A rapid, controlled-environment seedling root screen for wheat correlates well with rooting depths at vegetative, but not reproductive, stages at two field sites

Positional cloning and characterization reveal the role of TaSRN-3D and TaBSR1 in the regulation of seminal root number in wheat

Seminal roots play a critical role in water and nutrient absorption, particularly in the early developmental stages of wheat. However, the genes responsible for controlling SRN in wheat remain largely unknown. Genetic mapping and functional analyses identified a candidate gene (TraesCS3D01G137200, TaSRN-3D) encoding a Ser/Thr kinase glycogen synthase kinase 3 (STKc_GSK3) that regulated SRN in wheat. Additionally, experiments involving hormone treatment, nitrate absorption and protein interaction were conducted to explore the regulatory mechanism of TaSRN-3D. Results showed that the TaSRN-3D4332 allele inhibited seminal roots initiation and development, while loss-of-function mutants showed significantly higher seminal root number (SRN). Exogenous application of epi-brassinolide could increase the SRN in a HS2-allelic background. Furthermore, chlorate sensitivity and 15N uptake assays revealed that a higher number of seminal roots promoted nitrate accumulation. TaBSR1 (BIN2-related SRN Regulator 1, orthologous to OsGRF4/GL2 in rice) acts as an interactor of TaSRN-3D and promotes TaBSR1 degradation to reduce SRN. This study provides valuable insights into understanding the genetic basis and regulatory network of SRN in wheat, highlighting their roles as potential targets for root-based improvement in wheat breeding.

Regulation of root growth and elongation in wheat

Currently, the control of rhizosphere selection on farms has been applied to achieve enhancements in phenotype, extending from improvements in single root characteristics to the dynamic nature of entire crop systems. Several specific signals, regulatory elements, and mechanisms that regulate the initiation, morphogenesis, and growth of new lateral or adventitious root species have been identified, but much more work remains. Today, phenotyping technology drives the development of root traits. Available models for simulation can support all phenotyping decisions (root trait improvement). The detection and use of markers for quantitative trait loci (QTLs) are effective for enhancing selection efficiency and increasing reproductive genetic gains. Furthermore, QTLs may help wheat breeders select the appropriate roots for efficient nutrient acquisition. Single-nucleotide polymorphisms (SNPs) or alignment of sequences can only be helpful when they are associated with phenotypic variation for root development and elongation. Here, we focus on major root development processes and detail important new insights recently generated regarding the wheat genome. The first part of this review paper discusses the root morphology, apical meristem, transcriptional control, auxin distribution, phenotyping of the root system, and simulation models. In the second part, the molecular genetics of the wheat root system, SNPs, TFs, and QTLs related to root development as well as genome editing (GE) techniques for the improvement of root traits in wheat are discussed. Finally, we address the effect of omics strategies on root biomass production and summarize existing knowledge of the main molecular mechanisms involved in wheat root development and elongation.

Root system architecture variation among barley (Hordeum vulgare L.) accessions at seedling stage under soil acidity condition

MAIN CONCLUSION

Soil acidity in Ethiopian highlands impacts barley production, affecting root system architecture. Study on 300 accessions showed significant trait variability, with potential for breeding enhancement. Soil acidity poses a significant challenge to crop production in the highland regions of Ethiopia, particularly impacting barley, a crucial staple crop. This acidity serves as a key stressor affecting the root system architecture (RSA) of this crop. Hence, the objective of this study was to assess the RSA traits variability under acidic soil conditions using 300 barley accessions in a greenhouse experiment. The analysis of variance indicated substantial variations among the accessions across all traits studied. The phenotypic coefficient of variation ranged from 24.4% for shoot dry weight to 11.1% for root length, while the genotypic coefficient variation varied between 18.83 and 9.2% for shoot dry weight and root length, respectively. The broad-sense heritability ranged from 36.7% for leaf area to 69.9% for root length, highlighting considerable heritability among multiple traits. The genetic advances as a percent of the mean ranged from 13.63 to 29.9%, suggesting potential for enhancement of these traits through breeding efforts. Principal component analysis and cluster analysis grouped the genotypes into two major clusters, each containing varying numbers of genotypes with contrasting traits. This diverse group presents an opportunity to access a wide range of potential parent candidates to enhance genetic variablity in breeding programs. The Pearson correlation analysis revealed significant negative associations between root angle (RA) and other RSA traits. This helps indirect selection of accessions for further improvement in soil acidity. In conclusion, this study offers valuable insights into the RSA characteristics of barley in acidic soil conditions, aiding in the development of breeding strategies to enhance crop productivity in acidic soil environments.

Are high-throughput root phenotyping platforms suitable for informing root system architecture models with genotype-specific parameters? An evaluation based on the root model ArchiSimple and a small panel of wheat cultivars

Given the difficulties in accessing plant roots in situ, high-throughput root phenotyping (HTRP) platforms under controlled conditions have been developed to meet the growing demand for characterizing root system architecture (RSA) for genetic analyses. However, a proper evaluation of their capacity to provide the same estimates for strictly identical root traits across platforms has never been achieved. In this study, we performed such an evaluation based on six major parameters of the RSA model ArchiSimple, using a diversity panel of 14 bread wheat cultivars in two HTRP platforms that had different growth media and non-destructive imaging systems together with a conventional set-up that had a solid growth medium and destructive sampling. Significant effects of the experimental set-up were found for all the parameters and no significant correlations across the diversity panel among the three set-ups could be detected. Differences in temperature, irradiance, and/or the medium in which the plants were growing might partly explain both the differences in the parameter values across the experiments as well as the genotype × set-up interactions. Furthermore, the values and the rankings across genotypes of only a subset of parameters were conserved between contrasting growth stages. As the parameters chosen for our analysis are root traits that have strong impacts on RSA and are close to parameters used in a majority of RSA models, our results highlight the need to carefully consider both developmental and environmental drivers in root phenomics studies.

Protein biomarkers for root length and root dry mass on chromosomes 4A and 7A in wheat

Improving the wheat (Triticum aestivum L.) root system is important for enhancing grain yield and climate resilience. Total root length (RL) and root dry mass (RM) significantly contribute to water and nutrient acquisition directly impacting grain yield and stress tolerance. This study used label-free quantitative proteomics to identify proteins associated with RL and RM in wheat near-isogenic lines (NILs). NIL pair 6 had 113 and NIL pair 9 had 30 differentially abundant proteins (DAPs). Three of identified DAPs located within the targeted genomic regions (GRs) of NIL pairs 6 (qDT.4A.1) and 9 (QHtscc.ksu-7A), showed consistent gene expressions at the protein and mRNA transcription (qRT-PCR) levels for asparagine synthetase (TraesCS4A02G109900), signal recognition particle 19 kDa protein (TraesCS7A02G333600) and 3,4-dihydroxy-2-butanone 4-phosphate synthase (TraesCS7A02G415600). This study discovered, for the first time, the involvement of these proteins as candidate biomarkers for increased RL and RM in wheat. However, further functional validation is required to ascertain their practical applicability in wheat root breeding. SIGNIFICANCE OF THE STUDY: Climate change has impacted global demand for wheat (Triticum aestivum L.). Root traits such as total root length (RL) and root dry mass (RM) are crucial for water and nutrient uptake and tolerance to abiotic stresses such as drought, salinity, and nutrient imbalance in wheat. Improving RL and RM could significantly enhance wheat grain yield and climate resilience. However, breeding for these traits has been limited by lack of appropriate root phenotyping methods, advanced genotypes, and the complex nature of the wheat genome. In this study, we used a semi-hydroponic root phenotyping system to collect accurate root data, near-isogenic lines (NILs; isolines with similar genetic backgrounds but contrasting target genomic regions (GRs)) and label-free quantitative proteomics to explore the molecular mechanisms underlying high RL and RM in wheat. We identified differentially abundant proteins (DAPs) and their molecular pathways in NIL pairs 6 (GR: qDT.4A.1) and 9 (GR: QHtscc.ksu-7A), providing a foundation for further molecular investigations. Furthermore, we identified three DAPs within the target GRs of the NIL pairs with differential expression at the transcript level, as confirmed by qRT-PCR analysis which could serve as candidate protein biomarkers for RL and RM improvement.

Diversity, Variance, and Stability of Root Phenes of Peanut (Arachis hypogaea L.)

Root phenes are associated with the absorptive efficiency of water and fertilizers. However, there are few reports on the genetic variation and stability of peanut (Arachis hypogaea L.) root architecture under different environments. In this study, the diversity, variance and stability of root phenes of 89 peanut varieties were investigated with shovelomics (high throughput phenotyping of root system architecture) for two years in both field and laboratory experiments. The root phenes of these peanut genotypes presented rich diversity; for example, the value of total root length (TRL) ranged from 347.84 cm to 1013.80 cm in the field in 2018, and from 55.14 cm to 206.22 cm in the laboratory tests. The root phenes of different genotypes varied differently; for example, the coefficient of variation (CV) of TRL ranged from 24.0 to 83.5 across the two-year field test. Field and laboratory evaluations were highly correlated, especially on lateral root density (LRD) and root angle (RA), and the quadrant graph analysis of LRD and RA implied that 69.7% of the roots belong to the same type. These not only further reflect root phenes stability through different environment but also demonstrate that some root phenes identified at early stage can indicate their status at later growth stage. In addition, root phenes showed a strong correlation with shoot growth, especially root dry weight (RDW), TRL and（nodule number）NN. Thus, laboratory tests in combination with field shovelomics can efficiently screen and select genotypes with contrasting root phenes to optimize water and nutrient management.

Early root phenotyping in sweetpotato (Ipomoea batatas L.) uncovers insights into root system architecture variability

Background

We developed a novel, non-destructive, expandable, ebb and flow soilless phenotyping system to deliver a capable way to study early root system architectural traits in stem-derived adventitious roots of sweetpotato (Ipomoea batatas L.). The platform was designed to accommodate up to 12 stems in a relatively small area for root screening. This platform was designed with inexpensive materials and equipped with an automatic watering system.

Methods

To test this platform, we designed a screening experiment for root traits using two contrasting sweetpotato genotypes, 'Covington' and 'NC10-275'. We monitored and imaged root growth, architecture, and branching patterns every five days up to 20 days.

Results

We observed significant differences in both architectural and morphological root traits for both genotypes tested. After 10 days, root length, surface root area, and root volume were higher in 'NC10-275' compared to 'Covington'. However, average root diameter and root branching density were higher in 'Covington'.

Conclusion

These results validated the effective and efficient use of this novel root phenotyping platforming for screening root traits in early stem-derived adventitious roots. This platform allowed for monitoring and 2D imaging of root growth over time with minimal disturbance and no destructive root sampling. This platform can be easily tailored for abiotic stress experiments, and permit root growth mapping and temporal and dynamic root measurements of primary and secondary adventitious roots. This phenotyping platform can be a suitable tool for examining root system architecture and traits of clonally propagated material for a large set of replicates in a relatively small space.

The Allelopathic Activity of Aqueous Extracts of Helianthus annuus L., Grown in Boreal Conditions, on Germination, Development, and Physiological Indices of Pisum sativum L

Evaluation of the allelopathy relationship between different crops is a sensible strategy fallowing the correct use of positive effects and to avoid the disadvantageous effects among plants. This study aimed to detect the allelopathic effect of aqueous extracts of sunflower (Helianthus annuus L.), grown in a boreal climatic zone, on the growth, subsequent development, and physiological traits of pea (Pisum sativum L.). Three factors have been studied: donor plant fertilization (unfertilized and fertilized), aqueous extracts from donor plant organs (leaves and stems (L+S), heads (H) and roots (R)); four concentrations of extracts (0%, 25%, 50% and 75%). The aqueous extracts from fertilized sunflower donor plant at 25% and 50% concentration acted as potential biostimulants that stimulated pea seed germination (SG), whereas L+S and R extracts at 75% concentration from unfertilized donor plant inhibited SG, at 4 days after sowing. The aqueous extracts demonstrated a stimulating effect on above-ground and root dry mass, compared to the control. The concentration of extracts demonstrated a significant inhibitory effect on SPAD. R extract revealed the strongest allelopathic effect on physiological traits of pea. L+S and H extracts at 25% concentration had stimulating effects, while 50% and 75% concentrations showed inhibiting effects on the photosynthetic rate. The water use efficiency, stomatal conductance, and stomatal limitation were inhibited, whereas, the transpiration rate, photosynthetic water use efficiency and intercellular CO₂ concentration were stimulated, with an increasing of extract concentrations, comparatively to the control.

Quantification of the three-dimensional root system architecture using an automated rotating imaging system

BACKGROUND

Crop breeding based on root system architecture (RSA) optimization is an essential factor for improving crop production in developing countries. Identification, evaluation, and selection of root traits of soil-grown crops require innovations that enable high-throughput and accurate quantification of three-dimensional (3D) RSA of crops over developmental time.

RESULTS

We proposed an automated imaging system and 3D imaging data processing pipeline to quantify the 3D RSA of soil-grown individual plants across seedlings to the mature stage. A multi-view automated imaging system composed of a rotary table and an imaging arm with 12 cameras mounted with a combination of fan-shaped and vertical distribution was developed to obtain 3D image data of roots grown on a customized root support mesh. A 3D imaging data processing pipeline was developed to quantify the 3D RSA based on the point cloud generated from multi-view images. The global architecture of root systems can be quantified automatically. Detailed analysis of the reconstructed 3D root model also allowed us to investigate the Spatio-temporal distribution of roots. A method combining horizontal slicing and iterative erosion and dilation was developed to automatically segment different root types, and identify local root traits (e.g., length, diameter of the main root, and length, diameter, initial angle, and the number of nodal roots or lateral roots). One maize (Zea mays L.) cultivar and two rapeseed (Brassica napus L.) cultivars at different growth stages were selected to test the performance of the automated imaging system and 3D imaging data processing pipeline.

CONCLUSIONS

The results demonstrated the capabilities of the proposed imaging and analytical system for high-throughput phenotyping of root traits for both monocotyledons and dicotyledons across growth stages. The proposed system offers a potential tool to further explore the 3D RSA for improving root traits and agronomic qualities of crops.

Phenotypic and Genotypic Diversity of Roots Response to Salt in Durum Wheat Seedlings

Soil salinity is a serious threat to food production now and in the near future. In this study, the root system of six durum wheat genotypes, including one highly salt-tolerant (J. Khetifa) used as a check genotype, was evaluated, by a high-throughput phenotyping system, under control and salt conditions at the seedling stage. Genotyping was performed using 11 SSR markers closely linked with genome regions associated with root traits. Based on phenotypic cluster analysis, genotypes were grouped differently under control and salt conditions. Under control conditions, genotypes were clustered mainly due to a root angle, while under salt stress, genotypes were grouped according to their capacity to maintain higher roots length, volume, and surface area, as J. Khetifa, Sebatel, and Azeghar. SSR analysis identified a total of 42 alleles, with an average of about three alleles per marker. Moreover, quite a high number of Private alleles in total, 18 were obtained. The UPGMA phenogram of the Nei (1972) genetic distance clusters for 11 SSR markers and all phenotypic data under control conditions discriminate genotypes almost into the same groups. The study revealed as the combination of high-throughput systems for phenotyping with SSR markers for genotyping it's a useful tool to provide important data for the selection of suitable parental lines for salt-tolerance breeding. Nevertheless, the narrow root angle, which is an important trait in drought tolerance, is not a good indicator of salt tolerance. Instated for salt tolerance is more important the amount of roots.

Genotypic variation and covariation in wheat seedling seminal root architecture and grain yield under field conditions

Greater embryo size in a large and carefully phenotyped mapping population was genetically associated with a greater number of longer seminal roots to increase grain yield in droughted field environments. Breeding modification of root architecture is challenging in field environments owing to genetic and phenotypic complexity, and poor repeatability with root sampling. Seeds from a large mapping population varying in embryo size were harvested from a common glasshouse and standardised to a common size before assessing in rolled germination paper at 12 and 20 °C for seedling growth. Differences in genotype means were large and heritabilities high (h² = 0.55-0.93) indicating strong and repeatable genotypic differences for most root traits. Seminal roots 1 to 3 were produced on all seedlings, whereas growth of seminal roots 4, 5 and 6 was associated with differences in embryo size. Increases in seminal root number from 4 to 6 per plant were strongly, genetically correlated with increases in total seminal length (r_g = 0.84, < 0.01). Multivariate analysis confirmed initiation and growth of seminal roots 1, 2 and 3, and of roots 4, 5 and 6 behaved as genetically independent (r_Pg = 0.15 ns) cohorts. Tails representing extremes in seedling root length and number were associated with significant differences in grain yield of up to 35% in droughted field environments but were not different in irrigated environments. Increases in grain yield were linked to greater lengths of seminal roots 4, 5 and 6 and were largely independent of plant height or development. This is the first report on the genetic relationship of seedling root architecture and embryo size, and potential in selection of seminal root size for accessing deep-soil moisture in droughted environments.

The root system architecture of wheat establishing in soil is associated with varying elongation rates of seminal roots: quantification using 4D magnetic resonance imaging

Seedling establishment is the first stage of crop productivity, and root phenotypes at seed emergence are critical to a successful start of shoot growth as well as for water and nutrient uptake. In this study, we investigate seedling establishment in winter wheat utilizing a newly developed workflow based on magnetic resonance imaging (MRI). Using the eight parents of the MAGIC (multi-parent advanced generation inter-cross) population we analysed the 4D root architecture of 288 individual seedlings grown in natural soils with plant neighbors over 3 d of development. Time of root and shoot emergence, total length, angle, and depth of the axile roots varied significantly among these genotypes. The temporal data resolved rates of elongation of primary roots and first and second seminal root pairs. Genotypes with slowly elongating primary roots had rapidly elongating first and second seminal root pairs and vice versa, resulting in variation in root system architecture mediated not only by root angle but also by initiation and relative elongation of axile roots. We demonstrated that our novel MRI workflow with a unique planting design and automated measurements allowed medium throughput phenotyping of wheat roots in 4D and could give new insights into regulation of root system architecture.

Installation and imaging of thousands of minirhizotrons to phenotype root systems of field-grown plants

BACKGROUND

Roots are vital to plant performance because they acquire resources from the soil and provide anchorage. However, it remains difficult to assess root system size and distribution because roots are inaccessible in the soil. Existing methods to phenotype entire root systems range from slow, often destructive, methods applied to relatively small numbers of plants in the field to rapid methods that can be applied to large numbers of plants in controlled environment conditions. Much has been learned recently by extensive sampling of the root crown portion of field-grown plants. But, information on large-scale genetic and environmental variation in the size and distribution of root systems in the field remains a key knowledge gap. Minirhizotrons are the only established, non-destructive technology that can address this need in a standard field trial. Prior experiments have used only modest numbers of minirhizotrons, which has limited testing to small numbers of genotypes or environmental conditions. This study addressed the need for methods to install and collect images from thousands of minirhizotrons and thereby help break the phenotyping bottleneck in the field.

RESULTS

Over three growing seasons, methods were developed and refined to install and collect images from up to 3038 minirhizotrons per experiment. Modifications were made to four tractors and hydraulic soil corers mounted to them. High quality installation was achieved at an average rate of up to 84.4 minirhizotron tubes per tractor per day. A set of four commercially available minirhizotron camera systems were each transported by wheelbarrow to allow collection of images of mature maize root systems at an average rate of up to 65.3 tubes per day per camera. This resulted in over 300,000 images being collected in as little as 11 days for a single experiment.

CONCLUSION

The scale of minirhizotron installation was increased by two orders of magnitude by simultaneously using four tractor-mounted, hydraulic soil corers with modifications to ensure high quality, rapid operation. Image collection can be achieved at the corresponding scale using commercially available minirhizotron camera systems. Along with recent advances in image analysis, these advances will allow use of minirhizotrons at unprecedented scale to address key knowledge gaps regarding genetic and environmental effects on root system size and distribution in the field.

Genetic Analysis of Platform-Phenotyped Root System Architecture of Bread and Durum Wheat in Relation to Agronomic Traits

Roots are essential for water and nutrient uptake but are rarely the direct target of breeding efforts. To characterize the genetic variability of wheat root architecture, the root and shoot traits of 200 durum and 715 bread wheat varieties were measured at a young stage on a high-throughput phenotyping platform. Heritability of platform traits ranged from 0.40 for root biomass in durum wheat to 0.82 for the number of tillers. Field phenotyping data for yield components and SNP genotyping were already available for all the genotypes. Taking differences in earliness into account, several significant correlations between root traits and field agronomic performances were found, suggesting that plants investing more resources in roots in some stressed environments favored water and nutrient uptake, with improved wheat yield. We identified 100 quantitative trait locus (QTLs) of root traits in the bread wheat panels and 34 in the durum wheat panel. Most colocalized with QTLs of traits measured in field conditions, including yield components and earliness for bread wheat, but only in a few environments. Stress and climatic indicators explained the differential effect of some platform QTLs on yield, which was positive, null, or negative depending on the environmental conditions. Modern breeding has led to deeper rooting but fewer seminal roots in bread wheat. The number of tillers has been increased in bread wheat, but decreased in durum wheat, and while the root-shoot ratio for bread wheat has remained stable, for durum wheat it has been increased. Breeding for root traits or designing ideotypes might help to maintain current yield while adapting to specific drought scenarios.

Modifying root-to-shoot ratio improves root water influxes in wheat under drought stress

Drought intensity as experienced by plants depends upon soil moisture status and atmospheric variables such as temperature, radiation, and air vapour pressure deficit. Although the role of shoot architecture with these edaphic and atmospheric factors is well characterized, the extent to which shoot and root dynamic interactions as a continuum are controlled by genotypic variation is less well known. Here, we targeted these interactions using a wild emmer wheat introgression line (IL20) with a distinct drought-induced shift in the shoot-to-root ratio and its drought-sensitive recurrent parent Svevo. Using a gravimetric platform, we show that IL20 maintained higher root water influx and gas exchange under drought stress, which supported a greater growth. Interestingly, the advantage of IL20 in root water influx and transpiration was expressed earlier during the daily diurnal cycle under lower vapour pressure deficit and therefore supported higher transpiration efficiency. Application of a structural equation model indicates that under drought, vapour pressure deficit and radiation are antagonistic to transpiration rate, whereas the root water influx operates as a feedback for the higher atmospheric responsiveness of leaves. Collectively, our results suggest that a drought-induced shift in root-to-shoot ratio can improve plant water uptake potential in a short preferable time window during early morning when vapour pressure deficit is low and the light intensity is not a limiting factor for assimilation.

A toolkit to rapidly modify root systems through single plant selection

BACKGROUND

The incorporation of root traits into elite germplasm is typically a slow process. Thus, innovative approaches are required to accelerate research and pre-breeding programs targeting root traits to improve yield stability in different environments and soil types. Marker-assisted selection (MAS) can help to speed up the process by selecting key genes or quantitative trait loci (QTL) associated with root traits. However, this approach is limited due to the complex genetic control of root traits and the limited number of well-characterised large effect QTL. Coupling MAS with phenotyping could increase the reliability of selection. Here we present a useful framework to rapidly modify root traits in elite germplasm. In this wheat exemplar, a single plant selection (SPS) approach combined three main elements: phenotypic selection (in this case for seminal root angle); MAS using KASP markers (targeting a root biomass QTL); and speed breeding to accelerate each cycle.

RESULTS

To develop a SPS approach that integrates non-destructive screening for seminal root angle and root biomass, two initial experiments were conducted. Firstly, we demonstrated that transplanting wheat seedlings from clear pots (for seminal root angle assessment) into sand pots (for root biomass assessment) did not impact the ability to differentiate genotypes with high and low root biomass. Secondly, we demonstrated that visual scores for root biomass were correlated with root dry weight (r = 0.72), indicating that single plants could be evaluated for root biomass in a non-destructive manner. To highlight the potential of the approach, we applied SPS in a backcrossing program which integrated MAS and speed breeding for the purpose of rapidly modifying the root system of elite bread wheat line Borlaug100. Bi-directional selection for root angle in segregating generations successfully shifted the mean root angle by 30° in the subsequent generation (P ≤ 0.05). Within 18 months, BC₂F₄:F₅ introgression lines were developed that displayed a full range of root configurations, while retaining similar above-ground traits to the recurrent parent. Notably, the seminal root angle displayed by introgression lines varied more than 30° compared to the recurrent parent, resulting in lines with both narrow and wide root angles, and high and low root biomass phenotypes.

CONCLUSION

The SPS approach enables researchers and plant breeders to rapidly manipulate root traits of future crop varieties, which could help improve productivity in the face of increasing environmental fluctuations. The newly developed elite wheat lines with modified root traits provide valuable materials to study the value of different root systems to support yield in different environments and soil types.

Root Morphology, Allometric Relations and Rhizosheath of Ancient and Modern Tetraploid Wheats (Triticum durum Desf.) in Response to Inoculation with Trichoderma harzianum T-22

Early root traits and allometrics of wheat are important for competition and use of resources. They are under-utilized in research and un-explored in many ancient wheats. This is especially true for the rhizosheath emerging from root-soil interactions. We investigated root morphology, root/shoot relations and the amount of rhizosheath of four tetrapoid wheat seedlings (30 days after emergence): the italian landrace Saragolle Lucana and modern varieties Creso, Simeto and Ciclope, and tested the hypothesis that inoculation with Trichoderma harzianum T-22 (T-22) enhances rhizosheath formation and affects wheat varieties differently. Overall growth of non-inoculated plants showed different patterns in wheat varieties, with Saragolle and Ciclope at the two extremes: Saragolle invests in shoot rather than root mass, and in the occupation of space with highest (p < 0.05) shoot height to the uppermost internode (5.02 cm) and length-to-mass shoot (97.8 cm g^-1) and root (more than 140 m g^-1) ratios. This may be interpreted as maximizing competition for light but also as a compensation for low shoot efficiency due to the lowest (p < 0.05) recorded values of optically-measured chlorophyll content index (22.8). Ciclope invests in biomass with highest shoot (0.06 g) and root (0.04 g) mass and a thicker root system (average diameter 0.34 mm vs. 0.29 in Saragolle) as well as a highest root/shoot ratio (0.95 g g^-1 vs. 0.54 in Saragolle). Rhizosheath mass ranged between 22.14 times that of shoot mass in Ciclope and 43.40 in Saragolle (different for p < 0.05). Inoculation with Trichoderma increased the amount of rhizosheath from 9.4% in Ciclope to 36.1% in Simeto and modified root architecture in this variety more than in others. Ours are the first data on roots and seedling shoot traits of Saragolle Lucana and of Trichoderma inoculation effects on rhizosheath. This opens to new unreported interpretations of effects of Trichoderma inoculation on improving plant growth.

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.

Oilseed Rape Cultivars Show Diversity of Root Morphologies with the Potential for Better Capture of Nitrogen

The worldwide demand for vegetable oils is rising. Oilseed rape (Brassica napus) diversifies cereal dominated crop rotations but requires important nitrogen input. Yet, the root organ is offering an untapped opportunity to improve the nitrogen capture in soil. This study evaluates three culture systems in controlled environment, to observe root morphology and to identify root attributes for superior biomass production and nitrogen use. The phenotypic diversity in a panel of 55 modern winter oilseed rape cultivars was screened in response to two divergent nitrate supplies. Upon in vitro and hydroponic cultures, a large variability for root morphologies was observed. Root biomass and morphological traits positively correlated with shoot biomass or leaf area. The activities of high-affinity nitrate transport systems correlated negatively with the leaf area, while the combined high- and low-affinity systems positively with the total root length. The X-ray computed tomography permitted to visualize the root system in pipes filled with soil. The in vitro root phenotype at germination stage was indicative of lateral root deployment in soil-grown plants. This study highlights great genetic potential in oilseed rape, which could be manipulated to optimize crop root characteristics and nitrogen capture with substantial implications for agricultural production.

Genotypic Variability in Architectural Development of Mungbean (Vigna radiata L.) Root Systems and Physiological Relationships With Shoot Growth Dynamics

Selection for root system architectures (RSA) to match target growing environments can improve yields through better adaptation to water and nutrient-limiting conditions in grain legume crops such as mungbean. In this study, the architectural development of root systems in four contrasting mungbean varieties was studied over time to explore their relationships to above-ground growth and development. Key findings suggested that early maturing mungbean varieties were characterized by more rapid root elongation rates and leaf area development, resulting in more vigorous root and shoot growth during early growth stages compared with a late maturing variety. The early maturing varieties also showed root morphological traits generally adapted to water-limited environments, such as deeper, longer and lighter roots. Early maturing varieties more rapidly colonized the top 10-20 cm of the soil profile during early growth stages, whereas the later maturing variety developed less prolific but 20-50% thicker roots in the same profile layers in later stages of crop growth. The diversity of root characteristics identified in these commercial varieties suggests that there are opportunities to combine desirable root traits with maturity types to target different production environments. Examples include deeper, longer, and thinner roots for crops to exploit deep profile reserves of water and nutrients, and thicker and shallower root systems for crops grown in shallow soils with stratified nutrient reserves and/or more favorable in-season rainfall.

Fully-automated root image analysis (faRIA)

High-throughput root phenotyping in the soil became an indispensable quantitative tool for the assessment of effects of climatic factors and molecular perturbation on plant root morphology, development and function. To efficiently analyse a large amount of structurally complex soil-root images advanced methods for automated image segmentation are required. Due to often unavoidable overlap between the intensity of fore- and background regions simple thresholding methods are, generally, not suitable for the segmentation of root regions. Higher-level cognitive models such as convolutional neural networks (CNN) provide capabilities for segmenting roots from heterogeneous and noisy background structures, however, they require a representative set of manually segmented (ground truth) images. Here, we present a GUI-based tool for fully automated quantitative analysis of root images using a pre-trained CNN model, which relies on an extension of the U-Net architecture. The developed CNN framework was designed to efficiently segment root structures of different size, shape and optical contrast using low budget hardware systems. The CNN model was trained on a set of 6465 masks derived from 182 manually segmented near-infrared (NIR) maize root images. Our experimental results show that the proposed approach achieves a Dice coefficient of 0.87 and outperforms existing tools (e.g., SegRoot) with Dice coefficient of 0.67 by application not only to NIR but also to other imaging modalities and plant species such as barley and arabidopsis soil-root images from LED-rhizotron and UV imaging systems, respectively. In summary, the developed software framework enables users to efficiently analyse soil-root images in an automated manner (i.e. without manual interaction with data and/or parameter tuning) providing quantitative plant scientists with a powerful analytical tool.

Genome-wide association screening and verification of potential genes associated with root architectural traits in maize (Zea mays L.) at multiple seedling stages

Background

Breeding for new maize varieties with propitious root systems has tremendous potential in improving water and nutrients use efficiency and plant adaptation under suboptimal conditions. To date, most of the previously detected root-related trait genes in maize were new without functional verification. In this study, seven seedling root architectural traits were examined at three developmental stages in a recombinant inbred line population (RIL) of 179 RILs and a genome-wide association study (GWAS) panel of 80 elite inbred maize lines through quantitative trait loci (QTL) mapping and genome-wide association study.

Results

Using inclusive composite interval mapping, 8 QTLs accounting for 6.44–8.83 % of the phenotypic variation in root traits, were detected on chromosomes 1 (qRDW_v3-1-1 and qRDW/SDW_v3-1-1), 2 (qRBN_v1-2-1), 4 (qSUA_v1-4-1, qSUA_v2-4-1, and qROV_v2-4-1), and 10 (qTRL_v1-10-1, qRBN_v1-10-1). GWAS analysis involved three models (EMMAX, FarmCPU, and MLM) for a set of 1,490,007 high-quality single nucleotide polymorphisms (SNPs) obtained via whole genome next-generation sequencing (NGS). Overall, 53 significant SNPs with a phenotypic contribution rate ranging from 5.10 to 30.2 % and spread all over the ten maize chromosomes exhibited associations with the seven root traits. 17 SNPs were repeatedly detected from at least two growth stages, with several SNPs associated with multiple traits stably identified at all evaluated stages. Within the average linkage disequilibrium (LD) distance of 5.2 kb for the significant SNPs, 46 candidate genes harboring substantial SNPs were identified. Five potential genes viz. Zm00001d038676, Zm00001d015379, Zm00001d018496, Zm00001d050783, and Zm00001d017751 were verified for expression levels using maize accessions with extreme root branching differences from the GWAS panel and the RIL population. The results showed significantly (P < 0.001) different expression levels between the outer materials in both panels and at all considered growth stages.

Conclusions

This study provides a key reference for uncovering the complex genetic mechanism of root development and genetic enhancement of maize root system architecture, thus supporting the breeding of high-yielding maize varieties with propitious root systems.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07874-x.

Deciphering the genetic basis of wheat seminal root anatomy uncovers ancestral axial conductance alleles

Root axial conductance, which describes the ability of water to move through the xylem, contributes to the rate of water uptake from the soil throughout the whole plant lifecycle. Under the rainfed wheat agro-system, grain-filling is typically occurring during declining water availability (i.e., terminal drought). Therefore, preserving soil water moisture during grain filling could serve as a key adaptive trait. We hypothesized that lower wheat root axial conductance can promote higher yields under terminal drought. A segregating population derived from a cross between durum wheat and its direct progenitor wild emmer wheat was used to underpin the genetic basis of seminal root architectural and functional traits. We detected 75 QTL associated with seminal roots morphological, anatomical and physiological traits, with several hotspots harbouring co-localized QTL. We further validated the axial conductance and central metaxylem QTL using wild introgression lines. Field-based characterization of genotypes with contrasting axial conductance suggested the contribution of low axial conductance as a mechanism for water conservation during grain filling and consequent increase in grain size and yield. Our findings underscore the potential of harnessing wild alleles to reshape the wheat root system architecture and associated hydraulic properties for greater adaptability under changing climate.

Root-omics for drought tolerance in cool-season grain legumes

Root traits can be exploited to increase the physiological efficiency of crop water use under drought. Root length, root hairs, root branching, root diameter, and root proliferation rate are genetically defined traits that can help to improve the water productivity potential of crops. Recently, high-throughput phenotyping techniques/platforms have been used to screen the germplasm of major cool-season grain legumes for root traits and their impact on different physiological processes, including nutrient uptake and yield potential. Advances in omics approaches have led to the dissection of genomic, proteomic, and metabolomic structures of these traits. This knowledge facilitates breeders to improve the water productivity and nutrient uptake of cultivars under limited soil moisture conditions in major cool-season grain legumes that usually face terminal drought. This review discusses the advances in root traits and their potential for developing drought-tolerant cultivars in cool-season grain legumes.

Deep soil exploration vs. topsoil exploitation: distinctive rooting strategies between wheat landraces and wild relatives

AIMS

Diversity of root systems among genetic resources can contribute to optimize water and nutrient uptake. Topsoil exploitation vs. deep soil exploration represent two contrasting ideotypes in relation to resource use. Our study reveals how rooting patterns changed between wheat wild progenitors and landraces in regard to these ideotypes.

METHODS

Root (partitioning, morphology, distribution, elongation, anatomy) and shoot traits (dry-matter, leaf area, assimilation) of durum landraces, wild emmer and wild einkorn from Iran, Syria, Turkey and Lebanon were phenotyped using the GrowScreen-Rhizo platform. Distinctive rooting patterns were identified via principal component analysis and relations with collection site characteristics analyzed.

RESULTS

Shoot trait differentiation was strongly driven by seed weight, leading to superior early vigor of landraces. Wild progenitors formed superficial root systems with a higher contribution of lateral and early-emerging nodal axes to total root length. Durum landraces had a root system dominated by seminal axes allocated evenly over depth. Xylem anatomy was the trait most affected by the environmental influence of the collection site.

CONCLUSIONS

The durum landrace root system approximated a deep soil exploration ideotype which would optimize subsoil water uptake, while monococcum-type wild einkorn was most similar to a topsoil exploiting strategy with potential competitive advantages for subsistence in natural vegetation.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11104-020-04794-9.

Accessing Legacy Phosphorus in Soils

Repeated applications of phosphorus (P) fertilizers result in the buildup of P in soil (commonly known as legacy P), a large fraction of which is not immediately available for plant use. Long-term applications and accumulations of soil P is an inefficient use of dwindling P supplies and can result in nutrient runoff, often leading to eutrophication of water bodies. Although soil legacy P is problematic in some regards, it conversely may serve as a source of P for crop use and could potentially decrease dependence on external P fertilizer inputs. This paper reviews the (1) current knowledge on the occurrence and bioaccessibility of different chemical forms of P in soil, (2) legacy P transformations with mineral and organic fertilizer applications in relation to their potential bioaccessibility, and (3) approaches and associated challenges for accessing native soil P that could be used to harness soil legacy P for crop production. We highlight how the occurrence and potential bioaccessibility of different forms of soil inorganic and organic P vary depending on soil properties, such as soil pH and organic matter content. We also found that accumulation of inorganic legacy P forms changes more than organic P species with fertilizer applications and cessations. We also discuss progress and challenges with current approaches for accessing native soil P that could be used for accessing legacy P, including natural and genetically modified plant-based strategies, the use of P-solubilizing microorganisms, and immobilized organic P-hydrolyzing enzymes. It is foreseeable that accessing legacy P will require multidisciplinary approaches to address these limitations.

Root architecture for improved resource capture: trade-offs in complex environments

Root architecture is a promising breeding target for developing resource-efficient crops. Breeders and plant physiologists have called for root ideotypes that have narrow, deep root systems for improved water and nitrate capture, or wide, shallower root systems for better uptake of less mobile topsoil nutrients such as phosphorus. Yet evidence of relationships between root architecture and crop yield is limited. Many studies focus on the response to a single constraint, despite the fact that crops are frequently exposed to multiple soil constraints. For example, in dryland soils under no-till management, topsoil nutrient stratification is an emergent profile characteristic, leading to spatial separation of water and nutrients as the soil profile dries. This results in spatio-temporal trade-offs between efficient resource capture and pre-defined root ideotypes developed to counter a single constraint. We believe there is need to identify and better understand trade-offs involved in the efficient capture of multiple, spatially disjunct soil resources. Additionally, how these trade-offs interact with genotype (root architecture), environment (soil constraints), and management (agronomy) are critical unknowns. We argue that identifying root traits that enable efficient capture of multiple soil resources under fluctuating environmental constraints is a key step towards meeting the challenges of global food security.

The LATERAL ROOT DENSITY gene regulates root growth during water stress in wheat

Drought stress is the major limiting factor in agriculture. Wheat, which is the most widely grown crop in the world, is predominantly cultivated in drought-prone rainfed environments. Since roots play a critical role in water uptake, root response to water limitations is an important component for enhancing wheat adaptation. In an effort to discover novel genetic sources for improving wheat adaptation, we characterized a wheat translocation line with a chromosomal segment from Agropyron elongatum, a wild relative of wheat, which unlike common wheat maintains root growth under limited-water conditions. By exploring the root transcriptome data, we found that reduced transcript level of LATERAL ROOT DENSITY (LRD) gene under limited water in the Agropyron translocation line confers it the ability to maintain root growth. The Agropyron allele of LRD is down-regulated in response to water limitation in contrast with the wheat LRD allele, which is up-regulated by water deficit stress. Suppression of LRD expression in wheat RNAi plants confers the ability to maintain root growth under water limitation. We show that exogenous gibberellic acid (GA) promotes lateral root growth and present evidence for the role of GA in mediating the differential regulation of LRD between the common wheat and the Agropyron alleles under water stress. Suppression of LRD also had a positive pleiotropic effect on grain size and number under optimal growth conditions. Collectively, our findings suggest that LRD can be potentially useful for improving wheat response to water stress and altering yield components.

Image-Based, Organ-Level Plant Phenotyping for Wheat Improvement

Wheat was one of the first grain crops domesticated by humans and remains among the major contributors to the global calorie and protein budget. The rapidly expanding world population demands further enhancement of yield and performance of wheat. Phenotypic information has historically been instrumental in wheat breeding for improved traits. In the last two decades, a steadily growing collection of tools and imaging software have given us the ability to quantify shoot, root, and seed traits with progressively increasing accuracy and throughput. This review discusses challenges and advancements in image analysis platforms for wheat phenotyping at the organ level. Perspectives on how these collective phenotypes can inform basic research on understanding wheat physiology and breeding for wheat improvement are also provided.

Phenotyping in Arabidopsis and Crops-Are We Addressing the Same Traits? A Case Study in Tomato

The convenient model Arabidopsis thaliana has allowed tremendous advances in plant genetics and physiology, in spite of only being a weed. It has also unveiled the main molecular networks governing, among others, abiotic stress responses. Through the use of the latest genomic tools, Arabidopsis research is nowadays being translated to agronomically interesting crop models such as tomato, but at a lagging pace. Knowledge transfer has been hindered by invariable differences in plant architecture and behaviour, as well as the divergent direct objectives of research in Arabidopsis versus crops compromise transferability. In this sense, phenotype translation is still a very complex matter. Here, we point out the challenges of "translational phenotyping" in the case study of drought stress phenotyping in Arabidopsis and tomato. After briefly defining and describing drought stress and survival strategies, we compare drought stress protocols and phenotyping techniques most commonly used in the two species, and discuss their potential to gain insights, which are truly transferable between species. This review is intended to be a starting point for discussion about translational phenotyping approaches among plant scientists, and provides a useful compendium of methods and techniques used in modern phenotyping for this specific plant pair as a case study.

Root phenotypes of young wheat plants grown in controlled environments show inconsistent correlation with mature root traits in the field

Using a field to lab approach, mature deep-rooting traits in wheat were correlated to root phenotypes measured on young plants from controlled conditions. Mature deep-rooting root traits of 20 wheat genotypes at maturity were established via coring in three field trials across 2 years. Field traits were correlated to phenotypes expressed by the 20 genotypes after growth in four commonly used lab screens: (i) soil tubes for root emergence, elongation, length, and branching at four ages to 34 days after sowing (DAS); (ii) paper pouches 7 DAS and (iii) agar chambers for primary root (PR) number and angles at 8 DAS; and (iv) soil baskets for PR and nodal root (NR) number and angle at 42 DAS. Correlations between lab and field root traits (r2=0.45-0.73) were highly inconsistent, with many traits uncorrelated and no one lab phenotype correlating similarly across three field experiments. Phenotypes most positively associated with deep field roots were: longest PR and NR axiles from the soil tube screen at 20 DAS; and narrow PR angle and wide NR angle from soil baskets at 42 DAS. Paper and agar PR angles were positively and significantly correlated to each other, but only wide outer PRs in the paper screen correlated positively to shallower field root traits. NR phenotypes in soil baskets were not predicted by PR phenotypes in any screen, suggesting independent developmental controls and value in measuring both root types in lab screens. Strong temporal and edaphic effects on mature root traits, and a lack of understanding of root trait changes during plant development, are major challenges in creating controlled-environment root screens for mature root traits in the field.

Effects of breeding history and crop management on the root architecture of wheat

AIMS

Selection for optimal root system architecture (RSA) is important to ensure genetic gains in the sustainable production of wheat (Triticum aestivum L.). Here we examine the hypothesis that past wheat breeding has led to changes in RSA and that future breeding efforts can focus directly on RSA to improve adaptation to target environments.

METHODS

We conducted field trials using diverse wheat varieties, including modern and historic UK varieties and non-UK landraces, tested under contrasting tillage regimes (non-inversion tillage versus conventional ploughing) for two trial years or different seeding rates (standard versus high rate) for one trial year. We used field excavation, washing and measurement of root crowns ('shovelomics') to characterise RSA traits, including: numbers of seminal, crown and nodal roots per plant, and crown root growth angle.

RESULTS

We found differences among genotypes for all root traits. Modern varieties generally had fewer roots per plant than historic varieties. On average, there were fewer crown roots and root angles were wider under shallow non-inversion tillage compared with conventional ploughing. Crown root numbers per plant also tended to be smaller at a high seeding rate compared with the standard. There were significant genotype-by-year, genotype-by-tillage and genotype-by-seeding-rate interactions for many root traits.

CONCLUSIONS

Smaller root systems are likely to be a result of past selection that facilitated historical yield increases by reducing below-ground competition within the crop. The effects of crop management practices on RSA depend on genotype, suggesting that future breeding could select for improved RSA traits in resource-efficient farming systems.

Phenotyping: New Windows into the Plant for Breeders

Plant phenotyping enables noninvasive quantification of plant structure and function and interactions with environments. High-capacity phenotyping reaches hitherto inaccessible phenotypic characteristics. Diverse, challenging, and valuable applications of phenotyping have originated among scientists, prebreeders, and breeders as they study the phenotypic diversity of genetic resources and apply increasingly complex traits to crop improvement. Noninvasive technologies are used to analyze experimental and breeding populations. We cover the most recent research in controlled-environment and field phenotyping for seed, shoot, and root traits. Select field phenotyping technologies have become state of the art and show promise for speeding up the breeding process in early generations. We highlight the technologies behind the rapid advances in proximal and remote sensing of plants in fields. We conclude by discussing the new disciplines working with the phenotyping community: data science, to address the challenge of generating FAIR (findable, accessible, interoperable, and reusable) data, and robotics, to apply phenotyping directly on farms.

Phenotypic variability in bread wheat root systems at the early vegetative stage

BACKGROUND

Understanding root system morphology in bread wheat is critical for identifying root traits to breed cultivars with improved resource uptake and better adaptation to adverse environments. Variability in root morphological traits at early vegetative stages was examined among 184 bread wheat genotypes originating from 37 countries grown in a semi-hydroponic phenotyping system.

RESULTS

At the onset of tillering (Z2.1, 35 days after transplanting), plants had up to 42 cm in shoot height and 158 cm long in root depth. Phenotypic variation existed for both shoot and root traits, with a maximal 4.3-fold difference in total root length and 5-fold difference in root dry mass among the 184 genotypes. Of the 41 measured traits, 24 root traits and four shoot traits had larger coefficients of variation (CV ≥ 0.25). Strong positive correlations were identified for some key root traits (i.e., root mass, root length, and these parameters at different depths) and shoot traits (i.e., shoot mass and tiller number) (P ≤ 0.05). The selected 25 global traits (at whole-plant level) contributed to one of the five principal components (eigenvalues> 1) capturing 83.0% of the total variability across genotypes. Agglomerative hierarchical clustering analysis separated the 184 genotypes into four (at a rescaled distance of 15) or seven (at a rescaled distance of 10) major groups based on the same set of root traits. Strong relationships between performance traits (dry mass) with several functional traits such as specific root length, root length intensity and root tissue density suggest their linkage to plant growth and fitness strategies.

CONCLUSIONS

Large phenotypic variability in root system morphology in wheat genotypes was observed at the tillering stage using established semi-hydroponic phenotyping techniques. Phenotypic differences in and trait correlations among some interesting root traits may be considered for breeding wheat cultivars with efficient water acquisition and better adaptation to abiotic stress.

Measuring the Hydraulic Conductivity of Grass Root Systems

Root-system hydraulic conductivity (RSHC) is an important physiological characteristic that describes the inherent ability of roots to conduct water across a water-potential gradient between the root and the stem xylem. RSHC is commonly used as an indicator of plant functioning and adaptability to a given environment. A simple, fast, and easy-to-use protocol is described for the quantification of RSHC at the seedling stage in two important monocot species grown in hydroponic solution: Setaria viridis, a C4 model plant, and wheat, a C3 crop plant. This protocol can also be easily modified for use with almost any grass species and environmental treatments, such as salinity or hormone treatments. © 2020 by John Wiley & Sons, Inc. Basic Protocol: Setaria hydrostatic root-system hydraulic conductivity Alternate Protocol: Measuring the root conductivity of young plants with soft stems.

Segmentation of roots in soil with U-Net

BACKGROUND

Plant root research can provide a way to attain stress-tolerant crops that produce greater yield in a diverse array of conditions. Phenotyping roots in soil is often challenging due to the roots being difficult to access and the use of time consuming manual methods. Rhizotrons allow visual inspection of root growth through transparent surfaces. Agronomists currently manually label photographs of roots obtained from rhizotrons using a line-intersect method to obtain root length density and rooting depth measurements which are essential for their experiments. We investigate the effectiveness of an automated image segmentation method based on the U-Net Convolutional Neural Network (CNN) architecture to enable such measurements. We design a data-set of 50 annotated chicory (Cichorium intybus L.) root images which we use to train, validate and test the system and compare against a baseline built using the Frangi vesselness filter. We obtain metrics using manual annotations and line-intersect counts.

RESULTS

Our results on the held out data show our proposed automated segmentation system to be a viable solution for detecting and quantifying roots. We evaluate our system using 867 images for which we have obtained line-intersect counts, attaining a Spearman rank correlation of 0.9748 and an r 2 of 0.9217. We also achieve an F 1 of 0.7 when comparing the automated segmentation to the manual annotations, with our automated segmentation system producing segmentations with higher quality than the manual annotations for large portions of the image.

CONCLUSION

We have demonstrated the feasibility of a U-Net based CNN system for segmenting images of roots in soil and for replacing the manual line-intersect method. The success of our approach is also a demonstration of the feasibility of deep learning in practice for small research groups needing to create their own custom labelled dataset from scratch.

Variation in Root and Shoot Growth in Response to Reduced Nitrogen

Recently, root traits have been suggested to play an important role in developing greater nitrogen uptake and grain yield. However, relatively few breeding programs utilize these root traits. Over a series of experiments at different growth stages with destructive plant biomass measurements, we analyzed above-ground and below-ground traits in seven geographically diverse lines of wheat. Root and shoot biomass allocation in 14-day-old seedlings were analyzed using paper roll-supported hydroponic culture in two Hoagland solutions containing 0.5 (low) and 4 (high) mM of nitrogen (N). For biomass analysis of plants at maturity, plants were grown in 7.5 L pots filled with soil mix under two nitrogen treatments. Traits were measured as plants reached maturity. High correlations were observed among duration of vegetative growth, tiller number, shoot dry matter, and root dry matter. Functionality of large roots in nitrogen uptake was dependent on the availability of N. Under high N, lines with larger roots had a greater yield response to the increase in N input. Under low N, yields were independent of root size and dry matter, meaning that there was not a negative tradeoff to the allocation of more resources to roots, though small rooted lines were more competitive with regards to grain yield and grain N concentration in the low-N treatment. In the high-N treatment, the large-rooted lines were correlated to an increase in grain N concentration (r = 0.54) and grain yield (r = 0.43). In low N, the correlation between root dry matter to yield (r = 0.20) and grain N concentration (r = -0.38) decreased. A 15-fold change was observed between lines for root dry matter; however, only a ~5-fold change was observed in shoot dry matter. Additionally, root dry matter measured at the seedling stage did not correlate to the corresponding trait at maturity. As such, in a third assay, below-ground and above-ground traits were measured at key growth stages including the four-leaf stage, stem elongation, heading, post-anthesis, and maturity. We found that root growth appears to be stagnant from stem elongation to maturity.

Crop Improvement from Phenotyping Roots: Highlights Reveal Expanding Opportunities

Root systems determine the water and nutrients for photosynthesis and harvested products, underpinning agricultural productivity. We highlight 11 programs that integrated root traits into germplasm for breeding, relying on phenotyping. Progress was successful but slow. Today's phenotyping technologies will speed up root trait improvement. They combine multiple new alleles in germplasm for target environments, in parallel. Roots and shoots are detected simultaneously and nondestructively, seed to seed measures are automated, and field and laboratory technologies are increasingly linked. Available simulation models can aid all phenotyping decisions. This century will see a shift from single root traits to rhizosphere selections that can be managed dynamically on farms and a shift to phenotype-based improvement to accommodate the dynamic complexity of whole crop systems.

Testing deep placement of an 15N tracer as a method for in situ deep root phenotyping of wheat, barley and ryegrass

BACKGROUND

Deep rooting is one of the most promising plant traits for improving crop yield under water-limited conditions. Most root phenotyping methods are designed for laboratory-grown plants, typically measuring very young plants not grown in soil and not allowing full development of the root system.

RESULTS

This study introduced the 15N tracer method to detect genotypic variations of deep rooting and N uptake, and to support the minirhizotron method. The method was tested in a new semifield phenotyping facility on two genotypes of winter wheat, seven genotypes of spring barley and four genotypes of ryegrass grown along a drought stress gradient in four individual experiments. The 15N labeled fertilizer was applied at increasing soil depths from 0.4 to 1.8 m or from 0.7 to 2.8 m through a subsurface tracer supply system, and sampling of aboveground biomass was conducted to measure the 15N uptake. The results confirm that the 15N labeling system could identify the approximate extension of the root system. The results of 15N labeling as well as root measurements made by minirhizotrons showed rather high variation. However, in the spring barley experiment, we did find correlations between root observations and 15N uptake from the deepest part of the root zone. The labeled crop rows mostly had significantly higher 15N enrichment than their neighbor rows.

CONCLUSION

We concluded that the 15N tracer method is promising as a future method for deep root phenotyping because the method will be used for phenotyping for deep root function rather than deep root growth. With some modifications to the injection principle and sampling process to reduce measurement variability, we suggest that the 15N tracer method may be a useful tool for deep root phenotyping. The results demonstrated that the minirhizotrons observed roots of the tested rows rather than their neighboring rows.

Deciphering Root Architectural Traits Involved to Cope With Water Deficit in Oat

Drought tolerance is a complex phenomenon comprising many physiological, biochemical and morphological changes at both aerial and below ground levels. We aim to reveal changes on root morphology that promote drought tolerance in oat in both seedling and adult plants. To this aim, we employed two oat genotypes, previously characterized as susceptible and tolerant to drought. Root phenotyping was carried out on young plants grown either in pots or in rhizotrons under controlled environments, and on adult plants grown in big containers under field conditions. Overall, the tolerant genotype showed an increased root length, branching rate, root surface, and length of fine roots, while coarse to fine ratio decreased as compared with the susceptible genotype. We also observed a high and significant correlation between various morphological root traits within and between experiments, identifying several of them as appropriate markers to identify drought tolerant oat genotypes. Stimulation of fine root growth was one of the most prominent responses to cope with gradual soil water depletion, in both seedlings and adult plants. Although seedling experiments did not exactly match the response of adult plants, they were similarly informative for discriminating between tolerant and susceptible genotypes. This might contribute to easier and faster phenotyping of large amount of plants.

Genome-wide association study reveals genomic regions controlling root and shoot traits at late growth stages in wheat

BACKGROUND AND AIMS

Root system morphology is important for sustainable agriculture, but the genetic basis of root traits and their relationship to shoot traits remain to be elucidated. The aim of the present study was to dissect the genetic basis of root traits at late growth stages and its implications on shoot traits in wheat.

METHODS

Among 323 wheat accessions, we investigated phenotypic differences in root traits at booting and mid-grain fill stages in PVC tubes, shoot traits including plant height (PH), canopy temperature (CT) and grain yield per plant (YPP) in a field experiment, and performed a genome-wide association study with a Wheat 660K SNP Array.

KEY RESULTS

Deep-rooted accessions had lower CT and higher YPP than those with shallow roots, but no significant relationship was identified between root dry weight and shoot traits. Ninety-three significantly associated loci (SALs) were detected by the mixed linear model, among which three were hub SALs (Co-6A, Co-6B and Co-6D) associated with root depth at both booting and mid-grain fill stages, as well as CT and YPP. Minirhizotron system scanning results suggested that the causal genes in the three SALs may regulate root elongation in the field. The heritable independence between root depth and PH was demonstrated by linkage disequilibrium analysis. The YPP was significantly higher in genotypes which combined favourable marker alleles (FMAs) for root depth and PH, suggesting that a deep root and shorter plant height are suitable traits for pyramiding target alleles by molecular marker-assisted breeding.

CONCLUSIONS

These results uncovered promising genomic regions for functional gene discovery of root traits in the late growth period, enhanced understanding of correlation between root and shoot traits, and will facilitate intensive study on root morphology and breeding through molecular design.

Characterization of Cover Crop Rooting Types from Integration of Rhizobox Imaging and Root Atlas Information

Plant root systems are essential for sustainable agriculture, conveying resource-efficient genotypes and species with benefits to soil ecosystem functions. Targeted selection of species/genotypes depends on available root system information. Currently there is no standardized approach for comprehensive root system characterization, suggesting the need for data integration across methods and sources. Here, we combine field measured root descriptors from the classical Root Atlas series with traits from controlled-environment root imaging for 10 cover crop species to (i) detect descriptors scaling between distant experimental methods, (ii) provide traits for species classification, and (iii) discuss implications for cover crop ecosystem functions. Results revealed relation of single axes measures from root imaging (convex hull, primary-lateral length ratio) to Root Atlas field descriptors (depth, branching order). Using composite root variables (principal components) for branching, morphology, and assimilate investment traits, cover crops were classified into species with (i) topsoil-allocated large diameter rooting type, (ii) low-branched primary/shoot-born axes-dominated rooting type, and (iii) highly branched dense rooting type, with classification trait-dependent distinction according to depth distribution. Data integration facilitated identification of root classification variables to derive root-related cover crop distinction, indicating their agro-ecological functions.

Phytohormone Mediation of Interactions Between Plants and Non-Symbiotic Growth Promoting Bacteria Under Edaphic Stresses

The capacity of rhizoshere bacteria to influence plant hormonal status, by bacterial production or metabolism of hormones, is considered an important mechanism by which they promote plant growth, and productivity. Nevertheless, inoculating these bacteria into the plant rhizosphere may produce beneficial or detrimental results depending on bacterial effects on hormone composition and quantity in planta, and the environmental conditions under which the plants are growing. This review considers some effects of bacterial hormone production or metabolism on root growth and development and shoot physiological processes. We analyze how these changes in root and shoot growth and function help plants adapt to their growth conditions, especially as these change from optimal to stressful. Consistent effects are addressed, along with plant responses to specific environmental stresses: drought, salinity, and soil contamination (with petroleum in particular).

Genetic Screening for Mutants with Altered Seminal Root Numbers in Hexaploid Wheat Using a High-Throughput Root Phenotyping Platform

Roots are the main channel for water and nutrient uptake in plants. Optimization of root architecture provides a viable strategy to improve nutrient and water uptake efficiency and maintain crop productivity under water-limiting and nutrient-poor conditions. We know little, however, about the genetic control of root development in wheat, a crop supplying 20% of global calorie and protein intake. To improve our understanding of the genetic control of seminal root development in wheat, we conducted a high-throughput screen for variation in seminal root number using an exome-sequenced mutant population derived from the hexaploid wheat cultivar Cadenza. The screen identified seven independent mutants with homozygous and stably altered seminal root number phenotypes. One mutant, Cadenza0900, displays a recessive extra seminal root number phenotype, while six mutants (Cadenza0062, Cadenza0369, Cadenza0393, Cadenza0465, Cadenza0818 and Cadenza1273) show lower seminal root number phenotypes most likely originating from defects in the formation and activation of seminal root primordia. Segregation analysis in F2 populations suggest that the phenotype of Cadenza0900 is controlled by multiple loci whereas the Cadenza0062 phenotype fits a 3:1 mutant:wild-type segregation ratio characteristic of dominant single gene action. This work highlights the potential to use the sequenced wheat mutant population as a forward genetic resource to uncover novel variation in agronomic traits, such as seminal root architecture.

Three-Dimensional Time-Lapse Analysis Reveals Multiscale Relationships in Maize Root Systems with Contrasting Architectures

Understanding how an organism's phenotypic traits are conditioned by genetic and environmental variation is a central goal of biology. Root systems are one of the most important but poorly understood aspects of plants, largely due to the three-dimensional (3D), dynamic, and multiscale phenotyping challenge they pose. A critical gap in our knowledge is how root systems build in complexity from a single primary root to a network of thousands of roots that collectively compete for ephemeral, heterogeneous soil resources. We used time-lapse 3D imaging and mathematical modeling to assess root system architectures (RSAs) of two maize (Zea mays) inbred genotypes and their hybrid as they grew in complexity from a few to many roots. Genetically driven differences in root branching zone size and lateral branching densities along a single root, combined with differences in peak growth rate and the relative allocation of carbon resources to new versus existing roots, manifest as sharply distinct global RSAs over time. The 3D imaging of mature field-grown root crowns showed that several genetic differences in seedling architectures could persist throughout development and across environments. This approach connects individual and system-wide scales of root growth dynamics, which could eventually be used to predict genetic variation for complex RSAs and their functions.

Three-Dimensional Time-Lapse Analysis Reveals Multiscale Relationships in Maize Root Systems with Contrasting Architectures

Understanding how an organism's phenotypic traits are conditioned by genetic and environmental variation is a central goal of biology. Root systems are one of the most important but poorly understood aspects of plants, largely due to the three-dimensional (3D), dynamic, and multiscale phenotyping challenge they pose. A critical gap in our knowledge is how root systems build in complexity from a single primary root to a network of thousands of roots that collectively compete for ephemeral, heterogeneous soil resources. We used time-lapse 3D imaging and mathematical modeling to assess root system architectures (RSAs) of two maize (Zea mays) inbred genotypes and their hybrid as they grew in complexity from a few to many roots. Genetically driven differences in root branching zone size and lateral branching densities along a single root, combined with differences in peak growth rate and the relative allocation of carbon resources to new versus existing roots, manifest as sharply distinct global RSAs over time. The 3D imaging of mature field-grown root crowns showed that several genetic differences in seedling architectures could persist throughout development and across environments. This approach connects individual and system-wide scales of root growth dynamics, which could eventually be used to predict genetic variation for complex RSAs and their functions.

Genetic Dissection of the Seminal Root System Architecture in Mediterranean Durum Wheat Landraces by Genome-Wide Association Study

Roots are crucial for adaptation to drought stress. However, phenotyping root systems is a difficult and time-consuming task due to the special feature of the traits in the process of being analyzed. Correlations between root system architecture (RSA) at the early stages of development and in adult plants have been reported. In this study, the seminal RSA was analysed on a collection of 160 durum wheat landraces from 21 Mediterranean countries and 18 modern cultivars. The landraces showed large variability in RSA, and differences in root traits were found between previously identified genetic subpopulations. Landraces from the eastern Mediterranean region, which is the driest and warmest within the Mediterranean Basin, showed the largest seminal root size in terms of root length, surface, and volume and the widest root angle, whereas landraces from eastern Balkan countries showed the lowest values. Correlations were found between RSA and yield-related traits in a very dry environment. The identification of molecular markers linked to the traits of interest detected 233 marker-trait associations for 10 RSA traits and grouped them in 82 genome regions named marker-train association quantitative trait loci (MTA-QTLs). Our results support the use of ancient local germplasm to widen the genetic background for root traits in breeding programs.

Scanner-Based Minirhizotrons Help to Highlight Relations between Deep Roots and Yield in Various Wheat Cultivars under Combined Water and Nitrogen Deficit Conditions

Breeding for crops in the context of climate change necessitates phenotyping tools for roots in field conditions. Such in-field phenotyping requires the development of rapid and non-destructive measurement techniques for the screening of relevant root traits under sub-optimal conditions. In this study, we used scanner-based minirhizotrons to measure in situ the root length and surface/volume densities of roots for four wheat varieties, under four different growth conditions: irrigated and rainfed coupled with optimal and sub-optimal N fertilization under a Mediterranean climate. For all the treatments, grain yield correlates with minirhizotron-based root surface density measured at anthesis (r2 = 0.48). Irrigated and rainfed conditions led to contrasted relations between roots and grain yield: no correlation was found in irrigated plots, while under rainfed conditions and sub-optimal fertilization, the higher yields are related to a higher root colonization of the deeper soil layers (r2 = 0.40). Shoot biomass was correlated to grain yield in irrigated conditions, but not in rainfed conditions. However, for the latter, the total root weight, the proportion of which being mainly located in the top soil, is not related to the grain yield. In this way, we show the relationship between these higher grain yields and a stress avoidance mechanism of the root system characterized by a higher root density in the deep soil layers. Thus, unlike shoot biomass measurements, scanner-based minirhizotron allows the direct detection of such a stress-related root development, and therefore opens the door to a better prediction of grain yield.

Phenotypic and metabolic plasticity shapes life-history strategies under combinations of abiotic stresses

Plants developed various reversible and non-reversible acclimation mechanisms to cope with the multifaceted nature of abiotic-stress combinations. We hypothesized that in order to endure these stress combinations, plants elicit distinctive acclimation strategies through specific trade-offs between reproduction and defense. To investigate Brachypodium distachyon acclimation strategies to combinations of salinity, drought and heat, we applied a system biology approach, integrating physiological, metabolic, and transcriptional analyses. We analyzed the trade-offs among functional and performance traits, and their effects on plant fitness. A combination of drought and heat resulted in escape strategy, while under a combination of salinity and heat, plants exhibited an avoidance strategy. On the other hand, under combinations of salinity and drought, with or without heat stress, plant fitness (i.e., germination rate of subsequent generation) was severely impaired. These results indicate that under combined stresses, plants' life-history strategies were shaped by the limits of phenotypic and metabolic plasticity and the trade-offs between traits, thereby giving raise to distinct acclimations. Our findings provide a mechanistic understanding of plant acclimations to combinations of abiotic stresses and shed light on the different life-history strategies that can contribute to grass fitness and possibly to their dispersion under changing environments.

Breeding new varieties for controlled environments

Agricultural production in controlled environments is increasingly feasible, and may play an important role in providing nutrition and choice to growing urban centres. New technologies in lighting, ventilation, robotics and irrigation are just a few of the innovations that enable production of high-value specialty crops outside of a traditional field setting. However, despite all of the advances in the hardware within the plant factory operation, innovation of the most complex machine has been neglected - the plant itself. Indoor agricultural operations typically rely on legacy varieties, plants selected and bred for field conditions. In the field, phenotypic stability is paramount, as production must be consistent in an unpredictable and changing environment. However, the controlled environment affords focus on different breeding priorities as environmental flux, pests, pathogens and post-harvest quality are less formidable barriers to production. On the contrary, breeding for controlled environments shifts the focus to a completely different set of plant traits, such as rapid growth, performance in low light environments and active manipulation of plant stature. Instead of breeding for phenotypic stability, plants may be bred to maximise genetic plasticity, allowing specific traits to be presented as a function of the quality of the ambient light spectrum. In this scenario plant varieties may be grown with optimal size, supporting a focus on consumer traits like flavour or accumulation of health-related compounds. Gene editing may be a central technology in the production of designer plants for controlled environments. This review considers the opportunity for breeding for controlled environments, with a focus on a revision of priorities for controlled-environment breeders.