光谱学与光谱分析, 2017, 37 (10): 3074, 网络出版: 2017-12-25  

基于近红外自相关谱检测奶粉中的三聚氰胺

Detection of Melamine in Milk Powder Based on Near Infrared Auto-correlation Spectroscopy
作者单位
1 天津农学院农学与资源环境学院, 天津 300384
2 天津农学院农业分析测试中心, 天津 300384
3 天津农学院工程技术学院, 天津 300384
摘要
发展了一种基于近红外自相关谱定性定量分析掺三聚氰胺奶粉的检测方法。 分别配置40个纯奶粉样品和40个不同质量百分比浓度的掺三聚氰胺奶粉(10-4%~40%, w/w)样品, 采集了所有样品的一维近红外漫反射光谱, 以奶粉中掺入的三聚氰胺浓度为外扰进行相关计算, 选择随浓度变化敏感的7 000~4 200 cm-1为建模区间。 在提取自相关谱信息的基础上, 建立了定性定量分析掺三聚氰胺奶粉的偏最小二乘模型, 并与常规一维近红外谱模型的预测结果进行了比较。 所建立的方法对未知样品的识别正确率为100%, 预测均方根误差(RMSEP)为0.63%; 而一维近红外谱的识别正确率为96.2%, RMSEP为0.84%。 研究结果表明: 相对于常规一维近红外谱, 所建立的方法能提供更好的预测结果, 其原因可能是自相关谱能提取更多的特征信息。
Abstract
A method for detecting melamine in milk powder was developed based on near infrared (NIR) auto-correlation spectroscopy. Forty pure milk powder samples and forty adulterated milk powder samples with different relative factions of melamine (10-4%~40%, w/w) were prepared. The NIR reflectance spectra of all samples were collected in the range of 10 000~4 000 cm-1. Synchronous two-dimensional (2D) NIR correlation spectrum was calculated under the perturbation of melamine concentration, and the 7 000~4 200 cm-1 region was selected to establish a model. Then, based on the extracting information of auto-correlation spectra, the classification and quantification models of adulterated milk powder were established using partial least square (PLS) method. The 100% classification accuracy and the root mean square errors of prediction (RMSEP) of 0.63% were achieved, while the classification accuracy and RMSEP were 96.2% and 0.84%, respectively, using conventional one-dimensional NIR spectra, which showed that the auto-correlation spectra could provide better results, probably because more characteristic information could be extracted than conventional one-dimensional NIR spectra.

刘海学, 杨仁杰, 朱文碧, 孙雪杉, 刘洋, 靳涛, 靳皓. 基于近红外自相关谱检测奶粉中的三聚氰胺[J]. 光谱学与光谱分析, 2017, 37(10): 3074. LIU Hai-xue, YANG Ren-jie, ZHU Wen-bi, SUN Xue-shan, LIU Yang, JIN Tao, JIN Hao. Detection of Melamine in Milk Powder Based on Near Infrared Auto-correlation Spectroscopy[J]. Spectroscopy and Spectral Analysis, 2017, 37(10): 3074.

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