A modified data filtering strategy for targeted characterization of polymers in complex matrixes using drift tube ion mobility-mass spectrometry: Application to analysis of procyanidins in the grape seed extracts.

Abstract Backgrounds Polymers, widely existing in food or dietary materials, have been attracting researchers, facing challenges, and needing effective strategies on targeted characterization in complex matrixes. Methods A modified data filtering strategy (including locating with drift time and m/z ranges, multiple mass defect filtering, validating MS information, and evaluating MS/MS spectra) was developed and applied for procyanidins in the grape seed extracts (GSE) using drift tube ion mobility-mass spectrometry. The procyanidin ions’ trendlines were predicted by multi-model regression. Their collision cross-sections (CCSs) were calculated using single-field methods. Results and discussion Totally, 769 CCSs belonging to 686 procyanidins with polymer degrees at 1–15 were characterized. The exponent regression was the most reasonable model (r2 ≥ 0.9379) to reveal the trendlines. The change tendency of CCSs with their polymer degrees, charge states, and linkage types were investigated. Conclusion This study provided an innovative strategy for targeted characterization of polymers in complex matrixes.