IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v14y2024i6p909-d1411305.html
   My bibliography  Save this article

Fuzzy Mathematical Model of Photosynthesis in Jalapeño Pepper

Author

Listed:
  • Luz del Carmen García-Rodríguez

    (Regional Center for Optimization and Device Development, National Technological Institute of Mexico, Celaya 38020, Guanajuato, Mexico)

  • Joel Artemio Morales-Viscaya

    (Department of Electrical and Electronic Engineering, National Technological Institute of Mexico, Celaya 38010, Guanajuato, Mexico)

  • Juan Prado-Olivarez

    (Department of Electrical and Electronic Engineering, National Technological Institute of Mexico, Celaya 38010, Guanajuato, Mexico)

  • Alejandro Israel Barranco-Gutiérrez

    (Department of Electrical and Electronic Engineering, National Technological Institute of Mexico, Celaya 38010, Guanajuato, Mexico)

  • José Alfredo Padilla-Medina

    (Department of Electrical and Electronic Engineering, National Technological Institute of Mexico, Celaya 38010, Guanajuato, Mexico)

  • Alejandro Espinosa-Calderón

    (Regional Center for Optimization and Device Development, National Technological Institute of Mexico, Celaya 38020, Guanajuato, Mexico)

Abstract

Photosynthesis is one of the essential processes for life on the planet. Photosynthesis cannot be measured directly because this complex process involves different variables; therefore, if some variables of interest are integrated and measured, photosynthesis can be inferred through a mathematical model. This article presents a fuzzy mathematical model to estimate photosynthesis. This approach uses as input variables: Soil moisture, ambient temperature, incident radiation, relative humidity, and leaf temperature. The fuzzy system was trained through data obtained from experiments with jalapeño pepper plants and then validated against the LI-COR Li-6800 equipment. The correlation coefficient ( R 2 ) obtained was 0.95, which is a higher value than some published in the literature. Based on the Takagi-Sugeno method, the proposed model was designed and implemented on the MATLAB platform using ANFIS (adaptive neuro-fuzzy inference system) to determine the parameters, thus achieving a high-precision model. In addition, the fuzzy model can predict photosynthesis at different temperature changes, soil moisture levels, and light levels. The results of this study indicate the possibility of modeling photosynthesis using the fuzzy logic technique, whose performance is much higher than other methods published in recent articles.

Suggested Citation

  • Luz del Carmen García-Rodríguez & Joel Artemio Morales-Viscaya & Juan Prado-Olivarez & Alejandro Israel Barranco-Gutiérrez & José Alfredo Padilla-Medina & Alejandro Espinosa-Calderón, 2024. "Fuzzy Mathematical Model of Photosynthesis in Jalapeño Pepper," Agriculture, MDPI, vol. 14(6), pages 1-18, June.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:6:p:909-:d:1411305
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/14/6/909/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/14/6/909/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Brent R. Helliker & Suzanna L. Richter, 2008. "Subtropical to boreal convergence of tree-leaf temperatures," Nature, Nature, vol. 454(7203), pages 511-514, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Jinzhao & Wu, Huawu & Cheng, Yao & Jin, Zhao & Hu, Jing, 2021. "Stable isotope analysis of soil and plant water in a pair of natural grassland and understory of planted forestland on the Chinese Loess Plateau," Agricultural Water Management, Elsevier, vol. 249(C).
    2. Gan Huang & Jingyuan Xu & Christos N. Markides, 2023. "High-efficiency bio-inspired hybrid multi-generation photovoltaic leaf," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    3. Zhiqiang Wang & Heng Huang & Han Wang & Josep Peñuelas & Jordi Sardans & Ülo Niinemets & Karl J. Niklas & Yan Li & Jiangbo Xie & Ian J. Wright, 2022. "Leaf water content contributes to global leaf trait relationships," Nature Communications, Nature, vol. 13(1), pages 1-9, December.

    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:14:y:2024:i:6:p:909-:d:1411305. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.