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Modeling Population Dynamics of Kochia (Bassia scoparia) in Response to Diverse Weed Control Options

Published online by Cambridge University Press:  24 January 2019

O. Adewale Osipitan Open the ORCID record for O. Adewale Osipitan [Opens in a new window] ,
J. Anita Dille ,
Muthukumar V. Bagavathiannan  and
Stevan Z. Knezevic
O. Adewale Osipitan*
Affiliation:
Postdoctoral Research Associate, Northeast Research and Extension Center, Haskell Ag Lab, University of Nebraska–Lincoln, Concord, NE, USA
J. Anita Dille
Affiliation:
Professor, Department of Agronomy, Kansas State University, Manhattan, KS, USA
Muthukumar V. Bagavathiannan
Affiliation:
Assistant Professor, Department of Soil and Crop Sciences, Texas A&M University, College Station, TX, USA
Stevan Z. Knezevic
Affiliation:
Professor, Northeast Research and Extension Center, Haskell Ag Lab, University of Nebraska–Lincoln, Concord, NE, USA
*
*Author for correspondence: O. Adewale Osipitan, Northeast Research and Extension Center, Haskell Ag Lab, University of Nebraska–Lincoln, 57905 866 Road, Concord, NE 68728. (Email: waleos@unl.edu)
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Abstract

Kochia [Bassia scoparia (L.) A. J. Scott] is a problematic weed species across the Great Plains, as it is spreading fast and has developed herbicide-resistant biotypes. It is imperative to understand key life-history stages that promote population expansion of B. scoparia and control strategies that would provide effective control of these key stages, thereby reducing population growth. Diversifying weed control strategies has been widely recommended for the management of herbicide-resistant weeds. Therefore, the objectives of this study were to develop a simulation model to assess the population dynamics of B. scoparia and to evaluate the effectiveness of diverse weed control strategies on long-term growth rates of B. scoparia populations. The model assumed the existence of a glyphosate-resistant (GR) biotype in the B. scoparia population, but at a very low proportion in a crop rotation that included glyphosate-tolerant corn (Zea mays L.) and soybean [Glycine max (L.) Merr.]. The parameter estimates used in the model were obtained from various ecological and management studies on B. scoparia. Model simulations indicated that seedling recruitment and survival to seed production were more important than seedbank persistence for B. scoparia population growth rate. Results showed that a diversified management program, including glyphosate, could provide excellent control of B. scoparia populations and potentially eliminate already evolved GR B. scoparia biotypes within a given location. The most successful scenario was a diverse control strategy that included one or two preplant tillage operations followed by preplant or PRE application of herbicides with residual activities and POST application of glyphosate; this strategy reduced seedling recruitment, survival, and seed production during the growing season, with tremendous negative impacts on long-term population growth and resistance risk in B. scoparia.

Keywords

Prashant Jha, Montana State UniversityBest management practicesglyphosate resistanceherbicide resistancesimulation modelsweed population dynamics
Type
Research Article
Information
Weed Science , Volume 67 , Issue 1 , January 2019 , pp. 57 - 67
Copyright
© Weed Science Society of America, 2019 

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