Gopal, G.; Roy, N.; Mukherjee, A. Recent Developments in the Applications of GO/rGO-Based Biosensing Platforms for Pesticide Detection. Biosensors2023, 13, 488.
Gopal, G.; Roy, N.; Mukherjee, A. Recent Developments in the Applications of GO/rGO-Based Biosensing Platforms for Pesticide Detection. Biosensors 2023, 13, 488.
Gopal, G.; Roy, N.; Mukherjee, A. Recent Developments in the Applications of GO/rGO-Based Biosensing Platforms for Pesticide Detection. Biosensors2023, 13, 488.
Gopal, G.; Roy, N.; Mukherjee, A. Recent Developments in the Applications of GO/rGO-Based Biosensing Platforms for Pesticide Detection. Biosensors 2023, 13, 488.
Abstract
Pesticides are often used in different applications including agriculture, forestry, aquaculture, food industry, etc in order to insect pests and weeds. The indiscriminate usage of pesticides poses a massive threat to food, environmental and human health safety. Hence, the fabrication of a sensitive, and reliable sensor for the detection of pesticide residues in agro products and environmental samples is a critical subject to be considered. Recently, the graphene family including graphene oxide (GO) and reduced graphene oxide (rGO) have been frequently employed in the construction of sensors owing to their biocompatibility, high surface area to volume ratio, and excellent physiochemical, optical, and electrical properties. The integration of bio-recognition molecules with GO/rGO nanomaterials offers a promising detection strategy with outstanding repeatability, signal intensity, and low background noise. This review focuses on the latest developments (2018 to 2022) in the different types of GO/rGO-based biosensors such as surface plasmon resonance (SPR), fluorescence resonance energy transfer (FRET) and electrochemical based techniques, etc for pesticide analysis. The critical discussions on the advantages, limitations, and sensing mechanisms of emerging GO/rGO-based biosensors have been highlighted as well. Additionally, we explore the existing hurdles in GO/rGO-based biosensors, such as handling of difficult biological samples, reducing the total cost, and so on. This review also provides research gaps and viewpoints for future innovations in GO/rGO-based biosensors for pesticide determination mainly in areas with insufficient resources.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
