IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i5p4396-d1084717.html
   My bibliography  Save this article

Monitoring Root and Shoot Characteristics for the Sustainable Growth of Barley Using an IoT-Enabled Hydroponic System and AquaCrop Simulator

Author

Listed:
  • Monica Dutta

    (Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, India
    These authors contributed equally to this work.)

  • Deepali Gupta

    (Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, India)

  • Yasir Javed

    (College of Computer and Information Sciences, Prince Sultan University, Riyadh 12435, Saudi Arabia)

  • Khalid Mohiuddin

    (Department of Management Information System, College of Business, King Khalid University, Abha 62529, Saudi Arabia)

  • Sapna Juneja

    (Department of Computer and Information Sciences, International Islamic University, Kuala Lumpur 53100, Malaysia)

  • Zafar Iqbal Khan

    (College of Computer and Information Sciences, Prince Sultan University, Riyadh 12435, Saudi Arabia)

  • Ali Nauman

    (Department of Information and Communication Engineering, Yeungnam University, Gyeongsan-si 712-010, Republic of Korea
    These authors contributed equally to this work.)

Abstract

Vertical farming methods are gaining importance in the current era of urbanization and industrialization 5.0. These methods of farming enhance sustainability by consuming less space and reducing carbon emissions and greenhouse gas emissions. The Green Internet of Things (G-IoT) offers greater environmental sustainability by switching to a dormant mode while not in use, thereby consuming less energy. Each farming method has a different effect on the shoot and root growth of the plants. Thus, dedicated farming methods must be identified for each crop according to the type of crop under consideration. This leads to a need to compare and analyze the root as well as shoot growth trends of crops in different cultivation mediums, using different cultivation methods, thereby identifying the most suitable method for the cultivation of the crop. A comparative analysis of barley shoot and root growth in green IoT-embedded hydroponics and substrate cultivation methods has shown that hydroponics exhibits two times more shoot growth than substrate cultivation. Furthermore, the results were verified against the results obtained from the simulator, which confirmed that the hydroponic method of cultivation produced a year-round qualitative product with 17.112 tons of biomass and 8.556 tons of dry yield.

Suggested Citation

  • Monica Dutta & Deepali Gupta & Yasir Javed & Khalid Mohiuddin & Sapna Juneja & Zafar Iqbal Khan & Ali Nauman, 2023. "Monitoring Root and Shoot Characteristics for the Sustainable Growth of Barley Using an IoT-Enabled Hydroponic System and AquaCrop Simulator," Sustainability, MDPI, vol. 15(5), pages 1-17, March.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:4396-:d:1084717
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/5/4396/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/5/4396/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sundaram Manikandan & Ganesan Kaliyaperumal & Saqib Hakak & Thippa Reddy Gadekallu, 2022. "Curve-Aware Model Predictive Control (C-MPC) Trajectory Tracking for Automated Guided Vehicle (AGV) over On-Road, In-Door, and Agricultural-Land," Sustainability, MDPI, vol. 14(19), pages 1-24, September.
    2. Kanwalpreet Kour & Deepali Gupta & Kamali Gupta & Sapna Juneja & Manjit Kaur & Amal H. Alharbi & Heung-No Lee, 2022. "Controlling Agronomic Variables of Saffron Crop Using IoT for Sustainable Agriculture," Sustainability, MDPI, vol. 14(9), pages 1-16, May.
    3. Lenka Wimmerova & Zdenek Keken & Olga Solcova & Lubomir Bartos & Marketa Spacilova, 2022. "A Comparative LCA of Aeroponic, Hydroponic, and Soil Cultivations of Bioactive Substance Producing Plants," Sustainability, MDPI, vol. 14(4), pages 1-14, February.
    4. Sharnil Pandya & Thippa Reddy Gadekallu & Praveen Kumar Reddy Maddikunta & Rohit Sharma, 2022. "A Study of the Impacts of Air Pollution on the Agricultural Community and Yield Crops (Indian Context)," Sustainability, MDPI, vol. 14(20), pages 1-17, October.
    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. Mudita Uppal & Deepali Gupta & Sapna Juneja & Adel Sulaiman & Khairan Rajab & Adel Rajab & M. A. Elmagzoub & Asadullah Shaikh, 2022. "Cloud-Based Fault Prediction for Real-Time Monitoring of Sensor Data in Hospital Environment Using Machine Learning," Sustainability, MDPI, vol. 14(18), pages 1-19, September.
    2. Szymon Hoffman & Mariusz Filak & Rafał Jasiński, 2022. "Air Quality Modeling with the Use of Regression Neural Networks," IJERPH, MDPI, vol. 19(24), pages 1-33, December.
    3. Y. Supriya & Thippa Reddy Gadekallu, 2023. "Particle Swarm-Based Federated Learning Approach for Early Detection of Forest Fires," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    4. Kanwalpreet Kour & Deepali Gupta & Junaid Rashid & Kamali Gupta & Jungeun Kim & Keejun Han & Khalid Mohiuddin, 2023. "Smart Framework for Quality Check and Determination of Adulterants in Saffron Using Sensors and AquaCrop," Agriculture, MDPI, vol. 13(4), pages 1-21, March.
    5. Haipeng Chen & Jie Zhou & Jia Liang & Dungang Zang & Martinson Ankrah Twumasi & Qianling Shen, 2023. "Study on the Impact of Air Pollution on Agricultural Export Trade," Sustainability, MDPI, vol. 15(3), pages 1-18, January.

    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:jsusta:v:15:y:2023:i:5:p:4396-:d:1084717. 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.