Plant biologists are facing pressure to quantify the response of plants to changing environments and to breed plants that can respond to such changes.
One method of monitoring the response of plants to different environments is by studying their vein network patterns. And to help address the challenge of how to quickly examine a large quantity of leaves, researchers at the Georgia Institute of Technology have developed a software tool that extracts information about macroscopic vein structures directly from leaf images.
’The software can be used to help identify genes responsible for key leaf venation network traits and to test ecological and evolutionary hypotheses regarding the structure and function of leaf venation networks,’ said Joshua Weitz, an assistant professor in the Georgia Tech School of Biology.
The program, called Leaf Extraction and Analysis Framework Graphical User Interface (LEAF GUI), enables scientists and breeders to measure the properties of thousands of veins much more quickly than manual image-analysis tools.
LEAF GUI is a user-assisted software tool that takes an image of a leaf and, following a series of interactive steps to clean up the image, returns information on the structure of that leaf’s vein networks. Structural measurements include the dimensions, position and connectivity of all network veins, and the dimensions, shape and position of all non-vein areas, called areoles.
’The network extraction algorithms in LEAF GUI enable users with no technical expertise in image analysis to quantify the geometry of entire leaf networks – overcoming what was previously a difficult task due to the size and complexity of leaf venation patterns,’ said Charles Price, who worked on the project as a postdoctoral fellow at Georgia Tech and who is now an assistant professor of plant biology at the University of Western Australia.
While the Georgia Tech research team is currently using the software to extract network and areole information from leaves imaged under a wide range of conditions, LEAF GUI could also be used for other purposes, such as leaf classification and description.