Grabow, Bethany2016-07-222016-07-222016-08-01http://hdl.handle.net/2097/32835Stripe rust (caused by Puccinia striiformis f. sp. tritici) and leaf rust (caused by Puccinia triticina) are the top two diseases of winter wheat (Triticum aestivum) with a 20-year average yield loss of 4.9% in Kansas. Due to the significant yield losses caused by these diseases, the overall objective of this research was to identify environmental variables that favor stripe and leaf rust epidemics. The first objective was to verify the environmental conditions that favor P. triticina infections in an outdoor field environment. Wheat was inoculated with P. triticina and exposed to ambient weather conditions for 16 hours. Number of hours with temperature between 5 to 25°C and relative humidity >87% were highly correlated and predicted leaf rust infections with 89% accuracy. The results of this outdoor assay were used to develop variables to evaluate the association of environment with regional leaf rust epidemics. Before regional disease models can be developed for a forecast system, suitable predictors need to be identified. Objectives two and three of this research were to identify environmental variables associated with leaf rust and stripe rust epidemics and to evaluate these predictors in models. Mean yield loss on susceptible varieties was estimated for nine Kansas crop reporting districts (CRD’s). Monthly environmental variables were evaluated for association with stripe rust epidemics (>1% yield loss), leaf rust epidemics (>1% yield loss), severe stripe rust epidemics (>14% yield loss) and severe leaf rust epidemics (>7% yield loss) at the CRD scale. Stripe rust and leaf rust epidemics were both strongly associated with soil moisture conditions; however, the timing differed between these diseases. Stripe rust epidemics were associated with soil moisture in fall and winter, and leaf rust epidemics during winter and spring. Severe stripe rust and leaf rust epidemics were associated with favorable temperature (7 to 12°C) and temperature (15 to 20°C) with relative humidity (>87%) or precipitation in May using tree-based methods of classification, respectively. The preliminary models developed in this research could be coupled with disease observations and varietal resistance information to advise growers about the need for foliar fungicides against these rusts in Kansas winter wheat.en-USEpidemiologyFungiDisease modelingWheatLeaf rustStripe rustDissertation