FORECASTING AND MODELING OF SUCKING INSECT COMPLEX OF COTTON UNDER AGRO-ECOSYSTEM OF MULTAN- PUNJAB, PAKISTAN

Weather plays a critical role in population fluctuation of insects. pests forecasting is one of the best methods for monitoring and management of deleterious insects where pest management cost is very high. to develop pests forecasting model five years pests data was recorded by pests warning and quality control of pesticides department of agriculture, govt. of punjab, multan in different locations of district multan during 2006-2010. the correlation between weather and sucking insect pests was summarized on the basis of multivariate regression and correlation analysis tactics. mean comparison of population averages of insects was undertaken i.e., jassid (amrasca bigutulla bigutulla), whitefly (bemisia tabaci), thrips (thrips tabaci), cotton mealybug (phenacoccus solenopsis), dusky cotton bug (oxycarenus laetus) and cotton leaf curl virus (clcuv). the results suggested that relative humidity alone exhibited positive correlation with all mentioned insects. cotton mealy bug population increased steadily from 2006-2008 and then declined due to changing in environmental factors. whereas dusky cotton bug resurgence as a new pest on cotton crop was examined. regression analysis revealed that maximum temperature showed negative linear relation with whitefly population having 5.9 to 21.6% role. rainfall showed negative linear regression with jassid population having 1.3 to 3.4 % impact.