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Climate Change, Intercropping, Pest Control and Beneficial Microorganisms pp 373–399Cite as

Decision Support Systems: Concepts, Progress and Issues – A Review

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Part of the book series: Sustainable Agriculture Reviews ((SARV,volume 2))

Abstract

Agriculture is a complex process of air, water, weather, soil, plants, animals and micro-organisms, which are uneven in distribution. Because of the uncertainty and risk associated with agricultural production – due to vulnerability in weather, variability in soil, infestation of pests and insects – some most important decisions based on “what if” depends on the existing knowledge base of current and future physical conditions like soil and climate, yield and prices, crop and area. If the past pattern and exact impact of agriculture-associated resources are known, one can predict the likely occurrences of certain crop-related attributes in advance, so that farmers can put together safeguards by tiding over the controllable attributes, which are likely to have serious impact on crop growth and yield. Thus the quality of decision-making can play an important role in complex and uncertain situations.

Empirical evidence reveals that human judgement and decision-making can be far from optimal and could even deteriorate further with added complexity and stress. Therefore, aiding the deficiencies of human judgement and quality decision-making has been a major focus of research throughout the history particularly with the advancement in electronic processing of data and design of Decision Support System (DSS). DSS can help to reduce uncertainty and improve the decision-making process by providing access to data through procedures and analytical reasoning. Computerized decision support for sustainable agriculture is not new. These systems have been designed to address complex tasks involving agronomic, economic, regulatory, climate change and pollution control, enabling us to match the biological requirements of crop to the physical characteristics of land so that the objective specified by the user is obtained. Most agricultural DSSs aim to help stakeholders realize their strategic aim of securing a competitive advantage through timely decision-making.

While addressing the limitations in current decision support technologies, visionaries and researchers throughout times have talked of exploiting our mass of information to produce new knowledge automatically, build intelligent DSSs and eliminate human burdens associated with information-seeking and problem-solving activities.

DSSs are widely used and known with agriculture and they have proved to be important tools in the decision-making process from farm to fork. Unfortunately, ease of use, low adoption, failure to show cost benefits, complexity and user inputs, distrust for the output, lack of field testing, lack of integration among heterogeneous components, success measurements, non-involvement of end-user before and after development stages and under-definition of beneficiaries are some issues that need to be addressed. But keeping the amount of input data required as small as possible; keeping the system itself as flexible as possible; providing users with default values; ensured involvement of users from basic development stage; greater user involvement through participatory learning approaches; interactive prototyping as well as keeping DSS development manageable and small in scope can provide avenues for improvement in DSS research and development.

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Authors and Affiliations

  1. Krishi Vigyan Kendra, SKUAST(K), Shuhama, Alusteng, Srinagar, Kashmir, India

    Shabir Ahmad Mir

  2. Department of Computer Science, University of Kashmir, Hazratbal Campus, Srinagar, Kashmir, India

    S. M. K. Quadri

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  1. Shabir Ahmad Mir
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Correspondence to Shabir Ahmad Mir .

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    Eric Lichtfouse

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Mir, S.A., Quadri, S.M.K. (2009). Decision Support Systems: Concepts, Progress and Issues – A Review. In: Lichtfouse, E. (eds) Climate Change, Intercropping, Pest Control and Beneficial Microorganisms. Sustainable Agriculture Reviews, vol 2. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-2716-0_13

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