Abstract
Visible near-infrared (400–1000 nm) hyperspectral imaging technology (HSI) was first time used to evaluate changes in various quality attributes including moisture contents (MC), lightness (L*), yellowness (b*), hardness (H) and chewiness (ch) of Agaricus bisporus as affected by vacuum cooling (VC). Partial least squares regression (PLSR) models based on Savitzky-Golay (SG) smoothing combined with the first derivative (SG-1st der) spectral preprocessing achieved good results for predicting MC with R2P of 0.823 and RMSEP of 0.341%. Similarly, PLSR models based on full wavelengths achieved good results for predicting L*, b* and H, and ch with R2P of 0.796, 0.848 and 0.810, and 0.903, with RMSEP of 1.253, 0.808 and 9.254, and 2.717. Finally, pseudocolour maps were developed to visualize the distribution of these attributes during VC. The current study provides a rapid, real-time and non-destructive detection strategy for evaluating the VC process.
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