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adulteration detection of edible oils with castor oil by gas chromatography

Oil Crop Science 2016年第2期1卷 60-64页

作者： Wei HU Xuefang WANG Liangxiao ZHANG Peiwu LI Xiaoman SUN Jun JIANG Xiaoxia DING Qi ZHANG Oil Crops Research Institute Chinese Academy of Agricultural Sciences Wuhan 430062 P. R. China Key Laboratory of Biology and Genetic Improvement of Oil Crops Ministry of Agriculture Wuhan 430062 P. R. China Key Laboratory of detection for Mycotoxins Ministry of Agriculture Wuhan 430062 P. R. China Laboratory of Risk Assessment for Oilseeds Products ( Wuhan) Ministry of Agriculture Wuhan 430062 P. R. China Quality Inspection and Test Center for Oilseeds Products Ministry of Agriculture Wuhan 430062 P. R. China Hubei Collaborative Innovation Center for Green Transformation of Bio - Resources Wuhan 430062 P. R. China

Developing a method of adulteration detection is critical for protecting customers＂ rights which is a particular concern in food quality. In this study, fatty acid profiles of castor oils were estab-lished by GC and employed to classify 4 types of edible oils and castor oil with multivariate statistical methods. The results indicated that fatty acid profiles of edible oils could be used to classify the 5 kinds of oils. Meanwhile, simulated data test indicated that fatty acid profiles could be used to detect adultera-ted by 5% . Finally, a RF model was built to detect adulteration of edible oils with castor oils by fatty acid composition. The results from cross validation indicated that the oils adulterated by castor oil at low levels （5% 7V/V） could be completely separated from 4 kinds of edible oils. Therefore this model could be used to detect adulteration of 4 kinds of edible oil with castor oils.

关键词： fatty acid profiles adulteration detection castor oil GC chemometrics

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Identifying camellia oil adulteration with selected vegetable oils by characteristic near-infrared spectral regions

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Journal of Innovative Optical Health Sciences 2018年第2期11卷 78-89页

作者： Xuan Chu Wei Wang Chunyang Li Xin Zhao Hongzhe Jiang College of Engineering China Agricultural University Beijing 100083P.R.China Institute of Food Science and Technology Jiangsu Academy of Agricultural Sciences Nanjing 210014 P.R.China

In this paper,a methodology based on characteristic spectral bands of near infrared spectroscopy(1000-2500 nm)and multivariate analysis was proposed to identify camellia oil adulteration withvegetable oils,Sunflower,peanut and corn oils were selected to conduct the *** camlia oiland that adulterated with varying concentrations(1-10%with the gradient of 1%,10-40%withthe gradient of 5%,40-100%with the gradient of 10%)of each type of the three vegetable oilswere prepared,*** each type of adulterated oil,full-spectrum partial least squarespartial least squares(PLS)models and synergy interval partial least squares(SI-PLS)modelswere *** of these models were optimized simultaneously by cross-validation,The SI-PLS models were proved to be better than the full-spectrum PLS *** SI-PLSmodels,the correlation coefficients of predition set(Rp)were 0.9992,0.9998 and 0.9999 foradulteration with sunflower oil,peanut oiloil seperately;the corresponding root meansquare errors of prediction set(RMSEP).66nd ***,a new genericPLS model was built based on the chalselected from the intervals of thethree SI-PLS models to identify the oil adulterantsardless of the adultrated oil *** achieved with Rp=0.9988 and RMSEP==1.52,These results indicated that the charac-teristic near infrared spectral regions could determine the level of adulteration in the camllia oil.

关键词： Camllia oil adulteration detection characteristic near infrared spectral regions partial least squares synergy interval partial least squares

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