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.

Mass spectrometry in food authentication and origin traceability.

Food authentication and origin traceability are popular research topics, especially as concerns about food quality continue to increase. Mass spectrometry (MS) plays an indispensable role in food authentication and origin traceability. In this review, the applications of MS in food authentication and origin traceability by analyzing the main components and chemical fingerprints or profiles are summarized. In addition, the characteristic markers for food authentication are also reviewed, and the advantages and disadvantages of MS-based techniques for food authentication, as well as the current trends and challenges, are discussed. The fingerprinting and profiling methods, in combination with multivariate statistical analysis, are more suitable for the authentication of high-value foods, while characteristic marker-based methods are more suitable for adulteration detection. Several new techniques have been introduced to the field, such as proton transfer reaction mass spectrometry, ambient ionization mass spectrometry (AIMS), and ion mobility mass spectrometry, for the determination of food adulteration due to their fast and convenient analysis. As an important trend, the miniaturization of MS offers advantages, such as small and portable instrumentation and fast and nondestructive analysis. Moreover, many applications in food authentication are using AIMS, which can help food authentication in food inspection/field analysis. This review provides a reference and guide for food authentication and traceability based on MS.

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.

Identification and Validation of Metabolic Markers for Adulteration Detection of Edible Oils Using Metabolic Networks.

Food adulteration is a challenge faced by consumers and researchers. Due to DNA fragmentation during oil processing, it is necessary to discover metabolic markers alternative to DNA for adulteration detection of edible oils. However, the contents of metabolic markers vary in response to various factors, such as plant species, varieties, geographical origin, climate, and cultivation measures. Thus, it is difficult to identify a universal marker for all adulterants that may be present in some authentic samples. Currently, the specificity and selectivity of metabolic biomarkers are difficult to validate. Therefore, this study developed a screening strategy based on plant metabolic networks by developing a targeted analytical method for 56 metabolites in a metabolic network, using liquid/liquid extraction-liquid chromatography-tandem mass spectrometry (LC-MS/MS). We identified a chain of 11 metabolites that were related to isoflavonoid biosynthesis, which were detected in soybean oils but not rapeseed oils. Through multiple-marker mutual validation, these metabolites can be used as species-specific universal markers to differentiate soybean oil from rapeseed oil. Moreover, this method provides a model for screening characteristic markers of other edible vegetable oils and foods.

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.