Nondestructive Detection of Cold Fresh Mutton Based on Hyperspectral Imaging Technology

The hygiene and safety quality of cold fresh lamb meat is of great significance for food safety control and ensuring the safety of residents' consumption. The quality parameters of lamb meat can be used to measure its hygiene and safety, but traditional testing methods have low efficiency and can also affect the sample during the testing process. The aim of this study is to achieve non-destructive testing of cold fresh lamb meat, using spectral technology to detect indicators related to volatile basic nitrogen (TVB-N), pH value, coliform count (MPN), and total bacterial count (TBC). The experimental results show that this technology can effectively distinguish cold fresh lamb meat of different quality states, and has high prediction accuracy for key quality indicators. The validation accuracy of the DNN model reaches 90.09%. Hyperspectral imaging technology provides a highly promising new approach for rapid, accurate, and non-destructive testing of cold fresh lamb, which is expected to be widely applied in meat processing, circulation, and sales, ensuring consumer safety and promoting high-quality development of the industry.