Evidence map›Paper›PMID 40094810›Full record

ReviewPlants (Basel, Switzerland)2025

Unveiling Nature's Architecture: Geometric Morphometrics as an Analytical Tool in Plant Biology.

Federica Spani, Vittoria Locato, Laura De Gara

Abstract readReview
In one paragraph

Review in Plants (Basel, Switzerland), 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

3 authors.

Federica SpaniDepartment of Science and Technology for Sustainable Development and One Health, Research Unit of Food and Nutrition Sciences, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Roma, Italy.ORCID 0000-0001-9577-8875
Vittoria LocatoDepartment of Science and Technology for Sustainable Development and One Health, Research Unit of Food and Nutrition Sciences, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Roma, Italy.
Laura De GaraDepartment of Science and Technology for Sustainable Development and One Health, Research Unit of Food and Nutrition Sciences, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Roma, Italy.ORCID 0000-0001-5938-7113

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Geometric morphometrics (GMM) is an advanced morphometric method enabling quantitative analysis of shape and size variations in biological structures. Through high-resolution imaging and mathematical algorithms, GMM provides valuable insights into taxonomy, ecology, and evolution, making it increasingly relevant in plant science. This review synthesizes the existing literature and explores methodological details, research questions, and future directions, establishing a strong foundation for further study in plant biology. Following PRISMA 2020 guidelines, a rigorous literature search finally identified 83 studies for review. The review organized data on plant species, organs studied, GMM objectives, and methodological aspects, such as imaging and landmark positioning. Leaf and flower structures emerged as the most frequently analyzed organs, primarily in studies of shape variations. This review assesses the use of GMM in plant sciences, identifying knowledge gaps and inconsistencies, and suggesting areas for future research. By highlighting unaddressed topics and emerging trends, the review aims to guide researchers towards methodological challenges and innovations necessary for advancing the field.

Indexed as

landmark-based methodsplant organsplant sciencePRISMA 2020shape variationsize variation

Identifiers

PMID40094810
PMCPMC11901851

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.