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Comparison of Three Computational Approaches for Tree Crop Irrigation Decision Support


  • Panagiotis Christias

    (Faculty of Automatic Control and Computers, University Politehnica of Bucharest, 060042 Bucharest, Romania)

  • Ioannis N. Daliakopoulos

    (Department of Agriculture, Hellenic Mediterranean University, 71410 Heraklion, Greece
    LANDCO S.A., 15122 Maroussi, Greece)

  • Thrassyvoulos Manios

    (Department of Agriculture, Hellenic Mediterranean University, 71410 Heraklion, Greece)

  • Mariana Mocanu

    (Faculty of Automatic Control and Computers, University Politehnica of Bucharest, 060042 Bucharest, Romania)


This paper explores methodologies for developing intelligent automated decision systems for complex processes that contain uncertainties, thus requiring computational intelligence. Irrigation decision support systems (IDSS) promise to increase water efficiency while sustaining crop yields. Here, we explored methodologies for developing intelligent IDSS that exploit statistical, measured, and simulated data. A simple and a fuzzy multicriteria approach as well as a Decision Tree based system were analyzed. The methodologies were applied in a sample of olive tree farms of Heraklion in the island of Crete, Greece, where water resources are scarce and crop management is generally empirical. The objective is to support decision for optimal financial profit through high yield while conserving water resources through optimal irrigation schemes under various (or uncertain) intrinsic and extrinsic conditions. Crop irrigation requirements are modelled using the FAO-56 equation. The results demonstrate that the decision support based on probabilistic and fuzzy approaches point to strategies with low amounts and careful distributed water irrigation strategies. The decision tree shows that decision can be optimized by examining coexisting factors. We conclude that irrigation-based decisions can be highly assisted by methods such as decision trees given the right choice of attributes while keeping focus on the financial balance between cost and revenue.

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  • Panagiotis Christias & Ioannis N. Daliakopoulos & Thrassyvoulos Manios & Mariana Mocanu, 2020. "Comparison of Three Computational Approaches for Tree Crop Irrigation Decision Support," Mathematics, MDPI, vol. 8(5), pages 1-26, May.
  • Handle: RePEc:gam:jmathe:v:8:y:2020:i:5:p:717-:d:353649

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