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

Summary

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.

Abstract

High throughput phenotyping (phenomics) is a powerful tool for linking genes to their functions (see review¹ and recent examples^2-4). 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 tools^5,6. 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.

Protocol

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 to 1.86. Use long day conditions (16 hr light/8 hr dark) and constant temperature of 22 °C. Incubate in this condition for three days to allow the....

Results

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 .......

Discussion

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.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
far-red light LED	Orbitec	custom made
transparency	IKON	HSCA/5
scanner	Epson	Epson Perfection V700 PHOTO
Image J	NIH		http://rsbweb.nih.gov/ij/
LeafJ	custom		http://www.openwetware.org/wiki/Maloof_Lab
Air Display	Avatron Software Inc.		http://avatron.com/
iPad2	Apple Inc.		http://www.apple.com/