摘要
本文应用ICP-MS测定了黑龙江省两个地区椴树蜂蜜中的矿物质元素含量,发现不同地区椴树蜂蜜元素含量存在一定差异。应用主成分分析(PCA)、决策树(Decision Tree)、朴素贝叶斯(naive bayes)、神经网络(neural network)和支持向量机(support vector machine)等方法建立不同产地椴树蜂蜜溯源模型,采用决策树模型对26个蜂蜜样品的测试得到了验证,准确率为92.31%。ICP-MS测定蜂蜜中矿物质元素含量结合化学计量法可以用作不同产地椴树蜜溯源的有力工具。
In this work the contents of mineral elements of bass honey samples from Heilongjiang province were determined by ICP-MS.It can be found that there were relationships between the contents and the geographical origin of bass honey samples.Principal component analysis(PCA),Decision Tree,naive bayes,neural network and support vector machine were applied to classify bass honey samples according to their geographical origins.It was demonstrated that the accuracy rate of analyzing the 26 boney samples with decision tree model was 92.31%.It is concluded that the profles of mineral element by ICP-MS with chemometric methods could be a potential and powerful tool for the classification of bass honey samples from different geographical origins.
作者
孙艳
徐大江
翟凤云
刘志勇
Sun Yan;Xu Dajiang;Zhai Fengyun;Liu Zhiyong(Harbin Product Quality Supervision and Inspection Institute,Hartbin 150090,China)
出处
《中国蜂业》
2020年第9期59-62,共4页
Apiculture of China