The Genetic Analysis of Maize Root Complexity

The development of a healthy root system is an important part of the overall plant development program. Root branching and architecture are strongly linked to plant survival under abiotic (e.g., drought, flooding, nutrient deficiencies) and biotic (e.g., competition among plants, diseases, pests) stress conditions. A limited number of genetic studies is available relating corn root architecture and development with yield, root lodging, and tolerance to stresses under field conditions. This lack of in-depth knowledge is mainly due to the labor-intensive digging required to obtain root samples, the destructive nature of this procedure, and the highly heterogeneous root systems within and among different corn cultivars as a response to a complex soil matrix and diverse environmental signals. In addition, traditional measures such as root length and biomass do not provide an accurate quantification of root branching or complexity
We hypothesize that complex root systems, characterized by a high number of branching points, have a higher probability of finding adequate resources by exploring a larger portion of the soil face than root systems with less complex root systems. The complexity of root systems can be determined by applying the mathematical concept of fractal dimensions (FD). A key feature of fractals is self-similarity at varying scales, i.e., a small part of the structure resembles the whole structure. Fractals are dimensionless and fractal geometry allows for the description, study, and analysis of complex shapes found in nature. In general, FD is more suitable to describe complex natural objects than standard Euclidian geometry. We developed a root imaging device that allows capturing multiple images from rotating adult maize root systems. As a standard procedure we take six images from each root, i.e., one image from each side and two images from above. All images are stored and a dedicated MATLAB software package developed in our laboratory processes and evaluates each image. Using this high throughput root evaluation set up, we investigated the inheritance of the complexity of primary and secondary root systems in maize. Extensive germplasm screening and QTL experiments demonstrated that our technical approach reliably determines genetic differences between genotypes for root complexity and provides, therefore, the technical basis for a systematic investigation of maize root complexity. In addition, we are constantly investigating new algorithms and approaches for their usefulness to evaluate the complexity of root systems.