Integration of root phenes for soil resource acquisition

Cortical parenchyma wall width regulates root metabolic cost and maize performance under suboptimal water availability

We describe how increased root cortical parenchyma wall width (CPW) can improve tolerance to drought stress in maize by reducing the metabolic costs of soil exploration. Significant variation (1.0-5.0 µm) for CPW was observed in maize germplasm. The functional-structural model RootSlice predicts that increasing CPW from 2 µm to 4 µm is associated with a ~15% reduction in root cortical cytoplasmic volume, respiration rate, and nitrogen content. Analysis of genotypes with contrasting CPW grown with and without water stress in the field confirms that increased CPW is correlated with an ~32-42% decrease in root respiration. Under water stress in the field, increased CPW is correlated with 125% increased stomatal conductance, 325% increased leaf CO2 assimilation rate, 73-78% increased shoot biomass, and 92-108% increased yield. CPW was correlated with leaf mesophyll midrib parenchyma wall width, indicating pleiotropy. Genome-wide association study analysis identified candidate genes underlying CPW. OpenSimRoot modeling predicts that a reduction in root respiration due to increased CPW would also benefit maize growth under suboptimal nitrogen, which requires empirical testing. We propose CPW as a new phene that has utility under edaphic stress meriting further investigation.

Integrating GWAS with a gene co-expression network better prioritizes candidate genes associated with root metaxylem phenes in maize

Root metaxylems are phenotypically diverse structures whose function is particularly important under drought stress. Significant research has dissected the genetic machinery underlying metaxylem phenotypes in dicots, but that of monocots are relatively underexplored. In maize (Zea mays), a robust pipeline integrated a genome-wide association study (GWAS) of root metaxylem phenes under well-watered and water-stress conditions with a gene co-expression network to prioritize the strongest gene candidates. We identified 244 candidate genes by GWAS, of which 103 reside in gene co-expression modules most relevant to xylem development. Several candidate genes may be involved in biosynthetic processes related to the cell wall, hormone signaling, oxidative stress responses, and drought responses. Of those, six gene candidates were detected in multiple root metaxylem phenes in both well-watered and water-stress conditions. We posit that candidate genes that are more essential to network function based on gene co-expression (i.e., hubs or bottlenecks) should be prioritized and classify 33 essential genes for further investigation. Our study demonstrates a new strategy for identifying promising gene candidates and presents several gene candidates that may enhance our understanding of vascular development and responses to drought in cereals.

Plant root mechanisms and their effects on carbon and nutrient accumulation in desert ecosystems under changes in land use and climate

Deserts represent key carbon reservoirs, yet as these systems are threatened this has implications for biodiversity and climate change. This review focuses on how these changes affect desert ecosystems, particularly plant root systems and their impact on carbon and mineral nutrient stocks. Desert plants have diverse root architectures shaped by water acquisition strategies, affecting plant biomass and overall carbon and nutrient stocks. Climate change can disrupt desert plant communities, with droughts impacting both shallow and deep-rooted plants as groundwater levels fluctuate. Vegetation management practices, like grazing, significantly influence plant communities, soil composition, root microorganisms, biomass, and nutrient stocks. Shallow-rooted plants are particularly susceptible to climate change and human interference. To safeguard desert ecosystems, understanding root architecture and deep soil layers is crucial. Implementing strategic management practices such as reducing grazing pressure, maintaining moderate harvesting levels, and adopting moderate fertilization can help preserve plant-soil systems. Employing socio-ecological approaches for community restoration enhances carbon and nutrient retention, limits desert expansion, and reduces CO2 emissions. This review underscores the importance of investigating belowground plant processes and their role in shaping desert landscapes, emphasizing the urgent need for a comprehensive understanding of desert ecosystems.

Unlocking dynamic root phenotypes for simultaneous enhancement of water and phosphorus uptake

Phosphorus (P) and water are crucial for plant growth, but their availability is challenged by climate change, leading to reduced crop production and global food security. In many agricultural soils, crop productivity is confronted by both water and P limitations. The diminished soil moisture decreases available P due to reduced P diffusion, and inadequate P availability diminishes tissue water status through modifications in stomatal conductance and a decrease in root hydraulic conductance. P and water display contrasting distributions in the soil, with P being concentrated in the topsoil and water in the subsoil. Plants adapt to water- and P-limited environments by efficiently exploring localized resource hotspots of P and water through the adaptation of their root system. Thus, developing cultivars with improved root architecture is crucial for accessing and utilizing P and water from arid and P-deficient soils. To meet this goal, breeding towards multiple advantageous root traits can lead to better cultivars for water- and P-limited environments. This review discusses the interplay of P and water availability and highlights specific root traits that enhance the exploration and exploitation of optimal resource-rich soil strata while reducing metabolic costs. We propose root ideotype models, including 'topsoil foraging', 'subsoil foraging', and 'topsoil/subsoil foraging' for maize (monocot) and common bean (dicot). These models integrate beneficial root traits and guide the development of water- and P-efficient cultivars for challenging environments.

The nitrate transporter-sensor MtNPF6.8 regulates the branched chain amino acid/pantothenate metabolic pathway in barrel medic (Medicago truncatula Gaertn.) root tip

Nitrogen is the most limiting nutrient for plants, and it is preferentially absorbed in the form of nitrate by roots, which adapt to nitrate fluctuations by remodelling their architecture. Although core mechanisms of the response to nitrate availability are relatively well-known, signalling events controlling root growth and architecture have not all been identified, in particular in Legumes. However, the developmental effect of nitrate in Legumes is critical since external nitrate not only regulates root architecture but also N2-fixing nodule development. We have previously shown that in barrel medic (Medicago truncatula), the nitrate transporter MtNPF6.8 is required for nitrate sensitivity in root tip. However, uncertainty remains as to whether nitrogen metabolism itself is involved in the MtNPF6.8-mediated response. Here, we examine the metabolic effects of MtNPF6.8-dependent nitrate signalling using metabolomics and proteomics in WT and mtnpf6.8 root tips in presence or absence of nitrate. We found a reorchestration of metabolism due to the mutation, in favour of the branched chain amino acids/pantothenate metabolic pathway, and lipid catabolism via glyoxylate. That is, the mtnpf6.8 mutation was likely associated with a specific rerouting of acetyl-CoA production (glyoxylic cycle) and utilisation (pantothenate and branched chain amino acid synthesis). In agreement with our previous findings, class III peroxidases were confirmed as the main protein class responsive to nitrate, although in an MtNPF6.8-independent fashion. Our data rather suggest the involvement of other pathways within mtnpf6.8 root tips, such as Ca2+ signalling or cell wall methylation.

Root phenotypes for improved nitrogen capture

Background

Suboptimal nitrogen availability is a primary constraint for crop production in low-input agroecosystems, while nitrogen fertilization is a primary contributor to the energy, economic, and environmental costs of crop production in high-input agroecosystems. In this article we consider avenues to develop crops with improved nitrogen capture and reduced requirement for nitrogen fertilizer.

Scope

Intraspecific variation for an array of root phenotypes has been associated with improved nitrogen capture in cereal crops, including architectural phenotypes that colocalize root foraging with nitrogen availability in the soil; anatomical phenotypes that reduce the metabolic costs of soil exploration, improve penetration of hard soil, and exploit the rhizosphere; subcellular phenotypes that reduce the nitrogen requirement of plant tissue; molecular phenotypes exhibiting optimized nitrate uptake kinetics; and rhizosphere phenotypes that optimize associations with the rhizosphere microbiome. For each of these topics we provide examples of root phenotypes which merit attention as potential selection targets for crop improvement. Several cross-cutting issues are addressed including the importance of soil hydrology and impedance, phenotypic plasticity, integrated phenotypes, in silico modeling, and breeding strategies using high throughput phenotyping for co-optimization of multiple phenes.

Conclusions

Substantial phenotypic variation exists in crop germplasm for an array of root phenotypes that improve nitrogen capture. Although this topic merits greater research attention than it currently receives, we have adequate understanding and tools to develop crops with improved nitrogen capture. Root phenotypes are underutilized yet attractive breeding targets for the development of the nitrogen efficient crops urgently needed in global agriculture.

Plasticity of root hair and rhizosheath traits and their relationship to phosphorus uptake in sorghum

Sorghum is an essential crop for resilient and adaptive responses to climate change. The root systems of crop plants significantly contribute to the tolerance of abiotic stresses. There is little information on sorghum genotypes' root systems and plasticity to external P supply. In this paper, we investigated the variations in root systems, as well as the responses, trait relationships, and plasticity of two sorghum genotypes (Naga Red and Naga White), popularly grown in Ghana, to five external P concentrations ([P]ext): 0, 100, 200, 300, and 400 mg P kg-1 soil. Sorghum plants were grown in greenhouse pots and harvested for root trait measurements at the five-leaf and growing point differentiation (GPD) developmental stages. The plants were responsive to [P]ext and formed rhizosheaths. The two genotypes showed similar characteristics for most of the traits measured but differed significantly in total and lateral root lengths in favor of the red genotype. For example, at the five-leaf growth stage, the lateral root length of the red and white genotypes was 22.8 and 16.2 cm, respectively, but 124 and 88.9 cm, at the GPD stage. The responses and plasticity of the root system traits, including rhizosheath, to [P]ext were more prominent, positive, and linear at the five-leaf stage than at the GPD growth stage. At the five-leaf growth stage, total root length increased by about 2.5-fold with increasing [P]ext compared to the unamended soil. At the GPD stage, however, total root length decreased by about 1.83-fold as [P]ext increased compared to the unamended soil. Specific rhizosheath weight correlated with RHD, albeit weakly, and together explained up to 59% of the variation in tissue P. Root hair density was more responsive to P supply than root hair length and showed a similar total and lateral root length pattern. Most desirable responses to P occurred at a rate of 200-300 mg P kg-1 soil. It is concluded that sorghum would form rhizosheath, and [P]ext could be critical for the early vigorous growth of sorghum's responsive root and shoot traits. Beyond the early days of development, additional P application might be necessary to sustain the responses and plasticity observed during the early growth period, but this requires further investigation, potentially under field conditions.

Ideotype breeding for crop adaptation to low phosphorus availability on extensive organic farms

Organic farming in extensive production regions, such as the Canadian prairies have a particularly difficult challenge of replenishing soil reserves of phosphorus (P). Organic grains are exported off the farm while resupply of lost P is difficult due to limited availability of animal manures and low solubility of rock organic fertilizers. As a result, many organic farms on the prairies are deficient in plant-available P, leading to productivity breakdown. A portion of the solution may involve crop genetic improvement. A hypothetical 'catch and release' wheat ideotype for organic production systems is proposed to (i) enhance P uptake and use efficiency but (ii) translocate less P from the vegetative biomass into the grain. Root traits that would improve P uptake efficiency from less-available P pools under organic production are explored. The need to understand and classify 'phosphorus use efficiency' using appropriate indices for organic production is considered, as well as the appropriate efficiency indices for use if genetically selecting for the proposed ideotype. The implications for low seed P and high vegetative P are considered from a crop physiology, environmental, and human nutrition standpoint; considerations that are imperative for future feasibility of the ideotype.

Are absorptive root traits good predictors of ecosystem functioning? A test in a natural temperate forest

Trait-based approaches provide a useful framework to predict ecosystem functions under intensifying global change. However, our current understanding of trait-functioning relationships mainly relies on aboveground traits. Belowground traits (e.g. absorptive root traits) are rarely studied although these traits are related to important plant functions. We analyzed four pairs of analogous leaf and absorptive root traits of woody plants in a temperate forest and examined how these traits are coordinated at the community-level, and to what extent the trait covariation depends on local-scale environmental conditions. We then quantified the contributions of leaf and absorptive root traits and the environmental conditions in determining two important forest ecosystem functions, aboveground carbon storage, and woody biomass productivity. The results showed that both morphological trait pairs and chemical trait pairs exhibited positive correlations at the community level. Absorptive root traits show a strong response to environmental conditions compared to leaf traits. We also found that absorptive root traits were better predictors of the two forest ecosystem functions than leaf traits and environmental conditions. Our study confirms the important role of belowground traits in modulating ecosystem functions and deepens our understanding of belowground responses to changing environmental conditions.

RootSlice-A novel functional-structural model for root anatomical phenotypes

Root anatomy is an important determinant of root metabolic costs, soil exploration, and soil resource capture. Root anatomy varies substantially within and among plant species. RootSlice is a multicellular functional-structural model of root anatomy developed to facilitate the analysis and understanding of root anatomical phenotypes. RootSlice can capture phenotypically accurate root anatomy in three dimensions of different root classes and developmental zones, of both monocotyledonous and dicotyledonous species. Several case studies are presented illustrating the capabilities of the model. For maize nodal roots, the model illustrated the role of vacuole expansion in cell elongation; and confirmed the individual and synergistic role of increasing root cortical aerenchyma and reducing the number of cortical cell files in reducing root metabolic costs. Integration of RootSlice for different root zones as the temporal properties of the nodal roots in the whole-plant and soil model OpenSimRoot/maize enabled the multiscale evaluation of root anatomical phenotypes, highlighting the role of aerenchyma formation in enhancing the utility of cortical cell files for improving plant performance over varying soil nitrogen supply. Such integrative in silico approaches present avenues for exploring the fitness landscape of root anatomical phenotypes.

Large root cortical cells and reduced cortical cell files improve growth under suboptimal nitrogen in silico

Suboptimal nitrogen availability is a primary constraint to plant growth. We used OpenSimRoot, a functional-structural plant/soil model, to test the hypothesis that larger root cortical cell size (CCS), reduced cortical cell file number (CCFN), and their interactions with root cortical aerenchyma (RCA) and lateral root branching density (LRBD) are useful adaptations to suboptimal soil nitrogen availability in maize (Zea mays). Reduced CCFN increased shoot dry weight over 80%. Reduced respiration, reduced nitrogen content, and reduced root diameter accounted for 23%, 20%, and 33% of increased shoot biomass, respectively. Large CCS increased shoot biomass by 24% compared with small CCS. When simulated independently, reduced respiration and reduced nutrient content increased the shoot biomass by 14% and 3%, respectively. However, increased root diameter resulting from large CCS decreased shoot biomass by 4% due to an increase in root metabolic cost. Under moderate N stress, integrated phenotypes with reduced CCFN, large CCS, and high RCA improved shoot biomass in silt loam and loamy sand soils. In contrast, integrated phenotypes composed of reduced CCFN, large CCS and reduced lateral root branching density had the greatest growth in silt loam, while phenotypes with reduced CCFN, large CCS and high LRBD were the best performers in loamy sands. Our results support the hypothesis that larger CCS, reduced CCFN, and their interactions with RCA and LRBD could increase nitrogen acquisition by reducing root respiration and root nutrient demand. Phene synergisms may exist between CCS, CCFN, and LRBD. CCS and CCFN merit consideration for breeding cereal crops with improved nitrogen acquisition, which is critical for global food security.

Integration of reactive oxygen species and nutrient signalling to shape root system architecture

Yield losses due to nutrient deficiency are estimated as the primary cause of the yield gap worldwide. Understanding how plant roots perceive external nutrient status and elaborate morphological adaptations in response to it is necessary to develop reliable strategies to increase crop yield. In the last decade, reactive oxygen species (ROS) were shown to be key players of the mechanisms underlying root responses to nutrient limitation. ROS contribute in multiple ways to shape the root system in response to nutritional cues, both as direct effectors acting on cell wall architecture and as second messengers in signalling pathways. Here, we review the mutual interconnections existing between perception and signalling of the most common forms of the major macronutrients (nitrogen, phosphorus and potassium), and ROS in shaping plant root system architecture. We discuss recent advances in dissecting the integration of these elements and their impact on morphological traits of the root system, highlighting the functional ductility of ROS and enzymes implied in ROS metabolism, such as class III peroxidases.

Functional implications of multiseriate cortical sclerenchyma for soil resource capture and crop improvement

Suboptimal nutrient and water availability are primary constraints to crop growth. Global agriculture requires crops with greater nutrient and water efficiency. Multiseriate cortical sclerenchyma (MCS), a root anatomical trait characterized by small cells with thick cell walls encrusted with lignin in the outer cortex, has been shown to be an important trait for adaptation in maize and wheat in mechanically impeded soils. However, MCS has the potential to improve edaphic stress tolerance in a number of different crop taxa and in a number of different environments. This review explores the functional implications of MCS as an adaptive trait for water and nutrient acquisition and discusses future research perspectives on this trait for incorporation into crop breeding programs. For example, MCS may influence water and nutrient uptake, resistance to pests, symbiotic interactions, microbial interactions in the rhizosphere and soil carbon deposition. Root anatomical phenotypes are underutilized; however, important breeding targets for the development of efficient, productive and resilient crops urgently needed in global agriculture.

Phosphite treatment can improve root biomass and nutrition use efficiency in wheat

Phosphite represents a reduced form of phosphate that belongs to a class of crop growth-promoting chemicals termed biostimulants. Previous research has shown that phosphite application can enhance root growth, but its underlying mechanism, especially during environmental stresses, remains elusive. To uncover this, we undertook a series of morphological and physiological analyses under nutrient, water and heat stresses following a foliar application in wheat. Non-invasive 3D imaging of root system architecture directly in soil using X-ray Computed Tomography revealed that phosphite treatment improves root architectural traits and increased root biomass. Biochemical and physiological assays identified that phosphite treatment significantly increases Nitrate Reductase (NR) activity, leaf photosynthesis and stomatal conductance, suggesting improved Nitrogen and Carbon assimilation, respectively. These differences were more pronounced under heat or drought treatment (photosynthesis and photosystem II stability) and nutrient deficiency (root traits and NR). Overall our results suggest that phosphite treatment improves the ability of plants to tolerate abiotic stresses through improved Nitrogen and Carbon assimilation, combined with improved root growth which may improve biomass and yield.

4DRoot: Root phenotyping software for temporal 3D scans by X-ray computed tomography

Currently, plant phenomics is considered the key to reducing the genotype-to-phenotype knowledge gap in plant breeding. In this context, breakthrough imaging technologies have demonstrated high accuracy and reliability. The X-ray computed tomography (CT) technology can noninvasively scan roots in 3D; however, it is urgently required to implement high-throughput phenotyping procedures and analyses to increase the amount of data to measure more complex root phenotypic traits. We have developed a spatial-temporal root architectural modeling software tool based on 4D data from temporal X-ray CT scans. Through a cylinder fitting, we automatically extract significant root architectural traits, distribution, and hierarchy. The open-source software tool is named 4DRoot and implemented in MATLAB. The source code is freely available at https://github.com/TIDOP-USAL/4DRoot. In this research, 3D root scans from the black walnut tree were analyzed, a punctual scan for the spatial study and a weekly time-slot series for the temporal one. 4DRoot provides breeders and root biologists an objective and useful tool to quantify carbon sequestration throw trait extraction. In addition, 4DRoot could help plant breeders to improve plants to meet the food, fuel, and fiber demands in the future, in order to increase crop yield while reducing farming inputs.

Root phenotypes as modulators of microbial microhabitats

Plant roots are colonized by a multitude of microbial taxa that dynamically influence plant health. Plant-microbe interactions at the root-soil interface occur at the micro-scale and are affected by variation in root phenotypes. Different root phenotypes can have distinct impacts on physical and chemical gradients at the root-soil interface, leading to heterogeneous microhabitats for microbial colonization. Microbes that influence plant physiology will establish across these heterogeneous microhabitats, and, therefore, exploiting variation in root phenotypes can allow for targeted manipulation of plant-associated microbes. In this mini-review, we discuss how changes in root anatomy and architecture can influence resource availability and the spatial configuration of microbial microhabitats. We then propose research priorities that integrate root phenotypes and microbial microhabitats for advancing the manipulation of root-associated microbiomes. We foresee the yet-unexplored potential to harness diverse root phenotypes as a new level of precision in microbiome management in plant-root systems.

Multi-objective optimization of root phenotypes for nutrient capture using evolutionary algorithms

Root phenotypes are avenues to the development of crop cultivars with improved nutrient capture, which is an important goal for global agriculture. The fitness landscape of root phenotypes is highly complex and multidimensional. It is difficult to predict which combinations of traits (phene states) will create the best performing integrated phenotypes in various environments. Brute force methods to map the fitness landscape by simulating millions of phenotypes in multiple environments are computationally challenging. Evolutionary optimization algorithms may provide more efficient avenues to explore high dimensional domains such as the root phenotypic space. We coupled the three-dimensional functional-structural plant model, SimRoot, to the Borg Multi-Objective Evolutionary Algorithm (MOEA) and the evolutionary search over several generations facilitated the identification of optimal root phenotypes balancing trade-offs across nutrient uptake, biomass accumulation, and root carbon costs in environments varying in nutrient availability. Our results show that several combinations of root phenes generate optimal integrated phenotypes where performance in one objective comes at the cost of reduced performance in one or more of the remaining objectives, and such combinations differed for mobile and non-mobile nutrients and for maize (a monocot) and bean (a dicot). Functional-structural plant models can be used with multi-objective optimization to identify optimal root phenotypes under various environments, including future climate scenarios, which will be useful in developing the more resilient, efficient crops urgently needed in global agriculture.

Improving Soil Resource Uptake by Plants Through Capitalizing on Synergies Between Root Architecture and Anatomy and Root-Associated Microorganisms

Root architectural and anatomical phenotypes are highly diverse. Specific root phenotypes can be associated with better plant growth under low nutrient and water availability. Therefore, root ideotypes have been proposed as breeding targets for more stress-resilient and resource-efficient crops. For example, root phenotypes that correspond to the Topsoil Foraging ideotype are associated with better plant growth under suboptimal phosphorus availability, and root phenotypes that correspond to the Steep, Cheap and Deep ideotype are linked to better performance under suboptimal availability of nitrogen and water. We propose that natural variation in root phenotypes translates into a diversity of different niches for microbial associations in the rhizosphere, rhizoplane and root cortex, and that microbial traits could have synergistic effects with the beneficial effect of specific root phenotypes. Oxygen and water content, carbon rhizodeposition, nutrient availability, and root surface area are all factors that are modified by root anatomy and architecture and determine the structure and function of the associated microbial communities. Recent research results indicate that root characteristics that may modify microbial communities associated with maize include aerenchyma, rooting angle, root hairs, and lateral root branching density. Therefore, the selection of root phenotypes linked to better plant growth under specific edaphic conditions should be accompanied by investigating and selecting microbial partners better adapted to each set of conditions created by the corresponding root phenotype. Microbial traits such as nitrogen transformation, phosphorus solubilization, and water retention could have synergistic effects when correctly matched with promising plant root ideotypes for improved nutrient and water capture. We propose that elucidation of the interactive effects of root phenotypes and microbial functions on plant nutrient and water uptake offers new opportunities to increase crop yields and agroecosystem sustainability.

Integrated root phenotypes for improved rice performance under low nitrogen availability

Greater nitrogen efficiency would substantially reduce the economic, energy and environmental costs of rice production. We hypothesized that synergistic balancing of the costs and benefits for soil exploration among root architectural phenes is beneficial under suboptimal nitrogen availability. An enhanced implementation of the functional-structural model OpenSimRoot for rice integrated with the ORYZA_v3 crop model was used to evaluate the utility of combinations of root architectural phenes, namely nodal root angle, the proportion of smaller diameter nodal roots, nodal root number; and L-type and S-type lateral branching densities, for plant growth under low nitrogen. Multiple integrated root phenotypes were identified with greater shoot biomass under low nitrogen than the reference cultivar IR64. The superiority of these phenotypes was due to synergism among root phenes rather than the expected additive effects of phene states. Representative optimal phenotypes were predicted to have up to 80% greater grain yield with low N supply in the rainfed dry direct-seeded agroecosystem over future weather conditions, compared to IR64. These phenotypes merit consideration as root ideotypes for breeding rice cultivars with improved yield under rainfed dry direct-seeded conditions with limited nitrogen availability. The importance of phene synergism for the performance of integrated phenotypes has implications for crop breeding.

Root angle in maize influences nitrogen capture and is regulated by calcineurin B-like protein (CBL)-interacting serine/threonine-protein kinase 15 (ZmCIPK15)

Crops with reduced nutrient and water requirements are urgently needed in global agriculture. Root growth angle plays an important role in nutrient and water acquisition. A maize diversity panel of 481 genotypes was screened for variation in root angle employing a high-throughput field phenotyping platform. Genome-wide association mapping identified several single nucleotide polymorphisms (SNPs) associated with root angle, including one located in the root expressed CBL-interacting serine/threonine-protein kinase 15 (ZmCIPK15) gene (LOC100285495). Reverse genetic studies validated the functional importance of ZmCIPK15, causing a approximately 10° change in root angle in specific nodal positions. A steeper root growth angle improved nitrogen capture in silico and in the field. OpenSimRoot simulations predicted at 40 days of growth that this change in angle would improve nitrogen uptake by 11% and plant biomass by 4% in low nitrogen conditions. In field studies under suboptimal N availability, the cipk15 mutant with steeper growth angles had 18% greater shoot biomass and 29% greater shoot nitrogen accumulation compared to the wild type after 70 days of growth. We propose that a steeper root growth angle modulated by ZmCIPK15 will facilitate efforts to develop new crop varieties with optimal root architecture for improved performance under edaphic stress.

Whole-plant phenotypic engineering: moving beyond ratios for multi-objective optimization of nutrient use efficiency

Nutrient use efficiency (NUE) is typically measured as the ratio of yield to soil nutrient availability but ignores contributions of underlying plant traits. Relevant plant traits can be grouped as root acquisition efficiency, shoot radiation use efficiency, and plant metabolic efficiency. The intentional integration of these traits will lead to synergistic improvements of NUE. Recent progress in trait-focused research includes phenotyping root nutrient uptake rates and respiration, engineering reduced photorespiration, and identification of nutrient assimilation pathways. Traits need to be conceptualized in agricultural systems contexts to improve synchrony of plant demand and soil supply of nutrients, including consideration of crop mixtures. Use of simulation modeling and multi-objective optimization will allow accelerating NUE gains beyond selection for a single ratio.

Many paths to one goal: Identifying integrated rice root phenotypes for diverse drought environments

Drought is a major source of yield loss in the production of rice (Oryza sativa L.), and cultivars that maintain yield under drought across environments and drought stress scenarios are urgently needed. Root phenotypes directly affect water interception and uptake, so plants with root systems optimized for water uptake under drought would likely exhibit reduced yield loss. Deeper nodal roots that have a low metabolic cost per length (i.e., cheaper roots) via smaller root diameter and/or more aerenchyma and that transport water efficiently through smaller diameter metaxylem vessels may be beneficial during drought. Subsets of the Rice Diversity Panel 1 and Azucena × IR64 recombinant inbred lines were grown in two greenhouse and two rainout shelter experiments under drought stress to assess their shoot, root anatomical, and root architectural phenotypes. Root traits and root trait plasticity in response to drought varied with genotype and environment. The best-performing groups in the rainout shelter experiments had less plasticity of living tissue area in nodal roots than the worst performing groups. Root traits under drought were partitioned into similar groups or clusters via the partitioning-around-medoids algorithm, and this revealed two favorable integrated root phenotypes common within and across environments. One favorable integrated phenotype exhibited many, deep nodal roots with larger root cross-sectional area and more aerenchyma, while the other favorable phenotype exhibited many, deep nodal roots with small root cross-sectional area and small metaxylem vessels. Deeper roots with high theoretical axial hydraulic conductance combined with reduced root metabolic cost contributed to greater shoot biomass under drought. These results reflect how some root anatomical and architectural phenes work in concert as integrated phenotypes to influence the performance of plant under drought stress. Multiple integrated root phenotypes are therefore recommended to be selected in breeding programs for improving rice yield across diverse environments and drought scenarios.

Harnessing root architecture to address global challenges

Root architecture can be targeted in breeding programs to develop crops with better capture of water and nutrients. In rich nations, such crops would reduce production costs and environmental pollution and, in developing nations, they would improve food security and economic development. Crops with deeper roots would have better climate resilience while also sequestering atmospheric CO₂ . Deeper rooting, which improves water and N capture, is facilitated by steeper root growth angles, fewer axial roots, reduced lateral branching, and anatomical phenotypes that reduce the metabolic cost of root tissue. Mechanical impedance, hypoxia, and Al toxicity are constraints to subsoil exploration. To improve topsoil foraging for P, K, and other shallow resources, shallower root growth angles, more axial roots, and greater lateral branching are beneficial, as are metabolically cheap roots. In high-input systems, parsimonious root phenotypes that focus on water capture may be advantageous. The growing prevalence of Conservation Agriculture is shifting the mechanical impedance characteristics of cultivated soils in ways that may favor plastic root phenotypes capable of exploiting low resistance pathways to the subsoil. Root ideotypes for many low-input systems would not be optimized for any one function, but would be resilient against an array of biotic and abiotic challenges. Root hairs, reduced metabolic cost, and developmental regulation of plasticity may be useful in all environments. The fitness landscape of integrated root phenotypes is large and complex, and hence will benefit from in silico tools. Understanding and harnessing root architecture for crop improvement is a transdisciplinary opportunity to address global challenges.

Optimizing Crop Water Use for Drought and Climate Change Adaptation Requires a Multi-Scale Approach

Selection criteria that co-optimize water use efficiency and yield are needed to promote plant productivity in increasingly challenging and variable drought scenarios, particularly dryland cereals in the semi-arid tropics. Optimizing water use efficiency and yield fundamentally involves transpiration dynamics, where restriction of maximum transpiration rate helps to avoid early crop failure, while maximizing grain filling. Transpiration restriction can be regulated by multiple mechanisms and involves cross-organ coordination. This coordination involves complex feedbacks and feedforwards over time scales ranging from minutes to weeks, and from spatial scales ranging from cell membrane to crop canopy. Aquaporins have direct effect but various compensation and coordination pathways involve phenology, relative root and shoot growth, shoot architecture, root length distribution profile, as well as other architectural and anatomical aspects of plant form and function. We propose gravimetric phenotyping as an integrative, cross-scale solution to understand the dynamic, interwoven, and context-dependent coordination of transpiration regulation. The most fruitful breeding strategy is likely to be that which maintains focus on the phene of interest, namely, daily and season level transpiration dynamics. This direct selection approach is more precise than yield-based selection but sufficiently integrative to capture attenuating and complementary factors.

Root traits as drivers of plant and ecosystem functioning: current understanding, pitfalls and future research needs

The effects of plants on the biosphere, atmosphere and geosphere are key determinants of terrestrial ecosystem functioning. However, despite substantial progress made regarding plant belowground components, we are still only beginning to explore the complex relationships between root traits and functions. Drawing on the literature in plant physiology, ecophysiology, ecology, agronomy and soil science, we reviewed 24 aspects of plant and ecosystem functioning and their relationships with a number of root system traits, including aspects of architecture, physiology, morphology, anatomy, chemistry, biomechanics and biotic interactions. Based on this assessment, we critically evaluated the current strengths and gaps in our knowledge, and identify future research challenges in the field of root ecology. Most importantly, we found that belowground traits with the broadest importance in plant and ecosystem functioning are not those most commonly measured. Also, the estimation of trait relative importance for functioning requires us to consider a more comprehensive range of functionally relevant traits from a diverse range of species, across environments and over time series. We also advocate that establishing causal hierarchical links among root traits will provide a hypothesis-based framework to identify the most parsimonious sets of traits with the strongest links on functions, and to link genotypes to plant and ecosystem functioning.

A starting guide to root ecology: strengthening ecological concepts and standardising root classification, sampling, processing and trait measurements

In the context of a recent massive increase in research on plant root functions and their impact on the environment, root ecologists currently face many important challenges to keep on generating cutting-edge, meaningful and integrated knowledge. Consideration of the below-ground components in plant and ecosystem studies has been consistently called for in recent decades, but methodology is disparate and sometimes inappropriate. This handbook, based on the collective effort of a large team of experts, will improve trait comparisons across studies and integration of information across databases by providing standardised methods and controlled vocabularies. It is meant to be used not only as starting point by students and scientists who desire working on below-ground ecosystems, but also by experts for consolidating and broadening their views on multiple aspects of root ecology. Beyond the classical compilation of measurement protocols, we have synthesised recommendations from the literature to provide key background knowledge useful for: (1) defining below-ground plant entities and giving keys for their meaningful dissection, classification and naming beyond the classical fine-root vs coarse-root approach; (2) considering the specificity of root research to produce sound laboratory and field data; (3) describing typical, but overlooked steps for studying roots (e.g. root handling, cleaning and storage); and (4) gathering metadata necessary for the interpretation of results and their reuse. Most importantly, all root traits have been introduced with some degree of ecological context that will be a foundation for understanding their ecological meaning, their typical use and uncertainties, and some methodological and conceptual perspectives for future research. Considering all of this, we urge readers not to solely extract protocol recommendations for trait measurements from this work, but to take a moment to read and reflect on the extensive information contained in this broader guide to root ecology, including sections I-VII and the many introductions to each section and root trait description. Finally, it is critical to understand that a major aim of this guide is to help break down barriers between the many subdisciplines of root ecology and ecophysiology, broaden researchers' views on the multiple aspects of root study and create favourable conditions for the inception of comprehensive experiments on the role of roots in plant and ecosystem functioning.

Plasticity, exudation and microbiome-association of the root system of Pellitory-of-the-wall plants grown in environments impaired in iron availability

The investigation of the adaptive strategies of wild plant species to extreme environments is a challenging issue, which favors the identification of new traits for plant resilience. We investigated different traits which characterize the root-soil interaction of Parietaria judaica, a wild plant species commonly known as "Pellitory-of-the-wall". P. judaica adopts the acidification-reduction strategy (Strategy I) for iron (Fe) acquisition from soil, and it can complete its life cycle in highly calcareous environments without any symptoms of chlorosis. In a field-to-lab approach, the microbiome associated with P. judaica roots was analyzed in spontaneous plants harvested from an urban environment consisting in an extremely calcareous habitat. Also, the phenolics and carboxylates content and root plasticity and exudation were analyzed in P. judaica plants grown under three different controlled conditions mimicking the effect of calcareous environments on Fe availability: results show that P. judaica differentially modulates root plasticity under different Fe availability-impaired conditions, and that it induces, to a high extent, the exudation of caffeoylquinic acid derivatives under calcareous conditions, positively impacting Fe solubility.

A starting guide to root ecology: strengthening ecological concepts and standardising root classification, sampling, processing and trait measurements

In the context of a recent massive increase in research on plant root functions and their impact on the environment, root ecologists currently face many important challenges to keep on generating cutting-edge, meaningful and integrated knowledge. Consideration of the below-ground components in plant and ecosystem studies has been consistently called for in recent decades, but methodology is disparate and sometimes inappropriate. This handbook, based on the collective effort of a large team of experts, will improve trait comparisons across studies and integration of information across databases by providing standardised methods and controlled vocabularies. It is meant to be used not only as starting point by students and scientists who desire working on below-ground ecosystems, but also by experts for consolidating and broadening their views on multiple aspects of root ecology. Beyond the classical compilation of measurement protocols, we have synthesised recommendations from the literature to provide key background knowledge useful for: (1) defining below-ground plant entities and giving keys for their meaningful dissection, classification and naming beyond the classical fine-root vs coarse-root approach; (2) considering the specificity of root research to produce sound laboratory and field data; (3) describing typical, but overlooked steps for studying roots (e.g. root handling, cleaning and storage); and (4) gathering metadata necessary for the interpretation of results and their reuse. Most importantly, all root traits have been introduced with some degree of ecological context that will be a foundation for understanding their ecological meaning, their typical use and uncertainties, and some methodological and conceptual perspectives for future research. Considering all of this, we urge readers not to solely extract protocol recommendations for trait measurements from this work, but to take a moment to read and reflect on the extensive information contained in this broader guide to root ecology, including sections I-VII and the many introductions to each section and root trait description. Finally, it is critical to understand that a major aim of this guide is to help break down barriers between the many subdisciplines of root ecology and ecophysiology, broaden researchers' views on the multiple aspects of root study and create favourable conditions for the inception of comprehensive experiments on the role of roots in plant and ecosystem functioning.

Functional phenomics and genetics of the root economics space in winter wheat using high-throughput phenotyping of respiration and architecture

The root economics space is a useful framework for plant ecology but is rarely considered for crop ecophysiology. In order to understand root trait integration in winter wheat, we combined functional phenomics with trait economic theory, utilizing genetic variation, high-throughput phenotyping, and multivariate analyses. We phenotyped a diversity panel of 276 genotypes for root respiration and architectural traits using a novel high-throughput method for CO2 flux and the open-source software RhizoVision Explorer to analyze scanned images. We uncovered substantial variation in specific root respiration (SRR) and specific root length (SRL), which were primary indicators of root metabolic and structural costs. Multiple linear regression analysis indicated that lateral root tips had the greatest SRR, and the residuals from this model were used as a new trait. Specific root respiration was negatively correlated with plant mass. Network analysis, using a Gaussian graphical model, identified root weight, SRL, diameter, and SRR as hub traits. Univariate and multivariate genetic analyses identified genetic regions associated with SRR, SRL, and root branching frequency, and proposed gene candidates. Combining functional phenomics and root economics is a promising approach to improving our understanding of crop ecophysiology. We identified root traits and genomic regions that could be harnessed to breed more efficient crops for sustainable agroecosystems.

Functional phenomics and genetics of the root economics space in winter wheat using high-throughput phenotyping of respiration and architecture

The root economics space is a useful framework for plant ecology but is rarely considered for crop ecophysiology. In order to understand root trait integration in winter wheat, we combined functional phenomics with trait economic theory, utilizing genetic variation, high-throughput phenotyping, and multivariate analyses. We phenotyped a diversity panel of 276 genotypes for root respiration and architectural traits using a novel high-throughput method for CO₂ flux and the open-source software RhizoVision Explorer to analyze scanned images. We uncovered substantial variation in specific root respiration (SRR) and specific root length (SRL), which were primary indicators of root metabolic and structural costs. Multiple linear regression analysis indicated that lateral root tips had the greatest SRR, and the residuals from this model were used as a new trait. Specific root respiration was negatively correlated with plant mass. Network analysis, using a Gaussian graphical model, identified root weight, SRL, diameter, and SRR as hub traits. Univariate and multivariate genetic analyses identified genetic regions associated with SRR, SRL, and root branching frequency, and proposed gene candidates. Combining functional phenomics and root economics is a promising approach to improving our understanding of crop ecophysiology. We identified root traits and genomic regions that could be harnessed to breed more efficient crops for sustainable agroecosystems.

Phosphorus uptake is associated with the rhizosheath formation of mature cluster roots in white lupin under soil drying and phosphorus deficiency

Phosphorus (P) deficiency largely restricts plant growth and lead to severe yield losses. Therefore, identification of novel root traits to improve P uptake is needed to circumvent yield losses. White lupin (Lupinus albus) is a legume crop that develops cluster roots and has the high phosphorus use efficiency in low P soils. We aimed to investigate the association between cluster roots (CR) rhizosheath formation and P uptake in white lupin. Rhizosheath formation and P concentration were evaluated under four soil treatments. CR increased up to 2.5-fold of overall plant dry weight under SD-P compared to WW + P (control), partly attributable to variations in CR development. Our data showed that SD-P significantly increase rhizosheath weight in white lupin. Among the root segments, MCR showed improved P accumulation in the root which is associated with increased MCR rhizosheath weight. Additionally, a positive correlation was observed between MCR rhizosheath weight and P uptake. Moreover, high sucrose content was recorded in MCR, which may contribute in CR growth under SD-P. Expression analysis of genes related to sucrose accumulation (LaSUC1, LaSUC5, and LaSUC9) and phosphorus uptake (LaSPX3, LaPHO1, and LaPHT1) exhibited peaked expression in MCR under SD-P. This indicate that root sucrose status may facilitate P uptake under P starvation. Together, the ability to enhance P uptake of white lupin is largely associated with MCR rhizosheath under SD-P. Our results showed that gene expression modulation of CR forming plant species, demonstrating that these novel root structures may play crucial role in P acquisition from the soil. Our findings could be implicated for developing P and water efficient crop via CR development in sustainable agriculture.

Root engineering in maize by increasing cytokinin degradation causes enhanced root growth and leaf mineral enrichment

Root-specific expression of a cytokinin-degrading CKX gene in maize roots causes formation of a larger root system leading to higher element content in shoot organs. The size and architecture of the root system is functionally relevant for the access to water and soil nutrients. A great number of mostly unknown genes are involved in regulating root architecture complicating targeted breeding of plants with a larger root system. Here, we have explored whether root-specific degradation of the hormone cytokinin, which is a negative regulator of root growth, can be used to genetically engineer maize (Zea mays L.) plants with a larger root system. Root-specific expression of a CYTOKININ OXIDASE/DEHYDROGENASE (CKX) gene of Arabidopsis caused the formation of up to 46% more root dry weight while shoot growth of these transgenic lines was similar as in non-transgenic control plants. The concentration of several elements, in particular of those with low soil mobility (K, P, Mo, Zn), was increased in leaves of transgenic lines. In kernels, the changes in concentration of most elements were less pronounced, but the concentrations of Cu, Mn and Zn were significantly increased in at least one of the three independent lines. Our data illustrate the potential of an increased root system as part of efforts towards achieving biofortification. Taken together, this work has shown that root-specific expression of a CKX gene can be used to engineer the root system of maize and alter shoot element composition.

Mycorrhizal root colonization in maize fields is more affected by soil management and climate conditions than by plant genotype

This work aims to characterize the arbuscular mycorrhizal association between maize genotypes and the effects of soil physical-chemical attributes on the symbiosis. A preliminary greenhouse assay evaluated five maize landraces and five conventional modern genotypes in non-sterile, low-P soil. Sixty days after sowing, we measured plant height, stem diameter, shoot and root dry biomass, root colonization structures, and shoot P concentration and total accumulation. In a second stage, a 2-year on-farm study evaluated how soil physical-chemical attributes in fields with three plant genotype groups affected the arbuscular mycorrhizal fungal symbiosis in a maize diversity microcenter in Southern Brazil. We collected soil and plant material in farms growing landrace, conventional modern genotypes, or genetically modified (GM) maize. There were five collection points at each group, and we measured mycorrhizal colonization, soil physicochemical attributes, and shoot phosphorus concentration. The greenhouse study showed that genotypes have different growth strategies for root production and shoot growth. No differences in mycorrhizal colonization rates occurred among landraces and modern maize genotypes in the low-P soil. The field study showed that soil and climate conditions had a more marked effect on mycorrhizal root colonization than plant genotype groups (landrace, conventional modern genotypes, or GM maize).

Rice Seedling Growth Promotion by Biochar Varies With Genotypes and Application Dosages

While biochar use in agriculture is widely advocated, how the effect of biochar on plant growth varies with biochar forms and crop genotypes is poorly addressed. The role of dissolvable organic matter (DOM) in plant growth has been increasingly addressed for crop production with biochar. In this study, a hydroponic culture of rice seedling growth of two cultivars was treated with bulk mass (DOM-containing), water extract (DOM only), and extracted residue (DOM-free) of maize residue biochar, at a volumetric dosage of 0.01, 0.05, and 0.1%, respectively. On seedling root growth of the two cultivars, bulk biochar exerted a generally negative effect, while the biochar extract had a consistently positive effect across the application dosages. Differently, the extracted biochar showed a contrasting effect between genotypes. In another hydroponic culture with Wuyunjing 7 treated with biochar extract at sequential dosages, seedling growth was promoted by 95% at 0.01% dosage but by 26% at 0.1% dosage, explained with the great promotion of secondary roots rather than of primary roots. Such effects were likely explained by low molecular weight organic acids and nanoparticles contained in the biochar DOM. This study highlights the importance of biochar DOM and crop genotype when evaluating the effect of biochar on plants. The use of low dosage of biochar DOM could help farmers to adopt biochar technology as a solution for agricultural sustainability.

Characterization of contrasting rice (Oryza sativa L.) genotypes reveals the Pi-efficient schema for phosphate starvation tolerance

BACKGROUND

Phosphorus (P), being one of the essential components of nucleic acids, cell membranes and enzymes, indispensable for diverse cellular processes like photosynthesis/carbohydrate metabolism, energy production, redox homeostasis and signaling. Crop yield is severely affected due to Phosphate (Pi) deficiency; and to cope with Pi-deficiency, plants have evolved several strategies. Some rice genotypes are compatible with low Pi availability, whereas others are sensitive to Pi deficiency. However, the underlying molecular mechanism for low Pi tolerance remains largely unexplored.

RESULT

Several studies were carried out to understand Pi-deficiency responses in rice at seedling stage, but few of them targeted molecular aspects/responses of Pi-starvation at the advanced stage of growth. To delineate the molecular mechanisms for low Pi tolerance, a pair of contrasting rice (Oryza sativa L.) genotypes [viz. Pusa-44 (Pi-deficiency sensitive) and its near isogenic line (NIL-23, Pi-deficiency tolerant) harboring Phosphorus uptake 1 (Pup1) QTL from an aus landrace Kasalath] were used. Comparative morphological, physiological, and biochemical analyses confirmed some of the well-known findings. Transcriptome analysis of shoot and root tissues from 45-day-old rice plants grown hydroponically under P-sufficient (16 ppm Pi) or P-starved (0 ppm Pi) medium revealed that Pi-starvation stress causes global transcriptional reprogramming affecting several transcription factors, signaling pathways and other regulatory genes. We could identify several significantly up-regulated genes in roots of NIL-23 under Pi-starvation which might be responsible for the Pi starvation tolerance. Pathway enrichment analysis indicated significant role of certain phosphatases, transporters, transcription factors, carbohydrate metabolism, hormone-signaling, and epigenetic processes in improving P-starvation stress tolerance in NIL-23.

CONCLUSION

We report the important candidate mechanisms for Pi acquisition/solubilization, recycling, remobilization/transport, sensing/signalling, genetic/epigenetic regulation, and cell wall structural changes to be responsible for P-starvation tolerance in NIL-23. The study provides some of the novel information useful for improving phosphorus-use efficiency in rice cultivars.

Phenotyping Latin American Open-Pollinated Varieties of Popcorn for Environments with Low Water Availability

Drought is a common abiotic stress in tropical and subtropical regions that limits the growth and development of agricultural crops, mainly impacting grain yield. Acting through plant breeding is the most viable alternative for obtaining genotypes more tolerant of environments with stress. This work aims to select popcorn genotypes for environments with drought and to identify discriminating traits for the evaluation of drought tolerance in popcorn germplasm. Fifteen Latin American populations of popcorn were evaluated in water stress (WS) and well-watered (WW) conditions. The evaluated traits were based in morpho-agronomic, physiological and radicular descriptors. Data were submitted to individual and joint ANOVA and GT Biplot analysis. Variability was detected between populations for all traits in both conditions. The drought caused a reduction of 30.61% and 3.5% in grain yield and popping expansion, respectively. Based in GT biplot analysis, 880POP was the most stable in WS and WW, being indicated as a promising population for cultivation in environments with water limitation. This study is going to allow the establishment of a collection of great importance to maize germplasm and to provide information to facilitate the process of selection in breeding programs focused on drought tolerance.

Can smart nutrient applications optimize the plant's hidden half to improve drought resistance?

Global agriculture is challenged with achieving sustainable food security while the climate changes and the threat of drought increases. Much of the research attention has focused on above-ground plant responses with an aim to improve drought resistance. The hidden half, that is, the root system belowground, is receiving increasing attention as the interface of the plant with the soil. Because roots are a sensing organ for nutrients and moisture, we speculate that crop root system traits can be managed using smart nutrient application in order to increase drought resistance. Roots are known to be influenced both by their underlying genetics and also by responses to the environment, termed root plasticity. Though very little is known about the combined effect of water and nutrients on root plasticity, we explore the possibilities of root system manipulation by nutrient application. We compare the effects of different water or nutrient levels on root plasticity and its genetic regulation, with a focus on how this may affect drought resistance. We propose four primary mechanisms through which smart nutrient management can optimize root traits for drought resistance: (1) overall plant vigor, (2) increased root allocation, (3) influence specific root traits, and (4) use smart placement and timing to encourage deep rooting. In the longer term, we envision that beneficial root traits, including plasticity, could be bred into efficient varieties and combined with advanced precision management of water and nutrients to achieve agricultural sustainability.

Contrasting transcriptional responses to Fusarium virguliforme colonization in symptomatic and asymptomatic hosts

The broad host range of Fusarium virguliforme represents a unique comparative system to identify and define differentially induced responses between an asymptomatic monocot host, maize (Zea mays), and a symptomatic eudicot host, soybean (Glycine max). Using a temporal, comparative transcriptome-based approach, we observed that early gene expression profiles of root tissue from infected maize suggest that pathogen tolerance coincides with the rapid induction of senescence dampening transcriptional regulators, including ANACs (Arabidopsis thaliana NAM/ATAF/CUC protein) and Ethylene-Responsive Factors. In contrast, the expression of senescence-associated processes in soybean was coincident with the appearance of disease symptom development, suggesting pathogen-induced senescence as a key pathway driving pathogen susceptibility in soybean. Based on the analyses described herein, we posit that root senescence is a primary contributing factor underlying colonization and disease progression in symptomatic versus asymptomatic host-fungal interactions. This process also supports the lifestyle and virulence of F. virguliforme during biotrophy to necrotrophy transitions. Further support for this hypothesis lies in comprehensive co-expression and comparative transcriptome analyses, and in total, supports the emerging concept of necrotrophy-activated senescence. We propose that F. virguliforme conditions an environment within symptomatic hosts, which favors susceptibility through transcriptomic reprogramming, and as described herein, the induction of pathways associated with senescence during the necrotrophic stage of fungal development.

Nodal root diameter and node number in maize (Zea mays L.) interact to influence plant growth under nitrogen stress

Under nitrogen limitation, plants increase resource allocation to root growth relative to shoot growth. The utility of various root architectural and anatomical phenotypes for nitrogen acquisition are not well understood. Nodal root number and root cross-sectional area were evaluated in maize in field and greenhouse environments. Nodal root number and root cross-sectional area were inversely correlated under both high and low nitrogen conditions. Attenuated emergence of root nodes, as opposed to differences in the number of axial roots per node, was associated with substantially reduced root number. Greater root cross-sectional area was associated with a greater stele area and number of cortical cell files. Genotypes that produced few, thick nodal roots rather than many, thin nodal roots had deeper rooting and better shoot growth in low nitrogen environments. Fewer nodal roots offset the respiratory and nitrogen costs of thicker diameter roots, since total nodal root respiration and nitrogen content was similar for genotypes with many, thin and few, thick nodal roots. We propose that few, thick nodal roots may enable greater capture of deep soil nitrogen and improve plant performance under nitrogen stress. Synergistic interactions between an architectural and anatomical trait may be an important strategy for nitrogen acquisition. Understanding trait interactions among different root nodes has important implications in for improving crop nutrient uptake and stress tolerance.

Importance of individual root traits to understand crop root system in agronomic and environmental contexts

Resource acquisition, one of the major functions of roots, can contribute to crop growth and mitigating environmental impacts. The spatio-temporal distribution of roots in the soil in relation to the dynamics of the soil resources is critical in resource acquisition. Root distribution is determined by root system development. The root system consists of many individual roots of different types and ages. Each individual root has specific development, resource acquisition, and transport traits, which change with root growth. The integration of individual root traits in the root system could exhibit crop performance in the various environments via root distribution in the soil. However, the relationship between individual root traits and the pattern of root distribution is complicated. To understand this complicated relationship, we need to evaluate enormous numbers of individual root traits and understand the relationship between individual root development and root distribution as well as the integrated functions of individual root traits along with dynamics of resources in the soil.

Root phenotyping: important and minimum information required for root modeling in crop plants

As plants cannot relocate, they require effective root systems for water and nutrient uptake. Root development plasticity enables plants to adapt to different environmental conditions. Research on improvements in crop root systems is limited in comparison with that in shoots as the former are difficult to image. Breeding more effective root systems is proposed as the "second green revolution". There are several recent publications on root system architecture (RSA), but the methods used to analyze the RSA have not been standardized. Here, we introduce traditional and current root-imaging methods and discuss root structure phenotyping. Some important root structures have not been standardized as roots are easily affected by rhizosphere conditions and exhibit greater plasticity than shoots; moreover, root morphology significantly varies even in the same genotype. For these reasons, it is difficult to define the ideal root systems for breeding. In this review, we introduce several types of software to analyze roots and identify important root parameters by modeling to simplify the root system characterization. These parameters can be extracted from photographs captured in the field. This modeling approach is applicable to various legacy root data stored in old or unpublished formats. Standardization of RSA data could help estimate root ideotypes.

Root phenotyping: important and minimum information required for root modeling in crop plants

As plants cannot relocate, they require effective root systems for water and nutrient uptake. Root development plasticity enables plants to adapt to different environmental conditions. Research on improvements in crop root systems is limited in comparison with that in shoots as the former are difficult to image. Breeding more effective root systems is proposed as the "second green revolution". There are several recent publications on root system architecture (RSA), but the methods used to analyze the RSA have not been standardized. Here, we introduce traditional and current root-imaging methods and discuss root structure phenotyping. Some important root structures have not been standardized as roots are easily affected by rhizosphere conditions and exhibit greater plasticity than shoots; moreover, root morphology significantly varies even in the same genotype. For these reasons, it is difficult to define the ideal root systems for breeding. In this review, we introduce several types of software to analyze roots and identify important root parameters by modeling to simplify the root system characterization. These parameters can be extracted from photographs captured in the field. This modeling approach is applicable to various legacy root data stored in old or unpublished formats. Standardization of RSA data could help estimate root ideotypes.

Morphophysiology of Potato (Solanum tuberosum) in Response to Drought Stress: Paving the Way Forward

The cultivated potato (Solanum tuberosum L.) is currently the third most important food crop in the world and is becoming increasingly important to the local economies of developing countries. Climate change threatens to drastically reduce potato yields in areas of the world where the growing season is predicted to become hotter and drier. Modern potato is well known as an extremely drought susceptible crop, which has primarily been attributed to its shallow root system. This review addresses this decades old consensus, and highlights other, less well understood, morphophysiological features of potato which likely contribute to drought susceptibility. This review explores the effects of drought on these traits and goes on to discuss phenotypes which may be associated with drought tolerance in potato. Small canopies which increase harvest index and decrease evapotranspiration, open stem-type canopies which increase light penetration, and shallow but densely rooted cultivars, which increase water uptake, have all been associated with drought tolerance in the past, but have largely been ignored. While individual studies on a limited number of cultivars may have examined these phenotypes, they are typically overlooked due to the consensus that root depth is the only significant cause of drought susceptibility in potato. We review this work, particularly with respect to potato morphology, in the context of a changing climate, and highlight the gaps in our understanding of drought tolerance in potato that such work implies.

A Comparative Analysis of Quantitative Metrics of Root Architecture

High throughput phenotyping is important to bridge the gap between genotype and phenotype. The methods used to describe the phenotype therefore should be robust to measurement errors, relatively stable over time, and most importantly, provide a reliable estimate of elementary phenotypic components. In this study, we use functional-structural modeling to evaluate quantitative phenotypic metrics used to describe root architecture to determine how they fit these criteria. Our results show that phenes such as root number, root diameter, and lateral root branching density are stable, reliable measures and are not affected by imaging method or plane. Metrics aggregating multiple phenes such as total length, total volume, convex hull volume, and bushiness index estimate different subsets of the constituent phenes; they however do not provide any information regarding the underlying phene states. Estimates of phene aggregates are not unique representations of underlying constituent phenes: multiple phenotypes having phenes in different states could have similar aggregate metrics. Root growth angle is an important phene which is susceptible to measurement errors when 2D projection methods are used. Metrics that aggregate phenes which are complex functions of root growth angle and other phenes are also subject to measurement errors when 2D projection methods are used. These results support the hypothesis that estimates of phenes are more useful than metrics aggregating multiple phenes for phenotyping root architecture. We propose that these concepts are broadly applicable in phenotyping and phenomics.

WinRoots: A High-Throughput Cultivation and Phenotyping System for Plant Phenomics Studies Under Soil Stress

Soil stress, such as salinity, is a primary cause of global crop yield reduction. Existing crop phenotyping platforms cannot fully meet the specific needs of phenomics studies of plant response to soil stress in terms of throughput, environmental controllability, or root phenotypic acquisition. Here, we report the WinRoots, a low-cost and high-throughput plant soil cultivation and phenotyping system that can provide uniform, controlled soil stress conditions and accurately quantify the whole-plant phenome, including roots. Using soybean seedlings exposed to salt stress as an example, we demonstrate the uniformity and controllability of the soil environment in this system. A high-throughput multiple-phenotypic assay among 178 soybean cultivars reveals that the cotyledon character can serve as a non-destructive indicator of the whole-seedling salt tolerance. Our results demonstrate that WinRoots is an effective tool for high-throughput plant cultivation and soil stress phenomics studies.

Single and Combined Abiotic Stress in Maize Root Morphology

Plants are continually exposed to multiple stresses, which co-occur in nature, and the net effects are frequently more nonadditive (i.e., synergistic or antagonistic), suggesting "unique" responses with respect to that of the individual stress. Further, plant stress responses are not uniform, showing a high spatial and temporal variability among and along the different organs. In this respect, the present work investigated the morphological responses of different root types (seminal, seminal lateral, primary and primary lateral) of maize plants exposed to single (drought and heat) and combined stress (drought + heat). Data were evaluated by a specific root image analysis system (WinRHIZO) and analyzed by uni- and multivariate statistical analyses. The results indicated that primary roots and their laterals were the types more sensitive to the single and combined stresses, while the seminal laterals specifically responded to the combined only. Further, antagonistic and synergistic effects were observed for the specific traits in the primary and their laterals and in the seminal lateral roots in response to the combined stress. These results suggested that the maize root system modified specific root types and traits to deal with different stressful environmental conditions, highlighting that the adaptation strategy to the combined stress may be different from that of the individual ones. The knowledge of "unique or shared" responses of plants to multiple stress can be utilized to develop varieties with broad-spectrum stress tolerance.

Plasticity of the Root System Architecture and Leaf Gas Exchange Parameters Are Important for Maintaining Bottle Gourd Responses under Water Deficit

The evaluation of root system architecture (RSA) development and the physiological responses of crop plants grown under water-limited conditions are of great importance. The purpose of this study was to examine the short-term variation of the morphological and physiological plasticity of Lagenaria siceraria genotypes under water deficit, evaluating the changes in the relationship between the root system architecture and leaf physiological responses. Bottle gourd genotypes were grown in rhizoboxes under well-watered and water deficit conditions. Significant genotype-water regime interactions were observed for several RSA traits and physiological parameters. Biplot analyses confirmed that the drought-tolerant genotypes (BG-48 and GC) showed a high net CO₂ assimilation rate, stomatal conductance, transpiration rates with a smaller length, and a reduced root length density of second-order lateral roots, whereas the genotypes BG-67 and Osorno were identified as drought-sensitive and showed greater values for average root length and the density of second-order lateral roots. Consequently, a reduced length and density of lateral roots in bottle gourd should constitute a response to water deficit. The root traits studied here can be used to evaluate bottle gourd performance under novel water management strategies and as criteria for breeding selection.

A functional-structural model of upland rice root systems reveals the importance of laterals and growing root tips for phosphate uptake from wet and dry soils

BACKGROUND AND AIMS

Upland rice is often grown where water and phosphorus (P) are limited. To better understand the interaction between water and P availability, functional-structural models that mechanistically represent small-scale nutrient gradients and water dynamics in the rhizosphere are needed.

METHODS

Rice was grown in large columns using a P-deficient soil at three P supplies in the topsoil (deficient, sub-optimal and non-limiting) in combination with two water regimes (field capacity vs. drying periods). Root system characteristics, such as nodal root number, lateral types, interbranch distance, root diameters and the distribution of biomass with depth, as well as water and P uptake, were measured. Based on the observed root data, 3-D root systems were reconstructed by calibrating the structural architecure model CRootBox for each scenario. Water flow and P transport in the soil to each of the individual root segments of the generated 3-D root architectures were simulated using a multiscale flow and transport model. Total water and P uptake were then computed by adding up the uptake by all the root segments.

KEY RESULTS

Measurements showed that root architecture was significantly affected by the treatments. The moist, high P scenario had 2.8 times the root mass, double the number of nodal roots and more S-type laterals than the dry, low P scenario. Likewise, measured plant P uptake increased >3-fold by increasing P and water supply. However, drying periods reduced P uptake at high but not at low P supply. Simulation results adequately predicted P uptake in all scenarios when the Michaelis-Menten constant (Km) was corrected for diffusion limitation. They showed that the key drivers for P uptake are the different types of laterals (i.e. S- and L-type) and growing root tips. The L-type laterals become more important for overall water and P uptake than the S-type laterals in the dry scenarios. This is true across all the P treatments, but the effect is more pronounced as the P availability decreases.

CONCLUSIONS

This functional-structural model can predict the function of specific rice roots in terms of P and water uptake under different P and water supplies, when the structure of the root system is known. A future challenge is to predict how the structure root systems responds to nutrient and water availability.

Multiscale computational models can guide experimentation and targeted measurements for crop improvement

Computational models of plants have identified gaps in our understanding of biological systems, and have revealed ways to optimize cellular processes or organ-level architecture to increase productivity. Thus, computational models are learning tools that help direct experimentation and measurements. Models are simplifications of complex systems, and often simulate specific processes at single scales (e.g. temporal, spatial, organizational, etc.). Consequently, single-scale models are unable to capture the critical cross-scale interactions that result in emergent properties of the system. In this perspective article, we contend that to accurately predict how a plant will respond in an untested environment, it is necessary to integrate mathematical models across biological scales. Computationally mimicking the flow of biological information from the genome to the phenome is an important step in discovering new experimental strategies to improve crops. A key challenge is to connect models across biological, temporal and computational (e.g. CPU versus GPU) scales, and then to visualize and interpret integrated model outputs. We address this challenge by describing the efforts of the international Crops in silico consortium.