Rajski Łukasz, Petromelidou Styliani, Díaz-Galiano Francisco José, Ferrer Carmen, Fernández-Alba Amadeo Rodríguez
European Union Reference Laboratory for Pesticide Residues in Fruit & Vegetables, University of Almería, Agrifood Campus of International Excellence (ceiA3). Ctra, Sacramento s/n. La Cañada de San Urbano 04120-Almería, Spain.
Laboratory of Environmental Pollution Control, Department of Chemistry, Aristotle University of Thessaloniki, Thessaloniki, GR-541 24, Greece.
Talanta. 2021 Jun 1;228:122241. doi: 10.1016/j.talanta.2021.122241. Epub 2021 Feb 25.
The use of high-resolution mass spectrometry (HRMS) for the simultaneous target and non-target analysis of pesticide residues in food control is a subject that has been studied over the last decade. However, proving its efficacy compared to the more established triple quadrupole mass spectrometers (QQQ-MS2) is challenging. Various HRMS platforms have been evaluated, seemingly showing this approach not to be as effective as QQQ-MS2 for quantitative analysis, especially in routine food testing laboratories. The two main reasons are (i) the lower sensitivity especially in the case of the fragment ions produced and (ii) the lack of familiarity and an understanding of the most appropriate combination of HRMS acquisition modes to use. In fact, the number of different acquisition modes can appear as a puzzle to inexperienced users. This work was therefore focused on obtaining experimental data to gain a better understanding of the extended acquisition capabilities of a new Q-Orbitrap platform. Experimental data were obtained for 244 pesticides and their degradation products in commodities of varying matrix complexity (tomato, onion, avocado, and orange) using various combinations of acquisition modes. The best results for targeted analysis were obtained with a combination of full scan (FS), all-ions fragmentation (AIF) and target MS2 (tMS2) modes, and for non-target analysis using full scan (FS) and data-dependent MS2 (ddMS2) modes. All these acquisition modes (FS, AIF, tMS2, and ddMS2) could be applied simultaneously with cycle times ≤ 1 s. The tMS2 especially, proved to be a very powerful approach to increase sensitivity for MS2 fragments and identification rates. Overall, the results for the various pesticide-commodity combinations were fully satisfactory in terms of limit of quantitation (LOQ) repeatability and identification when considered against the SANTE EU Guideline criteria. In addition, the screening capabilities were evaluated for a non-target survey with the use of spectral libraries, the presence of non-target compounds was detected, thus proving the efficacy of the proposed approach. Another issue often overlooked is the optimization of use of spectral libraries, but in our experiments the compounds present in these libraries were not blindly sought in the screening analyses. To minimize the potential for false positives detects in our study, the extractability of the compounds present in the libraries, was also taken into account. The extractability of compounds using a QuEChERS acetonitrile procedure was estimated based on the physicochemical properties of target compounds. By removing compounds that will not be extracted, reduces the occurrences of false detects, reducing the time required for data processing and thus improving the efficiency of the overall screening workflow.
在食品检测中,使用高分辨率质谱(HRMS)同时进行农药残留的靶向和非靶向分析是过去十年中一直研究的课题。然而,与更成熟的三重四极杆质谱仪(QQQ-MS2)相比,证明其有效性具有挑战性。已经评估了各种HRMS平台,似乎表明这种方法在定量分析方面不如QQQ-MS2有效,特别是在常规食品检测实验室中。两个主要原因是:(i)灵敏度较低,特别是在产生的碎片离子的情况下;(ii)缺乏对最合适的HRMS采集模式组合的熟悉和理解。事实上,不同采集模式的数量对于没有经验的用户来说可能是个难题。因此,这项工作的重点是获取实验数据,以更好地理解新型Q-轨道阱平台的扩展采集能力。使用各种采集模式组合,针对不同基质复杂性(番茄、洋葱、鳄梨和橙子)商品中的244种农药及其降解产物获得了实验数据。靶向分析的最佳结果是通过全扫描(FS)、全离子碎裂(AIF)和靶向MS2(tMS2)模式的组合获得的,非靶向分析则使用全扫描(FS)和数据依赖型MS2(ddMS2)模式。所有这些采集模式(FS、AIF、tMS2和ddMS2)可以在循环时间≤1秒的情况下同时应用。特别是tMS2,被证明是提高MS2碎片灵敏度和识别率的非常有效的方法。总体而言,根据欧盟SANTE指南标准,各种农药-商品组合的定量限(LOQ)、重复性和识别结果完全令人满意。此外,通过使用光谱库对非靶向调查的筛查能力进行了评估,检测到了非靶向化合物的存在,从而证明了所提出方法的有效性。另一个经常被忽视的问题是光谱库使用的优化,但在我们的实验中,在筛查分析中并没有盲目寻找这些库中存在的化合物。为了在我们的研究中尽量减少假阳性检测的可能性,还考虑了库中存在的化合物的可提取性。使用QuEChERS乙腈程序根据目标化合物的物理化学性质估计化合物的可提取性。通过去除不会被提取的化合物,减少了假检测的发生,减少了数据处理所需的时间,从而提高了整体筛查工作流程的效率。