IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v11y2021i7p576-d580642.html
   My bibliography  Save this article

Implementation of a Fuzzy Logic Controller for the Irrigation of Rose Cultivation in Mexico

Author

Listed:
  • Romeo Urbieta Parrazales

    (Instituto Politécnico Nacional-CIC, Av. Juan de Dios Bátiz, Esq. Miguel Othón de Mendizábal, Col. Nueva Industrial Vallejo, Alcaldía Gustavo A. Madero, C.P. 07738 Ciudad de México, Mexico)

  • María T. Zagaceta Álvarez

    (Instituto Politécnico Nacional-ESIME Azcapotzalco, Av. de las Granjas 682, Col. Santa Catarina, Alcaldía de Azcapotzalco, C.P. 02250 Ciudad de México, Mexico)

  • Karen A. Aguilar Cruz

    (Instituto Politécnico Nacional-CIC, Av. Juan de Dios Bátiz, Esq. Miguel Othón de Mendizábal, Col. Nueva Industrial Vallejo, Alcaldía Gustavo A. Madero, C.P. 07738 Ciudad de México, Mexico)

  • Rosaura Palma Orozco

    (Instituto Politécnico Nacional-ESCOM, Av. Juan de Dios Bátiz s/n, Esq. Av. Miguel Othón de Mendizábal. Col. Lindavista, Alcaldía Gustavo A. Madero, C.P. 07738 Ciudad de México, Mexico)

  • José L. Fernández Muñoz

    (Instituto Politécnico Nacional-CICATA Legaria, Calzada Legaria No. 140, Miguel Hidalgo, C.P. 11280 Ciudad de México, Mexico)

Abstract

The design and implementation of a fuzzy logic controller (FLC) are presented, offering a solution to improve the irrigation of rose crops. The objective is to reduce the water consumption and operative costs, taking advantage of intelligent controllers and environmental characteristics in a specific region. Considering that the main controllable variables that affect the growth of plants are relative humidity (RH) and temperature (T), in this study, these variables are used to create a system whose aim is to provide an adequate amount of water for a rose crop in the State of Mexico. The Mamdani method was used for the FLC design and the membership functions, while the area centroid was considered as the defuzzification strategy. After implementing the FLC proposal using a field-programmable gate array (FPGA) in a domestic greenhouse, integrated by an array of [5 × 3] rose plants under natural restrictions, a reduction of 0.2 L per week with respect to the traditional manual irrigation system was found. The proposed design highlights the technological advantages of using a fuzzy logic-controlled irrigation system over traditional methods.

Suggested Citation

  • Romeo Urbieta Parrazales & María T. Zagaceta Álvarez & Karen A. Aguilar Cruz & Rosaura Palma Orozco & José L. Fernández Muñoz, 2021. "Implementation of a Fuzzy Logic Controller for the Irrigation of Rose Cultivation in Mexico," Agriculture, MDPI, vol. 11(7), pages 1-12, June.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:7:p:576-:d:580642
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/11/7/576/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/11/7/576/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Campos, Jean C. & Manrique-Silupú, José & Dorneanu, Bogdan & Ipanaqué, William & Arellano-García, Harvey, 2022. "A smart decision framework for the prediction of thrips incidence in organic banana crops," Ecological Modelling, Elsevier, vol. 473(C).
    2. Iqbal Hasan & Azad Srivastava & Zishan Raza Khan & S. A. M. Rizvi, 2023. "A Novel Fuzzy Inference-Based Decision Support System for Crop Water Optimization," SN Operations Research Forum, Springer, vol. 4(2), pages 1-15, June.
    3. Li Bin & Muhammad Shahzad & Hira Khan & Muhammad Mehran Bashir & Arif Ullah & Muhammad Siddique, 2023. "Sustainable Smart Agriculture Farming for Cotton Crop: A Fuzzy Logic Rule Based Methodology," Sustainability, MDPI, vol. 15(18), pages 1-18, September.
    4. Cristian Silviu Simionescu & Ciprian Petrisor Plenovici & Constanta Laura Augustin & Maria Magdalena Turek Rahoveanu & Adrian Turek Rahoveanu & Gheorghe Adrian Zugravu, 2022. "Fuzzy Quality Certification of Wheat," Agriculture, MDPI, vol. 12(10), pages 1-13, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:11:y:2021:i:7:p:576-:d:580642. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.