Potential Aroma Chemical Fingerprint of Oxidised Coffee Note by HS-SPME-GC-MS and Machine Learning

Potential Aroma Chemical Fingerprint of Oxidised Coffee Note by HS-SPME-GC-MS and Machine Learning

This study examines the volatilome of good and oxidised coffee samples from two commercial coffee species (i.e., <i>Coffea arabica</i> (arabica) and <i>Coffea canephora</i> (robusta)) in different packagings (i.e., standard with aluminium barrier and Eco-caps) to define a fin...

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Bibliographic Details
Main Authors: Giulia Strocchi, Eloisa Bagnulo, Manuela R. Ruosi, Giulia Ravaioli, Francesca Trapani, Carlo Bicchi, Gloria Pellegrino, Erica Liberto
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Foods
Subjects:
coffee volatilome
oxidative note
aroma fingerprint
HS-SPME-GC-MS/FPD
machine learning
Online Access:https://www.mdpi.com/2304-8158/11/24/4083

Internet

https://www.mdpi.com/2304-8158/11/24/4083

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