中文摘要：

为了快速、准确地检测掺杂牛奶,采用基于核隐变量正交投影（K-OPLS）法分析了掺杂牛奶的光谱.选用高斯函数作为核函数,内部交叉验证均方根（RMSECV）最小值作为评价指标,优选了核函数中的核宽度σ以及Y正交成分数.配置含四环素牛奶（0.01～0.3 gL-1）、三聚氰胺牛奶（0.01～～0.3 gL-1）和葡萄糖牛奶（0.01～～0.3 gL-1）各36个,采集纯牛奶及掺杂牛奶样品的红外光谱,采用K （PLS建立各掺杂牛奶与纯牛奶的判别模型.利用这些模型对未知样品进行判别,结果显示对掺杂四环素、三聚氰胺、葡萄糖牛奶的判别正确率分别为100％、100％、95.8％o.建立了同时判别3种掺杂牛奶与纯牛奶的K-OPLS模型,该模型对未知样品的判别正确率为93.1％;同时,与偏最小二乘判别PLS-DA方法的预测结果进行了比较,结果表明：K-OPLS建模方法对于复杂的牛奶体系具有较好的预测能力.

英文摘要：

To detect adulterated milk rapidly and accurately,the discrimination models for adulterated milk were established based on the method of Kernel Orthogonal Projection to Latent Structure （K-OPLS）.By using the Gaussian radial basis function as the kernel function and the minimum value of Root Mean Square Errors of Cross-validation （RMSECV）as an evaluation index,the width of the Gaussian kernel,the minimum value of the RMSECV,and the number of Y-orthogonal components （scalar） were selected in a optimization.36 samples with different concentrations of tetracycline （0.01 -0.3 gL-1）,melamine （0.01-0.3 gL-1） and glucose （0.01-0.3 gL-1） in milk were prepared,respectively.Then the infrared absorption spectra of all samples were measured.K-OPLS models for tetracycline-tainted milk,melamine-tainted milk and glucose-tainted milk were constructed.The resuits show that its classification accuracy for tetracycline-tainted milk,melamine-tainted milk and glucose-tainted milk are 100％,100％,95.8％,respectively.The K-OPLS model was used to classify the above three kinds of adulterated milk and pure milk and its classification accuracy for unknown samples is 93.1％.Compared with Partial Least Square Discriminant Analysis （PLS-DA）,K-OPLS methods show higher accuracy.The results indicate that the K-OPLS model has good prediction ability for complex milk systems.