Effect of Operational Parameters of Unmanned Aerial Vehicle (UAV) on Droplet Deposition in Trellised Pear Orchard

被引:16
|
作者
Qi, Peng [1 ,2 ,3 ]
Zhang, Lanting [1 ,2 ,3 ]
Wang, Zhichong [4 ]
Han, Hu [1 ,2 ,3 ]
Mueller, Joachim [4 ]
Li, Tian [1 ,2 ,3 ]
Wang, Changling [1 ,2 ,3 ]
Huang, Zhan [1 ,2 ,3 ]
He, Miao [1 ,2 ,3 ]
Liu, Yajia [1 ,2 ,3 ]
He, Xiongkui [1 ,2 ,3 ]
机构
[1] China Agr Univ, Coll Sci, Beijing 100193, Peoples R China
[2] China Agr Univ, Ctr Chem Applicat Technol, Beijing 100193, Peoples R China
[3] China Agr Univ, Coll Agr Unmanned Syst, Beijing 100193, Peoples R China
[4] Univ Hohenheim, Inst Agr Engn, Trop & Subtrop Grp, D-70599 Stuttgart, Germany
关键词
unmanned aerial vehicle; droplet deposition; spray coverage; droplet density; orthogonal experiment; pear orchard; CITRUS-TREES; SPRAYER; DESIGN;
D O I
10.3390/drones7010057
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Background: Unmanned Aerial Vehicles (UAVs) are increasingly being used commercially for crop protection in East Asia as a new type of equipment for pesticide applications, which is receiving more and more attention worldwide. A new model of pear cultivation called the 'Double Primary Branches Along the Row Flat Type' standard trellised pear orchards (FT orchard) is widely used in China, Japan, Korea, and other Asian countries because it saves manpower and is suitable for mechanization compared to traditional spindle and open-center cultivation. The disease and pest efficacy of the flat-type trellised canopy structure of this cultivation is a great challenge. Therefore, a UAV spraying trial was conducted in an FT orchard, and a four-factor (SV: Spray application volume rate, FS: Flight speed, FH: Flight height, FD: Flight direction) and 3-level orthogonal test were designed. Results: These data were used to analyze the effect, including spray coverage, deposit density, coefficient of variation, and penetration coefficient on the canopy, to determine the optimal operating parameters of the UAV for pest efficacy in FT orchards. The analysis of extremes of variance showed that factor FD had a significant effect on both spray coverage and deposition density. Followed by factor FS, which had a greater effect on spray coverage (p < 0.05), and factor SV, FH, which had a greater effect on deposition density (p < 0.05). The effects of different factors on spray coverage and deposit density were FD > FS > FH > SV, FD > FH > SV > FS, in that order. The SV3-FS1-FH1-FD3, which flight along the row with an application rate of 90 L/ha, a flight speed of 1.5 m/s, and a flight height of 4.5 m, was the optimal combination, which produced the highest deposit density and spray coverage. It was determined through univariate analysis of all experimental groups, using droplet density of 25/cm(2) and spray coverage of 1%, and uniformity of 40% as the measurement index, that T4 and T8 performed the best and could meet the control requirements in different horizontal and vertical directions of the pear canopy. The parameters were as follows: flight along the tree rows, application rate not less than 75 L/ha, flight speed no more than 2 m/s, and flight height not higher than 5 m. Conclusion: This article provides ample data to promote innovation in the use of UAVs for crop protection programs in pergola/vertical trellis system orchards such as FT orchards. At the same time, this project provided a comprehensive analysis of canopy deposition methods and associated recommendations for UAV development and applications.
引用
收藏
页数:24
相关论文
共 50 条
  • [21] A Nonlinear Filter for Efficient Attitude Estimation of Unmanned Aerial Vehicle (UAV)
    Goslinski, Jaroslaw
    Giernacki, Wojciech
    Krolikowski, Andrzej
    JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2019, 95 (3-4) : 1079 - 1095
  • [22] A Nonlinear Filter for Efficient Attitude Estimation of Unmanned Aerial Vehicle (UAV)
    Jarosław Gośliński
    Wojciech Giernacki
    Andrzej Królikowski
    Journal of Intelligent & Robotic Systems, 2019, 95 : 1079 - 1095
  • [23] Design and fabrication of a fixed-wing Unmanned Aerial Vehicle (UAV)
    El Adawy, Mohammed
    Abdelhalim, Elhassan H.
    Mahmoud, Mohannad
    Zeid, Mohamed Ahmed Abo
    Mohamed, Ibrahim H.
    Othman, Mostafa M.
    ElGamal, Gehad S.
    ElShabasy, Yahia H.
    AIN SHAMS ENGINEERING JOURNAL, 2023, 14 (09)
  • [24] Determination of Riparian Vegetation Biomass from an Unmanned Aerial Vehicle (UAV)
    Matese, Alessandro
    Berton, Andrea
    Chiarello, Valentina
    Dainelli, Riccardo
    Nati, Carla
    Pastonchi, Laura
    Toscano, Piero
    Di Gennaro, Salvatore Filippo
    FORESTS, 2021, 12 (11):
  • [25] The suitability of an unmanned aerial vehicle (UAV) for the evaluation of experimental fields and crops
    Pudelko, Rafal
    Stuczynski, Tomasz
    Borzecka-Walker, Magdalena
    ZEMDIRBYSTE-AGRICULTURE, 2012, 99 (04) : 431 - 436
  • [26] Measurement of Greenhouse Gases in UAE by Using Unmanned Aerial Vehicle (UAV)
    Abou-Elnour, Ali
    Odeh, Mohamed
    Abdelrhman, Mohammed
    Balkis, Ahmed
    Amira, Abdelraouf
    SENSORS AND SMART STRUCTURES TECHNOLOGIES FOR CIVIL, MECHANICAL, AND AEROSPACE SYSTEMS 2017, 2017, 10168
  • [27] Aerial surveys and tagging of free-drifting icebergs using an unmanned aerial vehicle (UAV)
    McGill, P. R.
    Reisenbichler, K. R.
    Etchemendy, S. A.
    Dawe, T. C.
    Hobson, B. W.
    DEEP-SEA RESEARCH PART II-TOPICAL STUDIES IN OCEANOGRAPHY, 2011, 58 (11-12) : 1318 - 1326
  • [28] Remote Measurement of Apple Orchard Canopy Information Using Unmanned Aerial Vehicle Photogrammetry
    Sun, Guoxiang
    Wang, Xiaochan
    Ding, Yongqian
    Lu, Wei
    Sun, Ye
    AGRONOMY-BASEL, 2019, 9 (11):
  • [29] Dual-Polarized Hexaferrite Antenna for Unmanned Aerial Vehicle (UAV) Applications
    Lee, Woncheol
    Hong, Yang-Ki
    Lee, Jaejin
    Gillespie, David
    Ricks, Kenneth G.
    Hu, Fei
    Abu-Qahouq, Jaber
    IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS, 2013, 12 : 765 - 768
  • [30] Research on detection method of pavement diseases based on Unmanned Aerial Vehicle (UAV)
    Mao, Zhijian
    Zhao, Chihang
    Zheng, Youfeng
    Mao, Yan
    Li, Hao
    Hua, Liru
    Liu, Yang
    2020 INTERNATIONAL CONFERENCE ON IMAGE, VIDEO PROCESSING AND ARTIFICIAL INTELLIGENCE, 2020, 11584