Prediction of total fat, fatty acid composition and nutritional parameters in fish fillets using MID-FTIR spectroscopy and chemometrics

Abstract

Fourier transform mid-infrared (MID-FTIR) spectroscopy coupled with partial least square algorithm (PLS-1) was used to predict total fat, fatty acid composition, and nutritional parameters as content of omega-3/100 g of fish, and fish lipid quality index (FLQ index) of Atlantic bluefin tuna, crevalle jack, and Atlantic Spanish mackerel chilled fillets. Chemometric model was developed with 84 samples from the 3 fish species at different season capture and varying the storage times. The performance of the regression model was evaluated according to coefficients of determination (R2), residual predictive deviation of cross-validation (RPDcv), and percentage relative difference (% RD). Chemometric model provided good reliability in the prediction of total fat (R2 = 0.968, RPDcv = 4.76), fatty acids (R2 between 0.893 and 0.996, RPDcv between 2.35 and 7.68), FLQ index (R2 = 0.997, RPDcv = 8.52), and content of omega-3/100 g of fish (R2 = 0.968, RPDcv = 3.74). The results demonstrated that chemometric model could be applied simultaneously to chilled fillets of these three species.