食品科学 ›› 2012, Vol. 33 ›› Issue (16): 120-123.

• 分析检测 • 上一篇    下一篇

基于近红外光谱对牛奶中掺杂尿素判别分析

杨仁杰1,2,刘 蓉1,*,徐可欣1   

  1. 1.天津大学 精密测试技术及仪器国家重点实验室 2.天津农学院机电工程系
  • 收稿日期:2011-07-21 修回日期:2012-07-05 出版日期:2012-08-25 发布日期:2012-09-07
  • 通讯作者: 杨仁杰 E-mail:rjyang1978@163.com
  • 基金资助:

    国家自然科学基金;高等学校博士学科点专项科研基金

Discrimination of Milk Adulteration with Urea Based on Near Infrared Spectroscopy

  • Received:2011-07-21 Revised:2012-07-05 Online:2012-08-25 Published:2012-09-07

摘要: 采集40个合格的纯牛奶样品,并配制含有尿素为1~20g/L的40个牛奶样品,研究掺杂尿素牛奶的二维相关近红外特性,在此基础上选择波数4200~4800cm-1为建模区间,采用偏最小二乘法建立定性、定量模型。结果指出通过判别偏最小二乘法可以实现纯牛奶及掺杂尿素牛奶的定性鉴别,判别正确率为100%;掺杂牛奶校正集相关系数R为0.999,交叉验证均方差为0.242,对未知样品集预测相关系数R达到0.999,预测标准偏差为0.57,这表明所建模型具有较好的预测效果。

关键词: 近红外光谱, 牛奶, 尿素, 掺杂, 偏最小二乘判别分析法

Abstract: Forty eligible pure milk samples were collected and 40 adulterated milk samples were prepared by adding urea with various concentrations (1-20 g/L). Two-dimensional correlation spectroscopy was calculated under the perturbation of adulteration. Based on the 2D correlation infrared spectroscopic characteristics, the spectra in the range of 4200-4800 cm-1  were selected for quantitative and qualitative by partial least squares. There results showed that a 100% recognition rate of samples was achieved by partial least square-discriminate analysis (PLS-DA). The correlation coefficient (R) of calibration sets was 0.999, and the root mean square errors of cross validation (RMSECV) were 0.242. The R between the predicted values and actual values was 0.999, and the root mean square errors of prediction (RMSEP) were 0.57. Therefore, the developed models have good prediction capacity.

Key words: near-infrared spectroscopy, milk, urea, adulteration, partial least square-discriminate analysis

中图分类号: