Linking root structure to functionality: the impact of root system architecture on citrate-enhanced phosphate uptake

Effects of low-molecular-weight organic acids on the transformation and phosphate retention of iron (hydr)oxides

The retention and mobilization of phosphate in soils are closely associated with the adsorption of iron (hydr)oxides and root exudation of low-molecular-weight organic acids (LMWOAs). This study investigated the role of LMWOAs in phosphate mobilization under incubation and field conditions. LMWOAs-mediated iron (hydr)oxide transformation and phosphate adsorption experiments revealed that the presence of LMWOAs decreased the phosphate adsorption capacity of iron (hydr)oxides by up to ~74 % due to the competition effect, while LMWOAs-induced iron mineral transformation resulted in an approximately six-fold increase in phosphate retention by decreasing the crystallinity and increasing the surface reactivity. Root simulation in rhizobox experiments demonstrated that LMWOAs can alter the contents of different extractable phosphate species and iron components, leading to 10 % ~ 30 % decreases in available phosphate in the near root region of two tested soils. Field experiments showed that crop covering between mango tree rows promoted the exudation of LMWOAs from mango roots. In addition, crop covering increased the contents of total phosphate and available phosphate by 9.08 % ~ 61.20 % and 34.33 % ~ 147.33 % in the rhizosphere soils of mango trees, respectively. These findings bridge the microscale and field scale to understand the delicate LMWOAs-mediated balance between the retention and mobilization of phosphate on iron (hydr)oxide surface, thereby providing important implications for mitigating the low utilization efficiency of phosphate in iron-rich soils.

Pseudomonas hefeiensis sp. nov., isolated from the rhizosphere of multiple cash crops in China

Three bacterial strains, FP250T, FP821, and FP53, were isolated from the rhizosphere soil of oilseed rape, licorice, and habanero pepper in Anhui Province, Xinjiang Uygur Autonomous Region, and Jiangsu Province, PR China, respectively. All strains were shown to grow at 4-37 °C and pH 6.0-9.0, and in the presence of 0-4.0 % (w/v) NaCl. Phylogenetic analyses based on 16S rRNA gene sequences or housekeeping genes (16S rRNA, gyrB, rpoB, and rpoD) and phylogenomic analysis showed that strains FP250T, FP821, and FP53 belong to the genus Pseudomonas, and are closely related to Pseudomonas kilonensis DSM 13647T, Pseudomonas brassicacearum JCM 11938T, Pseudomonas viciae 11K1T, and Pseudomonas thivervalensis DSM 13194T. The DNA G+C content of strain FP205T was 59.8 mol%. The average nucleotide identity and digital DNA-DNA hybridization values of strain FP205T with the most closely related strain were 93.2 % and 51.4 %, respectively, which is well below the threshold for species differentiation. Strain FP205T contained summed feature 3 (C16 : 1  ω6c and/or C16 : 1  ω7c), summed feature 8 (C18 : 1  ω7c and/or C18 : 1  ω6c) as major fatty acids, and diphosphatidylglycerol along with phosphatidylethanolamine and aminophospholipid as major polar lipids. The predominant isoprenoid quinone was ubiquinone-9. Based on these phenotypic, phylogenetic, and chemotaxonomic results, strain FP205T represents a novel species of the genus Pseudomonas, for which the name Pseudomonas hefeiensis sp. nov. is proposed. The type strain is FP205T (=ACCC 62447T=JCM 35687T).

Location: root architecture structures rhizosphere microbial associations

Root architectural phenotypes are promising targets for crop breeding, but root architectural effects on microbial associations in agricultural fields are not well understood. Architecture determines the location of microbial associations within root systems, which, when integrated with soil vertical gradients, determines the functions and the metabolic capability of rhizosphere microbial communities. We argue that variation in root architecture in crops has important implications for root exudation, microbial recruitment and function, and the decomposition and fate of root tissues and exudates. Recent research has shown that the root microbiome changes along root axes and among root classes, that root tips have a unique microbiome, and that root exudates change within the root system depending on soil physicochemical conditions. Although fresh exudates are produced in larger amounts in root tips, the rhizosphere of mature root segments also plays a role in influencing soil vertical gradients. We argue that more research is needed to understand specific root phenotypes that structure microbial associations and discuss candidate root phenotypes that may determine the location of microbial hotspots within root systems with relevance to agricultural systems.

3D U-Net Segmentation Improves Root System Reconstruction from 3D MRI Images in Automated and Manual Virtual Reality Work Flows

Magnetic resonance imaging (MRI) is used to image root systems grown in opaque soil. However, reconstruction of root system architecture (RSA) from 3-dimensional (3D) MRI images is challenging. Low resolution and poor contrast-to-noise ratios (CNRs) hinder automated reconstruction. Hence, manual reconstruction is still widely used. Here, we evaluate a novel 2-step work flow for automated RSA reconstruction. In the first step, a 3D U-Net segments MRI images into root and soil in super-resolution. In the second step, an automated tracing algorithm reconstructs the root systems from the segmented images. We evaluated the merits of both steps for an MRI dataset of 8 lupine root systems, by comparing the automated reconstructions to manual reconstructions of unaltered and segmented MRI images derived with a novel virtual reality system. We found that the U-Net segmentation offers profound benefits in manual reconstruction: reconstruction speed was doubled (+97%) for images with low CNR and increased by 27% for images with high CNR. Reconstructed root lengths were increased by 20% and 3%, respectively. Therefore, we propose to use U-Net segmentation as a principal image preprocessing step in manual work flows. The root length derived by the tracing algorithm was lower than in both manual reconstruction methods, but segmentation allowed automated processing of otherwise not readily usable MRI images. Nonetheless, model-based functional root traits revealed similar hydraulic behavior of automated and manual reconstructions. Future studies will aim to establish a hybrid work flow that utilizes automated reconstructions as scaffolds that can be manually corrected.

Perennial grass root system specializes for multiple resource acquisitions with differential elongation and branching patterns

Roots optimize the acquisition of limited soil resources, but relationships between root forms and functions have often been assumed rather than demonstrated. Furthermore, how root systems co-specialize for multiple resource acquisitions is unclear. Theory suggests that trade-offs exist for the acquisition of different resource types, such as water and certain nutrients. Measurements used to describe the acquisition of different resources should then account for differential root responses within a single system. To demonstrate this, we grew Panicum virgatum in split-root systems that vertically partitioned high water availability from nutrient availability so that root systems must absorb the resources separately to fully meet plant demands. We evaluated root elongation, surface area, and branching, and we characterized traits using an order-based classification scheme. Plants allocated approximately 3/4th of primary root length towards water acquisition, whereas lateral branches were progressively allocated towards nutrients. However, root elongation rates, specific root length, and mass fraction were similar. Our results support the existence of differential root functioning within perennial grasses. Similar responses have been recorded in many plant functional types suggesting a fundamental relationship. Root responses to resource availability can be incorporated into root growth models via maximum root length and branching interval parameters.

Nitrogen Fertilizer Type and Genotype as Drivers of P Acquisition and Rhizosphere Microbiota Assembly in Juvenile Maize Plants

Phosphorus (P) is an essential nutrient for plant growth and development, as well as an important factor limiting sustainable maize production. Targeted nitrogen (N) fertilization in the form of ammonium has been shown to positively affect Pi uptake under P-deficient conditions compared to nitrate. Nevertheless, its profound effects on root traits, P uptake, and soil microbial composition are still largely unknown. In this study, two maize genotypes F160 and F7 with different P sensitivity were used to investigate phosphorus-related root traits such as root hair length, root diameter, AMF association, and multiple P efficiencies under P limitation when fertilized either with ammonium or nitrate. Ammonium application improved phosphorous acquisition efficiency in the F7 genotype but not in F160, suggesting that the genotype plays an important role in how a particular N form affects P uptake in maize. Additionally, metabarcoding data showed that young maize roots were able to promote distinct microbial taxa, such as arbuscular mycorrhizal fungi, when fertilized with ammonium. Overall, the results suggest that the form of chemical nitrogen fertilizer can be instrumental in selecting beneficial microbial communities associated with phosphorus uptake and maize plant fitness.

A 3D image-based modelling approach for understanding spatiotemporal processes in phosphorus fertiliser dissolution, soil buffering and uptake by plant roots

Phosphorus (P) is a key yield-limiting nutrient for crops, but the main source of P fertiliser is finite. Therefore, efficient fertilisation is crucial. Optimal P application requires understanding of the dynamic processes affecting P availability to plants, including fertiliser dissolution rate and soil buffer power. However, standard soil testing methods sample at fixed time points, preventing a mechanistic understanding of P uptake variability. We used image-based modelling to investigate the effects of fertiliser dissolution rate and soil buffer power on P uptake by wheat roots imaged using X-ray CT. We modelled uptake based on 1-day, 1-week, and 14-week dissolution of a fixed quantity of total P for two common soil buffer powers. We found rapid fertiliser dissolution increased short-term root uptake, but total uptake from 1-week matched 1-day dissolution. We quantified the large effects root system architecture had on P uptake, finding that there were trade-offs between total P uptake and uptake per unit root length, representing a carbon investment/phosphorus uptake balance. These results provide a starting point for predictive modelling of uptake from different P fertilisers in different soils. With the addition of further X-ray CT image datasets and a wider range of conditions, our simulation approach could be developed further for rapid trialling of fertiliser-soil combinations to inform field-scale trials or management.

Abandoned agriculture soil can be recultivated by promoting biological phosphorus fertility when amended with nano-rock phosphate and suitable bacterial inoculant

In semi-arid regions, post-restoration vegetation recovery on abandoned agricultural lands often fails due to inherently low organic matter content and poor soil fertility conditions, including phosphorus (P). As such, amending these soils with controlled release P fertilizer, especially with suitable P solubilizing bacteria (PSB) may promote plant growth and productivity by stimulating biological P fertility. To this aim, a pot study was performed to evaluate the agronomic potential of maize and soil biological P pools, using encapsulated (ENRP) and non-encapsulated (NRP) nano-rock phosphate as the P fertilizer source, on reclaimed agricultural soil in the presence and absence of PSB inoculant. The experiment was setup following a 3 × 2 factorial arrangement with four replicates. Without PSB, NRP treatment showed marginal positive effects on plant growth, P nutrition and P use efficiency (PUE) compared to control treatment. Although larger gains with NRP treatment were more noticeable under PSB inoculation, ENRP was the most convenient slow-release P fertilizer, increasing plant growth, P nutrition and grain yield compared to all treatments. Importantly, PSB inoculation with ENRP resulted in significantly higher increase in soil CaCl2-P (8.91 mg P kg soil-1), citrate-P (26.98 mg P kg soil-1), enzyme-P (18.98 mg P kg soil-1), resin-P (11.41 mg P kg soil-1), and microbial-P (18.94 mg P kg soil-1), when compared to all treatment combinations. Although a decrease in soil HCl-P content was observed with both types of P fertilizer, significant differences were found only with PSB inoculation. A significant increase in soil biological P pools could be due to the higher specific area and crystalline structure of nano materials, providing increased number of active sites for PSB activity in the presence of biobased encapsulated shell. Furthermore, the increase in PSB abundance, higher root carboxylate secretions, and decreased rhizosphere pH in response to nano-structured P fertilizer, implies greater extension of rhizosphere promoting greater P mobilization and/or solubilization, particularly under PSB inoculated conditions. We conclude that cropping potential of abandoned agricultural lands can be enhanced by the use of nano-rock phosphate in combination with PSB inoculant, establishing a favorable micro-environment for higher plant growth and biochemical P fertility.

Responses of Fine Roots at Different Soil Depths to Different Thinning Intensities in a Secondary Forest in the Qinling Mountains, China

Fine roots make critical contributions to carbon stocks and terrestrial productivity, and fine roots with different diameters exhibit functional heterogeneity. However, the changed characteristics of fine roots with different diameters at different soil depths following thinning disturbances are poorly understood. We investigated the biomass, production, mortality and turnover rate of <0.5 mm, 0.5−1 mm, and 1−2 mm fine roots at 0−20 cm, 20−40 cm, and 40−60 cm soil depths under five thinning intensities (0%, 15%, 30%, 45%, and 60%) in a secondary forest in the Qinling Mountains. The biomass, production and turnover rate of <0.5 mm fine roots fluctuated with increasing thinning intensities, while the 0.5−1 mm and 1−2 mm fine-root biomass significantly decreased. The thinning intensities had no effects on the fine-root necromass or mortality. The change in the fine-root characteristics in deeper soils was more sensitive to the thinning intensities. The principal component analysis results showed that increased <0.5 mm fine-root biomass and production resulted from increased shrub and herb diversity and biomass and decreased soil nutrient availability, stand volume, and litter biomass, whereas the 0.5−1 mm and 1−2 mm fine-root biomass showed the opposite trends and changes. Our results suggest that different thinning intensities exhibit varied influential mechanisms on the changed characteristics of fine roots with different diameters.

X-ray microscopy enables multiscale high-resolution 3D imaging of plant cells, tissues, and organs

Capturing complete internal anatomies of plant organs and tissues within their relevant morphological context remains a key challenge in plant science. While plant growth and development are inherently multiscale, conventional light, fluorescence, and electron microscopy platforms are typically limited to imaging of plant microstructure from small flat samples that lack a direct spatial context to, and represent only a small portion of, the relevant plant macrostructures. We demonstrate technical advances with a lab-based X-ray microscope (XRM) that bridge the imaging gap by providing multiscale high-resolution three-dimensional (3D) volumes of intact plant samples from the cell to the whole plant level. Serial imaging of a single sample is shown to provide sub-micron 3D volumes co-registered with lower magnification scans for explicit contextual reference. High-quality 3D volume data from our enhanced methods facilitate sophisticated and effective computational segmentation. Advances in sample preparation make multimodal correlative imaging workflows possible, where a single resin-embedded plant sample is scanned via XRM to generate a 3D cell-level map, and then used to identify and zoom in on sub-cellular regions of interest for high-resolution scanning electron microscopy. In total, we present the methodologies for use of XRM in the multiscale and multimodal analysis of 3D plant features using numerous economically and scientifically important plant systems.

Arbuscular Mycorrhizal Fungus Alters Root System Architecture in Camellia sinensis L. as Revealed by RNA-Seq Analysis

Arbuscular mycorrhizal fungus (AMF), forming symbiosis with most terrestrial plants, strongly modulates root system architecture (RSA), which is the main characteristic of root in soil, to improve plant growth and development. So far, the studies of AMF on tea plant seedlings are few and the relevant molecular mechanism is not deciphered. In this study, the 6-month-old cutting seedlings of tea plant cultivar "Wancha No.4" were inoculated with an AMF isolate, Rhizophagus intraradices BGC JX04B and harvested after 6 months of growth. The indexes of RSA and sugar contents in root were determined. The transcriptome data in root tips of mycorrhizal and non-mycorrhizal cutting seedlings were obtained by RNA-sequence (Seq) analysis. The results showed that AMF significantly decreased plant growth, but increased the sucrose content in root and the higher classes of lateral root (LR) formation (third and fourth LR). We identified 2047 differentially expressed genes (DEGs) based on the transcriptome data, and DEGs involved in metabolisms of phosphorus (42 DEGs), sugar (39), lipid (67), and plant hormones (39) were excavated out. Variation partitioning analysis showed all these four categories modulated the RSA. In phosphorus (P) metabolism, the phosphate transport and release (DEGs related to purple acid phosphatase) were promoted by AMF inoculation, while DEGs of sugar transport protein in sugar metabolism were downregulated. Lipid metabolism might not be responsible for root branching but for AMF propagation. With respect to phytohormones, DEGs of auxin (13), ethylene (14), and abscisic acid (5) were extensively affected by AMF inoculation, especially for auxin and ethylene. The further partial least squares structural equation modeling analysis indicated that pathways of P metabolism and auxin, as well as the direct way of AMF inoculation, were of the most important in AMF promoting root branching, while ethylene performed a negative role. Overall, our data revealed the alterations of genome-wide gene expression in tea plant roots after inoculation with AMF and provided a molecular basis for the regulatory mechanism of RSA (mainly root branching) changes induced by AMF.

Resources for image-based high-throughput phenotyping in crops and data sharing challenges

High-throughput phenotyping (HTP) platforms are capable of monitoring the phenotypic variation of plants through multiple types of sensors, such as red green and blue (RGB) cameras, hyperspectral sensors, and computed tomography, which can be associated with environmental and genotypic data. Because of the wide range of information provided, HTP datasets represent a valuable asset to characterize crop phenotypes. As HTP becomes widely employed with more tools and data being released, it is important that researchers are aware of these resources and how they can be applied to accelerate crop improvement. Researchers may exploit these datasets either for phenotype comparison or employ them as a benchmark to assess tool performance and to support the development of tools that are better at generalizing between different crops and environments. In this review, we describe the use of image-based HTP for yield prediction, root phenotyping, development of climate-resilient crops, detecting pathogen and pest infestation, and quantitative trait measurement. We emphasize the need for researchers to share phenotypic data, and offer a comprehensive list of available datasets to assist crop breeders and tool developers to leverage these resources in order to accelerate crop breeding.

Plant phosphorus-acquisition and -use strategies affect soil carbon cycling

Increased anthropogenic nitrogen (N) deposition is driving N-limited ecosystems towards phosphorus (P) limitation. Plants have evolved strategies to respond to P limitation which affect N cycling in plant-soil systems. A comprehensive understanding of how plants with efficient P-acquisition or -use strategies influence carbon (C) and N cycling remains elusive. We highlight how P-acquisition/-use strategies, particularly the release of carboxylates into the rhizosphere, accelerate soil organic matter (SOM) decomposition and soil N mineralisation by destabilising aggregates and organic-mineral associations. We advocate studying the effects of P-acquisition/-use strategies on SOM formation, directly or through microbial turnover.

Biochar and Arbuscular Mycorrhizal Fungi Play Different Roles in Enabling Maize to Uptake Phosphorus

The addition of biochar alters soil habitats and has an active effect on the symbiotic relationship between plants and mycorrhizal fungi. However, it is still unclear whether this effect alters the strategy of phosphorus uptake by plants. Therefore, pot experiments were conducted in order to investigate the effects of mycorrhizal colonization and biochar addition on plant growth, phosphorus absorption, and rhizosphere Olsen-P supply in maize under two moisture conditions—60% field water capacity (FWC) and 40% FWC. It was found that the addition of biochar increased the colonization rate of arbuscular mycorrhizal fungi (AMF), and all the addition treatments significantly improved maize biomass, peroxidase (POD) activity, chlorophyll content, photosynthetic rate (Pn), plant height, leaf area, shoot phosphorus content, and phosphorus uptake by maize under the two moisture conditions. In addition, biochar had significant effects on root morphology under both water conditions, whereas AMF only showed significant effects under water stress. In contrast, phosphatase activity and microbial activity were higher in the AMF inoculation treatment than in the biochar addition treatment, and the trend was more significant under water stress. Principal component analysis (PCA) showed that root morphology, rhizosphere microbial activity, phosphatase activity, available phosphorus content, and shoot phosphorus content had significant positive correlations. It was concluded that biochar aids plant uptake of phosphorus mainly by regulating root morphology and plant phosphorus content, whereas the large mycelium of AMF enhances microbial activity and phosphatase activity, thereby enabling more efficient phosphorus uptake by maize, especially under conditions of water stress.

Overcoming the Challenges to Enhancing Experimental Plant Biology With Computational Modeling

The study of complex biological systems necessitates computational modeling approaches that are currently underutilized in plant biology. Many plant biologists have trouble identifying or adopting modeling methods to their research, particularly mechanistic mathematical modeling. Here we address challenges that limit the use of computational modeling methods, particularly mechanistic mathematical modeling. We divide computational modeling techniques into either pattern models (e.g., bioinformatics, machine learning, or morphology) or mechanistic mathematical models (e.g., biochemical reactions, biophysics, or population models), which both contribute to plant biology research at different scales to answer different research questions. We present arguments and recommendations for the increased adoption of modeling by plant biologists interested in incorporating more modeling into their research programs. As some researchers find math and quantitative methods to be an obstacle to modeling, we provide suggestions for easy-to-use tools for non-specialists and for collaboration with specialists. This may especially be the case for mechanistic mathematical modeling, and we spend some extra time discussing this. Through a more thorough appreciation and awareness of the power of different kinds of modeling in plant biology, we hope to facilitate interdisciplinary, transformative research.