An illustrated brochure on NAIP Component 4 sub-project C

Abstract

The goal of launched under the aegis of the Indian Council of Agricultural Research (ICAR) is to facilitate accelerated and sustainable transformation of Indian agriculture by collaborative development and application of agricultural innovation by the public research organizations in partnership with the farmer's groups, the private sector, the civil society organizations and other stakeholders. NAIP aims to achieve the objectives by supporting four components. Component 4 under NAIP ensures that Agriculture in India is a gamble with weather. Pest associated crop losses are higher in the tropics which are currently estimated between 10-30% of the total agricultural production valued at Rs 1400 billion in 2007. There are additional costs in the form of pesticides applied for pest control, currently valued at Rs 68 billion. Knowledge and information is the key to correct pest management decisions. Integrated Pest Management (IPM) is a system that emphasizes appropriate decision-making, depends heavily on intensive, accurate and timely information for field National Agricultural Innovation Project (NAIP) investments are made in basic science in order to sustain the flow of knowledge and innovations essential to keep the technology development process responsive to the ever-changing needs of agriculture. The Component 4 aims at making such investments in those frontier science areas of agricultural research that are strategically important for Indian agriculture. implementation by practitioners. Pest forecast are an important component of the broad IPM philosophy. Forewarning models provide lead time for managing impending pest attacks and thus minimize crop loss and optimize pest control leading to reduction in cost of cultivation. A Decision Support System (DSS) integrates a user-friendly front end to often-complex models, knowledge bases, expert systems, and database technologies. DSSs have emerged as essential tools to bridge the gap between science-based technology and end-users who make day-to-day management decisions. An IPM-DSS provides user all necessary information on pest developmental models including sampling, decision making criteria and management options. Such systems are essential to enhance the adoption and spread of IPM in the country. This sub project aims at integrating pest database, generated data from field, laboratory and remote sensing studies through a decision support system to strengthen the implementation of on-going integrated pest management programmes in rice and cotton.