作者
Taciana G.S. Guimarães,Floriatan Santos Costa,Iohanna M.N.R. Menezes,Ana P.R. Santana,Daniel Fernandes Andrade,Andrea Oliveira,Clarice D.B. Amaral,Mário H. Gonzalez
摘要
In this work, an innovative ultrasound-assisted matrix solid-phase dispersion (UA-MSPD) method and microwave-assisted extraction (MAE) were applied with amino acids-based deep eutectic solvents (AADES) for the extraction of arsenic (As) from medicinal herbs. Multivariate optimization by Doehlert design (DD) was performed to determine the optimal experimental conditions. The effects of temperature (TP), time (TM), and sample-solvent ratio (SSR) were evaluated, and the optimized conditions were 50 °C, 60 min, and 10:1 mg mL−1 for UA-MSPD and 100 °C, 40 min, and 40:1 mg mL−1 for MAE, employing AADES 2 (β-alanine, citric acid, and water), where the hydroxyl and carboxyl groups of the citric acid structure favored formation of a chelate complex with the analyte. AADES 3 (β-alanine, xylitol, and water) was effective for MAE, while AADES 1 (β-alanine, malic acid, and water) proved to be inefficient for As extraction. The parameters of the analytical methods were evaluated using certified reference materials. The accuracy, based on percentage recovery, was in the range 77–101 %, while the limits of detection and quantification were in the ranges 0.010–0.039 mg kg−1 and 0.011–0.130 mg kg−1, respectively. The analytical curves presented R2 > 0.99. The proposed methods were shown to be environmentally friendly, based on the Analytical Eco-Scale and RGB 12 procedures. Both optimized methods were applied for the determination of As in commercial medicinal herbs (0.059–0.101 mg kg−1), with the values obtained being within the maximum daily intake limit established by the World Health Organization (WHO). It should be noted that there are no previous reports in the literature concerning the application of a sample preparation method using AADES, employing their solid precursors, with no requirement for prior solvent synthesis, as proposed here in the case of the UA-MSPD method.