Rapid and non-destructive identification of water-injected beef samples using multispectral imaging analysis

文献类型： 外文期刊

第一作者： Liu, Jinxia

作者： Liu, Jinxia;Pan, Wenjuan;Ma, Fei;Liu, Changhong;Chen, Wei;Zheng, Lei;Cao, Yue;Zheng, Lei;Wang, Qiu;Yang, Jianbo

作者机构：

关键词： Multispectral imaging;Water-injected beef;Partial least squares regression;Feature information;Non-destructive analysis

期刊名称：FOOD CHEMISTRY （ 影响因子：7.514； 五年影响因子：7.516 ）

ISSN： 0308-8146

年卷期： 2016 年 190 卷

页码：

收录情况： SCI

摘要： Water-injected beef has aroused public concern as a major food-safety issue in meat products. In the study, the potential of multispectral imaging analysis in the visible and near-infrared (405-970 nm) regions was evaluated for identifying water-injected beef. A multispectral vision system was used to acquire images of beef injected with up to 21% content of water, and partial least squares regression (PLSR) algorithm was employed to establish prediction model, leading to quantitative estimations of actual water increase with a correlation coefficient (r) of 0.923. Subsequently, an optimized model was achieved by integrating spectral data with feature information extracted from ordinary RGB data, yielding better predictions (r = 0.946). Moreover, the prediction equation was transferred to each pixel within the images for visualizing the distribution of actual water increase. These results demonstrate the capability of multispectral imaging technology as a rapid and non-destructive tool for the identification of water-injected beef. (C) 2015 Elsevier Ltd. All rights reserved.

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