Yu, Y., Chen, W., Zhao, D., Zhang, H., Chen, W., Liu, R., & Li, C. (2025). Meat species authentication using portable hyperspectral imaging. Frontiers in Nutrition, 12. https://doi.org/10.3389/fnut.2025.1577642
Hyperspectral imaging (HSI) is revolutionizing food safety by enabling the detection of meat adulteration through the integration of spectral and spatial data. In this study, researchers developed a portable push broom HSI device with a spectral resolution of 5 nm and a spatial resolution of 0.1 mm, controlled via Raspberry Pi for efficient on-site analysis.
To classify different meat species, a support vector machine (SVM) model was combined with spectral space transformation (SST), significantly enhancing prediction accuracy.
The results revealed an impressive classification accuracy of 94.91%, validating the method’s robustness. Additionally, a visualization system was developed to map adulteration distribution, offering practical utility in real-time fraud detection. This portable hyperspectral system presents a promising solution for food quality assurance and safety control across the meat supply chain.
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