Liangxiao Zhang

Classification and Adulteration Detection of Vegetable Oils Based on Fatty Acid Profiles

The detection of adulteration of high priced oils is a particular concern in food quality and safety. Therefore, it is necessary to develop authenticity detection method for protecting the health of customers. In this study, fatty acid profiles of five edible oils were established by gas chromatography coupled with mass spectrometry (GC/MS) in selected ion monitoring mode. Using mass spectral characteristics of selected ions and equivalent chain length (ECL), 28 fatty acids were identified and employed to classify five kinds of edible oils by using unsupervised (principal component analysis and hierarchical clustering analysis), supervised (random forests) multivariate statistical methods. The results indicated that fatty acid profiles of these edible oils could classify five kinds of edible vegetable oils into five groups and are therefore employed to authenticity assessment. Moreover, adulterated oils were simulated by Monte Carlo method to establish simultaneous adulteration detection model for five kinds of edible oils by random forests. As a result, this model could identify five kinds of edible oils and sensitively detect adulteration of edible oil with other vegetable oils about the level of 10%.

Simultaneous determination of phenolic compounds in sesame oil using LC-MS/MS combined with magnetic carboxylated multi-walled carbon nanotubes.

A novel magnetic carboxylated multi-walled carbon nanotubes (c-MWCNT-MNPs) was proposed for magnetic solid-phase extraction coupled with liquid chromatography-tandem mass spectrometry to determine phenolic compounds in sesame oil. In this study, c-MWCNT-MNPs were acquired by simply dispersing Fe3O4 magnetic nanoparticles into carboxylated multi-walled carbon nanotubes. The major parameters affecting extraction efficiency were optimized, including the type and volume of desorption solvents, extraction and desorption time, washing solution, and sorbent amount. The limit of quantifications and limit of detections were from 0.03μg/kg to 43.00μg/kg and from 0.01μg/kg to 13.60μg/kg, respectively. The recoveries of phenolic compounds in vegetable oils were in the range of 83.8-125.9% with inter-day and intra-day precisions of less than 13.2%. It was confirmed that this method was simple, rapid and reliable with an excellent potential for routine analysis of phenolic compounds in oil samples.

Characterization of volatile components in four vegetable oils by headspace two-dimensional comprehensive chromatography time-of-flight mass spectrometry

Edible oil adulteration is the biggest source of food fraud all over the world. Since characteristic aroma is an important quality criterion for edible oils, we analyzed volatile organic compounds (VOCs) in four edible vegetable oils (soybean, peanut, rapeseed, and sunflower seed oils) by headspace comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (Headspace-GC×GC-TOFMS) in this study. After qualitative and quantitative analysis of VOCs, we used unsupervised (PCA) and supervised (Random forests) multivariate statistical methods to build a classification model for the four edible oils. The results indicated that the four edible oils had their own characteristic VOCs, which could be used as markers to completely classify these four edible oils into four groups.

Ion mobility spectrometry fingerprints: A rapid detection technology for adulteration of sesame oil

A simple and rapid detection technology was proposed based on ion mobility spectrometry (IMS) fingerprints to determine potential adulteration of sesame oil. Oil samples were diluted by n-hexane and analyzed by IMS for 20s. Then, chemometric methods were employed to establish discriminant models for sesame oils and four other edible oils, pure and adulterated sesame oils, and pure and counterfeit sesame oils, respectively. Finally, Random Forests (RF) classification model could correctly classify all five types of edible oils. The detection results indicated that the discriminant models built by recursive support vector machine (R-SVM) method could identify adulterated sesame oil samples (⩾ 10%) with an accuracy value of 94.2%. Therefore, IMS was shown to be an effective method to detect the adulterated sesame oils. Meanwhile, IMS fingerprints work well to detect the counterfeit sesame oils produced by adding sesame oil essence into cheaper edible oils.

Simultaneous determination of isoflavones and resveratrols for adulteration detection of soybean and peanut oils by mixed-mode SPE LC-MS/MS.

To ensure authenticity of vegetable oils, isoflavones (genistein, genistin, daidzein and daidzin) and resveratrols (cis-resveratrol and trans-resveratrol) were selected as the putative markers for adulteration of soybean and peanut oils. Firstly, mixed mode solid-phase extraction coupled with liquid chromatography tandem mass spectrometry (mixed-mode SPE LC-MS/MS) method was developed to analyze isoflavones and resveratrols in vegetable oils. The concentration of marker compounds in vegetable oils were 0.08-1.47mgkg(-1) for daidzein, ND-78.9μgkg(-1) for daidzin, 0.40-5.89mgkg(-1) for genistein, 1.2-114.9μgkg(-1) for genistin, 3.1-85.0μgkg(-1) for trans-resveratrol and 1.9-51.0μgkg(-1) for cis-resveratrol, which are compatible with the raw materials for oil press. Additionally, the applicability of this method has been successfully tested in thirteen vegetable oils from the market. Mixed-mode SPE LC-MS/MS method can simultaneously detect isoflavones and resveratrols in vegetable oils and assess adulteration and quality of soybean and peanut oils.

A Structure Identification and Toxicity Assessment of the Degradation Products of Aflatoxin B1 in Peanut Oil under UV Irradiation

Aflatoxins, a group of extremely hazardous compounds because of their genotoxicity and carcinogenicity to human and animals, are commonly found in many tropical and subtropical regions. Ultraviolet (UV) irradiation is proven to be an effective method to reduce or detoxify aflatoxins. However, the degradation products of aflatoxins under UV irradiation and their safety or toxicity have not been clear in practical production such as edible oil industry. In this study, the degradation products of aflatoxin B1 (AFB1) in peanut oil were analyzed by Ultra Performance Liquid Chromatograph-Thermo Quadrupole Exactive Focus mass spectrometry/mass spectrometry (UPLC-TQEF-MS/MS). The high-resolution mass spectra reflected that two main products were formed after the modification of a double bond in the terminal furan ring and the fracture of the lactone ring, while the small molecules especially nitrogen-containing compound may have participated in the photochemical reaction. According to the above results, the possible photodegradation pathway of AFB1 in peanut oil is proposed. Moreover, the human embryo hepatocytes viability assay indicated that the cell toxicity of degradation products after UV irradiation was much lower than that of AFB1, which could be attributed to the breakage of toxicological sites. These findings can provide new information for metabolic pathways and the hazard assessment of AFB1 using UV detoxification.

Untargeted fatty acid profiles based on the selected ion monitoring mode.

Fatty acids are potential biomarkers of some diseases and also key markers and quality parameters of different dietary fats and related products. Thus, untargeted fatty acid profiles are important in the study of dietary fat quality and fat-related diseases, as well as in other fields such as bioenergy. In addition, accurate identification of unknown components is a technological breakthrough for the selected ion monitoring (SIM) mode for untargeted profiles. In this study, we developed untargeted fatty acid profiles based on SIM. We also investigated mass spectral characteristics and equivalent chain lengths (ECL) to eliminate the influence of non-FAMEs for identifying fatty acids in samples. As an application example, fatty acid profiles were used to classify three edible vegetable oils. The results indicated that SIM-based untargeted fatty acid profiles could yield accurate qualitative and quantitative results for more fatty acids and benefit related studies of metabolite profiles.

Quantitative determination of major capsaicinoids in serum by ELISA and time-resolved fluorescent immunoassay based on monoclonal antibodies

To monitor capsaicinoids in serum on-site, three new monoclonal antibodies (mAbs) were firstly proposed using a conjugate of 4-[(4-hydroxy-3-methoxybenzyl) amino]-4-oxobutanoic acid as the immunogen. Among them, the YQQD8 mAb showed the highest sensitivity and cross-reactivity to major capsaicinoids, such as capsaicin, dihydrocapsaicin and N-vanillylnonanamide. A competitive indirect enzyme-linked immunosorbent assay (icELISA) and a time-resolved fluorescent immunochromatographic assay (TRFICA) were established based on this mAb. The linear range was 1.1-27.0ngmL(-1) for icELISA and 1.9-62.5ngmL(-1) for TRFICA and the limit of detection (LOD) of TRFICA was 1.5ngmL(-1). To decrease the interference of sample components and increase accuracy, serum samples were diluted four times before assays. As a result, the linear range of serum samples was 4.6-107.9ngmL(-1) for icELISA and 7.6-250.0ngmL(-1) for TRFICA. Both icELISA and TRFICA showed good recoveries (91.0-112.8% for icELISA and 87.6-111.5% for TRFICA) and concordant results in spiked experiments. Overall, this is the first report of immunoassay based on the mAbs for quantitative determination of major capsaicinoids, and the results demonstrate that both methods can meet the demands of rapid on-site assay for capsaicinoids in serum samples.

Rapid adulteration detection for flaxseed oil using ion mobility spectrometry and chemometric methods

To prevent the potential adulteration of flaxseed oil with high amounts of nutritional components, a simple and rapid adulteration detection method was proposed based on ion mobility spectrometry (IMS). After dilution in n-hexane, the edible oil sample was analyzed by IMS for 20 s. Subsequently, the multivariate statistical methods, including principal component analysis (PCA) and recursive support vector machine (R-SVM), were employed to establish a discriminant model for authentic and adulterated flaxseed oils. The cross validation results indicated that the R-SVM model could identify adulterated flaxseed oil samples (≥5%) with a high accuracy of 93.1%. Therefore, IMS could be used as an important tool to protect customers from adulterated flaxseed oil.

Rapid determination of trans-resveratrol in vegetable oils using magnetic hydrophilic multi-walled carbon nanotubes as adsorbents followed by liquid chromatography-tandem mass spectrometry.

In the present work, a rapid and simple procedure was developed and validated for the analysis of trans-resveratrol in vegetable oils based on magnetic hydrophilic multi-walled carbon nanotubes (h-MWCNT-MNPs) combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS). h-MWCNT-MNPs were simply obtained by wrapping amine-functionalized Fe3O4 magnetic nanoparticles into previously oxidized hydrophilic multi-walled carbon nanotubes. The major parameters affecting extraction efficiency were investigated, including the type and volume of desorption solvents, extraction and desorption time, washing solution, and sorbent amount. The limit of detection (LOD) and the limit of quantification (LOQ) were calculated as 0.6 and 2.0 μg/kg, respectively. The recoveries of trans-resveratrol in oil samples were in the range of 90.0-110.0% with RSDs of less than 17.5%. The results showed that only peanut oil contained trans-resveratrol, ranging from 8 ± 1 to 103 ± 12 μg/kg. The proposed method is reliable and robust, having an excellent potential for the analysis of trans-resveratrol in edible oils.