Comparative assessment of feature and component profiling workflow for supercritical fluid chromatography – high resolution mass spectrometry analysis

Supercritical fluid chromatography coupled to high-resolution mass spectrometry (SFCHRMS) is gaining attention for non-target screening (NTS), yet systematic evaluations of data-processing workflows remain scarce. Here, we present the first comprehensive comparison between a component-profile (CP) approach based on Region of Interest analysis combined with Component Detection Algorithm and Multivariate Curve Resolution (ROI-CODA-MCR) and a feature-profile (FP) workflow, MS-DIAL. Using extracted ion chromatograms (EICs) as ground truth, both workflows were optimized and benchmarked for standard detection, peak intensity reliability, blank filtering performance, and suspect screening for wastewater samples. Both detected a comparable number of standards (33-35 out of 37) but ROI-derived intensities closely matched EICs (average ratio ≈1, RSD = 5.8%), while MS-DIAL intensities deviated substantially (up to two orders of magnitude, RSD >200%). In non-target analysis, MS-DIAL produced ≈1000 features with many false positives, while ROI-CODA-MCR yielded ≈200 components with lower blank contributions and superior resolution of in-source fragments and adducts. MS-DIAL detected more suspect compounds, highlighting a higher risk of false negatives in the CP approach, particularly for low-intensity or sparse signals. Our results demonstrate that SFCHRMS datasets, often including intense background signals, challenge key assumptions underlying both FP and CP workflows and necessitate careful parameter optimization.