Improving fungal disease forecasts in winter wheat: A critical role of intra-day variations of meteorological conditions in the development of Septoria leaf blotch

Meteorological conditions are important factors in the development of fungal diseases in winter wheat and are the main inputs of the decision support systems used to forecast disease and thus determine timing for efficacious fungicide application. This study uses the Fourier transform method (FTM) to characterize temporal patterns of meteorological conditions between two neighbouring experimental sites used in a regional fungal disease monitoring and forecasting experiment in Luxembourg. Three meteorological variables (air temperature, relative humidity, and precipitation) were included, all conducive to infection of wheat by Zymoseptoria tritici cause of Septoria leaf blotch (STB) in winter wheat, from 2006 to 2009. The intraday, diurnal, dekadal and intra-seasonal variations of the meteorological variables were assessed using FTM, and the impact of existing contrasts between sites on the development of STB was analyzed. Although STB severities varied between sites and years (P ≤ 0.0003), the results indicated that the two sites presented the same patterns of meteorological conditions when compared at larger temporal scales (diurnal to intra-seasonal scales, with time periods >11 h). However, the intraday variations of all the variables were well discriminated between the sites and were highly correlated to STB severities. Our findings highlight and confirm the importance of intraday meteorological variation in the development of STB in winter wheat fields. Furthermore, the FTM approach has potential for identifying microclimatic conditions prevailing at given sites and could help in improving the prediction of disease forecast models used in regional warning systems.