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Optimization of spray operation parameters of unmanned aerial vehicle confers adequate levels of control of fall armyworm (). | LitMetric

Optimization of spray operation parameters of unmanned aerial vehicle confers adequate levels of control of fall armyworm ().

Front Plant Sci

Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences/Key Laboratory of Integrated Pest Management on Tropical Crops, Ministry of Agriculture and Rural Affairs, Haikou, China.

Published: May 2025


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Article Abstract

Introduction: The fall armyworm (FAW), , is a serious threat to maize production. Unmanned aerial vehicles (UAVs) represent a promising method for controlling FAW outbreaks. Given that FAW larvae primarily feed inside the maize whorl, we hypothesized that the efficacy of insecticide application depends on droplet density and coverage rate on the upper maize canopy.

Methods: This study evaluated the effects of spray operation parameters-including three flight heights (2.0, 2.5, and 3.0 m), three spray volumes (30.0, 37.5, and 45.0 L ha), and two nozzle types (XR11001VS and XR110015VS)-on droplet deposition distribution in maize canopies. Additionally, the control efficacy of 35% chlorantraniliprole water dispersible granules (WDG) against FAW was assessed over three consecutive years (2019-2021) to determine its correlation with droplet deposition.

Results: Results indicated that flight height, spray volume, and nozzle type significantly influenced droplet deposition distribution. Two treatments-XR110015VS nozzle with 37.5 L ha spray volume at 2.5 m flight height and XR110015VS nozzle with 45.0 L ha spray volume at 2.5 m flight height-achieved the highest droplet density, optimal coverage rate on the upper maize canopy, and the lowest damage index, confirming our hypothesis. These treatments also demonstrated comparable FAW control efficacy to traditional electric air-pressure knapsack sprayers.

Discussion: The findings provide practical insights for optimizing UAV-based insecticide applications to improve FAW management in maize production systems.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12095212PMC
http://dx.doi.org/10.3389/fpls.2025.1581367DOI Listing

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