Rapid detection of fish species and quality in the marketplace

"With increased seafood imports and limited monitoring, fraud and deception in seafood marketing is a growing safety and quality concern. The flesh of many fish species is similar in taste and texture and, therefore, it is difficult to identify species in fillet form. SafetySpect is developing a tabletop system incorporating multimode spectroscopy for real-time quality, adulteration and traceability (QAT) assessment of fish portions. The fish portion will be placed on the scanner plate for immediate analysis. The multimode spectroscopy measurement will be analyzed using algorithms developed using artificial intelligence methods and will display the fish species, quality and nutritional content in seconds. Phase 1 of this project will determine the feasibility of extending existing multimode spectroscopic data analysis for assessment of fish species and quality from 10 to 50 species commonly consumed in the US. We will collect data on fish species, quality, and nutrient content and combine these with spectral data using four reference spectroscopic systems. We will demonstrate scalability and evaluate accuracy of machine learning classification algorithms for the assessment of fish quality, nutrient content, and species authentication. We will determine the design/market requirements and product characteristics for implementing the QAT system in the seafood supply chain."