Optimal Resistance Management for Mixtures of High-Risk Fungicides: Robustness to the Initial Frequency of Resistance and Pathogen Sexual Reproduction.
Phytopathology
; 113(1): 55-69, 2023 Jan.
Article
en En
| MEDLINE
| ID: mdl-35881866
ABSTRACT
There is a strong consensus that selection for fungicide resistant pathogen strains can be most effectively limited by using applications of mixtures of fungicides designed to balance disease control against selection. However, how to do this in practice is not entirely characterized. Previous work indicates optimal mixtures of pairs of fungicides which are both at a high risk of resistance can be constructed using pairs of doses that select equally for both single resistant strains in the first year of application. What has not been addressed thus far is the important real-world case in which the initial levels of resistance to each fungicide differ, for example because the chemicals have been available for different lengths of time. We show how recommendations based on equal selection in the first year can be suboptimal in this case. We introduce a simple alternative approach, based on equalizing the frequencies of single resistant strains in the year that achieving acceptable levels of control is predicted to become impossible. We show that this strategy is robust to changes in parameters controlling pathogen epidemiology and fungicide efficacy. We develop our recommendation using a preexisting, parameterized model of Zymoseptoria tritici (the pathogen causing Septoria leaf blotch on wheat), which exemplifies the range of plant pathogens that predominantly spread clonally, but for which sexual reproduction forms an important component of the life cycle. We show that pathogen sexual reproduction can influence the rate at which fungicide resistance develops but does not qualitatively affect our optimal resistance management recommendation. [Formula see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Fungicidas Industriales
Tipo de estudio:
Etiology_studies
/
Guideline
/
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Phytopathology
Asunto de la revista:
BOTANICA
Año:
2023
Tipo del documento:
Article
País de afiliación:
Reino Unido