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Ecology and Epidemiology

Regional 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 (mailing address: National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307); Roland F. Line(2), and William S. Boyd(3). (2)Research plant pathologist, Agricultural Research Services, U.S. Department of Agriculture, Pullman, WA 99164; (3)Research associate, Department of Biological Sciences, University of Denver (mailing address: National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307). Phytopathology 73:1382-1385. Accepted for publication 12 April 1983. Copyright 1983 The American Phytopathological Society. DOI: 10.1094/Phyto-73-1382.

Statistical models were developed for predicting stripe rust (caused by Puccinia striiformis) on winter wheat cultivars Gaines, Nugaines, and Omar at Lind, Pullman, and Walla Walla, WA, and Pendleton, OR, in the Pacific Northwest. Two regional models were developed for each cultivar based on the relationship of disease intensity index to standardized negative degree days (NDDZ) accumulated during December and January, the Julian day of spring (JDS) (defined as the date when 40 or more positive degree days [PDD] had accumulated during the following 14 days) and PDD for the 80-day period after the JDS. The first model, which used NDDZ and JDS as independent variables, can be used in early spring to make disease intensity index predictions. Such predictions are needed to enable timely spring management decisions. The second model, which adds PDD as an independent variable, increases the accuracy of the prediction, but allows less time for managerial decisions. The accuracy of the models was verified in two tests by randomly removing the equivalent of two years’ data, reformulating the models from the remaining data, and using the new model to compare actual recorded disease and predicted disease. The predicted disease intensity index was within one standard error of the actual recorded disease index 70% of the time when NDDZ and JDS were used as independent variables. Incorrect predictions often occurred during years when spring conditions were unusually favorable or unfavorable for disease development. These predictions could be corrected by adding the PDD variable. With background knowledge of a region, predictions of disease intensity index in that region could be made with only meteorological data. The regional model was also used to predict stripe rust at a fifth site (Mt. Vernon, WA) which is in the far northwest corner of the Pacific Northwest and was not included in the development of the models.

Additional keywords: linear regression, quantitative epidemiology.