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.