An anti-fall and anti-drift unmanned aerial vehicle comprises an unmanned aerial vehicle body (1). At least one rotor (10) is disposed on the unmanned aerial vehicle body (1). Wings (3) are respectively disposed on the left side and the right side of the unmanned aerial vehicle body (1). An air bag (2) is disposed each wing (3) respectively. Protrusions (21) protruding downwards are disposed at the bottoms of the air bags (2). The two air bags (2) are located at the positions at the same height. The two air bags (2) are symmetrically disposed on the basis of the unmanned aerial vehicle body (1). Gas lighter than air is injected into the air bags (2). The air bags (2) are respectively disposed on the two sides of the unmanned aerial vehicle body (1), and therefore when the aerial vehicle lands, the air bags (2) can serve as an undercarriage. The beneficial effects that buffering is achieved and damage to the unmanned aerial vehicle body (1) is reduced can be achieved when the aerial vehicle falls and is exploded and falls to the ground. If the aerial vehicle falls to fields or water surfaces by accident, the aerial vehicle can float on the water surfaces under the action of the air bags (2), damage caused when the aerial vehicle sinks into water is avoided, and the safety performance of the aerial vehicle is improved. In addition, the protrusions (21) protruding downwards are disposed at the bottoms of the air bags (2), and therefore when the spraying work is conducted, the protrusions (21) can block side wind to reduce drifting of mist drops, and the utilization efficiency of the mist drops is improved.
Chemical harvest aids applied by ground-based machines with heavy wheels and high-volume spraying in cotton (Gossypium hirsutum L.) fields to defoliate leaves and ripen bolls before harvest threaten soil health and result in cotton yield loss. For example, ground-based machines roll over cotton plants at corners and pull the cotton branches between rows, resulting in yield loss. Furthermore, heavy wheels can cause soil compaction, resulting in decreased soil biodiversity. High-volume spraying often results in harvest aids polluting the soil. A new harvest-aid application method that can save water, increase harvest-aid utilization rate without damage to soils and crops is needed to apply chemical harvest aids before harvest. Small plant protection unmanned aerial vehicles (UAVs) with low-volume spraying methods have emerged as pesticide application technologies in recent years in China due to their high efficiency, high flexibility, low labor requirements, water savings and lack of damage to crops and soils. Here, UAVs are developed for chemical harvest-aid application by evaluating the cotton defoliation efficacy, boll opening rate, lint cotton yield and fiber quality components at two cotton field experimental sites in Xinjiang Uygur Autonomous Region of China in 2016 and 2017. Ground-based machine treatment is used as a reference. The assessment is proceeded with the following steps: (1) The spray volume of UAV is optimized in 2016; (2) The experiment of 2016 is repeated to determine the optimal spray volume in 2017. The results show the following: (1) The harvest-aid performance is sensitive to the spray volume in the UAV low-volume spraying treatment, and optimal defoliation efficacy is achieved when the spray volume is 22.5 L/ha and flight velocity is 4 m/s, according to the field tests in 2016 and 2017. (2) Low-volume spraying using UAV has no negative influence on the lint cotton yield and fiber quality components. In conclusion, it is feasible to use plant protection UAV for cotton harvest-aid applications in preparation for machine harvesting.
In this study, starch-based microparticles (MPs) fabricated by a water-in-water (w/w) emulsification-crosslinking method could be used as a controlled release delivery vehicle for food bioactives. Due to the processing route without the use of toxic organic solvents, it is expected that these microparticles can be used as delivery vehicles for controlled release of food bioactives. Octenyl succinic anhydride (OSA) starch was used as raw material. Optical microscopy showed OSA starch-based microparticles (OSA-MPs) had a good dispersibility. Scanning electron microscopy (SEM) showed OSA-MPs had a solid structure and spherical shape. X-ray diffraction (XRD) patterns revealed that OSA-MPs were of amorphous structure. A Plackett-Burman screening design methodology was employed to evaluate the effects of the process and formulation parameters on the particle size of OSA-MPs. Considering the statistical analysis of the results, it appeared that the OSA starch concentration (P = 0.0146), poly(ethylene glycol) (PEG) molecular weight (P = 0.0155), volume ratio of dispersed phase/continuous phase (P = 0.0204) and PEG concentration (P = 0.0230) had significant effect on particle size. (C) 2008 Elsevier Ltd. All rights reserved.
Defoliant spraying is an important aspect of mechanized cotton harvesting. Fully and uniformly spraying defoliant could improve the quality of defoliation and reduce the impurity content in cotton. Improving the coverage of defoliant droplets in the middle and lower layers of cotton and ensuring the full and even dispersion of droplets in the cotton canopy are essentially in increasing the defoliation effect. In this study, we assessed the effect of aviation spray adjuvants on droplet deposition, defoliation, boll opening and defoliant retention in cotton leaves sprayed by an unmanned aerial vehicle (UAV). The results showed that adding aviation spray adjuvants could significantly improve the defoliant droplet deposition. Fifteen days after spraying, the defoliation rate was 80.31% and the boll opening was 90.61%. The defoliation rate increased by 3.12-34.62% and the boll opening rate increased by 6.67-29.56% after the addition of aviation spray adjuvants. Using a vegetable oil adjuvant could significantly increase the droplet coverage rate and the retention of defoliants in cotton leaves.
Previous studies have confirmed that choosing nozzles that produce coarser droplets could reduce the risk of pesticide spray drift, but this conclusion is based on a large volume of application, and it is easy to ignore how this impacts the control effect. The difference from the conventional spray is that the carrier volume of Unmanned Aerial Vehicle (UAV) is very limited. Little was known about how to choose suitable nozzles with UAV's limited volume to ensure appropriate pest control. Droplet deposition with the addition of adjuvant and the LU110-010, LU110-015, and LU110-020 nozzles and control of planthoppers within nozzles treatments were studied by a quadrotor UAV in rice (Tillering and Flowering stages). Allura Red (10 g/L) was used as a tracer and Kromekote cards were used to collect droplet deposits. The results indicate that the density of the droplets covered by the LU110-01 nozzle is well above other treatments, while the differences in droplet deposition and coverage are not significant. The deposition and coverage were improved with the addition of adjuvant, especially in LU110-01 nozzles' treatment. The control effects of rice planthoppers treated by LU110-01 nozzle were 89.4% and 90.8% respectively, which were much higher than 67.6% and 58.5% of LU110-020 nozzle at 7 days in the Tillering and Flowering stage. The results suggest that selecting a nozzle with a small atomizing particle size for UAV could improve the control effect of planthoppers.
Rotor unmanned aerial vehicle (UAV) for plant protection has been widely applied in China in recent years. As a unique and crucial parameter of rotor UAV, the distribution shape and law of rotor wind field determine the spatial distribution of spraying droplets and influence the outcome of low-altitude pesticide spraying. However, the exploration of the interaction between rice canopy and wind field as well as the vertical decay mechanism is still an uncharted field in the study of three-dimensional wind field. In this paper, the author acquired vertical wind speed through S pitot sensor array, wind speed sensors were installed to acquire vertical wind speed data in the canopy, 30 cm beneath the canopy and 60 cm beneath the canopy. Contour maps at three height levels with wind speed of equal difference were drawn to calculate the equivalent area (the area surrounded by the contour line and the upper boundary) and maximum wind field width, all of which are direct parameters represent the distribution pattern of different wind speeds at equal time span. Under the condition that rice plants are well-distributed with consistent density, as the height decays arithmetically, coefficient variance (CV) of equivalent area is no more than 5% with basically equal reduction in equivalent area, the vertical wind field formed by the decayed airflow as it travels through rice plants distributes hierarchically. The decay rate of equivalent area and wind speed follow linear relation. When the height reduces from Ptop to Pmedium, the decay rate monotonically changes from 47.9% to 8.4%. When the height reduces from Pmedium to Pbottom, the decay rate monotonically changes from 53.7% to 22.4%. The lower the height is, the greater the decay rate is. Having analyzed the abnormal data ranges, the author found that the vortex formed under the interaction of wind field and rice canopy is the primary cause of abnormal data. Moreover, an ideal cone model was built on the basis of the rotor area and decay rate of equivalent area at equal height. The cone model not only justifies the vortex structure of rotor wind field but also provides theoretical foundation for the permeability study of droplets in rice canopy and the study of pollination parameters.
Appropriate Site Specific Weed Management (SSWM) is crucial to ensure the crop yields. Within SSWM of large-scale area, remote sensing is a key technology to provide accurate weed distribution information. Compared with satellite and piloted aircraft remote sensing, unmanned aerial vehicle (UAV) is capable of capturing high spatial resolution imagery, which will provide more detailed information for weed mapping. The objective of this paper is to generate an accurate weed cover map based on UAV imagery. The UAV RGB imagery was collected in 2017 October over the rice field located in South China. The Fully Convolutional Network (FCN) method was proposed for weed mapping of the collected imagery. Transfer learning was used to improve generalization capability, and skip architecture was applied to increase the prediction accuracy. After that, the performance of FCN architecture was compared with Patch_based CNN algorithm and Pixel_based CNN method. Experimental results showed that our FCN method outperformed others, both in terms of accuracy and efficiency. The overall accuracy of the FCN approach was up to 0.935 and the accuracy for weed recognition was 0.883, which means that this algorithm is capable of generating accurate weed cover maps for the evaluated UAV imagery.=20
Yao, Weixiang
Lan, Yubin
Hoffmann, W. Clint
Li, Jiyu
Guo, Shuang
Zhang, Huihui
Wang, Juan
To investigate the spray atomization characteristics of aerial nozzles adapted to manned agricultural helicopters under medium-low airflow velocity (0 to 27.8 m/s) conditions, the droplet size test was carried out in both wind tunnel and field tests. In the wind tunnel test, the laser diffraction device (LDD) was used to test the spray droplet size of CP02, CP03, and CP04 aerial nozzles. A Bell206L4 helicopter was used in the field test. The results in the wind tunnel test showed that due to the nozzles had been used for a long time and the cause of wear, the spray stability of individual nozzles was affected during the test. The limitation of droplet size measurement by using LDD was also found. The field test results showed that the main distribution range of the droplet size measured in the field test was consistent with the results of the wind tunnel test, but the droplet size value was significantly higher and the uniformity of droplet size distribution was poorer than the wind tunnel test value due to the influence of the actual environment. However, the results of field test and wind tunnel test can still be used as a reference for each other.
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