Work

Development of a QuEChERS-based method for the determination of quaternary ammonium compounds in different food matrices by LC-MS/MS

Year: 2024
Type: article
Abstract: A QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) - based method was developed and validated for the determination of six benzalkonium chloride (BAC) homologues (C8-C18) and four didecyldimethylammonium chloride (DDAC) homologues (C8-C14) in various food commodities. Quaternary ammonium compounds (QACs) are cationic surfactants and biocides commonly found in cleaning and disinfecting products widely used in industrial applications, households, agriculture, hospitals, and healthcare facilities and their usage has increased since the COVID-19 pandemic. The method was validated in terms of specificity, selectivity, linearity, limit of quantification (LOQ), accuracy (recovery percentage), precision (CV %) and matrix effect (ME %). %). Intraday and interday precision were evaluated at two levels. Mean recoveries for all matrices fell within 70–120 %, with CV% below 20 %. All calibration curves demonstrated excellent linearity (R² ≥ 0.998). The LOQ was set and verified at 0.01 mg/kg for each analyte. The results were satisfactory according to the SANTE/2021/11312 guidelines. In addition, the method included the elimination of water at each stage of sample preparation and throughout the chromatographic system to minimize background noise. The method was successfully applied to analyse 46 samples of animal origin. BAC C14 was the most frequently detected compound (76 % of the samples) and in two samples, the sum of BACs was above the MRL set by EU the Regulation. These findings, coupled with limited data on QAC levels in meat and seafood products, underscore the necessity for further investigation into these matrices. • The excessive use of QACs during the Covid 19 pandemic raised human health concerns. • It is important to monitor QACs due to their persistence in food contact surfaces. • Development of a Quechers-based method for routine analysis of QACs in food.
Language: English
Subfield: Food Science
Open Access status: hybrid
Estimated APC paid: $3,190
OpenAlex ID: W4402567659
FWCI: 1.167
Cites: 22
Cited by: 6
Related to: 10