Many chemical methods exist to measure specified contaminants and adulterants to ensure food safety, but analyses become more challenging if unknown, potentially hazardous compounds are present. Ultra-performance liquid chromatography and high-resolution mass spectrometry (UPLC/HR-MS) provides improved separation in both the chromatographic and mass-to-charge regimes and mass accuracies less than 5 ppm are routine.   These qualities are advantageous because they reduce chemical complexity and enable the generation of molecular formulae to aid in the identification of unknown compounds.  The aim of this work is to determine factors that influence the number of compounds that can be detected using non-targeted screening and UPLC/HR-MS.  To this end, infant rice cereal, orange juice, and yogurt were chosen to investigate the capabilities of the chosen sample preparation method, chromatographic gradient length, and the MS acquisition method.  Extraction methods included QuEChERS, the Universal method, and an acetonitrile shake-out; these samples were analyzed with a Nexera UPLC (Shimadzu) with a Kinetex C18 column hyphenated to a Q-Exactive mass spectrometer (Thermo).  Data processing was performed using Compound Discoverer (Thermo).  In general, the Universal method appeared to be the best choice for all three sample matrices analyzed in both positive and negative ion modes; this method extracted many of the same compounds as the other methods, but also had a large percentage of unique compounds associated with it.  Multiple MS methods were also examined to determine the number of molecular features that can be extracted from the data, including acquiring with different resolving powers, MS and MS-MS scans, and positive and negative ion modes.  The combined result of these analyses will be discussed with an emphasis on improving the detected chemical coverage for different sample types.<br/>

Non-targeted screening using LC/HR-MS: Impacts of sample preparation and acquisition methods on chemical coverage

254th National Meeting (2017)

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