Review paper maps pathway from destructive lab testing to AI-driven real-time monitoring of frozen seafood

A review paper published in Foods by researchers at Jiangsu University (China) maps a pathway from conventional destructive lab testing to continuous, non-destructive, AI-driven quality monitoring of frozen seafood across the cold chain.

Why conventional methods fall short

Freezing extends seafood shelf life and enables global distribution, but it cannot fully prevent quality deterioration during storage and transport. Frozen products undergo interconnected physicochemical changes: ice crystal growth, water redistribution, protein denaturation and oxidation, lipid oxidation, texture deterioration, and shifts in flavour and colour. Laboratory analyses and sensory evaluation remain the dominant assessment tools, yet they are destructive, labour-intensive, and too slow for rapid or real-time cold-chain monitoring.

Non-destructive sensing paired with machine learning

The review examines a range of non-destructive sensing technologies, including:

• near-infrared and Raman spectroscopy
• hyperspectral and fluorescence imaging
• low-field nuclear magnetic resonance
• electronic noses and tongues
• colorimetric sensor arrays
• biosensors

Combined with machine learning and deep learning, these tools can analyse complex data to evaluate freshness, spoilage, oxidation, water-holding capacity, and shelf life without damaging the product. The authors note that fusing information from multiple sensors with AI could yield a more comprehensive quality picture than relying on single measurements or indicators.

Barriers and the road to continuous monitoring

Several obstacles must be addressed before widespread commercial deployment: the need for larger and more diverse datasets, reliable performance across different seafood species and operating conditions, standardised validation methods, and more affordable and portable sensing equipment.

Looking ahead, the paper identifies the integration of sensing technologies with AI, Internet of Things (IoT) connectivity, cloud computing, and digital traceability systems as a promising pathway toward continuous, real-time quality monitoring throughout the seafood cold chain. Such systems could support better shelf-life management, earlier identification of quality deterioration, reduced food waste, improved food safety, and stronger product traceability.

Figure. Non-destructive sensing technologies used for frozen seafood quality assessment, as reviewed in the paper.

The review paper is available in open access in Foods. Source: IIR sector monitoring.