Literature DB >> 24848413

Governing principles can guide fungicide-resistance management tactics.

Frank van den Bosch1, Richard Oliver, Femke van den Berg, Neil Paveley.   

Abstract

Fungicide-resistance management would be more effective if principles governing the selection of resistant strains could be determined and validated. Such principles could then be used to predict whether a proposed change to a fungicide application program would decrease selection for resistant strains. In this review, we assess a governing principle that appears to have good predictive power. The principle states that reducing the product of the selection coefficient (defined as the difference between the per capita rate of increase of the sensitive and resistant strains) and the exposure time of the pathogen to the fungicide reduces the selection for resistance. We show that observations as well as modeling studies agree with the predicted effect (i.e., that a specific change to a fungicide program increased or decreased selection or was broadly neutral in its effect on selection) in 84% of the cases and that only 5% of the experimental results contradict predictions. We argue that the selection coefficient and exposure time principle can guide the development of resistance management tactics.

Keywords:  alternation; dose; exposure time; governing principle; mixture; resistance management; selection coefficient; spray timing; strategy; tactic

Mesh:

Substances:

Year:  2014        PMID: 24848413     DOI: 10.1146/annurev-phyto-102313-050158

Source DB:  PubMed          Journal:  Annu Rev Phytopathol        ISSN: 0066-4286            Impact factor:   13.078


  8 in total

1.  Extending the durability of cultivar resistance by limiting epidemic growth rates.

Authors:  Kevin Carolan; Joe Helps; Femke van den Berg; Ruairidh Bain; Neil Paveley; Frank van den Bosch
Journal:  Proc Biol Sci       Date:  2017-09-27       Impact factor: 5.349

2.  Dose and number of applications that maximize fungicide effective life exemplified by Zymoseptoria tritici on wheat - a model analysis.

Authors:  F van den Berg; N D Paveley; F van den Bosch
Journal:  Plant Pathol       Date:  2016-06-10       Impact factor: 2.590

3.  Improved Detection and Monitoring of Fungicide Resistance in Blumeria graminis f. sp. hordei With High-Throughput Genotype Quantification by Digital PCR.

Authors:  Katherine G Zulak; Belinda A Cox; Madeline A Tucker; Richard P Oliver; Francisco J Lopez-Ruiz
Journal:  Front Microbiol       Date:  2018-04-13       Impact factor: 5.640

Review 4.  Fungicide Resistance Evolution and Detection in Plant Pathogens: Plasmopara viticola as a Case Study.

Authors:  Federico Massi; Stefano F F Torriani; Lorenzo Borghi; Silvia L Toffolatti
Journal:  Microorganisms       Date:  2021-01-06

5.  Rapid in situ quantification of the strobilurin resistance mutation G143A in the wheat pathogen Blumeria graminis f. sp. tritici.

Authors:  Kejal N Dodhia; Belinda A Cox; Richard P Oliver; Francisco J Lopez-Ruiz
Journal:  Sci Rep       Date:  2021-02-25       Impact factor: 4.996

6.  The Evolution of Fungicide Resistance Resulting from Combinations of Foliar-Acting Systemic Seed Treatments and Foliar-Applied Fungicides: A Modeling Analysis.

Authors:  James L Kitchen; Frank van den Bosch; Neil D Paveley; Joseph Helps; Femke van den Berg
Journal:  PLoS One       Date:  2016-08-29       Impact factor: 3.240

7.  Agrichemicals and antibiotics in combination increase antibiotic resistance evolution.

Authors:  Brigitta Kurenbach; Amy M Hill; William Godsoe; Sophie van Hamelsveld; Jack A Heinemann
Journal:  PeerJ       Date:  2018-10-12       Impact factor: 2.984

8.  Low Amplitude Boom-and-Bust Cycles Define the Septoria Nodorum Blotch Interaction.

Authors:  Huyen T T Phan; Darcy A B Jones; Kasia Rybak; Kejal N Dodhia; Francisco J Lopez-Ruiz; Romain Valade; Lilian Gout; Marc-Henri Lebrun; Patrick C Brunner; Richard P Oliver; Kar-Chun Tan
Journal:  Front Plant Sci       Date:  2020-01-31       Impact factor: 5.753

  8 in total

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