Spatiotemporal variation of nitrate uptake kinetics within the maize (Zea mays L.) root system is associated with greater nitrate uptake and interactions with architectural phenes

Increasing maize nitrogen acquisition efficiency is a major goal for the 21st century. Nitrate uptake kinetics (NUK) are defined by I max and K m, which denote the maximum uptake rate and the affinity of transporters, respectively. Because NUK have been studied predominantly at the molecular and whole-root system levels, little is known about the functional importance of NUK variation within root systems. A novel method was created to measure NUK of root segments that demonstrated variation in NUK among root classes (seminal, lateral, crown, and brace). I max varied among root class, plant age, and nitrate deprivation combinations, but was most affected by plant age, which increased I max, and nitrate deprivation time, which decreased I max K m was greatest for crown roots. The functional-structural simulation SimRoot was used for sensitivity analysis of plant growth to root segment I max and K m, as well as to test interactions of I max with root system architectural phenes. Simulated plant growth was more sensitive to I max than K m, and reached an asymptote near the maximum I max observed in the empirical studies. Increasing the I max of lateral roots had the largest effect on shoot growth. Additive effects of I max and architectural phenes on nitrate uptake were observed. Empirically, only lateral root tips aged 20 d operated at the maximum I max, and simulations demonstrated that increasing all seminal and lateral classes to this maximum rate could increase plant growth by as much as 26%. Therefore, optimizing I max for all maize root classes merits attention as a promising breeding goal.

Plants in silico: why, why now and what?--an integrative platform for plant systems biology research

A paradigm shift is needed and timely in moving plant modelling from largely isolated efforts to a connected community endeavour that can take full advantage of advances in computer science and in mechanistic understanding of plant processes. Plants in silico (Psi) envisions a digital representation of layered dynamic modules, linking from gene networks and metabolic pathways through to cellular organization, tissue, organ and whole plant development, together with resource capture and use efficiency in dynamic competitive environments, ultimately allowing a mechanistically rich simulation of the plant or of a community of plants in silico. The concept is to integrate models or modules from different layers of organization spanning from genome to phenome to ecosystem in a modular framework allowing the use of modules of varying mechanistic detail representing the same biological process. Developments in high-performance computing, functional knowledge of plants, the internet and open-source version controlled software make achieving the concept realistic. Open source will enhance collaboration and move towards testing and consensus on quantitative theoretical frameworks. Importantly, Psi provides a quantitative knowledge framework where the implications of a discovery at one level, for example, single gene function or developmental response, can be examined at the whole plant or even crop and natural ecosystem levels.

Digital imaging of root traits (DIRT): a high-throughput computing and collaboration platform for field-based root phenomics

BACKGROUND

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.

DESCRIPTION

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.

CONCLUSION

DIRT is an automated high-throughput computing and collaboration platform for field based crop root phenomics. The platform is accessible at http://www.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.

Root phenes that reduce the metabolic costs of soil exploration: opportunities for 21st century agriculture

Crop genotypes with reduced metabolic costs of soil exploration would have improved water and nutrient acquisition. Three strategies to achieve this goal are (1) production of the optimum number of axial roots; (2) greater biomass allocation to root classes that are less metabolically demanding; and (3) reduction of the respiratory requirement of root tissue. An example of strategy 1 is the case of reduced crown root number in maize, which is associated with greater rooting depth, N capture and yield in low N soil. An example of strategy 2 is the case of increased hypocotyl-borne rooting in bean, which decreases root cost and increases P capture from low P soil. Examples of strategy 3 are the cases of increased formation of root cortical aerenchyma, decreased cortical cell file number and increased cortical cell size in maize, which decrease specific root respiration, increase rooting depth and increase water capture and yield under water stress. Root cortical aerenchyma also increases N capture and yield under N stress. Root phenes that reduce the metabolic cost of soil exploration are promising, underexploited avenues to the climate-resilient, resource-efficient crops that are urgently needed in global agriculture.

Manganese phytotoxicity: new light on an old problem

BACKGROUND

Manganese (Mn) is an essential micronutrient that is phytotoxic under certain edaphic and climatic conditions. Multiple edaphic factors regulate Mn redox status and therefore its phytoavailability, and multiple environmental factors including light intensity and temperature interact with Mn phytotoxicity. The complexity of these interactions coupled with substantial genetic variation in Mn tolerance have hampered the recognition of Mn toxicity as an important stress in many natural and agricultural systems.

SCOPE

Conflicting theories have been advanced regarding the mechanism of Mn phytotoxicity and tolerance. One line of evidence suggests that Mn toxicity ocurrs in the leaf apoplast, while another suggests that toxicity occurs by disruption of photosynthetic electron flow in chloroplasts. These conflicting results may at least in part be attributed to the light regimes employed, with studies conducted under light intensities approximating natural sunlight showing evidence of photo-oxidative stress as a mechanism of toxicity. Excessive Mn competes with the transport and metabolism of other cationic metals, causing a range of induced nutrient deficiencies. Compartmentation, exclusion and detoxification mechanisms may all be involved in tolerance to excess Mn. The strong effects of light, temperature, precipitation and other climate variables on Mn phytoavailability and phytotoxicity suggest that global climate change is likely to exacerbate Mn toxicity in the future, which has largely escaped scientific attention.

CONCLUSIONS

Given that Mn is terrestrially ubiquitous, it is imperative that the heightened risk of Mn toxicity to both managed and natural plant ecosystems be factored into evaluation of the potential impacts of global climate change on vegetation. Large inter- and intraspecific genetic variation in tolerance to Mn toxicity suggests that increased Mn toxicity in natural ecosystems may drive changes in community composition, but that in agroecosystems crops may be developed with greater Mn tolerance. These topics deserve greater research attention.

Intensive field phenotyping of maize (Zea mays L.) root crowns identifies phenes and phene integration associated with plant growth and nitrogen acquisition

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.

Reduced Lateral Root Branching Density Improves Drought Tolerance in Maize

An emerging paradigm is that root traits that reduce the metabolic costs of soil exploration improve the acquisition of limiting soil resources. Here, we test the hypothesis that reduced lateral root branching density will improve drought tolerance in maize (Zea mays) by reducing the metabolic costs of soil exploration, permitting greater axial root elongation, greater rooting depth, and thereby greater water acquisition from drying soil. Maize recombinant inbred lines with contrasting lateral root number and length (few but long [FL] and many but short [MS]) were grown under water stress in greenhouse mesocosms, in field rainout shelters, and in a second field environment with natural drought. Under water stress in mesocosms, lines with the FL phenotype had substantially less lateral root respiration per unit of axial root length, deeper rooting, greater leaf relative water content, greater stomatal conductance, and 50% greater shoot biomass than lines with the MS phenotype. Under water stress in the two field sites, lines with the FL phenotype had deeper rooting, much lighter stem water isotopic signature, signifying deeper water capture, 51% to 67% greater shoot biomass at flowering, and 144% greater yield than lines with the MS phenotype. These results entirely support the hypothesis that reduced lateral root branching density improves drought tolerance. The FL lateral root phenotype merits consideration as a selection target to improve the drought tolerance of maize and possibly other cereal crops.

Root anatomical phenes predict root penetration ability and biomechanical properties in maize (Zea Mays)

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.

Reduced frequency of lateral root branching improves N capture from low-N soils in maize

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.

Opportunities and challenges in the subsoil: pathways to deeper rooted crops

Greater exploitation of subsoil resources by annual crops would afford multiple benefits, including greater water and N acquisition in most agroecosystems, and greater sequestration of atmospheric C. Constraints to root growth in the subsoil include soil acidity (an edaphic stress complex consisting of toxic levels of Al, inadequate levels of P and Ca, and often toxic levels of Mn), soil compaction, hypoxia, and suboptimal temperature. Multiple root phenes under genetic control are associated with adaptation to these constraints, opening up the possibility of breeding annual crops with root traits improving subsoil exploration. Adaptation to Al toxicity, hypoxia, and P deficiency are intensively researched, adaptation to soil hardness and suboptimal temperature less so, and adaptations to Ca deficiency and Mn toxicity are poorly understood. The utility of specific phene states may vary among soil taxa and management scenarios, interactions which in general are poorly understood. These traits and issues merit research because of their potential value in developing more productive, sustainable, benign, and resilient agricultural systems.

Evolution of US maize (Zea mays L.) root architectural and anatomical phenes over the past 100 years corresponds to increased tolerance of nitrogen stress

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.

Response to elevated CO2 in the temperate C3 grass Festuca arundinaceae across a wide range of soils

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.

QTL mapping and phenotypic variation of root anatomical traits in maize (Zea mays L.)

Root anatomical trait variation is described for three maize RIL populations. Six quantitative trait loci (QTL) are presented for anatomical traits: root cross-sectional area, % living cortical area, aerenchyma area, and stele area. Root anatomy is directly related to plant performance, influencing resource acquisition and transport, the metabolic cost of growth, and the mechanical strength of the root system. Ten root anatomical traits were measured in greenhouse-grown plants from three recombinant inbred populations of maize [intermated B73 × Mo17 (IBM), Oh43 × W64a (OhW), and Ny821 × H99 (NyH)]. Traits included areas of cross section, stele, cortex, aerenchyma, and cortical cells, percentages of the cortex occupied by aerenchyma, and cortical cell file number. Significant phenotypic variation was observed for each of the traits, with maximum values typically seven to ten times greater than minimum values. Means and ranges were similar for the OhW and NyH populations for all traits, while the IBM population had lower mean values for the majority of traits, but a 50% greater range of variation for aerenchyma area. A principal component analysis showed a similar trait structure for the three families, with clustering of area and count traits. Strong correlations were observed among area traits in the cortex, stele, and cross-section. The aerenchyma and percent living cortical area traits were independent of other traits. Six QTL were identified for four of the traits. The phenotypic variation explained by the QTL ranged from 4.7% (root cross-sectional area, OhW population) to 12.0% (percent living cortical area, IBM population). Genetic variation for root anatomical traits can be harnessed to increase abiotic stress tolerance and provide insights into mechanisms controlling phenotypic variation for root anatomy.

Root foraging elicits niche complementarity-dependent yield advantage in the ancient 'three sisters' (maize/bean/squash) polyculture

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.

METHODS

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.

KEY RESULTS

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.

CONCLUSIONS

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.

Reduced root cortical cell file number improves drought tolerance in maize

We tested the hypothesis that reduced root cortical cell file number (CCFN) would improve drought tolerance in maize (Zea mays) by reducing the metabolic costs of soil exploration. Maize genotypes with contrasting CCFN were grown under well-watered and water-stressed conditions in greenhouse mesocosms and in the field in the United States and Malawi. CCFN ranged from six to 19 among maize genotypes. In mesocosms, reduced CCFN was correlated with 57% reduction of root respiration per unit of root length. Under water stress in the mesocosms, genotypes with reduced CCFN had between 15% and 60% deeper rooting, 78% greater stomatal conductance, 36% greater leaf CO2 assimilation, and between 52% to 139% greater shoot biomass than genotypes with many cell files. Under water stress in the field, genotypes with reduced CCFN had between 33% and 40% deeper rooting, 28% lighter stem water oxygen isotope enrichment (δ(18)O) signature signifying deeper water capture, between 10% and 35% greater leaf relative water content, between 35% and 70% greater shoot biomass at flowering, and between 33% and 114% greater yield than genotypes with many cell files. These results support the hypothesis that reduced CCFN improves drought tolerance by reducing the metabolic costs of soil exploration, enabling deeper soil exploration, greater water acquisition, and improved growth and yield under water stress. The large genetic variation for CCFN in maize germplasm suggests that CCFN merits attention as a breeding target to improve the drought tolerance of maize and possibly other cereal crops.

Large root cortical cell size improves drought tolerance in maize

The objective of this study was to test the hypothesis that large cortical cell size (CCS) would improve drought tolerance by reducing root metabolic costs. Maize (Zea mays) lines contrasting in root CCS measured as cross-sectional area were grown under well-watered and water-stressed conditions in greenhouse mesocosms and in the field in the United States and Malawi. CCS varied among genotypes, ranging from 101 to 533 µm(2). In mesocosms, large CCS reduced respiration per unit of root length by 59%. Under water stress in mesocosms, lines with large CCS had between 21% and 27% deeper rooting (depth above which 95% of total root length is located in the soil profile), 50% greater stomatal conductance, 59% greater leaf CO2 assimilation, and between 34% and 44% greater shoot biomass than lines with small CCS. Under water stress in the field, lines with large CCS had between 32% and 41% deeper rooting (depth above which 95% of total root length is located in the soil profile), 32% lighter stem water isotopic ratio of (18)O to (16)O signature, signifying deeper water capture, between 22% and 30% greater leaf relative water content, between 51% and 100% greater shoot biomass at flowering, and between 99% and 145% greater yield than lines with small cells. Our results are consistent with the hypothesis that large CCS improves drought tolerance by reducing the metabolic cost of soil exploration, enabling deeper soil exploration, greater water acquisition, and improved growth and yield under water stress. These results, coupled with the substantial genetic variation for CCS in diverse maize germplasm, suggest that CCS merits attention as a potential breeding target to improve the drought tolerance of maize and possibly other cereal crops.

QTL mapping and phenotypic variation for root architectural traits in maize (Zea mays L.)

QTL were identified for root architectural traits in maize. Root architectural traits, including the number, length, orientation, and branching of the principal root classes, influence plant function by determining the spatial and temporal domains of soil exploration. To characterize phenotypic patterns and their genetic control, three recombinant inbred populations of maize were grown for 28 days in solid media in a greenhouse and evaluated for 21 root architectural traits, including length, number, diameter, and branching of seminal, primary and nodal roots, dry weight of embryonic and nodal systems, and diameter of the nodal root system. Significant phenotypic variation was observed for all traits. Strong correlations were observed among traits in the same root class, particularly for the length of the main root axis and the length of lateral roots. In a principal component analysis, relationships among traits differed slightly for the three families, though vectors grouped together for traits within a given root class, indicating opportunities for more efficient phenotyping. Allometric analysis showed that trajectories of growth for specific traits differ in the three populations. In total, 15 quantitative trait loci (QTL) were identified. QTL are reported for length in multiple root classes, diameter and number of seminal roots, and dry weight of the embryonic and nodal root systems. Phenotypic variation explained by individual QTL ranged from 0.44% (number of seminal roots, NyH population) to 13.5% (shoot dry weight, OhW population). Identification of QTL for root architectural traits may be useful for developing genotypes that are better suited to specific soil environments.

Root anatomical phenes associated with water acquisition from drying soil: targets for crop improvement

Several root anatomical phenes affect water acquisition from drying soil, and may therefore have utility in breeding more drought-tolerant crops. Anatomical phenes that reduce the metabolic cost of the root cortex ('cortical burden') improve soil exploration and therefore water acquisition from drying soil. The best evidence for this is for root cortical aerenchyma; cortical cell file number and cortical senescence may also be useful in this context. Variation in the number and diameter of xylem vessels strongly affects axial water conductance. Reduced axial conductance may be useful in conserving soil water so that a crop may complete its life cycle under terminal drought. Variation in the suberization and lignification of the endodermis and exodermis affects radial water conductance, and may therefore be important in reducing water loss from mature roots into dry soil. Rhizosheaths may protect the water status of young root tissue. Root hairs and larger diameter root tips improve root penetration of hard, drying soil. Many of these phenes show substantial genotypic variation. The utility of these phenes for water acquisition has only rarely been validated, and may have strong interactions with the spatiotemporal dynamics of soil water availability, and with root architecture and other aspects of the root phenotype. This complexity calls for structural-functional plant modelling and 3D imaging methods. Root anatomical phenes represent a promising yet underexplored and untapped source of crop breeding targets.

Image-based high-throughput field phenotyping of crop roots

Current plant phenotyping technologies to characterize agriculturally relevant traits have been primarily developed for use in laboratory and/or greenhouse conditions. In the case of root architectural traits, this limits phenotyping efforts, largely, to young plants grown in specialized containers and growth media. Hence, novel approaches are required to characterize mature root systems of older plants grown under actual soil conditions in the field. Imaging methods able to address the challenges associated with characterizing mature root systems are rare due, in part, to the greater complexity of mature root systems, including the larger size, overlap, and diversity of root components. Our imaging solution combines a field-imaging protocol and algorithmic approach to analyze mature root systems grown in the field. Via two case studies, we demonstrate how image analysis can be utilized to estimate localized root traits that reliably capture heritable architectural diversity as well as environmentally induced architectural variation of both monocot and dicot plants. In the first study, we show that our algorithms and traits (including 13 novel traits inaccessible to manual estimation) can differentiate nine maize (Zea mays) genotypes 8 weeks after planting. The second study focuses on a diversity panel of 188 cowpea (Vigna unguiculata) genotypes to identify which traits are sufficient to differentiate genotypes even when comparing plants whose harvesting date differs up to 14 d. Overall, we find that automatically derived traits can increase both the speed and reproducibility of the trait estimation pipeline under field conditions.

Image-based high-throughput field phenotyping of crop roots

Current plant phenotyping technologies to characterize agriculturally relevant traits have been primarily developed for use in laboratory and/or greenhouse conditions. In the case of root architectural traits, this limits phenotyping efforts, largely, to young plants grown in specialized containers and growth media. Hence, novel approaches are required to characterize mature root systems of older plants grown under actual soil conditions in the field. Imaging methods able to address the challenges associated with characterizing mature root systems are rare due, in part, to the greater complexity of mature root systems, including the larger size, overlap, and diversity of root components. Our imaging solution combines a field-imaging protocol and algorithmic approach to analyze mature root systems grown in the field. Via two case studies, we demonstrate how image analysis can be utilized to estimate localized root traits that reliably capture heritable architectural diversity as well as environmentally induced architectural variation of both monocot and dicot plants. In the first study, we show that our algorithms and traits (including 13 novel traits inaccessible to manual estimation) can differentiate nine maize (Zea mays) genotypes 8 weeks after planting. The second study focuses on a diversity panel of 188 cowpea (Vigna unguiculata) genotypes to identify which traits are sufficient to differentiate genotypes even when comparing plants whose harvesting date differs up to 14 d. Overall, we find that automatically derived traits can increase both the speed and reproducibility of the trait estimation pipeline under field conditions.

Root cortical aerenchyma inhibits radial nutrient transport in maize (Zea mays)

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.

METHODS

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.

KEY RESULTS

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.

CONCLUSIONS

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.

Changes in chemical composition and digestibility of three maize stover components digested by white-rot fungi

Maize stover (total stem and leaves) is not considered a ruminant feed of high nutritive value. Therefore, an improvement in its digestibility may increase the viability of total forage maize production systems in marginal growth regions. The objective of this study was to describe the changes in chemical composition during the storage of contrasting components of maize stover (leaf, upper stem and lower stem) treated with either of two lignin degrading white-rot fungi (WRF; Pleurotus ostreatus, Trametes versicolor). Three components of maize stover (leaf, upper stem and lower stem), harvested at a conventional maturity for silage production, were digested with either of two WRF for one of four digestion durations (1-4 months). Samples taken prior to fungal inoculation were used to benchmark the changes that occurred. The degradation of acid detergent lignin was observed in all sample types digested with P. ostreatus; however, the loss of digestible substrate in all samples inoculated with P. ostreatus was high, and therefore, P. ostreatus-digested samples had a lower dry matter digestibility than samples prior to inoculation. Similarly, T. veriscolor-digested leaf underwent a non-selective degradation of the rumen-digestible components of fibre. The changes in chemical composition of leaf, upper stem and lower stem digested with either P. ostreatus or T. veriscolor were not beneficial to the feed value of the forage, and incurred high DM losses.

Integration of root phenes for soil resource acquisition

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 cortical burden influences drought tolerance in maize

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.

METHODS

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.

KEY RESULTS

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.

CONCLUSIONS

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.