The rapid and robust identification of agrochemical metabolites from animal, plant and e-fate studies is an ongoing challenge in new product development. The challenge is often exacerbated by the trend in lower application rates coupled with complex matrices. The application of high resolution LC-MS and LC-MS/MS remain the primary tool in industry for this purpose. Despite the welcome developments in instrument sensitivity, resolution and dynamic range, this does not necessarily guarantee the analyst a useable dataset. The importance of a good quality sample should remain paramount, especially with the associated cost of state of the art LC-MS instrumentation and the time pressures which exist in regulatory development. Fortunately, there are now more robust and powerful software packages which can assist the analytical chemist in mining meaningful data from the analysis of complex samples. This can lead to more rapid identification of unknown metabolites, which would otherwise remain extremely difficult to find and elucidate using classical sample clean-up techniques alone. This presentation will highlight the power of combining creative sample clean-up techniques in the laboratory together with quick and simple-to-apply software algorithms for refinement of high resolution MS datasets, beyond what is possible using these techniques on their own.

Combining sample clean-up techniques and high resolution LC-MS, with software manipulation, for metabolite identification in support of agrochemical product development

256th National Meeting (2018)

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