Comparison of spectral properties of three hyperspectral imaging (HSI) sensors in evaluating main chemical compositions of cured pork.

Hyperspectral imaging (HSI) is a promising technique to evaluate food quality in a rapid and non-destructive way. Several types of HSI sensors are now commercially available. The aim of the current study was to compare one single shot and two line-scanning based HSI sensors in different spectral regions by using two wavelength dispersive devices – a prism-grating-prism monochromator and a mosaic wavelength dispersion unit. The research sample was cured pork meat, which is a popular meat product due to its flavor and long shelf life. Three main chemical compositions of cured pork meat – moisture, protein and fat content – were evaluated. The spectral properties of the three sensors were employed to establish partial least squares regression (PLSR) predictive models by applying different optimal wavelengths selection strategies. The results showed that optimal wavelength selection was more important than the selection of the wavelength dispersion device. • Three hyperspectral imaging (HSI) systems were compared. • Prediction models for compositions of dry and wet cured pork were established. • Nine wavelengths were sufficient for predicting chemical compositions. • Slight differences between the two wavelengths dispersion systems were observed. • Optimal wavelength selection was a key step in improving models of HSI. [ABSTRACT FROM AUTHOR]