PTR-QiToF-MS and HSI for the characterization of fermented cocoa beans from different origins.
Cocoa beans
Computer Vision System
Geographical origin
PTR-QiToF-MS
Journal
Food chemistry
ISSN: 1873-7072
Titre abrégé: Food Chem
Pays: England
ID NLM: 7702639
Informations de publication
Date de publication:
15 Aug 2019
15 Aug 2019
Historique:
received:
03
09
2018
revised:
13
03
2019
accepted:
19
03
2019
entrez:
9
4
2019
pubmed:
9
4
2019
medline:
10
8
2019
Statut:
ppublish
Résumé
The wide range of geographical cocoa production areas and the increasing consumption trend towards single origin products induced the necessity to verify and certify cocoa beans origin for quality assurance purposes. In this study cocoa beans of various origins were examined by machine olfaction and machine vision techniques. Fifty-nine fermented and dried Forastero cocoa beans from 23 different geographical origins (Africa, Americas, Southeast Asia) were investigated using Proton Transfer Reaction-Quadrupole interface-Time of Flight-Mass Spectrometry and Hyperspectral Imaging to elucidate the geographical information in the beans. The volatile and spectral fingerprints showed the same tendency in clustering samples from Africa separate from those from the Americas. High variability was observed for the Southeast Asian samples, which is most likely related to differences in fermentation. Machine olfaction and machine vision characterization provided a similar degree of separation but are complementary rapid techniques, which may be further developed for use in practical settings.
Identifiants
pubmed: 30955653
pii: S0308-8146(19)30580-1
doi: 10.1016/j.foodchem.2019.03.095
pii:
doi:
Substances chimiques
Volatile Organic Compounds
0
Types de publication
Journal Article
Langues
eng
Pagination
591-602Informations de copyright
Copyright © 2019. Published by Elsevier Ltd.