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Comprehensive Evaluation of Soil Moisture Sensing Technology Applications Based on Analytic Hierarchy Process and Delphi

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  • Limin Yu

    (College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
    College of Information Science and Engineering, Shandong Agriculture and Engineering University, Jinan 250100, China)

  • Sha Tao

    (College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

  • Yanzhao Ren

    (National Engineering Laboratory for Agri-Product Quality Traceability, Beijing Technology and Business University, Beijing 100083, China)

  • Wanlin Gao

    (College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

  • Xinliang Liu

    (National Engineering Laboratory for Agri-Product Quality Traceability, Beijing Technology and Business University, Beijing 100083, China)

  • Yongkang Hu

    (College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

  • Redmond R. Shamshiri

    (Leibniz Institute for Agricultural Engineering and Bioeconomy, 14469 Potsdam, Germany)

Abstract

The demand for smart irrigation and water-saving practices in agriculture has triggered the development of different soil moisture sensing techniques that can operate under harsh field conditions. In this study, a soil moisture sensing technology appropriate for the field applications was comprehensively evaluated. From a qualitative and quantitative perspective, the Delphi and analytic hierarchy process methods were used to construct an index system involving technological advantage, economic benefit, risk analysis, policy support, four second-level indicators, and 23 fourth-level indicators. The results showed that economic benefits account for the largest weight. The practical evaluation resulted in 12 farms that showed that the selected soil water sensing methods performed reasonably and exhibited obvious water-saving irrigation benefits, which are usually used for scheduling irrigation. The overall score of M4 in different soil types was 0.2% lower than that of M5. Farms with reasonable economic conditions and a high awareness scored 5.3% higher on technology than those with modest economic conditions, which clearly affects the evaluation scores of the two technologies. The evaluation results help farmers and government decision-making bodies in technology selection, production decision-making, and risk control.

Suggested Citation

  • Limin Yu & Sha Tao & Yanzhao Ren & Wanlin Gao & Xinliang Liu & Yongkang Hu & Redmond R. Shamshiri, 2021. "Comprehensive Evaluation of Soil Moisture Sensing Technology Applications Based on Analytic Hierarchy Process and Delphi," Agriculture, MDPI, vol. 11(11), pages 1-16, November.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:11:p:1116-:d:675535
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    References listed on IDEAS

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    1. Skevas, Theodoros & Kalaitzandonakes, Nicholas, 2020. "Farmer awareness, perceptions and adoption of unmanned aerial vehicles: evidence from Missouri," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 23(3), August.
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    Cited by:

    1. Wang, Zeyi & Zhang, Hengjia & Wang, Yingying & Wang, Yong & Lei, Lian & Liang, Chao & Wang, Yucai, 2023. "Deficit irrigation decision-making of indigowoad root based on a model coupling fuzzy theory and grey relational analysis," Agricultural Water Management, Elsevier, vol. 275(C).
    2. Agata Jędrzejuk & Marcin Bator & Adrian Werno & Lukasz Karkoszka & Natalia Kuźma & Ewa Zaraś & Robert Budzynski, 2022. "Development of an Algorithm to Indicate the Right Moment of Plant Watering Using the Analysis of Plant Biomasses Based on Dahlia × hybrida," Sustainability, MDPI, vol. 14(9), pages 1-14, April.

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