The root system is important for plant adaptability to changing environments. Although the importance of the root system is well reported in the research literature there is still a considerable lack of knowledge with regard to the development of root systems per se, and how root system complexity contributes to plant performance under abiotic and biotic stresses. In order to close this knowledge gap, we first investigated the genetic basis of embryonic and post-embryonic maize root systems complexity. We define root complexity as the number of root branching points per soil volume.In subsequent studies, we evaluated the change of maize roots under low and adequate nitrogen levels and determined relationships between root characteristics and agronomic traits. The use of segregating populations (Chapter 1) and a North Carolina III crossing design (Chapter 2) allowed us to map regions in the maize genome involved in the inheritance of maize root complexity. In addition, we were able to estimate for the first time quantitative genetic parameters that characterize maize root complexity.This study was only possible because we developed an image based high-throughput root evaluation system. The application of this evaluation system allowed us to determine root complexity measures with yet unparalleled accuracy.We determined the complexity of a root system by calculating its fractal dimension (FD). We assumed that roots with a higher FD value explore a larger portion of the soil profile than roots with a smaller FD value. In addition, we accessed for the embryonic root system the primary root length (PRL), lateral root length (LRL), lateral seminal root number (LSRN), and lateral root number (LRN), and for the post-embryonic root system the root angle (RTA) and the stem diameter (STD).Two hundred thirty-one recombinant inbred lines (RILs) of the intermated B73×Mo17 (IBM) population were used.We choose this publically available population because all RILs were already genotyped with a large number of molecular markers, and both parental inbreds differ significantly for their above plant architecture. A large number of significant QTL were detected for all traits used to evaluate the embryonic and postembryonic root systems. The number of detected QTL varied between four for FD2 (embryonic root system) and 26 for PRL1 (embryonic root system).Subsets of these QTL were located in regions previously found by other studies or collocated with known and mapped root mutants. We detected no relationship between embryonic and postembryonic root system complexities. Although, many traits of the embryonic root system displayed moderate to high correlation coefficients. In general the same traits evaluated four and eight days after germination were highly related. For the postembryonic root system we found tight associations between FD values determined for images of the same root, which captured different parts of the roots. For the follow up studies, we focused on the most informative 60 IBM RILs, which displayed extreme root complexities. By crossing each RIL with both parental inbreds, we formed a North Carolina Design III population, which allowed us to estimate the degree of dominance involved in the inheritance of root complexity. First, we investigated the relationship between root complexity and root angle and above ground plant traits (Chapter 2). In total, seven above ground traits were measured, i.e., plant (PHT) and ear height (EHT), anthesis-silking interval (ASI), chlorophyll content using a SPAD meter (SPAD), plot yield (YLD) and grain yield per plant (GYT), as well as STD. Some of the most interesting results were the moderate correlations between PHT and EHT with YLD, GWT, FDV and RTA, RTA with YLD and GWT, FDH with FHV, STD with FDV and FDH, and the negative correlation between RTA and STD. We also confirmed previously reported results such as the significant relationship between RTA with grain yield. A large number of significant QTL were detected for all traits, the range varied between three for SPAD, FDV, and FDH, and 11 for ASI. No information was yet available about the average level of dominance for root complexity and root angle. As one of the first studies in this area, we were able to show that these root traits display partial dominance and significant heterosis. Second, we studied the effect of two different nitrogen rates on root fractal dimension, RTA, and STD (Chapter 3). This study is of particular importance due to the strong association between the amount of plant available nitrogen and yield. We found that in our experiments nitrogen treatments did not have a significant effect on any of the measured traits. Moderate to high heritability and genetic correlations were found for most of the measured traits. A large number of significant QTL were detected for all traits varying between two for RTA and five for FDH. This study was possible because we developed a high-throughput image analysis system composed of integrated hardware and software components to evaluate root complexity. Further improvements of this system allowed us to measure other traits like RTA and STD. The application of the system led to more accurate estimates of phenotypic and genotypic parameters. Regarding the several experiments, traits measured for the embryonic root system displayed moderate to high correlations and heritability but no significant correlations were found between embryonic and postembryonic root system. Based on our results, we hypothesized that different mechanisms might be involved in root development for the embryonic and postembryonic root system. When assessing the relationships between root traits and above ground traits several characteristics displayed moderate correlations, e.g., RTA and yield. We also discovered that root complexity and RTA displayed partial dominance and heterosis. This information together with our insights in the genetic architecture of root complexity and its relationship to agronomic performance will play a pivotal role in designing more efficient selection strategies to improve tolerance to abiotic and biotic stresses in maize.
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