# Table 2 Multiple linear regression models along with coefficients of determination (R2) regarding the impact of weather parameters on the seasonal abundance of different insect pests of betel leaf

Name of the insectRegression equationR2100R2% Role of individual factorF statistic
Black flyY = − 16.438 + 1.082X10.54754.754.7F1,10 = 12.09, P < 0.01
Y = 2.190 + 1.075X1− 0.227X20.57057.03.7F2,9 = 5.97, P < 0.05
Y = − 14.675 + 1.222X1− 0.057X2− 0.006X30.57957.90.9F3,8 = 3.67, P < 0.10
White flyY = − 12.201 + 0.726X10.34334.334.3F1,10 = 5.21, P < 0.05
Y = 31.610 + 0.710X1− 0.509X20.50350.316.0F2,9 = 4.56, P < 0.05
Y = 20.288 + 0.809X1− 0.395X2− 0.004X30.50950.90.6F3,8 = 2.76, P < 0.10
Red spider miteY = − 9.342 + 0.671X10.33933.933.9F1,10 = 5.12, P < 0.05
Y = 30.813 + 0.655X1− 0.489X20.51051.017.1F2,9 = 4.69, P < 0.05
Y = 2.843 + 0.725X1− 0.408X2− 0.003X30.51351.30.3F3,8 = 2.82, P < 0.10
Mealy bugY = − 10.008 + 0.645X10.36336.336.3F1,10 = 5.70, P < 0.05
Y = 27.265 + 0.630X1-0.454X20.53553.517.2F2,9 = 5.18, P < 0.05
Y = 1.223 + 0.683X1− 0.393X2− 0.002X30.53753.70.2F3,8 = 3.10, P = 0.089
1. Y = insect population/vine; X1 = average temperature (°C); X2 = relative humidity (%); X3 = average rainfall (mm)