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Quality assessment in frozen seafood: advances in sensing technologies and artificial intelligence.

Auteurs : MOHAMED M. T. O., NUNEKPEKU X., PREMPEH N. Y. A., JIANG W., LI H.

Type d'article : Article de périodique, Synthèse

Résumé

Frozen seafood plays an important role in the global food supply, but maintaining its quality during frozen storage and cold-chain distribution remains a significant challenge. Although freezing effectively slows microbial growth and enzymatic activity, it cannot completely prevent quality deterioration. During frozen storage, seafood undergoes a series of interconnected physicochemical changes, including ice crystal growth, protein denaturation and oxidation, lipid oxidation, water redistribution, and texture deterioration. These changes gradually reduce sensory quality, nutritional value, and overall commercial acceptability. Conventional quality assessment methods, including destructive laboratory analyses and sensory evaluation, are still widely used. However, they are often labor-intensive, time-consuming, and unsuitable for rapid or real-time monitoring in modern cold-chain systems. As a result, increasing attention has been given to non-destructive sensing technologies that can evaluate seafood quality quickly and objectively. This review summarizes the major mechanisms responsible for quality deterioration in frozen seafood, together with recent advances in sensing technologies used to monitor these changes. The sensing approaches discussed include near-infrared (NIR) and Raman spectroscopy, hyperspectral and fluorescence imaging, low-field nuclear magnetic resonance (LF-NMR), electronic nose (E-nose), electronic tongue (E-tongue), colorimetric sensor arrays (CSAs), and biosensors. This review also discusses the growing role of artificial intelligence in frozen seafood quality assessment, including chemometrics, machine learning, deep learning, and multi-sensor data fusion. Particular attention is given to their applications in quality prediction, industrial implementation, and decision support. Finally, current challenges and future research needs are highlighted, with emphasis on the development of interpretable, transferable, and real-time monitoring systems that can support more reliable quality assurance throughout the frozen seafood supply chain.

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Pages : 44 p.

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Détails

  • Titre original : Quality assessment in frozen seafood: advances in sensing technologies and artificial intelligence.
  • Identifiant de la fiche : 30035343
  • Langues : Anglais
  • Sujet : Technologie
  • Source : Foods - vol.15 - n. 16
  • Éditeurs : MDPI
  • Date d'édition : 08/2026
  • DOI : http://dx.doi.org/10.3390/foods15162799

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