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The Analytical Scientist / Issues / 2025 / December / Spectroscopy Uncovers Shared Oxidative Marker in Stored Fish Species
Food, Beverage & Agriculture Spectroscopy News and Research

Spectroscopy Uncovers Shared Oxidative Marker in Stored Fish Species

Autofluorescence analysis reveals a consistent FAD-linked signal across salmon, seabream, and amberjack during chilled storage

12/05/2025 2 min read

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Credit: AdobeStock.com

A comparative spectroscopy study has found that autofluorescence signals linked to flavin adenine dinucleotide (FAD) oxidation rise consistently across salmon, red seabream, and Japanese amberjack during chilled storage – pointing to a potential universal marker of oxidative deterioration in raw fish. The work also shows that autofluorescence does not track with inosinic acid (IMP) production, a widely used indicator of freshness.

Researchers in Japan measured autofluorescence spectra from vacuum-packed filets of the three species at four excitation wavelengths (275, 365, 405, and 455 nm), using trout salmon, red seabream, and amberjack prepared under identical conditions. The team applied principal component analysis and curve-fitting methods to decompose the heterogeneous fluorescence profiles and compare spectral changes during storage.

Across species, fluorescence components attributed to FAD oxidation increased over time, with the strongest rise in Japanese amberjack – consistent with its lack of the antioxidant carotenoid astaxanthin. Salmon, which contains high levels of astaxanthin, showed slower oxidative-linked spectral change. Despite these shared oxidative signatures, no fluorescent component correlated with IMP production, and no spectral feature changed in a common way across all species.

The authors report that autofluorescence “reflects oxidative progression during storage but does not correlate with IMP production,” concluding that the technique may support assessment of oxidative state, but is not suitable for predicting freshness via regression models. The findings underscore a key limitation for automated or AI-driven quality assessment tools: species-dependent spectral variability remains significant even under standardized measurement conditions.

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