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《Chinese Journal of Analytical Chemistry》 2010-06
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Prediction of Main Chemical Compositions in Biodiesel by Near Infrared Spectroscopy

KONG Cui-Ping, CHU Xiao-Li, DU Ze-Xue, LU Wan-Zhen (Research Institute of Petroleum Processing, Beijing 100083)  
A rapid method was established for the determination of the main chemical compositions in biodiesel (including fatty acid methyl esters, monoglycerides, diglyceride, triglyceride and glycerol) by the combination of near infrared spectra (NIR) and chemometrics. The reference values were obtained by the gas chromatographic method, which was correlated with the NIR spectra data by partial least squares regression method. The calibration models for multi-feedstock biodiesel and a single feedstock biodiesel were established respectively. The applicability of the calibration models was examined with the zanthoxylum oil biodiesel as an example. The results showed that a universal calibration model suitable for various biodiesel from different sources can be established by partial least-squares method. For this biodiesel manufactured from other fatty oils, the same calibration model can be extended by adding 10 more new samples. The calibration model so obtained will provide more accurate results. The NIR method is suggested as a rapid method for the quality control in the process of biodiesel production.
【Fund】: 中石化科研资助项目(No.S108071)
【CateGory Index】: TE667
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