摘要
为了提高稻米中重金属的检测效率,建立了一种微敞开体系-石墨消解-电感耦合等离子体质谱(ICP-MS)法同时测定稻米中Cr、Ni、Cu、Zn、As、Cd、Hg、Pb等8种重金属的方法。研究了影响稻米中Hg测定准确性的因素,并确定了稻米最佳称样量和酸定容体系。结果表明,稻米中蛋白质是影响Hg测定准确度的重要因素,选用0.4 g作为称样量可以减轻稻米中蛋白质对Hg测定的影响,HNO3(1%)+HCl(1%)混合溶液定容能有效提高Hg回收率。经过大米标准物质和实际样品验证,可以同时准确测定Cr、Ni、Cu、Zn、As、Cd、Hg、Pb,检出限、正确度、精密度和效率能满足大批量稻米中8种重金属的监测需求。
A micro-open graphite digestion coupled with ICP-MS for simultaneous determination of Cr,Ni,Cu,Zn,As,Cd,Hg,Pb in rice was established in order to improve the detection efficiency of heavy metals in rice.The determination factors affecting the accuracy of Hg in rice were studied,and the weight of rice and acid volume system were optimized in this work.The results showed that protein in rice was an important factor affecting the accuracy of Hg determination,and weighing quantity of 0.4 g can reduce the effect of protein in rice on Hg determination,and the HNO 3(1%)+HCl(1%)mixed solution can effectively improve the recovery of Hg.According to the rice reference materials and actual sample digestion,the method could accurately determine the content of Cr,Ni,Cu,Zn,As,Cd,Hg,Pb in rice simultaneously.The low detection limit,high accuracy and precision of this method can meet the monitoring needs of 8 heavy metals in large quantities of rice.
作者
江棋
彭锦芬
陈楚国
李蕾
邓腾灏博
陈永坚
赵沛华
文典
杜瑞英
JIANG Qi;PENG Jinfen;CHEN Chuguo;LI Lei;DENG Tenghaobo;CHEN Yongjian;ZHAO Peihua;WEN Dian;DU Ruiying(Institute of Quality Standard and Monitoring Technology for Agro-products of Guangdong Academy of Agricultural Sciences,Guangzhou,Guangdong 510640,China;Laboratory of Quality&Safety Risk Assessment for Agro-products(Guangzhou),Ministry of Agriculture and Rural Affairs,P.R.China,Guangzhou,Guangdong 510640,China;Laboratory of Quality&Safety Risk Assessment for Agro-products(Guangzhou),Guangdong Province,Guangzhou,Guangdong 510640,China;Guangdong Agricultural Monitoring Technology Co.,Ltd.,Guangzhou,Guangdong 510640,China)
出处
《中国无机分析化学》
CAS
北大核心
2023年第5期407-413,共7页
Chinese Journal of Inorganic Analytical Chemistry
基金
国家自然科学基金资助项目(41807475,41701369)
国家农产品质量安全风险评估计划项目(GJFP2019036)。