Meat superchilling monitoring by NIR: penetration limits and multivariate charts

Near-infrared spectroscopy offers promising non-destructive monitoring for food processing, but its effectiveness depends on both signal penetration and real-time detection of physiochemical changes. Therefore, this study investigates three key aspects of NIR application in meat superchilling: (i) assessing the thermal stability of the MicroNIR device under process conditions, (ii) evaluating the penetration depth of NIR signal in pork, beef and chicken tissues, and (iii) developing multivariate statistical control charts (MSCC) to monitor freezing dynamics through water-related spectral changes. Penetration depth was assessed by placing meat slices (2.5–30 mm) between polypropylene and a MicroNIR sensor, determining the maximum detectable depth. In a parallel experiment, cubed meat samples (30 × 30 × 30 mm) underwent controlled superchilling with spectra collected every 2 min and analysed through principal component analysis (PCA) and aquaphotomics. The MicroNIR demonstrated signal stability under varying temperature conditions, confirming its suitability for in-line monitoring. Results showed NIR penetrates up to 5 mm under refrigeration conditions, with reduced effectiveness under freezing. However, this was enough to detect the thin frozen surface layer characteristic of superchilling. Spectral variations during the process showed consistent trends, particularly in the water-related band. PCA highlighted key water phase transitions, while aquagrams mapped water structuring. MSCCs based on PCA and aquaphotomic markers reliably identified superchilling start and end in real time, closely matching temperature-based references. This work not only clarifies the effective penetration limits of NIR in refrigerated and frozen muscle tissues, but also proposes a robust, automatable strategy for process monitoring based on the spectral behaviour of water.