High-throughput screening of 54 alternative plasticizers in sesame oil using gas chromatography-quadrupole time-of-flight mass spectrometry

Abstract

Restrictions on the use of phthalates have led to the wide use of alternative plasticizers (APs) such as organophosphate, adipate, citrate, and sebacate. However, because plasticizers combine with polymers in plastic products via unstable noncovalent bonds, they can easily migrate out of these products, causing environmental pollution. In particular, their migration out of food packaging, containers, and other food-contact materials and into food has raised great concerns. Toxicological studies have shown that APs contain potentially toxic substances that can affect endocrine functions and cause neurotoxicity, genotoxicity, and other adverse effects. Thus, their potential risks to food should not be underestimated. Sesame oil is a necessity in daily cooking. The results of risk monitoring in recent years have indicated that sesame oil often contains phthalates in excess of the standard limits. However, the potential risks of APs in sesame oil have not yet been reported. Some common detection methods for APs include gas chromatography-mass spectrometry, gas chromatography-triple quadrupole mass spectrometry, and liquid chromatography-triple quadrupole mass spectrometry. Unfortunately, these methods use low-resolution mass spectrometry and are limited by the resolution, scan rate, and analysis mode. Gas chromatography-quadrupole time-of-flight mass spectrometry (GC-Q-TOF/MS) has the advantages of high resolution, sensitivity, and analysis speed. In full-scan mode, GC-Q-TOF/MS can accurately collect the full-spectrum mass number of target compounds with low content levels in complex substrates, thereby realizing efficient screening and quantitative analysis. It shows outstanding advantages in the trace analysis of pesticide residues and pollutants. Furthermore, it features strong qualitative and high screening abilities. Establishment of a personal compound database and library (PCDL) addresses limitations in the number of compounds that can be measured and enables the rapid identification of targets without the use of standard products. In addition, increasing the number of targets for synchronous screening enables the retrospective analysis of new targets. In this study, a method based on GC-Q-TOF/MS was developed for the determination of 54 APs in sesame oil. The samples were extracted with acetonitrile and purified using a PSA/silica solid-phase extraction column. The mass-spectral information of the samples was then collected by GC-Q-TOF/MS in full-scan mode, and the 54 APs were searched using an established high-resolution mass-spectrum database to simultaneously achieve the broad-spectrum screening, qualitative identification, and quantitative analysis of multiple targets. The effects of different extraction solvents and purification methods on sample extraction and purification were compared. The accuracy of the screening results was improved by optimizing the GC-separation conditions, quality-extraction window, retention-time deviation, and other screening parameters. The screening detection limits (SDLs) of the 54 APs ranged from 0.01 to 0.02 mg/kg; specifically, the SDL of 41 compounds was 0.01 mg/kg and that of 13 compounds were 0.02 mg/kg. The limits of quantification were in the range of 0.02-0.04 mg/kg. A total of 80 sesame-oil samples were rapidly screened using this method under optimal conditions. Five APs were identified from the 80 sesame-oil samples and quantitatively analyzed using the matrix-matched external-standard method. The results of this quantitative methodology showed that the five APs had good linear relationships in the range of 0.01-0.2 mg/L, with all correlation coefficients greater than 0.99. The accuracy and precision of the method were verified using a standard recovery test with blank sesame-oil samples. Under the three standard levels of 0.04, 0.08, and 0.2 mg/kg, the recoveries of the five APs ranged from 71.3% to 97.8%, and the relative standard deviations (RSDs) ranged from 0.4% to 6.1%(n=6). The developed method is fast, accurate, sensitive, and has high throughput. Thus, it can realize the efficient screening, qualitative identification, and quantitative analysis of the 54 APs in sesame oil and provides a potential solution for the monitoring of other contaminants in food.