Technologies for quantifying plant development are underdeveloped relative to technologies for studying and altering genomes. As a result, information about plant gene function inherent in mutant phenotypes or natural genetic variation remains hidden. Even when not hidden, morphological data is often not in a form compatible with computational analysis.

Our Approach to a Solution
We have shown that electronic image acquisition combined with computer-vision algorithms can render some important aspects of plant development into a numerical format compatible with bioinformatics analysis. The midline of an object, such as a root or a stem, contains much of the information about the size and shape of the object. Therefore, isolating midlines is the general first step in our process. Quantifying midline length and curvature distribution is one means of quantifying the size and shape of the object. Currently, completely automated analyses of Arabidopsis root gravitropism and seedling photomorphogenesis are possible using this approach. To give genome-scale impact to the computer-vision approach, throughput of acquisition and analysis must be increased. Two approaches to this end are being pursued.

Robotics to parallelize the data acquisition, grid computing to distribute the computation

Robotically moving a camera between samples such that each is visited and imaged at the desired time interval will increase the rate of data acquisition many-fold. A motion-control gantrydevice consisting of x,y,z computer-controlled linear slides on which a CCD camera will be mounted has been constructed and soon will be installed. The range of motion will be approximately 1 meter in x and y, with positioning resolution of approximately 10 microns. Samples in Petri plates will be held in an LED-illuminated 6 X 6 grid so that 36 experiments can be run in parallel. The resulting images stream to analysis and storage functions - results are returned to the experimenter as well as added to a database. A simplified data flow diagram is shown here.

Enabling the community to perform computer-vision-based experiments on plant development

Increased throughput will also be achieved by enabling many members of the community to perform their own morphometric experiments. A detailed guide to setting up an image acquisition apparatus can be found here. Phytomorph.wisc.edu will also provide access to image-analysis functions that operate on time series of digital images. Users will upload images and receive results electronically. Some analysis programs may be provided for downloading as stand-alone executables.

Feedback, questions, or accessibility issues: spalding@wisc.edu; Last updated: November 13, 2007