Raman Spectroscopy Emerges as a Fingerprinting Tool for Seafood Authenticity and Safety

Raman spectroscopy, a technique that reads the molecular fingerprints of a sample by measuring how laser light scatters from its chemical bonds, is being positioned as a powerful non-destructive screening tool for the world’s seafood supply. A critical review published in Discover Life examines how the technology, in all its variants from benchtop instruments to handheld devices, could transform authentication, freshness monitoring and contaminant detection across fisheries and aquaculture. The scale of the task is considerable: global fisheries and aquaculture production reached 235 million tonnes in 2024, including 195 million tonnes of aquatic animals, according to the FAO’s State of World Fisheries and Aquaculture 2026, supplying at least one-fifth of animal protein consumption for about 3.1 billion people and supporting more than 600 million livelihoods.

The review, authored by Shalu, Vishal, Aniruddha S. Sharangdhar, Raghvendra Katiyar, Yash Khalasi, Patekar Prakash and Kedar Nath Mohanta, takes an unusually cautious approach to the evidence. Rather than pooling accuracy figures from different studies, the authors organize findings by matrix, target analyte, excitation wavelength, sampling geometry, preprocessing strategy and validation design. They argue that this is essential because fish species, tissue types, storage conditions, reference assays and validation strategies differ so substantially across studies that directly comparing reported accuracies would be misleading. The conclusion they reach is measured: Raman spectroscopy is a promising alternative or complementary screening technology, not a replacement for established reference methods such as DNA sequencing, chromatography or elemental analysis.

One of the most pressing applications is species authentication. Seafood fraud, including mislabeling and species substitution, remains widespread. A 2025 United States meta-analysis of 35 studies covering 4,179 commercial samples reported an overall mislabeling rate of 39.1 percent, with species substitution in 26.2 percent of samples. Raman spectroscopy can discriminate species by capturing differences in protein, lipid and pigment composition. In a 2023 study spanning 11 biological species or groups, portable 785-nanometre Raman systems paired with hierarchical chemometric classifiers achieved 93 percent accuracy for both Salmonidae and non-Salmonidae groups at the second classification level, while benchtop models reached 90 and 84 percent respectively. The authors stress that such results demonstrate feasibility but that regulatory use would require broad spectral libraries, multiple biological replicates and independent validation.

The technique’s molecular specificity extends to detecting chemical deception within products. Raman combined with partial least squares regression has been investigated for quantitative adulteration assessment, with reported detection thresholds of 1 percent by weight for gelatin and 5 percent excess water in cited applications, values the review emphasizes are study-specific rather than universal limits. Surface-enhanced Raman spectroscopy, or SERS, which amplifies weak signals at nanostructured metal surfaces, can identify canned tuna, smoked salmon and fish sauce down to nanogram-level detection, and aptamer-modified substrates can solve the problem of invalid DNA testing in heavily processed canned fish.

Contaminant detection is where SERS shows some of its most striking numbers. A descriptive summary of reported chemical detection limits in the review found values ranging from 0.001 to 1.0 parts per billion, with a median of 0.05 parts per billion. The lowest reported value was 0.001 parts per billion for chloramphenicol, followed by 0.01 for enrofloxacin, 0.02 for malachite green and 0.05 for oxytetracycline. A 2018 study using silver nanoflower substrates achieved recoveries of 92 to 108 percent for in-situ SERS detection of malachite green in salmon extracts, with a limit of detection of 0.02 parts per billion, and could detect its metabolite leucomalachite green at sub-ppb levels. Mercury in digested fish tissue has been detected at 0.5 parts per billion with performance matching atomic absorption spectroscopy, while a gold-coated magnetic nanoparticle platform detected polycyclic aromatic hydrocarbons in smoked salmon and eels at 0.1 to 1 parts per billion.

Freshness assessment is another active frontier. Fish quality deteriorates after slaughter through glycolytic acidification, rigor mortis, enzymatic autolysis, lipid oxidation and microbial decomposition, and core indicators include total volatile basic nitrogen, trimethylamine, biogenic amines and the K-value, a nucleotide-degradation index central to aquatic-product freshness. Raman spectroscopy can quantify K-value using characteristic bands at 728 and 785 wavenumbers. Near-infrared Raman combined with a partial least squares model tested on Atlantic salmon and cod achieved a coefficient of determination above 0.92 with a cross-validation error of 0.97, and Raman-based K-index assessment has been verified in chilled sea bass. Raman-based prediction of total volatile basic nitrogen in sea bass has reported an external prediction R² of 0.898, while a 2024 study fusing NIR and Raman data for salmon reported an R² of 0.910, figures the review insists must not be treated as pooled estimates because species, storage regimes and validation designs differ.

The technology’s versatility across the value chain is remarkable. In processing, portable devices have predicted sodium chloride content with an R² of 0.93 and moisture content with an R² of 0.96 in cured fish, supporting online process control. In surimi production, the ratio of disulfide bond peaks at 500 and 540 wavenumbers correlates with gel breaking force at an R² of 0.91, allowing producers to fine-tune heating processes. A 2026 study even used single-cell Raman spectra from 14 microalgal species isolated from real aquaculture water, fed into a convolutional neural network, to distinguish harmful cyanobacteria from chlorophytes with a reported 99.6 percent classification accuracy, though the authors caution this came from a controlled dataset and does not constitute validated farm-wide monitoring.

Yet the review is emphatic that laboratory promise does not equal field readiness. Autofluorescence from biological fluorophores such as flavins, porphyrins and lipid oxidation products remains the most common technical challenge, masking weak Raman signals particularly in pigmented, smoked and fermented products. SERS substrate reproducibility, matrix fouling and analyte adsorption requirements constrain quantitative work. Handheld spectrometers, some weighing as little as 500 grams and now available from commercial platforms with built-in library matching, still trail laboratory instruments in resolution and sensitivity. Perhaps most fundamentally, fishery Raman datasets are often small, and spectra from the same specimen are not statistically independent, meaning random cross-validation can overestimate real-world performance. The field also lacks an open spectral library dedicated to fishery products and a unified spectral data format, creating barriers to cross-institutional comparison and model transfer.

To bridge the gap between demonstration and deployment, the authors propose a phased roadmap. Phase one, spanning zero to three years, focuses on standardized sampling, spectral libraries and external validation. Phase two, from three to six years, targets multi-site portable systems, reproducible SERS substrates and validated model transfer. Phase three, from six to ten years, envisions networked monitoring, federated learning, multimodal spectroscopy combining Raman with near-infrared and hyperspectral imaging, and selective in-line control where validation supports the intended decision.

The review’s overall message is one of disciplined optimism. Raman spectroscopy offers something genuinely distinctive: molecularly specific, non-destructive measurements with minimal sample preparation, applicable from fish markets and ports to aquaculture ponds and processing lines. But the authors are clear that the practical goal is not a paradigm shift by assertion. Positive or threshold-crossing screening results should remain linked to confirmatory reference methods until equivalence is demonstrated, and regulators should prioritize intended-use definitions, reference methods, decision thresholds and independent performance requirements. What emerges is a portrait of a technology at an inflection point, scientifically mature enough to be taken seriously by industry and regulators alike, yet honest enough about its own limitations to know that the hardest work, standardized validation across species, instruments and real-world conditions, still lies ahead.

Subject of Research: A review of Raman spectroscopy applications for authentication, freshness, contaminant detection and quality monitoring across the fisheries and aquaculture value chain.

Article Title: Application of Raman spectroscopy in fisheries and aquaculture

Article References: Shalu, Vishal, Sharangdhar, A. S., Katiyar, R., Khalasi, Y., Prakash, P., & Mohanta, K. N. (2026). Application of Raman spectroscopy in fisheries and aquaculture. Discover Life, 56(1), Article 45. https://doi.org/10.1007/s11084-026-09764-2

Image Credits: AI Generated

DOI: 10.1007/s11084-026-09764-2

Keywords: Raman spectroscopy, SERS, seafood fraud, species authentication, fish freshness, aquaculture, food safety, contaminant detection, chemometrics, portable spectrometers, microplastics, SORS