Prediction of textural changes in grass carp fillets as affected by vacuum freeze drying using hyperspectral imaging based on integrated group wavelengths

- HSI was used to predict textural features in vacuum freeze dried fish slices.
- Mean and median spectra were compared in performance of the predictive models.
- Integrated group wavelengths were selected for predicting different textures.
- Visualization was realized for displaying WBSF, hardness, gumminess and chewiness.

This study aimed to simultaneously predict different textural features in grass carps fillets (Ctenopharyngodon idella) during vacuum freeze drying using hyperspectral imaging models developed based on integrated group wavelengths in the range of 400 nm-1000 nm. Warner-Bratzler shear force (WBSF) is commonly used as an objective indicator for tenderness evaluation in fish products. First, partial least squares regression (PLSR) was employed to develop a quantitative function between the textural variations and the spectra extracted from the acquired hyperspectral images in the full spectral range at mean and median. Then the important wavelengths most related to WBSF, hardness, gumminess and chewiness were separately selected by regression coefficients (RC) from PLSR. Moreover, the integrated wavelengths for all the textural characteristics were determined by RC by considering all the individual group wavelengths. Finally, PLSR was conducted using different simplified group wavelengths and the performance of all the simplified models at mean or median were compared. The results showed that the integrated group wavelengths at median spectra proved to be the best for simultaneous prediction of WBSF (RP2 = 0.8774), hardness (RP2 = 0.8523), gumminess (RP2 = 0.7982) and chewiness (RP2 = 0.8453). The current study should widen the applications of hyperspectral imaging in the food industry.