Litcius/Paper detail

Quest of Intelligent Research Tools for Rapid Evaluation of Fish Quality: FTIR Spectroscopy and Multispectral Imaging Versus Microbiological Analysis

Maria Govari, Paschalitsa Tryfinopoulou, Foteini F. Parlapani, Ioannis S. Boziaris, Efstathios Ζ. Panagou, George‐John E. Nychas

2021Foods24 citationsDOIOpen Access PDF

Abstract

The aim of the present study was to assess the microbiological quality of farmed sea bass (Dicentrarchus labrax) fillets stored under aerobic conditions and modified atmosphere packaging (MAP) (31% CO2, 23% O2, 46% Ν2,) at 0, 4, 8, and 12 °C using Fourier transform infrared (FTIR) spectroscopy and multispectral imaging (MSI) in tandem with data analytics, taking into account the results of conventional microbiological analysis. Fish samples were subjected to microbiological analysis (total viable counts (TVC), Pseudomonas spp., H2S producing bacteria, Brochothrix thermosphacta, lactic acid bacteria (LAB), Enterobacteriaceae, and yeasts) and sensory evaluation, together with FTIR and MSI spectral data acquisition. Pseudomonas spp. and H2S-producing bacteria were enumerated at higher population levels compared to other microorganisms, regardless of storage temperature and packaging condition. The developed partial least squares regression (PLS-R) models based on the FTIR spectra of fish stored aerobically and under MAP exhibited satisfactory performance in the estimation of TVC, with coefficients of determination (R2) at 0.78 and 0.99, respectively. In contrast, the performances of PLS-R models based on MSI spectral data were less accurate, with R2 values of 0.44 and 0.62 for fish samples stored aerobically and under MAP, respectively. FTIR spectroscopy is a promising tool to assess the microbiological quality of sea bass fillets stored in air and under MAP that could be effectively employed in the future as an alternative method to conventional microbiological analysis.

Topics & Concepts

Sea bassPartial least squares regressionFourier transform infrared spectroscopyTotal Viable CountFood scienceDicentrarchusMultispectral imageEnvironmental scienceChemistryMathematicsBiologyBacteriaFish <Actinopterygii>Computer scienceFisheryArtificial intelligenceEngineeringStatisticsGeneticsChemical engineeringSpectroscopy and Chemometric AnalysesMeat and Animal Product QualityListeria monocytogenes in Food Safety