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Impact of Exposure to 2,4-D and Dicamba on Peanut Injury and Yield

Published online by Cambridge University Press:  20 January 2017

Ramon G. Leon ,
Jason A. Ferrell  and
Barry J. Brecke
Ramon G. Leon*
Affiliation:
West Florida Research and Education Center, University of Florida, Jay, FL 32565
Jason A. Ferrell
Affiliation:
Agronomy Department, University of Florida, Gainesville, FL 32611
Barry J. Brecke
Affiliation:
West Florida Research and Education Center, University of Florida, Jay, FL 32565
*
Corresponding author's E-mail: [email protected].
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Abstract

The potential widespread adoption of cotton and soybean varieties with 2,4-D and dicamba resistance traits in the southeastern US will increase the risk of accidental exposure of peanut to these herbicides because of drift or application errors. When such accidents occur, growers must decide between continuing the crop and terminating it. In order to make this decision, growers need to estimate the potential yield reduction caused by 2,4-D or dicamba. Dose-response studies were conducted under field conditions in Citra and Jay, FL in 2012 and 2013 to determine peanut injury and yield reduction after exposure to 70, 140, 280, 560, and 1120 g ae ha−1 of 2,4-D or to 35, 70, 140, 280, and 560 g ae ha−1 of dicamba at 21 and 42 d after planting (DAP). Only herbicide by rate interactions were significant (P < 0.04). Dicamba caused 2 to 5 times higher peanut injury and 0.5 to 2 times higher yield reductions than 2,4-D. Injury ranged from 0 to 35% when peanut plants were treated with 2,4-D and from 20 to 78% with dicamba. The maximum yield reduction was 41% with 1,120 g ha−1 of 2,4-D and 65% with 560 g ha−1 of dicamba. Linear regression indicated that the intercept for yield reduction was 12% for 2,4-D and 23% for dicamba, and there was a 2.5% and 7.7% increase in yield reduction per additional 100 g ha−1, respectively. Although high variability was observed for the different variables, there was a positive correlation between injury and peanut yield reduction (P < 0.0001) with Pearson's Rho values ranging from 0.45 to 0.59 for 2,4-D and from 0.27 to 0.55 for dicamba, suggesting that growers can use injury data to make rough projections of yield reduction and decide if they continue their crop, especially when injury is evident.

La amplia adopción potencial de variedades de algodón y soya con resistencia a 2,4-D y dicamba en el sureste de los Estados Unidos aumentará el riesgo en maní de exposición accidental a estos herbicidas debido a deriva o errores de aplicación. Cuando estos accidentes ocurran, los productores deberán decidir entre continuar con el cultivo o terminarlo. Para tomar esta decisión, los productores necesitan estimar el potencial de reducción del rendimiento a causa de 2,4-D o dicamba. Se realizaron estudios de respuesta a dosis bajo condiciones de campo en Citra y Jay, FL en 2012 y 2013 para determinar el daño y reducción de rendimiento en el maní después de la exposición a 70, 140, 280, 560 y 1120 g ae ha−1 de 2,4-D o a 35, 70, 140, 280, y 560 g ae ha−1 de dicamba a 21 y 42 d después de la siembra (DAP). Solamente interacciones entre el herbicida y la dosis fueron significativas (P<0.04). Dicamba causó de 2 a 5 veces mayor daño al maní y de 0.5 a 2 veces mayor reducción en el rendimiento que 2,4-D. La mayor reducción del rendimiento fue 41% con 1,120 g ha−1 de 2,4-D y 65% con 560 g ha−1 de dicamba. Regresiones lineales indicaron que el intercepto para la reducción del rendimiento fue 12% para 2,4-D y 23% para dicamba, y hubo un incremento de 2.5% y 7.7% en la pérdida de rendimiento por cada 100 g ha−1 adicionales de estos herbicidas, respectivamente. Aunque se observó una alta variabilidad para las diferentes variables, hubo una correlación positiva entre el daño y la reducción en el rendimiento del maní (P<0.0001) con valores de Rho de Pearson de 0.45 a 0.59 para 2,4-D y 0.27 a 0.55 para dicamba, lo que sugiere que los productores pueden usar datos de daño para hacer proyecciones aproximadas de pérdida de rendimiento y así decidir si continúan el cultivo, especialmente cuando el daño es evidente.

Keywords

2,4-Ddicambapeanut, Arachis hypogaea L.Chemical controldose-responsedriftherbicide injurysynthetic auxin
Type
Research Article
Information
Weed Technology , Volume 28 , Issue 3 , September 2014 , pp. 465 - 470
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Bailey, JA, Kapusta, G (1993) Soybean (Glycine max) tolerance to simulated drift of nicosulfuron and primisulfuron. Weed Technol 7:740–745 Google Scholar
Behrens, MR, Mutlu, N, Chakraborty, S, Dumitru, R, Jiang, WZ, LaVallee, BJ, Herman, PL, Clemente, TE, Weeks, DP (2007) Dicamba resistance: enlarging and preserving biotechnology-based weed management strategies. Science 316:1185–1188 Google Scholar
Behrens, R, Lueschen, WE (1979) Dicamba volatility. Weed Sci 27:468–493 CrossRefGoogle Scholar
Branch, WD (2007) Registration of 'Georgia-06G' peanut. J Plant Reg 1:120 CrossRefGoogle Scholar
Cobb, JL, Reynolds, DB, Irby, J, Norsworthy, JK, Steckel, LE, Mills, A, Montgomery, R, Sandbrink, J, Remund, KM (2013) A field scale comparison of AI and TTI nozzles to mitigate off-target movement of dicamba. Page 224 in Proceedings of 66th the Southern Weed Science Society Annual Meeting. Houston, TX Google Scholar
Craigmyle, BD, Ellis, JM, Bradley, KW (2013) Influence of herbicide programs on weed management in soybean with resistance to glufosinate and 2,4-D. Weed Technol 27:78–84 CrossRefGoogle 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 62:193–206 CrossRefGoogle Scholar
Grover, R, Maybank, J, Yoshida, K (1972) Droplet and vapor drift from butyl ester and dimethylamine salt of 2,4-D. Weed Sci 20:320–324 CrossRefGoogle Scholar
Johnson, WG, Young, B, Matthews, J, Marquardt, P, Slack, C, Bradley, K, York, A, Culpepper, S, Hager, A, Al-Khatib, K, Steckel, L, Moechnig, M, Loux, M, Bernards, M, Smeda, R (2010) Weed control in dicamba-resistant soybeans. Online. Crop Manag. DOI: Google Scholar
Lassiter, BR, Burke, IC, Thomas, WE, Pline-Srnic, WA, Jordan, DL, Wilcut, JW, and Wilkerson, GG (2007) Yield and physiological response of peanut to glyphosate drift. Weed Technol 21:954–960 CrossRefGoogle Scholar
Marple, ME, Al-Khatib, K, Peterson, DE (2008) Cotton injury and yield as affected by simulated drift of 2,4-D and dicamba. Weed Technol 22:609–614 Google Scholar
Norsworthy, JK, Scott, B, Stephenson, D, Reynolds, DB, Peterson, M, Kruger, G (2013) Volatility and off-target movement of formulations containing colex-D technology. Page 225 in Proceedings of 66th the Southern Weed Science Society Annual Meeting. Houston, TX Google Scholar
Perry, DH, Braxton, B, Ellis, AT, Haywood, RA, Lassiter, RB, Richburg, JS, Walton, LC (2013) Evaluating differential volatility of auxin-type herbicides utilizing novel field methodology. Page 79 in Proceedings of 66th the Southern Weed Science Society Annual Meeting. Houston, TX Google Scholar
Prostko, EP, Grey, TL, Marshall, MW, Ferrell, JA, Dotray, PA, Jordan, DL, Grichar, WJ, Brecke, BJ, Davis, JW (2011) Peanut yield response to dicamba. Peanut Sci 38:61–65 Google Scholar
Prostko, EP, Webster, TM, Marshall, MW, Leon, RG, Grey, TL, Ferrell, JA, Dotray, PA, Jordan, DL, Grichar, WJ, Brecke, BJ (2013) Glufosinate application timing and rate affect peanut yield response. Peanut Sci 40:115–119 Google Scholar
Robinson, AP, Simpson, DM, Johnson, WG (2012) Summer annual weed control with 2,4-D and glyphosate. Weed Technol 26:657–660 Google Scholar
Spaunhorst, DJ, Bradley, KW (2013) Influence of dicamba and dicamba plus glyphosate combinations on the control of glyphosate-resistant waterhemp (Amaranthus rudis). Weed Technol 27:675–681 Google Scholar
Strachan, SD, Ferry, NM, Cooper, TL (2013) Vapor movement of aminocyclopyrachlor, aminopyralid, and dicamba in the field. Weed Technol 27:143–155 Google Scholar
Urwin, CP, Wilson, RG, Mortensen, DA (1996) Response of dry edible bean (Phaseolus vulgaris) cultivars to four herbicides. Weed Technol 10:512–518 Google Scholar
Williams, EJ, Drexler, JS (1981) A non-destructive method for determining peanut pod maturity. Peanut Sci 8:134–141 Google Scholar
Wright, TR, Shan, G, Walsh, TA, Lira, JM, Cui, C, Song, P, Zhuang, M, Arnold, NL, Lin, G, Russell, SM, Cicchillo, RM, Peterson, MA, Simpson, DM, Zhou, N, Ponsamuel, KY, Zhang, Z (2010) Robust crop resistance to broadleaf and grass herbicides provided by aryloxalkanoate dioxygenase transgenes. Proc Natl Acad Sci USA 107:20240–20245 Google Scholar