Evidence map›Paper›PMID 36827442›Full record

ArticlePloS one2023

Visualization and quantification of coconut using advanced computed tomography postprocessing technology.

Shenghuang Lin, Yu Zhang, Li'an Luo, Mengxing Huang, Hongxing Cao, Jinyue Hu, Chengxu Sun, Jing Chen

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 39% of its field
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

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. 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

8 authors at 4 institutions in 1 country.

Shenghuang LinHaikou Affiliated Hospital of Central South University Xiangya School of Medicine, Haikou, China.
Yu ZhangCollege of Computer Science and Technology, Hainan University, Haikou, China.
Li'an LuoSiemens Healthineers, Guangzhou, China.
Mengxing HuangCollege of Information and Communication Engineering, Hainan University, Haikou, China.
Hongxing CaoCoconut Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wenchang, Hainan, People's Republic of China.
Jinyue HuHaikou Affiliated Hospital of Central South University Xiangya School of Medicine, Haikou, China.
Chengxu SunCoconut Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wenchang, Hainan, People's Republic of China.
Jing ChenHaikou Affiliated Hospital of Central South University Xiangya School of Medicine, Haikou, China.ORCID 0000-0001-7383-0273
Central South University · CNChinese Academy of Tropical Agricultural Sciences · CNHainan University · CNSiemens (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionComputed tomography (CT) is a non-invasive examination tool that is widely used in medicine. In this study, we explored its value in visualizing and quantifying coconut. MATERIALS AND

methodsTwelve coconuts were scanned using CT for three months. Axial CT images of the coconuts were obtained using a dual-source CT scanner. In postprocessing process, various three-dimensional models were created by volume rendering (VR), and the plane sections of different angles were obtained through multiplanar reformation (MPR). The morphological parameters and the CT values of the exocarp, mesocarp, endocarp, embryo, bud, solid endosperm, liquid endosperm, and coconut apple were measured. The analysis of variances was used for temporal repeated measures and linear and non-linear regressions were used to analyze the relationship between the data.

resultsThe MPR images and VR models provide excellent visualization of the different structures of the coconut. The statistical results showed that the weight of coconut and liquid endosperm volume decreased significantly during the three months, while the CT value of coconut apple decreased slightly. We observed a complete germination of a coconut, its data showed a significant negative correlation between the CT value of the bud and the liquid endosperm volume (y = -2.6955x + 244.91; R2 = 0.9859), and a strong positive correlation between the height and CT value of the bud (y = 1.9576 ln(x) -2.1655; R2 = 0.9691).

conclusionCT technology can be used for visualization and quantitative analysis of the internal structure of the coconut, and some morphological changes and composition changes of the coconut during the germination process were observed during the three-month experiment. Therefore, CT is a potential tool for analyzing coconuts.

Indexed as

CocosTomography, X-Ray ComputedEndospermTomography Scanners, X-Ray Computed

Identifiers

PMID36827442
PMCPMC9956593
OpenAlexW4321769818

What OpenQuestion holds

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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.