Title :
Weather Based Prediction of Pests in Cotton
Author :
Raghavendra, K.V. ; Bhupal Naik, D.S. ; Venkatramaphanikumar, S. ; Kumar, S. Deva ; Rama Krishna, S.V.
Author_Institution :
Dept. of Comput. Sci. & Eng., Vignan´s Found. for Sci., Technol. & Res., Guntur, India
Abstract :
The research work is focused to study the influence of weather parameters on the incidence of pests on cotton from the period 2006 to 2010 at Acharya N. G. Ranga Agricultural University, Lam farm, Guntur. Multiple Linear Regression (REG) and Generalized Linear Model (GLM) techniques are used to analyze the pooled pest´s data statistically along with weather parameters by SAS (Statistical Analysis System). The regression equations were developed for cotton pest using multiple linear regression models. The comparative study has been made for identifying the coefficient of determination (R2) which remains same for all kinds of pests when both REG procedure and GLM procedure models were fitted. The total influence of all the weather parameters was significant on thrips and while it was non-significant on jassid, aphids and whitefly.
Keywords :
crops; regression analysis; GLM procedure; REG procedure; SAS; aphids; cotton pest; generalized linear model technique; jassid; multiple linear regression models; pooled pest data analysis; regression equations; statistical analysis; statistical analysis system; weather based prediction; weather parameters; whitefly; Cotton; Equations; Mathematical model; Meteorology; Sociology; Statistics; Aphids; Correlation; Cotton; GLM Procedure; Jassid; REG Procedure; Thrips; Weather parameters; White Fly;
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2014 International Conference on
Print_ISBN :
978-1-4799-6928-9
DOI :
10.1109/CICN.2014.129
