Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-19T00:27:52.422Z Has data issue: false hasContentIssue false
  • English
  • Français

Modeling Glyphosate Resistance Management Strategies for Palmer Amaranth (Amaranthus palmeri) in Cotton

Published online by Cambridge University Press:  20 January 2017

Paul Neve ,
Jason K. Norsworthy ,
Kenneth L. Smith  and
Ian A. Zelaya
Paul Neve*
Affiliation:
School of Life Sciences, University of Warwick, Wellesbourne, Warwickshire CV35 9EF, United Kingdom
Jason K. Norsworthy
Affiliation:
University of Arkansas, Department of Crop, Soil, and Environmental Sciences, 1366 West Altheimer Drive, Fayetteville, AR 72704
Kenneth L. Smith
Affiliation:
University of Arkansas, Department of Crop, Soil, and Environmental Sciences, 1408 Scogin Drive, University of Arkansas–Monticello, Monticello, AR 71656
Ian A. Zelaya
Affiliation:
Weed Control Research, Syngenta LTD, Jealott's Hill International Research Centre, Bracknell, Berkshire RG42 6EY, United Kingdom
*
Corresponding author's E-mail: p.neve@warwick.ac.uk
Get access Rights & Permissions [Opens in a new window]

Abstract

A simulation model is used to explore management options to mitigate risks of glyphosate resistance evolution in Palmer amaranth in glyphosate-resistant cotton in the southern United States. Our first analysis compares risks of glyphosate resistance evolution for seven weed-management strategies in continuous glyphosate-resistant cotton monoculture. In the “worst-case scenario” with five applications of glyphosate each year and no other herbicides applied, evolution of glyphosate resistance was predicted in 74% of simulated populations. In other strategies, glyphosate was applied with various combinations of preplant, PRE, and POST residual herbicides. The most effective strategy included four glyphosate applications with a preplant fomesafen application, and POST tank mixtures of glyphosate plus S-metolachlor followed by glyphosate plus flumioxazin. This strategy reduced the resistance risk to 12% of populations. A second series of simulations compared strategies where glyphosate-resistant cotton was grown in one-to-one rotations with corn or cotton with other herbicide resistance traits. In general, crop rotation reduced risks of resistance by approximately 50% and delayed the evolution of resistance by 2 to 3 yr. These analyses demonstrate that risks of glyphosate resistance evolution in Palmer amaranth can be reduced by reducing glyphosate use within and among years, controlling populations with diverse herbicide modes of action, and ensuring that population size is kept low. However, no strategy completely eliminated the risk of glyphosate resistance.

Se utilizó un modelo de simulación para explorar opciones de manejo que mitiguen los riesgos de evolución de resistencia al glyphosate en Amaranthus palmeri en algodón resistente al glyphosate en el sur de los EE UU. Nuestro primer análisis compara los riesgos de evolución de resistencia al glyphosate para siete estrategias de manejo de malezas en un monocultivo continuo de algodón resistente al glyphosate. En el “peor escenario”, con cinco aplicaciones de glyphosate cada año y sin usar otros herbicidas, se predijo la evolución de resistencia al herbicida en 74% de las poblaciones simuladas. En otras estrategias, el glyphosate se aplicó con varias combinaciones de herbicidas residuales en pre-siembra, PRE y POST. La estrategia más efectiva incluyó cuatro aplicaciones de glyphosate con una aplicación pre-siembra de fomesafen, y aplicaciones POST con mezclas en tanque de glyphosate más S-metolachlor, seguidas de glyphosate más flumioxazin. Esta estrategia redujo el riesgo de resistencia a 12% de las poblaciones. Una segunda serie de simulaciones comparó estrategias donde el algodón resistente al glyphosate se cultivó en rotaciones una-a-una con maíz o algodón resistente a otros herbicidas. En general, la rotación de cultivos redujo los riesgos de resistencia en aproximadamente 50% y retrasó la evolución de la resistencia de 2 a 3 años. Estos análisis demuestran que los riesgos de evolución de resistencia al glyphosate en A. palmeri pueden ser disminuidos, reduciendo el uso del glyphosate durante y entre años, controlando las poblaciones con herbicidas de diversos modos de acción y asegurando que el tamaño de las poblaciones se mantenga bajo. Sin embargo, ninguna estrategia eliminó completamente los riegos de resistencia al glyphosate.

Keywords

FlumioxazinfomesafenglyphosateS-metolachlorPalmer amaranth, Amaranthus palmeri S. Wats AMAPAcorn, Zea mays L.cotton, Gossypium hirsutum L.Glyphosate-resistant cottonherbicide resistancepopulation dynamicssimulation model
Type
Weed Management—Major Crops
Information
Weed Technology , Volume 25 , Issue 3 , September 2011 , pp. 335 - 343
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

Baucom, R. S. and Mauricio, R. 2004. Fitness costs and benefits of novel herbicide tolerance in a noxious weed. Proc. Natl. Acad. Sci. U. S. A. 36:13386–13390.Google Scholar
Burke, I. C., Troxler, S. C., Askew, S. D., Wilcut, J. W., and Smith, W. D. 2005. Weed management systems in glyphosate-resistant cotton. Weed Technol. 19:422–429.Google Scholar
Clewis, S. B., Miller, D. K., Koger, C. H., Baughman, T. A., Price, A. J., Porterfield, D., and Wilcut, J. W. 2008. Weed management and crop response with glyphosate, s-metolachlor, trifoloxysulfuron, prometryn and MSMA in glyphosate-resistant cotton. Weed Technol. 22:160–167.CrossRefGoogle Scholar
Clewis, S. B., Wilcut, J. W., and Porterfield, D. 2006. Weed management with s-metolachlor and glyphosate mixtures in glyphosate-resistant strip- and conventional-tillage cotton (Gossypium hirsutum L.). Weed Technol. 20:232–241.CrossRefGoogle Scholar
Culpepper, A. S., Grey, T. L., Vencill, W. K., Kichler, J. M., Webster, T. M., Brown, S. M., York, A. C., Davis, J. W., and Hanna, W. W. 2006. Glyphosate-resistant Palmer amaranth (Amaranthus palmeri) confirmed in Georgia. Weed Sci. 54:620–626.CrossRefGoogle Scholar
Diggle, A. J., Neve, P. B., and Smith, F. P. 2003. Herbicides used in combination can reduce the probability of herbicide resistance in finite weed populations. Weed Res. 32:371–382.CrossRefGoogle Scholar
Dodds, D. M., Kirkpatrick, M. T., Barber, L. T., and Reynolds, D. B. 2008. Evaluation of trifloxysulfuron for weed control in cotton (Gossypium hirsutum L.). J. Cotton Sci. 12:211–217.Google Scholar
Everman, W. J., Clewis, S. B., York, A. C., and Wilcut, J. W. 2009. Weed control and yield with flumioxazin, fomesafen and S-metolachlor systems for glufosinate-resistant cotton residual weed management. Weed Technol. 23:391–397.Google Scholar
Foresman, C. and Glasgow, L. 2008. US grower perceptions and experiences with glyphosate-resistant weeds. Pest Manag. Sci. 64:388–391.Google Scholar
Gustafson, G. I. 2008. Sustainable use of glyphosate in North American cropping systems. Pest Manag. Sci. 64:409–416.Google Scholar
Heap, I. 2010. International Survey of Herbicide Resistant Weeds. http://www.weedscience.org. Accessed: December 15, 2010.Google Scholar
Keeley, P. E., Carter, C. H., and Thullen, R. M. 1987. Influence of planting date on growth of Palmer amaranth (Amaranthus palmeri). Weed Sci. 35:199–204.Google Scholar
Klingaman, T. E. and Oliver, L. R. 1994. Palmer amaranth (Amaranthus palmeri) interference in soybeans (Glycine max). Weed Sci. 42:523–527.Google Scholar
Neve, P. 2008. Simulation modeling to understand the evolution and management of glyphosate resistance in weeds. Pest Manag. Sci. 64:392–401.Google Scholar
Neve, P., Diggle, A. J., Smith, F. P., and Powles, S. B. 2003a. Simulating evolution of glyphosate resistance in Lolium rigidum I: population biology of a rare resistance trait. Weed Res. 43:404–417.Google Scholar
Neve, P., Diggle, A. J., Smith, F. P., and Powles, S. B. 2003b. Simulating evolution of glyphosate resistance in Lolium rigidum II: past, present and future glyphosate use in Australian cropping. Weed Res. 43:418–427.Google Scholar
Neve, P., Norsworthy, J. K., Smith, K. L., and Zelaya, I. A. 2011. Modeling evolution and management of glyphosate resistance in Amaranthus palmeri . Weed Res. 51:99–112.Google Scholar
Nichols, R. L., Bond, J., Culpepper, A. S., et al. 2009. Glyphosate-resistant Palmer amaranth (Amaranthus palmeri) spreads in the southern United States. Resist. Pest Manag. Newsl. 18(2):8–10.Google Scholar
Norsworthy, J. K., Griffith, G. M., Scott, R. C., Smith, K. L., and Oliver, L. R. 2008. Confirmation and control of glyphosate-resistant Palmer amaranth in Arkansas. Weed Technol. 22:108–113.Google Scholar
Norsworthy, J. K., Smith, K. L., Scott, R. C., and Gbur, E. E. 2007. Consultant perspectives on weed management needs in Arkansas cotton. Weed Technol. 21:825–831.Google Scholar
Patzoldt, W. L., Tranel, P. J., and Hager, A. G. 2005. A waterhemp (Amaranthus tuberculatus) biotype with multiple resistance across three herbicide sites of action. Weed Sci. 53:30–36.Google Scholar
Pedersen, B. P., Neve, P., Andreasen, C., and Powles, S. B. 2007. Ecological fitness of a glyphosate-resistant Lolium rigidum population: growth and seed production along a competition gradient. Basic Appl. Ecol. 8:258–268.Google Scholar
Scroggs, D. M., Miller, D. K., Griffin, J. L., Wilcut, J. W., Boluin, D. C., Stewart, A. M., and Vidrine, P. R. 2007. Effectiveness of PRE herbicide and POST glyphosate programs in second-generation glyphosate-resisant cotton. Weed Technol. 21:877–881.Google Scholar
Shoup, D. E., Al-Khatib, K., and Peterson, D. E. 2003. Common waterhemp (Amaranthus rudis) resistance to protoporphyrinogen oxidase-inhibiting herbicides. Weed Sci. 51:145–150.Google Scholar
Stanton, R. A., Pratley, J. E., Hudson, D., and Dill, G. M. 2008. A risk calculator for glyphosate resistance in Lolium rigidum (Gaud.). Pest Manag. Sci. 64:402–408.Google Scholar
Steckel, L. E., Main, C. L., Ellis, A. T., and Mueller, T. C. 2008. Palmer amaranth (Amaranthus palmeri) in Tennessee has low level glyphosate resistance. Weed Technol. 22:119–123.Google Scholar
Thornby, D. F. and Walker, S. R. 2009. Simulating the evolution of glyphosate resistance in grains farming in northern Australia. Ann. Bot. 104:747–756.Google Scholar
Werth, J. A., Preston, C., Taylor, I. N., Charles, G. W., Roberts, G. N., and Baker, J. 2008. Managing the risk of glyphosate resistance in Australian glyphosate-resistant cotton production systems. Pest Manag. Sci. 64:417–421.Google Scholar
Wise, A. M., Grey, T. L., Prostko, E. P., Vencill, W. K., and Webster, T. M. 2009. Establishing the geographical distribution and level of acetolactate synthase resistance of Palmer amaranth (Amaranthus palmeri) accessions in Georgia. Weed Technol. 23:214–220.Google Scholar
Wrubel, R. P. and Gressel, J. 1994. Are herbicide mixtures useful for delaying the rapid evolution of resistance? A case study. Weed Technol. 8:635–648.Google Scholar
Young, B. G. 2006. Changes in herbicide use patterns and production practices resulting from glyphosate-resistant crops. Weed Technol. 20:301–307.Google Scholar