Web enabled and weather based forewarning of yellow stem borer [scirpophaga incertulas (Walker)] and leaf folder [cnaphalocrcis medinalis (guenee)] for different rice growing locations of india

Abstract

Loss in yield and quality of crop produce due to pest infestation could be reduced considerably if the pest occurrence is known in advance and timely remedial measures are taken. Weather plays an important role in pest development. Therefore, weather based models can be an effective scientific tool for forewarning pests in advance. In this study, weather based forewarning models have been developed for yellow stem borer [Scirpophaga incertulas(Wa\ker)] and leaf folder [Cnaphalocrocis medinalis(Guenee)] of rice for different locations, viz., Aduthurai (Tamil Nadu), Chinsurah (West Bengal), Karjat (Maharashtra), Mandya (Karnataka), Ludhiana (Punjab) and Raipur (Chhattisgarh). The pest data comprised of population of yellow stem borer and leaf folder moths caught in light trap per week for different locations. Weather data relating to maximum and minimum temperature (°C), morning and evening relative humidity (%) and rainfall (mm) in respect of the locations were obtained from the meteorological observatories of the locations per se. Data of pest and weather on weekly basis in respect of Kharif and Rabi seasons of 11 years (2000-2010) for all locations, and of 16 years (1995-2010) for Mandya (KA) were used for developing the forewarning models. Weather of six lag weeks from week of forecast were used for development of weather indices. These weather indices were used as independent variables in model building against the pest population as dependent variables. Stepwise regression models for predicting the yellow stem borer population for peak periods of occurrence during Kharif [Aduthurai (TN), Karjat (MH) & Raipur (CG)] and Rabi [Chinsurah (WB) & Mandya (KA)] were developed with R2 > 0.9. Prediction of leaf folder for different weeks of Kharif for Aduthurai (TN) (32-35 SMW) and Ludhiana (PB) (32-36 SMW) and of Rabi for Aduthurai (TN) (44-47 SMW) gave R2 between 0.6 and 0.8, respectively indicating better leaf folder prediction for Rabi over Kharif season at Aduthurai (TN). Validation of the models for subsequent years (2011) has been done for all cases. These developed models were converted into web-based forewarning system using 3-tier architecture. Net Beans 8.0.1 IDE (Integrated Development Environment), MS SQL Server, Java Server Pages (JSP) technologies have been used for the development of the web enabled forecasting of the two rice pests.