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Advances in Developments and Trends of UAV Technology in the Context of Precision Agriculture

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  • Mingxia Li

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China)

  • Jiyu Li

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China)

Abstract

Agriculture, as a core pathway for advancing modern agricultural development, emphasizes data-driven perception and intelligent decision-making. Unmanned aerial vehicles (UAVs), with advantages such as high-resolution imaging, flexible deployment, and adaptability to diverse terrains, have become an essential tool in this domain. This Editorial synthesizes the key findings from nine representative studies featured in this Special Issue, focusing on recent advancements in UAV-based remote sensing, flight control, and precision spraying. The results indicate that the integration of multispectral imagery with deep learning models significantly enhances crop identification and parameter inversion accuracy. Flight control performance has been greatly improved through innovations such as free-tail configuration optimization and fuzzy sliding mode composite control, ensuring stable operations in complex environments. In the realm of precision spraying, progress in wind vortex regulation and airflow modeling has led to improved droplet deposition consistency and target accuracy. Overall, UAV technologies demonstrate strong potential for cross-disciplinary integration and scalable application, offering robust support for the intelligent transformation of agricultural production.

Suggested Citation

  • Mingxia Li & Jiyu Li, 2025. "Advances in Developments and Trends of UAV Technology in the Context of Precision Agriculture," Agriculture, MDPI, vol. 15(11), pages 1-5, May.
  • Handle: RePEc:gam:jagris:v:15:y:2025:i:11:p:1146-:d:1665320
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    References listed on IDEAS

    as
    1. Bingquan Tian & Hailin Yu & Shuailing Zhang & Xiaoli Wang & Lei Yang & Jingqian Li & Wenhao Cui & Zesheng Wang & Liqun Lu & Yubin Lan & Jing Zhao, 2024. "Inversion of Cotton Soil and Plant Analytical Development Based on Unmanned Aerial Vehicle Multispectral Imagery and Mixed Pixel Decomposition," Agriculture, MDPI, vol. 14(9), pages 1-18, August.
    2. Xiaoyi Du & Denghong Huang & Li Dai & Xiandan Du, 2024. "Recognition of Plastic Film in Terrain-Fragmented Areas Based on Drone Visible Light Images," Agriculture, MDPI, vol. 14(5), pages 1-18, May.
    3. Suiyuan Shen & Jiyu Li & Yu Chen & Jia Lv, 2025. "Fuzzy Extended State Observer-Based Sliding Mode Control for an Agricultural Unmanned Helicopter," Agriculture, MDPI, vol. 15(3), pages 1-17, January.
    4. Xiandan Du & Zhongfa Zhou & Denghong Huang, 2024. "Influence of Spatial Scale Effect on UAV Remote Sensing Accuracy in Identifying Chinese Cabbage ( Brassica rapa subsp. Pekinensis ) Plants," Agriculture, MDPI, vol. 14(11), pages 1-18, October.
    5. Hang Xing & Zhijie Liu & Taoran Huang & Minyue Dong & Jia Lv & Feng Tang, 2024. "Wind Vortex Target Control of a Plant Protection UAV Based on a Rice Wind Vortex–Flight Parameter Model," Agriculture, MDPI, vol. 14(8), pages 1-17, August.
    6. Youyan Huang & Lihui Yan & Zhongfa Zhou & Denghong Huang & Qianxia Li & Fuxianmei Zhang & Lu Cai, 2024. "Complex Habitat Deconstruction and Low-Altitude Remote Sensing Recognition of Tobacco Cultivation on Karst Mountainous," Agriculture, MDPI, vol. 14(3), pages 1-19, March.
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