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Profiling Volatile Compounds in Blackcurrant Fruit using Headspace Solid-Phase Microextraction Coupled to Gas Chromatography-Mass Spectrometry
Published on: June 9, 2021
Characterization of Volatile Profiles of Six Popular Edible Mushrooms Using Headspace-Solid-Phase Microextraction
Mun Yhung Jung1, Da Eun Lee1, Hong Yu Cheng1
1Dept. of Food Science and Biotechnology, Graduate School, Woosuk Univ., Samnye-ro 443, Samnye-eup, Wanju-gun, Jeonbuk Province, 55338, Republic of Korea.
Abstract:
The classification of six mushroom species (white beech, brown beech, button, oyster, king oyster, and enoki mushrooms) was successfully achieved using canonical discriminant analysis (CDA) on volatile metabolite data sets obtained by headspace-solid-phase microextraction gas chromatography (HS-SPME-GC). Twenty-seven major volatile compounds in six edible mushrooms were positively identified by HS-SPME-GC mass spectroscopy. The total volatile content was highest in brown beech mushroom (P < 0.05). Significant difference in volatile profile was observed between brown beach and white beech mushrooms. Button mushroom contained significantly higher contents of benzaldehyde and benzyl alcohol than the other mushrooms (P < 0.05). Oyster mushroom contained 1-octen-3-ol as the most prevalent volatile, representing 67% out of total volatiles. Hexanal (35.0%) and 1-octen-3-ol (22.5%) were the most abundant volatiles found in king oyster. Hexanal (29.1%) was the most prevalent volatile in enoki mushroom only. Several volatile pairs with very high positive correlation in their levels were identified, representing the highest correlation coefficient (r = 0.970) for the pair of t-2-octenal and 2,4-octandienal. CDA was much more efficient than principal component analysis for the differentiation of mushroom species. PRACTICAL APPLICATION: The present study provided the important information on the volatile metabolite profiles of popular six commercial mushroom species. The present data will be useful for the quality control of mushrooms cultivated in farms and mushroom products processed in food industry. The strategy of canonical discriminant analysis in combination with HS-SPME-GC could be expanded for the determining the authentication of mushroom species.
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