@ARTICLE{Litschmann_Tomas_A_2020, author={Litschmann, Tomas and Hausvater, Ervin and Dolezal, Petr}, volume={vol. 60}, number={No 2}, journal={Journal of Plant Protection Research}, pages={134-140}, howpublished={online}, year={2020}, publisher={Committee of Plant Protection PAS}, publisher={Institute of Plant Protection – National Research Institute}, abstract={This study describes a newly developed index for predicting and forecasting the first (and potentially subsequent) timing of fungicide application against late blight in potato crops based on weather variables measured close to the crop. Inputs for index calculation were the following: daily minimum temperature, mean relative air humidity and daily precipitation. The decisive moment in the process of forecasting is the sum of daily index values for the previous 5 days. The index was tested in various localities of the Czech and the Slovak Republics for several years with a relatively high success rate exceeding the accuracy of previously applied strategies – NoBlight and negative prognosis. In comparison to the mentioned methods, the calculated index corresponded very well to long-term wet periods and indicated the first application date correctly. In years with no wet periods (in this case, 2015 and 2017), it allowed postponing the first application and reducing the number of required sprays during the growing season. The method does not depend on determining the emergence date, so it can be presented on the internet without cooperation with specific growers in a given locality, and thus supply information for a wider range of users. With knowledge about crop development and the degree of resistance to late blight of grown varieties, users can subsequently choose a specific fungicide and its application date.}, type={Article}, title={A new method of potato late blight forecasting in the Czech Republic}, URL={http://czasopisma.pan.pl/Content/116464/PDF/x_AO_02_JPPR_60_2_440_Litschman.pdf}, doi={10.24425/jppr.2020.133306}, keywords={comparison using methods, forecasting models, late blight, Phytophthora infestans, potato}, }