Optimising fungicide application tactics: using mathematical modelling to understand qualitative and quantitative fungicide resistance management
type: CreativeWork
description: Plant diseases pose a significant threat to food security, and fungal plant pathogens can be particularly damaging due to enormous evolutionary potential. Two major control strategies for fungal pathogens include chemical control with fungicides and use of disease-resistant cultivars. Both strategies are threatened by pathogen evolution leading to fungicide resistance and loss of cultivar efficacy (‘cultivar breakdown’). Both fungicide resistance and cultivar breakdown can be characterised as qualitative or quantitative, depending on the genetic basis for resistance/breakdown. Mathematical models have an important role in understanding fungicide resistance and cultivar breakdown, and modelling studies offer numerous advantageous over experimental studies. We present a model of qualitative fungicide resistance and one of quantitative fungicide resistance and cultivar breakdown. The model of qualitative resistance extends a model from the literature, while the quantitative resistance model is entirely novel. Both models are parameterised to address Septoria, the most prevalent disease of wheat. Although qualitative resistance has been widely studied, many single-site fungicides (i.e. those challenged by qualitative resistance) face widespread resistance, meaning that quantitative resistance is increasingly important. However, the mechanisms underlying quantitative resistance/breakdown are more complex and suitable data for model fitting is harder to source. We present the first model of quantitative resistance to be fitted to field data for both fungicide resistance and cultivar breakdown. Fungicide mixtures can help delay resistance. Although many studies focus on mixtures of fungicides to which resistance is qualitative, the optimal strategy is not characterised if the initial resistance frequencies (RFs) to two fungicides in a mixture differ. Past work showed that equal selection for single resistant strains in the first year was the optimal strategy when initial R…
abstract: Plant diseases pose a significant threat to food security, and fungal plant pathogens can be particularly damaging due to enormous evolutionary potential. Two major control strategies for fungal pathogens include chemical control with fungicides and use of disease-resistant cultivars. Both strategies are threatened by pathogen evolution leading to fungicide resistance and loss of cultivar efficacy (‘cultivar breakdown’). Both fungicide resistance and cultivar breakdown can be characterised as qualitative or quantitative, depending on the genetic basis for resistance/breakdown. Mathematical models have an important role in understanding fungicide resistance and cultivar breakdown, and modelling studies offer numerous advantageous over experimental studies. We present a model of qualitative fungicide resistance and one of quantitative fungicide resistance and cultivar breakdown. The model of qualitative resistance extends a model from the literature, while the quantitative resistance model is entirely novel. Both models are parameterised to address Septoria, the most prevalent disease of wheat. Although qualitative resistance has been widely studied, many single-site fungicides (i.e. those challenged by qualitative resistance) face widespread resistance, meaning that quantitative resistance is increasingly important. However, the mechanisms underlying quantitative resistance/breakdown are more complex and suitable data for model fitting is harder to source. We present the first model of quantitative resistance to be fitted to field data for both fungicide resistance and cultivar breakdown. Fungicide mixtures can help delay resistance. Although many studies focus on mixtures of fungicides to which resistance is qualitative, the optimal strategy is not characterised if the initial resistance frequencies (RFs) to two fungicides in a mixture differ. Past work showed that equal selection for single resistant strains in the first year was the optimal strategy when initial R…
author: Taylor, Nick
language: eng
keywords: Epidemiology, Fungicide resistance, Mathematical modelling, Qualitative resistance, Quantitative resistance, Zymoseptoria tritici
license: https://creativecommons.org/licenses/by/4.0/
date published: 2022-09-30
date modified: 2026-07-22T22:24:13Z
provider: Cambridge University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Cambridge

PropertyValue
property ID: DOI
value: 10.17863/CAM.93613