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Application of 2D Correlation Infrared Spectroscopy to Identification of Adulterated Milk Using NPLS-DA Method

机译:二维相关红外光谱法在NPLS-DA法鉴别掺假牛奶中的应用

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In this paper, a new method for discriminate adulterated milk was proposed by combining two-dimensional (2D) correlation infrared spectroscopy with multi-way partial least squares discriminate analysis (NPLS-DA). 64 pure milk samples were collected and four adulteration types of milk with urea, melamine, tetracycline and glucose were prepared, respectively. IR spectra of pure milk and adulterated milk samples in the region of 900-1700cm-1 were measured. Based on the characteristics of 2D correlation infrared spectra, the discriminant model of pure milk and adulterated milk was conducted by using NPLS-DA method. The prediction rate of unknown samples was 90.7%. Finally, compared with NPLSDA and partial least squares discriminant analysis (PLS-DA) models, the NPLS-DA model showed excellent performance for prediction. This study demonstrates that 2D correlation spectra coupled with NPLS-DA is a promising way for rapid and non-expensive discrimination of adulterated milk.
机译:本文提出了一种将二维(2D)相关红外光谱与多路偏最小二乘判别分析(NPLS-DA)相结合的判别掺假牛奶的新方法。收集了64个纯牛奶样品,并分别制备了四种掺假类型的牛奶,分别为尿素,三聚氰胺,四环素和葡萄糖。测量了纯牛奶和掺假牛奶样品在900-1700cm-1区域的红外光谱。根据二维相关红外光谱的特点,采用NPLS-DA法建立了纯牛奶和掺假牛奶的判别模型。未知样品的预测率为90.7%。最后,与NPLSDA和偏最小二乘判别分析(PLS-DA)模型相比,NPLS-DA模型具有出色的预测性能。这项研究表明,二维相关光谱结合NPLS-DA是一种有前景的方法,可以快速,廉价地识别掺假牛奶。

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