Stomatal conductance tracks soil-to-leaf hydraulic conductance in faba bean and maize during soil drying.

Although regulation of stomatal conductance is widely assumed to be the most important plant response to soil drying, the picture is incomplete when hydraulic conductance from soil to the leaf, upstream of the stomata, is not considered. Here, we investigated to what extent soil drying reduces the conductance between soil and leaf, whether this reduction differs between species, how it affects stomatal regulation, and where in the hydraulic pathway it occurs. To this end, we noninvasively and continuously measured the total root water uptake rate, soil water potential, leaf water potential, and stomatal conductance of 4-week-old, pot-grown maize (Zea mays) and faba bean (Vicia faba) plants during 4 days of water restriction. In both species, the soil-plant conductance, excluding stomatal conductance, declined exponentially with soil drying and was reduced to 50% above a soil water potential of -0.1 MPa, which is far from the permanent wilting point. This loss of conductance has immediate consequences for leaf water potential and the associated stomatal regulation. Both stomatal conductance and soil-plant conductance declined at a higher rate in faba bean than in maize. Estimations of the water potential at the root surface and an incomplete recovery 22 h after rewatering indicate that the loss of conductance, at least partly, occurred inside the plants, for example, through root suberization or altered aquaporin gene expression. Our findings suggest that differences in the stomatal sensitivity among plant species are partly explained by the sensitivity of root hydraulic conductance to soil drying.

Deep-water uptake under drought improved due to locally increased root conductivity in maize, but not in faba bean.

Moderate soil drying can cause a strong decrease in the soil-root system conductance. The resulting impact on root water uptake depends on the spatial distribution of the altered conductance relatively to remaining soil water resources, which is largely unknown. Here, we analyzed the vertical distribution of conductance across root systems using a novel, noninvasive sensor technology on pot-grown faba bean and maize plants. Withholding water for 4 days strongly enhanced the vertical gradient in soil water potential. Therefore, roots in upper and deeper soil layers were affected differently: In drier, upper layers, root conductance decreased by 66%-72%, causing an amplification of the drop in leaf water potential. In wetter, deeper layers, root conductance increased in maize but not in faba bean. The consequently facilitated deep-water uptake in maize contributed up to 21% of total water uptake at the end of the measurement. Analysis of root length distributions with MRI indicated that the locally increased conductance was mainly caused by an increased intrinsic conductivity and not by additional root growth. Our findings show that plants can partly compensate for a reduced root conductance in upper, drier soil layers by locally increasing root conductivity in wetter layers, thereby improving deep-water uptake.

Rice increases phosphorus uptake in strongly sorbing soils by intra-root facilitation.

Upland rice (Oryza sativa) is adapted to strongly phosphorus (P) sorbing soils. The mechanisms underlying P acquisition, however, are not well understood, and models typically underestimate uptake. This complicates root ideotype development and trait-based selection for further improvement. We present a novel model, which correctly simulates the P uptake by a P-efficient rice genotype measured over 48 days of growth. The model represents root morphology at the local rhizosphere scale, including root hairs and fine S-type laterals. It simulates fast- and slowly reacting soil P and the P-solubilizing effect of root-induced pH changes in the soil. Simulations predict that the zone of pH changes and P solubilization around a root spreads further into the soil than the zone of P depletion. A root needs to place laterals outside its depletion- but inside its solubilization zone to maximize P uptake. S-type laterals, which are short but hairy, appear to be the key root structures to achieve that. Thus, thicker roots facilitate the P uptake by fine lateral roots. Uptake can be enhanced through longer root hairs and greater root length density but was less sensitive to total root length and root class proportions.

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.

Spatially Resolved Root Water Uptake Determination Using a Precise Soil Water Sensor.

To answer long-standing questions about how plants use and regulate water, an affordable, noninvasive way to determine local root water uptake (RWU) is required. Here, we present a sensor, the soil water profiler (SWaP), which can determine local soil water content (θ) with a precision of 6.10-5 cm3 ⋅ cm-3, an accuracy of 0.002 cm3 ⋅ cm-3, a temporal resolution of 24 min, and a one-dimensional spatial resolution of 1 cm. The sensor comprises two copper sheets, integrated into a sleeve and connected to a coil, which form a resonant circuit. A vector network analyzer, inductively coupled to the resonant circuit, measures the resonance frequency, against which θ was calibrated. The sensors were integrated into a positioning system, which measures θ along the depth of cylindrical tubes. When combined with modulating light (4-h period) and resultant modulating plant transpiration, the SWaP enables quantification of the component of RWU distribution that varies proportionally with total plant water uptake, and distinguishes it from soil water redistribution via soil pores and roots. Additionally, as a young, growing maize (Zea mays) plant progressively tapped its soil environment dry, we observed clear changes in plant-driven RWU and soil water redistribution profiles. Our SWaP setup can measure the RWU and redistribution of sandy-soil water content with unprecedented precision. The SWaP is therefore a promising device offering new insights into soil-plant hydrology, with applications for functional root phenotyping in nonsaline, temperature-controlled conditions, at low cost.

Dividing the pie: A quantitative review on plant density responses.

Plant population density is an important variable in agronomy and forestry and offers an experimental way to better understand plant-plant competition. We made a meta-analysis of responses of even-aged mono-specific stands to population density by quantifying for 3 stand and 33 individual plant variables in 334 experiments how much both plant biomass and phenotypic traits change with a doubling in density. Increasing density increases standing crop per area, but decreases the mean size of its individuals, mostly through reduced tillering and branching. Among the phenotypic traits, stem diameter is negatively affected, but plant height remains remarkably similar, partly due to an increased stem length-to-mass ratio and partly by increased allocation to stems. The reduction in biomass is caused by a lower photosynthetic rate, mainly due to shading of part of the foliage. Total seed mass per plant is also strongly reduced, marginally by lower mass per seed, but mainly because of lower seed numbers. Plants generally have fewer shoot-born roots, but their overall rooting depth seems hardly affected. The phenotypic plasticity responses to high densities correlate strongly with those to low light, and less with those to low nutrients, suggesting that at high density, shading affects plants more than nutrient depletion.

Soil compaction and the architectural plasticity of root systems.

Soil compaction is a serious global problem, and is a major cause of inadequate rooting and poor yield in crops around the world. Root system architecture (RSA) describes the spatial arrangement of root components within the soil and determines the plant's exploration of the soil. Soil strength restricts root growth and may slow down root system development. RSA plasticity may have an adaptive value, providing environmental tolerance to soil compaction. However, it is challenging to distinguish developmental retardation (apparent plasticity) or responses to severe stress from those root architectural changes that may provide an actual environmental tolerance (adaptive plasticity). In this review, we outline the consequences of soil compaction on the rooting environment and extensively review the various root responses reported in the literature. Finally, we discuss which responses enhance root exploration capabilities in tolerant genotypes, and to what extent these responses might be useful for breeding. We conclude that RSA plasticity in response to soil compaction is complex and can be targeted in breeding to increase the performance of crops under specific agronomical conditions.

Root Cortical Senescence Improves Growth under Suboptimal Availability of N, P, and K.

Root cortical senescence (RCS) in Triticeae reduces nutrient uptake, nutrient content, respiration, and radial hydraulic conductance of root tissue. We used the functional-structural model SimRoot to evaluate the functional implications of RCS in barley (Hordeum vulgare) under suboptimal nitrate, phosphorus, and potassium availability. The utility of RCS was evaluated using sensitivity analyses in contrasting nutrient regimes. At flowering (80 d), RCS increased simulated plant growth by up to 52%, 73%, and 41% in nitrate-, phosphorus-, and potassium-limiting conditions, respectively. Plants with RCS had reduced nutrient requirement of root tissue for optimal plant growth, reduced total cumulative cortical respiration, and increased total carbon reserves. Nutrient reallocation during RCS had a greater effect on simulated plant growth than reduced respiration or nutrient uptake. Under low nutrient availability, RCS had greater benefit in plants with fewer tillers. RCS had greater benefit in phenotypes with fewer lateral roots at low nitrate availability, but the opposite was true in low phosphorus or potassium availability. Additionally, RCS was quantified in field-grown barley in different nitrogen regimes. Field and virtual soil coring simulation results demonstrated that living cortical volume per root length (an indicator of RCS) decreased with depth in younger plants, while roots of older plants had very little living cortical volume per root length. RCS may be an adaptive trait for nutrient acquisition by reallocating nutrients from senescing tissue and secondarily by reducing root respiration. These simulated results suggest that RCS merits investigation as a breeding target for enhanced soil resource acquisition and edaphic stress tolerance.

Co-optimization of axial root phenotypes for nitrogen and phosphorus acquisition in common bean.

Background and Aims: Root architecture is a primary determinant of soil resource acquisition. We hypothesized that root architectural phenes will display both positive and negative interactions with each other for soil resource capture because of competition for internal resources and functional trade-offs in soil exploration. Methods: We employed the functional-structural plant model SimRoot to explore how interactions among architectural phenes in common bean determine the acquisition of phosphate and nitrate, two key soil resources contrasting in mobility. We evaluated the utility of basal root whorl number (BRWN) when basal root growth angle, hypocotyl-borne roots and lateral root branching density (LRBD) were varied, under varying availability of phosphate and nitrate. Key Results: Three basal root whorls were optimal in most phenotypes. This optimum shifted towards greater values when LRBD decreased and to smaller numbers when LRBD increased. The maximum biomass accumulated for a given BRWN phenotype in a given limiting nutrient scenario depended upon root growth angle. Under phosphorus stress shallow phenotypes grew best, whereas under nitrate stress fanned phenotypes grew best. The effect of increased hypocotyl-borne roots depended upon BRWN as well as the limiting nutrient. Greater production of axial roots due to BRWN or hypocotyl-borne roots reduced rooting depth, leading to reduced biomass under nitrate-limiting conditions. Increased BRWN as well as greater LRBD increased root carbon consumption, resulting in reduced shoot biomass. Conclusions: We conclude that the utility of a root architectural phenotype is determined by whether the constituent phenes are synergistic or antagonistic. Competition for internal resources and trade-offs for external resources result in multiple phenotypes being optimal under a given nutrient regime. We also find that no single phenotype is optimal across contrasting environments. These results have implications for understanding plant evolution and also for the breeding of more stress-tolerant crop phenotypes.

Ethylene modulates root cortical senescence in barley.

Background and Aims: Root cortical senescence (RCS) is a poorly understood phenomenon with implications for adaptation to edaphic stress. It was hypothesized that RCS in barley (Hordeum vulgare L.) is (1) accelerated by exogenous ethylene exposure; (2) accompanied by differential expression of ethylene synthesis and signalling genes; and (3) associated with differential expression of programmed cell death (PCD) genes. Methods: Gene expression of root segments from four barley genotypes with and without RCS was evaluated using quantitative real-time PCR (qRT-PCR). The progression of RCS was manipulated with root zone ethylene and ethylene inhibitor applications. Key Results: The results demonstrate that ethylene modulates RCS. Four genes related to ethylene synthesis and signalling were upregulated during RCS in optimal, low nitrogen and low phosphorus nutrient regimes. RCS was accelerated by root zone ethylene treatment, and this effect was reversed by an ethylene action inhibitor. Roots treated with exogenous ethylene had 35 and 46 % more cortical senescence compared with the control aeration treatment in seminal and nodal roots, respectively. RCS was correlated with expression of two genes related to programmed cell death (PCD). Conclusions: The development of RCS is similar to root cortical aerenchyma formation with respect to ethylene modulation of the PCD process.

OpenSimRoot: widening the scope and application of root architectural models.

OpenSimRoot is an open-source, functional-structural plant model and mathematical description of root growth and function. We describe OpenSimRoot and its functionality to broaden the benefits of root modeling to the plant science community. OpenSimRoot is an extended version of SimRoot, established to simulate root system architecture, nutrient acquisition and plant growth. OpenSimRoot has a plugin, modular infrastructure, coupling single plant and crop stands to soil nutrient and water transport models. It estimates the value of root traits for water and nutrient acquisition in environments and plant species. The flexible OpenSimRoot design allows upscaling from root anatomy to plant community to estimate the following: resource costs of developmental and anatomical traits; trait synergisms; and (interspecies) root competition. OpenSimRoot can model three-dimensional images from magnetic resonance imaging (MRI) and X-ray computed tomography (CT) of roots in soil. New modules include: soil water-dependent water uptake and xylem flow; tiller formation; evapotranspiration; simultaneous simulation of mobile solutes; mesh refinement; and root growth plasticity. OpenSimRoot integrates plant phenotypic data with environmental metadata to support experimental designs and to gain a mechanistic understanding at system scales.

Quantitative 3D Analysis of Plant Roots Growing in Soil Using Magnetic Resonance Imaging.

Precise measurements of root system architecture traits are an important requirement for plant phenotyping. Most of the current methods for analyzing root growth require either artificial growing conditions (e.g. hydroponics), are severely restricted in the fraction of roots detectable (e.g. rhizotrons), or are destructive (e.g. soil coring). On the other hand, modalities such as magnetic resonance imaging (MRI) are noninvasive and allow high-quality three-dimensional imaging of roots in soil. Here, we present a plant root imaging and analysis pipeline using MRI together with an advanced image visualization and analysis software toolbox named NMRooting. Pots up to 117 mm in diameter and 800 mm in height can be measured with the 4.7 T MRI instrument used here. For 1.5 l pots (81 mm diameter, 300 mm high), a fully automated system was developed enabling measurement of up to 18 pots per day. The most important root traits that can be nondestructively monitored over time are root mass, length, diameter, tip number, and growth angles (in two-dimensional polar coordinates) and spatial distribution. Various validation measurements for these traits were performed, showing that roots down to a diameter range between 200 µm and 300 µm can be quantitatively measured. Root fresh weight correlates linearly with root mass determined by MRI. We demonstrate the capabilities of MRI and the dedicated imaging pipeline in experimental series performed on soil-grown maize (Zea mays) and barley (Hordeum vulgare) plants.

Root cortical senescence decreases root respiration, nutrient content and radial water and nutrient transport in barley.

The functional implications of root cortical senescence (RCS) are poorly understood. We tested the hypotheses that RCS in barley (1) reduces the respiration and nutrient content of root tissue; (2) decreases radial water and nutrient transport; and (3) is accompanied by increased suberization to protect the stele. Genetic variation for RCS exists between modern germplasm and landraces. Nitrogen and phosphorus deficiency increased the rate of RCS. Maximal RCS, defined as the disappearance of the entire root cortex, reduced root nitrogen content by 66%, phosphorus content by 63% and respiration by 87% compared with root segments with no RCS. Roots with maximal RCS had 90, 92 and 84% less radial water, nitrate and phosphorus transport, respectively, compared with segments with no RCS. The onset of RCS coincided with 30% greater aliphatic suberin in the endodermis. These results support the hypothesis that RCS reduces root carbon and nutrient costs and may therefore have adaptive significance for soil resource acquisition. By reducing root respiration and nutrient content, RCS could permit greater root growth, soil resource acquisition and resource allocation to other plant processes. RCS merits investigation as a trait for improving the performance of barley, wheat, triticale and rye under edaphic stress.

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.

Benefits and limits of biological nitrification inhibitors for plant nitrogen uptake and the environment.

Plant growth and high yields are secured by intensive use of nitrogen (N) fertilizer, which, however, pollutes the environment, especially when N is in the form of nitrate. Ammonium is oxidized to nitrate by nitrifiers, but roots can release biological nitrification inhibitors (BNIs). Under what conditions does root-exudation of BNIs facilitate nitrogen N uptake and reduce pollution by N loss to the environment? We modeled the spatial-temporal dynamics of nitrifiers, ammonium, nitrate, and BNIs around a root and simulated root N uptake and net rhizosphere N loss over the plant's life cycle. We determined the sensitivity of N uptake and loss to variations in the parameter values, testing a broad range of soil-plant-microbial conditions, including concentrations, diffusion, sorption, nitrification, population growth, and uptake kinetics. An increase in BNI exudation reduces net N loss and, under most conditions, increases plant N uptake. BNIs decrease uptake in the case of (1) low ammonium concentrations, (2) high ammonium adsorption to the soil, (3) rapid nitrate- or slow ammonium uptake by the plant, and (4) a slowly growing or (5) fast-declining nitrifier population. Bactericidal inhibitors facilitate uptake more than bacteriostatic ones. Some nitrification, however, is necessary to maximize uptake by both ammonium and nitrate transporter systems. An increase in BNI exudation should be co-selected with improved ammonium uptake. BNIs can reduce N uptake, which may explain why not all species exude BNIs but have a generally positive effect on the environment by increasing rhizosphere N retention.

Pitfalls and potential of high-throughput plant phenotyping platforms.

Automated high-throughput plant phenotyping (HTPP) enables non-invasive, fast and standardized evaluations of a large number of plants for size, development, and certain physiological variables. Many research groups recognize the potential of HTPP and have made significant investments in HTPP infrastructure, or are considering doing so. To make optimal use of limited resources, it is important to plan and use these facilities prudently and to interpret the results carefully. Here we present a number of points that users should consider before purchasing, building or utilizing such equipment. They relate to (1) the financial and time investment for acquisition, operation, and maintenance, (2) the constraints associated with such machines in terms of flexibility and growth conditions, (3) the pros and cons of frequent non-destructive measurements, (4) the level of information provided by proxy traits, and (5) the utilization of calibration curves. Using data from an Arabidopsis experiment, we demonstrate how diurnal changes in leaf angle can impact plant size estimates from top-view cameras, causing deviations of more than 20% over the day. Growth analysis data from another rosette species showed that there was a curvilinear relationship between total and projected leaf area. Neglecting this curvilinearity resulted in linear calibration curves that, although having a high r2 (> 0.92), also exhibited large relative errors. Another important consideration we discussed is the frequency at which calibration curves need to be generated and whether different treatments, seasons, or genotypes require distinct calibration curves. In conclusion, HTPP systems have become a valuable addition to the toolbox of plant biologists, provided that these systems are tailored to the research questions of interest, and users are aware of both the possible pitfalls and potential involved.

Complementarity in root architecture for nutrient uptake in ancient maize/bean and maize/bean/squash polycultures.

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. METHODS: 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. KEY RESULTS: 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. CONCLUSIONS: 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.

Assessing the Storage Root Development of Cassava with a New Analysis Tool.

Storage roots of cassava plants crops are one of the main providers of starch in many South American, African, and Asian countries. Finding varieties with high yields is crucial for growing and breeding. This requires a better understanding of the dynamics of storage root formation, which is usually done by repeated manual evaluation of root types, diameters, and their distribution in excavated roots. We introduce a newly developed method that is capable to analyze the distribution of root diameters automatically, even if root systems display strong variations in root widths and clustering in high numbers. An application study was conducted with cassava roots imaged in a video acquisition box. The root diameter distribution was quantified automatically using an iterative ridge detection approach, which can cope with a wide span of root diameters and clustering. The approach was validated with virtual root models of known geometries and then tested with a time-series of excavated root systems. Based on the retrieved diameter classes, we show plausibly that the dynamics of root type formation can be monitored qualitatively and quantitatively. We conclude that this new method reliably determines important phenotypic traits from storage root crop images. The method is fast and robustly analyses complex root systems and thereby applicable in high-throughput phenotyping and future breeding.