Premium
Terahertz spectroscopy and chemometrics classification of transgenic corn oil from corn edible oil
Author(s) -
Liu Jianjun
Publication year - 2017
Publication title -
microwave and optical technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.304
H-Index - 76
eISSN - 1098-2760
pISSN - 0895-2477
DOI - 10.1002/mop.30362
Subject(s) - chemometrics , corn oil , partial least squares regression , terahertz radiation , terahertz spectroscopy and technology , spectroscopy , biological system , analytical chemistry (journal) , chemistry , microbiology and biotechnology , materials science , chromatography , computer science , food science , biology , machine learning , optoelectronics , physics , quantum mechanics
Terahertz spectroscopy coupled with chemometrics is illustrated to be a useful tool to identify the transgenic corn oil. Terahertz and physicochemical data are gather about transgenic and non‐transgenic corn oils. The two identification models of partial least squares discriminate analyses (PLS‐DA) are established and compared by using terahertz spectroscopy data and physicochemical data respectively. The result shows that PLS‐DA model with physicochemical data can not accurately distinguish between transgenic and non‐transgenic corn oils. Quite the contrary, the PLS‐DA model with terahertz spectroscopy data is better in the validation set; this model accurately identified transgenic corn oil with accuracy of 98.7%. The proposed method has advantages of fast, simple, nondestructive, and easy to operate. The results indicated that Terahertz spectroscopy coupled with chemometrics as a powerful tool to identify transgenic oil. © 2017 Wiley Periodicals, Inc. Microwave Opt Technol Lett 59:654–658, 2017