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作 者:杨德毅 俞立渊 蒋红英[2] 刁银军[2] YANG Deyi;YU Liyuan;JIANG Hongying;DIAO Yinjun(Jinhua Quality Supervion and Testing Center for Agricultural Products,Jinhua 321051,China;Jinhua polytecnical,Jinhua 321007,China)
机构地区:[1]金华市农产品质量综合监督检测中心,浙江金华321051 [2]金华职业技术学院,浙江金华321007
出 处:《金华职业技术学院学报》2020年第6期57-62,共6页Journal of Jinhua Polytechnic
基 金:2016年金华市科技计划项目“生物炭的制备及其对区域土壤重金属污染修复的应用示范研究”(2016-2-015)。
摘 要:目的为研究不同浓度硝酸溶液对石墨炉原子吸收(GFAAS)法测定食品中5种重金属的影响。方法用4种不同浓度硝酸溶液分别配制了镉(Cd)、铅(Pb)、铜(Cu)、铬(Cr)、镍(Ni)5种重金属标准系列溶液作为试样,质控样品采用微波消解法进行前处理后再检测分析。结果在本试验条件下,用0%(纯水)、1%、2.5%、5%4种硝酸溶液配制的5种重金属元素标准溶液的标准曲线性相关系数R2均大于0.997;精密度较好,RSD为0.57%~3.70%,但同一元素的检出限有较大差异;2个质控样品经检测后分别按以上不同的标准曲线计算5种重金属含量,回收率分别为84.4%~182.5%、92.0%~104.3%、34.4%~128.8%、33.2%~116.7%。在测定Cd和Pb时加入基体改进剂(Pd),可以减少不同浓度硝酸溶液对测定值的影响。结论综合分析比较,按本试验方法测定柑橘叶和大虾中5种重金属,用1%硝酸溶液配制各元素标准溶液标准曲线线性好、检出限低、精密度好,同时样品回收率最高。Objective In order to study the effect of different nitric acid solutions on the determination of 5 heavy metals in food by GFAAS.Methods Five heavy metal(Cd、Pb、Cu、Cr、Ni)series standard solutions were prepared with four different concentrations of nitric acid.The quality control samples were pretreated by microwave digestion and the results were analyzed.Results The results showed that under the conditions of this experiment,the standard curve correlation coefficient R2 of 5 heavy metal elements standard solutions prepared by 0%(pure water),1%,2.5%and 5%nitric acid solutions was higher than 0.997,and the precision was better,RSD was 0.57%~3.70%.The difference of detection limit of the same element was significant.According to the above standard curve of nitric acid solution,5 heavy metal elements in 2 quality control samples were calculated.The recoveries were 84.4%~182.5%,92.0%~104.3%,34.4%~128.8%and 33.2%~116.7%respectively.Adding matrix modifier in the determination of Cd and Pb can reduce the influence of different concentration of nitric acid solution on the measured value.Conclusion By the comparison,the standard curve of each element standard solution prepared with 1%nitric acid solution had good linearity,low detection limit,good precision and the highest sample recovery rate.
分 类 号:TS207.51[轻工技术与工程—食品科学]
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