IDEAS home Printed from https://ideas.repec.org/a/zib/zbnbda/v5y2023i2p57-63.html
   My bibliography  Save this article

The Potential Future Of Agriculture For Small Farms: Supervised Machine-Learning Smart Irrigation Concept For Vegetables

Author

Listed:
  • Arnesh Telukdarie

    (Johannesburg Business School)

  • Noluthando Gamede

    (Johannesburg Business School)

  • Inderasan Munien

    (Johannesburg Business School)

  • Andre Vermeulen

    (Johannesburg Business School)

  • Uche Onkonkwo

    (Johannesburg Business School)

Abstract

Sustainability is a crucial concept in agriculture and agricultural production. Since there is an intense competitiveness and risk in the sector, technical advancements are essential for improved development and sustainability. Small farms require cost effective solutions to match the standards of bigger producers, which essentially means best yields on crops, both in terms of quantity and quality. It is crucial to consider water crisis, climate change, and quality farm care when designing new solutions for agriculture. This study proposes the automation of farm irrigation systems based on a supervised machine learning model (SVM, Logistic Regression) that is cost-effective and precise response to farming demands. In order to show the practicality of this proposed new technology, an application was developed to represent the model results. The application created was for the user to be able to use the model to predict and control the valves in an irrigation system. This work is a potential solution for small farms in a country like South Africa, where sustainable farming is taking rise.

Suggested Citation

  • Arnesh Telukdarie & Noluthando Gamede & Inderasan Munien & Andre Vermeulen & Uche Onkonkwo, 2023. "The Potential Future Of Agriculture For Small Farms: Supervised Machine-Learning Smart Irrigation Concept For Vegetables," Big Data In Agriculture (BDA), Zibeline International Publishing, vol. 5(2), pages 57-63, July.
    • Handle: RePEc:zib:zbnbda:v:5:y:2023:i:2:p:57-63
    DOI: 10.26480/bda.02.2023.57.63
    as

    Download full text from publisher

    File URL: https://bigdatainagriculture.com/paper/issue22023/2bda2023-57-63.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.26480/bda.02.2023.57.63?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Namara, Regassa E., 2010. "Typology of irrigation systems in Ghana," IWMI Working Papers H043957, International Water Management Institute.
    2. Pereira, L.S. & Paredes, P. & Jovanovic, N., 2020. "Soil water balance models for determining crop water and irrigation requirements and irrigation scheduling focusing on the FAO56 method and the dual Kc approach," Agricultural Water Management, Elsevier, vol. 241(C).
    3. Bwambale, Erion & Abagale, Felix K. & Anornu, Geophrey K., 2022. "Smart irrigation monitoring and control strategies for improving water use efficiency in precision agriculture: A review," Agricultural Water Management, Elsevier, vol. 260(C).
    4. Zema, Demetrio Antonio & Nicotra, Angelo & Mateos, Luciano & Zimbone, Santo Marcello, 2018. "Improvement of the irrigation performance in Water Users Associations integrating data envelopment analysis and multi-regression models," Agricultural Water Management, Elsevier, vol. 205(C), pages 38-49.
    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. França, Ana Carolina Ferreira & Coelho, Rubens Duarte & da Silva Gundim, Alice & de Oliveira Costa, Jéfferson & Quiloango-Chimarro, Carlos Alberto, 2024. "Effects of different irrigation scheduling methods on physiology, yield, and irrigation water productivity of soybean varieties," Agricultural Water Management, Elsevier, vol. 293(C).
    2. Wu, Zhangsheng & Li, Yue & Wang, Rong & Xu, Xu & Ren, Dongyang & Huang, Quanzhong & Xiong, Yunwu & Huang, Guanhua, 2023. "Evaluation of irrigation water saving and salinity control practices of maize and sunflower in the upper Yellow River basin with an agro-hydrological model based method," Agricultural Water Management, Elsevier, vol. 278(C).
    3. Darouich, Hanaa & Karfoul, Razan & Ramos, Tiago B. & Moustafa, Ali & Shaheen, Baraa & Pereira, Luis S., 2021. "Crop water requirements and crop coefficients for jute mallow (Corchorus olitorius L.) using the SIMDualKc model and assessing irrigation strategies for the Syrian Akkar region," Agricultural Water Management, Elsevier, vol. 255(C).
    4. Imran Ali Lakhiar & Haofang Yan & Chuan Zhang & Guoqing Wang & Bin He & Beibei Hao & Yujing Han & Biyu Wang & Rongxuan Bao & Tabinda Naz Syed & Junaid Nawaz Chauhdary & Md. Rakibuzzaman, 2024. "A Review of Precision Irrigation Water-Saving Technology under Changing Climate for Enhancing Water Use Efficiency, Crop Yield, and Environmental Footprints," Agriculture, MDPI, vol. 14(7), pages 1-40, July.
    5. Charles Yaw Okyere & Ama Asantewah Ahene-Codjoe, 2022. "Irrigated Agriculture and Welfare: Panel Data Evidence from Southern Ghana," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 34(2), pages 583-610, April.
    6. Wang, Wendi & Straffelini, Eugenio & Tarolli, Paolo, 2023. "Steep-slope viticulture: The effectiveness of micro-water storage in improving the resilience to weather extremes," Agricultural Water Management, Elsevier, vol. 286(C).
    7. Ruiqi Zhang & Chunguang Hu & Yucheng Sun, 2024. "Decoding the Characteristics of Ecosystem Services and the Scale Effect in the Middle Reaches of the Yangtze River Urban Agglomeration: Insights for Planning and Management," Sustainability, MDPI, vol. 16(18), pages 1-26, September.
    8. Barry, Boubacar & Kortatsi, Benony & Forkuor, Gerald & Gumma, Murali Krishna & Namara, Regassa E. & Rebelo, Lisa-Maria & van den Berg, Joost & Laube, Wolfram, 2010. "Shallow groundwater in the Atankwidi Catchment of the White Volta Basin: current status and future sustainability," IWMI Research Reports 112969, International Water Management Institute.
    9. Xing Liu & Zhaoyang Cai & Yan Xu & Huihui Zheng & Kaige Wang & Fengrong Zhang, 2022. "Suitability Evaluation of Cultivated Land Reserved Resources in Arid Areas Based on Regional Water Balance," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1463-1479, March.
    10. Mondol, Md Anarul Haque & Zhu, Xuan & Dunkerley, David & Henley, Benjamin J., 2022. "Changing occurrence of crop water surplus or deficit and the impact of irrigation: An analysis highlighting consequences for rice production in Bangladesh," Agricultural Water Management, Elsevier, vol. 269(C).
    11. Liu, Meihan & Paredes, Paula & Shi, Haibin & Ramos, Tiago B. & Dou, Xu & Dai, Liping & Pereira, Luis S., 2022. "Impacts of a shallow saline water table on maize evapotranspiration and groundwater contribution using static water table lysimeters and the dual Kc water balance model SIMDualKc," Agricultural Water Management, Elsevier, vol. 273(C).
    12. Shao, Guomin & Han, Wenting & Zhang, Huihui & Liu, Shouyang & Wang, Yi & Zhang, Liyuan & Cui, Xin, 2021. "Mapping maize crop coefficient Kc using random forest algorithm based on leaf area index and UAV-based multispectral vegetation indices," Agricultural Water Management, Elsevier, vol. 252(C).
    13. Guilherme Jesus & Martim L. Aguiar & Pedro D. Gaspar, 2022. "Computational Tool to Support the Decision in the Selection of Alternative and/or Sustainable Refrigerants," Energies, MDPI, vol. 15(22), pages 1-20, November.
    14. Salgado, Ramiro & Mateos, Luciano, 2021. "Evaluation of different methods of estimating ET for the performance assessment of irrigation schemes," Agricultural Water Management, Elsevier, vol. 243(C).
    15. Pereira, L.S. & Paredes, P. & Hunsaker, D.J. & López-Urrea, R. & Mohammadi Shad, Z., 2021. "Standard single and basal crop coefficients for field crops. Updates and advances to the FAO56 crop water requirements method," Agricultural Water Management, Elsevier, vol. 243(C).
    16. Takeshima, Hiroyuki & Jimah, Kipo & Kolavalli, Shashidhara & Diao, Xinshen & Funk, Rebecca Lee, 2013. "Dynamics of transformation: Insights from an exploratory review of rice farming in the Kpong irrigation project:," IFPRI discussion papers 1272, International Food Policy Research Institute (IFPRI).
    17. Liu, Meihan & Shi, Haibin & Paredes, Paula & Ramos, Tiago B. & Dai, Liping & Feng, Zhuangzhuang & Pereira, Luis S., 2022. "Estimating and partitioning maize evapotranspiration as affected by salinity using weighing lysimeters and the SIMDualKc model," Agricultural Water Management, Elsevier, vol. 261(C).
    18. Grace L. Baldwin & Robert M. Stwalley, 2022. "Opportunities for the Scale-Up of Irrigation Systems in Ghana, West Africa," Sustainability, MDPI, vol. 14(14), pages 1-18, July.
    19. Ramos, Tiago B. & Oliveira, Ana R. & Darouich, Hanaa & Gonçalves, Maria C. & Martínez-Moreno, Francisco J. & Rodríguez, Mario Ramos & Vanderlinden, Karl & Farzamian, Mohammad, 2023. "Field-scale assessment of soil water dynamics using distributed modeling and electromagnetic conductivity imaging," Agricultural Water Management, Elsevier, vol. 288(C).
    20. Qiu, Rangjian & Li, Longan & Liu, Chunwei & Wang, Zhenchang & Zhang, Baozhong & Liu, Zhandong, 2022. "Evapotranspiration estimation using a modified crop coefficient model in a rotated rice-winter wheat system," Agricultural Water Management, Elsevier, vol. 264(C).

    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:zib:zbnbda:v:5:y:2023:i:2:p:57-63. 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: Zibeline International Publishing (email available below). General contact details of provider: https://bigdatainagriculture.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.