Above multiple regression models were used for prediction of karnal bunt disease for the respective stations for the years 2012-13 and 2017-18 and statistically evaluated the percent deviation over the actual analyzed data. After development of regression equation for prediction of seed born karnal bunt fungal disease with the different weather parameters over the wheat crop during the rabi season (Table 5). The 6th to 12th SMWs were found the suitable and significant with the higher level of coefficient of determination or predictability. The 6th to 12th SMWs were found the suitable and significant with the higher level of coefficient of determination or predictability. Multiple regression model was developed using significant meteorological parameters during 6th to 12th SMW was developed for Sirsa, Karnal, Hisar and Bawal. The significant weather relations evaluated from 6 to 12 standard meteorological weeks at respective station in the state. The variability in occurrence of karnal bunt disease for Hisar zone was explained up to 79% with the help of weather parameters. The variability in occurrence of karnal bunt disease for Rewari zone was explained up to 92% with the help of weather parameters. The long term meteorological data base of four stations predictive regression model development for prediction of seed born karnal bunt fungal disease with the different weather parameters over the wheat crop during the rabi season.
Table 5: Observed and predicted Karnal bunt disease for Haryana state