Plant Networks (Project Inactive)
The Weitz Group has led multiple projects to improve the characterization of the physical structure of plant networks across scales, linking structure with function and uncovering the underlying principles of growth whenever possible. The start of this work began when Dr. Weitz was a postdoc at Princeton University, working with Kiona Ogle and Henry Horn on ontogenetic scaling in woody plants.
The core distinguishing feature of the Weitz Group’s contributions was the development of algorithms and software to extract network information directly from imaging data as a means to overcome the data-deficit in analysis of plant networks. We have released multiple computational tools including LEAF GUI (Price et al., Plant Phys 2011), GiA Roots (Galkovskyi et al., BMC Plant Biology 2012), & Digital Imaging of Root Traits aka DIRT (Das et al., Plant Phys, 2015). Using GiA Roots, we demonstrated the potential heritability of rice root system architecture (RSA) traits and helped identify dozens of QTLs underlying rice RSA. Similarly, using DIRT, we identified the heritability of critical RSA traits using field-based experiments in maize and cowpea.
If you are interested in following-up with this topic, consider exploring the work of a former group member, Prof. Alexander Bucksch who directs the Computational Plant Science Laboratory at the University of Georgia.
Digital Imaging of Root Traits (DIRT)
Digital imaging of root traits (DIRT) measures traits of monocot and dicot roots from digital images. DIRT automates the extraction of root traits by making high-throughput grid computing environment available to end-users without technical training. To learn more, explore the DIRT website or read our papers on this tool published in Plant Methods and Plant Physiology