Evidence map›Paper›PMID 29599815›Full record

ArticlePlant methods2018

MowJoe: a method for automated-high throughput dissected leaf phenotyping.

Henrik Failmezger, Janne Lempe, Nasim Khadem, Maria Cartolano, Miltos Tsiantis, Achim Tresch

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Article in Plant methods, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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3 citing papers in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Henrik Failmezger *1Max Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, 50829 Cologne, Germany.
Janne Lempe *1Max Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, 50829 Cologne, Germany.
Nasim Khadem2Department of Biology, University of Cologne, Zülpicher Str. 47, 50674 Cologne, Germany.
Maria Cartolano1Max Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, 50829 Cologne, Germany.
Miltos Tsiantis1Max Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, 50829 Cologne, Germany.
Achim Tresch1Max Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, 50829 Cologne, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate and automated phenotyping of leaf images is necessary for high throughput studies of leaf form like genome-wide association analysis and other forms of quantitative trait locus mapping. Dissected leaves (also referred to as compound) that are subdivided into individual units are an attractive system to study diversification of form. However, there are only few software tools for their automated analysis. Thus, high-throughput image processing algorithms are needed that can partition these leaves in their phenotypically relevant units and calculate morphological features based on these units.

resultsWe have developed MowJoe, an image processing algorithm that dissects a dissected leaf into leaflets, petiolule, rachis and petioles. It employs image skeletonization to convert leaves into graphs, and thereafter applies algorithms operating on graph structures. This partitioning of a leaf allows the derivation of morphological features such as leaf size, or eccentricity of leaflets. Furthermore, MowJoe automatically places landmarks onto the terminal leaflet that can be used for further leaf shape analysis. It generates specific output files that can directly be imported into downstream shape analysis tools. We applied the algorithm to two accessions of

conclusionMowJoe is a tool for the semi-automated, quantitative high throughput shape analysis of dissected leaf images. It provides the statistical power for the detection of the genetic basis of quantitative morphological variations.

Identifiers

PMID29599815
PMCPMC5868070

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