Modelling the Relationship between Weather Variables and Yellow Stem Borer Population: A Count Data Modelling Approach

Aim: This study was conducted to model the relationship between discrete dependent variable (yellow stem borer population) and continuous weather variables.
 Data Description: The yellow (YSB) population standard meteorological week (SMW) wise variables (temperature, relative humidity, rainfall sunshine hours) data of Warangal centre (Telangana state) generated under All India Co-Ordinated Rice Improvement Project (AICRIP) from 2013-2021 were considered for study. YSB recorded daily using light trap with an incandescent bulb are counted as weekly cumulative catches.
 Methodology: trapped populations averages climatological inputs models consideration. In this classical linear regression i.e. step-wise multiple count such Poisson, negative binomial, zero inflated Poisson binomial employed.
 Result: empirical results revealed that viz., performed better compared regression, models, further outperformed all it yielded lowest mean square error (MSE) highest R2 values. average percentage reduction in accuracy zero-inflated over around 4 percent.
 Conclusion: Based on obtained study, is concluded performs they unable handle presence excess zeroes, a result provides more prediction lower Further, developed will be great assistance identifying factors influencing occurrence rice.