Hostname: page-component-8448b6f56d-c4f8m Total loading time: 0 Render date: 2024-04-18T15:28:04.184Z Has data issue: false hasContentIssue false
  • English
  • Français

Modeling the Evolution of Glyphosate Resistance in Barnyardgrass (Echinochloa crus-galli) in Cotton-Based Production Systems of the Midsouthern United States

Published online by Cambridge University Press:  20 January 2017

Muthukumar V. Bagavathiannan ,
Jason K. Norsworthy ,
Kenneth L. Smith  and
Paul Neve
Muthukumar V. Bagavathiannan*
Affiliation:
Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR 72701
Jason K. Norsworthy
Affiliation:
Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR 72701
Kenneth L. Smith
Affiliation:
Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR 72701
Paul Neve
Affiliation:
School of Life Sciences, University of Warwick, Wellesbourne, Warwick CV35 9EF, United Kingdom
*
Corresponding author's E-mail: muthu@uark.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Glyphosate-resistant (GR) weeds have been a prime challenge to the sustainability of GR cotton-based production systems of the midsouthern United States. Barnyardgrass is known to be a high-risk species for evolving herbicide resistance, and a simulation model was developed for understanding the likelihood of glyphosate resistance evolution in this species in cotton-based systems. Under a worst-case scenario of five glyphosate applications in monoculture GR cotton, the model predicts resistance evolution in about 9 yr of continuous glyphosate use, with about 47% risk by year 15. A unique insight from this model is that management in response to GR Palmer amaranth in this system (a reactive response) provided a proactive means to greatly reduce the risks of glyphosate resistance evolution in barnyardgrass. Subsequent model analysis revealed that the risk of resistance is high in fields characterized by high barnyardgrass seedbank levels, seedling emergence, and seed production per square meter, whereas the risk is low in fields with high levels of postdispersal seed loss and annual seedbank loss. The initial frequency of resistance alleles was a high determinant of resistance evolution (e.g., 47% risk at year 15 at an initial frequency of 5e−8 vs. 4% risk at 5e−10). Monte Carlo simulations were performed to understand the influence of various glyphosate use patterns and production practices in reducing the rate and risk of glyphosate resistance evolution in barnyardgrass. Early planting and interrow cultivation are useful tools. Crop rotation is effective, but the diversity of weed management options practiced in the rotational crop is more important. Diversifying weed management options is the key, yet application timing and the choice of management option is critical. Model analyses illustrate the relative effectiveness of a number of diversified glyphosate use strategies in preventing resistance evolution and preserving the long-term utility of glyphosate in midsouthern U.S. cotton-based production systems.

Las malezas resistentes a glyphosate (GR) han sido un reto primordial a la sostenibilidad de los sistemas de producción basados en algodón GR en el sur-medio de los Estados Unidos. Echinochloa crus-galli es reconocida como una maleza de alto riesgo de evolución de resistencia a herbicidas por lo que se desarrolló un modelo de simulación para entender la probabilidad de la evolución de resistencia a glyphosate en esta especie en sistemas basados en algodón. En el caso del peor escenario con cinco aplicaciones de glyphosate en monocultivo de algodón GR, el modelo predice la evolución de resistencia en aproximadamente 9 años de uso continuo de glyphosate, con cerca de 47% de riesgo en el año 15. Un detalle único de este modelo es que el manejo en respuesta a Amaranthus palmeri GR en este sistema (una respuesta reactiva) brindó los medios proactivos para reducir ampliamente el riesgo de la evolución de resistencia a glyphosate en E. crus-galli. El análisis siguiente del modelo reveló que el riesgo de resistencia es alto en campos caracterizados por tener niveles altos de bancos de semillas, emergencia de plántulas, y producción de semilla de E. crus-galli por metro cuadrado, mientras que el riesgo es bajo en campos con altos niveles de pérdida de semilla post-dispersión y pérdidas anuales del banco de semillas. La frecuencia inicial de alelos de resistencia fue un determinante importante en la evolución de resistencia (e.g., 47% de riesgo en el año 15 a una frecuencia inicial de 5e−8 vs. 4% de riesgo a 5e−10). Se realizaron simulaciones Monte Carlo para entender la influencia de varios patrones de uso de glyphosate y prácticas de producción en la reducción del riesgo y la tasa de evolución de resistencia a glyphosate en E. crus-galli. La siembra temprana y el cultivo entre hileras son herramientas útiles. La rotación de cultivos es efectiva, pero la diversidad en opciones de manejo de malezas en el cultivo de rotación es más importante. El diversificar las opciones de manejo de malezas es la clave, aunque el momento de aplicación y la escogencia de la opción de manejo son críticos. Análisis de modelos ilustran la efectividad relativa de utilizar un número variado de estrategias de uso de glyphosate en la prevención de la evolución de resistencia y la preservación de la utilidad de glyphosate en el largo plazo en los sistemas de producción basados en algodón en el sur-medio de los Estados Unidos.

Keywords

Glyphosate; barnyardgrassEchinochloa crus-galli (L.) Beauv. ECHCGcottonGossypium hirsutum L.Glyphosate-resistant cottonherbicide-resistant weedsimulation modelingSTELLA modelweed population dynamicsweed seedbank
Type
Weed Management—Major Crops
Information
Weed Technology , Volume 27 , Issue 3 , September 2013 , pp. 475 - 487
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

Alarcon-Reverte, R., Garcia, A., Jasieniuk, M., Lanini, T., Hanson, B. D., Fischer, A. J. 2011. Glyphosate Driven Selection Strikes Again: Investigating the Mechanism of Resistance in Echinochloa colona from California. http://ucanr.org/blogs/UCDWeedScience/blogfiles/6198.pdf. Accessed July 12, 2012.Google Scholar
Anderson, R. L. 2005. A multi-tactic approach to manage weed population dynamics in crop rotations. Agron. J. 97:1579–1583.Google Scholar
Bagavathiannan, M. V., Norsworthy, J. K., and Smith, K. L. 2012a. Post-dispersal herbivory of selected weed seeds as affected by residue cover. Abstract 350 in Proceedings of the Weed Science Society of America Meeting. Waikoloa, HI Weed Science Society of America.Google Scholar
Bagavathiannan, M. V., Norsworthy, J. K., and Smith, K. L. 2012b. Weed seed decay as affected by depth and duration of seed burial. in Proceedings of the Weed Science Society of America Meeting. Waikoloa, HI Weed Science Society of America.Google Scholar
Bagavathiannan, M. V., Norsworthy, J. K., Smith, K. L., and Burgos, N. 2011a. Seedbank size and emergence pattern of barnyardgrass (Echinochloa crus-galli) in Arkansas. Weed Sci. 59:359–365.Google Scholar
Bagavathiannan, M. V., Norsworthy, J. K., Smith, K. L., and Neve, P. 2011b. Seed production of barnyardgrass (Echinochloa crus-galli) in response to time of emergence in cotton and rice. J. Agric. Sci. 150:717–724.Google Scholar
Bagavathiannan, M. V., Norsworthy, J. K., Smith, K. L., and Neve, P. 2011c. Density dependent growth and reproduction in barnyardgrass (Echinochloa crus-galli). Page 131 in Proceedings of the Southern Weed Science Society Meeting. San Juan, PR Southern Weed Science Society.Google Scholar
Bagavathiannan, M. V., Norsworthy, J. K., Smith, K. L., and Neve, P. 2012c. Pollen-mediated gene flow in barnyardgrass. Page 166 in Proceedings of the Southern Weed Science Society Meeting. Charleston, SC Southern Weed Science Society.Google Scholar
Baltazar, A. and Smith, R. J. Jr. 1994. Propanil-resistant barnyardgrass (Echinochloa crus-galli) control in rice (Oryza sativa). Weed Technol. 8:576–581.Google Scholar
Beckie, H. J. 2006. Herbicide-resistant weeds: management tactics and practices. Weed Technol. 20:793–814.Google Scholar
Beckie, H. J. 2011. Herbicide-resistant weed management: focus on glyphosate. Pest Manag. Sci. 67:1037–1048.Google Scholar
Blackshaw, R. E. 1990. Influence of soil temperature, soil moisture, and seed burial depth on the emergence of round-leaved mallow (Malva pusilla). Weed Sci. 38:518–521.Google Scholar
Brewer, C. E. and Oliver, L. R. 2009. Confirmation and resistance mechanisms in glyphosate-resistant common ragweed (Ambrosia artemisiifolia) in Arkansas. Weed Sci. 57:567–573.Google Scholar
Buhler, D. D., Hartzler, R. G., and Forcella, F. 1997. Implications of weed seedbank dynamics to weed management. Weed Sci. 45:329–336.Google Scholar
Cardina, J., Herms, C. P., and Doohan, D. J. 2002. Crop rotation and tillage system effects on weed seedbanks. Weed Sci. 50:448–460.Google Scholar
Cardina, J., Norquay, H. M., Stinner, B. R., and McCartney, D. A. 1996. Postdispersal predation of velvetleaf (Abutilon theophrasti) seeds. Weed Sci. 44:534–539.Google Scholar
Cavan, G., Cussans, J., and Moss, S. R. 2000. Modelling different cultivation and herbicide strategies for their effect on herbicide resistance in Alopecurus myosuroides . Weed Res. 40:561–568.Google 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.Google Scholar
Davis, A. S. 2006. When does it make sense to target the weed seed bank? Weed Sci. 54:558–565.Google Scholar
Davis, A. S. and Renner, K. A. 2006. Influence of seed depth and pathogens on fatal germination of velvetleaf (Abutilon theophrasti) and giant foxtail (Setaria faberi). Weed Sci. 55:30–35.Google Scholar
DeVore, J. D., Norsworthy, J. K., and Brye, K. R. 2012a. Influence of deep tillage and a rye cover crop on glyphosate-resistant Palmer amaranth emergence in cotton. Weed Technol. 26:832–838.Google Scholar
DeVore, J. D., Norsworthy, J. K., and Brye, K. R. 2012b. Influence of deep tillage, a rye cover crop, and various soybean production systems on Palmer amaranth emergence in soybean. Weed Technol. In press.Google Scholar
Dickson, J. W., Scott, R. C., Burgos, N. R., Salas, R. A., and Smith, K. L. 2011. Confirmation of glyphosate-resistant Italian ryegrass (Lolium perenne ssp. multiflorum) in Arkansas. Weed Technol. 25:674–679.Google Scholar
Duke, S.O. and Powles, S. B. 2009. Glyphosate-resistant crops and weeds: now and in the future. AgBioForum. 12:346–357.Google Scholar
Egley, G. H. and Chandler, J. M. 1978. Germination and viability of weed seeds after 2.5 years in a 50-year buried seed study. Weed Sci. 26:230–239.Google Scholar
Faircloth, W. H., Patterson, M. G., Monks, C. D., and Goodman, W. R. 2001. Weed management programs for glyphosate-tolerant cotton (Gossypium hirsutum). Weed Technol. 15:544–551.Google Scholar
Gaines, T.A., Cripps, A., and Powles, S.B. 2012. Evolved resistance to glyphosate in junglerice (Echinochloa colona) from the tropical Ord River region in Australia. Weed Technol. 26:480–484.Google Scholar
Gallandt, E. R. 2006. How can we target the weed seedbank? Weed Sci. 54:588–596.Google Scholar
Givens, W. A., Shaw, D. R., Johnson, W. G., Weller, S. C., Young, B. G., Wilson, R. G., Owen, M.D.K., and Jordan, D. 2009. A grower survey of herbicide use patterns in glyphosate-resistant cropping systems. Weed Technol. 23:156–161.Google Scholar
Grichar, W. J., Besler, B. A., Brewer, K. D., and Minton, B. W. 2004. Using soil-applied herbicides in combination with glyphosate in a glyphosate-resistant cotton herbicide program. Crop Prot. 23:1007–1010.Google Scholar
Hartzler, R. G. 1996. Velvetleaf (Abutilon theophrasti) population dynamics following a single year's seed rain. Weed Technol. 10:581–586.Google Scholar
Heap, I. 2013. The International Survey of Herbicide Resistant Weeds. http://www.weedscience.com. Accessed January 7, 2013.Google Scholar
Jasieniuk, M., Brule-Babel, A. L., and Morrison, I. N. 1996. The evolution and genetics of herbicide resistance in weeds. Weed Sci. 44:176–193.Google Scholar
Keeley, P. E. and Thullen, R. J. 1991. Growth and interaction of barnyard grass (Echinochloa crus-galli) with cotton (Gossypium hirsutum). Weed Sci. 39:369–375.Google Scholar
Liebman, M. and Dyck, E. 1993. Crop rotation and intercropping strategies for weed management. Ecol. Appl. 3:92–122.Google Scholar
Liebman, M., Mohler, C. L., and Staver, C. P. 2001. Ecological Management of Agricultural Weeds. New York Cambridge University Press. 548 p.Google Scholar
Lovelace, M. L., Talbert, R. E., Schmidt, R. E., Scherder, E. F., and Reaper, J. R. 2000. Multiple resistance of propanil-resistant barnyardgrass (Echinochloa crus-galli) to quinclorac. 44n Proceedings of the Rice Technical Working Group Meeting. Biloxi, MS Rice Technical Working Group.Google Scholar
Massinga, R. A., Currie, R. S., Horak, M. J., and Boyer, J. Jr. 2001. Interference of Palmer amaranth in corn. Weed Sci. 49:202–208.Google Scholar
McClelland, M. R., Talbert, R. E., Smith, K. L., Barrentine, J. L., Matthews, S., and Sparks, O. C. 2003. Update on Glyphosate-Resistant Horseweed in Arkansas Cotton. Summaries of Arkansas Cotton Research. http://arkansasagnews.uark.edu/521-24.pdf. Accessed January 4, 2013.Google Scholar
[NASS] National Agricultural Statistics Service. 2012. Acreage (June 2012). http://usda01.library.cornell.edu/usda/nass/Acre//2010s/2012/Acre-06-29-2012.pdf. Accessed January 4, 2013.Google Scholar
Neve, P., Diggle, A. J., Smith, F. P., and Powles, S. B. 2003. 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. 2011a. Modelling evolution and management of glyphosate resistance in Amaranthus palmeri . Weed Res. 51:99–112.Google Scholar
Neve, P., Norsworthy, J. K., Smith, K. L., and Zelaya, I. A. 2011b. Modeling glyphosate resistance management strategies for Palmer amaranth (Amaranthus palmeri) in cotton. Weed Technol. 25:335–343.Google Scholar
Neve, P. and Powles, S. B. 2005. Recurrent selection with reduced herbicide rates results in the rapid evolution of herbicide resistance in Lolium rigidum . Theor. Appl. Genet. 110:1154–1166.Google Scholar
Neve, P., Vila-Aiub, M., and Roux, F. 2009. Evolutionary-thinking in agricultural weed management. New Phytol. 184:783–793.Google Scholar
Nichols, R. L., Bond, J., Culpepper, A. S., Dodds, D., Nandula, V., Main, C. L., Marshall, M. W., Mueller, T. C., Norsworthy, J. K., Price, A., Patterson, M., Scott, R. C., Smith, K. L., Steckel, L. E., Stephenson, D., Wright, D., and York, A. C. 2009. Glyphosate-resistant Palmer amaranth (Amaranthus palmeri) spreads in the southern United States. Resistant Pest Manag. Newsl. 18:8–10.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 (Amaranthus palmeri) in Arkansas. Weed Technol. 22:108–113.Google Scholar
Norsworthy, J. K., Riar, D., Jha, P., and Scott, R. C. 2011. Confirmation, control, and physiology of glyphosate-resistant giant ragweed (Ambrosia trifida) in Arkansas. Weed Technol. 25:430–435.Google Scholar
Norsworthy, J. K., Scott, R., Smith, K., Still, J., Estorninos, L. Jr., and Bangarwa, S. 2009. Confirmation and management of clomazone-resistant barnyardgrass in rice. Page 211 in Proceedings of the Southern Weed Science Society Meeting. Orlando, FL Southern Weed Science Society.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
Norsworthy, J. K., Ward, S., Shaw, D., Llewellyn, R., Nichols, R., Webster, T. M., Bradley, K., Frisvold, G., Powles, S., Burgos, N., Witt, W., and Barrett, M. 2012. Reducing the risks of herbicide resistance: best management practices and recommendations. Weed Sci. 60 (Special Issue):31–62.Google Scholar
Ogg, A. G. Jr. and Dawson, J. H. 1984. Time of emergence of 8 weed species. Weed Sci. 32:327–335.Google Scholar
Osten, V. A., Walker, S. R., Storrie, A., Widderick, M., Moylan, P., Robinson, G. R., and Galea, K. 2007. Survey of weed flora and management relative to cropping practices in the north-eastern grain region of Australia. Aus. J. Exp. Agric. 47:57–70.Google Scholar
Pimental, D., Acquay, H., Biltonen, M., Rice, P., Silva, M., Nelson, J., Lipner, V., Giordano, S., Horowitz, A., and D'Amore, M. 1992. Environmental and human costs of pesticide use. Bioscience. 42:750–760.Google Scholar
Porterfield, D., Wilcut, J. W., and Askew, S. D. 2002. Weed management with CGA-362622, fluometuron, and prometryn in cotton. Weed Sci. 50:642–647.Google Scholar
Preston, C. 2010. Australian Glyphosate Resistance Register. Australian Glyphosate Sustainability Working Group. www.glyphosateresistance.org.au. Accessed January 6, 2013.Google Scholar
Reddy, K. N. and Norsworthy, J. K. 2010. Glyphosate-resistant crop production systems: impact on weed species shifts. Pages 165–184 in Nandula, V. K., ed. Glyphosate Resistance in Crops and Weeds: History, Development, and Management. New York J. Wiley.Google Scholar
Riar, D. S., Norsworthy, J. K., Johnson, D. B., Scott, R. C., and Bagavathiannan, M. 2011. Glyphosate resistance in a johnsongrass (Sorghum halepense) biotype from Arkansas. Weed Sci. 59:299–304.Google Scholar
Rushing, G. S. and Oliver, L. R. 1998. Influence of planting date on common cocklebur interference in early maturing soybean. Weed Sci. 46:99–104.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. 56:320–326.Google Scholar
Shaner, D. 2013. My View. Herbicide Resistance Action Committee. http://www.hracglobal.com/Publications/MyView.aspx. Accessed January 7, 2013.Google Scholar
Soteres, J. K. 2012. The Roundup Ready revolution in agriculture. Abstract 309 in Proceedings of the Weed Science Society of America Meeting. Waikoloa, HI Weed Science Society of America.Google Scholar
Teasdale, J. R. 1995. Influence of narrow row/high population corn (Zea mays) on weed control and light transmittance. Weed Technol. 9:113–118.Google Scholar
Teasdale, J. R. and Mohler, C. L. 1993. Light transmittance, soil temperature, and soil moisture under residue of hairy vetch and rye. Agron. J. 85:673–680.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
[USDA-ERS] U.S. Department of Agriculture–Economic Research Service. 2012. Adoption of Genetically Engineered Crops in the U.S.: Recent Trends in GE Adoption. http://www.ers.usda.gov/data-products/adoption-of-genetically-engineered-crops-in-the-us/recent-trends-in-ge-adoption.aspx#.UXGDIGfy3z4. Accessed April 19, 2013.Google Scholar
Walker, S., Osten, V., Storrie, A., Robinson, G., Cook, T., and Galea, K. 2002. Weeds at risk of developing herbicide resistance in the different cropping systems of the northern region. Pages 620–621 in Proceedings of the 13th Australian Weeds Conference. Perth, WA Plant Protection Society of Western Australia.Google Scholar
Walsh, M. J., Harrington, R. B., and Powles, S. B. 2012. Harrington Seed Destructor: a new nonchemical weed control tool for global grain crops. Crop Sci. 52:1343–1347.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
Wiese, A. M. and Binning, L. K. 1987. Calculating the threshold temperature of development for weeds. Weed Sci. 35:177–179.Google Scholar
Wilson, M. J., Norsworthy, J. K., Johnson, D. B., McCallister, E. K., DeVore, J. D., Griffith, J. M., and Bangarwa, S. K. 2010. Herbicide programs for controlling ALS-resistant barnyardgrass in Clearfield rice. in Proceedings of the Rice Technical Working Group Meeting. Biloxi, MS Rice Technical Working Group.Google Scholar
Yu, Q., Han, H., Cawthray, G. R., Wang, S. F., and Powles, S. B. 2013. Enhanced rates of herbicide metabolism in low herbicide-dose selected resistant Lolium rigidum . Plant Cell Environ. 36:818–827.Google Scholar
Yuan, J. S., Tranel, P. J., and Stewart, C. N. 2007. Non–target-site herbicide resistance: a family business. Trends Plant Sci. 12:6–13.Google Scholar
Zelaya, I. A., Owen, M. D., and VanGessel, M. J. 2004. Inheritance of evolved glyphosate resistance in Conyza canadensis (L.) Cronq. Theor. Appl. Genet. 110:58–70.Google Scholar
Supplementary material: File

Bagavathiannan et al. supplementary material

Supplementary Information

Download Bagavathiannan et al. supplementary material(File)
File 233.8 KB