Large-scale evaluation of 2,4-D choline off-target movement and injury in 2,4-D-susceptible soybean

Abstract Enlist E3™ soybean cultivars permit over-the-top application of labeled glyphosate, glufosinate, and 2,4-D choline products. Increased Enlist E3™ trait adoption and use of 2,4-D choline postemergence across U.S. soybean production systems raise concerns regarding potential for 2,4-D off-target movement (OTM). A large-scale drift experiment was established near Sun Prairie, WI, and Arlington, WI, in 2019 and 2020, respectively. A 2,4-D-resistant soybean cultivar was planted in the center of the field (∼3 ha), while the surrounding area was planted with a 2,4-D-susceptible cultivar. An application of 785 ae ha–1 2,4-D choline plus 834 g ae ha–1 glyphosate was completed within the center block at R2 and V6 growth stages on August 1, 2019, and July 3, 2020, respectively. Filter papers were placed in-swath and outside of the treated area in one upwind transect and three downwind transects to estimate particle deposition. Low-volume air samplers ran for the 0.5-h to 48-h period following application to estimate 2,4-D air concentration. Injury to 2,4-D-susceptible soybean was assessed 21 d after treatment (0% to 100% injury). The 2,4-D deposition in-swath was 9,966 and 5,727 ng cm–2 in 2019 and 2020, respectively. Three-parameter log-logistic models estimated the distance to 90% reduction in 2,4-D deposition (D90) to be 0.63 m and 0.90 m in 2019 and 2020, respectively. In 2020, the 2,4-D air concentration detected was lower for the upwind (0.395 ng m–3) than the downwind direction (1.34 ng m–3), although both were lower than the amount detected in-swath (4.01 ng m–3). No soybean injury was observed in the downwind or upwind directions. Our results suggest that 2,4-D choline applications following label recommendations pose little risk to 2,4-D-susceptible soybean cultivars; however, further work is needed to understand 2,4-D choline OTM under different environmental conditions and the presence of other susceptible crops. Nomenclature: 2,4-D; 2; 4-Dicholorophenoxyacetic-acid; soybean; Glycine max (L.) Merr

[1]  T. C. Mueller,et al.  Dicamba emissions under field conditions as affected by surface condition , 2020, Weed Technology.

[2]  D. Stoltenberg,et al.  Spray solution pH and soybean injury as influenced by synthetic auxin formulation and spray additives , 2020, Weed Technology.

[3]  P. Chahal,et al.  Management of glyphosate-resistant Palmer amaranth (Amaranthus palmeri) in 2,4-D–, glufosinate-, and glyphosate-resistant soybean , 2020, Weed Technology.

[4]  Bruno C. Vieira,et al.  Particle drift potential of glyphosate plus 2,4-D choline pre-mixture formulation in a low-speed wind tunnel , 2020, Weed Technology.

[5]  P. Sikkema,et al.  Off-target movement assessment of dicamba in North America , 2020, Weed Technology.

[6]  Mandy D. Bish,et al.  Dicamba Losses to Air after Applications to Soybean under Stable and Nonstable Atmospheric Conditions , 2019, Journal of Environmental Quality.

[7]  V. Nandula Herbicide Resistance Traits in Maize and Soybean: Current Status and Future Outlook , 2019, Plants.

[8]  Mandy D. Bish,et al.  Inversion Climatology in High-Production Agricultural Regions of Missouri and Implications for Pesticide Applications , 2019, Journal of Applied Meteorology and Climatology.

[9]  J. Norsworthy,et al.  Off-Target Movement of Diglycolamine Dicamba to Non-dicamba Soybean Using Practices to Minimize Primary Drift , 2019, Weed Technology.

[10]  R. H. Grant,et al.  Surface Temperature Inversions and Risk of Off-Target Herbicide Damage in the Soybean- and Cotton-Growing Regions of the US , 2019, Crop, Forage & Turfgrass Management.

[11]  G. Kruger,et al.  Field Measurements of Drift of Conventional and Drift Control Formulations of 2,4-D Plus Glyphosate , 2018, Weed Technology.

[12]  L. Zobiole,et al.  Effect of Formulations and Spray Nozzles on 2,4-D Spray Drift under Field Conditions , 2018, Weed Technology.

[13]  Qing X. Li,et al.  Potential impact of the herbicide 2,4-dichlorophenoxyacetic acid on human and ecosystems. , 2017, Environment international.

[14]  W. G. Johnson,et al.  Glyphosate Plus 2,4-D Deposition, Absorption, and Efficacy on Glyphosate-Resistant Weed Species as Influenced by Broadcast Spray Nozzle , 2017, Weed Technology.

[15]  J. Keeling,et al.  Enlist™ Weed Control Systems for Palmer Amaranth (Amaranthus palmeri) Management in Texas High Plains Cotton , 2017, Weed Technology.

[16]  P. Sikkema,et al.  Response of glyphosate-resistant soybean to dicamba spray tank contamination during vegetative and reproductive growth stages. , 2016, Canadian Journal of Plant Science.

[17]  J. Ferrell,et al.  Effect of Glyphosate and Dicamba Drift Timing and Rates in Bell Pepper and Yellow Squash , 2016, Weed Technology.

[18]  D. Doohan,et al.  Response of Wine Grape Cultivars to Simulated Drift Rates of 2,4-D, Dicamba, and Glyphosate, and 2,4-D or Dicamba Plus Glyphosate , 2016, Weed Technology.

[19]  Florent Baty,et al.  Dose-Response Analysis Using R , 2015, PLoS ONE.

[20]  A. Culpepper,et al.  Evaluating the Volatility of Three Formulations of 2,4-D When Applied in the Field , 2015, Weed Technology.

[21]  R. S. Henry,et al.  Influence of Herbicide Active Ingredient, Nozzle Type, Orifice Size, Spray Pressure, and Carrier Volume Rate on Spray Droplet Size Characteristics , 2015, Weed Technology.

[22]  K. Bradley,et al.  Influence of Application Timings and Sublethal Rates of Synthetic Auxin Herbicides on Soybean , 2014, Weed Technology.

[23]  D. Mortensen,et al.  A Meta-Analysis on the Effects of 2,4-D and Dicamba Drift on Soybean and Cotton , 2014, Weed Science.

[24]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[25]  Jim Hanan,et al.  A comparison of initial spray characteristics produced by agricultural nozzles , 2013 .

[26]  K. M. Remund,et al.  Effect of Formulation and Application Time of Day on Detecting Dicamba in the Air under Field Conditions , 2013, Weed Science.

[27]  W. G. Johnson,et al.  Response of Soybean Yield Components to 2,4-D , 2013, Weed Science.

[28]  A. M. Stewart,et al.  Cotton, Peanut, and Soybean Response to Sublethal Rates of Dicamba, Glufosinate, and 2,4-D , 2012, Weed Technology.

[29]  Sanford Weisberg,et al.  An R Companion to Applied Regression , 2010 .

[30]  R. M. Cicchillo,et al.  Robust crop resistance to broadleaf and grass herbicides provided by aryloxyalkanoate dioxygenase transgenes , 2010, Proceedings of the National Academy of Sciences.

[31]  P. Westra,et al.  Vapor Movement of Synthetic Auxin Herbicides: Aminocyclopyrachlor, Aminocyclopyrachlor-Methyl Ester, Dicamba, and Aminopyralid , 2010, Weed Science.

[32]  H. Lischka,et al.  Interaction of the 2,4‐dichlorophenoxyacetic acid herbicide with soil organic matter moieties: a theoretical study , 2007 .

[33]  N. H. Spliid,et al.  Drift of 10 herbicides after tractor spray application. 2. Primary drift (droplet drift). , 2006, Chemosphere.

[34]  R. Behrens,et al.  Dicamba Volatility , 1979, Weed Science.