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Yield and Physiological Response of Peanut to Glyphosate Drift

Published online by Cambridge University Press:  20 January 2017

Bridget R. Lassiter*
Affiliation:
North Carolina State University, Raleigh, NC 27695-7620
Ian C. Burke
Affiliation:
North Carolina State University, Raleigh, NC 27695-7620
Walter E. Thomas
Affiliation:
North Carolina State University, Raleigh, NC 27695-7620
Wendy A. Pline-Srnić
Affiliation:
North Carolina State University, Raleigh, NC 27695-7620
David L. Jordan
Affiliation:
North Carolina State University, Raleigh, NC 27695-7620
John W. Wilcut
Affiliation:
North Carolina State University, Raleigh, NC 27695-7620
Gail G. Wilkerson
Affiliation:
North Carolina State University, Raleigh, NC 27695-7620
*
Corresponding author's E-mail: [email protected]

Abstract

Five experiments were conducted during 2001 and 2002 in North Carolina to evaluate peanut injury and pod yield when glyphosate was applied to 10 to 15 cm diameter peanut plants at rates ranging from 9 to 1,120 g ai/ha. Shikimic acid accumulation was determined in three of the five experiments. Visual foliar injury (necrosis and chlorosis) was noted 7 d after treatment (DAT) when glyphosate was applied at 18 g/ha or higher. Glyphosate at 280 g/ha or higher significantly injured the peanut plant and reduced pod yield. Shikimic acid accumulation was negatively correlated with visual injury and pod yield. The presence of shikimic acid can be detected using a leaf tissue assay, which is an effective diagnostic tool for determining exposure of peanut to glyphosate 7 DAT.

Type
Research
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Al-Khatib, K., Claassen, M. M., Stahlman, P. W., Geier, P. W., Regehr, D. L., Duncan, S. R., and Heer, W. F. 2003. Grain sorghum response to simulated drift from glufosinate, glyphosate, imazethypyr and sethoxidim. Weed Technol. 17:261265.Google Scholar
Al-Khatib, K., Currie, R. S., Maddux, L. D., Thompson, C. R., and Price, T. M. 2000. Corn response to simulated herbicide drift. Proc. N. Cent. Weed Sci. Soc. 55:56.Google Scholar
Al-Khatib, K. and Peterson, D. 1999. Soybean (Glycine max) response to simulated drift from selected sulfonylurea herbicides, dicamba, glyphosate, and glufosinate. Weed Technol. 13:264270.Google Scholar
Askew, S. D., Bailey, W. A., Scott, G. H., and Wilcut, J. W. 2002. Economic assessment of weed management for transgenic and nontransgenic cotton in tilled and nontilled systems. Weed Sci. 50:512520.Google Scholar
Askew, S. D. and Wilcut, J. W. 1999. Cost and weed management with herbicide programs in glyphosate-resistant cotton (Gossypium hirsutum). Weed Technol. 13:308313.CrossRefGoogle Scholar
Atkinson, D. 1985. Glyphosate damage symptoms and the effects of drift. Pages 455465. in Grossbard, E., Atkinson, D. eds. The Herbicide Glyphosate. London Butterworths.Google Scholar
Banks, P. A. and Schroeder, J. 2002. Carrier volume affects herbicide activity in simulated spray drift studies. Weed Technol. 16:833837.Google Scholar
Bhatti, M. A., Al-Khatib, K., and Parker, R. 1997. Wine grape (Vitis vinifera) response to fall exposure of simulated drift from selected herbicides. Weed Technol. 11:532536.Google Scholar
Brandenburg, R. L. 2003. Peanut insect and mite management. Pages 5874. in. 2003 Peanut Information. Raleigh, NC North Carolina Cooperative Extension Service Publ. AG-331.Google Scholar
Bromilow, R. H. and Chamberlain, K. 2000. The herbicide glyphosate and related molecules: physiochemical and structural factors determining their mobility in phloem. Pest Manag. Sci. 56:368373.Google Scholar
Brown, A. B. 2003. 2003 outlook and situation. Pages 12. in. 2003 Peanut Information. Raleigh, NC North Carolina Cooperative Extension Service Publ. AG-331.Google Scholar
Burke, I. C., Thomas, W. E., Pline-Srnic, W. A., Fisher, L. R., Smith, W. D., and Wilcut, J. W. 2005. Yield and physiological response of flue-cured tobacco to simulated glyphosate drift. Weed Technol. 19:255260.Google Scholar
Clewis, S. B., Thomas, W. E., and Wilcut, J. W. 2005. Weed management in Roundup Ready flex cotton. Proceedings of the Beltwide Cotton Conference [CD-ROM].Google Scholar
Colvin, D. L., MacDonald, G. E., Shilling, D. G., Mossler, M. A., Kvien, C., Swan, C. W., and Wehtje, G. R. 1990. Physiological and yield effects on peanut (Arachis hypogaea L.) from foliar applied yield enhancers. Proc. South. Weed Sci. Soc. 43:109.Google Scholar
Culpepper, A. S. and York, A. C. 1999. Weed management and net returns with transgenic, herbicide resistant, and nontransgenic cotton (Gossypium hirsutum). Weed Technol. 13:411420.CrossRefGoogle Scholar
Culpepper, A. S., York, A. C., Batts, R. B., and Jennings, K. M. 2000. Weed management in glufosinate- and glyphosate- resistant soybean (Glycine max). Weed Technol. 14:7788.Google Scholar
Draper, N. R. and Smith, H. 1981. Applied Regression Analysis. New York J. Wiley. 3342, 511.Google Scholar
Duke, S. O. 1988. Glyphosate. Pages 170. in Kearney, P.C., Kaufman, D.D. eds. Herbicides: Chemistry, Degradation, and Mode of Action. New York Mercel Dekker.Google Scholar
Ellis, J. M. and Griffin, J. 2002. Soybean (Glycine max) and cotton (Gossypium hirsutum) response to simulated drift of glyphosate and glufosinate. Weed Technol: 16:580586.Google Scholar
Ellis, J. M., Griffin, J. L., and Jones, C. A. 2002. Effect of carrier volume on corn (Zea mays) and soybean (Glycine max) response to simulated drift of glyphosate and glufosinate. Weed Technol. 16:587592.Google Scholar
Ellis, J. M., Griffin, J. L., Linscombe, S. D., and Webster, E. P. 2003. Rice (Oryza sativa) and corn (Zea mays) response to simulated drift of glyphosate and glufosinate. Weed Tech. 17:452460.Google Scholar
Feng, P. C. C., Chiu, T., Sammons, R. D., and Ryerse, J. S. 2003. Droplet size affects glyphosate retention, absorption, and translocation in corn. Weed Sci. 51:443448.Google Scholar
Frans, R., Talbert, R., Marx, D., and Crowley, H. 1986. Experimental design and techniques for measuring and analyzing plant responses to weed control practices. Pages 2946. in Camper, N.D. ed. Research Methods in Weed Science. 3rd ed. Champaign, IL Southern Weed Science Society.Google Scholar
Franz, J. E., Mao, M. K., and Sikorski, J. A. 1997. Uptake, transport, and metabolism in plants. Pages 521605. in. Glyphosate: A Unique Global Herbicide. ACS Monograph 189.Google Scholar
Jain, M., Bhatnagar, R. J., and Sarin, N. B. 1999. Isolation and biochemical diagnosis of cell lines of groundnut (Arachis hypogaea L.) selected on glyphosate. Pest. Science. 55:843849.Google Scholar
Jordan, D. L. 2003. Weed Management in Peanut. Pages 3560. 2003 Peanut Information. North Carolina Cooperative Extension Service AG-331.Google Scholar
Koger, C. H., Shaner, D. L., Krutz, L. J., Walker, T. W., Buehring, N., Henry, W. B., Thomas, W. E., and Wilcut, J. W. 2005. Rice (Oryza sativa) response to drift rates of glyphosate. Pest Manage. Sci. 61:11611167.Google Scholar
Kurtz, M. E. and Street, J. E. 2003. Response of rice to glyphosate applied to simulate drift. Weed Technol. 17:234238.Google Scholar
Lyon, L. L., Keeling, J. W., Baughman, T. A., Osbourne, T. S., and Dotray, P. A. 2003. Non-glyphosate tolerant cotton response to simulated drift rates of glyphosate. Proc. South. Weed Sci. Soc. 56:1415.Google Scholar
McIntosh, M. S. 1983. Analysis of combined experiments. Agron. J. 75:153155.Google Scholar
Owen, M. D. K. 2000. Current use of transgenic herbicide-resistant soybean and corn in the USA. Crop Prot. 19:765771.Google Scholar
Pline, W. A., Price, A. J., Wilcut, J. W., Edmisten, K. L., and Wells, R. W. 2001. Absorption and translocation of glyphosate in glyphosate-resistant cotton as influenced by application method and growth stage. Weed Sci. 49:460467.Google Scholar
Pline, W. A., Wilcut, J. W., Duke, S. O., Edmisten, K. L., and Wells, R. W. 2002. Tolerance and accumulation of shikimic acid in response to glyphosate applications in glyphosate-resistant and non glyphosate-resistant cotton (Gossypium hirsutum L.). J. Agric. Food Chem. 50:506512.Google Scholar
Ray, T. B. 1989. Herbicides as inhibitors of amino acid biosynthesis. Pages 112114. in Boger, P., Sandmann, G. eds. Target Sites of Herbicide Action. Boca Raton, FL CRC.Google Scholar
SAS 2001. SAS/STAT Users Guide. Version 8.2. Cary, NC SAS Institute.Google Scholar
Scott, G. H., Askew, S. D., Bennett, A. C., and Wilcut, J. W. 2001. Economic evaluation of HADSS™ computer program for weed management in nontransgenic and transgenic cotton. Weed Sci. 49:549557.CrossRefGoogle Scholar
Seefeldt, S. S., Jensen, J. E., and Fuerst, E. P. 1995. Log-logistic analysis of herbicide dose-response relationships. Weed Technol. 9:218227.Google Scholar
Shaner, D. L. 2000. The impact of glyphosate-tolerant crops on the use of other herbicides and on resistance management. Pest Manag. Sci. 56:320326.Google Scholar
Shew, B. 2003. Peanut disease management. Pages 7598. in. 2003 Peanut Information. Raleigh, NC North Carolina Cooperative Extension Service Publ. AG-331.Google Scholar
Singh, B. K. and Shaner, D. L. 1998. Rapid determination of glyphosate injury to plants and identification of glyphosate resistant plants. Weed Technol. 12:527530.Google Scholar
Steinrucken, H. C. and Amrhein, N. 1980. The herbicide glyphosate is a potent inhibitor of 5-enolpyruvylshikimic acid-3-phosphate synthase. Biochem. Biophys. Res. Commun. 94:12071212.Google Scholar
Thomas, W. E., Burke, I. C., Robinson, B. L., Pline-Srnic, W. A., Edmisten, K. L., Wells, R., and Wilcut, J. W. 2005. Yield and physiological response of nontransgenic cotton (Gossypium hirsutum) to simulated glyphosate drift. Weed Technol. 19:3542.Google Scholar
Thomas, W. E., Burke, I. C., and Wilcut, J. W. 2004a. Weed management in glyphosate-resistant corn with glyphosate, halosulfuron, and mesotrione. Weed Technol. 18:826834.Google Scholar
Thomas, W. E., Burke, I. C., and Wilcut, J. W. 2004b. Weed management in glyphosate-resistant corn with glyphosate and halosulfuron. Weed Technol. 18:10491057.Google Scholar
USDA National Agricultural Statistics Service 2002. http://www.nass.usda.gov/la/Ff051702.txt. Accessed: June 19, 2003.Google Scholar
USDA National Agricultural Statistics Service 2004. Agriculture chemical usage; 2003 Field Crops Summary. http://usda.mannlib.cornell.edu/reports/nassr/other/pcu-bb/agcs0504.pdf. Accessed: September 11, 2005.Google Scholar
USDA National Agricultural Statistics Service 2005. Crop Production Acreage. http://usda.mannlib.cornell.edu/reports/nassr/field/pcp-bba/acrg0605.txt. Accessed: January 20, 2006.Google Scholar
Wallace, A., Lancaster, R. A., and Hill, N. L. 1998. Application of non-selective herbicides during flowering of pasture legumes can reduce seed yield and alter seed characteristics. Aust. J. Exp. Agric. 38:583594.Google Scholar
York, A. C. 2006. Chemical Weed Control in Cotton. Pages 346359. in. 2006 North Carolina Agricultural Chemicals Manual. The College of Agricultural Sciences, North Carolina State University.Google Scholar
York, A. C., Jordan, D. L., and Wilcut, J. W. 1994. Peanut control in rotational crops. Peanut Sci. 21:4043.CrossRefGoogle Scholar