数字农科院2.0

Review of Active Plant Frost Protection Equipment and Technologies: Current Status, Challenges, and Future Prospects

文献类型: 外文期刊

作者: Liu, Tianhong;Zhang, Songchao;Sun, Tao;Ma, Cong;Xue, Xinyu

作者机构:

关键词: anti-frost heating system;plant frost protection;sprinkler irrigation;UAV;wind machine

期刊名称: AGRONOMY-BASEL

ISSN:

年卷期: 2025 年 15 卷 5 期

页码:

收录情况: SCIE(2025版)

摘要: Frost poses a significant threat to agricultural production, leading to reduced crop yields and deterioration in quality. This review systematically provides an overview of the types and causes of plant frost, and delves into the principles, research progress, and application status of three key active frost protection (FP) technologies: air disturbance, sprinkler irrigation, and heating. It also scrutinizes the challenges faced by current FP equipment, such as high costs, complex maintenance, and noise pollution. Air disturbance technology utilizes fans to mix upper and lower air layers, increasing the canopy temperature, with research focusing on fan optimization and unmanned aerial vehicle (UAV) application. Sprinkler irrigation technology releases latent heat through water freezing, with research centering on water saving and automation. Heating technology directly supplies heat, with attention on heat source optimization and mobile heating strategies. Finally, this review outlines the development trends of plant FP equipment and technologies, highlighting the promising application prospects of agricultural UAVs in FP, which can have multi-purpose use and effectively reduce costs.

分类号:

  • 相关文献

[1]Spatial and temporal distributions of nitrogen and crop yield as affected by nonuniformity of sprinkler fertigation. Li, JS,Li, B,Rao, MJ. 2005

[2]Effects of different irrigation methods on micro-environments and root distribution in winter wheat fields. Lu Guo-hua,Song Ji-qing,Bai Wen-bo,Wu Yong-Feng,Liu Yuan,Kang Yao-hu. 2015

[3]Characterizing center pivot irrigation with fixed spray plate sprinklers. Yan HaiJun,Jin HongZhi,Qian YiChao. 2010

[4]Field evaluation of crop yield as affected by nonuniformity of sprinkler-applied water and fertilizers. Li, JS,Rao, MJ. 2003

[5]Modeling crop yield as affected by uniformity of sprinkler irrigation system. Li, JS. 1998

[6]Experimental Characterization of Water Droplet Dynamics in Sprinkler Irrigation Using High-Speed Photography. Joseph Kwame Lewballah,Xingye Zhu,Peng Li,Alexander Fordjour. 2025

[7]Effect of Alternate Sprinkler Irrigation with Saline and Fresh Water on Soil Water-Salt Transport and Corn Growth. Jiang, Yue,Wang, Luya,Li, Yanfeng,Li, Hao,Xue, Run. 2025

[8]Numerical Simulation And Experimental Verification O.n Downwash Air Flow O f Six-Rotor Agricultural Unmanned Aerial Vehicle In Hover. Xue Xinyu,Yang Fengbo,Zhang Ling,Sun Zhu. 2017

[9]Development Of A Low-Cost Quadrotor U.av Based On Adrc F or Agricultural Remote Sensing. Xue, Xinyu,Zhang, Songchao,Zhang, Songchao,Sun, Tao,Chen, Chen,Sun, Zhu. 2019

[10]Drift and deposition of ultra-low altitude and low volume application in paddy field. Xue Xinyu,Tu Kang,Xue Xinyu,Qin Weicai,Lan, Yubin,Zhang, Huihui. 2014

[11]Estimating LAI for Cotton Using Multisource UAV Data and a Modified Universal Model. Yan, Puchen,Han, Qisheng,Feng, Yangming,Kang, Shaozhong. 2022

[12]A fast and robust method for plant count in sunflower and maize at different seedling stages using high-resolution UAV RGB imagery. Bai, Yi,Nie, Chenwei,Wang, Hongwu,Cheng, Minghan,Liu, Shuaibing,Yu, Xun,Shao, Mingchao,Wang, Zixu,Wang, Siyu,Tuohuti, Nuremanguli,Shi, Lei,Ming, Bo,Jin, Xiuliang. 2022

[13]Droplet distribution in cotton canopy using single-rotor and four-rotor unmanned aerial vehicles. Meng, Yanhua,Ma, Yan,Wang, Zhiguo,Hu, Hongyan. 2022

[14]Two-step ResUp&Down generative adversarial network to reconstruct multispectral image from aerial RGB image. Yanchao Zhang,Wen Yang,Wenbo Zhang,Jiya Yu,Jianxin Zhang,Yongjie Yang,Yongliang Lu,Wei Tang. 2022

[15]Predicting equivalent water thickness in wheat using UAV mounted multispectral sensor through deep learning techniques. Adama Traore,Syed Tahir Ata-Ul-karim,Aiwang Duan,Mukesh Kumar Soothar,Seydou Traore,Ben Zhao. 2021

[16]Detection and Counting of Maize Leaves Based on Two-Stage Deep Learning with UAV-Based RGB Image. Xu, Xingmei,Wang, Lu,Shu, Meiyan,Liang, Xuewen,Ghafoor, Abu Zar,Liu, Yunling,Ma, Yuntao,Zhu, Jinyu. 2022

[17]Data on three-year flowering intensity monitoring in an apple orchard: A collection of RGB images acquired from unmanned aerial vehicles. Chenglong Zhang,João Valente,Wensheng Wang,Pieter van Dalfsen,Peter Frans de Jong,Bert Rijk,Lammert Kooistra. 2023

[18]Quantitative estimation of organ-scale phenotypic parameters of field crops through 3D modeling using extremely low altitude UAV images. Binglin Zhu,Yan Zhang,Yanguo Sun,Yi Shi,Yuntao Ma,Yan Guo. 2023

[19]Identification of High Nitrogen Use Efficiency Phenotype in Rice (Oryza sativa L.) Through Entire Growth Duration by Unmanned Aerial Vehicle Multispectral Imagery. Liang Ting,Duan Bo,Luo Xiaoyun,Ma Yi,Yuan Zhengqing,Zhu Renshan, Peng Yi,Gong Yan,Fang Shenghui,Wu Xianting. 2021

[20]Estimating leaf area index using unmanned aerial vehicle data: Shallow vs. 2 deep machine learning algorithms. Shuaibing Liu, Xiuliang Jin*, Chenwei Nie, Siyu Wang, Xun Yu, Minghan Cheng, Mingchao Shao, Zixu Wang, Nuremanguli Tuohuti, Yi Bai, Yadong Liu. 2021

作者其他论文 更多>>