Table 4. Recent studies on meat quality detection using Raman spectra technique

Category Measured attribute Raman frequency range Analytical method Performance References
Grass carp surimi Changes of protein structure and amino acid residue microenvironment 2,900 cm–1 / Effective (Gao et al., 2018)
Bull beef Sensory characteristics (flavour) 1,300–2,800 cm–1 PLSR Correlation coefficient of 0.80–0.96 (Zhao et al., 2018)
Beef tallow, pork lard, chicken fat, duck oil Adulteration (unsaturated fatty acids and total fatty acids) 700–1,800 cm–1 Correlated linear Correlation coefficient of 0.96674 and 0.97148 (Lee et al., 2018)
Chicken Sodium chloride or sodium bicarbonate 1,659±0.58 cm–1 to 1,661±0.58 cm–1 one-way ANOVA / (Zhu et al., 2018)
Bovine Tenderness (shear force) 800–1,550 cm–1 PLSR Accuracy of 70%–88% (Bauer et al., 2016)
Lamb Intramuscular fat content and major fatty acid groups 500–1,800 cm–1 PLSR and linear regression Correlation coefficient of 0.93 (Fowler et al., 2015)
Bovine serum albumin Orientation of Norfloxacin 300–1,800 cm–1 / / (Lian et al., 2019)
Cooked meat Endpoint temperature 1,800–2,000 cm–1 PLS-DA and PCA Accuracy of 97.87% (Berhe et al., 2015)
Beef lions Eating quality traits (juiciness and tenderness) 671 nm PLSR / (Fowler et al., 2018)
Porcine meat pH 323–2,105 cm–1 ACO Correlation coefficient of 0.90 (Nache et al., 2016)
PLSR, partial least squares regression; ANOVA, one-way analysis of variance; PLS-DA, partial least squares-discriminant analysis; PCA, principle component analysis; ACO, ant colony optimization.