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Predicting the Evolution and Dynamics of Herbicide Resistance in Weed Populations

Published online by Cambridge University Press:  12 June 2017

Bruce D. Maxwell,
Mary Lynn Roush and
Steven R. Radosevich
Bruce D. Maxwell
Affiliation:
Dep. For. Sci., Oreg. State Univ., Corvallis, OR 97331
Mary Lynn Roush
Affiliation:
Dep. For. Sci., Oreg. State Univ., Corvallis, OR 97331
Steven R. Radosevich
Affiliation:
Dep. For. Sci., Oreg. State Univ., Corvallis, OR 97331
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Abstract

Herbicide resistance jeopardizes the usefulness of valuable chemical tools and, therefore, weed management in many crop systems. Models must be developed to evaluate management tactics that prevent, delay, or reduce resistance. The complexity of biological processes involved in herbicide resistance also requires models to focus research and to integrate experiments. A population model was developed that improves upon previous attempts to predict herbicide resistance dynamics. The model incorporates plant population demographics with the Hardy-Weinberg concept for gene segregation. The model simulates the evolution, spread, and subsequent dynamics of resistance in the presence and absence of a herbicide. Analysis of model simulations identified two sets of biological processes as key factors in the evolution and dynamics of herbicide-resistant weed populations. These are processes that influence ecological fitness and gene flow. Several options are suggested as examples for the management of resistant weed populations.

Keywords

Population modelresistance managementseed immigrationpollen immigrationpopulation genetics

Information

Type
Feature
Information
Weed Technology , Volume 4 , Issue 1 , March 1990, pp. 2 - 13
Copyright
Copyright © 1990 Weed Science Society of America 

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