基于低场核磁共振技术的奶粉品牌快速判别  

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

作　　者：杨莉 夏阿林 张榆 YANG Li;XIA A-lin;ZHANG Yu(School of Food and Chemical Engineering,Shaoyang University,Shaoyang,Hunan 422000,China)

机构地区：[1]邵阳学院食品与化学工程学院,湖南邵阳422000

出　　处：《食品与机械》2021年第8期105-109,共5页Food and Machinery

基　　金：湖南省教育厅科学研究重点项目(编号:16A236);邵阳学院研究生创新项目(编号:CX2019SY048)。

摘　　要：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。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.

关 键 词：奶粉 品牌 低场核磁共振 化学计量学 判别分析 

分 类 号：TS252.7[轻工技术与工程—农产品加工及贮藏工程] O657.2[轻工技术与工程—食品科学与工程]