Evidence map›Paper›PMID 39940528›Full record

ArticlePolymers2025

Cutting-Edge Sensor Design: MIP Nanoparticle-Functionalized Nanofibers for Gas-Phase Detection of Limonene in Predictive Agriculture.

Fabricio Nicolàs Molinari, Marcello Marelli, Enrico Berretti, Simone Serrecchia, Roxana Elisabeth Coppola, Fabrizio De Cesare, Antonella Macagnano

Abstract read
In one paragraph

Article in Polymers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

7 authors.

Fabricio Nicolàs MolinariInstitute of Atmospheric Pollution Research (IIA)-CNR, 00010 Montelibretti, RM, Italy.
Marcello MarelliInstitute of Science and Chemical Technologies "Giulio Natta" (SCITEC)-CNR, 20138 Milano, MI, Italy.ORCID 0000-0003-3662-7326
Enrico BerrettiInstitute for the Chemistry of OrganoMetallic Compounds (ICCOM)-CNR, 50019 Sesto Fiorentino, FI, Italy.
Simone SerrecchiaInstitute of Atmospheric Pollution Research (IIA)-CNR, 00010 Montelibretti, RM, Italy.ORCID 0009-0007-4648-4329
Roxana Elisabeth CoppolaNational Institute of Industrial Technology (INTI), Buenos Aires B1650WAB, Argentina.
Fabrizio De CesareInstitute of Atmospheric Pollution Research (IIA)-CNR, 00010 Montelibretti, RM, Italy.ORCID 0000-0001-9810-8746
Antonella MacagnanoInstitute of Atmospheric Pollution Research (IIA)-CNR, 00010 Montelibretti, RM, Italy.ORCID 0000-0002-6015-4832

Funding

Project "MOSSA"-European Regional Development Fund POR FESR Lazio 2014-2020, N. T0002E0001 and Project "TERRE" - Strategic Research Projects@CNR 2020-2022, N. SAC.AD002.173.041 T0002E0001
6 · The paper itself

Abstract

As population growth and climate change intensify pressures on agriculture, innovative strategies are vital for ensuring food security, optimizing resources, and protecting the environment. This study introduces a novel approach to predictive agriculture by utilizing the unique properties of terpenes, specifically S(-)-limonene, emitted by plants under stress. Advanced sensors capable of detecting subtle limonene variations offer the potential for early stress diagnosis and precise crop interventions. This research marks a significant leap in sensor technology, introducing an innovative active sensing material that combines molecularly imprinted polymer (MIP) technology with electrospinning. S(-)-limonene-selective MIP nanoparticles, engineered using methacrylic acid (MAA) and ethylene glycol dimethacrylate (EGDMA), were synthesized with an average diameter of ~160 nm and integrated into polyvinylpyrrolidone (PVP) nanofibers reinforced with multiwall carbon nanotubes (MWCNTs). This design produced a conductive and highly responsive sensing layer. The sensor exhibited rapid stabilization (200 s), a detection limit (LOD) of 190 ppb, and a selectivity index of 73% against similar monoterpenes. Optimal performance was achieved at 55% relative humidity, highlighting environmental conditions' importance. This pioneering use of polymeric MIP membranes in chemiresistive sensors for limonene detection opens new possibilities for monitoring VOCs, with applications in agricultural stress biomarkers, contaminant detection, and air quality monitoring, advancing precision agriculture and environmental protection.

Indexed as

BVOCsconductive sensorselectrospinninglimonenemolecular imprinted polymersmonoterpenesnanofibersnanoparticlespredictive agriculture

Identifiers

PMID39940528
PMCPMC11820196

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Registered trials

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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.