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Ecology and Epidemiology

Model for Predicting Severity of Septoria tritici Blotch on Winter Wheat. Stella Melugin Coakley, Associate research professor, Department of Biological Sciences, University of Denver (mail address: NCAR, P.O. Box 3000, Boulder, CO 80307); Larry R. McDaniel(2), and Gregory Shaner(3). (2)Research associate, Department of Biological Sciences, University of Denver (mail address: NCAR, P.O. Box 3000, Boulder, CO 80307); (3)Professor, Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN 47907. Phytopathology 75:1245-1251. Accepted for publication 15 May 1985. Copyright 1985 The American Phytopathological Society. DOI: 10.1094/Phyto-75-1245.

A statistical model was developed to predict severity of septoria tritici blotch (pathogen teleomorph: Mycosphaerella graminicola) on susceptible Monon winter wheat at the Purdue Agronomy Farm. Disease severity at adjusted Julian day 170 (which on the average was 17 June, 26 days after the average heading date of 22 May) was significantly correlated (P<0.05) with nine meteorological variables for the period between 2 March and 13 May. An equation was developed for predicting percent disease severity (ŷ) at adjusted Julian date 170 based on 1973-1984 data. The equation is ŷ = 147.480 - 3.025 X1 - 2.093 X2 (R2 = 0.86), in which X1 is the total consecutive days (8- 19 days) without precipitation between 26 March and 4 May, and X2 is the total consecutive days (12- 24 days) between 4 April and 3 May that minimum temperature was equal to or less than 7 C. Model selection and validation were based on the use of different regression analysis techniques, including Mallow's Cp statistic, Allen's PRESS statistic, and the variance inflation factor.

Additional keywords: data splitting, linear regression, multicollinearity, quantitative epidemiology, Septoria tritici, Septoria leaf blotch.