Li Wenlong, Wu Yuqing, Du Liuzi, Shang Xianwen, Shi Jiyong
Agricultural Product Processing and Storage Lab, School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
Foods. 2025 Aug 28;14(17):3026. doi: 10.3390/foods14173026.
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.
食品中异物的存在给消费者带来食品安全问题，并直接威胁到食品供应链。为了确保食品质量和卫生、提高经济效益以及保护消费者的健康权利，快速、无损地检测食品中的异物是一项亟待开展的任务。高光谱成像技术可以获取异物在多个波长下的高分辨率光谱信息，并且在食品安全检测中得到了广泛应用。然而，该系统的成本和尺寸仍然是其进一步发展的障碍。此外，目前在生产过程中获取异物样本以及存储和共享高光谱数据方面还没有有效的解决方案。本文综述介绍了高光谱成像系统，包括软件和硬件，以及一系列用于处理光谱图像的算法。重点关注用于异物检测任务的高光谱成像案例，并探讨未来的发展和挑战。
