LI Na, HUANG Haizhi, YU Xiaoping, et al. Research Progress of Adsorption Extraction of Pesticide and Veterinary Drug Residues in Agricultural Products Based on Metal-organic Frameworks[J]. Science and Technology of Food Industry, 2023, 44(1): 429−438. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2022020176.
Citation: LI Na, HUANG Haizhi, YU Xiaoping, et al. Research Progress of Adsorption Extraction of Pesticide and Veterinary Drug Residues in Agricultural Products Based on Metal-organic Frameworks[J]. Science and Technology of Food Industry, 2023, 44(1): 429−438. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2022020176.

Research Progress of Adsorption Extraction of Pesticide and Veterinary Drug Residues in Agricultural Products Based on Metal-organic Frameworks

  • Pesticide and veterinary drug residues in agricultural products are one of the main problems in the field of food safety. It is necessary to test the residual content of these drugs and set strict limits. At present, adsorption extraction materials such as zeolite and multi-walled carbon nanotubes have the problems of low adsorption capacity and easy clogging of pores. Metal-organic frameworks (MOFs) have been gradually applied in the adsorption extraction of pesticide and veterinary drug residues in agricultural products due to their characteristics of adjustable pores, hierarchical structure, large pore volume and surface area, excellent adsorption performance and recyclability. In this paper, the application status of MOFs as adsorbent for extraction of pesticide and veterinary drug residues in agricultural products is reviewed, and the adsorption application of MOFs is systematically described from the perspective of pesticide and veterinary drug types, and the excellent adsorption performance of MOFs is comprehensively analyzed. This paper gives a reference for the further development of MOFs adsorption extraction technology of pesticide and veterinary drug residues, provides a technical reference for food safety detection.
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