基于低场核磁共振技术的奶粉品牌快速判别

目的：采用低场核磁共振技术对6个不同品牌的270个奶粉样品进行检测判别。方法：采用主成分分析（PCA）、偏最小二乘判别分析（PLS-DA）、误差反传人工神经网络（BP-ANN）等化学计量学方法对样品数据进行处理。结果：采用PCA方法的主成分三维投影图无法达到对奶粉品牌快速判别的目的；PLS-DA方法的训练集和预测集的正确识别率分别为66.1%，52.2%，可信度较低，也难以实现奶粉品牌的快速判别；BP-ANN方法的训练集和预测集的正确识别率分别为99.4%， 100.0%。结论：低场核磁共振与BP-ANN结合可以很好地识别奶粉品牌。

Fast identification of milk powder brand based on low field nuclear magnetic resonance technology

Objective: 270 milk powder samples from 6 different brands were detected and distinguished by low field nuclear magnetic resonance combined with chemometrics. Methods: Three chemometrics methods of principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and backpropagation artificial neural network (BP-ANN) were used to process experimental data of samples statistically. Results: The PCA method based on three-dimensional projection could not achieve the purpose of rapid identification of milk powder brand; the correct recognition rates of training and prediction sets were 66.1% and 52.2% for the PLS-DA method, respectively, which was low in credibility and challenging to realize the rapid identification of milk powder brand; the correct recognition rates of training and prediction sets of were 99.4% and 100.0% for the BP-ANN method respectively. Conclusion: The combination of low field nuclear magnetic resonance and BP-ANN can identify the milk powder brand well.