Non-Destructive Detection of Water Content in Pork Based on NIR Spatially Resolved Spectroscopy

Water is one of the important factors affecting pork quality. In this study, near-infrared (NIR) spatially resolved (SR) spectroscopy was used to detect the water content of pork. The SR spectra of 150 pork samples were collected within the light source–detector (LS-D) distance range of 4–20 mm (distance interval 1 mm). Models were established based on single-point SR spectra of 17 different LS-D distances and combination SR spectra. The results indicated that combination SR spectra achieved better model performance than the single-point SR spectra, and the LS-D distance significantly affected the model accuracy. The optimal LS-D distance combination of 5, 7, 10, and 12 mm provided the best detection model with the calibration determination coefficient ( R 2 C ) of 0.915 and prediction determination coefficient ( R 2 P ) of 0.878. Using the competitive adaptive reweighted sampling (CARS) algorithm, 24 characteristic wavelengths were selected. The model built with the characteristic wavelengths also exhibited good detection accuracy, with a R 2 C of 0.909 and a R 2 P of 0.867, and the number of wavelengths was greatly reduced compared to the full-wavelength model. This study demonstrated that SR spectroscopy combined with the optimized LS-D distances and screened characteristic wavelengths can be a powerful tool for detecting the water content of pork.