Evidence map›Paper›PMID 40547190›Full record

ArticleAerobiologia2025

Advancing automated identification of airborne fungal spores: guidelines for cultivation and reference dataset creation.

Nicolas Bruffaerts, Elias Graf, Predrag Matavulj, Astha Tiwari, Ioanna Pyrri, Yanick Zeder, Sophie Erb, Maria Plaza, Silas Dietler, Tommaso Bendinelli and 2 more

Abstract read
In one paragraph

Article in Aerobiologia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

12 authors.

Nicolas BruffaertsMycology and Aerobiology, Sciensano, Brussels, Belgium.ORCID 0000-0001-6310-9140
Elias GrafSwisens AG, Emmen, Switzerland.ORCID 0000-0003-2829-8411
Predrag MatavuljInstitute for Data Science, University of Applied Sciences North Western Switzerland, Windish, Switzerland.ORCID 0000-0003-0229-7189
Astha TiwariMycology and Aerobiology, Sciensano, Brussels, Belgium.ORCID 0000-0002-4374-6297
Ioanna PyrriBiology Department, National and Kapodistrian University of Athens, Athens, Greece.ORCID 0000-0003-1076-6627
Yanick ZederSwisens AG, Emmen, Switzerland.
Sophie ErbFederal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland.ORCID 0000-0002-0700-283X
Maria PlazaFaculty of Medicine, University of Augsburg, Augsburg, Germany.ORCID 0000-0003-1192-2214
Silas DietlerCSEM Alpnach, Centre Suisse d'Electronique et de Microtechnique, Alpnach, Switzerland.
Tommaso BendinelliCSEM Alpnach, Centre Suisse d'Electronique et de Microtechnique, Alpnach, Switzerland.
Elizabet D'hoogeMycology and Aerobiology, Sciensano, Brussels, Belgium.ORCID 0009-0002-5798-0751
Branko SikoparijaBioSense Institute - Research Institute for Information Technologies in Biosystems, University of Novi Sad, Novi Sad, Serbia.ORCID 0000-0002-6766-4149

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Airborne bioparticles, including fungal spores, are of major concern for human and plant health, necessitating precise monitoring systems. While a European norm exists for manual volumetric monitoring, there's a growing interest in automated real-time methods. However, these methods rely heavily on machine learning, facing challenges due to diverse particle characteristics and limited training data availability, especially for fungal spores. This study aims to address this gap by outlining best practices for collecting reference material and creating tailored datasets for training algorithms. Using 17 fungal species from the Belgian fungi collection BCCM/IHEM, including five Supplementary Information: The online version contains supplementary material available at 10.1007/s10453-025-09864-y.

Indexed as

Airflow cytometryAutomatic identificationCulture collectionFungal sporesMachine learning

Identifiers

PMID40547190
PMCPMC12176942

What OpenQuestion holds

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LicenceCC BY
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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.