Determination of salmon freshness by computer vision based on eye color

文献类型： 外文期刊

第一作者： Jia, Zhixin

作者： Jia, Zhixin;Shi, Ce;Zhang, Jiaran;Yang, Xinting;Li, Meng;Jia, Zhixin;Shi, Ce;Zhang, Jiaran;Yang, Xinting;Jia, Zhixin;Shi, Ce;Zhang, Jiaran;Yang, Xinting;Jia, Zhixin;Shi, Ce;Zhang, Jiaran;Yang, Xinting

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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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