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

Abstract

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 (R2C) of 0.915 and prediction determination coefficient (R2P) 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 R2C of 0.909 and a R2P 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.