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Unpublished conference/Abstract (Scientific congresses and symposiums)
Distinguishing between Decaffeinated and Regular Coffee by HS-SPME-GC×GC-ToF-MS, Chemometrics, and Machine Learning
Gaida, Meriem; Zou, Yun; Franchina, Flavio A. et al.
2022 • 19th International GCxGC Symposium
Peer reviewed
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https://hdl.handle.net/2268/291713
 

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Keywords :
Coffee, decaffeination, Chemometrics, machine Learning; two-dimensional gas chromatography
Disciplines :
Chemistry
Author, co-author :
Gaida, Meriem  ;  Université de Liège - ULiège > Département de chimie (sciences) > Chimie analytique, organique et biologique
Zou, Yun
Franchina, Flavio A.;  University of Ferrara > Department of Chemical, Pharmaceutical and Agricultural Sciences
Stefanuto, Pierre-Hugues  ;  Université de Liège - ULiège > Département de chimie (sciences) > Chimie analytique, organique et biologique
Focant, Jean-François  ;  Université de Liège - ULiège > Département de chimie (sciences) > Chimie analytique, organique et biologique
Language :
English
Title :
Distinguishing between Decaffeinated and Regular Coffee by HS-SPME-GC×GC-ToF-MS, Chemometrics, and Machine Learning
Publication date :
02 June 2022
Event name :
19th International GCxGC Symposium
Event date :
29/05/2022-02/06/2022
Audience :
International
Peer reviewed :
Peer reviewed
Name of the research project :
“Chemical Information Mining in a Complex World”
Funders :
EOS - The Excellence Of Science Program
Funding number :
30897864
Available on ORBi :
since 03 June 2022

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