Study on fast discrimination of varieties of yogurt using Vis/NIR-spectroscopy

A new approach for discrimination of varieties of yogurt by means of VisINTR-spectroscopy was present in this paper. Firstly, through the principal component analysis (PCA) of spectroscopy curves of 5 typical kinds of yogurt, the clustering of yogurt varieties was processed. The analysis results showed that the cumulate reliabilities of PC1 and PC2 (the first two principle components) were more than 98.956%, and the cumulate reliabilities from PC1 to PC7 (the first seven principle components) was 99.97%. Secondly, a discrimination model of Artificial Neural Network (ANN-BP) was set up. The first seven principles components of the samples were applied as ANN-BP inputs, and the value of type of yogurt were applied as outputs, then the three-layer ANN-BP model was build. In this model, every variety yogurt includes 27 samples, the total number of sample is 135, and the rest 25 samples were used as prediction set. The results showed the distinguishing rate of the five yogurt varieties was 100%. It presented that this model was reliable and practicable. So a new approach for the rapid and lossless discrimination of varieties of yogurt was put forward.

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