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中国精品科技期刊2020
张高强, 袁建, 鞠兴荣, 何荣, 邢常瑞. 不同产地稻米中元素含量特征及其产地判别研究[J]. 食品工业科技, 2017, (14): 61-70. DOI: 10.13386/j.issn1002-0306.2017.14.013
引用本文: 张高强, 袁建, 鞠兴荣, 何荣, 邢常瑞. 不同产地稻米中元素含量特征及其产地判别研究[J]. 食品工业科技, 2017, (14): 61-70. DOI: 10.13386/j.issn1002-0306.2017.14.013
ZHANG Gao-qiang, YUAN Jian, JU Xing-rong, HE Rong, XING Chang-rui. Study on the characteristics of elements content and the discrimination of the origin of rice in different producing areas[J]. Science and Technology of Food Industry, 2017, (14): 61-70. DOI: 10.13386/j.issn1002-0306.2017.14.013
Citation: ZHANG Gao-qiang, YUAN Jian, JU Xing-rong, HE Rong, XING Chang-rui. Study on the characteristics of elements content and the discrimination of the origin of rice in different producing areas[J]. Science and Technology of Food Industry, 2017, (14): 61-70. DOI: 10.13386/j.issn1002-0306.2017.14.013

不同产地稻米中元素含量特征及其产地判别研究

Study on the characteristics of elements content and the discrimination of the origin of rice in different producing areas

  • 摘要: 分析不同地域稻米中元素含量的特点,研究三种加工程度下稻米溯源的效果,筛选出判别不同加工程度下稻米产地的有效指标。以湖北省、江苏省、辽宁省三个地域共66份稻米样品为研究对象,用电感耦合等离子体质谱法(ICP-MS)测定了不同加工程度(整籽粒、糙米、精米)下Be、B、Na、Mg、K、Ca、Ti、V、Cr、Mn、Fe、Co、Ni、Cu、Zn、Ga、As、Se、Rb、Sr、Mo、Cd、Sn、Sb、Ba、Pb共26种元素的含量,用SPSS对其进行了方差分析、主成分分析、聚类分析及判别分析。结果表明,来源地不同的稻米,同一加工程度间元素含量均有各自的特征。主成分分析和聚类分析能够使其分成不同类别,类别和来源地基本一致。在聚类分析中,整籽粒样品和精米样品的聚类效果要明显好于糙米样品。通过逐步判别分析筛选出了7个可以判别整籽粒样品产地来源的指标,依次是Sn、Mg、B、Cr、Sr、Ca、Ga,整体的正确判别率和交叉检验率均为100%。同样地,逐步判别分析也筛选出了7个可以判别精米样品产地来源的指标,依次是Ti、Ni、Ga、Sb、Cu、Na、Rb,整体的正确判别率为100%,整体的交叉检验率为96.7%。 

     

    Abstract: The characteristics of elements in rice from different areas were analyzed to explore the effect of three processing precisions of rice origin traceability, and to screen out the effective index in different processing precisions of rice origin discrimination.Total 66 kinds of rice samples from Hubei province, Jiangsu province, Liaoning province were regarded as the object of study.The contents of 26 chemical elements in different processing precisions ( whole grain, brown rice, polished rice) of Be, B, Na, Mg, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, As, Se, Rb, Sr, Mo, Cd, Sn, Sb, Ba, Pb were detected by ICPMS.Then SPSS was used to analyze the data by analysis of variance ( ANOVA) , principal component analysis ( PCA) , cluster analysis ( CA) and discriminant analysis ( DA) . The results showed that the element contents were different in the same processing precision from different provinces. PCA and CA classified the samples of rice into different categories, which was consistent to the geographical origin. In the cluster analysis, the clustering effect of whole grain samples and polished rice samples was significantly better than brown rice samples. Furthermore, seven elements of Sn, Mg, B, Cr, Sr, Ca, Ga were screened by DA and suggested as better tracers for whole grain samples origin assessment, a percentage of 100% of correct classification was achieved by whole and cross-validated.Similarly, seven elements of Ti, Ni, Ga, Sb, Cu, Na, Rb were screened by DA and suggested as better tracers for polished rice samples origin assessment, 100% correct classification for all samples from three different regions, a percentage of 96.7% of correct classification was achieved by cross-validated.

     

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