Laurence V. Madden, and
Simon G. Edwards
First author: State Key Laboratory of Crop Stress Biology in Arid Areas and College of Plant Protection, Northwest A&F University, Yangling, Shaanxi 712100, China, and Genetics and Crop Improvement, East Malling Research, New Road, East Malling, ME19 6BJ, UK; second author: Department of Plant Pathology, Ohio State University, Wooster 44691; and third author: Harper Adams University, TF10 8NB, Newport, Shropshire, UK.
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Accepted for publication 12 July 2013.
Fusarium head blight (FHB) of wheat and barley has been extensively researched worldwide; in contrast, there is limited information on the effects of environmental conditions on Fusarium toxin accumulation in oat grains. More than 300 samples of oat grain from various regions of the United Kingdom from 2006 to 2008 were analyzed for mycotoxin contamination due to infection by Fusarium spp. HT2 and T2 toxins were the two most commonly detected, and their concentrations in individual samples were highly correlated. Hourly weather data were obtained from meteorological recording stations near most of the sampling sites. Statistical modeling was applied to both the original toxin (HT2 plus T2) data and the toxin data adjusted for oat cultivars and number of cereal crops in the previous four seasons. Accumulation of HT2 and T2 toxin was positively correlated with warm and wet conditions during early May and dry conditions thereafter. Using a collection of 51 environmental variables summarized over three lengths (10, 15, and 20 days) of time periods encompassing early May, late May, and early July, all-subsets regression showed that many models, consisting of three to six predictor variables, could be identified with similar explanatory strength for the effect of environmental conditions on toxin accumulation. Most important predictor variables were related to wet conditions during the early-May period, which was before anthesis. These results suggest that the predominant period for Fusarium langsethiae infection of oat is likely to be before rather than during anthesis, as for other head blight pathogens. These empirical models may be further improved by using quantified pathogen biomass within the grains and weather predictor variables summarized in relation to plant growth stages (instead of calendar times).
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