Non-destructive monitoring the freshness of sea bass fillets using Raman spectroscopy with orthogonal signal correction and multivariate analysis

TVB-N is a commonly used chemical indicator for assessing the freshness of aquatic products during storage. In this study, the combination of Raman spectroscopy with multivariate analysis for monitoring the freshness of sea bass (Lateolabrax japonicus) fillets was investigated. Orthogonal signal correction (OSC) method was applied to pre-process the Raman spectra of sea bass fillets with different freshness levels. Results suggested that PLSR models outperformed PCR and SVMR models in monitoring TVB-N values of sea bass fillets. In comparison, the OSC-PLSR model with full-band Raman spectra showed the best performance for predicting TVB-N contents, with R2C of 0.981, RMSEC of 1.162 mgN/100 g, R2CV of 0.804, RMSECV of 3.756 mgN/100 g, R2P of 0.898, RMSEP of 2.199 mgN/100 g, and RPD of 3.824. In addition, sea bass fillets with three different freshness grades (firstgrade, second-grade, and spoilage) could be distinguished from the PCA score plot. The PLS-DA model showed an average classification accuracy of 91.11% for different freshness grades. The combination of Raman spectroscopy and chemometrics provided a new tool for the non-destructive evaluation of fish quality.

Automated summary

This study investigated the use of Raman spectroscopy combined with multivariate analysis to monitor the freshness of sea bass fillets. PLSR models outperformed PCR and SVMR models in monitoring the TVB-N values of the fillets. The combination of Raman spectroscopy and chemometrics provided a new tool for the non-destructive evaluation of fish quality.