D. E. Te Beest,
N. D. Paveley,
M. W. Shaw, and
F. van den Bosch
First and fourth authors: Biomathematics and Bioinformatics department, Rothamsted Research, Harpenden, Hertfordshire, AL5 2 JQ, UK; second author: ADAS High Mowthorpe, Duggleby, Malton, North Yorkshire, YO17 8BP, UK; and third author: School of Biological Sciences, University of Reading, Reading RG6 6AS, UK.
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Accepted for publication 8 January 2008.
Key weather factors determining the occurrence and severity of powdery mildew and yellow rust epidemics on winter wheat were identified. Empirical models were formulated to qualitatively predict a damaging epidemic (>5% severity) and quantitatively predict the disease severity given a damaging epidemic occurred. The disease data used was from field experiments at 12 locations in the UK covering the period from 1994 to 2002 with matching data from weather stations within a 5 km range. Wind in December to February was the most influential factor for a damaging epidemic of powdery mildew. Disease severity was best identified by a model with temperature, humidity, and rain in April to June. For yellow rust, the temperature in February to June was the most influential factor for a damaging epidemic as well as for disease severity. The qualitative models identified favorable circumstances for damaging epidemics, but damaging epidemics did not always occur in such circumstances, probably due to other factors such as the availability of initial inoculum and cultivar resistance.
Additional keywords:Blumeria graminis f. sp. tritici, climate change, data mining, epidemiology, Puccinia striiformis.
© 2008 The American Phytopathological Society