Meat species authentication using portable hyperspectral imaging

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...

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Main Authors: Yuewen Yu, Wei Chen, Dongjie Zhao, Hanwen Zhang, Wenliang Chen, Rong Liu, Chenxi Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-04-01
Series:Frontiers in Nutrition
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Online Access:https://www.frontiersin.org/articles/10.3389/fnut.2025.1577642/full
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author Yuewen Yu
Yuewen Yu
Wei Chen
Wei Chen
Wei Chen
Dongjie Zhao
Dongjie Zhao
Hanwen Zhang
Hanwen Zhang
Wenliang Chen
Wenliang Chen
Rong Liu
Rong Liu
Chenxi Li
Chenxi Li
author_facet Yuewen Yu
Yuewen Yu
Wei Chen
Wei Chen
Wei Chen
Dongjie Zhao
Dongjie Zhao
Hanwen Zhang
Hanwen Zhang
Wenliang Chen
Wenliang Chen
Rong Liu
Rong Liu
Chenxi Li
Chenxi Li
author_sort Yuewen Yu
collection DOAJ
description 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.
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spelling doaj-art-d7e4a2cfcfa545c296af07eb84336bc32025-08-20T03:04:11ZengFrontiers Media S.A.Frontiers in Nutrition2296-861X2025-04-011210.3389/fnut.2025.15776421577642Meat species authentication using portable hyperspectral imagingYuewen Yu0Yuewen Yu1Wei Chen2Wei Chen3Wei Chen4Dongjie Zhao5Dongjie Zhao6Hanwen Zhang7Hanwen Zhang8Wenliang Chen9Wenliang Chen10Rong Liu11Rong Liu12Chenxi Li13Chenxi Li14State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin, ChinaSchool of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, ChinaDepartment of Ophthalmology, Tianjin Eye Hospital, Nankai University Affiliated Eye Hospital, Nankai University, Tianjin, ChinaClinical College of Ophthalmology, Tianjin Medical University, Tianjin, ChinaTianjin Key Laboratory of Ophthalmology and Visual Science, Tianjin Eye Hospital, Tianjin, ChinaState Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin, ChinaSchool of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, ChinaState Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin, ChinaSchool of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, ChinaState Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin, ChinaSchool of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, ChinaState Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin, ChinaSchool of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, ChinaState Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin, ChinaSchool of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, ChinaIntroductionMeat 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.https://www.frontiersin.org/articles/10.3389/fnut.2025.1577642/fullhyperspectral imagingmeat adulterationmodel transferdiscrimination modeladulteration visualization
spellingShingle Yuewen Yu
Yuewen Yu
Wei Chen
Wei Chen
Wei Chen
Dongjie Zhao
Dongjie Zhao
Hanwen Zhang
Hanwen Zhang
Wenliang Chen
Wenliang Chen
Rong Liu
Rong Liu
Chenxi Li
Chenxi Li
Meat species authentication using portable hyperspectral imaging
Frontiers in Nutrition
hyperspectral imaging
meat adulteration
model transfer
discrimination model
adulteration visualization
title Meat species authentication using portable hyperspectral imaging
title_full Meat species authentication using portable hyperspectral imaging
title_fullStr Meat species authentication using portable hyperspectral imaging
title_full_unstemmed Meat species authentication using portable hyperspectral imaging
title_short Meat species authentication using portable hyperspectral imaging
title_sort meat species authentication using portable hyperspectral imaging
topic hyperspectral imaging
meat adulteration
model transfer
discrimination model
adulteration visualization
url https://www.frontiersin.org/articles/10.3389/fnut.2025.1577642/full
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