Nanophotonic Glyphosate Sensing Integrated into a Portable Optoelectronic Device with Deep-Learning Imaging

ACS Sensors 2026 Open access

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Authors: Jorge Molina-González, C Mateo Frausto-Avila, Haggeo Desirena, Erik Díaz‐Cervantes, Juan Emmanuel Ruiz Rocha, Noé Amir Rodríguez-Olivares, Andrés De Luna Bugallo, Mario A Quiroz-Juárez, Gonzalo Ramírez García
DOI: 10.1021/acssensors.5c03585
Cited by: 1
References: 44

Abstract

= 0.987, demonstrating high predictive accuracy in measurements completed in just 5 s. Each measurement involves capturing numerous images under white LED illumination and then under 975 nm laser excitation followed by automated data integration and analysis by the neural network to yield a glyphosate concentration value. A minimum detectable concentration of 12.5 ppm was achieved, within a linear response range up to 3125 ppm, underscoring the simplicity and practicality of the detection process. These results highlight the potential of this technology for rapid, reliable, and scalable monitoring of glyphosate in soil and water under field-relevant conditions.

Fields of Study & Subjects

Pesticide and Herbicide Environmental Studies Analytical Chemistry and Sensors Plant Surface Properties and Treatments

Publication details

Journal / source
ACS Sensors
Publisher
American Chemical Society (ACS)
Volume
11
Issue
2
Pages
1324–1335
Publication date
6 February 2026
Language
EN