CONCLUSIONS
The result concluded that among the station, over all predictability ranging and higher predictability were explained at Sirsa station, under semi-arid agroclimatic condition of western Haryana. 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 6thto 12th SMW was developed for Sirsa, Karnal, Hisar and Bawal. 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 therabi season. Among the station, over (+/positive) and under predictability (-ve/negative) percent deviation in the semi-arid, arid, humid and per humid agroclimatic condition of Haryana.