Applications of Multispectral Imaging for Rapid Detection of Food Adulteration

Yunlai Cai

doi:10.47297/taposatWSP2633-456936.20250606

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Applications of Multispectral Imaging for Rapid Detection of Food Adulteration

Volume 6, Issue 6

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Applications of Multispectral Imaging for Rapid Detection of Food Adulteration
Applications of Multispectral Imaging for Rapid Detection of Food Adulteration
College of Chemistry and Chemical Engineering, Xi'an University of Science and Technology, Xi'an, Shaanxi, 710600, China
Vol. 6, Issue 6, Pages: 182-187(2025)
Published：30 June 2025
DOI：10.47297/taposatWSP2633-456936.20250606
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Cai Yunlai.Applications of Multispectral Imaging for Rapid Detection of Food Adulteration[J].Theory and Practice of Science and Technology,2025,06(06):182-187.
DOI：

Cai Yunlai.Applications of Multispectral Imaging for Rapid Detection of Food Adulteration[J].Theory and Practice of Science and Technology,2025,06(06):182-187. DOI： 10.47297/taposatWSP2633-456936.20250606.

摘要

Abstract

The adulteration of food has become a global problem and a regular source of concern to food quality and safety. Traditional laboratory methods for detecting fraud and contaminants are often time-consuming and destructive

creating demand for rapid

on-site analytical techniques. Multispectral imaging technology

as a promising method

could be employed to fast and non-destructively identify food adulteration. This work presents a review on the principles of multispectral imaging and examines its applications across various food categories

including dairy and liquid products

powdered and plant-based products

and meat and seafood. Case examples from recent studies illustrate how multispectral imaging can reveal subtle adulteration that might evade conventional inspection. This work also considers the potential of this technology to enhance authenticity verification in the food industry and integrate into modern quality control practices. The paper concludes by addressing current challenges and prospects for deploying multispectral imaging in routine food monitoring.

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Keywords

references

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