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Identification of waste cooking oil and vegetable oil via Raman spectroscopy
Author(s) -
Huang Furong,
Li Yuanpeng,
Guo Huixian,
Xu Jie,
Chen Zhe,
Zhang Jun,
Wang Yong
Publication year - 2016
Publication title -
journal of raman spectroscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.748
H-Index - 110
eISSN - 1097-4555
pISSN - 0377-0486
DOI - 10.1002/jrs.4895
Subject(s) - cooking oil , raman spectroscopy , vegetable oil , partial least squares regression , peanut oil , waste oil , linear discriminant analysis , edible oil , chemistry , pulp and paper industry , identification (biology) , olive oil , environmental science , food science , mathematics , artificial intelligence , biodiesel , botany , computer science , engineering , organic chemistry , biology , physics , raw material , statistics , optics , catalysis
This paper made a qualitative identification of ordinary vegetable oil and waste cooking oil based on Raman spectroscopy. Raman spectra of 73 samples of four varieties oil were acquired through the portable Raman spectrometer. Then, a partial least squares discriminant analysis (PLS‐DA) model and a discrimination model based on characteristic wave band ratio were established. A classification variable model of olive oil, peanut oil, corn oil and waste cooking oil that was established through the PLS‐DA model could identify waste cooking oil accurately from vegetable oils. The identification model established based on selection of waveband characteristics and intensity ratio of different Raman spectrum characteristic peaks could distinguish vegetable oils from waste cooking oil accurately. Research results demonstrated that both ratio method and PLS‐DA could identify waste cooking oil samples accurately. The identification model based on characteristic waveband ratio is simpler than PLS‐DA model. It is widely applicable to identification of waste cooking oil. Copyright © 2016 John Wiley & Sons, Ltd.