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

Authors :
Yu, Seung-Hwa
Kang, Yeongho
Lee, Chun-Gu
Source :
Applied Sciences (2076-3417); Oct2023, Vol. 13 Issue 20, p11552, 13p
Publication Year :
2023

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
13
Issue :
20
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
173266824
Full Text :
https://doi.org/10.3390/app132011552