Publication
DLLμE/GC-MS as a Powerful Analytical Approach to Establish the Volatilomic Composition of Different Whiskeys
dc.contributor.author | Perestrelo, Rosa | |
dc.contributor.author | Caldeira, Michael | |
dc.contributor.author | Rodrigues, Freddy | |
dc.contributor.author | Pereira, Jorge A. M. | |
dc.contributor.author | Câmara, José S. | |
dc.date.accessioned | 2024-07-16T14:55:58Z | |
dc.date.available | 2024-07-16T14:55:58Z | |
dc.date.issued | 2022 | |
dc.description.abstract | The volatilomic fingerprint of nine different whiskeys was established using a rapid and sensitive analytical approach based on dispersive liquid–liquid microextraction (DLLµE) followed by gas chromatography mass spectrometry detection (GC-MS) and gas chromatography with flame ionization detection (GC-FID). The influence of the extractor solvent on the extraction efficiency of volatile compounds (VOCs) was evaluated by DLLµE/GC-MS. The highest amounts of VOCs were obtained using 5 mL of sample, dichloromethane as the extractor solvent, and acetone as the disperser solvent. The proposed method showed no matrix effect, good linearity (R2 ≥ 0.993) in the assessed concentration range, recovery (ranging from 70 to 99%, precision (RSD ≤ 15%) and sensitivity (low limits of detection and quantification). A total of 37 VOCs belonging to different biosynthetic pathways including alcohols, esters, acids, carbonyl compounds, furanic compounds and volatile phenols were identified and quantified using DLLµE/GC-MS and DLLµE/GC-FID, respectively. Alcohols (3-methylbutan-1-ol, propan-1-ol), esters (ethyl decanoate, ethyl octanoate, ethyl hexanoate), and acids (decanoic acid, octanoic acid, hexanoic acid) were the most abundant chemical families. The multivariate statistical analysis allowed for the discrimination of whiskeys based on their volatilomic fingerprint, namely octanoic acid, 2-furfural, ethyl octanoate, ethyl hexanoate, acetic acid, ethyl dodecanoate, butan-1-ol, and ethyl decanoate. | pt_PT |
dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
dc.identifier.citation | Perestrelo, R.; Caldeira, M.; Rodrigues, F.; Pereira, J.A.M.; Câmara, J.S. DLLµE/GC-MS as a Powerful Analytical Approach to Establish the Volatilomic Composition of Different Whiskeys. Beverages 2022, 8, 53. https:// doi.org/10.3390/beverages8030053 | pt_PT |
dc.identifier.doi | 10.3390/beverages8030053 | pt_PT |
dc.identifier.uri | http://hdl.handle.net/10400.13/5750 | |
dc.language.iso | eng | pt_PT |
dc.peerreviewed | yes | pt_PT |
dc.publisher | MDPI | pt_PT |
dc.relation | Madeira Chemistry Research Centre | |
dc.relation | Madeira Chemistry Research Centre | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
dc.subject | Whiskeys | pt_PT |
dc.subject | Volatile fingerprint | pt_PT |
dc.subject | Dispersive liquid–liquid microextraction | pt_PT |
dc.subject | GC-MS | pt_PT |
dc.subject | . | pt_PT |
dc.subject | Centro de Química da Madeira | pt_PT |
dc.subject | Faculdade de Ciências Exatas e da Engenharia | pt_PT |
dc.title | DLLμE/GC-MS as a Powerful Analytical Approach to Establish the Volatilomic Composition of Different Whiskeys | pt_PT |
dc.type | journal article | |
dspace.entity.type | Publication | |
oaire.awardTitle | Madeira Chemistry Research Centre | |
oaire.awardTitle | Madeira Chemistry Research Centre | |
oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00674%2F2020/PT | |
oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00674%2F2020/PT | |
oaire.citation.issue | 3 | pt_PT |
oaire.citation.startPage | 53 | pt_PT |
oaire.citation.title | Beverages | pt_PT |
oaire.citation.volume | 8 | pt_PT |
oaire.fundingStream | 6817 - DCRRNI ID | |
oaire.fundingStream | 6817 - DCRRNI ID | |
person.familyName | Perestrelo | |
person.familyName | Caldeira | |
person.familyName | Augusto Machado Pereira | |
person.familyName | Câmara | |
person.givenName | Rosa | |
person.givenName | Michael | |
person.givenName | Jorge | |
person.givenName | José | |
person.identifier | 1441319 | |
person.identifier | G-3003-2013 | |
person.identifier.ciencia-id | 251A-D5F7-9E32 | |
person.identifier.ciencia-id | EC12-EE8F-50E8 | |
person.identifier.ciencia-id | 481C-08CE-90E5 | |
person.identifier.orcid | 0000-0002-7223-1022 | |
person.identifier.orcid | 0000-0001-5371-7281 | |
person.identifier.orcid | 0000-0003-0316-5348 | |
person.identifier.orcid | 0000-0003-1965-3151 | |
person.identifier.rid | I-2307-2014 | |
person.identifier.rid | A-2461-2013 | |
person.identifier.scopus-author-id | 16686828800 | |
person.identifier.scopus-author-id | 16300962200 | |
person.identifier.scopus-author-id | 10140393000 | |
project.funder.identifier | http://doi.org/10.13039/501100001871 | |
project.funder.identifier | http://doi.org/10.13039/501100001871 | |
project.funder.name | Fundação para a Ciência e a Tecnologia | |
project.funder.name | Fundação para a Ciência e a Tecnologia | |
rcaap.rights | openAccess | pt_PT |
rcaap.type | article | pt_PT |
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relation.isAuthorOfPublication.latestForDiscovery | 2f4d7adf-ab6b-40ab-85d5-73995a784bda | |
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relation.isProjectOfPublication.latestForDiscovery | e64ad36a-83b5-467c-bbb3-449ffc0662f2 |
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