The Application of Near-Infrared Spectroscopy and Pattern Recognition to Quality Assessment of Toothpaste Samples of Different Brands
LIN Wei1,2, NI Yong-nian1, 2*
1. The State Key Laboratory of Food Science and Technology of Nanchang University, Nanchang 330047, China 2. Department of Chemistry, Nanchang University, Nanchang 330031, China
Abstract：The near-infrared spectroscopy (NIR) was combined with pattern recognitions method and applied to the quality assessment of toothpaste samples of four different brands. Several chemometrics approaches, such as principal component analysis (PCA), clustering analysis (CA), partial least squares (PLS), artificial neural networks (ANN) and K-nearest neighbor (kNN) were used to investigate the quality of toothpastes samples. The obtained results showed that the four clustering groups can be observed after the pretreatment of multiple scatter correction for the NIR data. It was also found that the quality of toothpastes of all the four brands was relatively stable, however, there is a significant difference in the quality between two brand kinds of toothpaste samples.
林 薇1，2, 倪永年1,2* . 近红外光谱法结合模式识别方法对不同品牌牙膏进行质量监控[J]. 光谱学与光谱分析, 2011, 31(08): 2106-2108.
LIN Wei1,2, NI Yong-nian1, 2* . The Application of Near-Infrared Spectroscopy and Pattern Recognition to Quality Assessment of Toothpaste Samples of Different Brands . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2011, 31(08): 2106-2108.
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