Comparison of Water Sensitive Paper and Glass Strip Sampling Approaches to Access Spray Deposit by UAV Sprayers

被引:10
作者
Ahmad, Fiaz [1 ,2 ,3 ]
Zhang, Songchao [1 ,2 ]
Qiu, Baijing [2 ]
Ma, Jing [2 ]
Xin, Huang [2 ]
Qiu, Wei [4 ]
Ahmed, Shibbir [2 ]
Chandio, Farman Ali [5 ]
Khaliq, Aftab [3 ]
机构
[1] Nanjing Inst Agr Mech, Minist Agr & Rural Affairs, Nanjing 210014, Peoples R China
[2] Jiangsu Univ, Sch Agr Engn, Zhenjiang 212013, Jiangsu, Peoples R China
[3] Bahauddin Zakariya Univ, Dept Agr Engn, Multan 60800, Pakistan
[4] Nanjing Agr Univ, Coll Engn, Nanjing 210031, Peoples R China
[5] Sindh Agr Univ, Fac Agr Engn, Dept Farm Power & Machinery, Tandojam 70060, Pakistan
来源
AGRONOMY-BASEL | 2022年 / 12卷 / 06期
关键词
UAV sprayers; sampling approach; depositions; water-sensitive paper; glass sampler; UNMANNED AERIAL VEHICLE; NUMERICAL-SIMULATION; DROPLET DEPOSITION; DRIFT; ADJUVANTS; EFFICACY; QUALITY; HEIGHT; SYSTEM;
D O I
10.3390/agronomy12061302
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Target and off-target spray depositions determine the spray's effectiveness and impact on the environment. A decisive stage in the measurement of spray deposition and drift is selecting an appropriate sampling approach under field conditions. There are various approaches available for sampling spray deposition and drift, during the evaluation of ground sprayers used for the UAV sprayer assessment, under field conditions. In this study, two sampling approaches (water-sensitive paper, and glass strip collectors) were compared to analyze spray deposition in target and off-target zones. The results showed a variation in the estimation of the spray deposits among the two applied sampling methods. The results showed that the water-sensitive paper recorded the droplet deposition in the target zone with a range from 0.049 to 4.866 mu Lcm(-2), whereas the glass strip recorded from 0.11 to 0.793 mu Lcm(-2). The results also showed the water sensitive paper recorded an 80.3% higher deposition than that of the glass strip at zero position during the driving flight height 2 m and flight speed 2 ms(-1) (T1 treatment). It can be concluded that variation in recorded depositing is due to the sampling material. It is recommended that the confident deposition results, measurement methods and sampling approaches must be standardized for UAV sprayers according to the field conditions and controlled within artificial assessments.
引用
收藏
页数:13
相关论文
共 47 条
  • [1] Droplet deposition density of organic liquid fertilizer at low altitude UAV aerial spraying in rice cultivation
    Abd Kharim, Muhammad Nurfaiz
    Wayayok, Aimrun
    Shariff, Abdul Rashid Mohamed
    Abdullah, Ahmad Fikri
    Husin, Ezrin Mohd
    [J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2019, 167
  • [2] Effect of operational parameters of UAV sprayer on spray deposition pattern in target and off-target zones during outer field weed control application
    Ahmad, Fiaz
    Qiu, Baijing
    Dong, Xiaoya
    Ma, Jing
    Huang, Xin
    Ahmed, Shibbir
    Chandio, Farman Ali
    [J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2020, 172
  • [3] Stability Analysis of a Sprayer UAV with a Liquid Tank with Different Outer Shapes and Inner Structures
    Ahmed, Shibbir
    Xin, Huang
    Faheem, Muhammad
    Qiu, Baijing
    [J]. AGRICULTURE-BASEL, 2022, 12 (03):
  • [4] A State-of-the-Art Analysis of Obstacle Avoidance Methods from the Perspective of an Agricultural Sprayer UAV's Operation Scenario
    Ahmed, Shibbir
    Qiu, Baijing
    Ahmad, Fiaz
    Kong, Chun-Wei
    Xin, Huang
    [J]. AGRONOMY-BASEL, 2021, 11 (06):
  • [5] Influence of spray characteristics on potential spray drift of field crop sprayers: A literature review
    Al Heidary, M.
    Douzals, J. P.
    Sinfort, C.
    Vallet, A.
    [J]. CROP PROTECTION, 2014, 63 : 120 - 130
  • [6] Spray drift as influenced by meteorological and technical factors
    Arvidsson, Tommy
    Bergstrom, Lars
    Kreuger, Jenny
    [J]. PEST MANAGEMENT SCIENCE, 2011, 67 (05) : 586 - 598
  • [7] Mapping Wheat Dry Matter and Nitrogen Content Dynamics and Estimation of Wheat Yield Using UAV Multispectral Imagery Machine Learning and a Variety-Based Approach: Case Study of Morocco
    Astaoui, Ghizlane
    Eddine Dadaiss, Jamal
    Sebari, Imane
    Benmansour, Samir
    Mohamed, Ettarid
    [J]. AGRIENGINEERING, 2021, 3 (01): : 29 - 49
  • [8] Field-crop-sprayer potential drift measured using test bench: Effects of boom height and nozzle type
    Balsari, Paolo
    Gil, Emilio
    Marucco, Paolo
    van de Zande, Jan C.
    Nuyttens, David
    Herbst, Andreas
    Gallart, Montserrat
    [J]. BIOSYSTEMS ENGINEERING, 2017, 154 : 3 - 13
  • [9] DropLeaf: A precision farming smartphone tool for real-time quantification of pesticide application coverage
    Brandoli, Bruno
    Spadon, Gabriel
    Esau, Travis
    Hennessy, Patrick
    Carvalho, Andre C. P. L.
    Amer-Yahia, Sihem
    Rodrigues, Jose F., Jr.
    [J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2021, 180
  • [10] Caldwell B.C., 2006, ASP APPL BIOL, V77, P371