Rapid extraction and detection of ellagic acid in plant samples using a selective magnetic molecularly imprinted polymer coupled to a fluorescence method

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URI: http://hdl.handle.net/10498/29446
DOI: 10.1016/j.greeac.2023.100058
ISSN: 2772-5774
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2023-05-05Department
Química AnalíticaSource
Green Analytical Chemistry. Vol. 5, June 2023, 100058Abstract
A remarkable growth was noticed in the development of molecularly imprinted polymers (MIPs), which have used as efficient synthetic antibodies that contain selective cavities to the target molecule. Hereunder, a novel strategy using MIP as a sorbent in solid-phase extraction was coupled to a fluorescence method for ellagic acid (EA) purification and immediate detection. The synthesis of magnetic-MIP (MMIP) using a rapid and green ultrasound technology was assessed by central composite design to determine the optimal polymerization conditions for a high-imprinting polymer. The MMIP was characterized by Fourier transform infrared spectroscopy, X-ray diffraction, thermogravimetric analysis, and scanning/transmission electron microscopy, which accurately confirmed the functional, magnetic, and morphological features of MMIP. The prepared MMIP was demonstrated to be selective for EA compared to many similar phenols. The spectrofluorometric method showed a linear range from 0.05 to 2 μg·mL−1 of EA, and the limits of detection (LOD) and quantification (LOQ) were 0.005 and 0.02 μg·mL−1, respectively. Besides, the novel proposed smartphone method using the ultraviolet lamp as the excitation source presented a linear range from 0.2 to 4 μg·mL−1, a LOQ of 0.2 μg·mL−1, and a LOD of 0.07 μg.mL−1. The proposed strategy revealed high efficiency in the extraction and detection of EA in grape, redberry, and green tea. Effectively, the calculated recoveries were ranging from 80 to 102% with low values of relative standard deviation ([removed]
Subjects
Magnetic molecularly imprinted polymer; Ellagic acid; Central composite design; Solid-phase extraction; Fluorescence detection; Smartphone detectionCollections
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