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Particle drift potential of glyphosate plus 2,4-D choline pre-mixture formulation in a low-speed wind tunnel

Published online by Cambridge University Press:  03 February 2020

Bruno C. Vieira Open the ORCID record for Bruno C. Vieira [Opens in a new window] ,
Thomas R. Butts Open the ORCID record for Thomas R. Butts [Opens in a new window] ,
Andre O. Rodrigues ,
Jerome J. Schleier III ,
Bradley K. Fritz Open the ORCID record for Bradley K. Fritz [Opens in a new window]  and
Greg R. Kruger Open the ORCID record for Greg R. Kruger [Opens in a new window]
Bruno C. Vieira*
Affiliation:
Graduate Student, West Central Research and Extension Center, University of Nebraska–Lincoln, North Platte, NE, USA
Thomas R. Butts
Affiliation:
Graduate Student, West Central Research and Extension Center, University of Nebraska–Lincoln, North Platte, NE, USA
Andre O. Rodrigues
Affiliation:
Graduate Student, West Central Research and Extension Center, University of Nebraska–Lincoln, North Platte, NE, USA
Jerome J. Schleier III
Affiliation:
Environmental Exposure Assessment, Corteva Agriscience, Indianapolis, IN, USA
Bradley K. Fritz
Affiliation:
Agricultural Engineer, USDA-ARS Aerial Application Technology Research Unit, College Station, TX, USA
Greg R. Kruger
Affiliation:
Associate Professor, West Central Research and Extension Center, University of Nebraska–Lincoln, North Platte, NE, USA
*
Author for correspondence: Bruno C. Vieira, West Central Research and Extension Center, University of Nebraska–Lincoln, 402 W. State Farm Road, North Platte, NE69101. (Email: bruno.vieira@unl.edu)
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Abstract

The introduction of 2,4-D–resistant soybean and cotton provided growers a new POST active ingredient to include in weed management programs. The technology raises concerns regarding potential 2,4-D off-target movement to sensitive vegetation, and spray droplet size is the primary management factor focused on to reduce spray particle drift. The objective of this study was to investigate the droplet size distribution, droplet velocity, and particle drift potential of glyphosate plus 2,4-D choline pre-mixture (Enlist Duo®) applications with two commonly used venturi nozzles in a low-speed wind tunnel. Applications with the TDXL11004 nozzle had larger DV0.1 (291 µm), DV0.5 (544 µm), and DV0.9 (825 µm) values compared with the AIXR11004 nozzle (250, 464, and 709 µm, respectively), and slower average droplet velocity (8.1 m s−1) compared with the AIXR11004 nozzle (9.1 m s−1). Nozzle type had no influence on drift deposition (P = 0.65), drift coverage (P = 0.84), and soybean biomass reduction (P = 0.76). Although the TDXL11004 nozzle had larger spray droplet size, the slower spray droplet velocity could have influenced the nozzle particle drift potential. As a result, both TDXL11004 and AIXR11004 nozzles had similar spray drift potential. Further studies are necessary to understand the impact of droplet velocity on drift potential at field scale and test how different tank solutions, sprayer configurations, and environmental conditions could influence the droplet size and velocity dynamics and consequent drift potential in pesticide applications.

Keywords

2,4-Ddroplet sizedroplet velocityherbicide driftsoybean injury2,4-Dglyphosatesoybean, Glycine max (L.) Merr.cotton, Gossypium hirsutum L.
Type
Research Article
Information
Weed Technology , Volume 34 , Issue 4 , August 2020 , pp. 520 - 527
Copyright
© Weed Science Society of America, 2020

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Footnotes

Associate Editor: Aaron Hager, University of Illinois

References

Al Heidary, M, Douzals, JP, Sinfort, C, Vallet, A (2014) Influence of spray characteristics on potential spray drift of field crop sprayers: a literature review. Crop Prot 63:120–130CrossRefGoogle Scholar
Alves, GS, Kruger, GR, Cunha, JPAR da, Santana, DG de, Pinto, LAT, Guimarães, F, Zaric, M (2017a) Dicamba spray drift as influenced by wind speed and nozzle type. Weed Technol 31:724–731CrossRefGoogle Scholar
Alves, GS, Kruger, GR, Cunha, JPAR da, Vieira, BC, Henry, RS, Obradovic, A, Grujic, M (2017b) Spray drift from dicamba and glyphosate applications in a wind tunnel. Weed Technol 31:387–395CrossRefGoogle Scholar
Antuniassi, UR, Moreira, CAF, Chechetto, RG, Pinheiro, ACTC, Lucio, FR (2016) Droplet spectra and drift potential generated by flat-fan nozzles spraying new formulations of 2,4-D engineered for drift reduction. Pages 1–10in Fritz, BK, Butts, TR, eds. Pesticide Formulation and Delivery Systems. Volume 38, Innovative Application, Formulation, and Adjuvant Technologies. West Conshohocken, PA: ASTM InternationalGoogle Scholar
Baetens, K, Nuyttens, D, Verboven, P, De Schampheleire, M, Nicolaï, B, Ramon, H (2007) Predicting drift from field spraying by means of a 3D computational fluid dynamics model. Comput Electron Agric 56:161–173CrossRefGoogle Scholar
Bagavathiannan, MV, Norsworthy, JK (2016) Multiple-herbicide resistance is widespread in roadside Palmer amaranth populations. PLoS ONE 11:e0148748CrossRefGoogle ScholarPubMed
Bueno, MR, Cunha, JPAR da, de Santana, DG (2017) Assessment of spray drift from pesticide applications in soybean crops. Biosyst Eng 154:35–45CrossRefGoogle Scholar
Butts, TR, Butts, LE, Luck, JD, Fritz, BK, Hoffmann, WC, Kruger, GR (2019) Droplet size and nozzle tip pressure from a pulse-width modulation sprayer. Biosyst Eng 178:52–69CrossRefGoogle Scholar
Butts, TR, Hoffmann, WC, Luck, JD, Kruger, GR (2018a) Droplet velocity from broadcast agricultural nozzles as influenced by pulse-width modulation. Pages 24–52in Fritz, BK, Butts, TR, eds. Pesticide Formulation and Delivery Systems. Volume 38, Innovative Application, Formulation, and Adjuvant Technologies. West Conshohocken, PA: ASTM InternationalGoogle Scholar
Butts, TR, Moraes, JG, Kruger, GR (2018b) Impact of plugged venturi nozzle air-inclusion ports on droplet-size distribution. Pages 76–88in Fritz, BK, Butts, TR, eds. Pesticide Formulation and Delivery Systems. Volume 38, Innovative Application, Formulation, and Adjuvant Technologies. West Conshohocken, PA: ASTM InternationalGoogle Scholar
Butts, TR, Samples, CA, Franca, LX, Dodds, DM, Reynolds, DB, Adams, JW, Zollinger, RK, Howatt, KA, Fritz, BK, Hoffmann, WC, Kruger, GR (2018c) Spray droplet size and carrier volume effect on dicamba and glufosinate efficacy. Pest Manag Sci 74:2020–2029CrossRefGoogle Scholar
Butts, TR, Vieira, BC, Latorre, DO, Werle, R, Kruger, GR (2018d) Competitiveness of herbicide-resistant waterhemp (Amaranthus tuberculatus) with soybean. Weed Sci 66:729–738CrossRefGoogle Scholar
Creech, CF, Henry, RS, Fritz, BK, Kruger, GR (2015) Influence of herbicide active ingredient, nozzle type, orifice size, spray pressure, and carrier volume rate on spray droplet size characteristics. Weed Technol 29:298–310CrossRefGoogle Scholar
De Cock, N, Massinon, M, Salah, SOT, Lebeau, F (2017) Investigation on optimal spray properties for ground based agricultural applications using deposition and retention models. Biosyst Eng 162:99–111CrossRefGoogle Scholar
Dorr, GJ, Hewitt, AJ, Adkins, SW, Hanan, J, Zhang, H, Noller, B (2013) A comparison of initial spray characteristics produced by agricultural nozzles. Crop Prot 53:109–117CrossRefGoogle Scholar
Dorr, GJ, Kempthorne, DM, Mayo, LC, Forster, WA, Zabkiewicz, JA, McCue, SW, Belward, JA, Turner, IW, Hanan, J (2014) Towards a model of spray–canopy interactions: interception, shatter, bounce and retention of droplets on horizontal leaves. Ecol Model 290:94–101CrossRefGoogle Scholar
Egan, JF, Barlow, KM, Mortensen, DA (2014) A meta-analysis on the effects of 2,4-D and dicamba drift on soybean and cotton. Weed Sci 62:193–206CrossRefGoogle Scholar
Ferguson, JC, O’Donnell, CC, Chauhan, BS, Adkins, SW, Kruger, GR, Wang, R, Urach Ferreira, PH, Hewitt, AJ (2015) Determining the uniformity and consistency of droplet size across spray drift reducing nozzles in a wind tunnel. Crop Prot 76:1–6CrossRefGoogle Scholar
Foster, HC, Sperry, BP, Reynolds, DB, Kruger, GR, Claussen, S (2018) Reducing herbicide particle drift: effect of hooded sprayer and spray quality. Weed Technol 32:714–721CrossRefGoogle Scholar
Fritz, BK, Hoffman, WC, Anderson, J (2016) Response surface method for evaluation of the performance of agricultural application spray nozzles. Pages 61–76in Goss, GR, ed. Pesticide Formulation and Delivery Systems. Volume 35, Pesticide Formulations, Adjuvants, and Spray Characterization in 2014. West Conshohocken, PA: ASTM InternationalCrossRefGoogle Scholar
Goering, C, Gebhardt, M, Bode, L (1972) Mathematical modeling of spray droplet deceleration and evaporation. Trans ASAE 15:220–225CrossRefGoogle Scholar
Havens, PL, Hillger, DE, Hewitt, AJ, Kruger, GR, Marchi-Werle, L, Czaczyk, Z (2018) Field measurements of drift of conventional and drift control formulations of 2,4-D plus glyphosate. Weed Technol 32:550–556CrossRefGoogle Scholar
Henry, RS, Kruger, GR, Fritz, BK, Hoffmann, WC, Bagley, WE (2014) Measuring the effect of spray plume angle on the accuracy of droplet size data. Pages 129–138in Sesa, C, ed. Pesticide Formulation and Delivery Systems. Volume 33, Sustainability: Contributions from Formulation Technology. West Conshohocken, PA: ASTM InternationalCrossRefGoogle Scholar
Hewitt, AJ (2000) Spray drift: impact of requirements to protect the environment. Crop Prot 19:623–627CrossRefGoogle Scholar
Hewitt, AJ (2008) Spray optimization through application and liquid physical property variables–I. The Environmentalist 28:25–30CrossRefGoogle Scholar
Hilz, E, Vermeer, AWP (2013) Spray drift review: the extent to which a formulation can contribute to spray drift reduction. Crop Prot 44:75–83CrossRefGoogle Scholar
Hoffman, WC, Fritz, BK, Gizotti-de-Moraes, J, Guerrerio, M, Kruger, GR (2018) Determining water-sensitive card spread factors for real-world tank mixes. Pages 12–21in Edlund, RK, ed. Pesticide Formulation and Delivery Systems. Volume 37, Formulations with Ingredients on the EPA’s List of Minimal Concern. West Conshohocken, PA: ASTM InternationalCrossRefGoogle Scholar
Hoffmann, CW, Fritz, BK, Bagley, WE, Kruger, GR, Henry, RS, Czaczyk, Z (2014a) Effects of nozzle spray angle on droplet size and velocity. Pages 139–150in Sesa, C, ed. Pesticide Formulation and Delivery Systems. Volume 33, Sustainability: Contributions from Formulation Technology. West Conshohocken, PA: ASTM InternationalCrossRefGoogle Scholar
Hoffmann, WC, Fritz, BK, Ledebuhr, MA (2014b) Evaluation of 1, 3, 6, 8-pyrene tetra sulfonic acid tetra sodium salt (PTSA) as an agricultural spray tracer dye. Appl Eng Agric 30:25–28Google Scholar
Johnson, AK, Roeth, FW, Martin, AR, Klein, RN (2006) Glyphosate spray drift management with drift-reducing nozzles and adjuvants. Weed Technol 20:893–897CrossRefGoogle Scholar
Kalsing, A, Rossi, CVS, Lucio, FR, Zobiole, LHS, Cunha, LCV da, Minozzi, GB (2018) Effect of formulations and spray nozzles on 2,4-D spray drift under field conditions. Weed Technol 32:379–384CrossRefGoogle Scholar
Knezevic, SZ, Streibig, JC, Ritz, C (2007) Utilizing R software package for dose-response studies: the concept and data analysis. Weed Technol 21:840–848CrossRefGoogle Scholar
Kruger, GR, Davis, VM, Weller, SC, Johnson, WG (2010) Control of horseweed (Conyza canadensis) with growth regulator herbicides. Weed Technol 24:425–429CrossRefGoogle Scholar
Kruger, GR, Davis, VM, Weller, SC, Stachler, JM, Loux, MM, Johnson, WG (2009) Frequency, distribution, and characterization of horseweed (Conyza canadensis) biotypes with resistance to glyphosate and ALS-inhibiting herbicides. Weed Sci 57:652–659CrossRefGoogle Scholar
Kruger, GR, Johnson, WG, Doohan, DJ, Weller, SC (2012) Dose response of glyphosate and dicamba on tomato (Lycopersicon esculentum) injury. Weed Technol 26:256–260CrossRefGoogle Scholar
Legleiter, TR, Young, BG, Johnson, WG (2018) Glyphosate plus 2,4-D deposition, absorption, and efficacy on glyphosate-resistant weed species as influenced by broadcast spray nozzle. Weed Technol 32:141–149CrossRefGoogle Scholar
Li, M, Tank, H, Kennedy, A, Zhang, H, Downer, B, Ouse, D, Liu, L (2013) Enlist Duo herbicide: a novel 2,4-D plus glyphosate premix formulation with low potential for off-target movement. Pages 3–14in Bernards, ML, ed. Pesticide Formulation and Delivery Systems. Volume 32, Innovating Legacy Products for New Uses. West Conshohocken, PA: ASTM InternationalCrossRefGoogle Scholar
Manuchehri, MR, Dotray, PA, Keeling, JW (2017) EnlistTM weed control systems for Palmer amaranth (Amaranthus palmeri) management in Texas high plains cotton. Weed Technol 31:793–799CrossRefGoogle Scholar
Matthews, G, Bateman, R, Miller, P (2014) Pesticide Application Methods. 4th ed. Hoboken, NJ: Wiley-Blackwell. 536 pCrossRefGoogle Scholar
Murphy, BP, Larran, AS, Ackley, B, Loux, MM, Tranel, PJ (2019) Survey of glyphosate-, atrazine- and lactofen-resistance mechanisms in Ohio waterhemp (Amaranthus tuberculatus) populations. Weed Sci 67:296–302CrossRefGoogle Scholar
Nandula, VK, Tyler, HL (2016) Effect of new auxin herbicide formulations on control of herbicide resistant weeds and on microbial activities in the rhizosphere. Am J Plant Sci 7:2429CrossRefGoogle Scholar
Nordby, A, Skuterud, R (1974) The effects of boom height, working pressure and wind speed on spray drift. Weed Res 14:385–395CrossRefGoogle Scholar
Nuyttens, D, Baetens, K, De Schampheleire, M, Sonck, B (2007) Effect of nozzle type, size and pressure on spray droplet characteristics. Biosyst Eng 97:333–345CrossRefGoogle Scholar
Nuyttens, D, Schampheleire, MD, Verboven, P, Brusselman, E, Dekeyser, D (2009) Droplet size and velocity characteristics of agricultural sprays. Trans ASABE 52:1471–1480CrossRefGoogle Scholar
Oliveira, MC, Pereira, GAM, Ferreira, EA, Santos, JB, Knezevic, SZ, Werle, R (2018) Additive design: the concept and data analysis. Weed Res 58:338–347CrossRefGoogle Scholar
Plewa, D, Bissonnette, S (2016) 2016 University of Illinois Plant Clinic Herbicide Resistance Report. http://bulletin.ipm.illinois.edu/?p=3821. Accessed: April 24, 2018Google Scholar
Regnier, EE, Harrison, SK, Loux, MM, Holloman, C, Venkatesh, R, Diekmann, F, Taylor, R, Ford, RA, Stoltenberg, DE, Hartzler, RG, Davis, AS, Schutte, BJ, Cardina, J, Mahoney, KJ, Johnson, WG (2016) Certified crop advisors’ perceptions of giant ragweed (Ambrosia trifida) distribution, herbicide resistance, and management in the corn belt. Weed Sci 64:361–377CrossRefGoogle Scholar
Reichard, DL, Zhu, H, Fox, RD, Brazee, RD (1992) Computer simulation of variables that influence spray drift. Trans ASAE 35:1401–1407CrossRefGoogle Scholar
Ritz, C, Baty, F, Streibig, JC, Gerhard, D (2015) Dose-response analysis using R. PLoS One 10:e0146021CrossRefGoogle ScholarPubMed
Robinson, AP, Simpson, DM, Johnson, WG (2012) Summer annual weed control with 2,4-D and glyphosate. Weed Technol 26:657–660CrossRefGoogle Scholar
Rodrigues, AO, Campos, LG, Creech, CF, Fritz, BK, Antuniassi, UR, Kruger, GR (2018) Influence of nozzle type, speed, and pressure on droplet size and weed control from glyphosate, dicamba, and glyphosate plus dicamba. Pages 61–75in Fritz, BK, Butts, TR, eds. Pesticide Formulation and Delivery Systems. Volume 38, Innovative Application, Formulation, and Adjuvant Technologies. West Conshohocken, PA: ASTM InternationalGoogle Scholar
Schampheleire, MD, Nuyttens, D, Baetens, K, Cornelis, W, Gabriels, D, Spanoghe, P (2008) Effects on pesticide spray drift of the physicochemical properties of the spray liquid. Precis Agric 10:409–420CrossRefGoogle Scholar
Schultz, JL, Chatham, LA, Riggins, CW, Tranel, PJ, Bradley, KW (2015) Distribution of herbicide resistances and molecular mechanisms conferring resistance in Missouri waterhemp (Amaranthus rudis Sauer) populations. Weed Sci 63:336–345CrossRefGoogle Scholar
Smith, HC, Ferrell, JA, Webster, TM, Fernandez, JV (2017) Cotton response to simulated auxin herbicide drift using standard and ultra-low carrier volumes. Weed Technol 31:1–9Google Scholar
Stroup, WW (2013) Generalized Linear Mixed Models: Modern Concepts, Methods and Applications. Boca Raton, FL: CRC Press. 529 pGoogle Scholar
Teske, ME, Bird, SL, Esterly, DM, Curbishley, TB, Ray, SL, Perry, SG (2002) AgDrift®: a model for estimating near-field spray drift from aerial applications. Environ Toxicol Chem 21:659–671CrossRefGoogle Scholar
Ucar, T, Hall, FR (2001) Windbreaks as a pesticide drift mitigation strategy: a review. Pest Manag Sci 57:663–675CrossRefGoogle ScholarPubMed
Vieira, BC, Butts, TR, Rodrigues, AO, Golus, JA, Schroeder, K, Kruger, GR (2018a) Spray particle drift mitigation using field corn (Zea mays L.) as a drift barrier. Pest Manag Sci 74:2038–2046CrossRefGoogle Scholar
Vieira, BC, Luck, JD, Amundsen, KL, Gaines, TA, Werle, R, Kruger, GR (2019) Response of Amaranthus spp. following exposure to sublethal herbicide rates via spray particle drift. PLoS ONE 14:e0220014CrossRefGoogle ScholarPubMed
Vieira, BC, Samuelson, SL, Alves, GS, Gaines, TA, Werle, R, Kruger, GR (2018b) Distribution of glyphosate-resistant Amaranthus spp. in Nebraska. Pest Manag Sci 74:2316–2324CrossRefGoogle ScholarPubMed
Wolf, RE (2003) Assessing the ability of Dropletscan to analyze spray droplets from a ground operated sprayer. Appl Eng Agric 19Google Scholar
Wright, TR, Shan, G, Walsh, TA, Lira, JM, Cui, C, Song, P, Zhuang, M, Arnold, NL, Lin, G, Yau, K, Russell, SM, Cicchillo, RM, Peterson, MA, Simpson, DM, Zhou, N, Ponsamuel, J, Zhang, Z (2010) Robust crop resistance to broadleaf and grass herbicides provided by aryloxyalkanoate dioxygenase transgenes. Proc Natl Acad Sci USA 107:20240–20245CrossRefGoogle ScholarPubMed
Yates, WE, Cowden, RE, Akesson, NB (1985) Drop size spectra from nozzles in high-speed airstreams. Trans ASAE 28:405–410CrossRefGoogle Scholar
Zhu, H, Reichard, DL, Fox, RD, Brazee, RD, Ozkan, HE (1994) Simulation of drift of discrete sizes of water droplets from field sprayers. Trans ASAE 37:1401–1407CrossRefGoogle Scholar