Discrimination between wild and farmed fish by using NIR spectroscopy
Seafood labeling is a critical tool for consumer information and protection. However, mislabeling, especially regarding origin or production methods, is on the rise. Among the most common forms of mislabeling is the substitution of high-value fish species with lower-value alternatives.
A major challenge is the ability to differentiate between wild-caught and farmed fish. In Spain, a recent development by the leading distribution chain, Mercadona, seeks to address this issue. They've announced a policy to sell wild-caught fish at their fish market counters, while farmed fish will be displayed in trays on refrigerated shelves. This initiative aims to provide consumers with clearer information about the origin of the fish they purchase.
But, while a big step in the right direction, it does not eliminate the potential for fraud at the source.
Given the global interest in combatting fraudulent labeling practices, particularly concerning the production methods of fish, there's a growing need for reliable detection methods. Official methods often prove time-consuming and costly, making them unsuitable for routine on-site monitoring. The ability to trace and authenticate food products is not only essential for economic reasons but also for ensuring safety.
In response to these challenges, a recent European study has been conducted focusing on sea bass (Dicentrarchus labrax). This prized seafood product is prevalent in Mediterranean countries, with both wild-caught and farmed varieties available in retail markets. However, farmed sea bass tends to dominate due to its lower price point.
The study aimed to assess the effectiveness of two techniques — Near-Infrared (NIR) spectroscopy and mass spectrometry—in discriminating between sea bass based on their production methods. By analyzing the docosahexaenoic and arachidonic fatty acid ratio using a Direct Sample Analysis (DSA) system integrated with a time-of-flight (TOF) mass spectrometer, researchers were able to establish a cut-off value of 3.42. This value effectively differentiated between wild-caught and farmed sea bass with 100% sensitivity and specificity.
Additionally, multivariate analysis with portable NIR spectroscopy allowed for the classification of fish production methods. Validation models demonstrated the potential of this approach, achieving high sensitivity (100%) and specificity (90%) in distinguishing between the two product categories.
These findings underscore the promise of utilizing accessible, rapid, and accurate screening methods to combat fraud in commercial sea bass production. The affordability and simplicity of portable NIR spectroscopy, coupled with its ability to create robust models, suggest its suitability for routine fraud control operations directly at production sites.