Title:
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Temperature relations of Leptosphaeria species on oilseed rape and their implications for forecasting
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This thesis uses a published model of phoma stem canker of oilseed rape as a case study to
investigate some aspects of unreliability in disease prediction models and their application
to predict climate change effects on disease.
The published model had four stages, predicting the threshold date for fungicide spray
(10% of plants with phoma leaf spots), the onset of stem canker symptoms, the final
disease severity pre-harvest and yield loss. For each stage the regression model was linear.
In order to accurately represent disease progress, linear disease models require a linear
relationship between fungal development and the predictive variables used.
Response to temperature was investigated in vitro and in plonto for the two pathogens
involved in phoma stem canker. In vitro the radial growth rate was linear across the range
of temperatures commonly experienced by crops in the UK. In planta, however, the
reaction norm for canker severity caused by the more aggressive pathogen, L. maculans,
suggested that it had a lower temperature optimum close to the present highest daily
mean temperatures in the UK. In planta results for the less aggressive L. biglobosa were
inconclusive.
Internal basal stem temperatures were monitored in oilseed rape crops. The temperature
experienced by the fungus during canker development at the base of the stem is buffered
from the extremes of air temperature and is dependent on plant growth stage.
An exploration of predictions versus observed disease data for recent years was made.
This revealed the model's inability, in its present form, to make accurate predictions in
years with unusual rain patterns during summer and autumn and in the presence of
modern resistant cultivars.
The implications for model accuracy of predicting disease in future climates for the UK in
the 2020s, 2050s and 2080s are discussed.
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