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Updated: May 14, 2026

LeafJ: An ImageJ Plugin for Semi-automated Leaf Shape Measurement

LeafJ: An ImageJ Plugin for Semi-automated Leaf Shape Measurement

Published on: January 21, 2013

LeafJ: an ImageJ plugin for semi-automated leaf shape measurement.

Julin N Maloof¹, Kazunari Nozue, Maxwell R Mumbach

¹Department of Plant Biology, University of California Davis, USA. jnmaloof@ucdavis.edu

Journal of Visualized Experiments : Jove

|February 6, 2013

Summary

A new ImageJ plugin, LeafJ, enables high-throughput measurement of leaf petiole length and blade parameters. This tool accelerates plant phenomics research, particularly for studying the shade avoidance syndrome (SAS) in Arabidopsis thaliana.

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Area of Science:

Plant biology
Genetics
Computational biology

Background:

High-throughput phenotyping (phenomics) is crucial for linking genes to plant functions.
Leaf morphology, including petiole length and blade area, is vital for understanding plant responses to environmental cues like shade.
Existing leaf analysis software lacks the ability to measure petiole length, hindering research on the shade avoidance syndrome (SAS).

Purpose of the Study:

To develop and validate a novel ImageJ plugin, LeafJ, for rapid and accurate measurement of leaf petiole length and blade parameters.
To present a complementary protocol for measuring leaf cell shape, area, and size using a touch-screen tablet.
To facilitate large-scale phenomics approaches in plant research, especially for SAS studies.

Main Methods:

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LeafJ: An ImageJ Plugin for Semi-automated Leaf Shape Measurement

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Development of the LeafJ ImageJ plugin for automated measurement of leaf traits.
Utilized a touch-screen tablet for manual correction and measurement of leaf cell characteristics.
Tested the system on the model plant Arabidopsis thaliana.

Main Results:

LeafJ enables rapid measurement of petiole length and leaf blade parameters, addressing a key limitation in existing phenotyping tools.
The touch-screen tablet protocol allows for efficient measurement of leaf cell shape, area, and size.
The developed system significantly enhances the capacity for large-scale leaf phenotyping.

Conclusions:

The LeafJ plugin and associated tablet protocol provide a powerful new system for comprehensive leaf phenotyping.
This advancement will accelerate research in plant genetics, environmental responses (e.g., SAS), and crop improvement.
The tools are versatile and applicable to a wide range of plant phenomics studies beyond shade avoidance.