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Use of a quality control approach to assess measurement uncertainty in the comparison of sample processing techniques in the analysis of pesticide residues in fruits and vegetables

机译:使用质量控制方法评估样品加工技术的测量不确定性在水果和蔬菜中农药残留量分析中的比较

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In routine monitoring of foods, reduction of analyzed test portion size generally leads to higher sample throughput, less labor, and lower costs of monitoring, but to meet analytical needs, the test portions still need to accurately represent the original bulk samples. With the intent to determine minimal fit-for-purpose sample size, analyses were conducted for up to 93 incurred and added pesticide residues in 10 common fruits and vegetables processed using different sample comminution equipment. The commodities studied consisted of apple, banana, broccoli, celery, grape, green bean, peach, potato, orange, and squash. A BlixerA (R) was used to chop the bulk samples at room temperature, and test portions of 15, 10, 5, 2, and 1 g were taken for analysis (n = 4 each). Additionally, 40 g subsamples (after freezing) were further comminuted using a cryomill device with liquid nitrogen, and test portions of 5, 2, and 1 g were analyzed (n = 4 each). Both low-pressure gas chromatography-tandem mass spectrometry (LPGC-MS/MS) and ultrahigh-performance liquid chromatography (UHPLC)-MS/MS were used for analysis. An empirical approach was followed to isolate and estimate the measurement uncertainty contribution of each step in the overall method by adding quality control spikes prior to each step. Addition of an internal standard during extraction normalized the sample preparation step to 0% error contribution, and coefficients of variation (CVs) were 6-7% for the analytical steps (LC and GC) and 6-9% for the sample processing techniques. In practice, overall CVs averaged 9-11% among the different analytes, commodities, batches, test portion weights, and analytical and sample processing methods. On average, CVs increased up to 4% and bias 8-12% when using 1-2 g test portions vs. 10-15 g.
机译:在食品的常规监测中,分析的测试部分尺寸的减少通常会导致更高的样本吞吐量,劳动力和更低的监测成本,而是为了满足分析需求,测试部分仍然需要准确地代表原始散装样品。随着确定最小的适合式样品大小,分析可在10个常见的水果和蔬菜中进行高达93个,并使用不同的样品粉碎设备处理的常见水果和蔬菜。学习的商品由苹果,香蕉,西兰花,芹菜,葡萄,青豆,桃子,土豆,橙子和壁球组成。使用Blixera(R)在室温下切碎体积样品,并考虑15,10,5,2和1g的测试部分进行分析(每个n = 4)。另外,使用具有液氮的冷冻机装置进一步粉碎40g子样品(冷冻后),并分析5,2和1g的测试部分(每个)。低压气相色谱 - 串联质谱(LPGC-MS / MS)和超高化学液相色谱(UHPLC)-MS / MS均用于分析。随后通过在每个步骤之前添加质量控制尖峰来隔离和估计每个步骤的测量不确定性贡献。在提取过程中添加内部标准将样品制备步骤标准化为0%误差贡献,并且分析步骤(LC和GC)的变异系数为6-7%,对于样品处理技术,6-9%。在实践中,不同的分析物,商品,批次,试验部分重量和分析和样品加工方法的总体CVS平均为9-11%。平均而言,在使用1-2g测试部分与10-15g时,CVS增加到4%,偏置8-12%。

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