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

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.