Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7591356 | Food Chemistry | 2016 | 6 Pages |
Abstract
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.
Keywords
Related Topics
Physical Sciences and Engineering
Chemistry
Analytical Chemistry
Authors
Jinxia Liu, Yue Cao, Qiu Wang, Wenjuan Pan, Fei Ma, Changhong Liu, Wei Chen, Jianbo Yang, Lei Zheng,