The fatty acid profile of crevalle jack was compared with that of Atlantic bluefin tuna, Atlantic Spanish mackerel, red snapper, and Nile tilapia. Crevalle jack and Atlantic Spanish mackerel showed similarities in their fatty acid profiles, with the saturated fatty acid > monounsaturated fatty acid > polyunsaturated fatty acid pattern. Atlantic bluefin tuna and red snapper followed a similar pattern to each other, with the polyunsaturated fatty acid > saturated fatty acid > monounsaturated fatty acid pattern, and the pattern for Nile tilapia was saturated fatty acid > monounsaturated fatty acid ≈ polyunsaturated fatty acid. In winter, the DHA+EPA content of crevalle jack (493.2 mg/100 g fillet) was 37% lower than Atlantic bluefin tuna and Atlantic Spanish mackerel, 35% higher than for the red snapper, and 2.8 fold higher than for the Nile tilapia. The best nutritional indices were for Atlantic bluefin tuna > red snapper > Atlantic Spanish mackerel > crevalle jack > Nile tilapia.

Fourier transform mid-infrared spectroscopy (MIR-FTIR) and a partial least square algorithm (PLS-1) were used to predict the deterioration indices, pH, and chemical composition of Atlantic bluefin tuna, crevalle jack, and Atlantic Spanish mackerel chilled fillets. To build calibration models, 90 samples from the 3 fish species were analysed to different seasons and were stored for various times. The performance of the regression models was evaluated based on the coefficients of determination (R 2 ), residual predictive deviation of cross-validation (RPDcv), and percentage relative difference (% RD). Chemometric models provided good reliability in the prediction of the chemical composition (R 2 between 0.969 and 0.992, RPDcv between 5.01 and 5.59%), the pH (R 2 = 0.987, RPDcv = 7.18), and can be used for screening of deterioration indices (R 2 between 0.944 and 0.969, RPDcv between 3.21 and 3.67%). The results demonstrated that the MIR-FTIR coupled with the PLS-1 algorithm could be simultaneously applied to predict the chemical parameters of chilled fillets of three fish species.Keywords: fish-fillet quality; MIR-FTIR spectroscopy; PLS algorithm; principal component analysis; fish chemical composition; chemometrics; deterioration indices La espectroscopía infrarroja media por transformada de Fourier (MIR-FTIR) y el algoritmo PLS-1 fueron utilizados para predecir índices de deterioro, pH y composición química de filetes refrigerados de atún aleta azul, jurel y sierra. Para construir los modelos de regresión fueron analizadas 90 muestras de las 3 especies, en diferentes estaciones y diversos tiempos de almacenamiento. Se evaluó el comportamiento de los modelos con base en los coeficientes de determinación (R 2 ), la desviación residual de predicción en la validación cruzada (RPDcv), y el porcentaje de diferencia relativa (%RD). Los modelos proporcionan una buena predicción de la composición química (R 2 entre 0,969-0,992, RPDcv entre 5,01-5,59%), el pH (R 2 = 0,987, RPDcv = 7,18), y se pueden utilizar para análisis de reconocimiento de índices de deterioro (R 2 entre 0,944-0,969, RPDcv entre 3,21-3,67%). Los resultados demostraron que la espectroscopía MIR-FTIR y el algoritmo PLS-1 pueden aplicarse simultáneamente para predecir parámetros químicos de filetes refrigerados. Palabras

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