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Characterization and Analysis of Okoume and Aiele Essential Oils from Gabon by GC-MS, Electronic Nose, and Their Antibacterial Activity Assessment

Authors :
Youssra Aghoutane
Mohammed Moufid
Soukaina Motia
Guy Stephane Padzys
Linda Priscilia Omouendze
Eduard Llobet
Benachir Bouchikhi
Nezha El Bari
Source :
Sensors, Vol 20, Iss 23, p 6750 (2020)
Publication Year :
2020
Publisher :
MDPI AG, 2020.

Abstract

Essential oil resins of Aucoumea klaineana (Okoume) and Canarium schweinfurthii (Aiele) species, of the Burseraceae family, were studied to investigate their bioactive constituents and their antibacterial activities. Aiele resin had a higher yield (6.86%) of essential oil than Okoume (3.62%). Twenty-one compounds for Okoume and eighteen for Aiele essential oil were identified using a gas chromatography-mass spectrometry (Gp-C-MS) technique. The main compounds identified in Okoume essential oil were benzenemethanol, α, α,4-trimethyl (28.85%), (+)-3-carene (3,7,7-trimethyl bicyclo[4.1.0]hept-3-ene) (17.93%), D-Limonene ((4R)-1-methyl-4-prop-1-en-2-ylcyclohexene) (19.36%). With regard to the Aiele essential oil, we identified (1R,4S)-1-methyl-4-propan-2-ylcyclohex-2-en-1-ol (26.64%), and 1-methyl-4-propan-2-ylcyclohex-2-en-1-ol (26.83%). Two strains of bacteria, Escherichia coli and Staphylococcus aureus, were used in antibacterial tests. S. aureus was found to be more sensitive to Okoume and Aiele essential oils, with a high inhibition zone ranging from 20 to 16 mm. In comparison, the inhibition zone ranged from 6 to 12 mm for E. coli. An electronic nose (e-nose) combined with pattern analysis methods such as principal component analysis (PCA), discriminant function analysis (DFA), and hierarchical cluster analysis (HCA) were used to discriminate the essential oil samples. In summary, the e-nose and GC-MS allowed the identification of bioactive compounds in the essential oil samples, which have a strong antimicrobial activity, with satisfactory results.

Details

Language :
English
ISSN :
14248220
Volume :
20
Issue :
23
Database :
Directory of Open Access Journals
Journal :
Sensors
Publication Type :
Academic Journal
Accession number :
edsdoj.1139b30be57b4032b5b33b8aef2e206a
Document Type :
article
Full Text :
https://doi.org/10.3390/s20236750