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

- 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.

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.