Total views : 137

Decision Support System for Climate Smartening of Tea Landscapes for Future Sustainability in North East India

Affiliations

  • Department of Computer Science and Engineering, Triguna Sen School of Technology, Assam University, Silchar – 788011, Assam, India
  • Tea Research Association, Tocklai Tea Research Institute, Jorhat – 785008, Assam, India
  • Department of Agricultural Engineering, Triguna Sen School of Technology, Assam University, Silchar – 788011, Assam, India

Abstract


Objectives: To develop a Decision Support System (DSS) for climate smartening tea production system in North East India. Methods/Statistical analysis: A database, model base, knowledge base and user interface are used as components. Database consists of historical and future climate data which are future climate projections, model base includes research findings to be used in DSS and knowledge base includes expert knowledge. The user interfaces interact with the database, model base, and knowledge base to generate an effectual environment to make quality decisions towards a resilient tea production system. Findings: The study brings out better understanding about the impact of the climatic parameters on tea yielding over the past years and also the future projections of their impact in spatio-temporal manner. The DSS also provides the user friendly tools to make decisions on adaptable measures (e.g. irrigation) that need to be adopted by the stakeholders, decision-makers and policy-makers so as to sustain tea production in the wake of climate change. Further, the DSS Framework developed in the study has multiple usages and provides instant decisions based on real-time data for tea plantations management with an insight into future. Since a web–based approach has been taken up, it provides an insightful and user-friendly appearance of data that can be accessed by an ample range of users at diverse geographical locations. Visual representations of the data facilitate communication of climate information among stakeholders and decision-makers in a much easier and comprehensible manner. Application/Improvements: The DSS has the scope to add further modules/ interfaces to further refine the DSS as and when additional information/data becomes available in future.

Keywords

Climate Change, Decision Support System, North East India, Resilient Tea Production, Tea Plantation

Full Text:

 |  (PDF views: 117)

References


  • Bhagat RM, Baruah RD, Safi que S. Climate and tea [Camellia sinensis (L.) O. Kuntze] production with special reference to North Eastern India: a review. Journal of Environment Research and Development. 2010; 4(4):1017–28.
  • Barua DN. Science and practice in tea culture. Published by Tea Research Association, Jorhat, Assam, India; 1989. p. 509.
  • Brown ME, Funk CC. Food security under climate change. Science. 2008 Feb 1; 319(5863):580–1. Crossref
  • Kaufmann RK, Snell SE. A biophysical model of corn yield: integrating climatic and social determinants. American Journal Agricultural Economics. 1997 Feb; 79(1):178–90.Crossref
  • Freckleton RP, Watkinson AR, Webb DJ, Th omas TH. Yield of sugar beet in relation to weather and nutrients. Agricultural and Forest Meteorology. 1999 Jan 25; 93(1):39–51. Crossref
  • Gadgil S, Rao PRS, Sridhar S. Modelling impact of climate variability on rainfed groundnut. Current Science. 1999; 76(4):557–69.
  • Tan GX, Shibasaki R. Global estimation of crop productivity and the impacts of global warming by GIS and EPIC integration.Ecological Modelling. 2003 Oct 15; 168(3):357–70.
  • Crossref
  • Venkateswaran G, Radhakrishnan B. Studies on the effect of drip irrigation in mature clonal tea. Two and a Bud. 2011; 58:93–7.
  • Bujarbarua P, Baruah S. Climate change: global risks, challenges and decisions. IOP Conference Series: Earth and Environmental Science. 2009 Mar; 6:1–4.
  • Ghosh A, Roy R. GIS anchored integrated plantation management.Proceedings of Map India Conference, NewDelhi, India; 2004. p. 1–7.
  • Moss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, Vuuren DPV, Carter TR, Emori S, Kainuma M, Kram T, Meehl GA, Mitchell JFB, Nakicenovic N, Riahi K, Smith SJ, Stouffer RJ, Thomson AM, Weyant JP, Wilbanks TJ. The next generation of scenarios for climate change research and 1183 assessment. Nature. 2010 Feb 11; 463:747–56.Crossref
  • Data Distribution Centre IPCC. Scenario process for AR5 [Internet]. 2017 [cited 2017 Jan 31]. Available from: Crossref
  • Chaturvedi RK, Joshi J, Jayaraman M, Bala G, Ravindranath NH. Multi-model climate change projections under representative concentration pathways. Current Science. 2012; 103(7):1–12.
  • Tea Research Association. Irrigation [Internet]. 2017 [cited 2017 Jan 31]. Available from: Crossref

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.