| Summary: | The objective of the study was to design a prediction model for eyespot (Tapesia yallundae) infection based on climatic factors (temperature, precipitation, air humidity). Data from experiment years 1994-2002 were used to study correlations between the eyespot infection index and individual weather characteristics. The model of prediction was constructed using multiple regression when a separate parameter is assigned to each factor, i.e. the frequency of days with optimum temperatures, humidity, and precipitation. The correlation between relative air humidity and precipitation and the infection index is significant.
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