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  1. Home
  3. Simultaneous Assessment Of Chicken Freshness And Authenticity Using A Single Multispectral Imaging Device: A Cross-laboratory Evaluation Using Identical Instruments.
  1. Home
  3. Simultaneous Assessment Of Chicken Freshness And Authenticity Using A Single Multispectral Imaging Device: A Cross-laboratory Evaluation Using Identical Instruments.

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Simultaneous Assessment of Chicken Freshness and Authenticity Using a Single Multispectral Imaging Device: A

Anastasia Lytou1, Maria-Konstantina Spyratou1, Aske Schultz Carstensen2

  • 1Laboratory of Microbiology and Biotechnology of Foods, Department of Food Science and Human Nutrition, School of Food and Nutritional Sciences, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece.

Sensors (Basel, Switzerland)
|May 13, 2026

View abstract on PubMed

Summary
This summary is machine-generated.
Keywords:
identical instrumentsmeat quality aspectsmicroorganismsportable sensorspectral imagingspoilage

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A portable multispectral imaging (MSI) system accurately assesses chicken meat freshness and authenticity. This technology offers rapid, simultaneous quality evaluation using a single instrument.

Area of Science:

  • Food Science
  • Analytical Chemistry
  • Agricultural Technology

Background:

  • Assessing chicken meat quality (freshness, authenticity) is crucial for food safety and consumer trust.
  • Current methods can be time-consuming or require multiple analyses.
  • Multispectral imaging (MSI) offers a potential non-destructive, rapid alternative.

Purpose of the Study:

  • To evaluate a portable MSI system for simultaneous assessment of chicken meat freshness and authenticity.
  • To compare the performance of different modeling techniques (PLS-R, kNN, SVM) for MSI data analysis.
  • To identify key wavelengths contributing to quality attribute prediction.

Main Methods:

  • A portable MSI system was used to analyze fresh and thawed chicken meat samples.
  • Samples were analyzed for total aerobic counts and subjected to MSI throughout storage.
  • Authenticity (origin) was assessed using Greek and Danish chicken samples.
  • Data were modeled using Partial Least Squares Regression (PLS-R), k-Nearest Neighbors (kNN), and Support Vector Machines (SVM).

    • Main Results:

    • The MSI system demonstrated potential for predicting total viable counts, with kNN and PLS-R showing strong performance (R² up to 0.979).
    • Wavelength 460 nm was identified as critical for freshness prediction.
    • Accurate classification of chicken origin (Greek vs. Danish) was achieved, with PLS-DA highlighting wavelengths 660 nm and 850 nm.
    • Optimal algorithms and significant wavelengths varied between fresh and thawed samples and for different quality attributes.

    Conclusions:

    • The portable MSI system is a promising tool for rapid, non-destructive, and simultaneous evaluation of chicken meat freshness and authenticity.
    • MSI combined with chemometric modeling provides a robust approach for quality control in the poultry industry.
    • Further research can optimize algorithms and explore broader applications for meat quality assessment.