Agricultural spray drone deposition, Part 1: methods for high-throughput spray pattern analysis

dc.contributor.authorKoo, Daewonen
dc.contributor.authorHenderson, Caleb A.en
dc.contributor.authorAskew, Shawn D.en
dc.date.accessioned2025-10-16T18:46:29Zen
dc.date.available2025-10-16T18:46:29Zen
dc.date.issued2024-11-01en
dc.description.abstractEffective pesticide application is dependent on precise and sufficient delivery of active ingredients to targeted pests. Water-sensitive papers (WSPs) have been used to estimate the stain coverage, droplet density, droplet size, total spray volume, and other spray-quality metrics by analyzing deposit stains using image analysis software. However, because WSPs are expensive, they are typically distributed along unidimensional transects at intervals of 0.5 m or more, which comprises 0.5% or less of the total treated area. This might limit the ability to accurately represent the deposition of agricultural sprayers with irregular patterns, such as agricultural drone sprayers in the early developmental stage. This study introduces a novel approach utilizing white Kraft paper and a blue colorant proxy for assessing spray deposition. A custom Python-based image analysis tool, SprayDAT (Spray Droplet Analysis Tool), was developed and compared with traditional image analysis software, DepositScan. Both models showed increased accuracy in detecting larger objects, with SprayDAT generally performing better for smaller droplets. DepositScan underestimated the total deposited spray volume by up to 2.7 times less compared with the colorant extraction assessed via spectrophotometry and the predicted output based on flow rate, coverage, and speed. Accuracy of software-estimated spray volume declined with increasing total stain coverage, likely due to overlapping stain objects. Droplet density exhibited a Gaussian trend, with peak density at approximately 22% stain cover, offering evidence for overlapped stains for both DepositScan and SprayDAT as stain cover increased. Both models showed exponential growth in volumetric median diameter (VMD) with increasing stain cover. SprayDAT is freely accessible through an online repository. It features a user-friendly interface for batch processing large sets of scanned images and offers versatility for customization to meet individual needs, such as adjusting spread factor, updating the standard curve for spray volume estimation, or modifying the stain detection threshold.en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1017/wsc.2024.66en
dc.identifier.eissn1550-2759en
dc.identifier.issn0043-1745en
dc.identifier.issue6en
dc.identifier.urihttps://hdl.handle.net/10919/138226en
dc.identifier.volume72en
dc.language.isoenen
dc.publisherCambridge University Pressen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectDeposition analysisen
dc.subjectdroplet sizeen
dc.subjectimage analysisen
dc.subjectSprayDATen
dc.subjectspray pattern analysisen
dc.subjectUAV applicationen
dc.titleAgricultural spray drone deposition, Part 1: methods for high-throughput spray pattern analysisen
dc.title.serialWeed Scienceen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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