ReviewFoods (Basel, Switzerland)2026
Carbon Dot-Based Sensors for Food Chemical Hazard Detection: Real-Food Applications, Sample Preparation, and Portable Analysis.
Review in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Carbon dots (CDs) are a heterogeneous family of fluorescent carbon nanomaterials that includes carbon quantum dots (CQDs) as a subclass. Owing to their favorable fluorescence, surface chemistry, and functionalization potential, CDs have been widely investigated for sensing analytes relevant to food chemical safety. This structured narrative review and evidence map examines a broad analytical corpus of 106 original CD-based studies published between 2016 and 29 August 2026, covering heavy metals and metalloids, pesticides, veterinary drugs and antibiotics, and food additives, adulterants, and processing contaminants. Food-matrix eligibility was then assessed separately: 68 studies experimentally applied the method to an actual food matrix and generated 98 study-food matrix combinations. This two-tier analysis shows that veterinary-drug studies focused mainly on dairy products, pesticide studies predominantly addressed fruits and vegetables, and the comparatively limited food applications for heavy metals concentrated in aquatic products. Centrifugation, filtration, organic-solvent extraction, and deproteinization remained common, indicating that rapid sensor response does not necessarily translate into rapid end-to-end food analysis. Paper-based, hydrogel, and smartphone-assisted platforms are advancing CD detection from visual observation toward calibration-based quantification; however, validation using commercial samples at native or unknown concentrations, incurred samples, cross-device consistency, and field standardization remain insufficient. The synthesis therefore identifies analytical reliability, complex-matrix compatibility, simplified pretreatment, multi-analyte detection, and standardized on-site quantification as priorities beyond the pursuit of lower detection limits.
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.