Journal
ANALYTICAL CHEMISTRY
Volume 90, Issue 22, Pages 13806-13813Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.8b04465
Keywords
-
Categories
Funding
- EJ Gallo Winery
- NY Wine Grape Foundation Enology Program [I-34]
- Agriculture and Food Research Initiative Award from the USDA National Institute of Food and Agriculture [2017-67007-25940]
- National Science Foundation [ECCS-15420819]
Ask authors/readers for more resources
Headspace (HS) extraction and preconcentration of volatiles by solid-phase microextraction (SPME) can improve the sensitivity and selectivity of ambient ionization-mass spectrometry approaches like direct analysis in real time (DART), but previous approaches to HS-SPME-DART-MS have been challenging to automate. This report describes the production of inexpensive, reusable solid-phase mesh-enhanced sorption from headspace (SPMESH) sheets by laser-etching mesh patterns into poly(dimethylsiloxane) (PDMS) sheets. Parallel headspace extraction of volatiles from multiple samples can be achieved by positioning the SPMESH sheets over multiwell plates and then attaching to a positioning stage for automated DART-MS quantitation. Using three representative odorants (3-isobutyl-2-methoxypyrazine, linalool, and methyl anthranilate), we achieved mu g/L-ng/L detection limits with SPMESH-DART-MS, with the DART-MS step requiring only 17 min for 24 samples. Acceptable repeatability (24% or less day-to-day variation) and excellent recovery from a grape matrix (99-106%) could be achieved. Through use of a Teflon gasket and stainless steel spacers, cross-contamination between the headspaces of adjacent wells could be limited to roughly 1%. Optimum SPMESH extraction and desorption parameters were determined by response surface methodology. In summary, sheet-based SPMESH provides a sensitive, readily automated approach for coupling with DART-MS and achieving high-throughput trace-level volatile analyses.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available