ArticleScientific reports2025
Performance evaluation of spraying drones compared to boom sprayers for spray applications.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Intelligent Perception, Decision-Making and Actuation Technologies for Precision Agrochemical Spraying: Current Advances and Future Perspectives.Sensors (Basel, Switzerland) · 2026Review
- The effect of rotor airflow from plant protection UAV on pesticide application in rice.Scientific reports · 2026Article
- Plant spraying quality when used by drone-robots.Scientific reports · 2026Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spraying drones represent a recent advancement in agricultural mechanization, particularly in the domain of pesticide application. Their adoption has steadily increased due to their operational flexibility and their potential to address labor shortages and limited field accessibility. This study evaluates and compares the technical performance of spraying drones and conventional boom sprayers under varying operational conditions. A comprehensive performance assessment of both systems is crucial for informed decision-making regarding their application, development, and investment potential. Field experiments were conducted at three forward speeds (low, medium, and high) for both sprayer types. Drone speeds were 21.6, 26.2, and 27.0 km·h⁻¹, while boom sprayer speeds were 4.39, 6.00, and 8.57 km·h⁻¹. Spray deposition and drift were assessed using a water-tartrazine dye solution, quantified via spectrophotometry. Droplet size and spray quality were evaluated using water-sensitive paper and image analysis. Key performance indicators included spray deposition, spray drift, the Coefficient of Variation (CV) of spray distribution, Volume Median Diameter (VMD), Number Median Diameter (NMD), and spray quality index (QI). The lowest deposition rate (2.67%) occurred at the highest drone speed, while the highest deposition (3.85%) was observed for the boom sprayer at its lowest speed. Significant differences were observed across all performance parameters depending on sprayer type and speed. Notably, VMD and QI differed significantly at p < 0.01, while NMD differed at p < 0.05. Among all treatments, drones achieved a superior QI of 1.27 compared to 3.07 for boom sprayers. Overall, spraying drones demonstrated favorable performance in terms of droplet uniformity and spray quality. These findings highlight their potential as an effective and innovative solution in modern agricultural practices. Nevertheless, their lower deposition rates and higher drift levels at greater speeds remain important technical challenges to be addressed.
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