Hyperspectral imaging for rapid evaluation and visualization of quality deterioration index of vacuum packaged dry-cured sausages

Abstract

A rapid and nondestructive method to evaluate and visualize quality of vacuum packaged dry-cured sausages was developed using hyperspectral imaging (HSI) spectroscopy. Changes in physicochemical, microbiological and sensory attributes of the packaged dry-cured sausages were monitored during storage at 20°C. Discriminant factor analysis (DFA) could classify samples into different groups as a function of storage time. The quality deterioration index (QDI) of the packaged dry-cured sausages was signified and assigned to the individual DFA classified groups. HSI spectroscopy was used to collect both spectral data in the wavelength range of 380–1000nm and spatial data of 68×68 pixels. Partial least squares (PLS) regression model was constructed to establish the relationship between the HSI hypercube data and the QDI. Distribution maps of the QDI were then constructed to visualize the quality attributes of the sausages. The color distribution map of the QDI enabled the identification of different qualities of the vacuum packaged sausages as a function of storage time. The results demonstrated that the HSI coupled with chemometric and image processing techniques can be used as a rapid and nondestructive method to evaluate quality of the sausages.