Accessible Farmed Seafood Identifiers - loamCode/GDST GitHub Wiki
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Challenge Statement:
The growth of traceable seafood depends in part on data sharing methods adapted to the length of the supply chain and robust mechanisms for connecting those data to the underlying seafood goods. Novel identifier technologies have been developed but they are often inaccessible for small-scale aquaculture farmers who operate with low margins and very small seafood species where individual identification is impractical.
Background:
The emerging standards from the Global Dialogue on Seafood Traceability define what data is needed and a framework for sharing that data interoperability between actors in the supply chain. To effectively leverage these standards, seafood supply chain actors will need to physically identify their seafood goods. These standards define a few options for a globally unique digital identifier that can be embedded in labels or RFID tags where it would be physically represented. Many high-profile seafood traceability pilots have leveraged identifier technologies that tag individual fish in high-value value chains. Shrimp species produced in aquaculture are managed in aggregate as average counts of specimens per pound or kilogram. The farms that produce shrimp are often the same small-scale operations which are pressed for cost-effective solutions. Addressing the challenge of traceability identifiers for small-scale farmed shrimp production is a representative case for the challenge facing many small-scale producers.
Possible Solution:
A successful solution would be an accessible physical identifier technology which could be employed by small-scale seafood producers globally. A successful solution would demonstrate not only how the cost but also day-to-day usage of the solution addresses the specific circumstances of small-scale farm producers like shrimp farmers. A successful solution will also demonstrate how the identifier can persist as seafood goods move from one actor to another in a supply chain. Some companies have also explored the idea of a card placed in the box containing the products with live monitoring of the temperature. This allows the added benefit of tracking disruptive events by crosschecking multiple data streams for anomalies between data that should look very similar.