Our People: Paul Lab

Biology, epidemiology, and integrated management of corn and wheat diseases

Paul LabProgram Areas

Fusarium head blight (FHB) of wheat; strength and importance of a within-field source of inoculum (surface residue) for FHB development under conditions of high background (air-blown) inoculum levels; the role of surface residue on the development of FHB is influenced by year-to-year variation in weather conditions; weather-related factors on FHB inoculum buildup and dissemination within wheat canopy; integrated disease management strategies for FHB; disease resistance and fungicide use on FHB, powdery mildew, and Stagonospora blotch of wheat.

Also: disease forecasting system for FHB of wheat; characterization of the resistance of commonly-cultivated corn hybrids to northern corn leaf blight (NCLB); determination of the race structure of the NCLB pathogen in Ohio; and development of risk-based management decision-making tools for foliar diseases of corn (gray leaf spot and northern corn leaf blight) and wheat (Stagonospora blotch and powdery mildew).

My general interest is epidemiology and integrated management of plant diseases, with emphasis on understanding the basic biology and ecology of plant pathogens and the use of this information to develop disease management tools for practical application. I am particularly interested in the use of statistical and computer models to describe plant disease dynamics in the field and the use of these models to make disease management decisions based on risk assessment and disease prediction.

An understanding of the basic biology and ecology of plant pathogens is indispensable for effective disease management through disease prediction and risk assessment. Basic research has to be an ongoing process if we are to understand the effects of changing weather patterns, shifts in pathogen populations, genetic manipulation of crops, and changes in cropping practices on the appearance of new and resurgence of existing plant diseases. I hope to use statistical and computer models to describe the effects and anticipate possible consequences of these changes on disease development and crop yield. I would like to take advantage of modern statistical techniques, sophisticated computer technology, large weather database, and fast and efficient information delivery systems to development and use prediction and risk assessment models as decision-making tools in integrated disease management programs.