Aim/Agenda

About us:

The occurrence of a severe epidemic of brown spot disease in rice (caused by Helminthosporium spp) within the historical region of Bengal (now encompassing West Bengal and Bangladesh) in the year 1942 led to a significant scarcity of rice. Furthermore, the inability of the civil authority to effectively manage such a catastrophic situation resulted in the occurrence of what came to be known as the Great Bengal Famine of 1943. Against this historical backdrop, the Central Government made the strategic decision in 1944 to enhance the scope and depth of research pertaining to many facets of rice cultivation. In the subsequent year, the governmental authorities made the decision to create a Central Institute for Rice Research, resulting in the establishment of the Central Rice Research Institute (CRRI) on April 23, 1946. The institute was situated in Bidyadharpur, Cuttack, Odisha, and was allocated a 60-hectare experimental farm by the Odisha government. The original Director of the organisation was Dr. K Ramiah, a renowned rice grower. Following this, in the year 1966, the administrative authority of the Institute was passed to the Indian Council of Agricultural Research (ICAR). In 2015, the Institute underwent a renaming process and was officially designated as ICAR-National Rice Research Institute (NRRI). ICAR-NRRI is an institute affiliated with the Indian Council of Agricultural Research (ICAR) and is under the Crop Science Division. The Institute operates three research stations, located in Hazaribag, Jharkhand, Gerua, Assam, and Naira, Andhra Pradesh. These stations are dedicated to conducting research on rice cultivation in specific ecological conditions, namely rainfed upland areas in Hazaribag, flood-prone rainfed lowlands in Gerua, and coastal saline environments in Naira. Under the administrative jurisdiction of ICAR-NRRI, there are two Krishi Vigyan Kendras (KVKs) that operate. The aforementioned locations are situated in Santhapur, Cuttack, Odisha and Jainagar, Koderma, Jharkhand, respectively.

What we do:

The mission of ICAR-NRRI is to safeguard the health of current and future generations of rice farmers and eaters. With the goal of increasing the efficiency, profitability, and long-term viability of rice farming, eco-friendly technology will be developed and disseminated. ICAR-NRRI conduct research in the areas of crop improvement and resource management, with a focus on enhancing and maintaining rice yield across various ecological conditions. This research will particularly emphasise rainfed habitats and the challenges posed by abiotic stress. Generation of appropriate technology through applied research for sustainable increase in productivity and income from rice and rice-based cropping/farming systems in all the ecosystems in view of decline in per capita availability of land. Collection, evaluation, conservation and exchange of rice germplasm and distribution of improved plant materials to different national and regional research centres. Development of technology for integrated pest disease and nutrient management for various farming situations. Characterization of rice environment in the country; evaluation of physical, biological, social-economic and institutional constraints to rice production under different agro-ecological conditions & in farmer situations and develop remedial measures for their amelioration. Maintain database on rice ecology, ecosystems, farming situations and comprehensive rice statistics for the country as a whole in relation to their potential productivity and profitability. Impart training to rice research workers, trainers and subject matter/extension specialists on improved rice production and rice-based cropping and farming systems. Collect and maintain information on all aspects of rice and rice-based cropping and farming systems in the country.

Objectives of the sub-project:

  • To develop algorithms for precision top dressing of N using hand held and drone mounted sensors for different rice ecologies.
  • To develop the forewarning system for insect and pest (yellow stem borer) & disease (BLB) by using environmental data, sensor and suitable machine learning technique.
  • To differentiate the symptoms of N deficiency with the other confounding symptoms from diseases (BLB).