AUTHOR=Yu Yuewen , Chen Wei , Zhao Dongjie , Zhang Hanwen , Chen Wenliang , Liu Rong , Li Chenxi 

TITLE=Meat species authentication using portable hyperspectral imaging

JOURNAL=Frontiers in Nutrition

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2025.1577642

DOI=10.3389/fnut.2025.1577642

ISSN=2296-861X

ABSTRACT=IntroductionMeat species fraud seriously harms the interests of consumers and causes food safety problems. Hyperspectral imaging is capable of integrating spectral and imaging technology to simultaneously obtain spectral and spatial information, and has been widely applied to detect adulteration and authenticity of meat.MethodsThis study aims to develop a portable hyperspectral imager (HSI) and a discrimination model for meat adulteration detection. The portable push broom HSI was designed with the spectral resolution of 5 nm and spatial resolution of 0.1 mm, and controlled with the Raspberry Pi to meet the requirement of on situ rapid detection. To improve generalization, the model transfer method was also developed to achieve model sharing across instruments, providing a reliable solution for rapid assessment of meat species.ResultsThe results demonstrate that the model transfer method can effectively correct the spectral differences due to instrument variation and improve the robustness of the model. The support vector machine (SVM) classifier combined with spectral space transformation (SST) achieved a best accuracy of 94.91%. Additionally, a visualization map was proposed to provide the distribution of meat adulteration, offering valuable insights for fraud detection.ConclusionThe portable HSI enables on-site analysis, making it an invaluable tool for various industries, including food safety and quality control.