Infrared spectroscopy technique for the nondestructive measurement of fat content in milk powder

被引:53
作者
Wu, D. [1 ]
Feng, S. [1 ]
He, Y. [1 ]
机构
[1] Zhejiang Univ, Coll Biosyst Engn & Food Sci, Hangzhou 310029, Peoples R China
基金
中国国家自然科学基金;
关键词
near- and mid-infrared spectroscopy; fat; milk powder; least-squares support vector machine;
D O I
10.3168/jds.2007-0164
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 [畜牧学];
摘要
The aim of this study was to investigate the potential of the infrared spectroscopy technique for nondestructive measurement of fat content in milk powder. Fat is an important component of milk powder. It is very important to be able to detect the fat content in milk powder using a rapid and nondestructive method. Near and mid infrared spectroscopy techniques were used to achieve this purpose. Least-squares support vector machine (LS-SVM) was applied to developing the fatcontent prediction model based on the infrared spectral transmission values. The results based on LS-SVM were better than those of back- propagation artificial neural networks. The determination coefficient for prediction of the results predicted by the LS-SVM model was 0.9796 and the root mean square error was 0.836708. It was concluded that infrared spectroscopy technique could quantify the fat content in milk powder rapidly and nondestructively. The process is simple and easy to operate. Moreover, the prediction results were compared between near infrared and mid infrared spectral data. The results showed that the performances of model with both mid infrared and near infrared spectral data were a little worse than that of the whole infrared spectral data. The results could be beneficial for designing a simple and nondestructive spectral sensor for the quantification of fat content in milk powder.
引用
收藏
页码:3613 / 3619
页数:7
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