Application of MIR- FTIR spectroscopy and chemometrics to the rapid prediction of fish fillet quality

作者：Hernandez Martinez M; Gallardo Velazquez T^*; Osorio Revilla G; Almaraz Abarca N; Castaneda Perez E

来源：CYTA - Journal of Food, 2014, 12(4): 369-377.

DOI：10.1080/19476337.2014.889213

• fish-fillet quality
• MIR-FTIR spectroscopy
• PLS algorithm
• principal component analysis
• fish chemical composition
• chemometrics
• deterioration indices
• calidad de filetes de pescado
• espectroscopia MIR-FTIR
• algoritmo PLS
• analisis de componentes principales
• composicion quimica del pescado
• quimiometria
• indices de deterioro

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. La espectroscopia infrarroja media por transformada de Fourier (MIR- FTIR) y el algoritmo PLS-1 fueron utilizados para predecir indices de deterioro, pH y composicion quimica de filetes refrigerados de atun aleta azul, jurel y sierra. Para construir los modelos de regresion fueron analizadas 90 muestras de las 3 especies, en diferentes estaciones y diversos tiempos de almacenamiento. Se evaluo el comportamiento de los modelos con base en los coeficientes de determinacion (R-2), la desviacion residual de prediccion en la validacion cruzada (RPDcv), y el porcentaje de diferencia relativa (%RD). Los modelos proporcionan una buena prediccion de la composicion quimica (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 analisis de reconocimiento de indices de deterioro (R-2 entre 0,944-0,969, RPDcv entre 3,21-3,67%). Los resultados demostraron que la espectroscopia MIR-FTIR y el algoritmo PLS-1 pueden aplicarse simultaneamente para predecir parametros quimicos de filetes refrigerados.

• 出版日期2014-11