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Quantifying Dicamba Volatility under Field Conditions: Part I, Methodology
Author(s) -
Leah S. Riter,
Erik D. Sall,
Naresh Pai,
Collin E. Beachum,
Thomas B. Orr
Publication year - 2020
Publication title -
journal of agricultural and food chemistry
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.203
H-Index - 297
eISSN - 1520-5118
pISSN - 0021-8561
DOI - 10.1021/acs.jafc.9b06451
Subject(s) - dicamba , volatility (finance) , environmental science , sampling (signal processing) , flux (metallurgy) , chemistry , environmental chemistry , biochemical engineering , computer science , engineering , mathematics , econometrics , biology , filter (signal processing) , weed control , computer vision , agronomy , organic chemistry
Quantitative assessment of the volatility of field applied herbicides requires orchestrated sampling logistics, robust analytical methods, and sophisticated modeling techniques. This manuscript describes a comprehensive system developed to measure dicamba volatility in an agricultural setting. Details about study design, sample collection, analytical chemistry, and flux modeling are described. A key component of the system is the interlaboratory validation of an analytical method for trace level detection (limit of quantitation of 1.0 ng/PUF) of dicamba in polyurethane foam (PUF) air samplers. Validation of field sampling and flux methodologies was conducted in a field trial that demonstrated agreement between predicted and directly measured dicamba air concentrations at a series of off-target locations. This validated system was applied to a field case study on two plots to demonstrate the utility of these methods under typical agricultural conditions. This case study resulted in a time-varying volatile flux profile, which showed that less than 0.2 ± 0.05% of the applied dicamba was volatilized over the 3-day sampling period.

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