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基于电感耦合等离子体质谱法对不同产地小米矿物元素的差异性分析
引用本文:潘少香,孟晓萌,刘雪梅,郑晓冬,谭梦男,宋 烨,吴茂玉,闫新焕.基于电感耦合等离子体质谱法对不同产地小米矿物元素的差异性分析[J].食品安全质量检测技术,2022,13(1):72-79.
作者姓名:潘少香  孟晓萌  刘雪梅  郑晓冬  谭梦男  宋 烨  吴茂玉  闫新焕
作者单位:中华全国供销合作总社济南果品研究院,济南果品研究院,济南果品研究院,济南果品研究院,济南果品研究院,济南果品研究院,济南果品研究院,济南果品研究院
基金项目:泉城产业领军人才创新项目
摘    要:采用电感耦合等离子体质谱法对小米(陕西、山西、内蒙古、河北、山东、东北产区)6大主产区不同品种样品的矿物元素进行检测,研究不同产地品种来源小米K、Ca、Na、Mg、Al、Fe、Cu、Zn、Mn、Se、B、Ti、Co、Sr、Mo 15种矿质元素含量差异并分析其显著性,同时采用主成分分析法和聚类分析法对不同产地小米矿质元素含量的差异进行分析,检测结果表明,不同产地品种小米元素含量差异显著,Se、Sr、Al 三种元素含量差异最为明显,变异系数最高,Zn、Cu、K 三种元素的变异系数最小。主成分分析结果表明,前两个主成分方差贡献率为 63.9%,K、Ca、Mg、Fe、Cu、Zn、Mn、B、Mo、Al、Se、Sr、Ti 是不同品种及产地来源小米的特征差异元素;聚类分析结果表明品种对小米元素分布造成的影响有限,地域环境因素是造成小米元素分布差异的主要因素。

关 键 词:小米  电感耦合等离子体质谱法  矿物元素  主成分分析  聚类分析
收稿时间:2021/9/30 0:00:00
修稿时间:2021/12/30 0:00:00

Analysis of the difference of mineral elements of millet from different regions based on inductively coupled plasma mass spectrometry
PAN Shao-Xiang,MENG Xiao-Meng,LIU Xue-Mei,ZHENG Xiao-Dong,TAN Meng-Nan,SONG Ye,WU Mao-Yu,YAN Xin-Huan.Analysis of the difference of mineral elements of millet from different regions based on inductively coupled plasma mass spectrometry[J].Food Safety and Quality Detection Technology,2022,13(1):72-79.
Authors:PAN Shao-Xiang  MENG Xiao-Meng  LIU Xue-Mei  ZHENG Xiao-Dong  TAN Meng-Nan  SONG Ye  WU Mao-Yu  YAN Xin-Huan
Affiliation:Jinan Fruit Research Institute, All China Federation of Supply & Marketing Co-operatives
Abstract:The contents of fifteen mineral elements of millet samples from six major producing areas (Shaanxi, Shanxi, Inner Mongolia, Hebei, Shandong and northeast China) were detected by inductively coupled plasma mass spectrometry after microwave digestion. The differences and significance of mineral elements were analyzed. At the same time, the principal component analysis (PCA) and cluster analysis method were adopted to analyze mineral elements content of differences between different varieties. The results showed that the contents of elements in millet from different producing areas were significantly different. Se, Sr and Al had the most obvious differences and the highest coefficient of variation, while Zn, Cu and K had the least coefficient of variation. The results of principal component analysis showed that the variance contribution rate of the first two principal components was 63.9%, and K, Ca, Mg, Fe, Cu, Zn, Mn, B, Mo, Al, Se, Sr and Ti were the characteristic elements of different varieties and millet of origin. The results of cluster analysis showed that cultivars had limited influence on the distribution of millet elements, and regional environmental factors were the main factors that caused the difference in the distribution of millet elements.
Keywords:millet  inductively coupled plasma mass spectrometry  trace elements  principal component analysis  clustering analysis
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