Liquid Chromatography with Post-Column Reagent Addition of Ammonia in Methanol Coupled to Negative Ion Electrospray Ionization Tandem Mass Spectrometry for Determination of Phenoxyacid Herbicides and their Degradation Products in Surface Water
Bibliographic record
Abstract
A new liquid chromatography (LC)-negative ion electrospray ionization (ESI(-))-tandem mass spectrometry (MS/MS) method with post-column addition of ammonia in methanol has been developed for the analysis of acid herbicides: 2,4-dichlorophenoxy acetic acid, 4-chloro-o-tolyloxyacetic acid, 2-(2-methyl-4-chlorophenoxy)butyric acid, mecoprop, dichlorprop, 4-(2,4-dichlorophenoxy) butyric acid, 2,4,5-trichlorophenoxy propionic acid, dicamba and bromoxynil, along with their degradation products: 4-chloro-2-methylphenol, 2,4-dichlorophenol, 2,4,5-trichlorophenol and 3,5-dibromo-4-hydroxybenzoic acid. The samples were extracted from the surface water matrix using solid-phase extraction (SPE) with a polymeric sorbent and analyzed with LC ESI(-) with selected reaction monitoring (SRM) using a three-point confirmation approach. Chromatography was performed on a Zorbax Eclipse XDB-C18 (50 x 4.6 mm i.d., 1.8 mum) with a gradient elution using water-methanol with 2 mM ammonium acetate mobile phase at a flow rate of 0.15 mL/min. Ammonia in methanol (0.8 M) was added post-column at a flow rate of 0.05 mL/min to enhance ionization of the degradation products in the MS source. One SRM transition was used for quantitative analysis while the second SRM along with the ratio of SRM1/SRM2 within the relative standard deviation determined by standards for each individual pesticide and retention time match were used for confirmation. The standard deviation of ratio of SRM1/SRM2 obtained from standards run on the day of analysis for different phenoxyacid herbicides ranged from 3.9 to 18.5%. Limits of detection (LOD) were between 1 and 15 ng L(-1) and method detection limits (MDL) with strict criteria requiring <25% deviation of peak area from best-fit line for both SRM1 and SRM2 ranged from 5 to 10 ng L(-1) for acid ingredients (except dicamba at 30 ng L(-1)) and from 2 to 30 ng L(-1) for degradation products. The SPE-LC-ESI(-) MS/MS method permitted low nanogram-per-liter determination of pesticides and degradation products for surface water samples.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".