Development of an alternative technique for rapid and accurate determination of fish caloric density based on hyperspectral imaging

• HSI was used to predict caloric density value in salmon fillets.
• Pixel outliers were detected and removed in each hyperspectral image by ROBPCA.
• Simplified PLSR, MLR and SVR models were built with good results presented.
• The visualization of caloric density distribution in salmon fillets was obtained.

This study aimed to develop an alternative technique for rapid, accurate and non-invasive determination of gross energy density values of salmon fillets based on hyperspectral imaging (900–1700 nm). Spectral data were extracted from the hyperspectral images with outlier pixels removed. Good performances were achieved with rPrP of 0.906 and 0.909, and normalized RMSEP of 6.768% and 7.064% for partial least squares regression (PLSR) and epsilon-support vector regression (epsilon-SVR) analysis, respectively. The optimized stepwise-PLS model built with four wavelengths (931, 1001, 1135 and 1168 nm) yielded good results with rPrP of 0.908 and normalized RMSEP of 6.871%. The distribution maps for visualizing energy density indices in all portions of the salmon fillet were subsequently generated. The overall results confirmed the successful development of a rapid and non-destructive technique using hyperspectral imaging for determining energy value of salmon fillets, and the provision of an alternative method for caloric density measurement for the food industry.