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