UAV-Based Agricultural Spraying: A Study on Spiral Movements and Pesticide Optimization

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Date

2025

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier B.V.

Abstract

Unmanned aerial vehicles (UAVs) have become an essential component of precision agriculture, providing enhanced accuracy and operational efficiency in pesticide application. This study presents an innovative spraying protocol that integrates spiral flight trajectories with volumetric classification of olive trees, enhancing operational performance while reducing environmental impact. Using high-resolution UAV imagery in conjunction with advanced image processing, trees were categorized into small, medium, and large canopy-volume classes. For each group, optimized spiral patterns with predefined turn counts and flight altitudes were assigned to achieve uniform droplet deposition across complex canopy structures. Field experiments conducted in the Hekimhan district of Malatya, Türkiye, demonstrated an 85 % improvement in spraying efficiency, a 15 % reduction in chemical usage, and a 20 % decrease in operational time compared with conventional methods. The proposed approach significantly improved targeting precision and minimized off-target drift. These results clearly indicate that the proposed protocol is scalable, environmentally sustainable, and operationally efficient for pesticide application in orchards and other tree-based agricultural systems.This approach demonstrates considerable potential for widespread adoption in precision agriculture, offering a replicable and adaptable framework for enhancing the efficiency and sustainability of pesticide application in diverse orchard systems. © 2025 Elsevier B.V., All rights reserved.

Description

Keywords

Agricultural Spraying, Optimization, Precision Agriculture, Spiral Movement, Unmanned Aerial Vehicle (UAV), Antennas, Efficiency, Environmental Impact, Forestry, Image Processing, Orchards, Pesticides, Sustainable Development, Volumetric Analysis, Flight Trajectory, Operational Efficiency

Turkish CoHE Thesis Center URL

WoS Q

Q2

Scopus Q

Q1

Source

Egyptian Journal of Remote Sensing and Space Sciences

Volume

28

Issue

4

Start Page

619

End Page

627
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