Trimethylation Enhancement Using Diazomethane (TrEnDi) Enables Enhanced Detection of Glufosinate and 3-(Methylphosphinico)propionic Acid from Complex Canola Samples.

Over the past century, agriculture practices have transitioned from manual cultivation to the use of an array of chemical herbicides for weed control including phosphinothricin, or glufosinate (GLUF). Consequently, the potential for long-term residual GLUF exposure in the food chain has increased, highlighting the need for improved analytical strategies for its detection, as well as the detection of its main breakdown product 3-(methylphosphinico)propionic acid (MPPA). Chemical derivatization strategies have been developed to improve the detection of GLUF and MPPA via liquid chromatography tandem mass spectrometry analyses. Herein, we employ trimethylation enhancement using diazomethane (TrEnDi) for the first time as a means to confer analytical advantages via quantitatively derivatizing these analytes into permethylated GLUF ([GLUF Tr ] + ) and MPPA ([MPPA Tr +H] + ). Comparing [GLUF Tr ] + and [MPPA Tr +H] + to underivatized counterparts, TrEnDi yields 2.8-fold and 1.7-fold improvements in reversed-phase chromatographic retention, respectively, while MS-based sensitivity is enhanced 4.1-fold and 11.0-fold, respectively. Successful analyte derivatization (with >99% yields) was further demonstrated on a commercial herbicide solution imparting consistent analytical enhancements. To investigate the benefits of TrEnDi in a bona fide agricultural scenario, simple aqueous extractions from distinct parts of field-grown canola plants were performed to quantify GLUF and MPPA before and after TrEnDi derivatization. In their underivatized forms, GLUF and MPPA were undetectable in all field samples, whereas [GLUF Tr ] + and [MPPA Tr +H] + were readily quantifiable using the same analysis conditions. Our results demonstrate that TrEnDi continues to be a useful tool to enhance the analytical characteristics of organic molecules that are traditionally difficult to detect.