Comprehensive adulteration detection of sesame oil based on characteristic markers.

Sesame oil has a unique flavor and is very popular in Asian countries, and this leads to frequent adulteration. In this study, comprehensive adulteration detection of sesame oil based on characteristic markers was developed. Initially, sixteen fatty acids, eight phytosterols, and four tocopherols were utilized to construct an adulteration detection model, which screened seven potentially adulterated samples. Subsequently, confirmatory conclusions were drawn based on the characteristic markers. Adulteration with rapeseed oil in 4 samples was confirmed using the characteristic marker of brassicasterol. The adulteration of soybean oil in 1 sample was confirmed using the isoflavone. The adulteration of 2 samples with cottonseed oil was demonstrated by sterculic acid and malvalic acid. The results showed that sesame oil adulteration could be detected by screening positive samples using chemometrics and verifying with characteristic markers. The comprehensive adulteration detection method could provide a system approach for market supervision of edible oils.

Establishment and evaluation of multiple adulteration detection of camellia oil by mixture design.

Multiple adulteration is a common trick to mask adulteration detection methods. In this study, the representative multiple adulterated camellia oils were prepared according to the mixture design. Then, these representative oils were employed to build two-class classification models and validate one-class classification model combined with fatty acid profiles. The cross-validation results indicated that the recursive SVM model possessed higher classification accuracy (97.9%) than PLS-DA. In OCPLS model, the optimal percentage of RO, SO, CO and SUO was 2.8%, 0%, 7.2%, 0% respectively in adulterated camellia oil, which is the most similar to the authentic camellia oils. Further validation showed that five adulterated oils with the optimal percentage could be correctly identified, indicating that the OCPLS model could identify multiple adulterated oils with these four cheaper oils. Moreover, this study serves as a reference for one class classification model evaluation and a solution for multiple adulteration detection of other foods.

Adulteration detection of essence in sesame oil based on headspace gas chromatography-ion mobility spectrometry.

Sesame oil is a traditional and delicious edible oil in China and Southeast Asia with a high price. However, sesame oil essence was often illegally added to cheaper edible oils to counterfeit sesame oil. In this study, a rapid and accurate headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) method was proposed to detect the counterfeit sesame oil where the other cheap oils were adulterated with essence. Combined with chemometric methods including principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA) and random forest (RF), authentic and counterfeit sesame oils adulterated with sesame essence (0.5%, w/w) were easily separated into two groups. More importantly, 2-methylbutanoic acid, 2-furfurylthiol, methylpyrazine, methional, and 2,5-dimethylpyrazine were found to be markers of sesame essence, which were used to directly identify the sesame essence. The determination of volatile compounds based on HS-GC-IMS was proven to be an effective method for adulteration detection of essence in sesame oil.

Multispecies Adulteration Detection of Camellia Oil by Chemical Markers.

Adulteration of edible oils has attracted attention from more researchers and consumers in recent years. Complex multispecies adulteration is a commonly used strategy to mask the traditional adulteration detection methods. Most of the researchers were only concerned about single targeted adulterants, however, it was difficult to identify complex multispecies adulteration or untargeted adulterants. To detect adulteration of edible oil, identification of characteristic markers of adulterants was proposed to be an effective method, which could provide a solution for multispecies adulteration detection. In this study, a simple method of multispecies adulteration detection for camellia oil (adulterated with soybean oil, peanut oil, rapeseed oil) was developed by quantifying chemical markers including four isoflavones, trans-resveratrol and sinapic acid, which used liquid chromatography tandem mass spectrometry (LC-MS/MS) combined with solid phase extraction (SPE). In commercial camellia oil, only two of them were detected of daidzin with the average content of 0.06 ng/g while other markers were absent. The developed method was highly sensitive as the limits of detection (LODs) ranged from 0.02 ng/mL to 0.16 ng/mL and the mean recoveries ranged from 79.7% to 113.5%, indicating that this method was reliable to detect potential characteristic markers in edible oils. Six target compounds for pure camellia oils, soybean oils, peanut oils and rapeseed oils had been analyzed to get the results. The validation results indicated that this simple and rapid method was successfully employed to determine multispecies adulteration of camellia oil adulterated with soybean, peanut and rapeseed oils.