Evidence map›Paper›PMID 42655586›Full record

ReviewSensors (Basel, Switzerland)2026

Graphene-Based Sensors for Food Freshness Monitoring: Recent Advances, Performance, and Practical Challenges.

Grazia Giuseppina Politano

Abstract readReview
In one paragraph

Review in Sensors (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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Grazia Giuseppina PolitanoDepartment of Environmental Engineering, University of Calabria, 87036 Rende, Italy.ORCID 0000-0001-8631-3670

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Food spoilage along the supply chain represents a major global challenge, contributing to economic losses, environmental impacts, and food safety concerns. Graphene-based materials have emerged as promising platforms for real-time food freshness monitoring owing to their high surface area, electrical conductivity, chemical sensitivity, and compatibility with flexible sensing architectures. This review critically examines graphene-based sensing strategies for food freshness and spoilage monitoring, including chemiresistive, dielectric, field-effect, optical/fluorescence, photoelectrochemical, mass-sensitive, and colorimetric approaches. Representative sensing platforms are compared in terms of analytical performance, including detection range, limit of detection, selectivity, response and recovery times, calibration, reproducibility, and stability. Particular attention is given to machine-learning-assisted sensing, multifunctional platforms for temperature, humidity, and gas monitoring, and the challenges associated with real-world implementation, including environmental interference, sensor fouling, signal drift, long-term stability, and cross-matrix validation. Finally, commercialization readiness, integration into intelligent packaging, and safety and regulatory considerations related to graphene-based food-contact applications are discussed. Overall, the review identifies the main technological gaps and future research priorities toward robust, scalable, and practical graphene-based systems for real-time food freshness monitoring.

Indexed as

Biosensing TechniquesFood AnalysisGraphiteFood PackagingFood SafetyGraphitefood freshnessfood packaginggraphene

Identifiers

PMID42655586
PMCPMC13517949

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.