Off-line SPE LC-LRMS Polyphenolic Fingerprinting and Chemometrics to Classify and Authenticate Spanish Honey

dc.contributor.author
García-Seval, Víctor
dc.contributor.author
Saurina, Javier
dc.contributor.author
Sentellas, Sonia
dc.contributor.author
Núñez Burcio, Oscar
dc.date.issued
2023-01-26T09:24:21Z
dc.date.issued
2023-01-26T09:24:21Z
dc.date.issued
2022-11-13
dc.date.issued
2023-01-26T09:24:22Z
dc.identifier
1420-3049
dc.identifier
https://hdl.handle.net/2445/192631
dc.identifier
726732
dc.description.abstract
The feasibility of non-targeted off-line SPE LC-LRMS polyphenolic fingerprints to address the classification and authentication of Spanish honey samples based on both botanical origin (blossom- and honeydew-honeys) and geographical production region was evaluated. With this aim, 136 honey samples belonging to different botanical varieties (multifloral and monofloral) obtained from different Spanish geographical regions with specific climatic conditions were analyzed. Polyphenolic compounds were extracted by off-line solid phase extraction (SPE) using HLB (3 mL, 60 mg) cartridges. The obtained extracts were then analyzed by C18 reversed-phase LC coupled to low-resolution mass spectrometry in a hybrid quadrupole-linear ion trap mass analyzer and using electrospray in negative ionization mode. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were employed to assess the pattern recognition capabilities of the obtained fingerprints to address honey classification and authentication. In general, a good sample discrimination was accomplished by PLS-DA, being able to differentiate both blossom-honey and honeydew-honey samples according to botanical varieties. Multiclass predictions by cross-validation for the set of blossom-honey samples showed sensitivity, specificity, and classification ratios higher than 60%, 85%, and 87%, respectively. Better results were obtained for the set of honeydew-honey samples, exhibiting 100% sensitivity, specificity, and classification ratio values. The proposed fingerprints demonstrated also to be good honey chemical descriptors to deal with climatic and geographical issues. Characteristic polyphenols of each botanical variety were tentatively identified by LC-MS/MS in multiple reaction monitoring mode to propose possible honey markers for future experiments (i.e., naringin for orange/lemon blossom honeys, syringic acid in thyme honeys, or galangin in rosemary honeys)
dc.format
16 p.
dc.format
application/pdf
dc.format
application/pdf
dc.language
eng
dc.publisher
MDPI
dc.relation
Reproducció del document publicat a: https://doi.org/10.3390/molecules27227812
dc.relation
Molecules, 2022, vol. 27, num. 22, p. 7812
dc.relation
https://doi.org/10.3390/molecules27227812
dc.rights
cc-by (c) García-Seval, Víctor et al., 2022
dc.rights
https://creativecommons.org/licenses/by/4.0/
dc.rights
info:eu-repo/semantics/openAccess
dc.source
Articles publicats en revistes (Enginyeria Química i Química Analítica)
dc.subject
Polifenols
dc.subject
Quimiometria
dc.subject
Polyphenols
dc.subject
Chemometrics
dc.title
Off-line SPE LC-LRMS Polyphenolic Fingerprinting and Chemometrics to Classify and Authenticate Spanish Honey
dc.type
info:eu-repo/semantics/article
dc.type
info:eu-repo/semantics/publishedVersion


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