Hostname: page-component-745bb68f8f-hvd4g Total loading time: 0 Render date: 2025-01-11T12:00:48.686Z Has data issue: false hasContentIssue false
  • English
  • Français

Response of Glyphosate-Tolerant Soybean Yield Components to Dicamba Exposure

Published online by Cambridge University Press:  20 January 2017

Andrew P. Robinson ,
David M. Simpson  and
William G. Johnson
Andrew P. Robinson
Affiliation:
Department of Botany and Plant Pathology, 915 W. State Street, Purdue University, West Lafayette, IN 47907
David M. Simpson
Affiliation:
Dow AgroSciences, 9330 Zionsville Road, Indianapolis, IN 46268
William G. Johnson*
Affiliation:
Department of Botany and Plant Pathology, 915 W. State Street, Purdue University, West Lafayette, IN 47907
*
Corresponding author's E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Exposure of soybean to dicamba can result in leaf malformation and sometimes yield loss, but it is unclear how yield components are affected by exposure to low quantities of this herbicide. The objectives were to characterize soybean injury and quantify changes in seed yield and yield components of soybean plants exposed to dicamba, and determine if seed yield loss can be estimated from visual injury ratings. Nine dicamba rates (0, 0.06, 0.23, 0.57, 1.1, 2.3, 4.5, 9.1, and 22.7 g ae ha−1) were applied at three growth stages (V2 – two trifoliates, V5-five trifoliates, or R2-full flowering soybean) to Beck's brand ‘342NRR’ soybean planted near Lafayette, IN, in 2009 and 2010 and near Fowler, IN, in 2009. Visually estimated soybean injury of 20% at the V2, V5, or R2 timing was 0.676 to 0.937 g ha−1 dicamba at 14 d after treatment (DAT) and 0.359 to 1.37 g ha−1 dicamba at 28 DAT. Seed yield was reduced by 5% from 0.042 to 0.528 g ha−1 dicamba and a 10% reduction was caused by 0.169 to 1.1 g ha−1 dicamba. The number of seeds m−2, pods m−2, reproductive nodes m−2, and nodes m−2 were the most sensitive yield components. Path analysis indicated that dicamba reduced seeds m−2, pods m−2, reproductive nodes m−2, and nodes m−2 which were the main causes of seed yield loss from dicamba exposure. The correlation of seed yield loss and visual soybean injury was significant (P < 0.0001) for both the V2 treatment timing (R 2 = 0.92) and the V5 and R2 treatment timings (R 2 = 0.91). Early-season injury rating of 8% at the V2 treatment and 2% at the V5 or R2 treatments caused 10% or more yield loss.

Keywords

Dicambasoybean, Glycine max (L.) Merr3,6-dichloro-o-anisic acidcrop injurydriftdose responsereproduction
Type
Physiology, Chemistry, and Biochemistry
Information
Weed Science , Volume 61 , Issue 4 , December 2013 , pp. 526 - 536
Copyright
Copyright © Weed Science Society of America 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Literature Cited

Al-Khatib, K. and Peterson, D. 1999. Soybean (Glycine max) response to simulated drift from selected sulfonylurea herbicides, dicamba, glyphosate, and glufosinate. Weed Technol. 13:264–270.Google Scholar
Andersen, S. M., Clay, S. A., Wrage, L. J., and Matthees, D. 2004. Soybean foliage residues of dicamba and 2,4-D and correlation to application rates and yield. Agron. J. 96:750–760.CrossRefGoogle Scholar
Auch, D. E. and Arnold, W. E. 1978. Dicamba use and injury on soybeans (Glycine max) in South Dakota. Weed Sci. 26:471–475.Google Scholar
Behrens, M. R., Mutlu, N., Chakraborty, S., Dumitru, R., Jiang, W. Z., LaVallee, B. J., Herman, P. L., Clemente, T. E., and Weeks, D. P. 2007. Dicamba resistance: enlarging and preserving biotechnology-based weed management strategies. Science 316:1185–1188.Google Scholar
Behrens, R. and Lueschen, W. E. 1979. Dicamba volatility. Weed Sci. 27:486–493.Google Scholar
Board, J. E. and Modali, H. 2005. Dry matter accumulation predictors for optimal yield in soybean. Crop Sci. 45:1790–1799.Google Scholar
Boerboom, C. 2004. Field case studies of dicamba movement to soybeans: University of Wisconsin. http://www.soils.wisc.edu/extension/FAPM/2004proceedings/Boerboom3.pdf. Accessed September 3, 2009.Google Scholar
Conley, S. P., Pedersen, P., and Christmas, E. P. 2009. Main-stem node removal effect on soybean seed yield and composition. Agron. J. 101:120–123.Google Scholar
De Bruin, J. L. and Pedersen, P. 2008. Soybean seed yield response to planting date and seeding rate in the Upper Midwest. Agron. J. 100:696–703.Google Scholar
Dexter, A., Slife, F., and Butler, H. 1971. Detoxification of 2,4-D by several plant species. Weed Sci. 19:721–726.Google Scholar
Fehr, W. R. and Caviness, C. E. 1977. Stages of Soybean Development. Special Report 80. Iowa Agriculture and Home Economics Experiment Station, Iowa State University. 11 p.Google Scholar
Gerber, C. K., Brouder, S. M., Camberato, J. J., Casteel, S. N., Creswell, T., Faghihi, J. J., Joern, B. C., Johnson, W. G., Krupke, C. H., Loven, J. S., Nice, G.R.W., Nielsen, R. L., Obermeyer, J. L., Ruhl, G. E., Steinhardt, G. C., and Wise, K. A. 2012. Corn and Soybean Field Guide. West Lafayette. IN Agriculture Communication Media Distribution Center. 324 p.Google Scholar
Kahlon, C. S., Board, J. E., and Kang, M. S. 2011. An analysis of yield component changes for new vs. old soybean cultivars. Agron. J. 103:13–22.Google Scholar
Kang, M. S. 1994. Applied Quantitative Genetics. Baton Rouge, LA M. S. Kang. 157 p.Google Scholar
Kelley, K. B., Wax, L. M., Hager, A. G., and Riechers, D. E. 2005. Soybean response to plant growth regulator herbicides is affected by other postemergence herbicides. Weed Sci. 53:101–112.Google Scholar
Knezevic, S. Z., Sikkema, P. H., Tardif, F., Hamill, A. S., Chandler, K., and Swanton, C. J. 1998. Biologically effective dose and selectivity of RPA 201772 for preemergence weed control in corn (Zea mays). Weed Technol. 12:670–676.Google Scholar
Knezevic, S. Z., Streibig, J. C., and Ritz, C. 2007. Utilizing R software package for dose-response studies: the concept and data analysis. Weed Technol. 21:840–848.Google Scholar
Kniss, A. R. and Lyon, D. J. 2011. Winter wheat response to preplant applications of aminocyclopyrachlor. Weed Technol. 25:51–57.Google Scholar
Kokubun, M. S. and Takahashi, S. 2001. Flower abortion caused by preanthesis water deficit is not attributed to impairment of pollen in soybean. Crop Sci. 41:1517–1521.Google Scholar
Lingle, S. E. and Suttle, J. C. 1985. A model system for the study of 2,4-D translocation in leafy spurge. Can. J. Plant Sci. 65:367–377.Google Scholar
Liu, F., Jensen, C. R., and Andersen, M. N. 2004. Drought stress effect on carbohydrate concentration in soybean leaves and pods during early reproductive development: its implication in altering pod set. Field Crops Res. 86:1–13.Google Scholar
Maybank, J., Yoshida, K., and Grover, R. 1978. Spray drift from agricultural pesticide applications. J. Air Pollut. Control Assoc. 28:1009–1014.Google Scholar
Ritz, C. and Strebig, J. 2011. Package ‘drc’. Available at http://cran.r-project.org/web/packages/drc/drc.pdf. Accessed June 9, 2011.Google Scholar
Robinson, A. P., Conley, S. P., Volenec, J. J., and Santini, J. B. 2009. Analysis of high yielding, early-planted soybean in Indiana. Agron. J. 101:131–139.Google Scholar
Robinson, A. P., Davis, V. M., Simpson, D. M., and Johnson, W. G. 2013. Response of soybean yield components to 2,4-D. Weed Sci. 61:68–76.Google Scholar
Robocker, W. C. 1976. Translocation and metabolism of dicamba in western bracken. Weed Sci. 24:435–438.Google Scholar
Sciumbato, A. S., Chandler, J. M., Senseman, S. A., Bovey, R. W., and Smith, K. L. 2004. Determining exposure to auxin-like herbicides. I. Quantifying injury to cotton and soybean. Weed Technol. 18:1125–1134.Google Scholar
Seber, G.A.F. and Wild, C. J. 1989. Nonlinear Regression. New York J. Wiley. 768 p.Google Scholar
Sionit, N. K. and Paul, J. 1977. Effect of water stress during different stages of growth of soybean. Agron. J. 69:274.Google Scholar
Spiess, A. and Neumeyer, N. 2010. An evaluation of R2 as an inadequate measure for nonlinear models in pharmacological and biochemical research: a Monte Carlo approach. BMC Pharmacol. 10:6–17.Google Scholar
Wax, L. M., Knuth, L. A., and Slife, F. W. 1969. Response of soybeans to 2,4-D, dicamba, and picloram. Weed Sci. 17:388–393.Google Scholar
Weidenhamer, J. D., Triplett, G. B. Jr., and Sobotka, F. E. 1989. Dicamba injury to soybean. Agron. J. 81:637–643.Google Scholar
Wolf, T. M., Grover, R., Wallace, K., Shewchuk, S. R., and Maybank, J. 1993. Effect of protective shields on drift and deposition characteristics of field sprayers. Can. J. Plant Sci. 73:1261–1273.Google Scholar