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Identification of Bioactive Compounds in Ginger Based on Molecularly Imprinted Polymer Quartz Crystal Microbalance Gas Sensor
Author(s) -
Fajar Hardoyono,
Kikin Windhani,
Herman Sambodo,
Hary Pudjianto
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/546/3/032012
Subject(s) - borneol , quartz crystal microbalance , chromatography , molecularly imprinted polymer , chemistry , citral , molecular imprinting , essential oil , materials science , analytical chemistry (journal) , adsorption , organic chemistry , medicine , alternative medicine , pathology , traditional chinese medicine , selectivity , catalysis
Borneol, citral, and geraniol have been investigated as the major bioactive compound commonly found in ginger. In this work, a molecularly imprinted polymer (MIP) coated quartz crystal microbalance (QCM) sensor array has been employed for selective recognition of bioactive compounds in the ginger essential oil. In the experiment, the concentration of these bioactive compounds previously was measured using solid phase micro extraction gas chromatography-mass spectroscopy (SPME-GC/MS). Design of MIPs as the template of target molecules was created using polyacrylic acid (PAA) polymer matrix and three molecular targets (borneol, citral, and geraniol). An array of QCM sensor was prepared using four 9-Mhz AT-cut quartz crystal embedded between vacuum-deposited Au electrodes. For data recording, the headspace system flew the odorant of three varieties of ginger essential oil as positive control odorant and wild ginger essential oil as negative control odorant into the QCM sensor chamber. Then, mass loading in the MIP films caused frequency change of QCM sensor array due to odorant adsorption in a thin layer of MIP. Principal component analysis (PCA) and linear discriminant analysis (LDA) were applied to analyse the QCM response sensor. PCA score plot showed segregation of feature response of ginger essential oil with and without the molecular target in the coordinate of principal components. Meanwhile, LDA was able to discriminate training datasets of 80 ginger samples containing borneol, citral, and borneol with accuracy more than 92.50%.

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