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A generalised individual-based algorithm for modelling the evolution of quantitative herbicide resistance in arable weed populations.

Chun LiuMelissa E BridgesShiv S KaundunLes GlasgowMicheal Dk OwenPaul Neve
Published in: Pest management science (2016)
The simulation model provides a robust and widely applicable framework for predicting the evolution of quantitative herbicide resistance in summer annual weed populations. The sensitivity analyses identified weed characteristics that would favour herbicide resistance evolution, including high annual fecundity, large resistance phenotypic variance and pre-existing herbicide resistance. Implications for herbicide resistance management and potential use of the model are discussed. © 2016 Society of Chemical Industry.
Keyphrases
  • high resolution
  • machine learning
  • risk assessment
  • mass spectrometry
  • genetic diversity