Dong Yi-Wei, Tu Zhen-Hua, Zhu Da-Zhou, Liu Ya-Wei, Wang Ya-Nan, Huang Jin-Li, Sun Bao-Li, Fan Zhong-Nan
Institute of Environment and Sustainable Development in Agriculture, The Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-Environment & Climate Change, Ministry of Agriculture, Beijing 100081, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2009 Nov;29(11):2934-8.
In the present study, 22 certified milk samples without melamine were collected, then 50 adulterated milk samples with added different content of melamine (0.1-1 500 mg x kg(-1)) were prepared. The near-infrared (NIR) spectra of these milk samples were measured. The possibility of using NIR spectra to detect melamine in milk was studied. Partial least square regression (PLSR) was applied to construct the calibration model between NIR spectra and the content of melamine. The results showed that NIR spectroscopy can not accurately predict the content of melamine because of its poor detection limit. However, the combination of NIR spectra and partial least square-discriminate analysis (PLS-DA) was applied to differentiate the certified milk samples and the adulterated milk sample. The classification accuracy was 100%. Therefore, NIR spectra could be used to preliminarily detect whether the milk was adulterated with melamine. As a complementary detecting method to the high performance liquid chromatography (HPLC), NIR spectra could improve the detecting efficiency of milk
在本研究中,收集了22份不含三聚氰胺的合格牛奶样本,然后制备了50份添加不同含量三聚氰胺(0.1 - 1500 mg·kg⁻¹)的掺假牛奶样本。测量了这些牛奶样本的近红外(NIR)光谱。研究了使用近红外光谱检测牛奶中三聚氰胺的可能性。应用偏最小二乘回归(PLSR)构建近红外光谱与三聚氰胺含量之间的校准模型。结果表明,由于其检测限较差,近红外光谱法不能准确预测三聚氰胺的含量。然而,将近红外光谱与偏最小二乘判别分析(PLS - DA)相结合用于区分合格牛奶样本和掺假牛奶样本。分类准确率为100%。因此,近红外光谱可用于初步检测牛奶是否掺有三聚氰胺。作为高效液相色谱(HPLC)的一种补充检测方法,近红外光谱可以提高牛奶的检测效率