文献类型： 外文期刊
作者： Jia, Zhixin 1 ; Li, Meng 2 ; Shi, Ce 1 ; Zhang, Jiaran 1 ; Yang, Xinting 1 ;
作者机构： 1.Beijing Acad Agr & Forestry Sci, Res Ctr Informat Technol, Beijing 100097, Peoples R China
2.China Agr Univ, Beijing 100097, Peoples R China
3.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, 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： Computer vision ?Salmon ?Eye color; parameters ?Chilled storage ?Freshness; indicators
期刊名称：FOOD PACKAGING AND SHELF LIFE （ 影响因子：8.749； 五年影响因子：8.737 ）
ISSN： 2214-2894
年卷期： 2022 年 34 卷
页码：
收录情况： SCI
摘要： To evaluate and predict the freshness of salmon nondestructively, a computer vision technology was developed based on eye color to predict multiple freshness indicators of salmon simultaneously during storage at 0 degrees C. The RGB, L*a*b* , and HSI color spaces of eye images were analyzed by an image processing algorithm. It is demonstrated that the eye color parameters R, G, B, L* , I, and Delta E were correlated with freshness indicators to establish the multiple linear regression (MLR) and support vector regression (SVR) models. The MLR models outperformed SVR models with high correlation coefficients R2, F value, and low relative errors. The achieved results showed that it was a nondestructive, fast method for predicting the freshness of salmon stored at 0 degrees C by evaluating the eye color parameters with computer vision.
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