European Journal of Plant Pathology (2013) 137, 689-706

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Xiangming Xu, Laurence V. Madden, Simon G. Edwards, Fiona M. Doohan, Antonio Moretti, L. Hornok, P. Nicholson and A. Ritieni (2013)
Developing logistic models to relate the accumulation of DON associated with Fusarium head blight to climatic conditions in Europe
European Journal of Plant Pathology 137 (4), 689-706
Abstract: Fusarium head blight (FHB) of wheat, caused by several Fusarium species, is a damaging disease, resulting not only in yield reduction but also accumulation of mycotoxins in grain. Epidemiology and management of FHB has been extensively studied worldwide. Data on FHB development and accumulation of mycotoxins were obtained in four European countries during 2001-2004 to study the effect of FHB development and environmental conditions on accumulation of deoxynivalenol (DON). The occurrence of DON was highly correlated with presence of one or more toxigenic Fusarium species. Hourly weather data recorded at each sampling site were summarised over several periods of different lengths (5-30 days) during the anthesis and pre-harvest period. All-subsets regression was used to determine the extent to which the probability of DON occurrence is related to weather variables and also the consistency of such a toxin-weather relationship. Combined with a re-sampling technique, all-subsets regression analysis showed the difficulties in identifying a single 'best' model of relating the probability of toxin >90 μg kg−1 to weather predictors. A wide range of inter-related weather predictors based on time windows around anthesis and pre-harvest were selected in different models. There were many alternative models based on weather predictors only with similar predictive power because of high correlation among weather predictors. The performance of these alternative models was generally poor, particularly in terms of the high proportion of false positive predictions (specificity was only around 0.60-0.65). Inclusion of the number of toxigenic Fusarium species at harvest into models did not improve the model sensitivity (ca. 0.75-0.80) but appreciably improved the specificity (ca. 0.70-0.75). On balance, weather summarised over a 15-day window frame led to models with better predictions than other three window frames (5, 10 and 30 days).
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Database assignments for author(s): Xiang Ming Xu, Paul Nicholson, Fiona M. Doohan, Simon G. Edwards, Laurence V. Madden

Research topic(s) for pests/diseases/weeds:
population dynamics/ epidemiology


Pest and/or beneficial records:

Beneficial Pest/Disease/Weed Crop/Product Country Quarant.
Fusarium culmorum
Fusarium graminearum