<p>Copper pesticides, such as copper sulfate, are widely used in agriculture but pose risks to human health and aquatic ecosystems due to the release of cupric ions. This study reports a novel green synthesis of silver nanoparticles using <i>Flemingia strobilifera</i> leaf extract, functionalized with sulfanilic acid, for detecting cupric ions in pond water. The nanoparticles were synthesized via a green route, marking the first use of this plant for nanoparticle synthesis. The sensor’s performance was evaluated by measuring its response to varying copper sulfate concentrations in pond water. The sensor exhibited good linearity and a detection limit of 1.23 µM, indicating high sensitivity along with high selectivity with other potential interfering analytes. This ecofriendly approach represents a significant advancement in green nanotechnology and highlights the potential of green-synthesized nanoparticles for environmental sensing, particularly in monitoring copper pollution in aquatic systems.</p>

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Detection of copper pesticides via leaf extract mediated AgNPs

  • Pohar Borah,
  • Rajib Biswas

摘要

Copper pesticides, such as copper sulfate, are widely used in agriculture but pose risks to human health and aquatic ecosystems due to the release of cupric ions. This study reports a novel green synthesis of silver nanoparticles using Flemingia strobilifera leaf extract, functionalized with sulfanilic acid, for detecting cupric ions in pond water. The nanoparticles were synthesized via a green route, marking the first use of this plant for nanoparticle synthesis. The sensor’s performance was evaluated by measuring its response to varying copper sulfate concentrations in pond water. The sensor exhibited good linearity and a detection limit of 1.23 µM, indicating high sensitivity along with high selectivity with other potential interfering analytes. This ecofriendly approach represents a significant advancement in green nanotechnology and highlights the potential of green-synthesized nanoparticles for environmental sensing, particularly in monitoring copper pollution in aquatic systems.