The Use of Unmanned Aerial Vehicles (UAVs) for Precision Weed Management in Agriculture: a Comprehensive Overview

Authors

  • Michal Kupec Slovak University of Agriculture, Faculty of Agrobiology and Food Resources, Institute of Crop Production, Slovakia
  • Štefan Týr Slovak University of Agriculture, Faculty of Agrobiology and Food Resources, Institute of Crop Production, Slovakia https://orcid.org/0000-0001-7795-7538

Keywords:

drones, weed infestation, modern agriculture, herbicide application, spot spraying

Abstract

Weed infestation remains a major challenge in modern agriculture, leading to reduced crop yields, increased production costs, and environmental impacts due to excessive herbicide use. Recent advances in unmanned aerial vehicles (UAVs) or drones have enabled site-specific weed control that minimizes chemical inputs while optimizing crop protection. This study summarizes the current state of UAV applications in weed detection, mapping, and targeted herbicide application, with an emphasis on the latest studies from 2020–2025. Various imaging sensors, including RGB, multispectral, and hyperspectral cameras, are discussed in terms of their accuracy, resolution, and operational limitations. Machine learning and deep learning algorithms, particularly convolutional neural networks (CNN) and YOLO models, are increasingly being used for automated weed classification and prescription map generation. Spot spraying using UAVs has shown the potential to reduce herbicide use by 30–50%, improve environmental sustainability, and reduce operating costs. Challenges such as flight stability, battery life, regulatory constraints, and field heterogeneity are also addressed. Finally, the review highlights future directions, including full automation of UAV missions, integration with robotic systems, real-time decision-making using artificial intelligence, and improved multisensory approaches. This synthesis provides a comprehensive reference for researchers, agronomists, and technology developers aiming to advance precision weed management and sustainable agriculture.

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Published

2026-07-01

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Section

Plant Science