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MOF-based sensor platforms for rapid detection of pesticides to maintain food quality and safety

  • Hessamaddin Sohrabi
  • , Parya Salahshour Sani
  • , Yasin Orooji*
  • , Mir Reza Majidi
  • , Yeojoon Yoon*
  • , Alireza Khataee*
  • *Corresponding author for this work
  • University of Tabriz
  • Zhejiang Normal University
  • Yonsei University Mirae Campus
  • People's Friendship University of Russia

Research output: Contribution to journalArticlepeer-review

113 Citations (Scopus)

Abstract

Pesticides are primarily used in agriculture to increase crop yield because of their highly lucrative, stable structure and agricultural benefits such as eliminating fungi, plant diseases, pests and insects to regulate the growth of crops. Apart from their rebel design and agricultural benefits, pesticides have severe toxicity to a variety of other living organisms. Therefore, developing effective pesticide detection systems is an ongoing challenge. Multiple technologies that for the rapid, easy, sensitive, and selective detection of these neurotoxic compounds are in demand. This paper reviews the recent advances in sensing assays based on the metal-organic framework (MOF) structure for pesticide detection. We have reviewed state-of-the-art optical biosensors for in-place sensing that have the advantages of a simple protocol, simple manipulation, super sensitivity, wide linear range, and cost-effectiveness. These biosensors use chemiluminescence with a short sensing time and a highly sensitive luminescence sensor that enables real-time detection by easy smartphone pairing. For profitable platforms, the obstacles related to sample preparation and equipment cost can be overcome by employing electrochemical sensors. The intensity, impedance, and potential difference measurement techniques used in these biosensors allow for low detection limits and observable durations in water, agricultural, and food samples containing high levels of pesticides.

Original languageEnglish
Article number113176
JournalFood and Chemical Toxicology
Volume165
DOIs
Publication statusPublished - Jul 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022 Elsevier Ltd

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Electrochemical sensing assays
  • Metal-organic-framework-based platforms
  • Optical sensing assays
  • Pesticides

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