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

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.