Structurally related impurity profiling of thiacloprid by orbitrap and de novo identification tool

Comprehensive impurity identification in agrochemicals is one key prerequisite for their safety evaluation and certified reference material development. Thiacloprid (THI), belonging to the first generation of neonicotinoids, has been among the most frequently used and detected insecticides. Herein, a novel protocol was developed for the impurity profiling of THI with liquid chromatography-high resolution mass spectrometry (orbitrap) and de novo identification tool (SIRIUS). With MS and MS/MS spectra, the calculated SIRIUS, isotope, fragment tree, and Zodiac scores were used to rank the chemical structure candidates. THI, the main component, was taken as a reference for chemical structure elucidation of impurities by the shared neutral loss and fragmented ions. Finally, 18 impurities were all elucidated and divided into five groups according to their structural difference and 14 impurities were reported for the first time without CAS number. Two impurities were verified with standards by retention time and UV spectrum. This work showed the success of combining de novo identification tool with human intelligence in impurity profiling of THI.

Automated summary

Comprehensive impurity identification is essential for the safety evaluation and development of certified reference materials in the field of agrochemicals. This study developed a novel protocol for impurity profiling of THI using liquid chromatography-high resolution mass spectrometry (orbitrap) and de novo identification tool (SIRIUS). The SIRIUS, isotope, fragment tree, and Zodiac scores were utilized to rank the chemical structure candidates based on MS and MS/MS spectra. By using THI as a reference, impurity chemical structures were elucidated through shared neutral loss and fragmented ions. A total of 18 impurities were successfully identified and categorized into five groups, with 14 impurities being reported for the first time without CAS number. Two impurities were verified with standards using retention time and UV spectrum. This study demonstrates the successful application of combining de novo identification tool with human intelligence in THI impurity profiling.