Conceptualization of a framework of decision support system for agriculture in hilly region

Authors

  • A. S. NAIN GB Pant University of Agriculture & Technology, Pantnagar – 263 145, India
  • K. K. SINGH Agromet Services, India Meteorological Department, New Delhi – 110 003, India

DOI:

https://doi.org/10.54302/mausam.v67i1.1178

Keywords:

Decision support system (DSS), Hilly region, Agriculture expert system (AES), Geospatial technology, Remote sensing, GIS, Soil information system (SIS)

Abstract

Decision support system (DSS) in agriculture helps farming community to take appropriate decision as per the situation to maximize economic return by enhancing productivity and reducing the cost of inputs. The prime most purpose of DSS is to enhance the input use efficiency by applying the input when it is needed most. The requirement of DSS in the hilly states is being felt more as environmental conditions vary greatly in tempo-spatial domain. Climate change associated with increasing probability of extreme weather conditions has further deepened the need of DSS. There have been many attempts in the past to use / develop DSS in the hilly regions. The serious efforts in this direction were initiated by fine tuning the Decision Support System for Agrotechnology Transfer (DSSAT) in Indian conditions. DSSAT helps to take appropriate decisions on selection of cultivar, sowing time, irrigation, fertilization and harvesting of crops. Of late geospatial technology alone and in combination with crop simulation model has also been used to develop DSS. Present paper underlines the efforts of researchers / academicians to develop DSS in hilly states with their usability and limitations. Paper also conceptualizes a framework of DSS for hilly regions by integrating a forewarning system and agriculture expert system.  

Downloads

Published

01-01-2016

How to Cite

[1]
A. S. . NAIN and K. K. . SINGH, “Conceptualization of a framework of decision support system for agriculture in hilly region”, MAUSAM, vol. 67, no. 1, pp. 195–204, Jan. 2016.

Issue

Section

Research Papers

Most read articles by the same author(s)

<< < 1 2 3 > >>