| Imaging-based techniques |
| Pu et al. (2015) | Pork | Hyperspectral imaging (HSI) (400–1,000 nm) | Classification of fresh and repeated frozen-thawed meat | Classification | CC%=93.14% | CC%=90.91% |
| Xie et al. (2015) | Pork | HSI (400–1,000 nm) | Prediction of color and water-holding capacity | CIE L* | - | r2=0.907 |
| Cooking loss | - | r2=0.845 |
| CIE b* | - | r2=0.814 |
| Drip loss | - | r2=0.762 |
| CIE a* | - | r2=0.716 |
| Cheng et al. (2018) | Pork | HSI (1,000–2,200 nm) | Prediction of tertiary protein structure and enzyme activity | Surface hydrophobicity | r2C=0.893 RMSEC=1.576 | r2P=0.896 RMSEP=1.549 |
| Ca2+-ATPase activity | r2C=0.896 RMSEC=0.014 | r2P=0.879 RMSEP=0.015 |
| Cheng et al. (2019) | Pork | HSI (1,000–2,200 nm) | Prediction of secondary protein structure | α-Helix fraction in actomyosin | r2C=0.789 RMSEC=2.170% | r2P=0.836 RMSEP=1.737% |
| Cheng et al. (2022b) | Pork | Fluorescence-HSI | Prediction of protein oxidation | Carbonyl content | r2C=0.9305 RMSEC=0.1011 | r2P=0.9275 RMSEP=0.0812 |
| Total sulfhydryl content | r2C=0.9550 RMSEC=1.6096 | r2P=0.9512 RMSEP=1.2979 |
| Cheng et al. (2023b) | Pork | HSI (400–1,002 nm) | Prediction of lipid and protein oxidation | TBARS | r2C=0.9889 RMSEC=0.0182 | r2P=0.9724 RMSEP=0.0227 |
| Carbonyl content | r2C=0.9824 RMSEC=0.0530 | r2P=0.9602 RMSEP=0.0702 |
| Cheng et al. (2023a) | Pork | HSI (400–1,002 nm) | Prediction of lipid oxidation | TBARS | r2C =0.9830 RMSEC=0.0153 | r2P =0.9697 RMSEP=0.0184 |
| Fluorescence-HSI | r2C=0.9833 RMSEC=0.0140 | r2P =0.9726 RMSEP=0.0182 |
| Wei et al. (2024) | Beef | HSI (328–1,115 nm) | Prediction of freezing point and water mobility | Freezing point | r2C=0.82 RMSEC=0.12 | r2P=0.76 RMSEP=0.11 |
| P21 | r2C=0.95 RMSEC=0.38 | r2P=0.80 RMSEP=0.67 |
| P22 | r2C=0.96 RMSEC=0.39 | r2P=0.84 RMSEP=0.71 |
| Jeong et al. (2025) | Pork | HSI (402–1,002 nm) | Classification of frozen storage conditions and thawing loss | Frozen storage conditions | CC%=83.20% | CC%=81.82% |
| Thawing loss | CC%=93.36% | CC%=91.92% |
| Spectroscopy-based techniques |
| Gudjónsdóttir et al. (2019) | Atlantic mackerel | Low-field nuclear magnetic resonance (LF-NMR) | Prediction of water content, total lipids, water-holding capacity | Water content | - | r2=0.799 |
| Total lipids | - | r2=0.760 |
| Water-holding capacity | - | r2=0.691 |
| Chen et al. (2020) | Beef | Raman spectroscopy | Prediction of texture properties | Hardness (g) | r2C=0.82 RMSEC=11.9 | r2P=0.82 RMSEP=12.8 |
| Tenderness (N) | r2C=0.83 RMSEC=2.78 | r2P=0.81 RMSEP=2.57 |
| Chewiness (g.s) | r2C=0.91 RMSEC=625 | r2P=0.80 RMSEP=942 |
| Firmness (g) | r2C=0.91 RMSEC=8.70 | r2P=0.81 RMSEP=11.5 |
| Springiness (%) | r2C=0.71 RMSEC=2.75 | r2P=0.53 RMSEP=2.26 |
| Chen et al. (2023) | Beef | Raman spectroscopy | Prediction of water content and water-holding capacity | Thawing loss | r2C=0.994 RMSEC=0.640 | r2P=0.971 RMSEP=1.436 |
| Water content | r2C=0.966 RMSEC=0.450 | r2P=0.928 RMSEP=0.582 |
| Ropodi et al. (2018) | Beef | Fourier-transform infrared (FTIR) | Classification of fresh and frozen beef at –20°C (7 and 32 d) | Classification | CC%=100% | CC%=93.33% |
| Cáceres-Nevado et al. (2021) | Pork | Near-infrared (NIR) | Classification of fresh and frozen pork at –20°C | Classification | CC%=99.35% | CC%=100% |