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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: [email protected]
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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 

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