Location: Food Systems Research Unit
Project Number: 8090-44000-001-000-D
Project Type: In-House Appropriated
Start Date: Apr 29, 2021
End Date: Apr 28, 2026
Objective:
Objective 1. Improving Production Systems: Develop data-informed small-farm strategies to improve the economic, environmental, and social sustainability of crop production systems based on research that considers feedback from value-added processors, informed consumers, and potential impact on nutritional/health outcomes. [NP 216 components 1c, 2a, 3b, 3c]
Objective 2. Enhancing Value Added Processing: Develop innovative solutions for specialty value-added processes and products to improve consumer health outcomes as well as economic, environmental, and social sustainability of the food system, while informing consumer choice and diversified production system management. [NP 216 components 2b, 2c]
Objective 3. Optimizing Consumer Outcomes: Production systems and value-added processing will be tied to consumer preferences, product nutrition, food safety and potential impacts on public health, thus enabling consumers to make safe, healthy, and informed food choices and facilitating targeted research for the improvement of production systems, food processing, and development and delivery of new products. [NP 216 component 3c]
Objective 4. Data Integration: Develop appropriate linkages and cooperation within and between the USDA-ARS and the University of Vermont, for the purpose of forming an integrated Food Systems program, including integrated data systems, comprehensive models, and submitting a proposal for becoming part of the Long-Term Agroecosystem Research (LTAR) network. [NP 216 components 1d, 2b, 3b, 3c]
Objective 5: Develop strategies for agricultural producers and other actors in the food system to improve soil health within the agricultural systems of the Northeast.
Approach:
Food systems are interconnected sets of elements that work together to produce, process, distribute, store, sell, and prepare food. They include the upstream activities that support production, such as the creation of farm inputs. They also include downstream activities, such as the disposal or recycling of food waste. This project will contribute towards improving human nutrition, ecological sustainability and economic viability of plant-based food systems in the New England States. To this end, the project scientists will work together with the University of Vermont, and other collaborators, to explore how the region can simultaneously improve diets through delivery of satisfying, culturally-appropriate, plant-based foods that are simultaneously affordable, sustainable, and support viable farms and food businesses. Research activities will focus at a range of scales, from individual actors, such as farmers and consumers, to larger geographic areas, such as watersheds or foodsheds. In addition, the unit will explore how systems change over time. Three overarching questions will guide the Unit’s research on plant-based food systems. First, how can different components across sectors of the food system encourage intake of healthy foods, such as whole grains, pulses, fruits, and vegetables, while also improving the overall quality of the diet and associated health outcomes? Second, how can plant-based food systems increase biological productivity and economic viability while also leveraging opportunities for reduced environmental impact, such as exploiting ecological synergies from integrated crop-livestock systems? And third, how can plant based farming systems interact with animal-production based systems, to improve sustainability and reduce environmental impacts? To create effective collaborations with the University of Vermont and stakeholder partners, the Research Unit will identify on-going efforts to understand and improve the ecological, economic, and social sustainability of New England food systems. This process will help ARS staff to design strategic research that answers key questions or integrates data in new ways that lead to transformative improvements. In addition, the Unit will develop a state-of-the-art facility for computational modeling and data visualization with the ability to link to other data sources and computing resources.
