Intelligent chemical profiling of 73 edible flowers by liquid chromatography-high resolution mass spectrometry combined with HRMS database and their authentication based on large-scale fingerprints.
Food Chem
; 446: 138683, 2024 Jul 15.
Article
em En
| MEDLINE
| ID: mdl-38428081
ABSTRACT
A commercial high-resolution MS database "TCM-PCDL" was innovatively introduced to automatically identify multi-components in 73 edible flowers rapidly and accurately by liquid chromatography-high resolution mass spectrometry, which can be time-consuming and labor-intensive in traditional manual method. The database encompasses over 2565 natural products with various energy levels. Unknown compounds can be identified through direct matching and scoring MS2 spectra with database. A total of 870 compounds were identified from 73 flowers, with polyphenols constituting up to 75%. Focusing on polyphenols, a high performance liquid chromatography (HPLC) method was developed to generate fingerprints from 510 batches, establishing an "HPLC database" that enabled accurate authentication using similarity scores and rankings. This method demonstrated an accuracy rate of 100% when applied to 30 unknown samples. For flowers prone to confusion, additional statistical analysis methods could be employed as aids in authentication. This study provides valuable insights for large-scale sample chemical profiling and authentication.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Extratos Vegetais
/
Espectrometria de Massas em Tandem
Idioma:
En
Revista:
Food Chem
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
China