基于纯牛奶、 掺杂牛奶样品间二维红外相关谱欧氏距离, 依据未知样品与校正集中“极值样品”欧氏距离平均值、 组内、 组间样品欧氏距离平均值, 提出了一种掺杂牛奶判别的新方法。分别配置掺杂尿素牛奶(0.01～0.3 g·L-1)和掺杂三聚氰胺牛奶(0.01～0.3 g·L-1)样品各16个, 采集纯牛奶及掺杂牛奶样品的红外光谱。以牛奶中掺杂物浓度为外扰, 构建纯牛奶与掺杂牛奶的同步二维红外相关谱, 并计算了各样品相关谱矩阵间的欧氏距离。在此基础上, 分别建立掺杂尿素牛奶、 掺杂三聚氰胺牛奶与纯牛奶的判别模型, 确定模型中的“极值样品”, 组内、 组间样品欧氏距离平均值。利用所建模型, 计算未知样品与“极值样品”的欧式距离, 并依据判别规则, 对未知样品进行判别。研究结果表明: 基于样品红外相关谱矩阵间欧氏距离可实现掺杂牛奶的判别, 其判别正确率为100%, 验证了该方法的有效性。该研究为掺杂牛奶的检测提供了一种新的可能方法。

Based on Euclidian distances between synchronous two-dimensional infrared correlation spectra, in terms of the average Euclidian distances between unknown samples and “extreme samples”, and average intra- and inter- Euclidian distances of samples in the calibration set, a new method for the discrimination of adulterated milk was proposed. Sixteen pure milk samples were collected and 16 adulterated milk samples with urea (0.01～0.3 g·L-1), and 16 adulterated milk samples with melamine (0.01～0.3 g·L-1) samples were prepared, respectively. The IR absorption spectra of all samples were measured at room temperature. The synchronous two-dimensional correlation spectra were generated from concentration-dependent spectral variation of adulterant in milk. The Euclidian distances were calculated between synchronous two-dimensional infrared correlation spectra of all samples. Then, the classification models were built respectively for adulterated milk with urea, and adulterated milk with melamine. The “extreme samples”, average intra- and inter- Euclidian distances were determined. Finally, the unknown samples in prediction set were predicted using constructed models in terms of classification rules of adulterated milk. The classification accuracy rates for pure milk and adulterated milk were 100%. The effectiveness of the proposed method was verified. The results obtained in this study revealed that synchronous two-dimensional infrared correlation spectra in combination with Euclidian distance has a feasible potential to discriminate adulterated milk and pure milk.