Glyphosate [(N-phosphonomethyl) Glycine], one of the most worldwide commercialized herbicides, has provoked many debates about its carcinogenic effects. Here, a smartphone-based surface plasmon resonance (SPR) sensor is proposed for glyphosate detection using different pH and concentrations. CuO nanoparticles have been added to glyphosate samples, diluted in ultra-pure water solutions, to enhance its detection. An increase of sensitivity was observed in acidic solutions reaching a dilution of 10 −8 (v/v), which is equivalent to 5 • 10 −7 ppm. This novel smartphonebased SPR device for glyphosate detection besides presenting very high sensitivity, it has also favorable features such as easy handling, portability, and real-time analysis.
Glyphosate [(N-phosphonomethyl) Glycine], one of the most worldwide commercialized herbicides, has provoked many debates about its carcinogenic effects. Here, a smartphone-based surface plasmon resonance (SPR) sensor is proposed for glyphosate detection using different pH and concentrations. CuO nanoparticles have been added to glyphosate samples, diluted in ultra-pure water solutions, to enhance its detection. An increase of sensitivity was observed in acidic solutions reaching a dilution of 10−8 (v/v), which is equivalent to 5·10−7 ppm. This novel smartphonebased SPR device for glyphosate detection besides presenting very high sensitivity, it has also favorable features such as easy handling, portability, and real-time analysis.
Resumo-A necessidade de diagnosticar a presença de retinopatia em pacientes diabéticos, impulsionou o desenvolvimento de algoritmos de processamento que fossem capazes de diagnosticar a doença em sua fase inicial. Neste projeto foram utilizadas técnicas de pré-processamento para melhorar a qualidade das imagens, visando a exclusão de artefatos indesejáveis. O algoritmo bioinspirado na colônia artificial de abelhas teve a função de buscar nas imagens características relacionadas aos exsudatos. Para a avaliação do algoritmo proposto foram usados testes de diagnósticos referentesà especificidade e acurácia alcançando 98% e 97%, respectivamente.
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