Challenges and opportunities for quantifying roots and rhizosphere interactions through imaging and image analysis

The morphology of roots and root systems influences the efficiency by which plants acquire nutrients and water, anchor themselves and provide stability to the surrounding soil. Plant genotype and the biotic and abiotic environment significantly influence root morphology, growth and ultimately crop yield. The challenge for researchers interested in phenotyping root systems is, therefore, not just to measure roots and link their phenotype to the plant genotype, but also to understand how the growth of roots is influenced by their environment. This review discusses progress in quantifying root system parameters (e.g. in terms of size, shape and dynamics) using imaging and image analysis technologies and also discusses their potential for providing a better understanding of root:soil interactions. Significant progress has been made in image acquisition techniques, however trade-offs exist between sample throughput, sample size, image resolution and information gained. All of these factors impact on downstream image analysis processes. While there have been significant advances in computation power, limitations still exist in statistical processes involved in image analysis. Utilizing and combining different imaging systems, integrating measurements and image analysis where possible, and amalgamating data will allow researchers to gain a better understanding of root:soil interactions

Challenges in imaging and predictive modeling of rhizosphere processes

Background Plant-soil interaction is central to human food production and ecosystem function. Thus, it is essential to not only understand, but also to develop predictive mathematical models which can be used to assess how climate and soil management practices will affect these interactions. Scope In this paper we review the current developments in structural and chemical imaging of rhizosphere processes within the context of multiscale mathematical image based modeling. We outline areas that need more research and areas which would benefit from more detailed understanding. Conclusions We conclude that the combination of structural and chemical imaging with modeling is an incredibly powerful tool which is fundamental for understanding how plant roots interact with soil. We emphasize the need for more researchers to be attracted to this area that is so fertile for future discoveries. Finally, model building must go hand in hand with experiments. In particular, there is a real need to integrate rhizosphere structural and chemical imaging with modeling for better understanding of the rhizosphere processes leading to models which explicitly account for pore scale processes

The role of the deep roots of perennial cereal kernza in a drying climate

Agricultural lands under annual crop production are prone to degradation and as the climate becomes increasingly variable researchers and farmers alike are looking at resilient crops such as perennial grains to produce food regeneratively. Perennial grain crops support a myriad of ecosystem services, such as reducing nitrate leaching, erosion control and increasing carbon storage. With their deep roots, perennial grain crops like Kernza (Intermediate wheatgrass) could furthermore avoid surface stresses such as droughts. This has however not been investigated before. Therefore we set out to determine the depth of root water uptake (RWU) of this crop and compared the contribution of deep roots before and after anthesis and between a year of adequate water supply (2019) and a year of drought (2018). Natural abundances of 2H and 18O were determined, but were unable to be used properly due to mistakes during sampling. A tracer application showed limited uptake from 2m depth. Furthermore, soil water content measurements were used to inverse model the soil hydraulic parameters under the Kernza crop in Hydrus 1D. Modelling RWU showed that the deep roots (>1m) were responsible for almost 50% of the RWU between anthesis and harvest in 2018, whereas they only contributed between 10% and 15% throughout 2019 and most of 2018 outside of the indicated period. Kernza may thus be an important addition to a farmers toolbox in areas with periodic droughts, but only if grain yields are increased to be competitive with annual cereals or when used as a multifunctional crop for grain, forage and other ecosystem services

Wheat root system architecture and soil moisture distribution in an aggregated soil using neutron computed tomography

Non-invasive techniques are essential to deepen our understanding of root-soil interactions in situ. Neutron computed tomography (NCT) is an example of such techniques that have been successfully used to study these interactions in high resolution. Many of the studies using NCT however, have invariably focused on lupine plants and thus there is limited information available on other more commercially important staple crop plants such as wheat and rice. Also considering the high neutron sensitivity to hydrogen (e.g. water in roots or soil organic matter), nearly all previous in-situ NCT studies have used a relatively homogeneous porous media such as sand, low in soil organic matter and free from soil aggregates, to obtain high-quality images. However to expand the scope of the use of NCT to other more commercially important crops and in less homogenous soils, in this study we focused on wheat root growth in a soil that contained a considerable amount of soil organic matter (SOM) and different sized aggregates. As such, the main aims of this research were (1) to unravel wheat (Triticum aestivum cv. Fielder) root system architecture (RSA) when grown in an aggregated sandy loam soil (<4 mm) with 4% SOM content, (2) Map in 3D, soil water distribution after a brief drying period and (3) to understand how the root system interacts with soil moisture distribution brought about by soil structural heterogeneity. To achieve these, wheat seedlings were grown for 13-days in aluminium tubes (100 mm height and 18 mm diameter) packed with soil and imaged for the first time at the IMAT neutron beamline (in the Rutherford Appleton Laboratory, UK). To the best of our knowledge, this is also the first study to use NCT to study wheat root architectural development. Our study proved that NCT can successfully be used to reveal wheat RSA in a heterogeneous aggregated soils with moderate amounts of SOM. Lateral root growth within the soil column was increased in regions with increased finer soil separates. NCT was also able to successfully map water distribution in a 3D and we show that large macro-aggregates preferentially retained relatively higher soil moisture in comparison to the smaller soil separates within our samples (Fig. 1). This highlights the importance large macro-aggregates in sustainable soil management as they may be able to provide plants water during periodic dry spells. More in situ investigations are required to further understand the impact of different aggregate sizes on RSA and water uptake

Spatial development of transport structures in apple (Malus x domestica Borkh.) fruit

The void network and vascular system are important pathways for the transport of gases, water and solutes in apple fruit (Malus x domestica Borkh). Here we used X-ray micro-tomography at various spatial resolutions to investigate the growth of these transport structures in 3D during fruit development of ‘Jonagold’ apple. The size of the void space and porosity in the cortex tissue increased considerably. In the core tissue, the porosity was consistently lower, and seemed to decrease towards the end of the maturation period. The voids in the core were more narrow and fragmented than the voids in the cortex. Both the void network in the core and in the cortex changed significantly in terms of void morphology. An automated segmentation protocol underestimated the total vasculature length by 9 to 12% in comparison to manually processed images. Vascular networks increased in length from a total of 5 meter at 9 weeks after full bloom, to more than 20 meter corresponding to 5 cm of vascular tissue per cubic centimeter of apple tissue. A high degree of branching in both the void network and vascular system and a complex three-dimensional pattern was observed across the whole fruit. The 3D visualisations of the transport structures may be useful for numerical modeling of organ growth and transport processes in fruit

Plant Growth Modelling and Applications: The Increasing Importance of Plant Architecture in Growth Models

Background Modelling plant growth allows us to test hypotheses and carry out virtual experiments concerning plant growth processes that could otherwise take years in field conditions. The visualization of growth simulations allows us to see directly and vividly the outcome of a given model and provides us with an instructive tool useful for agronomists and foresters, as well as for teaching. Functional-structural (FS) plant growth models are nowadays particularly important for integrating biological processes with environmental conditions in 3-D virtual plants, and provide the basis for more advanced research in plant sciences. Scope In this viewpoint paper, we ask the following questions. Are we modelling the correct processes that drive plant growth, and is growth driven mostly by sink or source activity? In current models, is the importance of soil resources (nutrients, water, temperature and their interaction with meristematic activity) considered adequately? Do classic models account for architectural adjustment as well as integrating the fundamental principles of development? Whilst answering these questions with the available data in the literature, we put forward the opinion that plant architecture and sink activity must be pushed to the centre of plant growth models. In natural conditions, sinks will more often drive growth than source activity, because sink activity is often controlled by finite soil resources or developmental constraints. PMA06 This viewpoint paper also serves as an introduction to this Special Issue devoted to plant growth modelling, which includes new research covering areas stretching from cell growth to biomechanics. All papers were presented at the Second International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA06), held in Beijing, China, from 13-17 November, 2006. Although a large number of papers are devoted to FS models of agricultural and forest crop species, physiological and genetic processes have recently been included and point the way to a new direction in plant modelling researc

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