Informative Wavelength Selection for Evaluation of Bacterial Spoilage in Raw Salmon (Salmo salar) Fillet Using FT-NIR Spectroscopy

Roma Panwar, Shin Ping Lin, Shyh Hsiang Lin, Jer An Lin, Yu Jen Wang, Yung Kun Chuang

Research output: Contribution to journalArticlepeer-review

Abstract

This study highlights the potential of Fourier-transform near-infrared (FT-NIR) spectroscopy for the on-site, nondestructive detection of spoilage caused by bacterial action in raw salmon (Salmo salar) fillets. A stepwise multiple linear regression model with first-derivative spectrum transformation was combined with the standard normal variate and detrend preprocessing techniques. The model achieved correlation values of 0.97 in both the calibration and validation sample sets, with root mean square error values of 0.18 and 0.20 log CFU/mL, respectively. These accurate results reveal the precision of FT-NIR spectroscopy for assessing the spoilage caused by bacteria. The most informative wavelengths (885.27 nm, 1026.27 nm, 1039.93 nm, 1068.38 nm, 1257.55 nm, 1267.75 nm, and 1453.49 nm) related to the total bacterial count’s identification were obtained. The innovative, cost-effective, and feasible approach outlined in this article is a promising methodology for enhancing the safety and quality standards of various fishery products.

Original languageEnglish
Article number2074
JournalFoods
Volume14
Issue number12
DOIs
Publication statusPublished - Jun 2025

Keywords

  • Fourier-transform near-infrared spectroscopy
  • informative wavelengths
  • salmon
  • spoilage
  • total bacterial count

ASJC Scopus subject areas

  • Food Science
  • Microbiology
  • Health(social science)
  • Health Professions (miscellaneous)
  • Plant Science

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