz-Marmol

  3. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Javier Del Cioppo-Morstadt

  4. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Néstor Vera-Lucio

  5. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Martha Bucaram-Leverone

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Rodríguez-García, M.Á., García-Sánchez, F. (2020). CropPestO: An Ontology Model for Identifying and Managing Plant Pests and Diseases. In: Valencia-García, R., Alcaraz-Marmol, G., Del Cioppo-Morstadt, J., Vera-Lucio, N., Bucaram-Leverone, M. (eds) Technologies and Innovation. CITI 2020. Communications in Computer and Information Science, vol 1309. Springer, Cham. https://doi.org/10.1007/978-3-030-62015-8_2

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  • DOI: https://doi.org/10.1007/978-3-030-62015-8_2

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