US Department of Agriculture, Agricultural Research Service, Eastern Regional Research Center, 600 East Mermaid Lane, Wyndmoor, PA, 19038, USA.
College of Science, China Agricultural University, Beijing, 100193, China.
Anal Bioanal Chem. 2018 Sep;410(22):5465-5479. doi: 10.1007/s00216-018-0905-1. Epub 2018 Feb 6.
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 Blixer® 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. Graphical abstract Efficient quality control approach to include sample processing.
在食品的常规监测中，减少分析测试部分的大小通常会导致更高的样品通量、更少的劳动力和更低的监测成本，但为了满足分析需求，测试部分仍需要准确代表原始的散装样品。为了确定最小的适用测试部分大小，对使用不同样品粉碎设备加工的 10 种常见水果和蔬菜中的 93 种实际和添加的农药残留进行了分析。研究的商品包括苹果、香蕉、西兰花、芹菜、葡萄、绿豆、桃、土豆、橙子和南瓜。使用 Blixer®在室温下切碎散装样品，并取 15、10、5、2 和 1 g 的测试部分进行分析（n = 4 个）。此外，40 g （冷冻后）的样品进一步用液氮冷冻的 cryomill 装置粉碎，取 5、2 和 1 g 的测试部分进行分析（n = 4 个）。均使用低压力气相色谱-串联质谱法（LPGC-MS/MS）和超高效液相色谱法-质谱法（UHPLC-MS/MS）进行分析。通过在每个步骤之前添加质量控制标准品，采用经验方法来分离和估计整个方法中每个步骤的测量不确定度贡献。在提取过程中添加内标使样品制备步骤归一化为 0%的误差贡献，并且分析步骤（LC 和 GC）的变异系数（CVs）为 6-7%，样品处理技术的 CVs 为 6-9%。在实践中，不同的分析物、商品、批次、测试部分重量、分析和样品处理方法之间的平均总体 CVs 为 9-11%。平均而言，与使用 10-15 g 测试部分相比，使用 1-2 g 测试部分时，CVs 增加了 4%，偏差增加了 8-12%。
