[Rapid discriminating hogwash oil and edible vegetable oil using near infrared optical fiber spectrometer technique].
In the present study, a new method using near infrared spectroscopy combined with optical fiber sensing technology was applied to the analysis of hogwash oil in blended oil. The 50 samples were a blend of frying oil and "nine three" soybean oil according to a certain volume ratio. The near infrared transmission spectroscopies were collected and the quantitative analysis model of frying oil was established by partial least squares (PLS) and BP artificial neural network The coefficients of determina- tion of calibration sets were 0.908 and 0.934 respectively. The coefficients of determination of validation sets were 0.961 and 0.952, the root mean square error of calibrations (RMSEC) was 0.184 and 0.136, and the root mean square error of predictions (RMSEP) was all 0.111 6. They conform to the model application requirement. At the same time, frying oil and qualified edible oil were identified with the principal component analysis (PCA), and the accurate rate was 100%. The experiment proved that near infrared spectral technology not only can quickly and accurately identify hogwash oil, but also can quantitatively detect hog- wash oil. This method has a wide application prospect in the detection of oil.
Bing-Fang
BF
Zhang
Li-Bo
LB
Yuan
Qing-Ming
QM
Kong
Wei-Zheng
WZ
Shen
Bing-Xiu
BX
Zhang
Cheng-Hai
CH
Liu
D002138:Calibration; D005506:Food Contamination; D016018:Least-Squares Analysis; D055100:Optical Fibers; D010938:Plant Oils / Q000032:analysis*; D025341:Principal Component Analysis; D013024:Soybean Oil / Q000032:analysis; D019265:Spectroscopy, Near-Infrared
D010938:Plant Oils; D013024:Soybean Oil