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  • Review Article
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Applications of hyperspectral imaging technology in the food industry

Nature Reviews Electrical Engineering volume 1, pages 251–263 (2024)Cite this article

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Abstract

Emerging issues related to food quality include the need to ensure food safety, detect adulteration and enable traceability throughout the food supply chain. Such issues must be addressed to ensure the quality, hygiene and nutritional value of food, and thereby safeguard the health and interests of consumers. Hyperspectral imaging, which combines spectroscopic data on the chemical constituents of a sample and high-resolution imaging of its physical features, is already being used in the food industry for quality inspection purposes. However, the complexity, high cost and large size of hyperspectral imaging equipment is a substantial obstacle to the widespread implementation of this technology. Moreover, the very large, information-rich datasets generated by hyperspectral imaging are difficult to interpret appropriately. This Review describes currently available types of hyperspectral imaging hardware as well as the wide range of image analysis and data modelling tools used to analyse hyperspectral data. Illustrative examples of hyperspectral imaging applications used for food quality inspection are described in detail, and future developments in hyperspectral imaging are presented. The overall aim of this Review is to provide guidance for non-specialist researchers in the selection of hyperspectral imaging equipment, software and models that are appropriate for their intended application.

Key points

  • Appropriate selection of hardware components of hyperspectral imaging systems is important because they determine the quality of the data obtained.

  • Image analysis and modelling tools can help researchers mine useful information from information-rich hyperspectral datasets.

  • Future development of hyperspectral imaging applications is likely to involve device miniaturization, improved analysis methods, data standardization and data-sharing initiatives.

  • Further expansion of hyperspectral imaging applications is expected.

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Fig. 1: Hyperspectral imaging systems used in food quality inspection.
Fig. 2: Principles of beamsplitter and cube imaging techniques.
Fig. 3: Information analysis of hyperspectral data.
Fig. 4: Applications of hyperspectral imaging technology in food quality inspection.
Fig. 5: An application of hyperspectral imaging technology in cereal quality inspection.

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Acknowledgements

The authors are grateful for the support of the Science and Technology Plan Projects of Guangzhou City (2024B03J1315) (H.P.) and the Guangdong Basic and Applied Basic Research Foundation (2022A1515012489) (H.P.).

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Author notes

  1. These authors contributed equally: Da-Wen Sun, Hongbin Pu.

Authors and Affiliations

  1. School of Food Science and Engineering, South China University of Technology, Guangzhou, China

    Da-Wen Sun, Hongbin Pu & Jingxiao Yu

  2. Academy of Contemporary Food Engineering, South China University of Technology, Guangzhou, China

    Da-Wen Sun, Hongbin Pu & Jingxiao Yu

  3. Engineering and Technological Research Centre of Guangdong Province on Intelligent Sensing and Process Control of Cold Chain Foods; & Guangdong Province Engineering Laboratory for Intelligent Cold Chain Logistics Equipment for Agricultural Products, Guangzhou, China

    Da-Wen Sun, Hongbin Pu & Jingxiao Yu

  4. Food Refrigeration and Computerized Food Technology (FRCFT), Agriculture and Food Science Centre, University College Dublin, Dublin, Ireland

    Da-Wen Sun

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All authors researched data for the article and contributed substantially to discussions of its content. H.P. and J.Y. wrote the first draft of the article. D.-W.S. reviewed and edited the manuscript before submission.

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Related links

Food-101: https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/

Food-500: http://123.57.42.89/Dataset_ict/ISIA_Food500_Dir/

UECFood-256: http://foodcam.mobi/dataset256.html

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Sun, DW., Pu, H. & Yu, J. Applications of hyperspectral imaging technology in the food industry. Nat Rev Electr Eng 1, 251–263 (2024). https://doi.org/10.1038/s44287-024-00033-w

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