Evidence map›Paper›PMID 32727350›Full record

ArticleBMC bioinformatics2020

Statistical shape analysis of tap roots: a methodological case study on laser scanned sugar beets.

Behrend Heeren, Stefan Paulus, Heiner Goldbach, Heiner Kuhlmann, Anne-Katrin Mahlein, Martin Rumpf, Benedikt Wirth

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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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

7 authors.

Behrend HeerenInstitute for Numerical Simulation, University of Bonn, Endenicher Allee 60, Bonn, 53115, Germany. behrend.heeren@ins.uni-bonn.de.ORCID http://orcid.org/0000-0003-4397-7834
Stefan PaulusInstitute of Sugar Beet Research, Germany, Holtenser Landstr. 77, Göttingen, 37079, Germany.
Heiner GoldbachINRES Plant Nutrition, University of Bonn, Karlrobert-Kreiten-Strasse 13, Bonn, 53115, Germany.
Heiner KuhlmannInstitute for Geodesy and Geoinformation, University of Bonn, Nussallee 17, Bonn, 53115, Germany.
Anne-Katrin MahleinInstitute of Sugar Beet Research, Germany, Holtenser Landstr. 77, Göttingen, 37079, Germany.
Martin RumpfInstitute for Numerical Simulation, University of Bonn, Endenicher Allee 60, Bonn, 53115, Germany.
Benedikt WirthInstitute for Analysis and Numerics, University of Münster, Einsteinstr. 62, Münster, 48149, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe efficient and robust statistical analysis of the shape of plant organs of different cultivars is an important investigation issue in plant breeding and enables a robust cultivar description within the breeding progress. Laserscanning is a highly accurate and high resolution technique to acquire the 3D shape of plant surfaces. The computation of a shape based principal component analysis (PCA) built on concepts from continuum mechanics has proven to be an effective tool for a qualitative and quantitative shape examination.

resultsThe shape based PCA was used for a statistical analysis of 140 sugar beet roots of different cultivars. The calculation of the mean sugar beet root shape and the description of the main variations was possible. Furthermore, unknown and individual tap roots could be attributed to their cultivar by means of a robust classification tool based on the PCA results.

conclusionThe method demonstrates that it is possible to identify principal modes of root shape variations automatically and to quantify associated variances out of laserscanned 3D sugar beet tap root models. The introduced approach is not limited to the 3D shape description by laser scanning. A transfer to 3D MRI or radar data is also conceivable.

Indexed as

LasersStatistics as TopicBeta vulgarisPlant RootsPrincipal Component Analysis3D point cloudsEnergy minimizationShape variationTap roots

Identifiers

PMID32727350
PMCPMC7388232

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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.