VIEW ARTICLE

Ecology and Epidemiology

Statistical Models for Predicting Stripe Rust on Winter Wheat in the Pacific Northwest. Stella Melugin Coakley, Associate research professor, Department of Biological Sciences, University of Denver, Pullman, WA 99164, (mailing address: National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307); William S. Boyd(2), and Roland F. Line(3). (2)Research associate, Department of Biological Sciences, University of Denver, Pullman, WA 99164; (3)Research plant pathologist, Agricultural Research Service, U.S. Department of Agriculture, Pullman, WA 99164. Phytopathology 72:1539-1542. Accepted for publication 18 May 1982. Copyright 1982 The American Phytopathological Society. DOI: 10.1094/Phyto-72-1539.

Statistical models developed for predicting stripe rust (caused by Puccinia striiformis) on winter wheat cultivars Gaines, Nugaines, and Omar at Pullman, WA, also predicted disease intensity at four other locations (Lind, Mt. Vernon, and Walla Walla, WA; and Pendleton, OR) in the Pacific Northwest when the negative degree days data used to develop the models were first standardized (NDDZ). There was no significant difference between the measured mean disease intensity and the mean disease intensity predicted by the NDDZ model at any of the sites. Positive degree days accumulated at the sites partially explained the model’s small, but consistent, underprediction at Mt. Vernon and overprediction at Lind, Walla Walla, and Pendleton. The results demonstrate that a model for predicting disease intensity by using macrometeorological conditions can be useful at other locations within a synoptic weather region.