ArticleJournal of plant diseases and protection : scientific journal of the German Phytomedical Society (DPG)2024
Assessing the predictability of fungicide resistance evolution through in vitro selection.
Article in Journal of plant diseases and protection : scientific journal of the German Phytomedical Society (DPG), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- The dual role of azoles: lifesaving antifungals and drivers of resistance - a One Health perspective.Nature communications · 2026Review
- Article
- Wound-dependent infection byFrontiers in plant science · 2025Article
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Authors and funding
1 author.
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Abstract
Plant pathogens are highly adaptable, and have evolved to overcome control measures including multiple classes of fungicides. More effective management requires a thorough understanding of the evolutionary drivers leading to resistance. Experimental evolution can be used to investigate evolutionary processes over a compressed timescale. For fungicide resistance, applications include predicting resistance ahead of its emergence in the field, testing potential outcomes under multiple different fungicide usage scenarios or comparing resistance management strategies. This review considers different experimental approaches to in vitro selection, and their suitability for addressing different questions relating to fungicide resistance. When aiming to predict the evolution of new variants, mutational supply is especially important. When assessing the relative fitness of different variants under fungicide selection, growth conditions such as temperature may affect the results as well as fungicide choice and dose. Other considerations include population size, transfer interval, competition between genotypes and pathogen reproductive mode. However, resistance evolution in field populations has proven to be less repeatable for some fungicide classes than others. Therefore, even with optimal experimental design, in some cases the most accurate prediction from experimental evolution may be that the exact evolutionary trajectory of resistance will be unpredictable.
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