Qualitative-Quantitative Analysis of Rice Bran Oil Adulteration Based on Laser Near Infrared Spectroscopy
TU Bin1, SONG Zhi-qiang1, ZHENG Xiao1*, ZENG Lu-lu1, YIN Cheng1, HE Dong-ping2, QI Pei-shi3
1. School of Mechanical Engineering, Wuhan Polytechnic University, Wuhan 430023, China 2. College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China 3. Pashun Group, Wuhan 430023, China
Abstract：The purpose of this study is mainly to have qualitative-quantitative analysis on the adulteration in rice bran oil by near-infrared spectroscopy analytical technology combined with chemo metrics methods. The author configured 189 adulterated oil samples according to the different mass ratios by selecting rice bran oil as base oil and choosing soybean oil, corn oil, colza oil, and waste oil of catering industry as adulterated oil. Then, the spectral data of samples was collected by using near-infrared spectrometer, and it was pre-processed through the following methods, including without processing, Multiplicative Scatter Correction(MSC), Orthogonal Signal Correction(OSC), Standard Normal Variate and Standard Normal Variate transformation De-Trending(SNV_DT). Furthermore, this article extracted characteristic wavelengths of the spectral datum from the pre-processed date by Successive Projections Algorithm(SPA), established qualitatively classified calibration methods of adulterated oil through classification method of Support Vector Machine(SVM), optimized model parameters(C, g) by Mesh Search Algorithm and determined the optimal process condition. In extracting characteristic wavelengths of the spectral datum from pretreatment by Backward interval Partial Least Squares(BiPLS) and SPA, quantitatively classified calibration models of adulterated oil through Partial Least Squares(PLS) and Support Vector Machine Regression(SVR) was established respectively. In the end, the author optimized the combination of model parameters(C, g) by Mesh Search Algorithm and determined the optimal parameter model. According to the analysis, the accuracy of prediction set and calibration set for SVC model reached 95% and 100% respectively. Compared with the prediction of the adulteration oil content of rice bran oil which was established by the PLS model, the SVR model is the better one, although both of them could implement the content prediction. Furthermore, the correlation coefficient R is above 0.99 and the Root Mean Square Error (MSE) is below 5.55×10-4. The results show that the near-infrared spectroscopy technology is effective in qualitative-quantitative analysis on the adulteration of rice bran oil. And the method is applicable to analyze adulteration in other oils.
