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

被引:86
作者
He, Yong [1 ]
Feng, Shuijuan [1 ]
Deng, Xunfei [1 ]
Li, Xiaoli [1 ]
机构
[1] Zhejiang Univ, Coll Biosyst Engn & Food Sci, Dept Biosyst Engn, Hangzhou 310029, Peoples R China
基金
中国国家自然科学基金; 高等学校博士学科点专项科研基金;
关键词
spectroscopy; yogurt; principal component analysis; artificial neural network; discrimination;
D O I
10.1016/j.foodres.2005.12.008
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
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. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:645 / 650
页数:6
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