Recent advances in the application of direct analysis in real time-mass spectrometry (DART-MS) in food analysis.

Advantages and limitations Contamination detection Direct analysis in real time Food authentication and traceability Mass spectrometry

Journal

Food research international (Ottawa, Ont.)
ISSN: 1873-7145
Titre abrégé: Food Res Int
Pays: Canada
ID NLM: 9210143

Informations de publication

Date de publication:
Jul 2024
Historique:
received: 07 02 2024
revised: 30 04 2024
accepted: 07 05 2024
medline: 2 6 2024
pubmed: 2 6 2024
entrez: 1 6 2024
Statut: ppublish

Résumé

Direct analysis in real time-mass spectrometry (DART-MS) has evolved as an effective analytical technique for the rapid and accurate analysis of food samples. The current advancements of DART-MS in food analysis are described in this paper. We discussed the DART principles, which include devices, ionization mechanisms, and parameter settings. Numerous applications of DART-MS in the fields of food and food products analysis published during 2018-2023 were reviewed, including contamination detection, food authentication and traceability, and specific analyte analysis in the food matrix. Furthermore, the challenges and limitations of DART-MS, such as matrix effect, isobaric component analysis, cost considerations and accessibility, and compound selectivity and identification, were discussed as well.

Identifiants

pubmed: 38823841
pii: S0963-9969(24)00558-1
doi: 10.1016/j.foodres.2024.114488
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

114488

Informations de copyright

Copyright © 2024 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Yang Wang (Y)

Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China. Electronic address: wang.yang1986@hotmail.com.

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Classifications MeSH