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A Simulation Model for Epidemics of Stem Rust in Ryegrass Seed Crops

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Title A Simulation Model for Epidemics of Stem Rust in Ryegrass Seed Crops
Names Pfender, W. F. (creator)
Upper, D. (creator)
Date Issued 2015-01 (iso8601)
Note To the best of our knowledge, one or more authors of this paper were federal employees when contributing to this work. This is the publisher’s final pdf. The article was published by the American Phytopathological Society and is in the public domain. The published article can be found at: http://apsjournals.apsnet.org/loi/phyto.
Abstract A simulation model (STEMRUST_G, named for stem rust of grasses)
was created for stem rust (caused by Puccinia graminis subsp.
graminicola) in perennial ryegrass grown to maturity as a seed crop. The
model has a daily time step and is driven by weather data and an initial
input of disease severity from field observation. Key aspects of plant
growth are modeled. Disease severity is modeled as rust population
growth, where individuals are pathogen colonies (pustules) grouped in
cohorts defined by date of initiation and plant part infected. Infections
due to either aerial spread or within-plant contact spread are modeled.
Pathogen cohorts progress through life stages that are modeled as disease
cycle components (colony establishment, latent period, infectious period,
and sporulation) affected by daily weather variables, plant growth, and
fungicide application. Fungicide effects on disease cycle components are
modeled for two commonly used active ingredients, applied preinfection
or postinfection. Previously validated submodels for certain disease cycle
components formed the framework for integrating additional processes,
and the complete model was calibrated with field data from 10 stem rust
epidemics. Discrepancies between modeled outcomes and the calibration
data (log₁₀[modeled] – log₁₀[observed]) had a mean near zero but considerable
variance, with 1 standard deviation = 0.5 log₁₀ units (3.2-fold).
It appears that a large proportion of the modeling error variance may be
due to variability in field observations of disease severity. An action
threshold for fungicide application was derived empirically, using a
constructed weather input file favorable for disease development. The
action threshold is a negative threshold, representing a level of disease
(latent plus visible) below which damaging levels of disease are unable to
develop before the yield-critical crop stage. The model is in the public
domain and available on the Internet.
Genre Article
Topic Azoxystrobin
Identifier Pfender, W. F., & Upper, D. (2015). A Simulation Model for Epidemics of Stem Rust in Ryegrass Seed Crops. Phytopathology, 105(1), 45-56. doi:10.1094/PHYTO-03-14-0068-R

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