Dec 11, 2023
DeltaTrak, University of South Florida awarded patent

DeltaTrak and the University of South Florida have jointly received a patent from the U.S. Patent and Trademark Office for an approach to monitoring and encoding the quality of perishable goods along the supply chain.

In a temperature-dependent supply chain for perishable products, different transportation temperature ranges are acceptable for various product categories. For example, fresh flowers, seafood, and most produce typically travel at temperatures between 36-46°F. While some less-sensitive produce, such as asparagus and avocados, may only require protection from extreme temperature variations.

DeltaTrak-logoTemperature abuses in the cold chain frequently occur, leading to increased food waste and safety concerns. Around 12% of food waste in the U.S. happens during distribution due to inappropriate refrigeration. Monitoring perishable products exposed to temperature variations along the supply chain is crucial to prevent shipping products with reduced shelf life. Current algorithms predict the shelf life of perishable products but don’t comprehensively consider product and transportation quality.

“To address these issues, we created a system and method to estimate product conditions upon arrival at a destination and objectively quantify temperature management quality from harvest to destination,” Fred Wu, DeltaTrak CEO, said in a news release.

The invention aims to enhance post-harvest monitoring and modeling of the perishable supply chain using sensors and analytics. It introduces a quality code for perishable products, which includes three key components: an initial cooling score, a transportation temperature score, and a predicted remaining shelf-life score. These scores are generated using temperature profiles and known effects on the product.

“The system includes sensors, processing hardware, and software to calculate the quality code, which is alphanumeric,” Ismail Uysal, associate professor and undergraduate director at the University of South Florida’s Department of Electrical Engineering, said in the release. “The quality code can be used to improve quality control during product inspection at destinations, pinpoint issues in the supply chain, and enhance efficiency with automated predictive algorithms,” which can include AI and machine learning based analytics.

For instance, it can tell if the product’s quality suffered because it took a long time to cool down or because the temperature inside the shipping container was too high. Typically, experts would need to analyze temperature logger data to make such assessments, but with this quality code, it’s easy to pinpoint supply chain issues.

The new system addresses the need to assess and improve the quality of perishable products in the cold supply chain by providing a comprehensive quality code that considers both product and transportation quality which will lead to reduced waste, improved product quality and an increase in shelf life.


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