Evidence map›Paper›PMID 33317442›Full record

ArticleBMC bioinformatics2020

Flora Capture: a citizen science application for collecting structured plant observations.

David Boho, Michael Rzanny, Jana Wäldchen, Fabian Nitsche, Alice Deggelmann, Hans Christian Wittich, Marco Seeland, Patrick Mäder

Abstract read
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Emerging technologies in citizen science and potential for insect monitoring.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
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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

8 authors.

David BohoInstitute for Computer and Systems Engineering, Technische Universität Ilmenau, Helmholtzplatz 5, 98693, Ilmenau, Germany.
Michael RzannyDepartment Biogeochemical Integration, Max-Planck-Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745, Jena, Germany.
Jana WäldchenDepartment Biogeochemical Integration, Max-Planck-Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745, Jena, Germany. jwald@bgc-jena.mpg.de.
Fabian NitscheInstitute for Computer and Systems Engineering, Technische Universität Ilmenau, Helmholtzplatz 5, 98693, Ilmenau, Germany.
Alice DeggelmannDepartment Biogeochemical Integration, Max-Planck-Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745, Jena, Germany.
Hans Christian WittichInstitute for Computer and Systems Engineering, Technische Universität Ilmenau, Helmholtzplatz 5, 98693, Ilmenau, Germany.
Marco SeelandInstitute for Computer and Systems Engineering, Technische Universität Ilmenau, Helmholtzplatz 5, 98693, Ilmenau, Germany.
Patrick MäderInstitute for Computer and Systems Engineering, Technische Universität Ilmenau, Helmholtzplatz 5, 98693, Ilmenau, Germany.

Funding

Bundesministerium für Bildung und Forschung 01IS20062Bundesministerium für Bildung und Forschung 01LC1319Bundesministerium für Umwelt, Naturschutz, Bau und Reaktorsicherheit 3514685C19Bundesministerium für Umwelt, Naturschutz, Bau und Reaktorsicherheit 3519685A08Bundesministerium für Umwelt, Naturschutz, Bau und Reaktorsicherheit 3519685B08Stiftung Naturschutz Thüringen SNT-082-248-03/2014Thüringer Ministerium für Umwelt, Energie und Naturschutz 68678
6 · The paper itself

Abstract

backgroundDigital plant images are becoming increasingly important. First, given a large number of images deep learning algorithms can be trained to automatically identify plants. Second, structured image-based observations provide information about plant morphological characteristics. Finally in the course of digitalization, digital plant collections receive more and more interest in schools and universities.

resultsWe developed a freely available mobile application called Flora Capture allowing users to collect series of plant images from predefined perspectives. These images, together with accompanying metadata, are transferred to a central project server where each observation is reviewed and validated by a team of botanical experts. Currently, more than 4800 plant species, naturally occurring in the Central European region, are covered by the application. More than 200,000 images, depicting more than 1700 plant species, have been collected by thousands of users since the initial app release in 2016.

conclusionFlora Capture allows experts, laymen and citizen scientists to collect a digital herbarium and share structured multi-modal observations of plants. Collected images contribute, e.g., to the training of plant identification algorithms, but also suit educational purposes. Additionally, presence records collected with each observation allow contribute to verifiable records of plant occurrences across the world.

Indexed as

SoftwareFlowersImage Processing, Computer-AssistedNeural Networks, ComputerPlantsCitizen scienceDigital herbariumnDigital plant collectionMobile appMulti-organ plant identificationStructured plant observations

Identifiers

PMID33317442
PMCPMC7734824

What OpenQuestion holds

Textmetadata
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.