Background: Weed resistance to foliar herbicides has dramatically increased worldwide in the last two decades. As a consequence, current practices of weed management have changed, with an increased adoption of soil-applied herbicides to restore control of herbicide-resistant weeds. We foresee metabolism-based resistance and cross-resistance to soil-applied herbicides as a potential global consequence to the increased and widespread adoption of new and old soil-applied herbicides. Thus, the aim of this study is to use computer simulation modelling to quantify and rank the risk of weeds evolving resistance to soil-applied herbicides under different usage strategies (single herbicide use, rotations and mixtures) and population genetic hypotheses.
Results: Simulations indicate that without rotation it takes twice as long to select for resistance to a particular soil-applied herbicide - trifluralin - than to any other herbicide option considered. Relative to trifluralin-only use, simple herbicide rotation patterns have no effect in delaying resistance, whereas more complex rotation patterns can delay resistance two- or three-fold. Herbicide mixtures further delay resistance up to six-fold in comparison to single use or simple herbicide rotations.
Conclusion: By computer modelling simulations we demonstrate that mixtures maximize herbicide effectiveness and the selection heterogeneity of soil-applied herbicides, and delay herbicide resistance evolution in weedy plants. Our study is consistent with previous state-of-art scientific evidence (i.e. epidemiological and modelling studies across different systems and pests) and extension efforts (i.e. 'rotate herbicide mixtures') to provide insight to manage the selection and evolution of weed resistance. © 2019 Society of Chemical Industry.
Keywords: herbicide resistance; herbicide stewardship; pro-active weed management; selection heterogeneity; selection intensity.
© 2019 Society of Chemical Industry.