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Updated: Feb 12, 2026

LeafJ: An ImageJ Plugin for Semi-automated Leaf Shape Measurement
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MowJoe: a method for automated-high throughput dissected leaf phenotyping.

Henrik Failmezger1,2, Janne Lempe1, Nasim Khadem2

  • 11Max Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, 50829 Cologne, Germany.

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Summary

MowJoe is a new image analysis tool that automatically dissects dissected leaves into leaflets and other components. This enables high-throughput quantitative trait analysis for genetic studies of plant morphology.

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Area of Science:

  • Plant biology
  • Bioinformatics
  • Image analysis

Background:

  • High-throughput phenotyping of leaf images is crucial for genetic studies.
  • Dissected leaves offer valuable insights into form diversification.
  • Limited software exists for automated analysis of dissected leaves.

Purpose of the Study:

  • To develop an automated image processing algorithm for dissected leaf analysis.
  • To enable high-throughput quantitative trait analysis of leaf morphology.
  • To facilitate the genetic dissection of morphological variations.

Main Methods:

  • Developed MowJoe, an image processing algorithm.
  • Utilized image skeletonization to convert leaves into graphs.
  • Applied graph-based algorithms for leaf partitioning and feature extraction.

Main Results:

  • MowJoe successfully dissects dissected leaves into leaflets, petiolules, rachises, and petioles.
  • Derived morphological features like leaf size and leaflet eccentricity.
  • Automatically placed landmarks for further shape analysis.
  • Demonstrated robust discrimination between *Cardamine hirsuta* accessions.

Conclusions:

  • MowJoe provides semi-automated, high-throughput shape analysis for dissected leaf images.
  • Enables statistical power for detecting the genetic basis of quantitative morphological variations.