Abstract
The presence of foreign matter in food poses food safety issues for consumers and directly threatens the food supply chain. In order to ensure food quality and hygiene, promote economic efficiency, and protect consumers' health rights, the rapid, non-destructive detection of foreign matter in food is an urgent task that requires development. Hyperspectral imaging technology can obtain high-resolution spectral information of foreign matter in multiple wavelengths, and it is widely used in food safety testing. However, the cost and size of the system remain obstacles to further development. Additionally, there are currently no effective solutions for acquiring foreign matter samples or for storing and sharing hyperspectral data during production. This review introduces hyperspectral imaging systems, covering both the software and hardware, as well as a series of algorithms for processing spectral images. The focus is on cases of hyperspectral imaging used for foreign matter detection tasks, with an examination of future developments and challenges.