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成都理工大学 核技术与自动化工程学院 成都 610059
Received:09 March 2017,
Revised:07 April 2017,
Published:10 August 2017
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Guangxi WANG, Yan HU, Qiong LUO, et al. Determination and analysis of mineral elements content in rice samples[J]. Nuclear techniques, 2017, 40(8): 080501
Guangxi WANG, Yan HU, Qiong LUO, et al. Determination and analysis of mineral elements content in rice samples[J]. Nuclear techniques, 2017, 40(8): 080501 DOI: 10.11889/j.0253-3219.2017.hjs.40.080501.
采用粉末压片制样,用波长色散X射线荧光光谱法对湖北、四川和黑龙江产地大米中Mn、Fe、Cu、Zn、Mg、P、S、K、Ca 9种元素含量进行测定,并用主成分和聚类分析对结果进行分析。讨论了各目标元素测量条件,运用经验系数法和散射射线作内标对基体效应进行校正,通过测量国家生物标准物质建立了工作曲线。分析结果表明,该方法检出限较低、精密度较好、准确度较高,不同产地大米样品中目标元素含量差异显著。前4个主成分的累计方差贡献率为89.3%,30份大米样品分布在三个区域,分别来自三个产地。聚类分析在阈值为9时,将大米样品分成三类,与主成分分析结果一致。因此矿质元素可作为大米产地溯源的指标。
Background
2
Mineral elements play an important role in the human body and mainly derive from food. The rice is staple food of most people in our country. Therefore
it is important to determine accurately the content of mineral elements in rice.
Purpose
2
This study aims to establish an accurate analysis method for the rice measurement and distinguish the rice from different places.
Methods
2
Wavelength dispersive X-ray fluorescence (WDXRF) spectrometry was applied to the measurement of Mn
Fe
Cu
Zn
Mg
P
S
K
Ca 9 elements in rice (produced in Hubei
Sichuan and Heilongjiang) with pressed powder pellets. Principal component and cluster analysis analyzed determination results. The measuring conditions of target elements were investigated. The matrix effect was corrected by empirical coefficient method and scattered radiation as internal standard and working curve was established with national biological standard reference materials.
Results
2
The detection limit of this method was low
and its precision and accuracy were high. There were diverse contents of target elements from different places. Four principal components could account for 89.3% of total variance. 30 samples could be divided to three regions which came from three different places. Cluster analysis showed the samples could be clustered into three groups at the threshold of 9 levels. The results were consistent with the result of principal component analysis.
Conclusion
2
This method can accurately determine the content of mineral elements in rice and the mineral elements can be used as a traceability of producing area.
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