Feasibility of NIR interactance hyperspectral imaging for on-line measurement of crude composition in vacuum packed dry-cured ham slices

There is a growing market for packaged slices of dry-cured ham. The heterogeneity of the composition of slices between packages is an important drawback when aiming to offer consumers a product with a known and constant composition which fits individual consumer expectations. The aim of this work was to test the feasibility of NIR interactance imaging for on-line analysis of water, fat and salt and their spatial distribution in dry-cured ham slices. PLSR models for predicting water, fat and salt contents with NIR spectra were developed with a calibration set of samples (n=82). The models were validated with an external validation set (n=42). The predictive models were accurate enough for screening purposes. The errors of prediction were 1.34%, 1.36% and 0.71% for water, fat and salt, respectively. The spatial distribution of these components within the slice was also obtained. •Composition of dry-cured ham is predicted with NIR interactance hyperspectral imaging.•Average spectra of packed slices of ham are used to build PLS prediction models.•Water, fat and salt predictions are accurate enough for on-line screening purposes.•Informative images of water, fat and salt distribution in ham slices are obtained.