Article

Close-range air-assisted precision spot-spraying for robotic applications: Aerodynamics and spray coverage analysis

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Abstract

Orchards and grapevines are currently sprayed overall. Most bush and tree crop sprayers use airflow assistance which generates movements in canopy exposing both sides of the leaves to the spray. Also, large coherent vortices are formed further contributing to improved spray coverage. A new close-range air-assisted spot-spraying method for the selective treatments of disease foci is evaluated here which is promising for reduction of pesticides. Targets structures are expected to have typical diameters around 150 mm and the size of the unit matches this. In contrast to conventional methods, this size of unit prevents the generation of large scale coherent turbulent structures in the airflow that could provide spray coverage of both sides of the target leaves. Therefore, to enhance the beneficial effects of local turbulence, and to induce leaf movement whilst retaining the small size of the spray unit, a rotating screen to generate airflow pulses with discrete peaks in velocity was added and tested. Experiments on the close-range spraying of young grapevine plants using the rotating airflow screen were performed. A high-speed camera, image analysis system and water sensitive papers were used for analysis of the spraying. Natural frequencies of individual leaves showed sharp fluctuations at discrete frequencies and single leaf fluctuations of root mean square velocity corresponded well to the pulsating airflow. Spraying was evaluated as percentage spray coverage and number of droplet impacts. Spray coverage of front side of leaves (facing the sprayer) was good, but coverage on the back of the leaves was limited.

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... In Fig. 12, Fig. 14 and Fig. 16, the x-axis represents height of plant. However, in Fig. 12, the y-axis represents that size of probability that 80 measurement results are in the interval of (0-5), (5)(6)(7)(8)(9)(10). . . (295-300), in Fig. 14, the y-axis represents that size of probability that 80 measurement results are in the interval of (0-5), (5)(6)(7)(8)(9)(10). . . ...
... However, in Fig. 12, the y-axis represents that size of probability that 80 measurement results are in the interval of (0-5), (5)(6)(7)(8)(9)(10). . . (295-300), in Fig. 14, the y-axis represents that size of probability that 80 measurement results are in the interval of (0-5), (5)(6)(7)(8)(9)(10). . . (825-830), in Fig. 16, the y-axis represents that size of probability that 80 measurement results are in the interval of (0-5), (5)(6)(7)(8)(9)(10). . . ...
... (295-300), in Fig. 14, the y-axis represents that size of probability that 80 measurement results are in the interval of (0-5), (5)(6)(7)(8)(9)(10). . . (825-830), in Fig. 16, the y-axis represents that size of probability that 80 measurement results are in the interval of (0-5), (5)(6)(7)(8)(9)(10). . . (995-1000). ...
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A computational fluid dynamics (CFD) model to simulate airflow from air-assisted orchard sprayers through pear canopies was validated for three different sprayers; single-fan (Condor V), two-fan (Duoprop) and four-fan sprayers (AirJet Quatt). The first two sprayers are widely used in Belgium and the latter one is a new design. Validation experiments were carried out in an experimental orchard (pcfruit, Velm, Belgium) in spring 2008. Ultrasonic anemometers were used to measure the time-averaged velocity components at different vertical positions before the tree and after the tree when the sprayers were driven through the orchard. The model was able to predict accurately the peak jet velocity, Um from all the sprayers considered at all distances from the sprayer centre and vertical positions. More than 95% of the local relative errors of Um were below 20%. Average relative errors, E, and root mean square errors, ERMS, were all less than 11.04% and 1.68 m s−1, respectively. The regions of high- (up to 18.0 m s−1 upstream) and low (down to 2.8 m s−1 downstream)-air velocity zones for all the sprayers were accurately predicted. The simulation results showed that the Condor V sprayer had a highly disturbed vertical jet velocity profile, especially at higher heights. The Duoprop sprayer had high jet velocities at the two-fan positions and lower jet velocity in between the two fans. Within the canopy height the AirJet Quatt sprayer showed a more uniform distribution of air than the other two sprayers except the minor peaks at the fan positions. These situations were all confirmed by the measurements.
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The performance of several commercial and experimental software packages (Gotas, StainMaster, ImageTool, StainAnalysis, AgroScan, DropletScan and Spray_imageI and II) that produce indicators of crop spraying quality based on the image processing of water-sensitive papers used as artificial targets were compared against known coverage, droplet size spectra and class size distribution verified through manual counting. A number of artificial targets used to test the software were obtained by controlled spray applications and given droplet density between 14 and 108 drops cm−2 and a wide range of droplet size spectra. The results showed that artificial targets coupled with an appropriate image system can be an accurate technique to compute spray parameters. The between-methods differences were 6.7% for droplet density, 11.5% for volume median diameter, <3% for coverage (%) and <3% coverage density. For the 16 droplet class size distribution tested the between-methods differences were all <15%. However, most of the image analysis systems were not effective in accurately measuring coverage density when coverage rate is greater than about 17%. The Spray_imageII software estimated the coverage density with a mean absolute error of 2% and the absolute error is below 10%, even with about 43% of coverage rate. This software, when compared to the other programmes tested, provided the best accuracy for coverage and droplet size spectrum as well as for droplet class size distribution.