Research on Rice based Cropping systems
In India rice is grown in 43.7 m ha with a production of 92 m t and a productivity of 2.1 tonnes ha-1 of which, rainfed rice is grown in 22.5 m ha (ca 50%) with a productivity of about 1 tonne ha-1. Pest outbreaks are common in rice growing regions, which result in 20-50% yield loss. About 18% of the total pesticide consumption in the country is in rice. Prevalent cropping systems and associated weather in the region influence the pest population dynamics to a greater extent. In this context, a detailed study of the prevailing agro-ecosystems will help to understand the ecological processes that are in operation. There is a research gap in integrating this knowledge on cropping systems and weather in the form of models for forecasting the timing and intensity of pest attacks. In the sub-project three major irrigated rice and two rainfed rice based cropping systems have been selected for study at six locations targeting four major insect pests for generating information required for the development of a DSS.

Research on Cotton based Cropping systems

India has more acreage in cotton than any other country, about 9.5 m ha, but the yields are among the lowest in the world- about 503 kg lint ha-1. Cotton cultivation in the country has been revolutionised with the introduction and release of Bt-cotton for commercial cultivation in the country in the year 2002. The coverage of this new technology has been spectacular (0.038 m ha in 2002 to 5.5 m ha in 2007-08, 58% area). The number of Bt-cotton hybrids permitted by GEAC now stands at 134 (cf 3 hybrids in 2002). A rapidly changing pest scenario in cotton is being witnessed with the advent of Bt-cotton. While the target pest, American bollworm, has been reduced substantially, new pest problems have cropped up and are spreading quickly to all the cotton growing areas. The cases of mealy bug and mirid bug menace in cotton are testimonies to this trend. Therefore, there is an urgent need to generate research data on the dynamics of emerging pests in a holistic manner and develop models that can predict the timing and likely pest intensity along with decision support systems for their effective management. In the sub-project three major cotton based cropping systems have been selected for study at four locations targeting four major insect pests.

Cotton and Rice account for nearly 70% of the pesticides used in the country. The decline in the natural enemy composition in rice ecosystem by 3.5 times and in cotton ecosystem by 12 times clearly indicates the ill effects of pesticides. Knowledge and information is the key to judicious pest management decisions, which can lead to rational use of pesticides. Integrated Pest Management is a system that emphasizes appropriate decision-making and depends heavily on accurate and timely information for field implementation by practitioners. Forecast of pests is an important component of the broad IPM philosophy. Past data sets on crop-pest-disease-weather relations will be used in development of a usable database. The sub project involves field studies in two major cropping systems: rice-based and cotton-based cropping systems for development of pest forewarning models based both on biological and ecological processes. The rice-based cropping systems include rice-ricepulse, rice-wheat and rice-rice-rice systems targeting stem borer, brown plant hopper, and white backed plant hopper and leaf folder. The cotton based cropping systems include cotton + pigeonpea/fallow, cotton-wheat and cotton-groundnut/maize sequence targeting mealy bug, mirid bugs, pink bollworm and Helicoverpa bollworm. These field studies will result in generating information on off-season survival, pest-carry over on alternate hosts and pestnatural enemy interactions. Complementing field studies, laboratory experiments under controlled environmental conditions will generate data on developmental growth rates for mealy bug and mirid bugs in cotton; WBPH and leaf folder in rice. These studies will lead to insect phenology models for estimating the timing of pest attack. Extrapolation of model results over larger areas is possible through remote sensing techniques. First, generation of spectral library using hand held spectro-radiometer for crop damage due to insect pests will aid in developing pest specific vegetation indices which in turn leads to area-wide crop condition assessment using space borne remote sensing data. Further, derivation of spatial distribution of meteorological variables will lead to extrapolation of model outputs at the regional level. Integration of all the four components i.e., past database; generated data on field, laboratory and remote sensing studies though the development of a decision support system will strengthen the on-going integrated pest management delivery in rice and cotton with objectivity.

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Expected outcome and impact of the project