Application of a Tandem Mass Spectrometer and Core–Shell Particle Column for the Determination of 151 Pesticides in Grains
Bibliographic record
Abstract
A comparison of ultrahigh performance liquid chromatography (UHPLC) with a 2.6 μm core-shell particle column (Kinetex C(18)) and conventional liquid chromatography (LC) with a 3 μm porous particle column (Atlantis dC(18)), coupled with electrospray ionization tandem mass spectrometry (ESI-MS/MS), for the determination of 151 pesticides in grains is presented in this study. Pesticides were extracted from grain samples using a procedure known as QuEChERS (quick, easy, cheap, effective, rugged, and safe). Quantification, with an analytical range from 5 to 500 μg/kg, was achieved using matrix-matched standard calibration curves with isotopically labeled standards or a chemical analogue as internal standards. The method performance parameters that included overall recovery, intermediate precision, and measurement uncertainty were evaluated using a designed experiment, that is, the nested design. The UHPLC (Kinetex C(18)) was superior to conventional LC (Atlantis dC(18)) as it yielded a shorter analytical run time, increased method sensitivity, and improved method performance. For UHPLC/ESI-MS/MS (Kinetex C(18)), 90% of the pesticides studied had recoveries between 81 and 110%, 88% of the pesticides had intermediate precision ≤20%, and 84% of the pesticides showed measurement uncertainty ≤40%. As compared to UHPLC/ESI-MS/MS (Kinetex dC(18)), the LC/ESI-MS/MS (Atlantis dC(18)) showed a relatively lower sensitivity, less repeatability, and larger measurement uncertainty. UHPLC/ESI-MS/MS with 2.6 μm core-shell particle column and scheduled MRM proved to be a good choice for quantification or determination of pesticides in grains.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".