Detection of the Protein Content of Ningxia Tan Sheep Using Hyperspectral Reflectance Imaging

Abstract

Near-infrared (NIR) hyperspectral imaging technique (900-1700nm) was evaluated to predict the protein content of Tan sheep. This research adopted NIR hyperspectral imaging to get imaging information of 72 mutton samples, multiplicative scatter correction was used to spectral data preprocessing. The optimal wavelengths were obtained through linear-regression analysis, BP neural network combined with actual measured values were established the prediction model and verified this model. The results showed that the prediction effect of model was very well. Correlation coefficient (Rp) and root mean squared error of prediction (RMSEP) of the protein were 0.87 and 1.19. The results indicated that it is feasible to predict the protein content of Tan sheep for NIR hyperspectral imaging technique.