The stellar and sub-stellar IMF of simple and composite populations

The current knowledge on the stellar IMF is documented. It appears to become top-heavy when the star-formation rate density surpasses about 0.1Msun/(yr pc^3) on a pc scale and it may become increasingly bottom-heavy with increasing metallicity and in increasingly massive early-type galaxies. It declines quite steeply below about 0.07Msun with brown dwarfs (BDs) and very low mass stars having their own IMF. The most massive star of mass mmax formed in an embedded cluster with stellar mass Mecl correlates strongly with Mecl being a result of gravitation-driven but resource-limited growth and fragmentation induced starvation. There is no convincing evidence whatsoever that massive stars do form in isolation. Various methods of discretising a stellar population are introduced: optimal sampling leads to a mass distribution that perfectly represents the exact form of the desired IMF and the mmax-to-Mecl relation, while random sampling results in statistical variations of the shape of the IMF. The observed mmax-to-Mecl correlation and the small spread of IMF power-law indices together suggest that optimally sampling the IMF may be the more realistic description of star formation than random sampling from a universal IMF with a constant upper mass limit. Composite populations on galaxy scales, which are formed from many pc scale star formation events, need to be described by the integrated galactic IMF. This IGIMF varies systematically from top-light to top-heavy in dependence of galaxy type and star formation rate, with dramatic implications for theories of galaxy formation and evolution.Comment: 167 pages, 37 figures, 3 tables, published in Stellar Systems and Galactic Structure, Vol.5, Springer. This revised version is consistent with the published version and includes additional references and minor additions to the text as well as a recomputed Table 1. ISBN 978-90-481-8817-

Accelerating root system phenotyping of seedlings through a computer-assisted processing pipeline

Background: There are numerous systems and techniques to measure the growth of plant roots. However, phenotyping large numbers of plant roots for breeding and genetic analyses remains challenging. One major difficulty is to achieve high throughput and resolution at a reasonable cost per plant sample. Here we describe a cost-effective root phenotyping pipeline, on which we perform time and accuracy benchmarking to identify bottlenecks in such pipelines and strategies for their acceleration. Results: Our root phenotyping pipeline was assembled with custom software and low cost material and equipment. Results show that sample preparation and handling of samples during screening are the most time consuming task in root phenotyping. Algorithms can be used to speed up the extraction of root traits from image data, but when applied to large numbers of images, there is a trade-off between time of processing the data and errors contained in the database. Conclusions: Scaling-up root phenotyping to large numbers of genotypes will require not only automation of sample preparation and sample handling, but also efficient algorithms for error detection for more reliable replacement of manual interventions

Measuring root system traits of wheat in 2D images to parameterize 3D root architecture models

Background and aimsThe main difficulty in the use of 3D root architecture models is correct parameterization. We evaluated distributions of the root traits inter-branch distance, branching angle and axial root trajectories from contrasting experimental systems to improve model parameterization.MethodsWe analyzed 2D root images of different wheat varieties (Triticum aestivum) from three different sources using automatic root tracking. Model input parameters and common parameter patterns were identified from extracted root system coordinates. Simulation studies were used to (1) link observed axial root trajectories with model input parameters (2) evaluate errors due to the 2D (versus 3D) nature of image sources and (3) investigate the effect of model parameter distributions on root foraging performance.ResultsDistributions of inter-branch distances were approximated with lognormal functions. Branching angles showed mean values <90°. Gravitropism and tortuosity parameters were quantified in relation to downwards reorientation and segment angles of root axes. Root system projection in 2D increased the variance of branching angles. Root foraging performance was very sensitive to parameter distribution and variance.Conclusions2D image analysis can systematically and efficiently analyze root system architectures and parameterize 3D root architecture models. Effects of root system projection (2D from 3D) and deflection (at rhizotron face) on size and distribution of particular parameters are potentially significant

An automated, cost-effective and scalable, flood-and-drain based root phenotyping system for cereals

Background: Genetic studies on the molecular mechanisms of the regulation of root growth require the characterisation of a specific root phenotype to be linked with a certain genotype. Such studies using classical labour-intensive methods are severely hindered due to the technical limitations that are associated with the impeded observation of the root system of a plant during its growth. The aim of the research presented here was to develop a reliable, cost-effective method for the analysis of a plant root phenotype that would enable the precise characterisation of the root system architecture of cereals. Results: The presented method describes a complete system for automatic supplementation and continuous sensing of culture solution supplied to plants that are grown in transparent tubes containing a solid substrate. The presented system comprises the comprehensive pipeline consisting of a modular-based and remotely-controlled plant growth system and customized imaging setup for root and shoot phenotyping. The system enables an easy extension of the experimental capacity in order to form a combined platform that is comprised of parallel modules, each holding up to 48 plants. The conducted experiments focused on the selection of the most suitable conditions for phenotyping studies in barley: an optimal size of the glass beads, diameters of the acrylic tubes, composition of a medium, and a rate of the medium flow. Conclusions: The developed system enables an efficient, accurate and highly repeatable analysis of the morphological features of the root system of cereals. Because a simple and fully-automated control system is used, the experimental conditions can easily be normalised for different species of cereals. The scalability of the module-based system allows its capacity to be adjusted in order to meet the requirements of a particular experiment