Nondestructive monitoring of chicken meat freshness using hyperspectral imaging technology

This study investigated the capability of hyperspectral imaging technology for monitoring the freshness of chicken meat during storage. Fresh chicken meats were prepared and stored in a refrigerator at 4 °C for 8 days. Hyperspectral images were obtained every 24 hours for meat samples with ImSpector V10E, and the average spectral reflectance data for each sample were extracted. The bacteria in colony forming unit (CFU) for each meat sample was measured by the basic bacterial cultivation techniques. Simple correlation analysis and the two band vegetation index (TBVI) methods were used to develop the spectra-based CFU prediction models. Results indicated that the model with the TBVI based on the wavelengths 700 nm and 650 nm achieved the optimal estimation of CFU on meat surface (R2=0.9328). The TBVI values based on the above two wavelengths were calculated for all pixels on meat images, and were visualized by displaying the TBVI values for all corresponding pixels on a new image. The predicted CFU for meat samples were then calculated and visualized by incorporating the model into the new TBVI image. The results demonstrated the promising potential of hyperspectral imaging technology for the detection of bacteria on meat surface.