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Institute for Sustainable Food Systems

Innovative solutions for a healthy and productive world

Institute for Sustainable Food Systems

Innovative solutions for a healthy and productive world

Decision makers are faced with challenging questions that require alternative options for a sustainable food production system. Advanced computer-based tools, models, and decision support systems can play an important role in this process.



  • How do we know if the food system is sustainable, efficient, fair, economically viable or resilient? What are the important indicators? Environmental health, community and family conditions, health care, tax revenue, profitability, school access, free trade, poverty, malnutrition or rule of law?
  • What are the key factors influencing success (or failure)? Regulations, leadership, education, innovation, consumer behavior, market structure?
  • Which investments will have the greatest impact in promoting sustainable food systems? Infrastructure, genetic research, disease control, market analysis, community structure, information technology, education?
  • To answer these questions, and many more, we need indicators and metrics. Many of which are not currently collected in a consistent manner by any institution.

What are we doing to address these challenges?

The Decision Support System for Agrotechnology Transfer (DSSAT): ISFS researchers Gerrit Hoogenboom, Senthold Asseng, Vakhtang Shelia, Cheryl Porter, Ken Boote, and Jim Jones are working with scientists at the International Fertilizer Development Center in Alabama, USDA-ARS, CGIAR and many other institutions to develop dynamic computer simulation models that can predict crop yield, resource use, and environmental impact as a function of local weather and soil conditions, crop management, and plant genetics. 

DSSAT was an outcome of the International Benchmark Sites Network for Agrotechnology Transfer (IBSNAT) that was funded from 1982 through 1992 by the US Agency for International Development (USAID) to address food security in developing countries using a systems analysis and modeling approach. DSSAT now encompasses simulation models for over 40 crops for cereals, grain legumes, root and tuber crops, oil and fiber crops, vegetables and forages. The crop simulation models have been applied at different spatial and temporal scales, ranging from gene-based modeling, irrigation and fertilizer management, precision farming, feedstock for biofuel, soil carbon sequestration, to climate change impact assessment for food and nutrition security in 2050 and beyond. The DSSAT software is now Open Source and can be requested from the DSSAT portal at, while the source code is available from International workshops are organized annually to provide capacity building for both new and advanced users ( DSSAT Development Sprints and modeling hackathons are held biannually to advance the crop models with new scientific knowledge and improve the DSSAT associated tools, utilities and application programs. DSSAT currently has a network of over 16,000 scientists interested in the development and application of crop modeling for decision support.

The Fisheries Performance Indicators Project: ISFS researchers, James Anderson, Taryn Garlock and Frank Asche are working with researchers at Univ. of Washington, The World Bank and several other institutions to develop Fishery Performance Indicators. The FPIs are designed to determine how fisheries management systems are performing in order to achieve community, economic, and ecological sustainability.

The FPI project was initiated by James Anderson in 2009 with the support of the International Coalition of Fisheries Association (ICFA). The Fishery Performance Indicators (FPIs) consist of 68 output and 54 input metrics of fishery performance spanning the ‘triple bottom line’ dimensions of ecology, economics and community in a fishery system. The FPIs were developed as a response to the fact that most global fisheries performance assessment approaches emphasize primarily fish stock and ecological conditions, and contain little information on economic and social issues. Moreover, fisheries management systems are often prohibitively expensive – especially in poorer regions of the world. Data-poor fishery systems needed assessment, and there needed to be a comparable approach – a common language, a common metric. The FPIs are a completely independent, science-based and objective tool, providing indicators not only for outcomes; but also for input factors that facilitates good governance and positive fisheries outcomes.   Much can to be learned by comparing systems to determine what works and what does not.