| Literature DB >> 32796576 |
Manoj Ghaste1,2, Nicholas C Hayden3, Matthew J Osterholt3, Julie Young3, Bryan Young3, Joshua R Widhalm1,2.
Abstract
Dicamba is a moderately volatile herbicide used for post-emergent control of broadleaf weeds in corn, soybean, and a number of other crops. With increased use of dicamba due to the release of dicamba-resistant cotton and soybean varieties, growing controversy over the effects of spray drift and volatilization on non-target crops has increased the need for quantifying dicamba collected from water and air sampling. Therefore, this study was designed to evaluate stable isotope-based direct quantification of dicamba from air and water samples using single-quadrupole liquid chromatography-mass spectrometry (LC-MS). The sample preparation protocols developed in this study utilize a simple solid-phase extraction (SPE) protocol for water samples and a single-step concentration protocol for air samples. The LC-MS detection method achieves sensitive detection of dicamba based on selected ion monitoring (SIM) of precursor and fragment ions and relies on the use of an isotopically labeled internal standard (IS) (D3-dicamba), which allows for calculating recoveries and quantification using a relative response factor (RRF). Analyte recoveries of 106-128% from water and 88-124% from air were attained, with limits of detection (LODs) of 0.1 ng mL-1 and 1 ng mL-1, respectively. The LC-MS detection method does not require sample pretreatment such as ion-pairing or derivatization to achieve sensitivity. Moreover, this study reveals matrix effects associated with sorbent resin used in air sample collection and demonstrates how the use of an isotopically labeled IS with RRF-based analysis can account for ion suppression. The LC-MS method is easily transferrable and offers a robust alternative to methods relying on more expensive tandem LC-MS/MS-based options.Entities:
Keywords: LC–MS; dicamba; herbicide volatility; internal standard quantification; selected ion monitoring
Mesh:
Substances:
Year: 2020 PMID: 32796576 PMCID: PMC7465465 DOI: 10.3390/molecules25163649
Source DB: PubMed Journal: Molecules ISSN: 1420-3049 Impact factor: 4.411
Figure 1Chemical structure of dicamba.
Liquid chromatography (LC) solvent gradient program.
| Time | A (%) | B (%) | Flow µL min−1 |
|---|---|---|---|
| 0 | 80 | 20 | 300 |
| 2 | 80 | 20 | 300 |
| 10 | 25 | 75 | 300 |
| 11 | 25 | 75 | 300 |
| 12 | 80 | 20 | 300 |
| 13 | 80 | 20 | 300 |
Figure 2Detection of dicamba in selected ion monitoring (SIM) mode with m/z 219 (parent ion, dashed line) and m/z 175 (fragment ion, solid line) ions shown (1 µg mL−1). Shaded region of dicamba structure shows COOH fragment that is lost from precursor ion (m/z 219) that results in fragment ion (m/z 175).
Figure 3Mass spectrometry (MS) full scan spectrum of dicamba analytical standard showing isotopic pattern corresponding to 35Cl m/z 175 (A) and m/z 219 (C), and 37Cl m/z 177 (B) and m/z 221 (D).
Method recovery in air and water samples. RSD, relative standard deviation.
| Concentration of Dicamba Added (ng mL−1) | % Recovery | RSD % | ||
|---|---|---|---|---|
|
| Level 1 | 0.1 | 128 | 10.3 |
| Level 2 | 1.0 | 108 | 5.6 | |
| Level 3 | 10.0 | 110 | 4.9 | |
|
| Level 1 | 1.0 | 124 | 9.2 |
| Level 2 | 5.0 | 88 | 5.5 | |
| Level 3 | 10.0 | 88 | 3.3 |
Figure 4Schematic diagram of the vapor chamber (side view) used in the experiment.
Dicamba levels in air samples.
| Dicamba Application (g ae ha−1) | Total Amount of Dicamba (ng) Per Sample | |||||
|---|---|---|---|---|---|---|
| Rep 1 | Rep 2 | Rep 3 | Rep 4 | Average | RSD % | |
| 560 | 729.7 | 763.2 | 549.4 | 741.1 | 668.7 | 14.8 |
| 2240 | 5172.8 | 4592.6 | 3975.1 | 4480.7 | 4092.2 | 12.0 |
Dicamba quantification from 500 mL water samples. Conc., concentration.
| (ng mL−1) | ||||||
|---|---|---|---|---|---|---|
| Sample | Rep 1 | Rep 2 | Rep 3 | Rep 4 | Average Conc. | RSD % |
|
| 296.5 | 278.0 | 293.7 | 274.1 | 285.6 | 4 |
|
| 115.1 | 111.9 | 114.1 | 109.5 | 112.7 | 2 |
|
| 76.8 | 72.1 | 70.6 | 76.3 | 74.0 | 4 |