|Sharma-Poudyal, Dipak - WASHINGTON STATE UNIV|
Submitted to: APS Annual Meeting
Publication Type: Abstract Only
Publication Acceptance Date: April 1, 2008
Publication Date: June 1, 2008
Citation: Sharma-Poudyal, D., Chen, X. 2008. Development of models for improved prediction of stripe rust epidemics in the US Pacific Northwest. APS Annual Meeting. Phyto 98:S144. Technical Abstract: Epidemics of wheat stripe rust, caused by Puccinia striiformis f. sp. tritici, are primarily affected by winter temperatures in the US Pacific Northwest (PNW). Previous models based on temperatures of entire December and January did not provide accurate predictions for some years when the winter month temperatures did not follow the normal pattern. To develop models for more accurate predictions, we conducted regression analyses to determine the effects of average moving temperatures of 10, 20, 30, and 60 days on stripe rust epidemic using temperature and yield loss data of Pullman, WA from 1975 to 2007. In general, the correlation of the lowest average moving temperature of 20 days to yield losses was as good as that of the lowest average moving temperature of 60 days. However, for those years with unusual winter month temperatures, the 20-day model fit the observed value much better than the 60-day model. The new models predict yield losses rather than just disease severities for susceptible cultivars at the flowering stage, making them more useful in the disease management. These models guided us to use temperature factors to determine indices of winter and summer survival of the pathogen in various areas of the PNW, which may lead to geographic mapping of over-wintering and over-summering regions for the pathogen throughout the United States.