Effect of food matrices on AFB1 recovery by lateral flow immunoassay with deep eutectic solvents as a green alternative to conventional extraction
摘要
D ifferent samples may cause various types of matrix interference in lateral flow immunoassay (LFA), while deep eutectic solvents (DESs) as emerging green solvents can be synthesized to adapt to different extraction processes by adjusting the composition of hydrogen bond donors (HBDs) and hydrogen bond acceptors (HBAs). Initially, 30 types of food samples were selected to explore the total dilution factors (tDFs) and limit of detection (LODs) on AFB1 detection by acetonitrile/water extraction. The matrix effect may be induced by some food matrices with high-fat content, including pumpkin seed kernel, almond, pecan, black sesame seed, walnut, and pine nut (tDFs exceeding 70-fold). DES-5 composed of Bet and EG with a molar ratio of 1:3, and a water content of 5% was selected as the optimal extraction solvent, which possessed a strong binding energy with AFB1 (− 147.35 kJ/mol) but weak interaction with four main fatty acids (− 67.28 kJ/mol to − 74.20 kJ/mol). The DES-based LFA demonstrated that the LODs of pumpkin seed kernel, almond, pecan, black sesame seed, walnut, and pine nut were 0.74 μg/kg, 1.18 μg/kg, 1.01 μg/kg. 0.68 μg/kg, 0.98 μg/kg, and 1.21 μg/kg with recoveries of 79.39% ~ 94.21%, which was about 50% lower than that by acetonitrile/water extraction. According to the results of Soxhlet extraction, 73.46% ~ 85.91% of the total fat content of six food samples with high-fat content was transferred to the upper layer, and the fat content of detection phases (1.16 ~ 3.71 mg/g) by DES extraction (2 mL) was much lower than that of detection phases (4.76 ~ 6.35 mg/g) by acetonitrile/water extraction (2 mL). These results demonstrate that DESs as promising green extraction solvents can weaken the fat-induced matrix effect to achieve accurate detection of AFB1, which may provide a new strategy for reducing the interference of other compounds in the use of LFA.
Graphical abstract