Systems Informatics and Analysis

  • Yogendra Shastri
  • Alan C. Hansen
  • Luis F. Rodríguez
  • K. C. Ting


Various biomass feedstock production and provision (BFPP) tasks discussed in earlier chapters are highly interconnected. Design and operational decisions for any task impact decisions for most other tasks. In view of such complex interactions, it is critical that we also look beyond an individual task and focus on the techno-economic feasibility of the complete production and provision system. This calls for a holistic view of the BFPP system. Systems theory based approaches that integrate systems informatics and analysis methods are ideally suited to achieve this objective. This chapter reviews the literature on the application of such approaches for BFPP. The basics of informatics, modeling and analysis, and decision support are first discussed. Then their applications for different system classes, namely, crop growth and management systems, on-farm production systems, local biomass provision systems, and regional/national/global systems, are presented. The literature review illustrated that applications of the systems-based tools at the crop growth, establishment, and management levels as well as the local biomass provision level have been numerous. Many of these developments have built on tools already existing for conventional crops. Systems theory applications to the on-farm production scale have been limited, possibly due to lack of field study data as well as limited commercial farming. In contrast, interest in studying the regional/national/global systems has increased in recent years. We conclude that greater efforts are needed to validate these tools and to study issues cutting across multiple scales. We also recommend that seamless integration of informatics, analysis, and decision support tools is necessary to achieve a truly concurrent science, engineering, and technology-based platform for decision making in the future.


Decision Support System Corn Stover Energy Crop Bioenergy Crop Mixed Integer Linear Programming Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Yogendra Shastri
    • 1
  • Alan C. Hansen
    • 2
  • Luis F. Rodríguez
    • 3
    • 4
  • K. C. Ting
    • 2
  1. 1.Department of Chemical EngineeringIndian Institute of Technology Bombay, PowaiMumbaiIndia
  2. 2.Department of Agricultural and Biological EngineeringUniversity of Illinois at Urbana-ChampaignUrbanaUSA
  3. 3.Department of Agricultural and Biological EngineeringUniversity of Illinois at Urbana- ChampaignUrbanaUSA
  4. 4.Information Trust InstituteUrbanaUSA

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