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ARS Home » Northeast Area » Burlington, Vermont » Food Systems Research Unit » Research » Research Project #445199

Research Project: Modeling Fresh Produce Supply Chain Systems in the Northeast US

Location: Food Systems Research Unit

Project Number: 8090-44000-001-007-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Sep 1, 2023
End Date: Aug 31, 2026

Domestic production of fresh fruits and vegetables is concentrated in the “Fruitful Rim,” a farm resource region that includes parts of the states of Arizona, California, Florida, Georgia, Idaho, Oregon, South Carolina, Texas, and Washington. However, adapting to climate change and responding to consumer interest in local and regional foods may require increased production from farms in other parts of the country. Likewise, supplying fruits and vegetables in quantities needed to meet national dietary recommendations may require development of new domestic production centers. The fresh produce industry in the Northeast U.S. is characterized by a relatively large number of smaller producers and by a diversity of products, including more than 40 individual fruit and vegetable crops. There is a need to understand how Northeast fresh produce supply chains could be developed to contribute to stable and sustainable regional and national food systems. To this end, the goal of this project is to evaluate the structure of Northeast fresh produce supply chains to identify missing infrastructural components, such as aggregation or processing and to assess the system-wide cost, food loss, and greenhouse gas emissions. In pursuit of this goal, this project has five objectives: 1) Develop a Northeastern U.S. fresh produce supply chain model to describe the county-to-county flows of the millions of pounds of produce harvested, imported, shipped, consumed, and exported throughout the region, 2) Assess the agricultural capacity of the Northeast U.S. for fresh produce production under scenarios of land availability and crop productivity, 3) Estimate the most cost-efficient supply chain configuration to expand Northeast U.S. production under scenarios of increased regional self-reliance, 4) Identify how the system could adapt to a likely large-scale increase in produce consumption, 5) Measure the environmental tradeoffs and synergies between cost and greenhouse gas emissions in optimizing fresh produce supply chain configuration.

Cooperator and Agency scientists will develop a modeling system for estimating the capacity, cost, and greenhouse gas emissions of Northeastern fresh produce supply chains. This modeling system will be created using existing agricultural supply chain optimization routines already in use for national and subnational analyses. The model will be parameterized using publicly available secondary data on crop acreage, crop production, and fresh produce infrastructure, or imputations made from such data. The first step is to develop a fresh produce supply chain model for the Northeast region, from farm to consumers, to estimate costs, food loss, and greenhouse gas emissions. To do this, Cooperator and Agency scientists will build a national cost minimization model of the fresh produce supply chain to describe how domestically grown or imported fresh produce moves from numerous farms and custom ports to domestic consumers and export ports. Publicly available data on crop acreage and yield, produce shipments, production costs, and life cycle emissions will be used to validate the model and to explore possible synergies and tradeoffs between economic and environmental performance for various scenarios of fresh produce supply chain expansion in the Northeast. Once the supply chain model is created and validated, Cooperator and Agency scientists will examine scenarios of potential increased regional self-reliance. To identify the optimal supply chain configuration to expand fresh produce production for self-reliance in the Northeast, Cooperator and Agency scientists will first assess the agricultural capacity of the region building on earlier analyses of land suitability for fruit and vegetable production and estimates of land availability and productivity from publicly available data sources. Optimization routines will be used to determine the most optimal spatial patterns for minimizing costs, minimizing food losses, and minimizing GHG emissions of the whole supply chain systems. Tradeoffs and synergies between economic and environmental performance for alternate scenarios will be examined.