A LC-MS/MS method with electrospray ionization and atmospheric pressure chemical ionization source for analysis of pesticides in hemp
Bibliographic record
Abstract
BACKGROUND: Pesticide testing for hemp has traditionally focused on techniques like QuEChERS with dSPE and SPE which demand time-consuming sample preparation, typically resulting in poor recovery rates for some pesticides, and requires the use of both LC-MS/MS and GC-MS/MS based instruments to cover the analysis for all regulated pesticides. In this study, we describe a streamlined approach for working with LC-MS/MS featuring a dual electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) sources using solvent extraction for faster and easier sample preparation and with 80-120% recovery for the analysis of all of 66 pesticides (regulated by California state in cannabis) with low detection limits in hemp. METHODS: A simple solvent extraction with acetonitrile was used to extract pesticides from hemp. A LC-MS/MS system with dual ESI and APCI source was used to determine sensitivity for the analysis of 66 pesticides in hemp matrix, 62 pesticides were analyzed using an 18-min LC-MS/MS method with an ESI source and the other 4 pesticides were measured using a 6-min LC-MS/MS method with an APCI source. RESULTS: The limit of quantitation (LOQ) of all 66 pesticides in hemp was in the range of 0.0025-0.1 μg/g which was well below the California state action limits of these analytes in cannabis products. A simple, fast, and cost-effective solvent extraction method was used for sample preparation to get good recovery in the range of 80-120% with RSD less than 20%. The unique ionization mechanism of chlorinated pesticides such as pentachloronitrobenzene using the LC-MS/MS system with an APCI source was elucidated. The proficiency test report generated with the LC-MS/MS method showed acceptable results for all of 66 pesticides in hemp with all of th z scores less than 2 with no false positives and negatives. The stability data collected over 5 days showed RSD less than 20% for 66 pesticides in hemp, and this demonstrated the robustness of the LC-MS/MS system used in this work. CONCLUSIONS: A LC-MS/MS method with dual ESI and APCI sources was developed for the analysis of 66 pesticides in hemp. The recovery of all pesticides from a hemp matrix was in the acceptable range of 80-120% with RSD less than 20%.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".