Dynamic root growth and architecture responses to limiting nutrient availability: linking physiological models and experimentation

Soil application potential of post-sorbents produced by co-sorption of humic substances and nutrients from sludge anaerobic digestion reject water

This study introduces a novel soil conditioning approach using humic substances (HSs) and nutrients co-recovered from reject water from sewage sludge anaerobic digestion. For the first time, HSs and nutrients were simultaneously recovered through sorption on low-cost, environmentally inert materials: natural rock opoka (OP) and waste autoclaved aerated concrete (WAAC). This innovative application of OP and WAAC as carriers and delivery agents for soil-relevant substances offers potential for resource recovery and soil conditioning. Results indicate that the post-sorption opoka (PS-OP) and post-sorption waste autoclaved aerated concrete (PS-WAAC) effectively release retained HSs at 350-480 μg g⁻1 d⁻1, respectively. These materials also show potential as NPK fertilizers, releasing 280-430 μg g⁻1 d⁻1 N-NH₄⁺, 80-150 μg g⁻1 d⁻1 P-PO₄³⁻, and 270-350 μg g⁻1 d⁻1 K⁺. Additionally, PS-OP demonstrated promising fungicide properties, reducing P. diachenii growth by 31% at a concentration of 1 g L⁻1. A two-way ANOVA indicated that the effects of PS-OP and PS-WAAC on soil physicochemical and biological parameters varied with plant species. Both post-sorbents improved the quality of soil collected from sand mining area, increasing cation exchange capacity by 7%-85% and organic matter content by 10%-58%. They also enhanced the functional potential of soil microbial communities, increasing their metabolic activities by 23%-36% in soils sown with clover and by 33%-39% in soils sown with rapeseed. An opposite effect was observed in soils sown with sorghum, suggesting these amendments may not universally act as plant biostimulants. The effectiveness of these post-sorbents in enhancing plant growth varied depending on plant species and the mineral base of the post-sorbent. PS-OP increased the total length of clover and sorghum by 41% and 36%, and their fresh biomass by 82% and 80%, respectively. In turn, PS-WAAC increased the total length of clover and sorghum by 76% and 17%, and their fresh biomass by 29% and 15%, respectively. It was notably more effective than PS-OP for rapeseed. This study proposes a strategy to decrease reliance on non-renewable resources and costly sorbents while minimizing environmental impact. It shows that PS-OP and PS-WAAC can enhance soil quality, microbial activity, and plant growth. Given their origins, these amendments are recommended for soil remediation, particularly in degraded areas. Future research should focus on optimizing their application across various plant species to maximize effectiveness.

Growth, Biochemical Traits, Antioxidant Enzymes, and Essential Oils of Four Aromatic and Medicinal Plants Cultivated in Phosphate-Mine Residues

Revegetation emerges as a promising approach to alleviate the adverse impacts of mining residues. However, it is essential to evaluate the characteristics of these materials and select suitable plant species to ensure successful ecosystem restoration. This study aimed to investigate the effects of phosphate-mine residues (MR) on the growth, biochemical properties, and essential oil concentration of Rosmarinus officinalis L., Salvia Officinalis L., Lavandula dentata L., and Origanum majorana L. The results showed that R. officinalis L. appeared to be particularly well-suited to thriving in MR soil. Our finding also revealed that L. dentata L., O. majorana L., and S. officinalis L. grown in MR exhibited significantly lower growth performance (lower shoot length, smaller leaves, and altered root structure) and higher antioxidant activities, with an alterations of photosynthetic pigment composition. They showed a decrease in total chlorophylls when grown on MR (0.295, 0.453, and 0.562 mg g-1 FW, respectively) compared to the control (0.465, 0.807, and 0.808 mg g-1 FW, respectively); however, they produced higher essential oil content (1.8%, 3.06%, and 2.88%, respectively). The outcomes of this study could offer valuable insights for the advancement of revegetation technologies and the utilization of plant products derived from phosphate-mine residues.

Impact of fertilization depth on sunflower yield and nitrogen utilization: a perspective on soil nutrient and root system compatibility

Introduction

The depth of fertilizer application significantly influences soil nitrate concentration (SNC), sunflower root length density (RLD), sunflower nitrogen uptake (SNU), and yield. However, current studies cannot precisely capture subtle nutrient variations between soil layers and their complex relationships with root growth. They also struggle to assess the impact of different fertilizer application depths on sunflower root development and distribution as well as their response to the spatial and temporal distribution of nutrients.

Methods

The Agricultural Production Systems sIMulator (APSIM) model was employed to explore the spatial and temporal patterns of nitrogen distribution in the soil at three controlled-release fertilizer (CRF) placement depths: 5, 15, and 25 cm. This study investigated the characteristics of the root system regarding nitrogen absorption and utilization and analyzed their correlation with sunflower yield formation. Furthermore, this study introduced the modified Jaccard index (considering the compatibility between soil nitrate and root length density) to analyze soil-root interactions, providing a deeper insight into how changes in CRF placement depth affect crop growth and nitrogen uptake efficiency.

Results

The results indicated that a fertilization depth of 15 cm improved the modified Jaccard index by 6.60% and 7.34% compared to 5 cm and 25 cm depths, respectively, maximizing sunflower yield (an increase of 9.44%) and nitrogen absorption rate (an increase of 5.40%). This depth promoted a greater Root Length Density (RLD), with an increases of 11.95% and 16.42% compared those at 5 cm and 25 cm, respectively, enhancing deeper root growth and improving nitrogen uptake. In contrast, shallow fertilization led to higher nitrate concentrations in the topsoil, whereas deeper fertilization increased the nitrate concentrations in the deeper soil layers.

Discussion

These results provide valuable insights for precision agriculture and sustainable soil management, highlighting the importance of optimizing root nitrogen absorption through tailored fertilization strategies to enhance crop production efficiency and minimize environmental impact.

Ensifer adhaerens strain OV14 seed application enhances Triticum aestivum L. and Brassica napus L. development

Given the challenges imposed by climate change and societal challenges, the European Union established ambitious goals as part of its Farm to Fork (F2F) strategy. Focussed on accelerating the transition to systems of sustainable food production, processing and consumption, a key element of F2F is to reduce the use of fertilisers by at least 20% and plant protection products by up to 50% by 2030. In recent years, a substantial body of research has highlighted the potential impact of microbial-based applications to support crop production practices through both biotic/abiotic stresses via maintaining or even improving yields and reducing reliance on intensive chemical inputs. Here, we have characterised the ability of a new soil-borne free-living bacterium strain Ensifer adhaerens OV14 (EaOV14) to significantly enhance crop vigour index by up to 50% for monocot (wheat, Triticum aestivum L., p < 0.0001) and by up to 40% for dicot (oilseed rape, Brassica napus L., p < 0.0001) species under in-vitro conditions (n = 360 seedlings/treatment). The beneficial effect was further studied under controlled glasshouse growing conditions (n = 60 plants/treatment) where EaOV14 induced significantly increased seed yield of spring oilseed rape compared to the controls (p < 0.0001). Moreover, using bespoke rhizoboxes, enhanced root architecture (density, roots orientation, roots thickness etc.) was observed for spring oilseed rape and winter wheat, with the median number of roots 55% and 33% higher for oilseed rape and wheat respectively, following EaOV14 seed treatment compared to the control. In addition, EaOV14 treatment increased root tip formation and root volume, suggesting the formation of a more robust root system architecture post-seed treatment. However, like other microbial formulations, the trade-offs associated with field translation, such as loss or limited functionality due to inoculum formulation or environmental distress, need further investigation. Moreover, the delivery method requires further optimisation to identify the optimal inoculum formulation that will maximise the expected beneficial impact on yield under field growing conditions.

'Root of all success': Plasticity in root architecture of invasive wild radish for adaptive benefit

Successful plant establishment in a particular environment depends on the root architecture of the seedlings and the extent of edaphic resource utilization. However, diverse habitats often pose a predicament on the suitability of the fundamental root structure of a species that evolved over a long period. We hypothesized that the plasticity in the genetically controlled root architecture in variable habitats provides an adaptive advantage to worldwide-distributed wild radish (Raphanus raphanistrum, Rr) over its close relative (R. pugioniformis, Rp) that remained endemic to the East Mediterranean region. To test the hypothesis, we performed a reciprocal comparative analysis between the two species, growing in a common garden experiment on their native soils (Hamra/Sandy for Rr, Terra Rossa for Rp) and complementary controlled experiments mimicking the major soil compositions. Additionally, we analyzed the root growth kinetics via semi-automated digital profiling and compared the architecture between Rr and Rp. In both experiments, the primary roots of Rr were significantly longer, developed fewer lateral roots, and showed slower growth kinetics than Rp. Multivariate analyses of seven significant root architecture variables revealed that Rr could successfully adapt to different surrogate growth conditions by only modulating their main root length and number of lateral roots. In contrast, Rp needs to modify several other root parameters, which are very resource-intensive, to grow on non-native soil. Altogether the findings suggest an evo-devo adaptive advantage for Rr as it can potentially establish in various habitats with the minimal tweak of key root parameters, hence allocating resources for other developmental requirements.

Scions impact biomass allocation and root enzymatic activity of rootstocks in grafted melon and watermelon plants

Vegetable grafting is increasingly recognized as an effective and sustainable plant production alternative. Grafted plants usually show increased uptake of water and minerals compared with self-rooted plants, mostly thought a consequence of the vigorous rootstocks selected. However, while studies frequently addressed the effects of rootstocks on the performance of scions, knowledge on the influences of scions on biomass allocation, morphology, and metabolic activity of roots is rare. In particular, the plasticity of root traits affecting resource acquisition and its efficiency remains poorly understood. Two different rootstock species, Cucurbita maxima × Cucurbita moschata and Lagenaria siceraria, were grafted in combination with melon (Cucumis melo) and watermelon (Citrullus lanatus). Self-grafted rootstocks were used as control. Plant biomass and root traits were determined after destructive harvesting 30 and/or 60 days after grafting. Traits included biomass allocation, leaf and root morphology, potential activities of four extracellular enzymes on root tips and basal root segments, and root respiration. Successfully grafted scions increase the ratio of root to whole plant dry matter (RMF), and increased ratios of root length to whole plant dry matter (RLR) and to plant leaf area (RL : LA). In contrast, morphological root traits such as diameter, tissue density, and specific root length remain surprisingly stable, and thus scion-induced changes of those traits may only play a minor role for the beneficial effects of grafting in Cucurbitaceae. Incompatibility in melon/L. siceraria grafts, however, was likely responsible for the reduced root growth in combination with clear changes in root morphological traits. Reduced root respiration rates seem to be the effects of a non-compatible rootstock-scion combination rather than an active, C-efficiency increasing acclimation. In contrast, heterografts with melon and watermelon frequently resulted in root-stock-specific, often enhanced potential enzymatic activities of acid phosphatase, β-glucosidase, leucine-amino-peptidase, and N-acetyl-glucosaminidase both at root tips and basal parts of lateral roots-presenting a potential and complementary mechanism of grafted plants to enhance nutrient foraging. The studied melon and watermelon scions may thus increase the nutrient foraging capacity of grafted plants by fostering the relative allocation of C to the root system, and enhancing the extracellular enzymatic activities governed by roots or their rhizobiome.

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

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

Simulating Root Growth as a Function of Soil Strength and Yield With a Field-Scale Crop Model Coupled With a 3D Architectural Root Model

Accurate prediction of root growth and related resource uptake is crucial to accurately simulate crop growth especially under unfavorable environmental conditions. We coupled a 1D field-scale crop-soil model running in the SIMPLACE modeling framework with the 3D architectural root model CRootbox on a daily time step and implemented a stress function to simulate root elongation as a function of soil bulk density and matric potential. The model was tested with field data collected during two growing seasons of spring barley and winter wheat on Haplic Luvisol. In that experiment, mechanical strip-wise subsoil loosening (30-60 cm) (DL treatment) was tested, and effects on root and shoot growth at the melioration strip as well as in a control treatment were evaluated. At most soil depths, strip-wise deep loosening significantly enhanced observed root length densities (RLDs) of both crops as compared to the control. However, the enhanced root growth had a beneficial effect on crop productivity only in the very dry season in 2018 for spring barley where the observed grain yield at the strip was 18% higher as compared to the control. To understand the underlying processes that led to these yield effects, we simulated spring barley and winter wheat root and shoot growth using the described field data and the model. For comparison, we simulated the scenarios with the simpler 1D conceptual root model. The coupled model showed the ability to simulate the main effects of strip-wise subsoil loosening on root and shoot growth. It was able to simulate the adaptive plasticity of roots to local soil conditions (more and thinner roots in case of dry and loose soil). Additional scenario runs with varying weather conditions were simulated to evaluate the impact of deep loosening on yield under different conditions. The scenarios revealed that higher spring barley yields in DL than in the control occurred in about 50% of the growing seasons. This effect was more pronounced for spring barley than for winter wheat. Different virtual root phenotypes were tested to assess the potential of the coupled model to simulate the effect of varying root traits under different conditions.

Nutrient deficiency effects on root architecture and root-to-shoot ratio in arable crops

Plant root traits play a crucial role in resource acquisition and crop performance when soil nutrient availability is low. However, the respective trait responses are complex, particularly at the field scale, and poorly understood due to difficulties in root phenotyping monitoring, inaccurate sampling, and environmental conditions. Here, we conducted a systematic review and meta-analysis of 50 field studies to identify the effects of nitrogen (N), phosphorous (P), or potassium (K) deficiencies on the root systems of common crops. Root length and biomass were generally reduced, while root length per shoot biomass was enhanced under N and P deficiency. Root length decreased by 9% under N deficiency and by 14% under P deficiency, while root biomass was reduced by 7% in N-deficient and by 25% in P-deficient soils. Root length per shoot biomass increased by 33% in N deficient and 51% in P deficient soils. The root-to-shoot ratio was often enhanced (44%) under N-poor conditions, but no consistent response of the root-to-shoot ratio to P-deficiency was found. Only a few K-deficiency studies suited our approach and, in those cases, no differences in morphological traits were reported. We encountered the following drawbacks when performing this analysis: limited number of root traits investigated at field scale, differences in the timing and severity of nutrient deficiencies, missing data (e.g., soil nutrient status and time of stress), and the impact of other conditions in the field. Nevertheless, our analysis indicates that, in general, nutrient deficiencies increased the root-length-to-shoot-biomass ratios of crops, with impacts decreasing in the order deficient P > deficient N > deficient K. Our review resolved inconsistencies that were often found in the individual field experiments, and led to a better understanding of the physiological mechanisms underlying root plasticity in fields with low nutrient availability.

Challenges to design-oriented breeding of root system architecture adapted to climate change

Roots are essential organs for capturing water and nutrients from the soil. In particular, root system architecture (RSA) determines the extent of the region of the soil where water and nutrients can be gathered. As global climate change accelerates, it will be important to improve belowground plant parts, as well as aboveground ones, because roots are front-line organs in the response to abiotic stresses such as drought, flooding, and salinity stress. However, using conventional breeding based on phenotypic selection, it is difficult to select breeding lines possessing promising RSAs to adapted to abiotic stress because roots remain hidden underground. Therefore, new breeding strategies that do not require phenotypic selection are necessary. Recent advances in molecular biology and biotechnology can be applied to the design-oriented breeding of RSA without phenotypic selection. Here I summarize recent progress in RSA ideotypes as "design" and RSA-related gene resources as "materials" that will be needed in leveraging these technologies for the RSA breeding. I also highlight the future challenges to design-oriented breeding of RSA and explore solutions to these challenges.

An Analysis of Soil Coring Strategies to Estimate Root Depth in Maize (Zea mays) and Common Bean (Phaseolus vulgaris)

A soil coring protocol was developed to cooptimize the estimation of root length distribution (RLD) by depth and detection of functionally important variation in root system architecture (RSA) of maize and bean. The functional-structural model OpenSimRoot was used to perform in silico soil coring at six locations on three different maize and bean RSA phenotypes. Results were compared to two seasons of field soil coring and one trench. Two one-sided T-test (TOST) analysis of in silico data suggests a between-row location 5 cm from plant base (location 3), best estimates whole-plot RLD/D of deep, intermediate, and shallow RSA phenotypes, for both maize and bean. Quadratic discriminant analysis indicates location 3 has ~70% categorization accuracy for bean, while an in-row location next to the plant base (location 6) has ~85% categorization accuracy in maize. Analysis of field data suggests the more representative sampling locations vary by year and species. In silico and field studies suggest location 3 is most robust, although variation is significant among seasons, among replications within a field season, and among field soil coring, trench, and simulations. We propose that the characterization of the RLD profile as a dynamic rhizo canopy effectively describes how the RLD profile arises from interactions among an individual plant, its neighbors, and the pedosphere.

Integrative Transcriptome and Proteome Analysis Identifies Major Molecular Regulation Pathways Involved in Ramie (Boehmeria nivea (L.) Gaudich) under Nitrogen and Water Co-Limitation

Water and N are the most important factors affecting ramie (Boehmeria nivea (L.) Gaudich) growth. In this study, de novo transcriptome assembly and Tandem Mass Tags (TMT) based quantitative proteome analysis of ramie under nitrogen and water co-limitation conditions were performed, and exposed to treatments, including drought and N-deficit (WdNd), proper water but N-deficit (WNd), proper N but drought (WdN), and proper N and water (CK), respectively. A total of 64,848 unigenes (41.92% of total unigenes) were annotated in at least one database, including NCBI non-redundant protein sequences (Nr), Swiss-Prot, Protein family (Pfam), Gene Ontology (GO) and KEGG Orthology (KO), and 4268 protein groups were identified. Most significant changes in transcript levels happened under water-limited conditions, but most significant changes in protein level happened under water-limited conditions only with proper N. Poor correlation between differentially expressed genes (DEGs) and differentially expressed proteins (DEPs) was observed in ramie responding to the treatments. DEG/DEP regulation patterns related to major metabolic processes responding to water and N deficiency were analyzed, including photosynthesis, ethylene responding, glycolysis, and nitrogen metabolism. Moreover, 41 DEGs and 61 DEPs involved in regulating adaptation of ramie under water and N stresses were provided in the study, including DEGs/DEPs related to UDP—glucuronosyhransferase (UGT), ATP synthase, and carbonate dehydratase. The strong dependency of N-response of ramie on water conditions at the gene and protein levels was highlighted. Advices for simultaneously improving water and N efficiency in ramie were also provided, especially in breeding N efficient varieties with drought resistance. This study provided extensive new information on the transcriptome, proteome, their correlation, and diversification in ramie responding to water and N co-limitation.

Influence of Cotton Root System Size on Tolerance to Rotylenchulus reniformis

The factors that influence the ability of cotton to minimize yield loss despite parasitism by Rotylenchulus reniformis (i.e., tolerance) were evaluated for 12 cotton genotypes. Reproduction of R. reniformis and total length of the root system were measured under greenhouse conditions, and the relationship of those variables to yield loss caused by R. reniformis in infested fields was evaluated. Values for nematodes per gram of root and root length were standardized by setting the genotype with greatest value as 100% and then calculating a percentage for each genotype. There was significant variability among genotypes in yield loss, resistance, and root length. Average yield loss for the genotypes ranged from 10.4% for IAC 26RMD to 43.2% for IMACD 5675B2RF. The least nematode reproduction was on IAC 26RMD, which had 49.6% of the reproduction on the susceptible check, Deltapine 16. The genotype with the shortest total root length was 34% less than the genotype with the greatest length. There was a significant linear relationship between percentage yield loss caused by R. reniformis and root length and nematodes per gram of root, both expressed as a percentage of the maximum, represented by the following equation: Yield loss (%) = 16.1258 - 0.1918*(% maximum root length) + 0.3728*(% maximum eggs + vermiform/g of roots). We conclude that tolerance to R. reniformis in cotton is influenced by the size of the root system and the parasitic load on the plant (nematodes per gram of root). Management approaches that increase root growth may lower the parasitic load, thereby reducing losses in cotton to R. reniformis.

Growth and Distribution of Maize Roots in Response to Nitrogen Accumulation in Soil Profiles after Long-Term Fertilization Management on a Calcareous Soil

The replacement of inorganic fertilizer nitrogen by manure is highlighted to have great potential to maintain crop yield while delivering multiple functions, including the improvement of soil quality. However, information on the dynamics of root distributions in response to chemical fertilizers and manure along the soil profile is still lacking. The aim of this study was to investigate the temporal-spatial root distributions of summer maize (Zea mays L.) from 2013 to 2015 under four treatments (unfertilized control (CK), inorganic fertilizer (NPK), manure + 70% NPK (NPKM), and NPKM + straw (NPKMS)). Root efficiency for shoot N accumulation was increased by 89% in the NPKM treatment compared with the NPK treatment at V12 (the emergence of the twelfth leaf) of 2014. Root growth at 40–60 cm was consistently stimulated after manure and/or straw additions, especially at V12 and R3 (the milk stage) across three years. Root length density (RLD) in the diameter <0.2 mm at 0–20 cm was significantly positively correlated with soil water content and negatively with soil mineral N contents in 2015. The RLD in the diameter >0.4 mm at 20–60 cm, and RLD <0.2 mm, was positively correlated with shoot N uptake in 2015. The root length density was insensitive in response to fertilization treatments, but the variations in RLD along the soil profile in response to fertilization implies that there is a great potential to manipulate N supply levels and rooting depths to increase nutrient use efficiency. The importance of incorporating a manure application together with straw to increase soil fertility in the North China Plain (NCP) needs further studies.

Phenotyping field-state wheat root system architecture for root foraging traits in response to environment×management interactions

An important aspect of below-ground crop physiology is its root foraging performance, which is inherently related to root system architecture (RSA). A 2-yr field experiment was conducted and the field-state wheat RSA was phenotyped for root foraging trait (RFT). Four RSA-derived traits, i.e. Root horizontal angle (RHA), axial root expansion volume (AREV), RSA convex hull volume (CHV) and effective volume per unit root length (EVURL), were analyzed for RFTs in response to environment × management interactions. Results showed a dynamical RHA process but without statistical difference both within crop seasons and tillage treatments. AREV increased with root developmental stages, revealing an overall better root performance in the first year. However, tillage treatments did not induce observed difference within both crop seasons. CHV varied drastically from year to year and between tillage treatments, correlating well to the root length, but not with RHA. EVURL was both sensitive to tillage treatments and crop seasons, being a potential indicator for RFT. Above all, tillage effect on RFT was statistically far less than that induced by crop seasons. Pro/E assisted modeling can be used as an effective means for phenotyping integrated, RSA-derived, RFTs for root foraging response to induced environment × management interactions.

Non-invasive imaging of plant roots in different soils using magnetic resonance imaging (MRI)

BACKGROUND

Root systems are highly plastic and adapt according to their soil environment. Studying the particular influence of soils on root development necessitates the adaptation and evaluation of imaging methods for multiple substrates. Non-invasive 3D root images in soil can be obtained using magnetic resonance imaging (MRI). Not all substrates, however, are suitable for MRI. Using barley as a model plant we investigated the achievable image quality and the suitability for root phenotyping of six commercially available natural soil substrates of commonly occurring soil textures. The results are compared with two artificially composed substrates previously documented for MRI root imaging.

RESULTS

In five out of the eight tested substrates, barley lateral roots with diameters below 300 µm could still be resolved. In two other soils, only the thicker barley seminal roots were detectable. For these two substrates the minimal detectable root diameter was between 400 and 500 µm. Only one soil did not allow imaging of the roots with MRI. In the artificially composed substrates, soil moisture above 70% of the maximal water holding capacity (WHCmax) impeded root imaging. For the natural soil substrates, soil moisture had no effect on MRI root image quality in the investigated range of 50-80% WHCmax.

CONCLUSIONS

Almost all tested natural soil substrates allowed for root imaging using MRI. Half of these substrates resulted in root images comparable to our current lab standard substrate, allowing root detection down to a diameter of 300 µm. These soils were used as supplied by the vendor and, in particular, removal of ferromagnetic particles was not necessary. With the characterization of different soils, investigations such as trait stability across substrates are now possible using noninvasive MRI.

Comparative UAV and Field Phenotyping to Assess Yield and Nitrogen Use Efficiency in Hybrid and Conventional Barley

With the commercialization and increasing availability of Unmanned Aerial Vehicles (UAVs) multiple rotor copters have expanded rapidly in plant phenotyping studies with their ability to provide clear, high resolution images. As such, the traditional bottleneck of plant phenotyping has shifted from data collection to data processing. Fortunately, the necessarily controlled and repetitive design of plant phenotyping allows for the development of semi-automatic computer processing tools that may sufficiently reduce the time spent in data extraction. Here we present a comparison of UAV and field based high throughput plant phenotyping (HTPP) using the free, open-source image analysis software FIJI (Fiji is just ImageJ) using RGB (conventional digital cameras), multispectral and thermal aerial imagery in combination with a matching suite of ground sensors in a study of two hybrids and one conventional barely variety with ten different nitrogen treatments, combining different fertilization levels and application schedules. A detailed correlation network for physiological traits and exploration of the data comparing between treatments and varieties provided insights into crop performance under different management scenarios. Multivariate regression models explained 77.8, 71.6, and 82.7% of the variance in yield from aerial, ground, and combined data sets, respectively.

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.

Sowing Density: A Neglected Factor Fundamentally Affecting Root Distribution and Biomass Allocation of Field Grown Spring Barley (Hordeum Vulgare L.)

Studies on the function of root traits and the genetic variation in these traits are often conducted under controlled conditions using individual potted plants. Little is known about root growth under field conditions and how root traits are affected by agronomic practices in particular sowing density. We hypothesized that with increasing sowing density, root length density (root length per soil volume, cm cm(-3)) increases in the topsoil as well as specific root length (root length per root dry weight, cm g(-1)) due to greater investment in fine roots. Therefore, we studied two spring barley cultivars at ten different sowing densities (24-340 seeds m(-2)) in 2 consecutive years in a clay loam field in Germany and established sowing density dose-response curves for several root and shoot traits. We took soil cores for measuring roots up to a depth of 60 cm in and between plant rows (inter-row distance 21 cm). Root length density increased with increasing sowing density and was greatest in the plant row in the topsoil (0-10 cm). Greater sowing density increased specific root length partly through greater production of fine roots in the topsoil. Rooting depth (D50) of the major root axes (root diameter class 0.4-1.0 mm) was not affected. Root mass fraction decreased, while stem mass fraction increased with sowing density and over time. Leaf mass fraction was constant over sowing density but greater leaf area was realized through increased specific leaf area. Considering fertilization, we assume that light competition caused plants to grow more shoot mass at the cost of investment into roots, which is partly compensated by increased specific root length and shallow rooting. Increased biomass per area with greater densities suggest that density increases the efficiency of the cropping system, however, declines in harvest index at densities over 230 plants m(-2) suggest that this efficiency did not translate into greater yield. We conclude that plant density is a modifier of root architecture and that root traits and their utility in breeding for greater productivity have to be understood in the context of high sowing densities.

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.

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.

Regulation of plant root system architecture: implications for crop advancement

Root system architecture (RSA) plays a major role in plant fitness, crop performance, and grain yield yet only recently has this role been appreciated. RSA describes the spatial arrangement of root tissue within the soil and is therefore crucial to nutrient and water uptake. Recent studies have identified many of the genetic and environmental factors influencing root growth that contribute to RSA. Some of the identified genes have the potential to limit crop loss caused by environmental extremes and are currently being used to confer drought tolerance. It is hypothesized that manipulating these and other genes that influence RSA will be pivotal for future crop advancements worldwide.