Measuring spray droplet size under unmanned aerial spraying system (UASS) downwash airflow using an...

Area of Science:

• Agricultural Engineering
• Precision Agriculture
• Spray Technology

Background:

• Accurate spray droplet size distribution is crucial for optimizing pesticide application via unmanned aerial spraying systems (UASSs).
• Conventional methods like water-sensitive paper (WSP) and photographic paper (PP) suffer from inaccuracies due to droplet spread and coalescence.
• In-flight laser diffraction is impractical for field measurements under turbulent downwash conditions.

Purpose of the Study:

• To develop and validate an image-processing-based liquid immersion method for characterizing UASS spray droplet size distribution.
• To compare the performance of the silicone oil (SO) method against WSP and PP.
• To validate the SO method against a laboratory-standard laser diffraction instrument.

Main Methods:

• A custom test apparatus was designed to collect droplets from a UASS using silicone oil as the collection medium.
• High-resolution images of collected droplets were analyzed to determine droplet size distributions.
• The SO method's results were compared with WSP, PP, and laser diffraction measurements.

Main Results:

• Silicone oil (SO)-based Dv50 estimates showed strong correlation with laser diffraction and lower variability than WSP and PP.
• Droplet-size uniformity was higher for SO (CV 10-12%) compared to WSP (16-22%) and PP (22-32%).
• The SO method provided more consistent estimates in high-deposition areas where paper-based methods showed inflated sizes.

Conclusions:

• The proposed SO liquid-immersion workflow is a practical, cost-effective, and field-deployable method for UASS spray quality assessment.
• This method supports evidence-based optimization of nozzle settings and flight parameters for improved targeting.
• The SO method aids in mitigating off-target pesticide drift, enhancing application performance.