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响应面优化原子荧光光谱法测定富硒木薯中的硒含量 被引量:4

Optimization of AFS by response surface methodology for determination of selenium in selenium-enriched cassava
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摘要 采用单因素及响应面分析法,对盐酸提取-原子荧光光谱法测定微量硒的条件进行了优化,并对富硒木薯中无机硒含量进行了测定。结果表明,无机硒提取条件为:提取剂盐酸浓度为30%,水浴温度为100°,水浴时间30 min,超声时间30 min;最佳仪器测定参数为:载液盐酸浓度为6.0%;硼氢化钾浓度为2.0%;介质盐酸浓度为12.5%。该法无机硒回收率为93.0%~107%,检出限为0.465μg·L^(-1),可用于直接测定木薯中的无机硒和间接测定有机硒。实验还发现,富硒木薯中硒主要以有机硒的形态存在,多数木薯样品有机硒均占总硒的70%以上,符合《富有机硒食品含硒量要求》(DBS42/002-2014)的规定。 The conditions for determination of trace Se by atomic fluorescence spectrometry after hydrochloric acid extraction was optimized using single factor and response surface methodology,and the content of inorganic Se in selenium-enriched cassava was determined.The results showed that,the optimal conditions for inorganic Se extraction were: an extraction agent of 30% HCl,100℃ of water bath temperature,30 min of water bath time,and 30 min of ultrasonic time.The optimal instrument parameters for Se determination were: a carrier liquid of 6. 0%HCl,a KBH4 of 2. 0%,and a medium solution with 12. 5%HCl.The recovery rate of the method was 93. 0% ~ 107%,and the detection limit was 0. 465 μg·L^(-1). The method could be used for the determination of inorganic and organic Se in cassava samples.The experimental results also showed that Se in selenium-enriched cassava mainly existed as organic Se species,and the organic Se in most cassava samples were accounted for more than 70%of total Se,meet the"Requirements of se lenium content in organic selenium-rich foods"( DBS42/002-2014).
作者 蒋翠文 谢丽萍 李焘 牙禹 蔡卓 JIANG Cuiwen;XIE Liping;LI Tao;YA Yu;CAI Zhuo( Institute for Agricultural Product Quality Safety and Testing Technology,Guangxi Academy ofAgricultural Sciences,Nanning 530007,China; School of Chemistry and Chemical Engineering,Guangxi University,Nanning 530004,China)
出处 《化学研究与应用》 CAS CSCD 北大核心 2018年第6期1036-1040,共5页 Chemical Research and Application
基金 广西自然科学基金资助项目(2015GXNSFAA139239)资助 广西农业科学院科技发展基金(桂农科2017JM64)资助
关键词 富硒木薯 无机硒 有机硒 响应面法 selenium-enriched cassava inorganic selenium organic selenium response surface methodology
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