Weather based prediction model for green leafhopper (GLH), Nephotettix virescens distant of rice in middle gangetic plains

The GLH Nephotettix virescens Distant occurrence began to increase during the 33^rd SMW (3.0 GLH/15 sweeps) and peaked during the 40^th SMW (19 GLH/15 sweeps). The GLH sweep net catches revealed maximum and significant positive correlation with sun shine hours of current week, and showed a significant negative correlation with evening relative humidity and wind speed of 2-lag week and current week. On the other hand, GLH catches revealed a positive correlation with maximum temperature and morning relative humidity of current, 1-lag as well as 2-lag week. Minimum temperature and rainfall of current, 1-lag, 2-lag week and current, 1-lag week, respectively, were negatively correlated with GLH catches. T_max, T_min, and SSH were found to be the most significant weather influences that affected GLH sweep net catches. With pest and weather data obtained during Kharif 2019, the model was validated (R² = 0.92, RSME = 0.218, and MAE = 0.303).