Monitoring of the Pesticide Droplet Deposition with a Novel Capacitance Sensor

Wang, Pei; Yu, Wei; Ou, Mingxiong; Gong, Chang‐De; Jia, Weidong

doi:10.3390/s19030537

Cited by 22 publications

(16 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, there are relatively few devices that enable real-time monitoring in conjunction with sensor network technology. Although literature on wind speed measuring equipment, methods, and online rapid detection [23] exists, the detection of the downwash airflow field under UAV has not fully been elucidated.…”

Section: Introductionmentioning

confidence: 99%

Design of UAV Downwash Airflow Field Detection System Based on Strain Effect Principle

Zhang

et al. 2019

Sensors

Self Cite

View full text Add to dashboard Cite

Accurate measurement of the downwash flow field of plant protection unmanned aerial vehicles (UAVs) is essential for analyzing the spatial distribution of droplets. To realize on-line rapid detection of the downwash flow field of a multi-rotor UAV, a flexible polypropylene detection device based on the principle of full bridge strain effect was proposed. Its performance principle was based on the physical deformation caused by wind pressure. The Fluid Flow and Static Structural modules of ANSYS 16.0 finite element software were used to simulate one-way fluid-solid coupling interaction. The surface of the resistive strain gauge embedded in the flexible detecting structure responded well to wind speed variation, hence it was suitable for downwash airflow wind field detection. By solving the strain force on the surface of the flexible detection structure, the length and layout of the grating wire of the strain gauge on the surface of the flexible detection structure were optimized. Meanwhile at 4 m·s−1 wind speed, the output voltage at varied bridge flexible acquisition systems in the acquisition card was measured. Results indicated coefficient of variation of 3.67%, 1.63% and 1.5%, respectively, which proved the good data acquisition consistency of the system. Through calibration test, the regression equation for the relationship between output voltage and wind speed for three unique sensor signal measuring circuits was established. The determination coefficients R2 for single bridge, half bridge and full bridge circuits were 0.9885, 0.9866 and 0.9959, respectively. In conclusion, by applying the multi-rotor plant protection UAV test platform, the results indicated the maximum relative error of the wind speed at each sampling point of the system at 1.0 m altitude was below 5.61%. Simulated and measured value had an RMSE maximum error of 0.1246 m·s−1. Moreover, downwash airflow detection not only has high accuracy but also has high sensitivity. Thus, there is convenience and practicability in the plant protection offered by this approach. The rapid measurement of UAV wind field and the established two-dimensional wind field model can provide a basis for precise application of agricultural aviation.

show abstract

Section: Introductionmentioning

confidence: 99%

Design of UAV Downwash Airflow Field Detection System Based on Strain Effect Principle

Zhang

et al. 2019

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…Therefore, many strategies, mainly different application techniques, have been developed to improve the amount of pesticide deposited on the target plant . To evaluate spraying efficiency, it is imperative that a facile methodology is developed to assess the performance of different spraying techniques in terms of distribution and the amount of product deposited on target crops …”

Section: Introductionmentioning

confidence: 99%

“…2,3 To evaluate spraying efficiency, it is imperative that a facile methodology is developed to assess the performance of different spraying techniques in terms of distribution and the amount of product deposited on target crops. [4][5][6] When assessing spray deposition, if pesticides themselves are used in each application scenario, different analytical methods are needed to determine the pesticide deposited on the target crops due to the different physicochemical properties of each pesticide. This is time and cost prohibitive.…”

Section: Introductionmentioning

confidence: 99%

Water‐soluble food dye of Allura Red as a tracer to determine the spray deposition of pesticide on target crops

Gao

Wang

Zhou

et al. 2019

Pest Management Science

View full text Add to dashboard Cite

BACKGROUND Quantification of spray deposition on a target crop is of vital importance to optimize pesticide application. In traditional determinations of spray deposition, a large amount of organic solvent is used to extract pesticides from the target crops. In this study, a water‐soluble food dye of Allura Red was developed as a tracer to determine pesticide spray deposition on a rice target crop. RESULTS The addition of Allura Red does not obviously alter the physicochemical properties of pesticides (viscosity, density and surface tension) and droplet spectra. An ultra‐performance liquid chromatography (UPLC) analytical method was developed and validated to determine the deposition amount of Allura Red on rice plants. Method accuracy and precision for Allura Red were found to be satisfactory with recoveries of 96.07% to 107.48%. To validate the method, comparative deposition analyses were carried out using representative systematic and non‐systematic pesticides (nitenpyram and chlorothalonil) under the same spraying scenarios using a Potter spray tower. Allura Red and pesticides showed comparable deposition under the same application conditions with ratios from 0.98 to 1.21. A field trial using an unmanned aerial vehicle sprayer further indicated that the deposition rates for Allura Red and nitenpyram on rice seedling were 13.04% and 11.07%, with corresponding relative standard deviation values (n = 5) of 16.39% and 18.79%. CONCLUSION A laboratory test and field trial confirmed that the developed method of using Allura Red as a tracer for spray deposition assessment is feasible and practicable. © 2019 Society of Chemical Industry

show abstract

“…A total of 13 papers were published in this Special Issue entitled: "Emerging Sensor Technology in Agriculture", and the topics addressed include different emerging technologies with applications on ecosystems (grasslands) [1] and several agriculture crops such as peppers [2], apples [2,3], grapevines [2,[4][5][6][7], cocoa trees [6], citrus [8], legumes [9], wheat and rice [10,11]. Two papers were also related to the use of remote sensing to detect forage quality [9], regions of interest of pigs [12], and pesticide droplet deposition [13] using machine learning.…”

mentioning

confidence: 99%

“…Other management practices such as pesticide application require accurate monitoring methods to assess efficiency in the distribution of droplets within crop canopies to minimize detrimental effects in the environment and maximize application efficiency. A rapid method to detect spraying deposit was developed based on capacitance sensors [13].…”

mentioning

confidence: 99%