When the unmanned aerial vehicle (UAV) is used for aerial spraying, the downwash airflow generated by the UAV rotor will interact with the crop canopy and form a conical vortex shape in the crop plant. The size of the vortex will directly affect the outcome of the spraying operation. Six one-way spraying were performed by the UAV in a rice field with different but random flying altitude and velocities within the optimal operational range to form different vortex patterns. The spraying reagent was clear water, which was collected by water sensitive paper (WSP), and then the WSP was analyzed to study the droplets deposition effects in different vortex states. The results showed that the formation of the vortex significantly influenced the droplet deposition. To be specific, the droplet deposition amount in the obvious-vortex (OV) state was about 1.5 times of that in the small-scale (SV) vortex state, and 7 times of that in the non-vortex (NV) state. In the OV state, the droplets mainly deposited directly below and on both sides of the route. The deposition amount, coverage rate and droplet size increased from top to bottom of the crops with the deposition amount, coverage rate, and volume median diameter (VMD) ranging 0.204–0.470 μL/cm 2 , 3.31%-7.41%, and 306–367μm, respectively. In the SV state, droplets mainly deposited in the vortex area directly below the route. The deposition amount in the downwind direction was bigger than that in the upwind direction. The maximum of deposition amount, coverage rate and droplet size were found in the middle layer of the crops, the range are 0.177–0.334μL/cm 2 , 2.71%-5.30%, 295–370μm, respectively. In the NV state, the droplet mainly performed drifting motion, and the average droplet deposition amount in the downwind non-effective region was 29.4 times of that in the upwind non-effective region and 8.7 times of the effective vortex region directly below the route. The maximum of deposition amount, coverage rate and droplet size appeared in the upper layer of the crop, the range are 0.006–0.132μL/cm 2 , 0.17%-1.82%, 120–309μm, respectively, and almost no droplet deposited in the middle and lower part of the crop. The coefficient of variation (CV) of the droplet deposition amount was less than 40% in the state of obvious-vortex and small-scale vortex, and the worst penetration appeared in the non-vortex amounting to 65.97%. This work offers a basis for improving the spraying performance of UAV.

Spray drift has always been a focus research area in the field of unmanned aerial vehicle (UAV) application. Under the fixed premises of UAV operating parameters, such as height, speed and spraying liquid, the droplet drift is mainly affected by meteorological conditions. In this research, the spray drift and deposition tests were conducted using a QuanFeng120 UAV in a pineapple field under various different meteorological conditions. The experimental results showed that with the changes of UAV operating height and wind speed, the start position of the in-swath deposition area changed 4 m in the extreme situation. The percentage of the total spray drift was from 15.42% to 55.76%. The position of cumulative spray drift that accounted for 90% of the total spray drift was from 3.70 m to 46.50 m relative to the flight line. According to the downwind spray drift curve, the nonlinear equations of the same type under the four operating conditions of the UAV were fitted. The spray drift and the deposition of UAV application were significantly affected by different meteorological conditions and UAV operating heights. The results could provide a theoretical basis for UAV spraying in pineapple plants and support for spray drift control and prediction.

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In recent decades, scientific and technological developments have continued to increase in speed, with researchers focusing not only on the innovation of single technologies but also on the cross-fertilization of multidisciplinary technologies. Unmanned aerial vehicle (UAV) technology has seen great progress in many aspects, such as geometric structure, flight characteristics, and navigation control. The You Only Look Once (YOLO) algorithm was developed and has been refined over the years to provide satisfactory performance for the real-time detection and classification of multiple targets. In the context of technology cross-fusion becoming a new focus, researchers have proposed YOLO-based UAV technology (YBUT) by integrating the above two technologies. This proposed integration succeeds in strengthening the application of emerging technologies and expanding the idea of the development of YOLO algorithms and drone technology. Therefore, this paper presents the development history of YBUT with reviews of the practical applications of YBUT in engineering, transportation, agriculture, automation, and other fields. The aim is to help new users to quickly understand YBUT and to help researchers, consumers, and stakeholders to quickly understand the research progress of the technology. The future of YBUT is also discussed to help explore the application of this technology in new areas.

It is difficult for the handheld/backpack or ground machinery to spray pineapple plant fields because the plant profile is relatively inaccessible. In this situation, unmanned aerial vehicles (UAVs) are a good choice for easy access and no physical damage to the crops. Aerial spray quality and optimum application parameter settings can be influenced by many factors such as UAV type, UAV operating parameters, meteorological conditions, crop growth period, and pest species. The objective of this study was to investigate the effects of different meteorological conditions and UAV operating height on the spray application in pineapple fields. There were five treatments involving three UAV operating heights. Mylar cards, water-sensitive papers, and airborne concentrations of spray were sampled at various locations from −10 to 50 m downwind of the edge of the sprayed blocks. The results indicated that as the wind speed increased, the swath location was displaced 2 to 4 m, the percent area coverage uniformity changed along with the spray penetration capacity, and the 90% of total measured drift distance varied from 3.7 to 46.5 m. The test results again proved that droplet size and wind speed were significant factors in spray transport and impacted the UAV spray quality.