Comparative analysis of pork tenderness prediction using different optical scattering parameters

Abstract

This study aimed at the assessment of pork tenderness using hyperspectral backscattering imaging technique. Backscattering images for 54 pork samples in the spectral range of 480–900 nm were characterized by 3-parameter Lorentzian distribution function (LD) and diffusion equation (DE), which represent a statistical model and a theoretical model respectively. Characteristic parameters spectra were obtained and employed to establish partial least squares regression (PLSR) models for the Warner-Bratzler Shear Force (WBSF) values of pork samples. By contrast, the results showed that LD function interpreted pork scattering profiles more accurately than DE model between 480 and 600 nm. The PLSR model based on two-LD parameter combinations (the asymptotic value a and the peak value b of the backscattering profile) gained the best prediction results, with correlation coefficient in the prediction set (Rp) of 0.902, root mean square error of prediction (RMSEP) of 5.218 N, indicating that hyperspectral backscattering imaging technique coupled with LD model is preferable for rapid and nondestructive evaluation of pork tenderness.