Development and optimization of an LC-MS/MS method for the detection of Magnolia officinalis extracts in cosmetics: insights from DFT-assisted sample preparation

Abstract

A sensitive LC-MS/MS method was developed for detecting Magnolia officinalis extracts, targeting magnolol, honokiol, magnoflorine and magnocurarine in complex cosmetic matrices, meeting the growing industry demand for reliable quality control solutions amidst the expanding applications of the extracts. Method optimization systematically addressed matrix effects and sample preparation, supported by density functional theory (DFT) calculations, which provided molecular-level insights into the analyte behavior. Validation confirmed a high extraction recovery of 90.7–106.2%, a low detection limit of 0.15 mg kg⁻¹, excellent linearity with R² ≥ 0.9994 over 0.5–10 mg kg⁻¹, and precise and accurate intra- and inter-day results with an RSD ≤ 4.15% and accuracies of 90.6–106.3%. This method demonstrated reliability for quality control through its application in spiked creams, aqueous solutions, masks, and oils, concurrently verifying label claims for functional phenolics regarding content and composition and screening for prohibited/restricted alkaloid-substances, demonstrating its dual utility in quality assurance and regulatory compliance.