Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Pest Management Scie...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Pest Management Science
Article . 2024 . Peer-reviewed
License: CC BY NC
Data sources: Crossref
https://doi.org/10.1101/2023.0...
Article . 2023 . Peer-reviewed
Data sources: Crossref
versions View all 3 versions
addClaim

Workflows for detecting fungicide resistance in net form and spot form net blotch pathogens

Authors: Noel L. Knight; Kul C. Adhikari; Kejal N. Dodhia; Wesley J. Mair; Francisco J. Lopez‐Ruiz;

Workflows for detecting fungicide resistance in net form and spot form net blotch pathogens

Abstract

Abstract BACKGROUND Fungicide resistance in Pyrenophora teres f. maculata and P. teres f. teres has become an important disease management issue. Control of the associated barley foliar diseases, spot form and net form net blotch, respectively, relies on three major groups of fungicides, demethylation inhibitors (DMIs), succinate dehydrogenase inhibitors (SDHIs) and quinone outside inhibitors (QoIs). However, resistance has been reported for the DMI and SDHI fungicides in Australia. To enhance detection of different resistance levels, phenotyping and genotyping workflows were designed. RESULTS The phenotyping workflow generated cultures directly from lesions and compared growth on discriminatory doses of tebuconazole (DMI) and fluxapyroxad (SDHI). Genotyping real‐time polymerase chain reaction (PCR) assays were based on alleles associated with sensitivity or resistance to the DMI and SDHI fungicides. These workflows were applied to spot form and net form net blotch collections from 2019 consisting predominantly of P. teres f. teres from South Australia and P. teres f. maculata from Western Australia. For South Australia the Cyp51A L489‐3 and SdhC ‐R134 alleles, associated with resistance to tebuconazole and fluxapyroxad, respectively, were the most prevalent. These alleles were frequently found in single isolates with dual resistance. This study also reports the first detection of a 134 base pair insertion located at position‐66 (PtTi‐6) in the Cyp51A promoter of P. teres f. maculata from South Australia. For Western Australia, the PtTi‐1 insertion was the most common allele associated with resistance to tebuconazole. CONCLUSION The workflow and PCR assays designed in this study have been demonstrated to efficiently screen P. teres collections for both phenotypic and genetic resistance to DMI and SDHI fungicides. The distribution of reduced sensitivity and resistance to DMI and SDHI fungicides varied between regions in south‐western Australia, suggesting the emergence of resistance was impacted by both local pathogen populations and disease management programmes. The knowledge of fungicide resistance in regional P. teres collections will be important for informing appropriate management strategies. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Related Organizations
Keywords

Ascomycota, Amides, Fungicides, Industrial, Workflow, Plant Diseases

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    6
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
hybrid