Nondestructive identification of soybean protein in minced chicken meat based on hyperspectral imaging and VGG16-SVM

A rapid and nondestructive method for identification of soybean protein in minced chicken meat based on visible-near infrared hyperspectral imaging (HSI) technology and VGG16-SVM model was proposed in this study. The hyperspectral data from 400.89 nm to 1000.19 nm of samples with different soybean protein contents were collected. Spectral data was transformed into spectrograms through Continuous wavelet transform (CWT). Comparing with other methods, the optimum data preprocessing results were obtained for the subsequent research. Then, VGG16-SVM model based on VGG16 network in which fully connected layer was replaced by support vector machine (SVM) was established to identify soybean protein in minced chicken meat. The results showed that VGG16-SVM model with radial basis function (RBF) as kernel function performed best and the classification accuracy reached 98.1%. Meanwhile, the proposed model was superior to the SVM, convolution neural network (CNN) and VGG16 model. It is feasible and effective for combining HSI technology and VGG16-SVM to realize nondestructive identification of soybean protein in minced chicken meat.