journal article·2023-10-22Open access

Comparison of the Spray Effects of Air Induction Nozzles and Flat Fan Nozzles Installed on Agricultural Drones

Seung-Hwa Yu, Yeongho Kang, Chun-Gu Lee

Applied Sciences· Volume 13· Issue 20

Abstract

Pest control is essential for increasing agricultural production. Agricultural drones with spraying systems for pest control have generated great interest among farmers. However, spraying systems installed on unmanned aerial vehicles, like any other sprayer, can cause damage to the environment due to drift of the agent. Air induction (AI) nozzles are known to produce less drift (e.g., larger spray drops) than other nozzles, but there is a lack of research analyzing their effectiveness in combination with drones. In this study, AI and flat fan nozzles were installed on drones to evaluate their spray and pest control performance. Aerial spraying was conducted on rice and soybeans to measure the coverage and penetration ratio and analyze the crop production as well as the crop damage due to pests and diseases. The drone flight was conducted at an altitude of 3 m and a velocity of 2 m/s. Spray droplets were collected using water-sensitive paper at two heights above the soil surface. The experiments showed that the crop coverage with the AI nozzle was 130% higher than that with the flat fan nozzle. The drift reduction of AI nozzles increased the coverage of spray droplets. But the difference in the penetration ratios, which is the ratio of agents to be delivered inside the crop, was not significant between the nozzles. Also, there was no significant difference in crop yield and pest control efficacy. Consequently, the performance of the AI nozzle did not show differences from that of the XR nozzle, except for coverage. However, the AI nozzle raised less drift, so it should be considered for use in aerial control.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Plant Surface Properties and Treatments · Electrohydrodynamics and Fluid Dynamics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

National Academy of Agricultural Science, Rural Development Administration, Jeonju 54875, Republic of Korea

Jeollabuk-do Agricultural Research & Extension Services, Iksan 54591, Republic of Korea

Funding

Cooperative Research Program for Agriculture Science and Technology Development

References (53)

Show source-provided references
1. UN (2022). World Population Prospects: Summary of Results, UN. UN DESA/POP/2022/TR/NO. 3.
2. Agriculture in 2050: Recalibrating Targets for Sustainable Intensification10.1093/biosci/bix010 ↗
3. Crop losses to pests10.1017/S0021859605005708 ↗
4. Skendžić, S., Zovko, M., Živković, I.P., Lešić, V., and Lemić, D. (2021). The Impact of Climate Change on Agricultural Insect Pests. Insects, 12.10.3390/insects12050440 ↗
5. FAO (2022). World Food and Agriculture–Statistical Yearbook 2022, FAO.
6. Pesticide Application Technology: Research and Development and the Growth of the Industry10.13031/2013.24377 ↗
7. OECD (2021). State of the Knowledge—Literature Review on Unmanned Aerial Spray Systems in Agriculture, OECD.
8. Hanif, A.S., Han, X., and Yu, S.-H. (2022). Independent Control Spraying System for UAV-Based Precise Variable Sprayer: A Review. Drones, 6.10.3390/drones6120383 ↗
9. Nozzle Pressure Response Characteristics of Variable Rate System for Unmanned Aerial Applications10.1007/s42853-019-00002-4 ↗
10. Characteristics of unmanned aerial spraying systems and related spray drift: A review10.3389/fpls.2022.870956 ↗
11. Unmanned Aerial Vehicles in Agriculture: A Review of Perspective of Platform, Control, and Applications10.1109/ACCESS.2019.2932119 ↗
12. (2021). Agricultural and Forestry Machinery—Unmanned Aerial Spraying Systems—Environmental Requirements (Standard No. DIS 23117-1).
13. Review of agricultural spraying technologies for plant protection using unmanned aerial vehicle (UAV)
14. Tsouros, D.C., Bibi, S., and Sarigiannidis, P.G. (2019). A Review on UAV-Based Applications for Precision Agriculture. Information, 10.10.3390/info10110349 ↗
15. Morales-Rodríguez, P.A., Cano Cano, E., Villena, J., and López-Perales, J.A. (2022). A Comparison between Conventional Sprayers and New UAV Sprayers: A Study Case of Vineyards and Olives in Extremadura (Spain). Agronomy, 12.10.3390/agronomy12061307 ↗
16. Wang, L., Huang, X., Li, W., Yan, K., Han, Y., Zhang, Y., Pawlowski, L., and Lan, Y. (2022). Progress in Agricultural Unmanned Aerial Vehicles (UAVs) Applied in China and Prospects for Poland. Agriculture, 12.10.3390/agriculture12030397 ↗
17. Zhang, Y., Huang, X., Lan, Y., Wang, L., Lu, X., Yan, K., Deng, J., and Zeng, W. (2021). Development and Prospect of UAV-Based Aerial Electrostatic Spray Technology in China. Appl. Sci., 11.10.3390/app11094071 ↗
18. Recent development of unmanned aerial vehicle for plant protection in East Asia
19. Testing a multi-rotor unmanned aerial vehicle for spray application in high slope terraced vineyard10.4081/jae.2019.853 ↗
20. Spray uniformity testing of unmanned aerial spraying system for precise agro-chemical applications
21. Lee, C.-G., Yu, S.-H., and Rhee, J.-Y. (2023). Effects of Unmanned Aerial Spray System Flight Altitude and Collector Height on Spray Deposition Measured Using a Food Dye Tracer. Agriculture, 13.10.3390/agriculture13010096 ↗
22. Aerial Spray Drift from Different Formulations of Glyphosate10.13031/2013.2735 ↗
23. (2009). Establishing a Framework for Community Action to Achieve the Sustainable Use of Pesticides (Standard No. DIRECTIVE 2009/128/EC).
24. Spray drift review: The extent to which a formulation can contribute to spray drift reduction10.1016/j.cropro.2012.10.020 ↗
25. Chen, S., Lan, Y., Zhou, Z., Ouyang, F., Wang, G., Huang, X., Deng, X., and Cheng, S. (2020). Effect of Droplet Size Parameters on Droplet Deposition and Drift of Aerial Spraying by Using Plant Protection UAV. Agronomy, 10.10.3390/agronomy10020195 ↗
26. Effects of Spray Parameters of Drone on the Droplet Deposition in Sugarcane Canopy10.1007/s12355-019-00792-z ↗
27. Experimental Analysis of the Downwash Airflow Created by a Single Rotor Blade in Agricultural Drones10.1007/s42853-021-00109-7 ↗
28. Drift potential of UAV with adjuvants in aerial applications
29. Numerical verification on influence of multi-feature parameters to the downwash airflow field and operation effect of a six-rotor agricultural UAV in flight10.1016/j.compag.2021.106425 ↗
30. Yang, F., Xue, X., Cai, C., Sun, Z., and Zhou, Q. (2018). Numerical Simulation and Analysis on Spray Drift Movement of Multirotor Plant Protection Unmanned Aerial Vehicle. Energies, 11.10.3390/en11092399 ↗
31. Influence of the downwash airflow distribution characteristics of a plant protection UAV on spray deposit distribution10.1016/j.biosystemseng.2022.01.016 ↗
32. Effect of Injection Angle on Drift Potential Reduction in Pesticide Injection Nozzle Spray Applied in Domestic Agricultural Drones10.1007/s42853-021-00093-y ↗
33. Measurement and Prediction of Atomization Parameters from Fixed-Wing Aircraft Spray Nozzles10.13031/2013.23123 ↗
34. Guo, H., Zhou, J., Liu, F., He, Y., Huang, H., and Wang, H. (2020). Application of Machine Learning Method to Quantitatively Evaluate the Droplet Size and Deposition Distribution of the UAV Spray Nozzle. Appl. Sci., 10.10.3390/app10051759 ↗
35. Efficacy of cotton harvest aids applications with unmanned aerial vehicles (UAV) and ground-based field sprayers—A case study comparison10.1016/j.atech.2022.100047 ↗
36. Technologies, T. (2014). Catalog 51A-M, TeeJet.
37. Drift of Droplets from Air-Induction Nozzles10.13031/trans.13421 ↗
38. Developments in application technology10.1007/s10669-007-9039-2 ↗
39. Spray Characteristics and Drift Reduction Potential with Air Induction and Conventional Flat-Fan Nozzles10.13031/2013.23129 ↗
40. Design and Performance Evaluation of Air Induction (AI) Nozzles to Reduce Drift Potential for Agricultural Unmanned Aerial Vehicles (UAVs)10.1007/s42853-021-00119-5 ↗
41. Lou, Z., Xin, F., Han, X., Lan, Y., Duan, T., and Fu, W. (2018). Effect of Unmanned Aerial Vehicle Flight Height on Droplet Distribution, Drift and Control of Cotton Aphids and Spider Mites. Agronomy, 8.10.3390/agronomy8090187 ↗
42. Spray Penetration into Peanut Canopies with Hydraulic Nozzle Tips10.1016/j.biosystemseng.2003.11.012 ↗
43. Development of a Canopy Opener to Improve Spray Deposition and Coverage Inside Soybean Canopies: Part 1. Mathematical Models to Assist Opener Development10.13031/2013.25389 ↗
44. (2020). Spray Nozzle Classification by Droplet Spectra (Standard No. ANSI/ASAE S572.3).
45. Hofman, V., and Solseng, E. (2004). Spray Equipment and Calibration, North Dakota State University.
46. The use of a water sensitive dye for the detection and assessment of small spray droplets10.1016/0021-8634(70)90099-5 ↗
47. A model to estimate the spray deposit by simulated water sensitive papers10.1016/j.cropro.2019.104861 ↗
48. Performance of new flat fan nozzle design in spray deposition, penetration and control of soybean rust10.1007/s10658-019-01803-1 ↗
49. Coverage and drift potential associated with nozzle and speed selection for herbicide applications using an unmanned aerial sprayer10.1017/wet.2019.101 ↗
50. Effects of citrus tree-shape and spraying height of small unmanned aerial vehicle on droplet distribution
51. Drolet Size and Leaf Morphology Effects on Pesticide Spray Deposition10.13031/2013.2700 ↗
52. Modelling operation parameters of UAV on spray effects at different growth stages of corns
53. Wang, G., Lan, Y., Yuan, H., Qi, H., Chen, P., Ouyang, F., and Han, Y. (2019). Comparison of Spray Deposition, Control Efficacy on Wheat Aphids and Working Efficiency in the Wheat Field of the Unmanned Aerial Vehicle with Boom Sprayer and Two Conventional Knapsack Sprayers. Appl. Sci., 9.10.3390/app9020218 ↗