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Comparison of Three Computational Approaches for Tree Crop Irrigation Decision Support

Author

Listed:
  • 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)

Abstract

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.

Suggested Citation

  • 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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    References listed on IDEAS

    as
    1. Gravel, Nicolas & Marchant, Thierry & Sen, Arunava, 2018. "Conditional expected utility criteria for decision making under ignorance or objective ambiguity," Journal of Mathematical Economics, Elsevier, vol. 78(C), pages 79-95.
    2. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    3. Paredes, P. & Wei, Z. & Liu, Y. & Xu, D. & Xin, Y. & Zhang, B. & Pereira, L.S., 2015. "Performance assessment of the FAO AquaCrop model for soil water, soil evaporation, biomass and yield of soybeans in North China Plain," Agricultural Water Management, Elsevier, vol. 152(C), pages 57-71.
    4. Ali, M.H. & Talukder, M.S.U., 2008. "Increasing water productivity in crop production--A synthesis," Agricultural Water Management, Elsevier, vol. 95(11), pages 1201-1213, November.
    5. Egea, Gregorio & Diaz-Espejo, Antonio & Fernández, José E., 2016. "Soil moisture dynamics in a hedgerow olive orchard under well-watered and deficit irrigation regimes: Assessment, prediction and scenario analysis," Agricultural Water Management, Elsevier, vol. 164(P2), pages 197-211.
    6. Er-Raki, S. & Chehbouni, A. & Hoedjes, J. & Ezzahar, J. & Duchemin, B. & Jacob, F., 2008. "Improvement of FAO-56 method for olive orchards through sequential assimilation of thermal infrared-based estimates of ET," Agricultural Water Management, Elsevier, vol. 95(3), pages 309-321, March.
    7. Günther Fischer, 2018. "Transforming the global food system," Nature, Nature, vol. 562(7728), pages 501-502, October.
    8. Carmona-Torres, Carmen & Parra-López, Carlos & Hinojosa-Rodríguez, Ascensión & Sayadi, Samir, 2014. "Farm-level multifunctionality associated with farming techniques in olive growing: An integrated modeling approach," Agricultural Systems, Elsevier, vol. 127(C), pages 97-114.
    9. Blaney, Harry F. & Criddle, Wayne D., 1962. "Determining Consumptive Use and Irrigation Water Requirements," Technical Bulletins 171000, United States Department of Agriculture, Economic Research Service.
    10. Lovelli, S. & Perniola, M. & Ferrara, A. & Di Tommaso, T., 2007. "Yield response factor to water (Ky) and water use efficiency of Carthamus tinctorius L. and Solanum melongena L," Agricultural Water Management, Elsevier, vol. 92(1-2), pages 73-80, August.
    11. Allen, Richard G. & Pruitt, William O. & Wright, James L. & Howell, Terry A. & Ventura, Francesca & Snyder, Richard & Itenfisu, Daniel & Steduto, Pasquale & Berengena, Joaquin & Yrisarry, Javier Basel, 2006. "A recommendation on standardized surface resistance for hourly calculation of reference ETo by the FAO56 Penman-Monteith method," Agricultural Water Management, Elsevier, vol. 81(1-2), pages 1-22, March.
    12. Luce, R Duncan & Krantz, David H, 1971. "Conditional Expected Utility," Econometrica, Econometric Society, vol. 39(2), pages 253-271, March.
    13. Kipkorir, E. C. & Raes, D. & Massawe, B., 2002. "Seasonal water production functions and yield response factors for maize and onion in Perkerra, Kenya," Agricultural Water Management, Elsevier, vol. 56(3), pages 229-240, August.
    14. Michael Stuart, 1988. "28. Introduction to Probability and Statistics for Engineers and Scientists," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 151(2), pages 381-382, March.
    15. Istanbulluoglu, Ahmet, 2009. "Effects of irrigation regimes on yield and water productivity of safflower (Carthamus tinctorius L.) under Mediterranean climatic conditions," Agricultural Water Management, Elsevier, vol. 96(12), pages 1792-1798, December.
    16. Vladimir Chernov & Oleksandr Dorokhov & Liudmyla Dorokhova & Vladimir Chubuk, 2015. "Using fuzzy logic for solution of economic tasks - two examples of decision making under uncertainty," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 11(1), pages 85-100.
    17. Moriana, A. & Girón, I.F. & Martín-Palomo, M.J. & Conejero, W. & Ortuño, M.F. & Torrecillas, A. & Moreno, F., 2010. "New approach for olive trees irrigation scheduling using trunk diameter sensors," Agricultural Water Management, Elsevier, vol. 97(11), pages 1822-1828, November.
    18. Faruk Gul & Wolfgang Pesendorfer, 2014. "Expected Uncertain Utility Theory," Econometrica, Econometric Society, vol. 82(1), pages 1-39, January.
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