通过分析指标评价优化后超声和红外辅助提取的绿度

IF 5.2 Q1 CHEMISTRY, ANALYTICAL
Florencia Cora Jofre , Silvana M. Azcarate , José M. Camiña , Pablo Pacheco , Marianela Savio
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引用次数: 7

摘要

样品制备涉及一个关键步骤,因为有机物含量高,意味着在分析之前会分解。在超声(USAE)和红外(IRAE)辐射的辅助下,优化并比较了使用稀释HNO3制备样品的两种替代分析策略。多元素测定采用MIP-OES法。为了优化实验条件,进行了以表面为中心的中心复合材料设计,分别考虑了IRAE和USAE的四个和五个因素。溶解有机碳(DOC)、残留酸度(RA)和固体残留物(SR)显著影响待评估的响应。采用响应面方法来寻找质量、稀释试剂(HNO3和H2O2)、时间和温度的最佳组合,以最大限度地减少动物饲料样品中元素提取的响应。优化的实验条件:样品质量为500 mg,浴温为60°C,萃取时间为30 min,2 mol L−1 HNO3和27%H2O2,用于验证USAE程序。建立的IRAE条件是500 mg猪饲料样品,然后加入2 mL 2 mol L−1 HNO3和23%H2O2,照射23分钟。回收率为81~114%,精密度良好(RSD<;4%)。使用五个指标工具,证明了所提出方法的绿色性。IRAE法简便、可靠、快速、易操作,成功地应用于农产品样品中钙、铜、铁、钾、镁、锰、磷、锌的测定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing the greenness of optimized ultrasound and infrared assisted extraction through analytical metrics

Sample preparation involves a critical step due to the high organic matter content that implies its decomposition, prior to analysis. Two alternative analytical strategies for sample preparation employing diluted HNO3 were optimized and compared, assisted by ultrasound (USAE) and infrared (IRAE) radiation. Multielement determination was achieved by MIP OES. For optimization of experimental conditions, a central composite design centered on the faces was carried out, considering four and five factors for IRAE and USAE, respectively. Dissolved organic carbon (DOC), residual acidity (RA) and solid residue (SR), significantly influence the responses to be evaluated. The response surface methodology was implemented to find the best combination of mass, diluted reagents (HNO3 and H2O2), time and temperature in order to minimize responses for elemental extraction in animal feed samples. The optimized experimental conditions: 500 mg of sample mass, 60 °C of bath temperature, 30 min of extraction time, 2 mol L−1 HNO3 and 27% H2O2, were used to validate the USAE procedure. The conditions established for IRAE were 500 mg of the swine feed sample, followed by the addition of 2 mL of 2 mol L−1 HNO3 and 23% H2O2, irradiating for 23 min. Recoveries ranged from 81 to 114%, with good precision (RSD < 4%). Using five index tools the greenness of the proposed methods was demonstrated. According to IRAE simplicity, reliability, fast and easy to implement, it was successfully applied to the determination of Ca, Cu, Fe, K, Mg, Mn, P and Zn in agrifood samples.

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