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Porphyrin fluorescence imaging for real-time monitoring and visualization of the freshness of beef stored at different temperatures

文献类型： 外文期刊

作者： Liu, Huan 1 ; Zhu, Lei 1 ; Ji, Zengtao 1 ; Zhang, Min 1 ; Yang, Xinting 1 ;

作者机构： 1.Beijing Acad Agr & Forestry Sci, Res Ctr Informat Technol, Beijing 100097, Peoples R China

2.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

3.Minist Agr & Rural Affairs, Acad Agr Planning & Engn, Beijing 100125, Peoples R China

4.Natl Engn Lab Agriprod Qual Traceabil, Beijing 100097, Peoples R China

5.Minist Agr & Rural Affairs, Key Lab Cold Chain Logist Technol Agroprod, Beijing 100097, Peoples R China

关键词： Porphyrin; Fluorescence imaging; Beef; Freshness; Visualization

期刊名称：FOOD CHEMISTRY （ 影响因子：8.8； 五年影响因子：8.6 ）

ISSN： 0308-8146

年卷期： 2024 年 442 卷

页码：

收录情况： SCI

摘要： This study presents a novel fluorescence imaging method for the real-time monitoring of beef quality deterioration and freshness. The fluorescence property of porphyrin in the form of heme can be used to characterize quality changes in beef during storage. Therefore, a fluorescence imaging system with an excitation light source of 440 nm and a CCD camera with a specific wavelength filter of 595 nm was constructed, and the porphyrin fluorescence images of beef samples stored at different temperatures were then collected. The quantitative model for predicting the microbial freshness indicator (TVC) of beef was built with the support vector machine regression (SVR) algorithm and produced satisfactory results with Rc2 and Rp2 of 0.858 and 0.812, respectively. The classification model based on the support vector machine (SVM) algorithm classified beef freshness into "fresh" and "spoiled", with calibration and prediction accuracy of 100 % and 90.9 %, respectively.

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