Abstract

Freshness is an important quality of squid with respect to determining the market price. The methods of evaluation of freshness fail to be widely used as a result of the lack of rapidity and quantitation. In the present study, a rapid and non-destructive quantification of squid freshness by Fourier transform infrared spectroscopy (FTIR) spectra combined with chemometric techniques was performed. The relatively linear content change of trimethylamine (TMA-N) and dimethylamine (DMA-N) of squid during storage at 4 °C indicated their feasibility as a freshness indicator, as also confirmed by sensory evaluation. The spectral changes were mainly caused by the degradation of proteins and the production of amines by two-dimensional infrared correlation spectroscopy, among which TMA-N, DMA-N and putrescine were the main amines. The successive projections algorithm (SPA) was employed to select the sensitive wavenumbers to freshness for modeling prediction including partial least-squares regression, support vector regression (SVR) and back-propagation artificial neural network. Generally, the SPA-SVR model of the selected characteristic wavenumber showed a higher prediction accuracy for DMA-N (R2 P =0.951; RMSEP =0.218), whereas both SPA-SVR (R2 P =0.929; RMSEP =2.602) and Full-SVR (R2 P =0.941; RMSEP =2.492) models had a higher predictive ability of TMA-N. The results of the present study demonstrate that FTIR spectroscopy coupled with multivariate calibration shows significant potential for the prediction of freshness in squid. © 2021 Society of Chemical Industry.

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