High resolution synchrotron imaging of wheat root hairs growing in soil and image based modelling of phosphate uptake

Root hairs are known to be highly important for uptake of sparingly soluble nutrients, particularly in nutrient deficient soils. Development of increasingly sophisticated mathematical models has allowed uptake characteristics to be quantified. However, modelling has been constrained by a lack of methods for imaging live root hairs growing in real soils.We developed a plant growth protocol and used Synchrotron Radiation X-ray Tomographic Microscopy (SRXTM) to uncover the 3D interactions of root hairs in real soil. We developed a model of phosphate uptake by root hairs based directly on the geometry of hairs and associated soil pores as revealed by imaging.Previous modelling studies found that root hairs dominate phosphate uptake. By contrast, our study suggests that hairs and roots contribute equally. We show that uptake by hairs is more localised than by roots and strongly dependent on root hair and aggregate orientation.The ability to image hair-soil interactions enables a step change in modelling approaches, allowing a more realistic treatment of processes at the scale of individual root hairs in soil pores

Root Hair Mutations Displace the Barley Rhizosphere Microbiota

The rhizosphere, the thin layer of soil surrounding and influenced by plant roots, defines a distinct and selective microbial habitat compared to unplanted soil. The microbial communities inhabiting the rhizosphere, the rhizosphere microbiota, engage in interactions with their host plants which span from parasitism to mutualism. Therefore, the rhizosphere microbiota emerges as one of the determinants of yield potential in crops. Studies conducted with different plant species have unequivocally pointed to the host plant as a driver of the microbiota thriving at the root–soil interface. Thus far, the host genetic traits shaping the rhizosphere microbiota are not completely understood. As root hairs play a critical role in resource exchanges between plants and the rhizosphere, we hypothesized that they can act as a determinant of the microbiota thriving at the root–soil interface. To test this hypothesis, we took advantage of barley (Hordeum vulgare) mutant lines contrasting for their root hair characteristics. Plants were grown in two agricultural soils, differentiating in their organic matter contents, under controlled environmental conditions. At early stem elongation rhizosphere specimens were collected and subjected to high-resolution 16S rRNA gene profiling. Our data revealed that the barley rhizosphere microbiota is largely dominated by members of the phyla Bacteroidetes and Proteobacteria, regardless of the soil type and the root hair characteristics of the host plant. Conversely, ecological indices calculated using operational taxonomic units (OTUs) presence, abundance, and phylogeny revealed a significant impact of root hair mutations on the composition of the rhizosphere microbiota. In particular, our data indicate that mutant plants host a reduced-complexity community compared to wild-type genotypes and unplanted soil controls. Congruently, the host genotype explained up to 18% of the variation in ecological distances computed for the rhizosphere samples. Importantly, this effect is manifested in a soil-dependent manner. A closer inspection of the sequencing profiles revealed that the root hair-dependent diversification of the microbiota is supported by a taxonomically narrow group of bacteria, with a bias for members of the orders Actinomycetales, Burkholderiales, Rhizobiales, Sphingomonadales, and Xanthomonadales. Taken together, our results indicate that the presence and function of root hairs are a determinant of the bacterial community thriving in the rhizosphere and their perturbations can markedly impact on the recruitment of individual members of the microbiota

Influence of root and leaf traits on the uptake of nutrients in cover crops

Aims: Cover crops play an important role in soil fertility as they can accumulate large amounts of nutrients. This study aimed at understanding the nutrient uptake capacity of a wide range of cover crops and at assessing the relevance of acquisition strategies. Methods: A field experiment was conducted to characterize 20 species in terms of leaf and root traits. Plant traits were related to nutrient concentration and shoot biomass production with a redundancy analysis. Acquisition strategies were identified using a cluster analysis. Results: Root systems varied greatly among cover crop species. Five nutrient acquisition strategies were delineated. Significant amounts of nutrients (about 120 kg ha−1 of nitrogen, 30 kg ha−1 of phosphorus and 190 kg ha−1 of potassium) were accumulated by the species in a short period. Nutrient acquisition strategies related to high accumulations of nutrients consisted in either high shoot biomass and root mass and dense tissues, or high nutrient concentrations and root length densities. Species with high root length densities showed lower C/N ratios. Conclusions: The same amounts of nutrients were accumulated by groups with different acquisition strategies. However, their nutrient concentrations offer different perspectives in terms of nutrient release for the subsequent crop and nutrient cycling improvement

Mapping soil deformation around plant roots using in vivo 4D X-ray Computed Tomography and Digital Volume Correlation

The mechanical impedance of soils inhibits the growth of plant roots, often being the most significant physical limitation to root system development. Non-invasive imaging techniques have recently been used to investigate the development of root system architecture over time, but the relationship with soil deformation is usually neglected. Correlative mapping approaches parameterised using 2D and 3D image data have recently gained prominence for quantifying physical deformation in composite materials including fibre-reinforced polymers and trabecular bone. Digital Image Correlation (DIC) and Digital Volume Correlation (DVC) are computational techniques which use the inherent material texture of surfaces and volumes, captured using imaging techniques, to map full-field deformation components in samples during physical loading.Here we develop an experimental assay and methodology for four-dimensional, in vivo X-ray Computed Tomography (XCT) and apply a Digital Volume Correlation (DVC) approach to the data to quantify deformation. The method is validated for a field-derived soil under conditions of uniaxial compression, and a calibration study is used to quantify thresholds of displacement and strain measurement. The validated and calibrated approach is then demonstrated for an in vivo test case in which an extending maize root in field-derived soil was imaged hourly using XCT over a growth period of 19 h. This allowed full-field soil deformation data and 3D root tip dynamics to be quantified in parallel for the first time.This method paves the way for comparative studies of contrasting soils and plant genotypes, improving our understanding of the fundamental mechanical processes which influence root system development