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Fungicide resistance risk assessment based on traits associated with the rate of pathogen evolution
Author(s) -
Grimmer Michael K,
van den Bosch Frank,
Powers Stephen J,
Paveley Neil D
Publication year - 2015
Publication title -
pest management science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.296
H-Index - 125
eISSN - 1526-4998
pISSN - 1526-498X
DOI - 10.1002/ps.3781
Subject(s) - fungicide , biology , resistance (ecology) , risk assessment , trait , quantitative trait locus , microbiology and biotechnology , predictive power , predictive value , toxicology , genetics , medicine , agronomy , gene , computer science , philosophy , computer security , epistemology , programming language
BACKGROUND A new fungicide resistance risk assessment method is described, based on traits (of pathogens, fungicides and agronomic systems) that are associated with rapid or slow occurrence of resistance. Candidate traits tested for their predictive value were those for which there was a mechanistic rationale that they could be determinants of the rate of resistance evolution. RESULTS A dataset of 61 European cases of resistance against single‐site‐acting fungicides was assembled. For each case, the number of years from product introduction to first detection of resistance (the FDR time) was quantified – varying from 2 to 24 years. Short and long predicted FDR times represent high and low resistance risk respectively. Regression analysis identified traits that were statistically associated with FDR time. A model combining these traits explained 61% of the variation in FDR time. Validation showed that this predictive power was highly unlikely to have occurred by chance. CONCLUSION Unlike previous methods, trait‐based risk assessment can be used to assess resistance risk for fungicides with new modes of action, when there is no prior knowledge of resistance behaviour. Risk predictions using the new method provide a more reliable basis for resistance management decisions. © 2014 Society of Chemical Industry

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