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ARS Home » Pacific West Area » Corvallis, Oregon » Forage Seed and Cereal Research Unit » Research » Publications at this Location » Publication #311085
Title: Evaluation of the ryegrass stem rust model STEMRUST_G and its implementation as a decision aid

Author
item Pfender, William
item COOP, L - Oregon State University
item Seguin, Sheila
item MELLBYE, M - Oregon State University
item GINGRICH, G - Oregon State University
item SILBERSTEIN, T - Oregon State University

Submitted to: Phytopathology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/24/2014
Publication Date: 1/1/2015
Citation: Pfender, W.F., Coop, L.B., Seguin, S.G., Mellbye, M.E., Gingrich, G.A., Silberstein, T.B. 2015. Evaluation of the ryegrass stem rust model STEMRUST_G and its implementation as a decision aid. Phytopathology. 105:35-44.

Interpretive Summary: STEMRUST_G, a simulation model for epidemics of stem rust in perennial ryegrass grown to maturity as a seed crop, was validated for use as a decision aid for disease management with fungicides. Model validation was by comparison of model output with observed disease severities in 35 epidemics at 9 location-years in the Pacific Northwest US. We judge the model acceptable for its purposes, based on several tests, including graphs of modeled disease progress that were similar with actual disease, and statistical tests of accuracy and reliability. An interactive web site, created using the model, estimates the level of latent (invisible) and visible disease since the last scouting observation, given season-long weather conditions up to the present, and estimates effects of fungicides on the disease process. In large-plot experiments in grower fields, the decision aid produced disease management outcomes (management cost and seed yield) as good as, or better than, the growers' standard practice. In future, STEMRUST_G could be modified to create similar models and decision aids for stem rust of wheat and barley.

Technical Abstract: STEMRUST_G, a simulation model for epidemics of stem rust in perennial ryegrass grown to maturity as a seed crop, was validated for use as an heuristic tool and as a decision aid for disease management with fungicides. Model validation was by comparison of model output with observed disease severities in 35 epidemics at 9 location-years in the Pacific Northwest US. We judge the model acceptable for its purposes, based on several tests. Graphs of modeled disease progress were generally congruent with plotted disease severity observations. There was negligible average bias in the 570 modeled-vs-observed comparisons across all data, although there was large variance in size of the deviances. Modeled severities were accurate in more than 80% of the comparisons, where accuracy is defined as the modeled value being within twice the 95% confidence interval of the observed value, within + 1 day of the observation date. An interactive web site, created using the model, estimates the level of latent (invisible) and expressed disease since the last scouting observation, given season-long weather conditions up to the present, and it estimates effects of fungicides on several aspects of the disease process. In large-plot experiments in grower fields, the decision aid produced disease management outcomes (management cost and seed yield) as good as, or better than, the growers' standard practice. In future, STEMRUST_G could be modified to create similar models and decision aids for stem rust of wheat and barley.