Rapid and Non-destructive Detection of Iron Porphyrin Content in Pork Using Multispectral Imaging Approach
2016
Ma, Fei | Qin, Hao | Zhou, Cunliu | Wang, Xia | Chen, Conggui | Zheng, Lei
The feasibility of using multispectral imaging (MSI) technique (405–970 nm) for predicting iron porphyrin (IP) content in pork was assessed. Based on nine feature wavelengths identified by successive projections algorithm (SPA), a partial least squares regression (PLSR) calibration model was established, leading to a determination coefficient (R ²) of 0.996 for the prediction set. Visualization of IP content in each pixel of the multispectral images using the prediction model offers an effective way to monitor the distribution and real-time evolution of IP content during the manufacturing process. The results revealed the potentiality of MSI technique combined with PLSR calibration analysis as a rapid and non-destructive evaluation method of IP content for the agri-food industry.
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