ArticleBiosensors2023
Localized Surface Plasmon Resonance-Based Nanosensor for Rapid Detection of Glyphosate in Food Samples.
Article in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- A Review on Biomedical, Biomolecular, and Environmental Monitoring Applications of Cysteamine Functionalized Nanomaterials.Micromachines · 2025Review
- Highly stable SERS-based mirrored aptasensor for selective detection of alpha-fetoprotein.Mikrochimica acta · 2025Article
- Surface-Enhanced Raman Scattering Combined with Machine Learning for Rapid and Sensitive Detection of Anti-SARS-CoV-2 IgG.Biosensors · 2024Article
- Tamm Plasmon Polariton Biosensors Based on Porous Silicon: Design, Validation and Analysis.Biosensors · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
In this study, we developed a biosensor based on the localized surface plasmon resonance (LSPR) phenomenon of gold nanoparticles (AuNPs) to detect the widely used herbicide glyphosate in food samples. To do so, either cysteamine or a specific antibody for glyphosate were conjugated to the surface of the nanoparticles. AuNPs were synthesized using the sodium citrate reduction method and had their concentration determined via inductively plasma coupled mass spectrometry. Their optical properties were analyzed using UV-vis spectroscopy, X-ray diffraction, and transmission electron microscopy. Functionalized AuNPs were further characterized via Fourier-transform infrared spectroscopy, Raman scattering, Zeta potential, and dynamic light scattering. Both conjugates succeeded in detecting the presence of glyphosate in the colloid, although nanoparticles functionalized with cysteamine tended to aggregate at high concentrations of the herbicide. On the other hand, AuNPs functionalized with anti-glyphosate functioned at a broad concentration range and successfully identified the presence of the herbicide in non-organic coffee samples and when it was added to an organic coffee sample. This study demonstrates the potential of AuNP-based biosensors to detect glyphosate in food samples. The low-cost and specificity of these biosensors make them a viable alternative to current methods for detecting glyphosate in foodstuffs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.