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| Hyperspectral Imaging-Based Simultaneous Assessment of Processing Quality of Chilled Pork |
| HE Jiaxin, GUO Chuanyu, LIU Yuling, WANG Yawen, HAN Ge, PAN Jinfeng, LI Shengjie |
| 1. School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, China; 2. National Engineering Research Center of Seafood, Dalian 116034, China; 3. State Key Laboratory of Seafood Processing and Safety Control, Dalian 116034, China |
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Abstract This study aimed to establish a rapid method based on hyperspectral imaging for the simultaneous assessment of texture characteristics and water-holding capacity in chilled pork. The visible-near-infrared (VIS-NIR, 400–1 050 nm) and near-infrared (NIR, 900–1 700 nm) spectra of pork samples were acquired. Three spectral preprocessing methods—Savitzky-Golay (S-G) smoothing, first derivative (1st-der), and second derivative (2nd-der)—as well as two feature wavelength selection methods—successive projections algorithm (SPA) and two-dimensional correlation spectroscopy (2D-COS)—were compared for their effects on the predictive performance of the partial least squares regression (PLSR) model. The results showed that the model developed using the NIR spectral range exhibited prediction coefficient of determination (R2p) and calibration coefficient of determination (R2 c) values closer to 1, along with lower root mean square error of calibration and root mean square error of prediction, indicating better overall performance compared to the model based on the VISNIR data. Among the spectral preprocessing methods, the best one was 2nd-der, and the 2nd-der-NIR-PLSR model exhibited the best performance with R2c ranging from 0.848 to 0.932 and R2p ranging from 0.648 to 0.829. Additionally, it was found that both SPA and 2D-COS for feature wavelength extraction led to a significant decline in the predictive ability of the PLSR model. In conclusion, the model established based on the full spectral data with 2nd-der preprocessing provides a reliable technical solution for the rapid and non-destructive detection of texture and water-holding capacity in chilled pork.
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Published: 22 September 2026
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2026, Vol. 40 
