Comparison of Major Volatile Compounds in Three Varieties of Ginger Grown in Indonesia using Solid Phase Micro Extraction Gas Chromatography/Mass Spectroscopy Followed by Electronic Nose Based on Metal Oxide Semiconductor Gas Sensor

Solid Phase Micro Extraction-Gas Chromatography/Mass Spectroscopy (SPME-GC/MS) was employed to identify major compounds in three varieties of ginger grown in Indonesia, namely: small-white ginger (SWG), big-white ginger (BWG), and red ginger (RG). SWG was dominated by b-sesquiphellandrene and a-farn...

Full description

Bibliographic Details
Main Authors: Fajar HARDOYONO, Kikin WINDHANI
Format: Article
Language:English
Published: IFSA Publishing, S.L. 2019-02-01
Series:Sensors & Transducers
Subjects:
Online Access:https://sensorsportal.com/HTML/DIGEST/february_2019/Vol_230/P_3064.pdf
Description
Summary:Solid Phase Micro Extraction-Gas Chromatography/Mass Spectroscopy (SPME-GC/MS) was employed to identify major compounds in three varieties of ginger grown in Indonesia, namely: small-white ginger (SWG), big-white ginger (BWG), and red ginger (RG). SWG was dominated by b-sesquiphellandrene and a-farnesene. The major chemical compounds identified in BWG were dominated by: a- zingiberene, cedren-13-ol, 8-,b-bisabolene, and neral, while curcumene, neral, a-zingiberene, citral, and geraniol were most dominant in RG. Sensory analysis using electronic nose (e-nose) based on metal oxide semiconductor (MOS) gas sensor was also employed to measure the sensory response of these gingers. Principal component analysis (PCA) of feature e-nose response showed that the feature response of three gingers can be separated. The score plot in the PC1-PC2 coordinate of PCA obtained 89.30 % of variance at two principal components. PC1 contributed 58.30 % of the variance, while PC2 contributed 31.00 %. Furthermore, hierarchical cluster analysis (HCA) of feature response of three gingers indicated that the similarity level between BWG and RG is almost 36.12 %, due to the presence of a-zingiberene and neral, that was identified more than 10 % both in BWG and RG.
ISSN:2306-8515
1726-5479