<i>Assessment of spray deposition and losses in the apple orchard from agricultural unmanned aerial vehicle in China</i>

2018 ◽  
Author(s):  
Longlong Li ◽  
Yajia Liu ◽  
Xiongkui He ◽  
Jianli Song ◽  
Aijun Zeng ◽  
...  
Author(s):  
E. Hadas ◽  
G. Jozkow ◽  
A. Walicka ◽  
A. Borkowski

The estimation of dendrometric parameters has become an important issue for agriculture planning and for the efficient management of orchards. Airborne Laser Scanning (ALS) data is widely used in forestry and many algorithms for automatic estimation of dendrometric parameters of individual forest trees were developed. Unfortunately, due to significant differences between forest and fruit trees, some contradictions exist against adopting the achievements of forestry science to agricultural studies indiscriminately.<br> In this study we present the methodology to identify individual trees in apple orchard and estimate heights of individual trees, using high-density LiDAR data (3200&amp;thinsp;points/m<sup>2</sup>) obtained with Unmanned Aerial Vehicle (UAV) equipped with Velodyne HDL32-E sensor. The processing strategy combines the alpha-shape algorithm, principal component analysis (PCA) and detection of local minima. The alpha-shape algorithm is used to separate tree rows. In order to separate trees in a single row, we detect local minima on the canopy profile and slice polygons from alpha-shape results. We successfully separated 92&amp;thinsp;% of trees in the test area. 6&amp;thinsp;% of trees in orchard were not separated from each other and 2&amp;thinsp;% were sliced into two polygons. The RMSE of tree heights determined from the point clouds compared to field measurements was equal to 0.09&amp;thinsp;m, and the correlation coefficient was equal to 0.96. The results confirm the usefulness of LiDAR data from UAV platform in orchard inventory.


2019 ◽  
Vol 9 (2) ◽  
pp. 218 ◽  
Author(s):  
Guobin Wang ◽  
Yubin Lan ◽  
Huizhu Yuan ◽  
Haixia Qi ◽  
Pengchao Chen ◽  
...  

As a new low volume application technology, unmanned aerial vehicle (UAV) application is developing quickly in China. The aim of this study was to compare the droplet deposition, control efficacy and working efficiency of a six-rotor UAV with a self-propelled boom sprayer and two conventional knapsack sprayers on the wheat crop. The total deposition of UAV and other sprayers were not statistically significant, but significantly lower for run-off. The deposition uniformity and droplets penetrability of the UAV were poor. The deposition variation coefficient of the UAV was 87.2%, which was higher than the boom sprayer of 31.2%. The deposition on the third top leaf was only 50.0% compared to the boom sprayer. The area of coverage of the UAV was 2.2% under the spray volume of 10 L/ha. The control efficacy on wheat aphids of UAV was 70.9%, which was comparable to other sprayers. The working efficiency of UAV was 4.11 ha/h, which was roughly 1.7–20.0 times higher than the three other sprayers. Comparable control efficacy results suggest that UAV application could be a viable strategy to control pests with higher efficiency. Further improvement on deposition uniformity and penetrability are needed.


Author(s):  
Changling Wang ◽  
Herbst Andreas ◽  
Aijun Zeng ◽  
Wongsuk Supakorn ◽  
Baiyu Qiao ◽  
...  

2018 ◽  
Vol 61 (5) ◽  
pp. 1539-1546 ◽  
Author(s):  
Colin R. Brown ◽  
Durham K. Giles

Abstract. Unmanned aerial vehicles (UAVs) are now being used to perform commercial pesticide applications in California, but little information is available regarding the amount of pesticide drift resulting from these applications. The physical dimensions and operating speed of UAVs differ substantially from those of manned aircraft and fall outside the validated range of spray dispersion models. This study measured spray drift from a 0.84 ha aerial pesticide application of imidacloprid performed with a Yamaha R-Max II UAV over a Napa Valley vineyard. Downwind deposition samples, in-swath deposition samples, and downwind air samples were collected up to 48 m downwind of the application field. In-swath deposition samples measured approximately 57% of the target rate, while downwind drift deposition decreased from approximately 0.4% at 7.5 m downwind to 0.03% at 48 m downwind. All air samples were below the method detection limit. A drift deposition curve fitted to measured ground deposition using a log-log second-degree polynomial function yielded an R2 value of 0.985. An estimated 0.28% to 0.54% of applied material was lost as drift out to 50 m downwind of the field edge based on ground deposition measurements, 82% of which deposited within the first 7.5 m downwind. Uncertainty in mass accountancy and deposition measurements is discussed, with sources of error including obstructions in the downwind measurement area, low collection efficiency of the sampling media, a high coefficient of variation of spray deposition in the treatment field, and possible photodegradation of the tracer material. Keywords: Aerial application, AGDISP, Pesticide deposition, Pesticide drift, Remotely piloted aircraft, UAV, Unmanned aerial vehicle, Vineyard.


2020 ◽  
Vol 20 (4) ◽  
pp. 332-342
Author(s):  
Hyung Jun Park ◽  
Seong Hee Cho ◽  
Kyung-Hwan Jang ◽  
Jin-Woon Seol ◽  
Byung-Gi Kwon ◽  
...  

2018 ◽  
pp. 7-13
Author(s):  
Anton M. Mishchenko ◽  
Sergei S. Rachkovsky ◽  
Vladimir A. Smolin ◽  
Igor V . Yakimenko

Results of experimental studying radiation spatial structure of atmosphere background nonuniformities and of an unmanned aerial vehicle being the detection object are presented. The question on a possibility of its detection using optoelectronic systems against the background of a cloudy field in the near IR wavelength range is also considered.


Author(s):  
Amir Birjandi ◽  
◽  
Valentin Guerry ◽  
Eric Bibeau ◽  
Hamidreza Bolandhemmat ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document