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ARS Home » Southeast Area » Mississippi State, Mississippi » Crop Science Research Laboratory » Genetics and Sustainable Agriculture Research » Research » Publications at this Location » Publication #399543
Research Project: Closing the Yield Gap of Cotton, Corn, and Soybean in the Humid Southeast with More Sustainable Cropping Systems

Location: Genetics and Sustainable Agriculture Research

Title: Comparison of weather acquisition periods influencing a statistical model of aerial pesticide drift

Author
item THOMSON, STEVEN - National Institute Of Food And Agriculture (NIFA)
item Huang, Yanbo

Submitted to: Agronomy
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/7/2023
Publication Date: 1/10/2023
Citation: Thomson, S.J., Huang, Y. 2023. Comparison of weather acquisition periods influencing a statistical model of aerial pesticide drift. Agronomy. 13(213):1-11. https://doi.org/10.3390/agronomy13010213.
DOI: https://doi.org/10.3390/agronomy13010213

Interpretive Summary: Aerial pesticide spray application has been facing the challenge of off-target drift to cause economic loss and environmental damage. The scientists of USDA NIFA and USDA ARS collaboratively investigated and compared weather acquisition periods that have influences on a statistical analytical model of the spray drift caused during plant protection operation. The results indicated the weather factorial influence on the model which is useful for parameter specification in practical aerial spray application. This study could provide a guideline for general agricultural aviation analysis and UAV spray application studies.

Technical Abstract: Off-target drift of crop protection materials from aerial spraying can be detrimental to sensitive crops, beneficial insects, and the environment. So, it is very important to accurately characterize weather effects for accurate recommendations on drift mitigation. Wind is the single-most important weather factor influencing localized off-target drift of crop protection materials. In drift sampling experiments, it is difficult to accurately characterize wind speed and direction at a drift sampling location, owing to the natural variability of spray movement on the way to the sampling target. Although it is difficult or impossible to exactly track wind movement to a target, much information can be gained by altering the way wind speed and tracking is characterized from field experiments and analyzed using statistical models of spray drift. In this study two methods of characterizing weather were compared to see how they affect results from a statistical model of downwind spray drift using field data. Use of a method that implemented weather averages over the length of a spray run resulted in model-based estimates for spray tracer concentration that compared well with field data averages. Model results using this method showed only a slight sensitivity to changes in wind speed, and this difference was more pronounced further downwind. The degree of this effect was consistent with field results. Another method that used single weather values obtained at the beginning of each run resulted in an unexpected inverse relationship of residue concentration with respect to increases in wind speed by sensitivity analysis and would thus not be recommended for use in a statistical model of downwind spray drift. This study could provide a guideline for general agricultural aviation analysis and UAV spray application studies.