【摘要】 将近、中红外光谱数据进行融合,并结合偏最小二乘法建立了两个品牌掺杂牛奶的判别模型。分别准备伊利和蒙牛纯牛奶样品各40个、掺杂三聚氰胺牛奶样品各40个。室温下,采集所有样品的近红外透射光谱和中红外衰减全反射光谱。在融合近、中红外光谱数据的基础上,分别建立了伊利、蒙牛以及两品牌牛奶的判别模型,3个模型对预测集未知样品的判别正确率分别为96.2%、96.2%和94.2%。为了比较,分别建立了单一近红外光谱和中红外光谱的伊利、蒙牛以及两品牌牛奶的判别模型。研究结果表明:相对于单一的近红外光谱和中红外光谱,融合近、中红外光谱能减小不同牛奶品牌对模型预测性能的影响,可提供更好的分析结果。更多还原

【Abstract】 The models of two brands of adulterated milk were constructed based on the information fusion of near and mid infrared spectroscopy combined with partial least squares discriminant analysis(PLS-DA).40 Yili pure milk samples,40 Mengniu pure milk samples,40 Yili milk adulterated with melamine samples,and 40 Mengniu milk adulterated with melamine samples,were prepared respectively.Then,near infrared transmittance spectra and mid infrared attenuated total reflectance spectra of all samples were obtained under room temperature.Based on the fused data of near and mid infrared spectra,the discrimination models of Yili,Mengniu and both brands milk were established.The classification accuracies of three discrimination models for prediction set were 96.2%,96.2% and 94.2%,respectively.For comparing,the discriminant models of Yili,Mengniu and two brands milk were established using near infrared spectra and mid infrared spectra individually.The results show that the fusion of near and mid infrared spectra not only can reduce the effect of different brands milk on the model,but also can provide better results compared with near infrared spectra and mid infrared spectra individually.更多还原