Identification of Bioactive Compounds in Ginger Based on Molecularly Imprinted Polymer Quartz Crystal Microbalance Gas Sensor

被引:8
|
作者
Hardoyono, Fajar [1 ]
Windhani, Kikin [2 ]
Sambodo, Herman [2 ]
Pudjianto, Hary [2 ]
机构
[1] Inst Agama Islam Negeri IAIN Purwokerto, Lab Phys, Jalan A Yani 40 A, Purwokerto 53171, Central Java, Indonesia
[2] Univ Jenderal Soedirman, Fac Econ & Business, Agro Econ Res Grp, Jalan HR Bunyamin 806, Purwokerto, Central Java, Indonesia
来源
9TH ANNUAL BASIC SCIENCE INTERNATIONAL CONFERENCE 2019 (BASIC 2019) | 2019年 / 546卷
关键词
quartz crystal microbalance; molecularly imprinted polymer; borneol; citral; geraniol; principal component analysis; linear discriminant analysis; ELECTRONIC NOSE; GC-MS; GERANIOL;
D O I
10.1088/1757-899X/546/3/032012
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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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页数:11
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