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Spray drift evaluation with point clouds data of 3D LiDAR as a potential alternative to the sampling method

Spray drift is an inescapable consequence of agricultural plant protection operation, which has always been one of the major concerns in the spray application industry. Spray drift evaluation is essential to provide a basis for the rational selection of spray technique and working surroundings. Nowa...

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Autores principales: Li, Longlong, Zhang, Ruirui, Chen, Liping, Liu, Boqin, Zhang, Linhuan, Tang, Qing, Ding, Chenchen, Zhang, Zhen, Hewitt, Andrew J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9340218/
https://www.ncbi.nlm.nih.gov/pubmed/35923876
http://dx.doi.org/10.3389/fpls.2022.939733
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author Li, Longlong
Zhang, Ruirui
Chen, Liping
Liu, Boqin
Zhang, Linhuan
Tang, Qing
Ding, Chenchen
Zhang, Zhen
Hewitt, Andrew J.
author_facet Li, Longlong
Zhang, Ruirui
Chen, Liping
Liu, Boqin
Zhang, Linhuan
Tang, Qing
Ding, Chenchen
Zhang, Zhen
Hewitt, Andrew J.
author_sort Li, Longlong
collection PubMed
description Spray drift is an inescapable consequence of agricultural plant protection operation, which has always been one of the major concerns in the spray application industry. Spray drift evaluation is essential to provide a basis for the rational selection of spray technique and working surroundings. Nowadays, conventional sampling methods with passive collectors used in drift evaluation are complex, time-consuming, and labor-intensive. The aim of this paper is to present a method to evaluate spray drift based on 3D LiDAR sensor and to test the feasibility of alternatives to passive collectors. Firstly, a drift measurement algorithm was established based on point clouds data of 3D LiDAR. Wind tunnel tests included three types of agricultural nozzles, three pressure settings, and five wind speed settings were conducted. LiDAR sensor and passive collectors (polyethylene lines) were placed downwind from the nozzle to measure drift droplets in a vertical plane. Drift deposition volume on each line and the number of LiDAR droplet points in the corresponding height of the collecting line were calculated, and the influencing factors of this new method were analyzed. The results show that 3D LiDAR measurements provide a rich spatial information, such as the height and width of the drift droplet distribution, etc. High coefficients of determination (R(2) > 0.75) were observed for drift points measured by 3D LiDAR compared to the deposition volume captured by passive collectors, and the anti-drift IDK12002 nozzle at 0.2 MPa spray pressure has the largest R(2) value, which is 0.9583. Drift assessment with 3D LiDAR is sensitive to droplet density or drift mass in space and nozzle initial droplet spectrum; in general, larger droplet density or drift mass and smaller droplet size are not conducive to LiDAR detection, while the appropriate threshold range still needs further study. This study demonstrates that 3D LiDAR has the potential to be used as an alternative tool for rapid assessment of spray drift.
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spelling pubmed-93402182022-08-02 Spray drift evaluation with point clouds data of 3D LiDAR as a potential alternative to the sampling method Li, Longlong Zhang, Ruirui Chen, Liping Liu, Boqin Zhang, Linhuan Tang, Qing Ding, Chenchen Zhang, Zhen Hewitt, Andrew J. Front Plant Sci Plant Science Spray drift is an inescapable consequence of agricultural plant protection operation, which has always been one of the major concerns in the spray application industry. Spray drift evaluation is essential to provide a basis for the rational selection of spray technique and working surroundings. Nowadays, conventional sampling methods with passive collectors used in drift evaluation are complex, time-consuming, and labor-intensive. The aim of this paper is to present a method to evaluate spray drift based on 3D LiDAR sensor and to test the feasibility of alternatives to passive collectors. Firstly, a drift measurement algorithm was established based on point clouds data of 3D LiDAR. Wind tunnel tests included three types of agricultural nozzles, three pressure settings, and five wind speed settings were conducted. LiDAR sensor and passive collectors (polyethylene lines) were placed downwind from the nozzle to measure drift droplets in a vertical plane. Drift deposition volume on each line and the number of LiDAR droplet points in the corresponding height of the collecting line were calculated, and the influencing factors of this new method were analyzed. The results show that 3D LiDAR measurements provide a rich spatial information, such as the height and width of the drift droplet distribution, etc. High coefficients of determination (R(2) > 0.75) were observed for drift points measured by 3D LiDAR compared to the deposition volume captured by passive collectors, and the anti-drift IDK12002 nozzle at 0.2 MPa spray pressure has the largest R(2) value, which is 0.9583. Drift assessment with 3D LiDAR is sensitive to droplet density or drift mass in space and nozzle initial droplet spectrum; in general, larger droplet density or drift mass and smaller droplet size are not conducive to LiDAR detection, while the appropriate threshold range still needs further study. This study demonstrates that 3D LiDAR has the potential to be used as an alternative tool for rapid assessment of spray drift. Frontiers Media S.A. 2022-07-18 /pmc/articles/PMC9340218/ /pubmed/35923876 http://dx.doi.org/10.3389/fpls.2022.939733 Text en Copyright © 2022 Li, Zhang, Chen, Liu, Zhang, Tang, Ding, Zhang and Hewitt. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Li, Longlong
Zhang, Ruirui
Chen, Liping
Liu, Boqin
Zhang, Linhuan
Tang, Qing
Ding, Chenchen
Zhang, Zhen
Hewitt, Andrew J.
Spray drift evaluation with point clouds data of 3D LiDAR as a potential alternative to the sampling method
title Spray drift evaluation with point clouds data of 3D LiDAR as a potential alternative to the sampling method
title_full Spray drift evaluation with point clouds data of 3D LiDAR as a potential alternative to the sampling method
title_fullStr Spray drift evaluation with point clouds data of 3D LiDAR as a potential alternative to the sampling method
title_full_unstemmed Spray drift evaluation with point clouds data of 3D LiDAR as a potential alternative to the sampling method
title_short Spray drift evaluation with point clouds data of 3D LiDAR as a potential alternative to the sampling method
title_sort spray drift evaluation with point clouds data of 3d lidar as a potential alternative to the sampling method
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9340218/
https://www.ncbi.nlm.nih.gov/pubmed/35923876
http://dx.doi.org/10.3389/fpls.2022.939733
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