![8
Components of Decision Support System for
policy decisions
Tool and technology that handles
various spatial databases, and is a young
area of information technology
Examine and analyze a wider range of
agricultural related resources such as
soil, weather, hydrology, various socio-
economic variables simultaneously and
accurately.
DSS with GIS, organize and analyze
spatial data, address the problems
related to spatial and temporal
variability of various natural resources
on which the performance of agricultural
systems depends.
GIS [Geographic Information System]
Sources of Funding
1.) Department of Agriculture
2.) Indian Council of Agricultural Research
3.) Department of Science & Technology
4.) Various NGOs
IMPLEMENTATION OF PROPOSED SOLUTION](https://image.slidesharecdn.com/6-pandavas-1377885138-130830125051-phpapp01/85/Pandavas-8-320.jpg)
Pandavas
- 1. DSS as a Catalyst in Indian Agriculture TEAM : PANDAVAS SAMAGRA KUMAR | SIDDHANT SANJAY | VISHAL DHAWAN | MANISH CHAUDHARY| GUNJAN KUMAR VERMA IIT KHARAGPUR
- 2. CONTENTS 2 • Problem Statement • Proposed Solution • Implementation of the Solution • Impact of the Solution • Challenges & Mitigation Factors
- 3. PROBLEM AT A GLANCE India’s GDP showed a rapid decline from 30% to 14.5% in the last two decades. The growth rate for the agricultural sector during the 11th FYP was 3.5% whereas the economic growth rate was 8.2%. India’s productivity is only 3.1 ton/hectare versus the global average of 4.2 ton/hectare. OVERVIEW CAUSES Primary sector of Economy. Over 65% of population is involved in this sector Importance in International Trade Contribution to Foreign Exchange Resources Vast Employment Opportunities Source of Government Income Basis of Economic Development REASONS FOR SELECTING THE CAUSE 3 Overcrowding Poor Technique of Production Inadequate Irrigation Facilities Inefficient Government Policies Inadequate Storage Facilities Illiteracy & Poor Economic Condition RECENT TREND
- 4. PROPOSED SOLUTION DECISION SUPPORT SYSTEM (DSS) 4 The Proposed Framework of DSS Building Decision Support System (DSS) is an interactive, flexible, and adaptable computer based informat ion system that utilizes decision rules, models, and model base coupled with a comprehensive database and the decision makers own insights, leading to specific, implementable decisions in solving problems that would not be amenable to management science models. Thus, a DSS supports complex decision making and increases its effectiveness MEANING AND CONCEPT
- 5. PROPOSED SOLUTION • To enhance the interface between the agricultural, meteorological and socio-economic communities and farmers and other stakeholders; • To establish the forecasting needs for decision making in crop production; • To develop the capacity for integrated climate and agricultural simulation and prediction for decision making for a range of farming systems; and • To demonstrate the capability and value of improved climate prediction for improving crop production at farm to national scales as a proof of concept. OBJECTIVES 5 MERITS • Time Saving • Enhance Effectiveness • Cost Reduction • Promote Learning • Increase Organizational Control • Encourages exploration and discovery on the part of the decision maker • Create Innovative ideas to speed up the performance
- 6. IMPLEMENTATION OF PROPOSED SOLUTION 6 Data Gathering Data Processing Data Analysis and Design Decision Making Data Implementa tion Deliberation Stakeholders review and interpret data, inform scientists and policymakers Scenario Analysis with feedback and requirement of stakeholders and decision makers Evaluation Performed by stakeholders, policy makers, Coop Extension Analysis Scientists, Engineers & Policymakers, collect analyze data present to stakeholder Implementation Decision made will be conveyed to stakeholder, he’ll use this knowledge, to give favourable result.
- 7. 7 Various Components of Decision Support System (DSS) for Crop Productivity Management IMPLEMENTATION OF PROPOSED SOLUTION
- 8. 8 Components of Decision Support System for policy decisions Tool and technology that handles various spatial databases, and is a young area of information technology Examine and analyze a wider range of agricultural related resources such as soil, weather, hydrology, various socio- economic variables simultaneously and accurately. DSS with GIS, organize and analyze spatial data, address the problems related to spatial and temporal variability of various natural resources on which the performance of agricultural systems depends. GIS [Geographic Information System] Sources of Funding 1.) Department of Agriculture 2.) Indian Council of Agricultural Research 3.) Department of Science & Technology 4.) Various NGOs IMPLEMENTATION OF PROPOSED SOLUTION
- 9. 9 IMPACT OF DECISION SUPPORT SYSTEM Criteria to Measure the Impact of DSS •Crop productivity •Soil Fertility •Land Use •Irrigation •Crop wastage •Amount of Fertilizers used •Livestock productivity Scalability of DSS Monitoring Mechanism Sustainability of DSS •Initiation in few districts till Panchayat level . •An official ,appointed; will be responsible for providing required information & training to farmers. • NGOs will be consulted to create awareness at a large scale . •After development , expansion will be done at national scale. •A panel will be formed which will be responsible only for proper management of DSS at every level. •This panel will consist of specialist from every field such as scientists, software engineers, water management personnel, finance department personnel, etc. •Feedback forms will be circulated among everyone related to DSS ranging from analysts to farmers. •Collected feedback forms will be analyzed and proper steps will be taken for the development of DSS. •Peasants will be trained regularly to take maximum advantage of DSS. •Technological amendments & advancements will be done regularly.
- 10. 10 CHALLENGES & MITIGATION FACTORS CHALLENGES Social Essential for climate, agriculture and social scientists to collaborate at all stages Client-community expectation and understanding. Need to maximize local participation. Ability of farmers to cope with climate variability and perception of factors. Quality data availability and accessibility a necessary condition for site selection Farmers are often short of time (to learn and use DSS) Technological Develop approaches to predict crop prediction and resource use at field and regional scale. Many farmers are not computer oriented. Systems analysis of key decisions; factors influencing decision-making and attitudes to climate risks. Current knowledge, perceptions and practices about how climate variability influence crop production. Economical & Political Need to consider scaling issues in working from sub-national to national scales. Distribution of Funding at various scales. Credit Availability to Farmers. Political constraints in various states against DSS.
- 11. 11 CHALLENGES & MITIGATION FACTORS MITIGATION MEASURES •Case studies about capability in climate forecasting can be used to facilitate improved decision-making about crop production. •Interim workshops with scientists and end-user communities. •Final top-level conference to present science and engage policy-makers and other end-users. •Building scientific capacity to conduct interdisciplinary studies that involve the participation of clients. •Evaluation of the value of improved climate variability prediction Criteria describing popularity of DSS •Widespread problems need to be addressed; •These products need to be location specific; •There needs to be strong support from initial users; •Relevance, simplicity, effectiveness, and low cost are key attributes; •Products other than computer-based products should be considered; and14 •Users need to be closely involved in the development of these products. Impact of DSS (Production vs Time Graph)