Quantitative analysis of plant root system architecture

The root system of a plant is responsible for supplying it with essential nutrients. The plant’s ability to explore the surrounding soil is largely determined by its root system architecture (RSA), which varies with both genetic and environmental conditions. X-ray micro computed tomography (µCT) is a powerful tool allowing the non-invasive study of the root system architecture of plants grown in natural soil environments, providing both 3D descriptions of root architecture and the ability to make multiple measurements over a period of time. Once volumetric µCT data is acquired, the root system must first be segmented from the surrounding soil environment and then described. Automated and semi-automated software tools can be used to extract roots from µCT images, but current methods for the recovery of RSA traits from the resulting volumetric descriptions are somewhat limited. This thesis presents a novel tool (RooTh) which, given a segmented µCT image, skeletonises the root system and quantifies global and local root traits with minimal user interaction. The computationally inexpensive method used takes advantage of curve-fitting and active contours to find the optimal skeleton and thus evaluate root traits objectively. A small-scale experiment was conducted to validate and compare root traits extracted using the method presented here alongside other 2D imaging tools. The results show a good degree of correlation between the two methods