In Situ Rapid Analysis of Squalene, Tocopherols, and Sterols in Walnut Oils Based on Supercritical Fluid Chromatography-Quadrupole Time-of-Flight Mass Spectrometry.

Quantification of liposoluble micronutrients in large-scale vegetable oil samples is urgently needed, because their health benefits are increasingly emphasized. However, current analytical methods are limited to either labor-intensive preparation processes or time-consuming chromatography separation. In this work, an online oil matrix separation strategy for direct, rapid, and simultaneous determination of squalene, tocopherols, and phytosterols in walnut oil (WO) was developed on the basis of the lipid class separation mode of supercritical fluid chromatography. A single run was completed in 13 min containing 6 min of column cleaning and balancing. Satisfactory limit of detections (0.05-0.20 ng/mL), limit of quantifications (0.15-0.45 ng/mL), recoveries (70.61-101.44%), and matrix effects (78.43-91.62%) were achieved, indicating the reliability of this method. In addition, eight sterol esters were identified in WO, which have not previously been reported. The proposed method was applied to characterize the liposoluble micronutrient profile of WO samples obtained from different walnut cultivars, geographical origins, and processes.

Detection of walnut oil adulterated with high-linoleic acid vegetable oils using triacylglycerol pseudotargeted method based on SFC-QTOF-MS.

Authentication of walnut oil (WO) is challenging due to the adulteration of high-linoleic acid vegetable oils (HLOs) with similar fatty acid composition. To allow the discrimination of WO adulteration, a rapid, sensitive and stable scanning method based on supercritical fluid chromatography quadrupole time-of-flight mass spectrometry (SFC-QTOF-MS) was established to profile 59 potential triacylglycerol (TAGs) in HLOs samples within 10 min. Limit of quantitation of the proposed method is 0.002 µg mL-1 and the relative standard deviations range from 0.7% to 12.0%. TAGs profiles of WO samples from various varieties, geography origins, ripeness, and processing methods were used to construct orthogonal partial least squares-discriminant analysis (OPLS-DA) and OPLS models that were highly accurate in both qualitative and quantitative prediction at adulteration levels as low as 5% (w/w). This study advances the TAGs analysis to characterize vegetable oils and holds promise as an efficient method for oil authentication.