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Hydrothermal time models for conidial germination and mycelial growth of the seed pathogen Pyrenophora semeniperda

  • Connor W. Barth
    ,
  • Susan E. Meyer(corresponding author)
    ,
  • ,
  • Phil S. Allen
*Corresponding author for this work
  • Rocky Mountain Research Station, USDA Forest Service
    ,
  • ,
  • Brigham Young University
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Abstract

Population-based threshold models using hydrothermal time (HTT) have been widely used to model seed germination. We used HTT to model conidial germination and mycelial growth for the seed pathogen Pyrenophora semeniperda in a novel approach to understanding its interactions with host seeds. Germination time courses and mycelial growth rates for P.semeniperda were measured on PDA amended to achieve a series of five water potentials (ca. 0 to -6MPa) at six constant temperatures (5-30°C). Conidial germination was described with alternative population-based models using constant or variable base and maximum temperature and water potential parameters. Mycelial growth was modeled as a continuous, linear process with constant base temperature and base water potential. Models based on HTT showed reasonable fit to germination and growth rate data sets. The best-fit conidial germination model (R2=0.859) was based on variable base and maximum temperature as a function of water potential. The good fit of the linear mycelial growth model (R2=0.916) demonstrated the utility of HTT for modeling continuous as well as population-based processes. HTT modeling may be a useful approach to the quantification of germination and growth processes in a wide range of filamentous fungi.

Bibliographic Information

Output type

Research Output:
Contribution to journal
Article
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 720-730 (11 pages)

Journal (Volume, Issue Number)

Fungal Biology (Volume 119, Issue 8)

Publication milestones

  • Published - 01/08/2015

Publication status

Published - 01/08/2015

ISSN

1878-6146

Publication IDs

  • Scopus: 84937975220
  • PubMed: 26228560