National Food Institute, Research Group for Analytical Food Chemistry, Technical University of Denmark, Kemitorvet Building 202, Kgs. Lyngby, DK-2800, Denmark.
University of Tartu, Institute of Chemistry, Ravila 14a, Tartu 50411, Estonia.
Food Chem. 2020 Jul 15;318:126460. doi: 10.1016/j.foodchem.2020.126460. Epub 2020 Feb 20.
LC/ESI/MS is the technique of choice for qualitative and quantitative food monitoring; however, analysis of a large number of compounds is challenged by the availability of standard substances. The impediment of detection of food contaminants has been overcome by the suspect and non-targeted screening. Still, the results from one laboratory cannot be compared with the results of another laboratory as quantitative results are required for this purpose. Here we show that the results of the suspect and non-targeted screening for pesticides can be made quantitative with the aid of in silico predicted electrospray ionization efficiencies and this allows direct comparison of the results obtained in two different laboratories. For this purpose, six cereal matrices were spiked with 134 pesticides and analysed in two independent labs; a high correlation for the results with the R of 0.85.
LC/ESI/MS 是用于定性和定量食品监测的首选技术;然而,由于标准物质的可用性,对大量化合物的分析受到了挑战。通过嫌疑和非靶向筛选,已经克服了对食品污染物检测的阻碍。尽管如此,由于需要定量结果,一个实验室的结果不能与另一个实验室的结果进行比较。在这里,我们表明,借助于计算机预测的电喷雾电离效率,可以对农药的嫌疑和非靶向筛选结果进行定量,这允许对两个不同实验室获得的结果进行直接比较。为此,将 134 种农药添加到六种谷物基质中,并在两个独立的实验室中进行分析;结果的相关性很高,相关系数为 0.85。