Quantifying leaf venation patterns: two-dimensional maps
Article first published online: 30 OCT 2008
© 2008 The Authors. Journal compilation © 2008 Blackwell Publishing Ltd
The Plant Journal
Volume 57, Issue 1, pages 195–205, January 2009
How to Cite
Rolland-Lagan, A.-G., Amin, M. and Pakulska, M. (2009), Quantifying leaf venation patterns: two-dimensional maps. The Plant Journal, 57: 195–205. doi: 10.1111/j.1365-313X.2008.03678.x
- Issue published online: 22 DEC 2008
- Article first published online: 30 OCT 2008
- Received 30 May 2008; revised 5 August 2008; accepted 20 August 2008; published online 30 October 2008.
- network patterns;
- leaf veins;
- spatial data;
The leaf vasculature plays crucial roles in transport and mechanical support. Understanding how vein patterns develop and what underlies pattern variation between species has many implications from both physiological and evolutionary perspectives. We developed a method for extracting spatial vein pattern data from leaf images, such as vein densities and also the sizes and shapes of the vein reticulations. We used this method to quantify leaf venation patterns of the first rosette leaf of Arabidopsis thaliana throughout a series of developmental stages. In particular, we characterized the size and shape of vein network areoles (loops), which enlarge and are split by new veins as a leaf develops. Pattern parameters varied in time and space. In particular, we observed a distal to proximal gradient in loop shape (length/width ratio) which varied over time, and a margin-to-center gradient in loop sizes. Quantitative analyses of vein patterns at the tissue level provide a two-way link between theoretical models of patterning and molecular experimental work to further explore patterning mechanisms during development. Such analyses could also be used to investigate the effect of environmental factors on vein patterns, or to compare venation patterns from different species for evolutionary studies. The method also provides a framework for gathering and overlaying two-dimensional maps of point, line and surface morphological data.