2024 : 11 : 24
Mohammad Reza Hadjmohammadi

Mohammad Reza Hadjmohammadi

Academic rank: Professor
ORCID:
Education: PhD.
ScopusId:
HIndex:
Faculty: Faculty of Chemistry
Address: Babolsar
Phone: 01135302350

Research

Title
Amino acids- based hydrophobic natural deep eutectic solvents as a green acceptor phase in two-phase hollow fiber-liquid microextraction for the determination of caffeic acid in coffee, green tea, and tomato samples
Type
JournalPaper
Keywords
Caffeic acid Deep eutectic solvent Amino acid Hallow fiber Food samples
Year
2021
Journal MICROCHEMICAL JOURNAL
DOI
Researchers Negar Nooraee Nia ، Mohammad Reza Hadjmohammadi

Abstract

In this research, a series of new hydrophobic natural deep eutectic solvents (NADESs) were prepared and utilized as an acceptor phase in two-phase hollow fiber-liquid microextraction (HF-LPME) for the extraction and determination of caffeic acid in coffee, green tea, and tomato samples. The extraction solvent was prepared by mixing amino acids (as hydrogen bond acceptor) and lactic acid (as hydrogen bond donor). The highly stable NADESs (serine: lactic acid) were impregnated in the supported liquid membrane (SLM) and lumen of the hollow fiber. The amino acid-based deep eutectic solvent is a new generation of the extraction solvents for the HF-LPME method which is benefited from cost-effectiveness and lower toxicity. Physical properties of these NADESs, including their melting point, density, and viscosity were also determined. The extracted analyte was analyzed by high-performance liquid chromatography-ultraviolet detection (HPLC-UV). Response surface methodology (RSM) and central composite design (CCD) were applied to optimize the influence of the main extraction parameters. Under the optimal conditions, the proposed method exhibited a wide linear range of 1.0–500.0 ng mL􀀀 1 (R2 = 0.984) with satisfactory recoveries above 92.0%. The limit of detection (LOD) and Limit of quantification (LOQ) were of 0.3 ng mL􀀀 1 and 0.9 ng mL􀀀 1, respectively. The enrichment factor ranged in 418–438 while intra-day and inter-day RSD (relative standard deviation) (n = 5) were below 4.1%. Based on the results, the proposed simple, sensitive, effective, and eco-friendly method can be successfully applied for the analysis of caffeic acid in real food samples