Evidence map›Paper›PMID 35268593›Full record

ArticleMolecules (Basel, Switzerland)2022

Real-Time Detection of Phenylacetaldehyde in Wine: Application of a Microwave Sensor Based on Molecularly Imprinted Silica.

Jérôme Rossignol, Philippe Cayot, Didier Stuerga, Régis D Gougeon, Elias Bou-Maroun

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Jérôme RossignolLaboratoire Interdisciplinaire Carnot de Bourgogne, CNRS UMR 6303, Departement Interface, GERM, University Bourgogne Franche-Comté, 21078 Dijon, France.
Philippe CayotUMR Procédés Alimentaires et Microbiologiques, PAM UMR A 02.102, University Bourgogne Franche-Comté, AgroSup Dijon, 21000 Dijon, France.ORCID 0000-0002-6998-8569
Didier StuergaLaboratoire Interdisciplinaire Carnot de Bourgogne, CNRS UMR 6303, Departement Interface, GERM, University Bourgogne Franche-Comté, 21078 Dijon, France.ORCID 0000-0003-0794-3602
Régis D GougeonUMR Procédés Alimentaires et Microbiologiques, PAM UMR A 02.102, University Bourgogne Franche-Comté, AgroSup Dijon, 21000 Dijon, France.ORCID 0000-0002-5371-5523
Elias Bou-MarounUMR Procédés Alimentaires et Microbiologiques, PAM UMR A 02.102, University Bourgogne Franche-Comté, AgroSup Dijon, 21000 Dijon, France.ORCID 0000-0003-0208-858X

Funding

SAYENS MISMO project
6 · The paper itself

Abstract

Molecularly imprinted sol-gel silica (MIS) coupled to a microwave sensor was designed and used to detect phenylacetaldehyde (PAA), a chemical tracer of wine oxidation. The developed method is fast, cheap and could replace the classical chromatographic methods, which require a tedious sample preparation and are expensive. To reach our objective, five MIS and their control non-imprinted silica (NIS) were synthesized and their extraction capacity toward PAA was studied in hydro alcoholic medium. The selected polymers, based on this first step, were subjected to a selectivity study in the presence of PAA and three other competing molecules. The best polymer was integrated in a microwave sensor and was used to assess PAA in red wine. The developed sensor was able to detect PAA at the µg·L

Indexed as

AcetaldehydeMicrowavesSilicon DioxideWineBenzaldehydesMolecular ImprintingOxidation-ReductionAcetaldehydeBenzaldehydesphenylacetaldehydeSilicon Dioxidefast analysismicrowave sensormolecularly imprinted silicaphenylacetaldehydewine oxidation

Identifiers

PMID35268593
PMCPMC8911824

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.