Resource Magazine July/August 2013 : Page 5

are hard to study in a non-destructive manner, since instru-ments that allow studying a root system in situ do not exist, and destructive methods require ample labor when conducted in a high-throughput fashion. Although there is no dispute about the importance of the root system for the health, resilience, survivability, and yield potential of any plant, the study of root systems is utterly deficient compared to the study of aboveground plant features. Studying the plant’s root system is not merely justified by the intuitive idea that the whole plant should be studied equally intensively; research indicates that, with regard to yield potential, the root might be more important than the aboveground plant! Time is of the essence In 2009, Graeme Hammer and his colleagues published a “fast-breaking paper” in Crop Science titled “Can changes in canopy and/or root system architecture explain historical maize yield trends in the U.S. Corn Belt?” The authors rea-soned that, based on crop models, the root architecture in general and the root angle in particular likely had a more pro-found impact on the maize yield increases over the past decades than aboveground indicators, such as leaf erectness. If this hypothesis is correct, then the study of the root struc-ture of maize (and potentially other crops) needs to be expanded. However, this can only be done if new techniques are developed that allow high-throughput phenotyping of root systems. For this purpose, professors in the departments of Agricultural and Biological Engineering and Crop Sciences at the University of Illinois have developed the Corn Root Imaging Box (CRIB), an instrument that can image up to 600 maize roots per day. This throughput is very important, since a typical maize experiment can consist of thousands of plants. The CRIB features highly diffuse illumination, which prevents shadows from obscuring fine root structures. The digital cameras are computer controlled, as is the system that rotates the roots to acquire lateral images. To obtain highly detailed images, the root images are accompanied by a background image that is taken before the root is inserted into the CRIB. By combining the root and background images in a differential manner, high contrast and sharp images are obtained, ready for processing. Tackling the problem by going backward One of the most complicated tasks in maize root analysis is measuring the complexity of the root system. Intuitively, a highly complex root system would enable the plant to reach water and nutrients easily, provide plant stability, and adapt to the soil matrix surrounding it. There is, howev-er, no useful definition of root complexity, let alone a standard measurement methodology. Even the terminology varies and includes terms such as architecture, morphology, and structure. In spite of the lack of standards, we quantified the elusive complexity of the roots by calculating their fractal dimension, an index that was first defined by mathematician Benoit Mandelbrot in 1975. Later, in their book The Algorithmic Beauty of Plants , Przemyslaw Prusinkiewicz and Aristid Lindenmayer showed how fractals can be used to create artificial plants that have a striking similar-ity to their natural counterparts. In our research, we worked backward. By assuming that the root system resembles a fractal-like structure, we used a technique termed the “box counting method” to calculate the fractal dimension (a number between Corn Root Imaging Box (CRIB). RESOURCE July/August 2013 5

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