Terra-Fresh Symposium: FFAR Grantee Presents Final Results

9:00 am - 5:00 pm ET

ASU SkySong Building 1, Room 201 Global 1475 North Scottsdale Road, Suite 200 Scottsdale, AZ 85257

Virtual and In-person (Scottsdale, AZ)

  • Health-Agriculture Nexus
  • Informational Session

The Foundation for Food & Agriculture Research (FFAR) awarded a $963,513 grant to Arizona State University researchers to develop tools that enable farmers to more effectively meet consumer demand and reduce food waste.

Researchers are hosting the Terra-Fresh Symposium to present their final results.

Terra-Fresh (short for Technology Enabled Fresh Supply Chains) is an integrated planning and coordination environment that seeks to exploit the new technological realties of the supply chain of fresh agricultural products for the benefit of the growers, consumers, and the environment (www.terra-fresh.com).

The objective of Terra-Fresh is to make direct connections between the growers, particularly small growers, and the most attractive markets. Terra-Fresh does this through a series of interacting tools that include opportunity discovery, contract negotiation, opportunity allocation based on agronomic potential and risk profile, and logistics analysis.

Terra-Fresh aims to achieve benefits across at least three main dimensions: 1) increased profitability of growers; 2) greater availability of affordable, nutritious food for consumers, and 3) reduction of food waste throughout the supply chain.

In this final symposium we will present research results on

  1. Using data mining and artificial intelligence tools for market opportunity discovery
  2. Planning and coordination tools for coalition of growers
  3. Developing efficient logistics for small harvests
  4. Research roadmap efficient system wide logistics solutions

View agenda and register to attend either virtually or in-person.

Connecting Growers & Markets

Read Impact Report Highlight.

FFAR Grant Develops Tools to Predict Consumer Demand, Reduce Food Waste

FFAR Grant Develops Tools to Predict Consumer Demand, Reduce Food Waste