Evidence map›Paper›PMID 37680357›Full record

ArticleFrontiers in plant science2023

Pitfalls and potential of high-throughput plant phenotyping platforms.

Hendrik Poorter, Grégoire M Hummel, Kerstin A Nagel, Fabio Fiorani, Philipp von Gillhaussen, Olivia Virnich, Ulrich Schurr, Johannes A Postma, Rick van de Zedde, Anika Wiese-Klinkenberg

Abstract read
In one paragraph

Article in Frontiers in plant science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Understanding the genetics of root system architecture in pigeonpea [Cajanus cajan (L.) Millsp.].TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. A high-throughput pipeline for phenotyping, object detection and quantification of leaf trichomes.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. 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

10 authors.

Hendrik PoorterPlant Sciences (IBG-2), Forschungszentrum Jülich GmbH, Jülich, Germany.
Grégoire M HummelPhenospex, Heerlen, Netherlands.
Kerstin A NagelPlant Sciences (IBG-2), Forschungszentrum Jülich GmbH, Jülich, Germany.
Fabio FioraniPlant Sciences (IBG-2), Forschungszentrum Jülich GmbH, Jülich, Germany.
Philipp von GillhaussenInternational Plant Phenotyping Network e.V. (IPPN), Jülich, Germany.
Olivia VirnichPlant Sciences (IBG-2), Forschungszentrum Jülich GmbH, Jülich, Germany.
Ulrich SchurrPlant Sciences (IBG-2), Forschungszentrum Jülich GmbH, Jülich, Germany.
Johannes A PostmaPlant Sciences (IBG-2), Forschungszentrum Jülich GmbH, Jülich, Germany.
Rick van de ZeddePlant Sciences Group, Wageningen University & Research, Wageningen, Netherlands.
Anika Wiese-KlinkenbergPlant Sciences (IBG-2), Forschungszentrum Jülich GmbH, Jülich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Automated high-throughput plant phenotyping (HTPP) enables non-invasive, fast and standardized evaluations of a large number of plants for size, development, and certain physiological variables. Many research groups recognize the potential of HTPP and have made significant investments in HTPP infrastructure, or are considering doing so. To make optimal use of limited resources, it is important to plan and use these facilities prudently and to interpret the results carefully. Here we present a number of points that users should consider before purchasing, building or utilizing such equipment. They relate to (1) the financial and time investment for acquisition, operation, and maintenance, (2) the constraints associated with such machines in terms of flexibility and growth conditions, (3) the pros and cons of frequent non-destructive measurements, (4) the level of information provided by proxy traits, and (5) the utilization of calibration curves. Using data from an Arabidopsis experiment, we demonstrate how diurnal changes in leaf angle can impact plant size estimates from top-view cameras, causing deviations of more than 20% over the day. Growth analysis data from another rosette species showed that there was a curvilinear relationship between total and projected leaf area. Neglecting this curvilinearity resulted in linear calibration curves that, although having a high r

Indexed as

calibration curvedigital biomasshigh-throughput plant phenotypingleaf mass per areasensors

Identifiers

PMID37680357
PMCPMC10481964

What OpenQuestion holds

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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.