Potential of two-dimensional correlation-based dual-band visible/near infrared spectroscopy to predict total volatile basic nitrogen content in meat

Abstract

In the meat industry, it is essential to monitor the total volatile basic nitrogen (TVB-N) content due to its impact on human diets safety. In the present study, two-dimensional correlation spectroscopy (2D-COS) was combined with dual-band visible/near-infrared spectroscopy to identify the characteristic wavelengths of TVB-N in pork meat during storage. Reflectance spectra of pork longissimus dorsi muscles at 350–1100 nm and 1000–2500 nm were obtained during a 13-day storage period. The dual-band spectra were merged via parabolic fitting, and subjected to pre-treatments using absorbance conversion, first derivation (FD), and standard normal variate transformation (SNV). Then, the storage day was used as the external perturbation factor, and 2D-COS was performed on the dynamic spectra to identify TVB-N-related wavebands. Twenty-five characteristic wavelengths were selected, and a simplified partial least square regression (PLSR) model was established with a correlation coefficient (Rp) of 0.9591, root mean square error on prediction (RMSEP) of 1.8341 mg/100 g, and relative percent deviation (RPD) of 3.2518. These results outperformed those of the model based on full wavebands data (Rp = 0.9215, RMSEP = 2.8191 mg/100 g, RPD = 2.1114). This study accurately predicted TVB-N values in pork meat, and the integration of 2D-COS and dual-band spectra had great potential for real-time meat freshness evaluation.