Unknown

Dataset Information

0

Electrostatic Spray Ionization-Mass Spectrometry for Direct and Fast Wine Characterization.


ABSTRACT: Due to the globally existed and economically motivated adulteration including mislabeling and/or blending, fast wine characterization is important in wine industry. Herein, we developed an electrostatic spray ionization-mass spectrometry (ESTASI-MS)-based method to distinguish wines. Wine samples were directly analyzed by ESTASI-MS without any pretreatment. Microdroplets of wine were deposited on a plastic plate for analysis. The collection of each mass spectrometric datum can be accomplished in 1-2 min without any need of pretreatment to the sample, followed by principle component analysis to discriminate wines with different labels and vintages. Long-term storage of wine was simulated and characterized by utilizing the method. High-performance liquid chromatography-MS was further applied to identify the distinctive compounds in wines to indicate their difference. We found that the method can offer a strategy for quick wine analysis, which is of practical value in wine industry for wine classification and aging control.

SUBMITTER: Bi H 

PROVIDER: S-EPMC6643611 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

altmetric image

Publications

Electrostatic Spray Ionization-Mass Spectrometry for Direct and Fast Wine Characterization.

Bi Hongyan H   Xi Minjie M   Zhang Rutan R   Wang Chengyu C   Qiao Liang L   Xie Jing J  

ACS omega 20181220 12


Due to the globally existed and economically motivated adulteration including mislabeling and/or blending, fast wine characterization is important in wine industry. Herein, we developed an electrostatic spray ionization-mass spectrometry (ESTASI-MS)-based method to distinguish wines. Wine samples were directly analyzed by ESTASI-MS without any pretreatment. Microdroplets of wine were deposited on a plastic plate for analysis. The collection of each mass spectrometric datum can be accomplished in  ...[more]

Similar Datasets

| S-EPMC5731662 | biostudies-literature
| S-EPMC8151837 | biostudies-literature
| S-EPMC6529299 | biostudies-literature
| S-EPMC3750536 | biostudies-literature
| S-EPMC6537876 | biostudies-literature
| S-EPMC3245870 | biostudies-literature
| S-EPMC10537605 | biostudies-literature
| S-EPMC3770260 | biostudies-literature
| S-EPMC3039116 | biostudies-literature
| S-EPMC4426755 | biostudies-other