Study on lossless discrimination of varieties of yogurt using the Visible/NIR-spectroscopy

A new approach for the rapid and lossless discrimination of varieties of yogurt by Visible/NIR-spectroscopy was put forward. Through the principal component analysis of spectroscopy curves of 5 typical kinds of yogurt, the clustering of yogurt varieties was processed. The results end to be that the cumulate reliabilities of the first two principle components (PC1, PC2) were more than 98.9%, and the first seven principle component (PC1 to PC7) were 99.97%. In addition, an artificial neural network (BP-ANN) model was set up. The first seven principles components of the samples were applied as BP-ANN inputs and the values of the type of yogurt were applied as outputs, which build the three-layer BP-ANN. With this model, the discrimination of yogurt came to be possible. The results of distinguishing the rate of the five yogurt varieties came to be satisfied. It presented that this model was reliable and practicable.