Evidence map›Paper›PMID 36432787›Full record

ArticlePlants (Basel, Switzerland)2022

Comparison of Two Simplified Versions of the Gielis Equation for Describing the Shape of Bamboo Leaves.

Weihao Yao, Ülo Niinemets, Wenjing Yao, Johan Gielis, Julian Schrader, Kexin Yu, Peijian Shi

Abstract read
In one paragraph

Article in Plants (Basel, Switzerland), 2022. 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.

Weihao YaoBamboo Research Institute, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China.
Ülo NiinemetsInstitute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, 51006 Tartu, Estonia.
Wenjing YaoBamboo Research Institute, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China.ORCID 0000-0001-8424-0172
Johan GielisDepartment of Biosciences Engineering, University of Antwerp, B-2020 Antwerp, Belgium.ORCID 0000-0002-4536-3839
Julian SchraderSchool of Natural Sciences, Macquarie University, Sydney, NSW 2109, Australia.ORCID 0000-0002-8392-211X
Kexin YuBamboo Research Institute, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China.
Peijian ShiBamboo Research Institute, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China.ORCID 0000-0003-4696-0130

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bamboo is an important component in subtropical and tropical forest communities. The plant has characteristic long lanceolate leaves with parallel venation. Prior studies have shown that the leaf shapes of this plant group can be well described by a simplified version (referred to as SGE-1) of the Gielis equation, a polar coordinate equation extended from the superellipse equation. SGE-1 with only two model parameters is less complex than the original Gielis equation with six parameters. Previous studies have seldom tested whether other simplified versions of the Gielis equation are superior to SGE-1 in fitting empirical leaf shape data. In the present study, we compared a three-parameter Gielis equation (referred to as SGE-2) with the two-parameter SGE-1 using the leaf boundary coordinate data of six bamboo species within the same genus that have representative long lanceolate leaves, with >300 leaves for each species. We sampled 2000 data points at approximately equidistant locations on the boundary of each leaf, and estimated the parameters for the two models. The root−mean−square error (RMSE) between the observed and predicted radii from the polar point to data points on the boundary of each leaf was used as a measure of the model goodness of fit, and the mean percent error between the RMSEs from fitting SGE-1 and SGE-2 was used to examine whether the introduction of an additional parameter in SGE-1 remarkably improves the model’s fitting. We found that the RMSE value of SGE-2 was always smaller than that of SGE-1. The mean percent errors among the two models ranged from 7.5% to 20% across the six species. These results indicate that SGE-2 is superior to SGE-1 and should be used in fitting leaf shapes. We argue that the results of the current study can be potentially extended to other lanceolate leaf shapes.

Indexed as

leaf shapepercent errorPleioblastuspolar anglepolar radius

Identifiers

PMID36432787
PMCPMC9699164

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.