• Journal of Food Hygiene and Safety
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• 제3권2호
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• pp.59-63
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• 1988

A technique of high-performance liquid chromatography (HPLC) was applied to tbe detection and estimation for composition of linseed oil, perilla oil and soybean oil in edible sesame oil. Tbe triglycerides were separated into five peaks in sesame 011, seven peaks in linseed oil, perilla oil and soybean oil by HPLC. From the resulls separated by HPLC on the basis of PN (partition number), tbese observations indicate tbat adullerants linseed oil, perilla oil and soybean oil in sesame oil for the ratio of minimum 4%, respectively can be detected. As a resull, it was suggested that tbe use of HPLC can provide more detailed Information concerning adulteration of sesame all.

• Journal of Food Hygiene and Safety
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• 제3권3호
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• pp.105-109
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• 1988

To develop a method for detecting and e&timating the quantity of adulterant rapeseed oil in sesame oil, five kinds of sesame oils and three kinds of rapeseed oils collected from different sources were fractionated by TLC (thin layer chromatography) and separated on the basis of PN (partition number) by HPLC (high performance liquid chromatography). These obsenations indicate that the proportion of adulterant rapeseed oil when mixed minimum 4% with sesame oil can be detected.

• Journal of Food Hygiene and Safety
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• 제6권1호
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• pp.57-66
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• 1991

In the present study, an attempt was made to use FV (Fatty acid ratio & Villavecchia reaction) value determination as a reliable method for the detection and analysis of the adulteration of sesame oils. FV value was defined as fatty acid ratio, C18 : I + C18 : 2/C16 : ${\times}C18$ : 3, times modified Villavecchia-Suarez test value. Seventy-four sesame oils collected from markets were evaluated using this method. Only II among 74 collected sesame oils were found to be pure sesame oil by FV value determination. In 63 adulterated sesame oils, it was revealed 23 samples were adulterated soybean oil, to with rice bran oil, 10 with sesame dregs extract oil, 8 with perilla seed oil, 7 with corn oil, 3 with cotton seed oil, and 2 with rape seed oil.

• Korean Journal of Food Science and Technology
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• 제25권4호
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• pp.345-350
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• 1993

Fatty acid composition of sesame oil could be distinguished from that of rapeseed oil and soybean oil by the content of linolenic acid. The relative composition of each fatty acid revealed the clear difference between sesame oil and other vegetable oils except corn oil. Ricebran oil was different from sesame oil in the relative composition of palmitic acid with respect to stearic acid and cottonseed oil in oleic acid to linoleic acid. ${\delta}^{13}C$ of corn oil was $19.40%_{\circ}$, in oleic acid and $-17.11%_{\circ}$, in linoleic acid, while that of sesame oil was $-27.60%_{\circ}$ in oleic acid and $-27.70%_{\circ}$ in linoleic acid. Therefore, most adulterant could be detected by comparing the ratio of fatty acids in vegetable oils except corn oil. It could, however, be detected by comparing carbon isotope ratio in the case of corn oil.

• Korean Journal of Agricultural Science
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• 제46권2호
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• pp.257-271
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• 2019

The use of food grade hexane (FGH) for edible oil extraction is responsible for the presence of benzene in the crude oil. Benzene is a Group 1 carcinogen and could pose a serious threat to the health of consumer. However, its detection still depends on classical methods using chromatography which requires a rapid non-destructive detection method. Hence, the aim of this study was to investigate the feasibility of using Fourier transform infrared (FTIR) spectroscopy combined with multivariate analysis to detect and quantify the benzene residue in edible oil (sesame and cottonseed oil). Oil samples were adulterated with varying quantities of benzene, and their FTIR spectra were acquired with an attenuated total reflectance (ATR) method. Optimal variables for a partial least-squares regression (PLSR) model were selected using the variable importance in projection (VIP) and the selectivity ratio (SR) methods. The developed PLS models with whole variables and the VIP- and SR-selected variables were validated against an independent data set which resulted in $R^2$ values of 0.95, 0.96, and 0.95 and standard error of prediction (SEP) values of 38.5, 33.7, and 41.7 mg/L, respectively. The proposed technique of FTIR combined with multivariate analysis and variable selection methods can detect benzene residuals in edible oils with the advantages of being fast and simple and thus, can replace the conventional methods used for the same purpose.