Evaluation of the temporal distribution of Fusarium graminearum airborne inoculum above the wheat canopy and its relationship with Fusarium head blight and DON concentration

Abstract

With the aim of unravelling the role of airborne Fusarium graminearum inoculum in the epidemic of Fusarium head blight (FHB) caused by this species in wheat spikes, a network of Burkard air samplers was set up in five wheat fields distributed in Belgium from 2011 to 2013. Each year from April to July, the daily amounts of F. graminearum inoculum above the wheat canopy were quantified using a newly developed TaqMan qPCR assay. The pattern of spore trapping observed was drastically different per year and per location with a frequency of detection between 9 and 66% and a mean daily concentration between 0.8 and 10.2 conidia-equivalent/m3. In one location, air was sampled for a whole year. Inoculum was frequently detected from the wheat stem elongation stage until the end of the harvesting period, but high inoculum levels were also observed during the fall. Using a window-pane analysis, different periods of time around wheat flowering (varying in length and starting date) were investigated for their importance in the relation between airborne inoculum and FHB parameters (FHB severity, frequency of F. graminearum infection and DON). For almost all the combinations of variables, strong and significant correlations were found for multiple window lengths and starting times. Inoculum quantities trapped around flowering were highly correlated with F. graminearum infection (up to R = 0.84) and DON (up to R = 0.9). Frequencies of detection were also well correlated with both of these parameters. DON concentrations at harvest could even be significantly associated with the F. graminearum inoculum trapped during periods finishing before the beginning of the anthesis (R = 0.77). Overall, these results highlight the key role of the airborne inoculum in F. graminearum epidemics and underline the importance of monitoring it for the development of disease forecasting tools.