Carbohydrate determination in honey samples by ion chromatography-mass spectrometry (HPAEC-MS).


Journal

Analytical and bioanalytical chemistry
ISSN: 1618-2650
Titre abrégé: Anal Bioanal Chem
Pays: Germany
ID NLM: 101134327

Informations de publication

Date de publication:
Sep 2020
Historique:
received: 10 02 2020
accepted: 20 05 2020
revised: 30 04 2020
pubmed: 4 6 2020
medline: 15 4 2021
entrez: 4 6 2020
Statut: ppublish

Résumé

Honey is a complex mixture of carbohydrates, in which the monosaccharides glucose and fructose are the most abundant compounds. Currently, more than 20 oligosaccharides have been identified in different varieties of honey normally at quite low concentration. A method was developed and validated using high-performance anion-exchange chromatography coupled to a mass spectrometry detector to investigate the composition of carbohydrates in honey samples. The method was tested for linearity range, trueness, instrumental and method detection and quantification limits, repeatability, and reproducibility. It was applied to determine seven monosaccharides, eight disaccharides, four trisaccharides, and one tetrasaccharide in various honey samples. The present work describes the composition of sugars in unifloral, multifloral, and some honeydew honey, which were produced and collected by beekeepers in the Trentino Alto-Adige region. Statistical techniques have been used to establish a relationship based on levels of carbohydrates among different Italian honey. The results emphasize that mono- and oligosaccharide profiles can be useful to discriminate different honeys according to their floral characteristics and inter-annual variability.

Identifiants

pubmed: 32488387
doi: 10.1007/s00216-020-02732-3
pii: 10.1007/s00216-020-02732-3
doi:

Substances chimiques

Anions 0
Carbohydrates 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

5217-5227

Auteurs

Raffaello Tedesco (R)

Department of Environmental Sciences, Informatics and Statistics (DAIS), University of Venice Ca' Foscari, Via Torino 155, 30172, Venice, Mestre, Italy.
Fondazione Edmund Mach (FEM), via E. Mach,1, 38010, Trento, San Michele all'Adige, Italy.

Elena Barbaro (E)

Department of Environmental Sciences, Informatics and Statistics (DAIS), University of Venice Ca' Foscari, Via Torino 155, 30172, Venice, Mestre, Italy. barbaro@unive.it.
Institute of Polar Sciences, National Research Council of Italy, (ISP-CNR), Via Torino 155, 30172, Venice, Mestre, Italy. barbaro@unive.it.

Roberta Zangrando (R)

Department of Environmental Sciences, Informatics and Statistics (DAIS), University of Venice Ca' Foscari, Via Torino 155, 30172, Venice, Mestre, Italy.
Institute of Polar Sciences, National Research Council of Italy, (ISP-CNR), Via Torino 155, 30172, Venice, Mestre, Italy.

Annapaola Rizzoli (A)

Fondazione Edmund Mach (FEM), via E. Mach,1, 38010, Trento, San Michele all'Adige, Italy.

Valeria Malagnini (V)

Fondazione Edmund Mach (FEM), via E. Mach,1, 38010, Trento, San Michele all'Adige, Italy.

Andrea Gambaro (A)

Department of Environmental Sciences, Informatics and Statistics (DAIS), University of Venice Ca' Foscari, Via Torino 155, 30172, Venice, Mestre, Italy.
Institute of Polar Sciences, National Research Council of Italy, (ISP-CNR), Via Torino 155, 30172, Venice, Mestre, Italy.

Paolo Fontana (P)

Fondazione Edmund Mach (FEM), via E. Mach,1, 38010, Trento, San Michele all'Adige, Italy.

Gabriele Capodaglio (G)

Department of Environmental Sciences, Informatics and Statistics (DAIS), University of Venice Ca' Foscari, Via Torino 155, 30172, Venice, Mestre, Italy.
Institute of Polar Sciences, National Research Council of Italy, (ISP-CNR), Via Torino 155, 30172, Venice, Mestre, Italy.

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