Development of eAgromet Prototype to Improve the Performance of Integrated Agromet Advisory Service View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2014

AUTHORS

P. Krishna Reddy , A. V. Trinath , M. Kumaraswamy , B. Bhaskar Reddy , K. Nagarani , D. Raji Reddy , G. Sreenivas , K. Dakshina Murthy , L. S. Rathore , K. K. Singh , N. Chattopadhyay

ABSTRACT

In several countries, the systems for forecasting weather are being operated to deal with weather and its related factors affecting agricultural production. India meteorological department (IMD) is providing several types of weather forecasts. One of the forecast service is medium range forecast (MRF). As a part of MRF, the expected values of rain fall, temperature, cloud cover, humidity, wind speed and wind direction for next five days are forecasted twice a week by considering district as a unit. Agriculture is markedly affected by weather condition during crop season. IMD in collaboration with Indian Council of Agriculture Research (ICAR) and State Agriculture Universities (SAUs) has set-up about 130 Agro-meteorological Field Units (AMFUs) and each AMFU covers about five districts. Based on MRF, IMD is rendering Integrated Agromet Advisory Service to the farming community of the country in the form of agromet advisory bulletin. The agromet advisory bulletins contain possible risk mitigation measures for the major crops and livestock. Based on the weather forecast, a group of interdisciplinary scientists and agromet scientists at AMFU prepare district-level agromet advisory bulletins. These bulletins are sent to the farmers and other stakeholders of the corresponding district. To ease the process of preparing agromet bulletins, an effort has started to build IT-based agrometeorological advisory system called, eAgromet. In this paper, we explain the concepts of eAgromet and its operation. More... »

PAGES

168-188

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-05693-7_11

DOI

http://dx.doi.org/10.1007/978-3-319-05693-7_11

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1051560885


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