Modernizing Fishmeal Processing: Cutting-Edge NIR Technology Enhances Quality Control

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Researchers from the University of Iceland and Matis Food and Biotech R&D in Reykjavík have unveiled an innovative study leveraging near-infrared (NIR) spectroscopy for real-time monitoring of fishmeal and oil processing. This advanced method promises to optimize product quality and streamline production, particularly in lipid composition and protein concentration—key markers for high-value fishmeal products.

Fine powdery brown mixture of fishmeal showing grainy texture © fotogurmespb - stock.adobe.com

Fine powdery brown mixture of fishmeal showing grainy texture © fotogurmespb - stock.adobe.com

The production of fishmeal and fish oil, primarily from pelagic species like mackerel and herring, has remained largely unchanged for decades. With rising competition from alternative protein sources and increasing demands for higher-value products, this traditional industry faces pressure to modernize. Current quality assessment methods, however, are slow, labor-intensive, and destructive. The study, published in Foods by María Gudjónsdóttir, Gudrún Svana Hilmarsdóttir, Ólafur Ögmundarson, and Sigurjón Arason, introduces a game-changing approach using near-infrared (NIR) spectroscopy and chemometrics to predict critical chemical quality parameters throughout the processing pipeline (1–3).

NIR Spectroscopy: A Non-Destructive, Real-Time Tool

NIR spectroscopy, a rapid and non-destructive analytical technique, measures the absorption of light in the near-infrared region by chemical bonds, such as C-H, O-H, and N-H. This allows for precise detection of moisture, protein, and lipid content in fishmeal—a substantial improvement over traditional methods like the Kjeldahl nitrogen test. Paired with advanced chemometric data processing, NIR spectroscopy simplifies calibration while offering detailed insights into the chemical variations occurring at each processing stage (1–3).

Key Findings

Predicting Water Content: The study demonstrated NIR spectroscopy’s robustness in predicting water content across a wide range (0.3–93 g/100 g). Partial least square regression (PLSR) models showed exceptional performance, with a coefficient of determination (R²) of 0.9938 and a root mean square error of cross-validation (RMSECV) of 2.41 g/100 g. This accuracy enables precise process adjustments, ensuring optimal water removal to improve product quality (1).

Lipid Content Monitoring: Total lipid content, ranging from 1.2% to nearly 100% during processing, was effectively predicted by NIR models. The study highlighted the technique’s potential to reduce reliance on labor-intensive and environmentally harmful lipid extraction methods. Importantly, it allows producers to monitor lipid degradation in real time, optimizing the retention of valuable omega-3 fatty acids like docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) (1).

Fat-Free Dry Matter (FFDM) Analysis: The research also explored the prediction of FFDM, a measure of protein concentration and other non-lipid components. NIR spectroscopy achieved reliable predictions (R² = 0.9356, RMSECV = 5.58 g/100 g), outperforming traditional methods that cannot differentiate between protein and non-protein nitrogen. This capability is vital for maintaining the consistency of high-protein fishmeal products (1).

Fatty Acid Composition: NIR spectroscopy proved highly effective in distinguishing fatty acid saturation levels, including saturated (SFA), monounsaturated (MUFA), and polyunsaturated fatty acids (PUFA). DHA and EPA, critical omega-3 fatty acids, were also successfully monitored, with high prediction accuracy (R² values of 0.8785 and 0.8689, respectively). This insight ensures product quality while preserving the health benefits of these essential lipids (1).

Implications for Industry

This pioneering approach offers significant economic and environmental benefits. By replacing traditional, time-intensive methods with a faster, non-destructive alternative, fishmeal producers can achieve consistent product quality, minimize waste, and reduce costs. Additionally, NIR’s ability to monitor key parameters online in real time supports the shift towards producing high-value, human-grade fish protein concentrates (1).

Final Comment

The study by Gudjónsdóttir and her colleagues marks a milestone in fishmeal and oil production. By combining NIR spectroscopy with chemometric modeling, the team has demonstrated a scalable solution for real-time quality monitoring and process optimization. This innovation not only enhances the sustainability and profitability of fishmeal production but also paves the way for broader applications in the food and biotech industries (1).

References

(1) Gudjónsdóttir, M.; Hilmarsdóttir, G. S.; Ögmundarson, Ó.; Arason, S. Near-Infrared Spectroscopy and Chemometrics for Effective Online Quality Monitoring and Process Control during Pelagic Fishmeal and Oil Processing. Foods 202413 (8), 1186. DOI: 10.3390/foods13081186

(2) Cozzolino, D.; Chree, A.; Murray, I.; Scaife, J. R. The Assessment of the Chemical Composition of Fishmeal by Near Infrared Reflectance Spectroscopy. Aquac. Nutr. 2002, 8 (2), 149–155. DOI: 10.1046/j.1365-2095.2002.00206.x

(3) Cozzolino, D.; Chree, A.; Murray, I.; Scaife, J. R. Usefulness of Near Infrared Spectroscopy to Monitor the Extent of Heat Treatment in Fish Meal. IJFST 2009, 44 (8), 1579–1584. DOI: 10.1111/j.1365-2621.2008.01845.x

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