Plant root systems are key drivers of plant function and yield. They are also under-explored targets to meet global food and energy demands. Many new technologies have been developed to characterize crop root system architecture (CRSA). These technologies have the potential to accelerate the progress in understanding the genetic control and environmental response of CRSA. Putting this potential into practice requires new methods and algorithms to analyze CRSA in digital images. Most prior approaches have solely focused on the estimation of root traits from images, yet no integrated platform exists that allows easy and intuitive access to trait extraction and analysis methods from images combined with storage solutions linked to metadata. Automated high-throughput phenotyping methods are increasingly used in laboratory-based efforts to link plant genotype with phenotype, whereas similar field-based studies remain predominantly manual low-throughput.
Here, we present an open-source phenomics platform “DIRT”, as a means to integrate scalable supercomputing architectures into field experiments and analysis pipelines. DIRT is an online platform that enables researchers to store images of plant roots, measure dicot and monocot root traits under field conditions, and share data and results within collaborative teams and the broader community. The DIRT platform seamlessly connects end-users with large-scale compute “commons” enabling the estimation and analysis of root phenotypes from field experiments of unprecedented size.
DIRT is an automated high-throughput computing and collaboration platform for field based crop root phenomics. The platform is accessible at http://dirt.iplantcollaborative.org/ and hosted on the iPlant cyber-infrastructure using high-throughput grid computing resources of the Texas Advanced Computing Center (TACC). DIRT is a high volume central depository and high-throughput RSA trait computation platform for plant scientists working on crop roots. It enables scientists to store, manage and share crop root images with metadata and compute RSA traits from thousands of images in parallel. It makes high-throughput RSA trait computation available to the community with just a few button clicks. As such it enables plant scientists to spend more time on science rather than on technology. All stored and computed data is easily accessible to the public and broader scientific community. We hope that easy data accessibility will attract new tool developers and spur creative data usage that may even be applied to other fields of science.
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Soils vary widely in mineral nutrient availability and physical characteristics, but the influence of this variability on plant responses to elevated CO2 remains poorly understood. As a first approximation of the effect of global soil variability on plant growth response to CO2, we evaluated the effect of CO2 on tall fescue (Festuca arundinacea) grown in soils representing 10 of the 12 global soil orders plus a high-fertility control. Plants were grown in small pots in continuously stirred reactor tanks in a greenhouse. Elevated CO2 (800 ppm) increased plant biomass in the high-fertility control and in two of the more fertile soils. Elevated CO2 had variable effects on foliar mineral concentration—nitrogen was not altered by elevated CO2, and phosphorus and potassium were only affected by CO2 in a small number of soils. While leaf photosynthesis was stimulated by elevated CO2 in six soils, canopy photosynthesis was not stimulated. Four principle components were identified; the first was associated with foliar minerals and soil clay, and the second with soil acidity and foliar manganese concentration. The third principle component was associated with gas exchange, and the fourth with plant biomass and soil minerals. Soils in which tall fescue did not respond to elevated CO2 account for 83% of global land area. These results show that variation in soil physical and chemical properties have important implications for plant responses to global change, and highlight the need to consider soil variability in models of vegetation response to global change.
soil taxonomy; soil orders; elevated CO2; Festuca arundinaceae; tall fescue
Background and Aims
Since ancient times in the Americas, maize, bean and squash have been grown together in a polyculture known as the ‘three sisters’. This polyculture and its maize/bean variant have greater yield than component monocultures on a land-equivalent basis. This study shows that below-ground niche complementarity may contribute to this yield advantage.
Monocultures and polycultures of maize, bean and squash were grown in two seasons in field plots differing in nitrogen (N) and phosphorus (P) availability. Root growth patterns of individual crops and entire polycultures were determined using a modified DNA-based technique to discriminate roots of different species.
The maize/bean/squash and maize/bean polycultures had greater yield and biomass production on a land-equivalent basis than the monocultures. Increased biomass production was largely caused by a complementarity effect rather than a selection effect. The differences in root crown architecture and vertical root distribution among the components of the ‘three sisters’ suggest that these species have different, possibly complementary, nutrient foraging strategies. Maize foraged relatively shallower, common bean explored the vertical soil profile more equally, while the root placement of squash depended on P availability. The density of lateral root branching was significantly greater for all species in the polycultures than in the monocultures.
It is concluded that species differences in root foraging strategies increase total soil exploration, with consequent positive effects on the growth and yield of these ancient polycultures.
‘Three sisters’; niche complementarity; polyculture; intercropping; nitrogen; phosphorus; plant nutrition; root architecture; root foraging; maize; bean; squash; Zea mays; Phaseolus vulgaris; Cucurbita
Root phenes were phenotyped on all whorls of field-grown maize for the first time, and their integration could explain up to 70% of shoot mass variation in low nitrogen soils.
Root architecture is an important regulator of nitrogen (N) acquisition. Existing methods to phenotype the root architecture of cereal crops are generally limited to seedlings or to the outer roots of mature root crowns. The functional integration of root phenes is poorly understood. In this study, intensive phenotyping of mature root crowns of maize was conducted to discover phenes and phene modules related to N acquisition. Twelve maize genotypes were grown under replete and deficient N regimes in the field in South Africa and eight in the USA. An image was captured for every whorl of nodal roots in each crown. Custom software was used to measure root phenes including nodal occupancy, angle, diameter, distance to branching, lateral branching, and lateral length. Variation existed for all root phenes within maize root crowns. Size-related phenes such as diameter and number were substantially influenced by nodal position, while angle, lateral density, and distance to branching were not. Greater distance to branching, the length from the shoot to the emergence of laterals, is proposed to be a novel phene state that minimizes placing roots in already explored soil. Root phenes from both older and younger whorls of nodal roots contributed to variation in shoot mass and N uptake. The additive integration of root phenes accounted for 70% of the variation observed in shoot mass in low N soil. These results demonstrate the utility of intensive phenotyping of mature root systems, as well as the importance of phene integration in soil resource acquisition.
Capture; corn; interaction; root system architecture; RSA; soil; synergism; trait; uptake
Suboptimal availability of water and nutrients is a primary limitation to plant growth in terrestrial ecosystems. The acquisition of soil resources by plant roots is therefore an important component of plant fitness and agricultural productivity. Plant root systems comprise a set of phenes, or traits, that interact. Phenes are the units of the plant phenotype, and phene states represent the variation in form and function a particular phene may take. Root phenes can be classified as affecting resource acquisition or utilization, influencing acquisition through exploration or exploitation, and in being metabolically influential or neutral. These classifications determine how one phene will interact with another phene, whether through foraging mechanisms or metabolic economics. Phenes that influence one another through foraging mechanisms are likely to operate within a phene module, a group of interacting phenes, that may be co-selected. Examples of root phene interactions discussed are: (1) root hair length × root hair density, (2) lateral branching × root cortical aerenchyma (RCA), (3) adventitious root number × adventitious root respiration and basal root growth angle (BRGA), (4) nodal root number × RCA, and (5) BRGA × root hair length and density. Progress in the study of phenes and phene interactions will be facilitated by employing simulation modeling and near-isophenic lines that allow the study of specific phenes and phene combinations within a common phenotypic background. Developing a robust understanding of the phenome at the organismal level will require new lines of inquiry into how phenotypic integration influences plant function in diverse environments. A better understanding of how root phenes interact to affect soil resource acquisition will be an important tool in the breeding of crops with superior stress tolerance and reduced dependence on intensive use of inputs.
root architecture; phenomics; functional traits; ideotype; soil resources
Root bending, tensile strength, and ability to penetrate hard soil are related to anatomical phenes that are subject to selection in crop breeding programs.
The ability of roots to penetrate hard soil is important for crop productivity but specific root phenes contributing to this ability are poorly understood. Root penetrability and biomechanical properties are likely to vary in the root system dependent on anatomical structure. No information is available to date on the influence of root anatomical phenes on root penetrability and biomechanics. Root penetration ability was evaluated using a wax layer system. Root tensile and bending strength were evaluated in plant roots grown in the greenhouse and in the field. Root anatomical phenes were found to be better predictors of root penetrability than root diameter per se and associated with smaller distal cortical region cell size. Smaller outer cortical region cells play an important role in stabilizing the root against ovalization and reducing the risk of local buckling and collapse during penetration, thereby increasing root penetration of hard layers. The use of stele diameter was found to be a better predictor of root tensile strength than root diameter. Cortical thickness, cortical cell count, cortical cell wall area and distal cortical cell size were stronger predictors of root bend strength than root diameter. Our results indicate that root anatomical phenes are important predictors for root penetrability of high-strength layers and root biomechanical properties.
Anatomy; bending strength; phenes; tensile strength.
Comprehensive analysis of maize root phenotypes over the past century indicates that they have evolved to be more efficient in acquiring nitrogen.
Increasing the nitrogen use efficiency of maize is an important goal for food security and agricultural sustainability. In the past 100 years, maize breeding has focused on yield and above-ground phenes. Over this period, maize cultivation has changed from low fertilizer inputs and low population densities to intensive fertilization and dense populations. The authors hypothesized that through indirect selection the maize root system has evolved phenotypes suited to more intense competition for nitrogen. Sixteen maize varieties representing commercially successful lines over the past century were planted at two nitrogen levels and three planting densities. Root systems of the most recent material were 7 º more shallow, had one less nodal root per whorl, had double the distance from nodal root emergence to lateral branching, and had 14% more metaxylem vessels, but total mextaxylem vessel area remained unchanged because individual metaxylem vessels had 12% less area. Plasticity was also observed in cortical phenes such as aerenchyma, which increased at greater population densities. Simulation modelling with SimRoot demonstrated that even these relatively small changes in root architecture and anatomy could increase maize shoot growth by 16% in a high density and high nitrogen environment. The authors concluded that evolution of maize root phenotypes over the past century is consistent with increasing nitrogen use efficiency. Introgression of more contrasting root phene states into the germplasm of elite maize and determination of the functional utility of these phene states in multiple agronomic conditions could contribute to future yield gains.
Anatomy; architecture; density; maize; nitrogen; phenotype; root.
Maize genotypes producing fewer lateral roots extend them further into the soil, improving overall plant N acquisition.
Suboptimal nitrogen (N) availability is a primary constraint for crop production in developing countries, while in developed countries, intensive N fertilization is a primary economic, energy, and environmental cost for crop production. We tested the hypothesis that under low-N conditions, maize (Zea mays) lines with few but long (FL) lateral roots would have greater axial root elongation, deeper rooting, and greater N acquisition than lines with many but short (MS) lateral roots. Maize recombinant inbred lines contrasting in lateral root number and length were grown with adequate and suboptimal N in greenhouse mesocosms and in the field in the USA and South Africa (SA). In low-N mesocosms, the FL phenotype had substantially reduced root respiration and greater rooting depth than the MS phenotype. In low-N fields in the USA and SA, the FL phenotype had greater rooting depth, shoot N content, leaf photosynthesis, and shoot biomass than the MS phenotype. The FL phenotype yielded 31.5% more than the MS phenotype under low N in the USA. Our results are consistent with the hypothesis that sparse but long lateral roots improve N capture from low-N soils. These results with maize probably pertain to other species. The FL lateral root phenotype merits consideration as a selection target for greater crop N efficiency.
Branching; frequency; lateral root; maize (Zea mays); nitrogen (N); respiration.
Background and Aims
Formation of root cortical aerenchyma (RCA) can be induced by nutrient deficiency. In species adapted to aerobic soil conditions, this response is adaptive by reducing root maintenance requirements, thereby permitting greater soil exploration. One trade-off of RCA formation may be reduced radial transport of nutrients due to reduction in living cortical tissue. To test this hypothesis, radial nutrient transport in intact roots of maize (Zea mays) was investigated in two radiolabelling experiments employing genotypes with contrasting RCA.
In the first experiment, time-course dynamics of phosphate loading into the xylem were measured from excised nodal roots that varied in RCA formation. In the second experiment, uptake of phosphate, calcium and sulphate was measured in seminal roots of intact young plants in which variation in RCA was induced by treatments altering ethylene action or genetic differences.
In each of three paired genotype comparisons, the rate of phosphate exudation of high-RCA genotypes was significantly less than that of low-RCA genotypes. In the second experiment, radial nutrient transport of phosphate and calcium was negatively correlated with the extent of RCA for some genotypes.
The results support the hypothesis that RCA can reduce radial transport of some nutrients in some genotypes, which could be an important trade-off of this trait.
Aerenchyma; radial transport; root; nutrient uptake; phosphorus; sulfur; calcium; maize; Zea mays
A hypothetical ideotype is presented to optimize water and N acquisition by maize root systems. The overall premise is that soil resource acquisition is optimized by the coincidence of root foraging and resource availability in time and space. Since water and nitrate enter deeper soil strata over time and are initially depleted in surface soil strata, root systems with rapid exploitation of deep soil would optimize water and N capture in most maize production environments.
• The ideotype Specific phenes that may contribute to rooting depth in maize include (a) a large diameter primary root with few but long laterals and tolerance of cold soil temperatures, (b) many seminal roots with shallow growth angles, small diameter, many laterals, and long root hairs, or as an alternative, an intermediate number of seminal roots with steep growth angles, large diameter, and few laterals coupled with abundant lateral branching of the initial crown roots, (c) an intermediate number of crown roots with steep growth angles, and few but long laterals, (d) one whorl of brace roots of high occupancy, having a growth angle that is slightly shallower than the growth angle for crown roots, with few but long laterals, (e) low cortical respiratory burden created by abundant cortical aerenchyma, large cortical cell size, an optimal number of cells per cortical file, and accelerated cortical senescence, (f) unresponsiveness of lateral branching to localized resource availability, and (g) low Km and high Vmax for nitrate uptake. Some elements of this ideotype have experimental support, others are hypothetical. Despite differences in N distribution between low-input and commercial maize production, this ideotype is applicable to low-input systems because of the importance of deep rooting for water acquisition. Many features of this ideotype are relevant to other cereal root systems and more generally to root systems of dicotyledonous crops.
Root phenes; ideotype; water; nitrogen; architecture; anatomy
Background and Aims
Root cortical aerenchyma (RCA) increases water and nutrient acquisition by reducing the metabolic costs of soil exploration. In this study the hypothesis was tested that living cortical area (LCA; transversal root cortical area minus aerenchyma area and intercellular air space) is a better predictor of root respiration, soil exploration and, therefore, drought tolerance than RCA formation or root diameter.
RCA, LCA, root respiration, root length and biomass loss in response to drought were evaluated in maize (Zea mays) recombinant inbred lines grown with adequate and suboptimal irrigation in soil mesocosms.
Root respiration was highly correlated with LCA. LCA was a better predictor of root respiration than either RCA or root diameter. RCA reduced respiration of large-diameter roots. Since RCA and LCA varied in different parts of the root system, the effects of RCA and LCA on root length were complex. Greater crown-root LCA was associated with reduced crown-root length relative to total root length. Reduced LCA was associated with improved drought tolerance.
The results are consistent with the hypothesis that LCA is a driver of root metabolic costs and may therefore have adaptive significance for water acquisition in drying soil.
Root; aerenchyma; respiration; drought; cortex; Zea mays
Background and Aims
During their domestication, maize, bean and squash evolved in polycultures grown by small-scale farmers in the Americas. Polycultures often overyield on low-fertility soils, which are a primary production constraint in low-input agriculture. We hypothesized that root architectural differences among these crops causes niche complementarity and thereby greater nutrient acquisition than corresponding monocultures.
A functional–structural plant model, SimRoot, was used to simulate the first 40 d of growth of these crops in monoculture and polyculture and to determine the effects of root competition on nutrient uptake and biomass production of each plant on low-nitrogen, -phosphorus and -potassium soils.
Squash, the earliest domesticated crop, was most sensitive to low soil fertility, while bean, the most recently domesticated crop, was least sensitive to low soil fertility. Nitrate uptake and biomass production were up to 7 % greater in the polycultures than in the monocultures, but only when root architecture was taken into account. Enhanced nitrogen capture in polycultures was independent of nitrogen fixation by bean. Root competition had negligible effects on phosphorus or potassium uptake or biomass production.
We conclude that spatial niche differentiation caused by differences in root architecture allows polycultures to overyield when plants are competing for mobile soil resources. However, direct competition for immobile resources might be negligible in agricultural systems. Interspecies root spacing may also be too large to allow maize to benefit from root exudates of bean or squash. Above-ground competition for light, however, may have strong feedbacks on root foraging for immobile nutrients, which may increase cereal growth more than it will decrease the growth of the other crops. We note that the order of domestication of crops correlates with increasing nutrient efficiency, rather than production potential.
‘Three sisters’; polyculture; root architecture; SimRoot; functional–structural model; nutrient deficiency; maize; bean; squash; niche complementarity; root competition
Recent advances in root biology are making it possible to genetically design root systems with enhanced soil exploration and resource capture. These cultivars would have substantial value for improving food security in developing nations, where yields are limited by drought and low soil fertility, and would enhance the sustainability of intensive agriculture. Many of the phenes controlling soil resource capture are related to root architecture. We propose that a better understanding of the root phenome is needed to effectively translate genetic advances into improved crop cultivars. Elementary, unique root phenes need to be identified. We need to understand the ‘fitness landscape’ for these phenes: how they affect crop performance in an array of environments and phenotypes. Finally, we need to develop methods to measure phene expression rapidly and economically without artefacts. These challenges, especially mapping the fitness landscape, are non-trivial, and may warrant new research and training modalities.
root architecture; phenome; plant breeding
Background and Aims
Timing of reproduction is a key life-history trait that is regulated by resource availability. Delayed reproduction in soils with low phosphorus availability is common among annuals, in contrast to the accelerated reproduction typical of other low-nutrient environments. It is hypothesized that this anomalous response arises from the high marginal value of additional allocation to root growth caused by the low mobility of phosphorus in soils.
To better understand the benefits and costs of such delayed reproduction, a two-resource dynamic allocation model of plant growth and reproduction is presented. The model incorporates growth, respiration, and carbon and phosphorus acquisition of both root and shoot tissue, and considers the reallocation of resources from senescent leaves. The model is parameterized with data from Arabidopsis and the optimal reproductive phenology is explored in a range of environments.
The model predicts delayed reproduction in low-phosphorus environments. Reproductive timing in low-phosphorus environments is quite sensitive to phosphorus mobility, but is less sensitive to the temporal distribution of mortality risks. In low-phosphorus environments, the relative metabolic cost of roots was greater, and reproductive allocation reduced, compared with high-phosphorus conditions. The model suggests that delayed reproduction in response to low phosphorus availability may be reduced in plants adapted to environments where phosphorus mobility is greater.
Delayed reproduction in low-phosphorus soils can be a beneficial response allowing for increased acquisition and utilization of phosphorus. This finding has implications both for efforts to breed crops for low-phosphorus soils, and for efforts to understand how climate change may impact plant growth and productivity in low-phosphorus environments.
Dynamic allocation budget; optimization; Arabidopsis thaliana; flowering phenology; root–shoot partitioning; phosphorus availability
Background and Aims
The formation of root cortical aerenchyma (RCA) reduces root respiration and nutrient content by converting living tissue to air volume. It was hypothesized that RCA increases soil resource acquisition by reducing the metabolic and phosphorus cost of soil exploration.
To test the quantitative logic of the hypothesis, SimRoot, a functional–structural plant model with emphasis on root architecture and nutrient acquisition, was employed. Sensitivity analyses for the effects of RCA on the initial 40 d of growth of maize (Zea mays) and common bean (Phaseolus vulgaris) were conducted in soils with varying degrees of phosphorus availability. With reference to future climates, the benefit of having RCA in high CO2 environments was simulated.
The model shows that RCA may increase the growth of plants faced with suboptimal phosphorus availability up to 70 % for maize and 14 % for bean after 40 d of growth. Maximum increases were obtained at low phosphorus availability (3 µm). Remobilization of phosphorus from dying cells had a larger effect on plant growth than reduced root respiration. The benefit of both these functions was additive and increased over time. Larger benefits may be expected for mature plants. Sensitivity analysis for light-use efficiency showed that the benefit of having RCA is relatively stable, suggesting that elevated CO2 in future climates will not significantly effect the benefits of having RCA.
The results support the hypothesis that RCA is an adaptive trait for phosphorus acquisition by remobilizing phosphorus from the root cortex and reducing the metabolic costs of soil exploration. The benefit of having RCA in low-phosphorus soils is larger for maize than for bean, as maize is more sensitive to low phosphorus availability while it has a more ‘expensive’ root system. Genetic variation in RCA may be useful for breeding phosphorus-efficient crop cultivars, which is important for improving global food security.
Zea mays; Phaseolus vulgaris; root cortical aerenchyma; phosphorus deficiency; SimRoot; functional structural modelling; carbon economy
• Background and Aims Root hair density (i.e. the number of root hairs per unit root length) in Arabidopsis thaliana varies among individual plants in response to different nutrient stresses. The degree of such variation, defined as inequality, serves as a unique indicator of the uniformity of response within a plant population to nutrient availability.
• Methods Using the Gini coefficient (G) as an inequality index, the inequality of root hair density in Arabidopsis thaliana ‘Columbia’ was evaluated under conditions of nutrient stresses; in particular the effect of phosphorus and its interaction with ethylene.
• Key Results With decreasing phosphorus concentration, root hair density increased while inequality decreased logarithmically. The addition of the ethylene precursor 1-aminocyclopropane-1-carboxylate (ACC) under high phosphorus increased root hair density and decreased inequality by 7-fold. Inhibition of ethylene action with 1-methylcyclopropene (MCP) and silver thiosulphate (STS) under low phosphorus decreased root hair density, and increased inequality by 9-fold and 4-fold, respectively. The ethylene action inhibitors had little effect on root hair density under high phosphorus, but inequality increased 3-fold in the presence of MCP and decreased 2-fold in the presence of STS. Compared with the control, deficiencies in S, N and K increased inequality of root hair density, whereas deficiencies in P, Ca, B, Mn, Fe, Zn, Cu and Mg decreased inequality. In particular, the inequality of root hair density increased by over 2-fold under deficiencies of N or K, but decreased 14-fold under phosphorus deficiency.
• Conclusions The inequality analysis indicates a strong correlation between prevalent signals from the environment (i.e. phosphorus stress) and the response of the plant, and the role of ethylene in this response. As the environmental signals become stronger, an increasing proportion of individuals respond, resulting in a decrease in variation in responsiveness among individual plants as indicated by reduced inequality.
Arabidopsis thaliana; root hairs; nutrient deficiencies; phosphorus; ethylene; Gini coefficient; inequality; Lorenz curve
• Background and Aims Fractal analysis allows calculation of fractal dimension, fractal abundance and lacunarity. Fractal analysis of plant roots has revealed correlations of fractal dimension with age, topology or genotypic variation, while fractal abundance has been associated with root length. Lacunarity is associated with heterogeneity of distribution, and has yet to be utilized in analysis of roots. In this study, fractal analysis was applied to the study of root architecture and acquisition of diffusion‐limited nutrients. The hypothesis that soil depletion and root competition are more closely correlated with a combination of fractal parameters than by any one alone was tested.
• Model The geometric simulation model SimRoot was used to dynamically model roots of various architectures growing for up to 16 d in three soil types with contrasting nutrient mobility. Fractal parameters were calculated for whole roots, projections of roots and vertical slices of roots taken at 0, 2·5 and 5 cm from the root origin. Nutrient depletion volumes, competition volumes, and relative competition were regressed against fractal parameters and root length.
• Key Results Root length was correlated with depletion volume, competition volume and relative competition at all times. In analysis of three‐dimensional, projected roots and 0 cm slices, log(fractal abundance) was highly correlated with log(depletion volume) when times were pooled. Other than this, multiple regression yielded better correlations than regression with single fractal parameters. Correlations decreased with age of roots and distance of vertical slices from the root origin. Field data were also examined to see if fractal dimension, fractal abundance and lacunarity can be used to distinguish common bean genotypes in field situations. There were significant differences in fractal dimension and fractal abundance, but not in lacunarity.
• Conclusions These results suggest that applying fractal analysis to research of soil exploration by root systems should include fractal abundance, and possibly lacunarity, along with fractal dimension.
Fractal dimension; fractal abundance; lacunarity; phosphorus; depletion; competition; Phaseolus vulgaris; SimRoot; simulation modelling