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

Published: January 21st, 2013



1Department of Plant Biology, University of California Davis
* These authors contributed equally

Demonstration of key methods for high throughput leaf measurements. These methods can be used to accelerate leaf phenotyping when studying many plant mutants or otherwise screening plants by leaf phenotype.

High throughput phenotyping (phenomics) is a powerful tool for linking genes to their functions (see review1 and recent examples2-4). Leaves are the primary photosynthetic organ, and their size and shape vary developmentally and environmentally within a plant. For these reasons studies on leaf morphology require measurement of multiple parameters from numerous leaves, which is best done by semi-automated phenomics tools5,6. Canopy shade is an important environmental cue that affects plant architecture and life history; the suite of responses is collectively called the shade avoidance syndrome (SAS)7. Among SAS responses, shade induced leaf petiole elongation and changes in blade area are particularly useful as indices8. To date, leaf shape programs (e.g. SHAPE9, LAMINA10, LeafAnalyzer11, LEAFPROCESSOR12) can measure leaf outlines and categorize leaf shapes, but can not output petiole length. Lack of large-scale measurement systems of leaf petioles has inhibited phenomics approaches to SAS research. In this paper, we describe a newly developed ImageJ plugin, called LeafJ, which can rapidly measure petiole length and leaf blade parameters of the model plant Arabidopsis thaliana. For the occasional leaf that required manual correction of the petiole/leaf blade boundary we used a touch-screen tablet. Further, leaf cell shape and leaf cell numbers are important determinants of leaf size13. Separate from LeafJ we also present a protocol for using a touch-screen tablet for measuring cell shape, area, and size. Our leaf trait measurement system is not limited to shade-avoidance research and will accelerate leaf phenotyping of many mutants and screening plants by leaf phenotyping.

1. Plant Materials

Note that this plant growth protocol is aimed for detecting shade avoidance response. You can grow plants under your favorite condition.

  1. Sprinkle Arabidopsis thaliana seeds on water soaked filter papers in 9 cm Petri dishes and store (stratify) them at 4 °C for four days in the dark.
  2. Transfer these Petri dishes to simulated sun conditions: 80-100 μE photosynthetically active radiation (PAR) and far-red supplement to bring the R:FR ratio .......

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1. Leaf Images Showing Estimates of the Petiole and Leaf Blade Boundary, and Their Measurement Window

One of the most useful features of LeafJ is automated detection of leaf blade/petiole boundary (Figure 1). The LeafJ algorithm works as follows: the built-in ImageJ ParticleAnalyzer functionality is used to find and determine the orientation of the leaves inside of the user selection. For each leaf the width of the leaf is determined along the leaf's entire axis. Then the change .......

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Our "LeafJ" plugin enables measurement of petiole length semi-automatically, increasing throughput nearly 6 times over manual measurement. Petiole length is an important index of SAS and is also a landmark of other phenomena, such as submergence resistance and hyponastic growth17. Therefore this plugin may be useful to a wide range of plant researchers.

Our plugin is implemented in a well-established java-based free software, ImageJ. This enables easy cross-platform installation. E.......

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LeafJ was written by JNM while he was on sabbatical in Dr. Katherine Pollard's lab at the Gladstone Institutes.

This work was supported by a grant from the National Science Foundation (grant number IOS-0923752).


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Name Company Catalog Number Comments
Name of the reagent Company Catalogue number
far-red light LED Orbitec custom made
transparency IKON HSCA/5
scanner Epson Epson Perfection V700 PHOTO
Image J NIH
LeafJ custom
Air Display Avatron Software Inc.
iPad2 Apple Inc.

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