Hyperspectral Imaging for Foreign Matter Detection in Foods: Advances, Challenges, and Future Directions

Li, Wenlong; Wu, Yuqing; Du, Liuzi; Shang, Xianwen; Shi, Jiyong

doi:10.3390/foods14173026

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Hyperspectral Imaging for Foreign Matter Detection in Foods: Advances, Challenges, and Future Directions

by

Wenlong Li

,

Yuqing Wu

,

Liuzi Du

,

Xianwen Shang

and

Jiyong Shi

^*

Agricultural Product Processing and Storage Lab, School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China

^*

Author to whom correspondence should be addressed.

Foods 2025, 14(17), 3026; https://doi.org/10.3390/foods14173026

Submission received: 27 July 2025 / Revised: 11 August 2025 / Accepted: 15 August 2025 / Published: 28 August 2025

(This article belongs to the Special Issue Advances of Novel Technologies in Food Analysis and Food Safety)

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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.

Keywords: hyperspectral imaging; deep learning; adulteration detection; food safety

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MDPI and ACS Style

Li, W.; Wu, Y.; Du, L.; Shang, X.; Shi, J. Hyperspectral Imaging for Foreign Matter Detection in Foods: Advances, Challenges, and Future Directions. Foods 2025, 14, 3026. https://doi.org/10.3390/foods14173026

AMA Style

Li W, Wu Y, Du L, Shang X, Shi J. Hyperspectral Imaging for Foreign Matter Detection in Foods: Advances, Challenges, and Future Directions. Foods. 2025; 14(17):3026. https://doi.org/10.3390/foods14173026

Chicago/Turabian Style

Li, Wenlong, Yuqing Wu, Liuzi Du, Xianwen Shang, and Jiyong Shi. 2025. "Hyperspectral Imaging for Foreign Matter Detection in Foods: Advances, Challenges, and Future Directions" Foods 14, no. 17: 3026. https://doi.org/10.3390/foods14173026

APA Style

Li, W., Wu, Y., Du, L., Shang, X., & Shi, J. (2025). Hyperspectral Imaging for Foreign Matter Detection in Foods: Advances, Challenges, and Future Directions. Foods, 14(17), 3026. https://doi.org/10.3390/foods14173026

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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Hyperspectral Imaging for Foreign Matter Detection in Foods: Advances, Challenges, and Future Directions

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