Root anatomical features are critical for plant performance characterization, yet phenotyping at the anatomical scale remains limited by the extreme annotation burden of cellular segmentation. We present a two-stage segmentation framework that greatly reduces annotation requirements while maintaining high accuracy across diverse plant species and imaging conditions. Our approach decomposes multi-class segmentation into species-agnostic tissue identification followed by tissue type classification. By designing robust input representations invariant to imaging artifacts and morphological variations, our framework enables rapid adaptation to new species with fewer than 40 labeled images. Additionally, the first stage automatically generates tissue boundaries, transforming tedious manual tracing into simple tissue labeling. We validate our method on pearl millet, and sorghum root cross-sections from different imaging protocols, achieving state-of-the-art performance while dramatically reducing deployment time. This efficiency breakthrough enables scalable root phenotyping across diverse crop species, accelerating the development of climate-resilient varieties for global food security.

BACKGROUND:Root hairs play a key role in plant nutrient and water uptake. Historically, root hair traits have largely been quantified manually. As such, this process has been laborious and low-throughput. However, given their importance for plant health and development, high-throughput quantification of root hair morphology could help underpin rapid advances in the genetic understanding of these traits. With recent increases in the accessibility and availability of artificial intelligence (AI) and machine learning techniques, the development of tools to automate plant phenotyping processes has been greatly accelerated. RESULTS:We present pyRootHair, a high-throughput, AI-powered software application to automate root hair trait extraction from microscope images of plant roots grown on agar plates. pyRootHair is capable of batch processing over 600 images per hour without manual input from the end user. In this study, we deploy pyRootHair on a panel of 24 diverse wheat (Triticum aestivum and Triticum turgidum ssp. durum) cultivars and uncover a large, previously unresolved amount of variation in many root hair traits. We show that the overall root hair profile falls under 2 distinct shape categories and that different root hair traits often correlate with each other. We also demonstrate that pyRootHair can be deployed on a range of plant species, including oat (Avena sativa), rice (Oryza sativa), teff (Eragrostis tef), and tomato (Solanum lycopersicum). CONCLUSIONS:The application of pyRootHair enables users to rapidly screen a large number of plant germplasm resources for variation in root hair morphology, supporting high-resolution measurements and high-throughput data analysis. This facilitates downstream investigation of the impacts of root hair genetic control and morphological variation on plant performance. pyRootHair is installable via PyPI (https://pypi.org/project/pyRootHair/) and can be accessed on GitHub at https://github.com/iantsang779/pyRootHair.

Soil compaction is an increasing problem in global agriculture, causing more severe effects when soil dries. Since insensitivity to the plant hormone ethylene maintains root elongation in compact soil, wheat cultivars with reduced sensitivity to ethylene were hypothesised to have greater root and shoot growth in compact soil, and higher plant water status when this soil dried. Screening wheat cultivars revealed root-applied ethephon solution or exposure to ethylene gas inhibited root elongation of the cultivar Chewink#1 more than Kutz. These cultivars were glasshouse-grown in soil columns with a factorial combination of soil compaction and drying, and in field trials with different tillage or irrigation treatments. Although both cultivars had similar root and shoot biomass in loose soil irrespective of soil moisture, Kutz accumulated more biomass than Chewink#1 in compact soil. Greater root development of Kutz deeper in the soil profile (also occurring in field experiments) was associated with cultivar differences in water relations, as Kutz maintained higher stomatal conductance and leaf water potential, with lower foliar ABA concentration, as compact soil dried. Although further investigations with specific wheat alleles conferring ethylene sensitivity are needed, cultivars with less ethylene-sensitive root growth may grow better in compact soils, as observed in rice.

Plants and their ability to capture atmospheric CO2 are indispensable for the buildup of soil organic matter, underscoring their crucial role in terrestrial carbon cycling. Yet, the plant physiological processes regulating soil carbon inputs and their environmental controls remain severely underrepresented in soil carbon research, which limits our understanding of soil carbon sequestration potential across biomes and land uses. Root biomass constitutes a major input of organic matter to soil that is particularly difficult to estimate. Here, we outline a framework for the explicit integration of root growth physiology into soil carbon dynamics. Using data acquired in rice (Oryza sativa, L.), we provide mechanistic evidence that the expansion of cortical cells in growing roots is a key process determining the fate of the carbon plants allocate to their root system. We combined measurements of carbon partitioning between biomass formation and respiration in growing roots with three-dimensional quantifications of root cortical cell size using high resolution (1.8 μm) X-ray Computed Tomography. With increasing cortical cell size, indicating greater contribution of cell expansion over cell division to root growth, more carbon was allocated to root biomass formation and less to root respiration (R2 = 0.83). We then integrated our experimental findings with data obtained from the literature covering different land use types to highlight the fundamental importance of including root physiological processes in estimating soil carbon inputs. The established structural-functional relationships between root cortical cell size and carbon partitioning point out the paramount role of root physiology in improving our understanding and prediction of carbon fluxes and retention in plant-soil systems. We therefore propose that measurements of root cortical anatomy be included when assessing global change impacts on soil carbon inputs and the potential of soils to sequester carbon.

Wild relatives of wheat harbour genetic diversity essential for improving resilience to climate-driven stresses, yet their deployment is hampered by unresolved evolutionary relationships and the absence of reference genomes. Here we present a chromosome-scale reference genome for Thinopyrum bessarabicum , a diploid halophyte and high-priority donor for wheat salt tolerance breeding. A key unresolved question is whether the diploid J genome contributed directly to the subgenome composition of extant polyploid Thinopyrum species, and which genomic features underpin its exceptional salt tolerance. Using this resource, we show that the diploid J genome of Th. bessarabicum is not represented among the subgenomes of polyploid Thinopyrum species, resolving a long-standing ambiguity in Triticeae genomics. Gene-level resolution of the reciprocal 4/5 chromosomal translocation across six related Triticeae species identifies conserved breakpoint gene pairs, supporting a single ancestral rearrangement. Genome-wide gene content analysis shows that halophytic capacity is underpinned by quantitative expansion of conserved stress-response gene families. Salt tolerance phenotyping validates chromosome 5J as a tolerance locus in both Th. bessarabicum and wheat introgression lines. A physically anchored marker framework and dual-reference skim-sequencing pipeline enable precise megabase-resolution characterisation of Th. bessarabicum introgressions in wheat, providing a genomic foundation for deploying J-genome diversity in crop improvement.

Plant phenotyping increasingly relies on (semi-)automated image-based analysis workflows to improve its accuracy and scalability. However, many existing solutions remain overly complex, difficult to reimplement and maintain, and pose high barriers for users without substantial computational expertise. To address these challenges, we introduce PhenoAssistant: a pioneering AI-driven system that streamlines plant phenotyping via intuitive natural language interaction. PhenoAssistant leverages a large language model to orchestrate a curated toolkit supporting tasks including automated phenotype extraction, data visualisation and automated model training. We validate PhenoAssistant through several representative case studies and a set of evaluation tasks. By significantly lowering technical hurdles, PhenoAssistant underscores the promise of AI-driven methodologies to democratising AI adoption in plant biology.

BACKGROUND:The reconstruction of 3-dimensional (3D) plant models can offer advantages over traditional 2-dimensional approaches by more accurately capturing the complex structure and characteristics of different crops. Conventional 3D reconstruction techniques often produce sparse or noisy representations of plants using software or are expensive to capture in hardware. Recently, view synthesis models have been developed that can generate detailed 3D scenes, and even 3D models, from only RGB images and camera poses. These models offer unparalleled accuracy but are currently data hungry, requiring large numbers of views with very accurate camera calibration. RESULTS:In this study, we present a view synthesis dataset comprising 20 individual wheat plants captured across 6 different time frames over a 15-week growth period. We develop a camera capture system using 2 robotic arms combined with a turntable, controlled by a re-deployable and flexible image capture framework. We trained each plant instance using two recent view synthesis models: 3D Gaussian splatting (3DGS) and neural radiance fields (NeRF). Our results show that both 3DGS and NeRF produce high-fidelity reconstructed images of a plant subject from views not captured in the initial training sets. We also show that these approaches can be used to generate accurate 3D representations of these plants as point clouds, with 0.74-mm and 1.43-mm average accuracy compared with a handheld scanner for 3DGS and NeRF, respectively. CONCLUSION:We believe that these new methods will be transformative in the field of 3D plant phenotyping, plant reconstruction, and active vision. To further this cause, we release all robot configuration and control software, alongside our extensive multiview dataset. We also release all scripts necessary to train both 3DGS and NeRF, all trained models data, and final 3D point cloud representations. Our dataset can be accessed via https://plantimages.nottingham.ac.uk/ or https://https://doi.org/10.5524/102661. Our software can be accessed via https://github.com/Lewis-Stuart-11/3D-Plant-View-Synthesis.

Soils are highly heterogeneous and dynamic systems, experiencing a constant flow of plant root exudates and moisture fluctuations that affect nutrient distribution, soil physicochemical properties, and microbial metabolisms. Plant roots adjust their development within the soil matrix (growth, branching, root angle, and anatomical features) by integrating local environmental conditions with physiologically informed signals. These physiological responses and the adaptability of roots are commonly defined as plasticity. Although genetically determined, root plasticity is modulated by local fluctuations in water and nutrient availability, environmental changes, and soil properties as well as by the root-associated microbiota. Roots and their vicinity are colonized by taxonomically and functionally diverse microbial species. Specific members within these communities can establish chemical communication with plants via root-derived signals, thereby tapping into the plant's hormonal and developmental network, influencing root plasticity. Given that most root traits associated with plasticity have been discovered under axenic conditions, our knowledge of the multiple potential mechanisms by which members of the root-associated microbiota modulate root plastic responses is still limited. In this review, we explore the recent progress in this field and identify specific avenues for future research toward advancing molecular and ecological understanding of microbial-mediated root plasticity in terrestrial systems.

SUMOylation is essential in plant and animal cells, but it remains unknown how small ubiquitin-like modifier (SUMO) components act in concert to modify specific targets in response to environmental stresses. In this study, we characterize every SUMO component in the Arabidopsis root to create a complete SUMO Cell Atlas in eukaryotes. This unique resource reveals wide spatial variation, where SUMO proteins and proteases have subfunctionalized in both their expression and subcellular localization. During stress, SUMO conjugation is mainly driven by tissue-specific regulation of the SUMO E2-conjugating enzyme. Stress-specific modulation of the SUMO pathway reveals unique combinations of proteases being targeted for regulation in distinct root tissues by salt, osmotic, and biotic signals. Our SUMO Cell Atlas resources reveal how this posttranslational modification (PTM) influences cellular- and tissue-scale adaptations during root development and stress responses. To our knowledge, we provide the first comprehensive study elucidating how multiple stress inputs can regulate an entire PTM system.

To meet the demands of a rising human population, plant breeders will need to develop improved crop varieties that maximize yield in the face of increasing pressure on crop production. Historically, the optimization of crop root architecture has represented a challenging breeding target due to the inaccessibility of the root systems. Root hairs, single cell projections from the root epidermis, are perhaps the most overlooked component of root architecture traits. Root hairs play a central role in facilitating water, nutrient uptake, and soil cohesion. Current root hair architectures may be sub-optimal under future agricultural production regimes, coupled with an increasingly variable climate. Here, we review the genetic control of root hair development in the world's three most important crops: rice, maize and wheat, and highlight conservation of gene function between monocots and the model dicot species Arabidopsis. Advances in genomic techniques including Gene-Editing combined with traditional plant breeding methods have the potential to overcome many inherent issues associated with the design of improved root hair architectures. Ultimately, this will enable detailed characterization of the effects of contrasting root hair morphology strategies on crop yield and resilience, and the development of new varieties better adapted to deliver future food security.

Soil structure is a crucial soil physical property that determines a soil's ability to support the growth and development of plants. Soil compaction modifies soil structure by reducing pore space between soil particles thereby leading to a denser soil fabric. This often limits root growth by increasing soil strength and penetration resistance requiring roots to increase the energy needed to elongate and explore deeper soil. Apart from soil compaction, soil moisture also plays an important role in determining how resistant soil is to root penetration. An understanding of how the synergy of both compaction and moisture content affect root growth is essential to improving plant productivity. We used wheat (Triticum aestivum) seedlings to investigate the differences in root architectural properties using X-ray Computed Tomography imaging under three different compaction levels (1.3, 1.5 and 1.7 Mg m- 3) maintained at two different water contents (100% and 70% of field capacity). This was performed on soils of two different textures, a sandy loam and a sandy clay loam. Soil compaction to 1.7 g cm-3 significantly reduced root length, volume and surface area compared to lower compaction levels. Increased soil compaction also resulted in increased root growth angle in the sandy clay loam. Compaction reduced gas diffusivity in both soils (as determined by modelling). Soil moisture on the other hand had a significant impact on average root diameter; plants grown at 100% of field capacity had a higher average root diameter than those at 70% field capacity. Compaction up to 1.7 Mg m- 3 adversely effected wheat root growth in both soil textures regardless of moisture content.

Seedling root traits impact plant establishment under challenging environments. Pearl millet is one of the most heat and drought tolerant cereal crops that provides a vital food source across the sub-Saharan Sahel region. Pearl millet’s early root system features a single fast-growing primary root which we hypothesize is an adaptation to the Sahelian climate. Using crop modeling, we demonstrate that early drought stress is an important constraint in agrosystems in the Sahel where pearl millet was domesticated. Furthermore, we show that increased pearl millet primary root growth is correlated with increased early water stress tolerance in field conditions. Genetics including genome-wide association study and quantitative trait loci (QTL) approaches identify genomic regions controlling this key root trait. Combining gene expression data, re-sequencing and re-annotation of one of these genomic regions identified a glutaredoxin-encoding gene PgGRXC9 as the candidate stress resilience root growth regulator. Functional characterization of its closest Arabidopsis homolog AtROXY19 revealed a novel role for this glutaredoxin (GRX) gene clade in regulating cell elongation. In summary, our study suggests a conserved function for GRX genes in conferring root cell elongation and enhancing resilience of pearl millet to its Sahelian environment.

BackgroundRoot hairs are single-celled projections on root surfaces, critical for water and nutrient uptake. Here, we describe the first short root hair mutant in wheat (Triticum aestivum L.), identified in a mutagenized population and termed here short root hair 1 (srh1).ResultsWhile the srh1 mutant can initiate root hair bulges, lack of subsequent extension results in very short root hairs. Due to its semi-dominant nature, heterozygous lines displayed intermediate root hair lengths compared to wild-type. Bulked segregant analysis in a BC1F3 segregating population genotyped via exome capture sequencing localized the genetic control of this mutant to a region on the long arm of chromosome 3A. Via RNA sequencing and bioinformatic analysis, we identified two promising candidate genes. The first was a respiratory burst oxidase homolog (RBOH) encoding gene TaNOX3-A, orthologous to RBOH genes controlling root hair elongation in rice (OsNOX3) and maize (ZmRTH5), that carries a missense mutation in a conserved region of the predicted protein. RBOHs are membrane bound proteins that produce reactive oxygen species (ROS) which trigger cell wall extensibility, allowing subsequent root hair elongation. Notably, reduced ROS levels were observed in srh1 root hair bulges compared to wild-type. The second candidate was the calreticulin-3 encoding gene TaCRT3-A, located within the wider srh1 interval and whose expression was significantly downregulated in srh1 root tissues.ConclusionsThe identification of a major effect gene controlling wheat root hair morphology provides an entry point for future optimization of root hair architecture best suited to future agricultural environments.

Soil structure is a crucial soil physical property that determines a soil’s ability to support the growth and development of plants. Soil compaction modifies soil structure by reducing pore space between soil particles thereby leading to a denser soil fabric. This often limits root growth by increasing soil strength and penetration resistance requiring roots to increase the energy needed to elongate and explore deeper soil. Apart from soil compaction, soil moisture also plays an important role in determining how resistant soil is to root penetration. An understanding of how the synergy of both compaction and moisture content affect root growth is essential to improving plant productivity. We used wheat (Triticum aestivum) seedlings to investigate the differences in root architectural properties (root length, diameter, angle, volume and surface area) using X-ray Computed Tomography imaging under three different compaction levels (1.3, 1.5 and 1.7 Mg m-3) maintained at two different water contents (100% and 70% of field capacity). This was performed on soils of two different textures, a sandy loam and a sandy clay loam. Soil compaction to 1.7g cm-3 significantly reduced root length, volume and surface area compared to lower compaction levels. Increased soil compaction also resulted in increased root growth angle in the sandy clay loam. Compaction reduced gas diffusivity in both soils (as determined by modelling). Soil moisture on the other hand had a significant impact on average root diameter; plants grown at 100% of field capacity had a higher average root diameter than those at 70% field capacity. Compaction up to 1.7 Mg m-3 adversely effected wheat root growth in both soil textures regardless of moisture content.

Despite extensive research over the last century concerning the application of nitrogen fertilizer to support the production of wheat (Triticum aestivum L.), our understanding on how this impacts on root growth in subsoils is limited. In this study, we investigated how different rates of nitrogen fertilization (100, 200 and 350 kg/ha N) affected the root and shoot growth of three different wheat genotypes. We collected field soil cores to a depth of 100 cm and scanned them using X-ray Computed Tomography (CT) to quantify the volume of macropores and stony material. The collected soil cores were then destructively segmented to determine root number density. Our results showed nitrogen fertilization rate had a limited effect on root growth and proliferation in both the topsoil and subsoil. Furthermore, wheat genotype did not play a significant role in determining root growth at any depth, with no significant differences between the different genotypes. However, soil macroporosity was positively correlated to root number density, accounting for 48% of the variation. Our results provide evidence that soil management (e.g. cultivation techniques) may be the key to improving subsoil rooting regardless of crop genotype and nitrogen rates applied.

Organ loss occurs frequently during plant and animal evolution. Sometimes, non-functional organs are retained through evolution. Vestigial organs are defined as genetically determined structures that have lost their ancestral (or salient) function.1,2,3 Duckweeds, an aquatic monocot family, exhibit both these characteristics. They possess a uniquely simple body plan, variably across five genera, two of which are rootless. Due to the existence of closely related species with a wide diversity in rooting strategies, duckweed roots represent a powerful system for investigating vestigiality. To explore this, we employed a panel of physiological, ionomic, and transcriptomic analyses, with the main goal of elucidating the extent of vestigiality in duckweed roots. We uncovered a progressive reduction in root anatomy as genera diverge and revealed that the root has lost its salient ancestral function as an organ required for supplying nutrients to the plant. Accompanying this, nutrient transporter expression patterns have lost the stereotypical root biased localization observed in other plant species. While other examples of organ loss such as limbs in reptiles4 or eyes in cavefish5 frequently display a binary of presence/absence, duckweeds provide a unique snapshot of an organ with varying degrees of vestigialization in closely related neighbors and thus provide a unique resource for exploration of how organs behave at different stages along the process of loss.

Rising temperatures and extreme heat events threaten rice production. Half of the global population relies on rice for basic nutrition, and therefore developing heat-tolerant rice is essential. During vegetative development, reduced photosynthetic rates can limit growth and the capacity to store soluble carbohydrates. The photosystem II (PSII) complex is a particularly heat-labile component of photosynthesis. We have developed a high-throughput chlorophyll fluorescence-based screen for photosynthetic heat tolerance capable of screening hundreds of plants daily. Through measuring the response of maximum PSII efficiency to increasing temperature, this platform generates data for modelling the PSII-temperature relationship in large populations in a small amount of time. Coefficients from these models (photosynthetic heat tolerance traits) demonstrated high heritabilities across African (Oryza glaberrima) and Asian (Oryza sativa, Bengal Assam Aus Panel) rice diversity sets, highlighting valuable genetic variation accessible for breeding. Genome-wide association studies were performed across both species for these traits, representing the first documented attempt to characterize the genetic basis of photosynthetic heat tolerance in any species to date. A total of 133 candidate genes were highlighted. These were significantly enriched with genes whose predicted roles suggested influence on PSII activity and the response to stress. We discuss the most promising candidates for improving photosynthetic heat tolerance in rice.

Root system architecture (RSA) is important in optimizing the use of nitrogen. High-throughput phenotyping techniques may be used to study root system architecture traits under controlled environments. A root pheno-typing platform, consisting of germination paper-based pouch and wick coupled with image analysis, was used to characterize root seedling traits in 30 landrace-derived bread wheat genotypes and the bread wheat parent Paragon under hydroponic high N (HN) and low N (LN) conditions. In addition, two glasshouse experiments under HN and LN conditions were carried out to measure whole plant performance including flag-leaf photo-synthetic rate, N uptake and biomass per plant for 13 wheat genotypes of which eight were common with those in the root phenotyping hydroponic experiment. There were significant differences in RSA traits between ge-notypes for seminal root number per plant, lateral root number per plant, seminal root length per plant and seminal root angle, with transgressive segregation for landrace-derived lines above the elite parental cultivar Paragon under HN and LN conditions. In the glasshouse experiments, genetic variation in flag-leaf photosynthesis rate was found in landrace-derived genotypes in the range 25.9-33.3 mu mol m- 2 s- 1 under HN and in N uptake in the ranges 0.37-0.48 g N plant-1and 0.21-0.30 g plant-1 under HN and LN conditions, respectively (P < 0.05), with transgressive segregation above Paragon. Plant Nitrogen Nutrition Index also showed transgressive segre-gation in the landrace-derived lines above Paragon under HN and LN conditions. Greater maximum root depth and more lateral roots per plant in the hydroponic screen were each correlated with increased biomass per plant under LN conditions. Results from this study demonstrated genetic variation for seedling RSA traits in landrace-derived lines above the elite parental cultivar Paragon, which potentially could be utilized to improve N-use efficiency in breeding programmes.

Duckweeds are morphologically simplified, free floating aquatic monocots comprising both rooted and rootless genera. This has led to the idea that roots in these species may be vestigial, but empirical evidence supporting this is lacking. Here we show that duckweed roots are no longer required for their ancestral role of nutrient uptake. Comparative analyses of nearly all rooted duckweed species revealed a highly reduced anatomy, with greater simplification in the more recently diverged genus Lemna . A series of root excision experiments demonstrated that roots are dispensable for normal growth in Spirodela polyrhiza and Lemna minor . Furthermore, ionomic analyses of fronds in these two species showed little difference in the elemental composition of plants in rooted versus root-excised samples. In comparison, another free-floating member of the Araceae, Pistia stratiotes , which colonized the aquatic environment independently of duckweeds, has retained a more complex root anatomy. Whilst Pistia roots were not absolutely required for growth, their removal inhibited plant growth and resulted in a broad change in the mineral profile of aerial tissues. Collectively, these observations suggest that duckweeds and Pistia may be different stages along a trajectory towards root vestigialization Given this, along with the striking diversity of root phenotypes, culminating in total loss in the most derived species, we propose that duckweed roots are a powerful system with which to understand organ loss and vestigiality.One sentence summary Through their adaption to the aquatic environment, duckweed roots have progressively become structurally reduced making them an ideal plant model with which to study vestigiality.