Evidence map›Paper›PMID 42883190›Full record

ReviewMolecules (Basel, Switzerland)2026

Miniaturized Electronic Noses for Food Quality and Safety: Applications in Lipid Oxidation Monitoring.

Maxence Floch, Aynur Gunenc, Farah Hosseinian

Abstract readReview
In one paragraph

Review in Molecules (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

3 authors.

Maxence FlochFood Science, Chemistry Department, Carleton University, Ottawa, ON K1S 5B6, Canada.
Aynur GunencFood Science, Chemistry Department, Carleton University, Ottawa, ON K1S 5B6, Canada.ORCID 0000-0002-3324-1770
Farah HosseinianFood Science, Chemistry Department, Carleton University, Ottawa, ON K1S 5B6, Canada.

Funding

Natural Sciences and Engineering Research Council of Canada Discovery Grant No RGPIN-2026-05242
6 · The paper itself

Abstract

Lipid oxidation is a major degradation process in lipid-rich food systems, producing volatile organic compounds (VOCs) associated with rancidity, off-flavours, and reduced shelf life. Although conventional techniques such as gas chromatography-mass spectrometry (GC-MS) provide reliable identification and quantification of oxidation products, their laboratory-based operation and complex sample preparation limit their suitability for rapid, real-time monitoring. This review examines recent advances in miniaturized and portable electronic-nose (e-nose) systems for monitoring lipid oxidation and food quality through volatile fingerprint analysis. Unlike chromatographic techniques, e-noses generate characteristic response patterns using sensor arrays coupled with pattern recognition and machine learning algorithms rather than directly identifying individual compounds. The relationship between oxidation-derived volatiles, including aldehydes, ketones, alcohols, and hydrocarbons, and e-nose responses are discussed across various food matrices. Metal oxide semiconductor (MOS) sensors remain the most widely investigated technology because of their robustness, scalability, and portability, while electrochemical, conducting polymer, quartz crystal microbalance (QCM), optical, field-effect transistor (FET), and surface acoustic wave (SAW) sensors are also reviewed. Recent developments in chemometric, machine learning, and deep learning approaches for classification, prediction, and sensor-drift compensation are highlighted, alongside applications in edible oils, meat, dairy products, fermented foods, beverages, coffee, and cocoa. Despite considerable progress, sensor drift, humidity interference, calibration transfer, reproducibility, and limited industrial validations remain important challenges. Future research should prioritize sensor stability, standardized validation protocols, and integration with smart-food-monitoring platforms for reliable real-time quality assessment and shelf-life applications.

Indexed as

Electronic NoseFood AnalysisFood QualityFood SafetyLipidsOxidation-ReductionVolatile Organic CompoundsLipidsVolatile Organic Compoundse-nosefood-quality monitoringlipid oxidationreal-time measurementsensor arraysvolatile compounds

Identifiers

PMID42883190
PMCPMC13665735

What OpenQuestion holds

Textmetadata
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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.