中文摘要：

将二维中红外相关谱与多维偏最小二乘判别法相结合,建立了掺假蜂蜜与纯蜂蜜的判别模型.分别配置纯蜂蜜和掺蔗糖蜂蜜样品各30个,室温下,在650-4000 cm^-1范围内采集了所有样品的衰减全反射光谱.在研究纯蜂蜜和掺假蜂蜜光谱特征的基础上,基于二维中红外相关谱矩阵建立了掺假蜂蜜的多维偏最小二乘判别模型,并与常规一维中红外谱的偏最小二乘判别模型的预测结果进行了比较.两个模型对未知样品的判别正确率分别为95%和90%.研究结果表明：基于二维中红外相关谱的多维偏最小二判别模型能更有效地提取掺假蜂蜜的特征信息,能提供高的判别正确率.

英文摘要：

The classification model of adulterated honey was constructed based on two-dimensional （2D）mid-infrared correlation spectroscopy combined with N-way partial least squares discriminant analysis （NPLS-DA） . Firstly, 30 pure honey samples and 30 adulterated honey with sugar samples were prepared respectively. Then, mid-infrared attenuated total reflectance spectra of all samples were obtained in the region of 650-4 000 cm1 under room temperature. Spectral features of pure honey and adulterated honey were studied. NPLS-DA model was built using 2D mid-infrared correlation spectra. For comparison, the partial least squares discriminant analysis （PLS-DA） model was built using one-dimensional （ 1 D） mid-infrared spectra. The classification accuracies of two classification models for prediction set were 95% and 90%, respectively. The results show that NPLS-DA model can effectively extract feature information of adulterated honey using 2D mid-infrared correlation spectra and provide higher accurate rates.