Root phenotyping: important and minimum information required for root modeling in crop plants

Open stomata 1 and phosphate starvation response 1 regulate tomato root system architecture during heterogeneous phosphate availability

Plants frequently encounter uneven phosphate (Pi) distribution, yet most studies focuses on uniform low-Pi conditions. SUCROSE NONFERMENTING1-RELATED KINASE 2.6 (SnRK2.6) protein, also known as Open stomata 1 (OST1), is well-characterized in ABA signaling and stress responses. However, its role in low-Pi response is poorly understood. We investigated root system architecture (RSA) remodeling under uneven Pi distribution. Using split-root tomato plants with half roots in sufficient Pi (+Pi) and half in low Pi (-Pi), we observed low-Pi responses in both root sectors. Local low-Pi triggered the ABA accumulation in the local root regions, generating spatially distinct OST1 expression patterns. In mechanism, phosphate starvation response 1 (PHR1) directly binds to the OST1 promoter, activating its expression its expression under low-Pi conditions. This localized OST1 transcriptional regulation mediated both local and systemic RSA adaptations. Crucially, these Pi-responsive RSA remodeling were completely absent in ost1 and notabilis (not) mutants. These findings demonstrate that spatial phosphate availability shapes tomato root architecture through ABA-dependent OST1 activation and PHR1-mediated transcriptional regulation, identifying a previously unknown adaptive response to nutrient heterogeneity.

Navigating nitrogen sustainability with microbiome-associated phenotypes

Crop microbiomes promote plant health through various mechanisms, including nutrient provisioning. However, agriculture neglected the importance of these microbiome-associated phenotypes (MAPs) in conventional management approaches originating from the Green Revolution. Green Revolution innovations, such as nitrogen fertilizers and high-yielding germplasm, supported an increase in global crop yields. Yet these advances also led to many environmental issues, including disruptions in microbially mediated nitrogen transformations that have reduced reliance on microbiomes for sustainable nitrogen acquisition. Overcoming the challenges introduced by the Green Revolution requires a shift toward ecologically informed agronomic strategies that incorporate MAPs into breeding and management decisions. Agriculture in the Anthropocene needs to mindfully manage crop microbiomes to decouple agrochemical inputs from profitable yields, minimizing the environmental repercussions of modern agriculture.

Decreased root hydraulic traits in German winter wheat cultivars over 100 years of breeding

Wheat (Triticum aestivum L.) plays a vital role in global food security, and understanding its root traits is essential for improving water uptake under varying environmental conditions. This study investigated how over a century of breeding has influenced root morphological and hydraulic properties in 6 German winter wheat cultivars released between 1895 and 2002. Field and hydroponic experiments were used to measure root diameter, root number, branching density, and whole root system hydraulic conductance (Krs). The results showed a significant decline in root axes number and Krs with release year, while root diameter remained stable across cultivars. Additionally, dynamic functional-structural modeling using the whole-plant model CPlantBox was employed to simulate Krs development with root system growth, revealing that older cultivars consistently had higher hydraulic conductance than modern ones. The combined approach of field phenotyping and modeling provided a comprehensive view of the changes in root traits arising from breeding. These findings suggest that breeding may have unintentionally favored cultivars with smaller root systems and more conservative water uptake strategies under the high-input, high-density conditions of modern agriculture. The results of this study may inform future breeding efforts aimed at optimizing wheat root systems, helping to develop cultivars with water uptake strategies better tailored to locally changing environmental conditions.

Genome-wide analysis of the phosphate transporter gene family in oats: insights into phosphorus and water deficiency responses

Phosphorus (P) and water are essential for plant growth and development, exerting a significant influence on global crop production. The phosphate transporter (PHT) gene family plays a pivotal role in phosphate (Pi) uptake, transport, and homeostasis under diverse environmental conditions. In this study, we conducted a comprehensive genome-wide identification and characterization of the PHT gene family in Avena sativa. A total of 32 non-redundant AsPHT genes were identified in the OT3098 genome, classified into two subfamilies: AsPHT1 (21 genes) and AsPHO (11 genes). AsPHT1 proteins were predominantly hydrophobic with one or two exons, whereas AsPHO proteins were hydrophilic, exhibiting a more complex structure with 13-15 exons. Cis-regulatory element analysis revealed an abundance of hormone- and stress-responsive elements in the promoters of AsPHT genes, indicating their potential roles in adaptive responses to Pi and water deficiency. Gene expression profiling under low Pi and drought conditions demonstrated differential expression of 22 AsPHT genes in roots and leaves at the seedling stage, with distinct responses to the two stresses, highlighting the functional diversity of the AsPHT gene family. These findings provide valuable insights into the molecular mechanisms underlying Pi and water acquisition in oats and offer potential applications for developing varieties with enhanced Pi use efficiency and drought tolerance.

Enhancing drought resilience in durum wheat: effect of root architecture and genotypic performance in semi-arid rainfed regions

Background

Developing drought-adapted genotypes is a primary goal for achieving resilient agriculture in the Mediterranean region. Durum wheat, a widely grown crop in the drylands of the Mediterranean basin, would significantly benefit from increased drought resistance.

Methods

We investigated a diverse set of 30 durum wheat varieties, including both local landraces and modern cultivars that have proven successful in Algeria. These varieties were evaluated in field trials over two consecutive years with contrasting rainfall patterns (one very dry, the other quite wet). Grain yield (PGY), yield components, and flag leaf characteristics such as area, canopy temperature, or rolling index were evaluated. Data from previous studies of root traits recorded on the same set of genotypes at seedling and adult growth stages were used to search for possible associations with grain yield and other agronomic traits measured in the current work.

Results

Genotypic variation was found for all traits measured under both conditions. Grain yield and aerial biomass were reduced by 76% (from 5.28 to 1.97 Mg ha-1) and 66% (from 15.94 to 3.80 Mg ha-1), respectively in the dry year, whereas the harvest index increased by 32%. The breeding history of the germplasm (cultivar vs. landrace) had a significant effect on the traits studied. Landraces showed higher biomass only under drought (4.27 vs. 3.63 Mg ha-1), whereas modern cultivars out-yielded landraces only under non-drought conditions (5.56 vs. 4.49 Mg ha-1). Promising associations were found between root and agronomic traits, especially with grain yield, indicating that a profuse (large root length) and shallow (wide root angle) root system was related to increased yield of modern cultivars only in the dry year, without penalizing yield in the wet year.

Conclusion

Breeding programs could improve grain yield under Algerian, semi-arid conditions, by making crosses between selected landraces with good growth potential under drought and modern cultivars, with high efficiency of biomass conversion into grain, and searching for lines with acceptable agronomic performance, which combine these desirable traits from landraces and modern cultivars, with the presence of shallow and profuse root systems.

Distinct water and phosphorus extraction patterns are key to maintaining the productivity of sorghum under drought and limited soil resources

Nutrient and water limitations contribute to yield losses in semi-arid regions. Therefore, crop rotations incorporating nitrogen-fixing legumes and drought-tolerant sorghum varieties offer a strategy to improve the utilization of scarce soil resources. Under semi-arid, field-like conditions, sorghum crop rotations with either cowpea pre-crop or fallow, including two early and three late maturing genotypes, were tested to identify stress adaptation traits of sorghum to water and phosphorus limitations. Morphological and physiological parameters were evaluated on a single-plant basis. Lower soil P content significantly delayed flowering compared to higher P levels. However, improved P availability arising from pre-crop residues reduced this effect. Mycorrhizal infection rates and root-to-shoot ratios were positively correlated with panicle N and P content at anthesis under low P conditions. Although drought significantly impacted yield, early maturing genotypes with the highest reduction in shoot biomass and reduced water use before flowering, could sustain yield production. Early-maturing genotypes characterized by high root-to-shoot ratios, rapid AMF establishment, and reduced water use before flowering exhibit a strong potential for maintaining yield and biomass production on nutrient-poor soils in semi-arid regions. Such genotypes conserve water before flowering and thus can alleviate post-flowering water stress, ensuring adequate P uptake despite low soil P availability.

Multiscale Mathematical Modeling in Systems Biology: A Framework to Boost Plant Synthetic Biology

Global food insecurity and environmental degradation highlight the urgent need for more sustainable agricultural solutions. Plant synthetic biology emerges as a promising yet risky avenue to develop such solutions. While synthetic biology offers the potential for enhanced crop traits, it also entails risks of extensive environmental damage. This review highlights the complexities and risks associated with plant synthetic biology, while presenting the potential of multiscale mathematical modeling to assess and mitigate those risks effectively. Despite its potential, applying multiscale mathematical models in plants remains underutilized. Here, we advocate for integrating technological advancements in agricultural data analysis to develop a comprehensive understanding of crops across biological scales. By reviewing common modeling approaches and methodologies applicable to plants, the paper establishes a foundation for creating and utilizing integrated multiscale mathematical models. Through modeling techniques such as parameter estimation, bifurcation analysis, and sensitivity analysis, researchers can identify mutational targets and anticipate pleiotropic effects, thereby enhancing the safety of genetically engineered species. To demonstrate the potential of this approach, ongoing efforts are highlighted to develop an integrated multiscale mathematical model for maize (Zea mays L.), engineered through synthetic biology to enhance resilience against Striga (Striga spp.) and drought.

The value of early root development traits in breeding programs for biomass yield in perennial ryegrass (Lolium perenne L.)

KEY MESSAGE

Early root traits, particularly total root length, are heritable and show positive genetic correlations with biomass yield in perennial ryegrass; incorporating them into breeding programs can enhance genetic gain. Perennial ryegrass (Lolium perenne L.) is an important forage grass widely used in pastures and lawns, valued for its high nutritive value and environmental benefits. Despite its importance, genetic improvements in biomass yield have been slow, mainly due to its outbreeding nature and the challenges of improving multiple traits simultaneously. This study aims to assess the potential advantages of including early root traits in the perennial ryegrass breeding process. Root traits, including total root length (TRL) and root angle (RA) were phenotyped in a greenhouse using rhizoboxes, and genetic correlations with field yield were estimated across three European locations over two years. Bivariate models estimated significant genetic correlations of 0.40 (SE = 0.14) between TRL and field yield, and a weak but positive correlation to RA of 0.15 (SE = 0.14). Heritability estimates were 0.36 for TRL, 0.39 for RA, and 0.31 for field yield across locations. Incorporating root trait data into selection criteria can improve the efficiency of breeding programs, potentially increasing genetic gain by approximately 10%. This results highlight the potential of early root traits to refine selection criteria in perennial ryegrass breeding programs, contributing to higher yield and efficiency.

A Field-to-Parameter Pipeline for Analyzing and Simulating Root System Architecture of Woody Perennials: Application to Grapevine Rootstocks

Understanding root system architecture (RSA) is essential for improving crop resilience to climate change, yet assessing root systems of woody perennials under field conditions remains a challenge. This study introduces a pipeline that combines field excavation, in situ 3-dimensional digitization, and transformation of RSA data into an interoperable format to analyze and model the growth and water uptake of grapevine rootstock genotypes. Eight root systems of each of 3 grapevine rootstock genotypes ("101-14", "SO4", and "Richter 110") were excavated and digitized 3 and 6 months after planting. We validated the precision of the digitization method, compared in situ and ex situ digitization, and assessed root loss during excavation. The digitized RSA data were converted to root system markup language (RSML) format and imported into the CPlantBox modeling framework, which we adapted to include a static initial root system and a probabilistic tropism function. We then parameterized it to simulate genotype-specific growth patterns of grapevine rootstocks and integrated root hydraulic properties to derive a standard uptake fraction (SUF) for each genotype. Results demonstrated that excavation and in situ digitization accurately reflected the spatial structure of root systems, despite some underestimation of fine root length. Our experiment revealed significant genotypic variations in RSA over time and provided new insights into genotype-specific water acquisition capabilities. Simulated RSA closely resembled the specific features of the field-grown and digitized root systems. This study provides a foundational methodology for future research aimed at utilizing RSA models to improve the sustainability and productivity of woody perennials under changing climatic conditions.

Desert-adapted plant growth-promoting pseudomonads modulate plant auxin homeostasis and mitigate salinity stress

By providing adaptive advantages to plants, desert microorganisms are emerging as promising solutions to mitigate the negative and abrupt effects of climate change in agriculture. Among these, pseudomonads, commonly found in soil and in association with plants' root system, have been shown to enhance plant tolerance to salinity and drought, primarily affecting root system architecture in various hosts. However, a comprehensive understanding of how these bacteria affect plant responses at the cellular, physiological and molecular levels is still lacking. In this study, we investigated the effects of two Pseudomonas spp. strains, E102 and E141, which were previously isolated from date palm roots and have demonstrated efficacy in promoting drought tolerance in their hosts. These strains colonize plant roots, influencing root architecture by inhibiting primary root growth while promoting root hair elongation and lateral root formation. Strains E102 and E141 increased auxin levels in Arabidopsis, whereas this effect was diminished in IAA-defective mutant strains, which exhibited reduced IAA production. In all cases, the effectiveness of the bacteria relies on the functioning of the plant auxin response and transport machinery. Notably, such physiological and morphological changes provide an adaptive advantage to the plant, specifically under stress conditions such as salinity. Collectively, this study demonstrates that by leveraging the host's auxin signalling machinery, strains E102 and E141 significantly improve plant resilience to abiotic stresses, positioning them as potential biopromoters/bioprotectors for crop production and ecosystem restoration in alignment with Nature-based Solution approaches.

Cytokinins regulate spatially specific ethylene production to control root growth in Arabidopsis

Two principal growth regulators, cytokinins and ethylene, are known to interact in the regulation of plant growth. However, information about the underlying molecular mechanism and positional specificity of cytokinin/ethylene crosstalk in the control of root growth is scarce. We have identified the spatial specificity of cytokinin-regulated root elongation and root apical meristem (RAM) size, both of which we demonstrate to be dependent on ethylene biosynthesis. Upregulation of the cytokinin biosynthetic gene ISOPENTENYLTRANSFERASE (IPT) in proximal and peripheral tissues leads to both root and RAM shortening. By contrast, IPT activation in distal and inner tissues reduces RAM size while leaving the root length comparable to that of mock-treated controls. We show that cytokinins regulate two steps specific to ethylene biosynthesis: production of the ethylene precursor 1-aminocyclopropane-1-carboxylate (ACC) by ACC SYNTHASEs (ACSs) and its conversion to ethylene by ACC OXIDASEs (ACOs). We describe cytokinin- and ethylene-specific regulation controlling the activity of ACSs and ACOs that are spatially discrete along both proximo/distal and radial root axes. Using direct ethylene measurements, we identify ACO2, ACO3, and ACO4 as being responsible for ethylene biosynthesis and ethylene-regulated root and RAM shortening in cytokinin-treated Arabidopsis. Direct interaction between ARABIDOPSIS RESPONSE REGULATOR 2 (ARR2), a member of the multistep phosphorelay cascade, and the C-terminal portion of ETHYLENE INSENSITIVE 2 (EIN2-C), a key regulator of canonical ethylene signaling, is involved in the cytokinin-induced, ethylene-mediated control of ACO4. We propose tight cooperation between cytokinin and ethylene signaling in the spatially specific regulation of ethylene biosynthesis as a key aspect of the hormonal control of root growth.

Advancing hyperspectral imaging techniques for root systems: a new pipeline for macro- and microscale image acquisition and classification

BACKGROUND

Understanding the environmental impacts on root growth and root health is essential for effective agricultural and environmental management. Hyperspectral imaging (HSI) technology provides a non-destructive method for detailed analysis and monitoring of plant tissues and organ development, but unfortunately examples for its application to root systems and the root-soil interface are very scarce. There is also a notable lack of standardized guidelines for image acquisition and data analysis pipelines.

METHODS

This study investigated HSI techniques for analyzing rhizobox-grown root systems across various imaging configurations, from the macro- to micro-scale, using the imec VNIR SNAPSCAN camera. Focusing on three graminoid species with different root architectures allowed us to evaluate the influence of key image acquisition parameters and data processing techniques on the differentiation of root, soil, and root-soil interface/rhizosheath spectral signatures. We compared two image classification methods, Spectral Angle Mapper (SAM) and K-Means clustering, and two machine learning approaches, Random Forest (RF) and Support Vector Machine (SVM), to assess their efficiency in automating root system image classification.

RESULTS

Our study demonstrated that training a RF model using SAM classifications, coupled with wavelength reduction using the second derivative spectra with Savitzky-Golay (SG) smoothing, provided reliable classification between root, soil, and the root-soil interface, achieving 88-91% accuracy across all configurations and scales. Although the root-soil interface was not clearly resolved, it helped to improve the distinction between root and soil classes. This approach effectively highlighted spectral differences resulting from the different configurations, image acquisition settings, and among the three species. Utilizing this classification method can facilitate the monitoring of root biomass and future work investigating root adaptations to harsh environmental conditions.

CONCLUSIONS

Our study addressed the key challenges in HSI acquisition and data processing for root system analysis and lays the groundwork for further exploration of VNIR HSI application across various scales of root system studies. This work provides a full data analysis pipeline that can be utilized as an online Python-based tool for the semi-automated analysis of root-soil HSI data.

GA-sensitive Rht13 gene improves root architecture and osmotic stress tolerance in bread wheat

The root architecture, more seminal roots, and Deeper roots help the plants to uptake the resources from the deeper soil layer to ensure better growth. The Gibberellic acid-sensitive (GA-sensitive) Rht genes are well known for increasing drought tolerance in wheat. Much work has been performed on the effect of these genes on the plant agronomic traits and little work has been done on the effect of Rht genes on seminal roots and root architecture. This study was designed to evaluate 200 wheat genotypes under normal and osmotic stress. The genotypes were sown in the solution culture and laid under CRD factorial arrangement with three replications and two factors i.e., genotypes and treatments viz. normal and osmotic stress (20% PEG-6000) applied one week after germination. The data was recorded for the root traits. Results demonstrated that out of 200 genotypes, the GA-sensitive Rht13 gene was amplified in 21 genotypes with a fragment length of 1089 bp. In comparison, the GA-insensitive Rht1 gene was amplified in 24 genotypes with a band size of 228 bp. From 200 wheat genotypes, 122 genotypes produced 5 seminal roots, 4 genotypes 4 seminal roots, and 74 genotypes 3 seminal roots. The genotypes G-3 (EBW11TALL#1/WESTONIA-Rht5//QUAIU#1), G-6 (EBW01TALL#1/SILVERSTAR-Rht13B//ROLF07) and G-8 (EBW01TALL#1/SILVERSTAR-Rht13B//NAVJ07) produced 5 seminal roots and have longer coleoptile (> 4.0 cm), root (> 11.0 cm) and shoot (> 17 cm) under normal and osmotic stress. Furthermore, Ujala 16, Galaxy-13, and Fareed-06 produced 3 seminal roots and have short coleoptile (< 3 cm), root (< 9.0 cm) and shoot (< 10.0 cm). These results showed that the genotypes showing the presence of GA-sensitive Rht genes produced a greater number of seminal roots, increased root/shoot growth, and osmotic stress tolerance compared to the genotypes having GA-insensitive Rht genes. Thus, the Rht13 gene improved the root architecture which will help to uptake the nutrients from deeper soil layers. Utilization of Rht13 in wheat breeding has the potential to improve osmotic stress tolerance in wheat.

Genome-Wide Association study for root system architecture traits in field soybean [Glycine max (L.) Merr.]

Roots play a crucial role in plant development, serving to absorb water and nutrients from the soil while also providing structural stability. However, the impacts of global warming can impede root growth by altering soil conditions that hinder overall plant growth. To address this challenge, there is a need to screen and identify plant genotypes with superior Root System Architecture traits (RSA), that can be used for future breeding efforts in enhancing their resilience to these environmental changes. In this project, 500 mid to late-maturity soybean accessions were grown on blue blotting papers hydroponically with six replicates and assessed seven RSA traits. Genome-Wide Association Studies (GWAS) were carried out with root phenotypic data and SNP data from the SoySNP50K iSelect SNP BeadChip, using both the TASSEL 5.0 and FarmCPU techniques. A total of 26 significant SNP-trait correlations were discovered, with 11 SNPs on chromosome 13. After SNP selection, we identified 14 candidate genes within 100-kb regions flanking the SNPs, which are related to root architecture. Notably, Glyma.17G258700, which exhibited substantial differential expression in root tips and its Arabidopsis homolog, AT4G24190 (GRP94) is involved in the regulation of meristem size and organization. Other candidate genes includes Glyma.03G023000 and Glyma.13G273500 that are also play a key role in lateral root initiation and root meristem growth, respectively. These findings significantly contribute to the discovery of key genes associated with root system architecture, facilitating the breeding of resilient cultivars adaptable to changing climates.

Root Cortical Senescence Enhances Drought Tolerance in Cotton

The root cortical senescence (RCS) is closely associated with root absorptive function. However, characteristics and responses of RCS to drought stress in cotton have received little attention. This study subjected the drought-tolerant variety 'Guoxin 02' and the drought-sensitive variety 'Ji 228' to drought stress (8% PEG6000) and no-stress (0% PEG6000) treatments to determine the characteristics and responses of cotton RCS to drought stress. The results showed that the greater the distance from the root tip, the more severe the RCS occurrence under drought stress compared with non-stress treatment. The occurrence of RCS in 'Guoxin 02' increased by 14.03%-20.18% compared to 'Ji 228' under drought stress. The RCS was negatively correlated with root respiration but positively correlated with root length and leaf water potential. The silencing of RCS-related genes (GhSAG12 and GhbHLH121) can mitigate the drought-induced RCS phenomenon in cotton; however, reduced drought tolerance. Exogenous abscisic acid (ABA) treatment can promote RCS generation. Conversely, ABA synthesis exhibits contrasting effects. In summary, endogenous hormones regulated RCS, which reduced the root metabolic and seemingly achieved more resource redistribution to new roots, thereby fully utilize deep water resources. Thus, the study demonstrates the potential of RCS in improving the drought stress tolerance of cotton.

From leaf to multiscale models of photosynthesis: applications and challenges for crop improvement

To keep up with the growth of human population and to circumvent deleterious effects of global climate change, it is essential to enhance crop yield to achieve higher production. Here we review mathematical models of oxygenic photosynthesis that are extensively used, and discuss in depth a subset that accounts for diverse approaches providing solutions to our objective. These include models (1) to study different ways to enhance photosynthesis, such as fine-tuning antenna size, photoprotection and electron transport; (2) to bioengineer carbon metabolism; and (3) to evaluate the interactions between the process of photosynthesis and the seasonal crop dynamics, or those that have included statistical whole-genome prediction methods to quantify the impact of photosynthesis traits on the improvement of crop yield. We conclude by emphasizing that the results obtained in these studies clearly demonstrate that mathematical modelling is a key tool to examine different approaches to improve photosynthesis for better productivity, while effective multiscale crop models, especially those that also include remote sensing data, are indispensable to verify different strategies to obtain maximized crop yields.

An advanced three-dimensional phenotypic measurement approach for extracting Ginkgo root structural parameters based on terrestrial laser scanning

The phenotyping of plant roots is essential for improving plant productivity and adaptation. However, traditional techniques for assembling root phenotyping information are limited and often labor-intensive, especially for woody plants. In this study, an advanced approach called accurate and detailed quantitative structure model-based (AdQSM-based) root phenotypic measurement (ARPM) was developed to automatically extract phenotypes from Ginkgo tree root systems. The approach involves three-dimensional (3D) reconstruction of the point cloud obtained from terrestrial laser scanning (TLS) to extract key phenotypic parameters, including root diameter (RD), length, surface area, and volume. To evaluate the proposed method, two approaches [minimum spanning tree (MST)-based and triangulated irregular network (TIN)-based] were used to reconstruct the Ginkgo root systems from point clouds, and the number of lateral roots along with RD were extracted and compared with traditional methods. The results indicated that the RD extracted directly from point clouds [coefficient of determination (R 2) = 0.99, root-mean-square error (RMSE) = 0.41 cm] outperformed the results of 3D models (MST-based: R 2 = 0.71, RMSE = 2.20 cm; TIN-based: R 2 = 0.54, RMSE = 2.80 cm). Additionally, the MST-based model (F1 = 0.81) outperformed the TIN-based model (F1 = 0.80) in detecting the number of first-order and second-order lateral roots. Each phenotyping trait fluctuated with a different cloud parameter (CP), and the CP value of 0.002 (r = 0.94, p < 0.01) was found to be advantageous for better extraction of structural phenotypes. This study has helped with the extraction and quantitative analysis of root phenotypes and enhanced our understanding of the relationship between architectural parameters and corresponding physiological functions of tree roots.

Protein research in millets: current status and way forward

MAIN CONCLUSION

Millets' protein studies are lagging behind those of major cereals. Current status and future insights into the investigation of millet proteins are discussed. Millets are important small-seeded cereals majorly grown and consumed by people in Asia and Africa and are considered crops of future food security. Although millets possess excellent climate resilience and nutrient supplementation properties, their research advancements have been lagging behind major cereals. Although considerable genomic resources have been developed in recent years, research on millet proteins and proteomes is currently limited, highlighting a need for further investigation in this area. This review provides the current status of protein research in millets and provides insights to understand protein responses for climate resilience and nutrient supplementation in millets. The reference proteome data is available for sorghum, foxtail millet, and proso millet to date; other millets, such as pearl millet, finger millet, barnyard millet, kodo millet, tef, and browntop millet, do not have any reference proteome data. Many studies were reported on stress-responsive protein identification in foxtail millet, with most studies on the identification of proteins under drought-stress conditions. Pearl millet has a few reports on protein identification under drought and saline stress. Finger millet is the only other millet to have a report on stress-responsive (drought) protein identification in the leaf. For protein localization studies, foxtail millet has a few reports. Sorghum has the highest number of 40 experimentally proven crystal structures, and other millets have fewer or no experimentally proven structures. Further proteomics studies will help dissect the specific proteins involved in climate resilience and nutrient supplementation and aid in breeding better crops to conserve food security.

Genome-wide association studies of root system architecture traits in a broad collection of Brassica genotypes

The root systems of Brassica species are complex. Eight root system architecture (RSA) traits, including total root length, total root surface area, root average diameter, number of tips, total primary root length, total lateral root length, total tertiary root length, and basal link length, were phenotyped across 379 accessions representing six Brassica species (B. napus, B. juncea, B. carinata, B. oleracea, B. nigra, and B. rapa) using a semi-hydroponic system and image analysis software. The results suggest that, among the assessed species, B. napus and B. oleracea had the most intricate and largest root systems, while B. nigra exhibited the smallest roots. The two species B. juncea and B. carinata shared comparable root system complexity and had root systems with larger root diameters. In addition, 313 of the Brassica accessions were genotyped using a 19K Brassica single nucleotide polymorphism (SNP) array. After filtering by TASSEL 5.0, 6,213 SNP markers, comprising 5,103 markers on the A-genome (covering 302,504 kb) and 1,110 markers on the C-genome (covering 452,764 kb), were selected for genome-wide association studies (GWAS). Two general linear models were tested to identify the genomic regions and SNPs associated with the RSA traits. GWAS identified 79 significant SNP markers associated with the eight RSA traits investigated. These markers were distributed across the 18 chromosomes of B. napus, except for chromosome C06. Sixty-five markers were located on the A-genome, and 14 on the C-genome. Furthermore, the major marker-trait associations (MTAs)/quantitative trait loci (QTLs) associated with root traits were located on chromosomes A02, A03, and A06. Brassica accessions with distinct RSA traits were identified, which could hold functional, adaptive, evolutionary, environmental, pathological, and breeding significance.

Plant root mechanisms and their effects on carbon and nutrient accumulation in desert ecosystems under changes in land use and climate

Deserts represent key carbon reservoirs, yet as these systems are threatened this has implications for biodiversity and climate change. This review focuses on how these changes affect desert ecosystems, particularly plant root systems and their impact on carbon and mineral nutrient stocks. Desert plants have diverse root architectures shaped by water acquisition strategies, affecting plant biomass and overall carbon and nutrient stocks. Climate change can disrupt desert plant communities, with droughts impacting both shallow and deep-rooted plants as groundwater levels fluctuate. Vegetation management practices, like grazing, significantly influence plant communities, soil composition, root microorganisms, biomass, and nutrient stocks. Shallow-rooted plants are particularly susceptible to climate change and human interference. To safeguard desert ecosystems, understanding root architecture and deep soil layers is crucial. Implementing strategic management practices such as reducing grazing pressure, maintaining moderate harvesting levels, and adopting moderate fertilization can help preserve plant-soil systems. Employing socio-ecological approaches for community restoration enhances carbon and nutrient retention, limits desert expansion, and reduces CO2 emissions. This review underscores the importance of investigating belowground plant processes and their role in shaping desert landscapes, emphasizing the urgent need for a comprehensive understanding of desert ecosystems.

The State of the Art in Root System Architecture Image Analysis Using Artificial Intelligence: A Review

Roots are essential for acquiring water and nutrients to sustain and support plant growth and anchorage. However, they have been studied less than the aboveground traits in phenotyping and plant breeding until recent decades. In modern times, root properties such as morphology and root system architecture (RSA) have been recognized as increasingly important traits for creating more and higher quality food in the "Second Green Revolution". To address the paucity in RSA and other root research, new technologies are being investigated to fill the increasing demand to improve plants via root traits and overcome currently stagnated genetic progress in stable yields. Artificial intelligence (AI) is now a cutting-edge technology proving to be highly successful in many applications, such as crop science and genetic research to improve crop traits. A burgeoning field in crop science is the application of AI to high-resolution imagery in analyses that aim to answer questions related to crops and to better and more speedily breed desired plant traits such as RSA into new cultivars. This review is a synopsis concerning the origins, applications, challenges, and future directions of RSA research regarding image analyses using AI.

Evaluation of drought-tolerant varieties based on root system architecture in cotton (Gossypium hirsutum L.)

BACKGROUND

Root system architecture (RSA) exhibits significant genetic variability and is closely associated with drought tolerance. However, the evaluation of drought-tolerant cotton cultivars based on RSA in the field conditions is still underexplored.

RESULTS

So, this study conducted a comprehensive analysis of drought tolerance based on physiological and morphological traits (i.e., aboveground and RSA, and yield) within a rain-out shelter, with two water treatments: well-watered (75 ± 5% soil relative water content) and drought stress (50 ± 5% soil relative water content). The results showed that principal component analysis identified six principal components, including highlighting the importance of root traits and canopy parameters in influencing drought tolerance. Moreover, the systematic cluster analysis was used to classify 80 cultivars into 5 categories, including drought-tolerant cultivars, relatively drought-tolerant cultivars, intermediate cultivars, relatively drought-sensitive cultivars, and drought-sensitive cultivars. Further validation of the drought tolerance index showed that the yield drought tolerance index and biomass drought tolerance index of the drought-tolerant cultivars were 8.97 and 5.05 times higher than those of the drought-sensitive cultivars, respectively.

CONCLUSIONS

The RSA of drought-tolerant cultivars was characterised by a significant increase in average length-all lateral roots, a significant decrease in average lateral root emergence angle and a moderate root/shoot ratio. In contrast, the drought-sensitive cultivars showed a significant decrease in average length-all lateral roots and a significant increase in both average lateral root emergence angle and root/shoot ratio. It is therefore more comprehensive and accurate to assess field crop drought tolerance by considering root performance.

The crucial role of lateral root angle in enhancing drought resilience in cotton

Introduction

Plant responses to drought stress are influenced by various factors, including the lateral root angle (LRA), stomatal regulation, canopy temperature, transpiration rate and yield. However, there is a lack of research that quantifies their interactions, especially among different cotton varieties.

Methods

This experiment included two water treatments: well-watered (75 ± 5% soil relative water content) and drought stress (50 ± 5% soil relative water content) starting from the three-leaf growth stage.

Results

The results revealed that different LRA varieties show genetic variation under drought stress. Among them, varieties with smaller root angles show greater drought tolerance. Varieties with smaller LRAs had significantly increased stomatal opening by 15% to 43%, transpiration rate by 61.24% and 62.00%, aboveground biomass by 54% to 64%, and increased seed cotton yield by 76% to 79%, and decreased canopy temperature by 9% to 12% under drought stress compared to the larger LRAs. Varieties with smaller LRAs had less yield loss under drought stress, which may be due to enhanced access to deeper soil water, compensating for heightened stomatal opening and elevated transpiration rates. The increase in transpiration rate promotes heat dissipation from leaves, thereby reducing leaf temperature and protecting leaves from damage.

Discussion

Demonstrating the advantages conferred by the development of a smaller LRA under drought stress conditions holds value in enhancing cotton's resilience and promoting its sustainable adaptation to abiotic stressors.

Glutaredoxin regulation of primary root growth is associated with early drought stress tolerance in pearl millet

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.

Modeling the effects of strigolactone levels on maize root system architecture

Maize is the most in-demand staple crop globally. Its production relies strongly on the use of fertilizers for the supply of nitrogen, phosphorus, and potassium, which the plant absorbs through its roots, together with water. The architecture of maize roots is determinant in modulating how the plant interacts with the microbiome and extracts nutrients and water from the soil. As such, attempts to use synthetic biology and modulate that architecture to make the plant more resilient to drought and parasitic plants are underway. These attempts often try to modulate the biosynthesis of hormones that determine root architecture and growth. Experiments are laborious and time-consuming, creating the need for simulation platforms that can integrate metabolic models and 3D root growth models and predict the effects of synthetic biology interventions on both, hormone levels and root system architectures. Here, we present an example of such a platform that is built using Mathematica. First, we develop a root model, and use it to simulate the growth of many unique 3D maize root system architectures (RSAs). Then, we couple this model to a metabolic model that simulates the biosynthesis of strigolactones, hormones that modulate root growth and development. The coupling allows us to simulate the effect of changing strigolactone levels on the architecture of the roots. We then integrate the two models in a simulation platform, where we also add the functionality to analyze the effect of strigolactone levels on root phenotype. Finally, using in silico experiments, we show that our models can reproduce both the phenotype of wild type maize, and the effect that varying strigolactone levels have on changing the architecture of maize roots.

Root responses to abiotic stress: a comparative look at root system architecture in maize and sorghum

Under all environments, roots are important for plant anchorage and acquiring water and nutrients. However, there is a knowledge gap regarding how root architecture contributes to stress tolerance in a changing climate. Two closely related plant species, maize and sorghum, have distinct root system architectures and different levels of stress tolerance, making comparative analysis between these two species an ideal approach to resolve this knowledge gap. However, current research has focused on shared aspects of the root system that are advantageous under abiotic stress conditions rather than on differences. Here we summarize the current state of knowledge comparing the root system architecture relative to plant performance under water deficit, salt stress, and low phosphorus in maize and sorghum. Under water deficit, steeper root angles and deeper root systems are proposed to be advantageous for both species. In saline soils, a reduction in root length and root number has been described as advantageous, but this work is limited. Under low phosphorus, root systems that are shallow and wider are beneficial for topsoil foraging. Future work investigating the differences between these species will be critical for understanding the role of root system architecture in optimizing plant production for a changing global climate.

Outer apoplastic barriers in roots: prospects for abiotic stress tolerance

Floods and droughts are becoming more frequent as a result of climate change and it is imperative to find ways to enhance the resilience of staple crops to abiotic stresses. This is crucial to sustain food production during unfavourable conditions. Here, we analyse the current knowledge about suberised and lignified outer apoplastic barriers, focusing on the functional roles of the barrier to radial O2 loss formed as a response to soil flooding and we discuss whether this trait also provides resilience to multiple abiotic stresses. The barrier is composed of suberin and lignin depositions in the exodermal and/or sclerenchyma cell walls. In addition to the important role during soil flooding, the barrier can also restrict radial water loss, prevent phytotoxin intrusion, salt intrusion and the main components of the barrier can impede invasion of pathogens in the root. However, more research is needed to fully unravel the induction pathway of the outer apoplastic barriers and to address potential trade-offs such as reduced nutrient or water uptake. Nevertheless, we suggest that the outer apoplastic barriers might act as a jack of all trades providing tolerance to multiple abiotic and/or biotic stressors.

Plant Nutrition-New Methods Based on the Lessons of History: A Review

As with new technologies, plant nutrition has taken a big step forward in the last two decades. The main objective of this review is to briefly summarise the main pathways in modern plant nutrition and attract potential researchers and publishers to this area. First, this review highlights the importance of long-term field experiments, which provide us with valuable information about the effects of different applied strategies. The second part is dedicated to the new analytical technologies (tomography, spectrometry, and chromatography), intensively studied environments (rhizosphere, soil microbial communities, and enzymatic activity), nutrient relationship indexes, and the general importance of proper data evaluation. The third section is dedicated to the strategies of plant nutrition, i.e., (i) plant breeding, (ii) precision farming, (iii) fertiliser placement, (iv) biostimulants, (v) waste materials as a source of nutrients, and (vi) nanotechnologies. Finally, the increasing environmental risks related to plant nutrition, including biotic and abiotic stress, mainly the threat of soil salinity, are mentioned. In the 21st century, fertiliser application trends should be shifted to local application, precise farming, and nanotechnology; amended with ecofriendly organic fertilisers to ensure sustainable agricultural practices; and supported by new, highly effective crop varieties. To optimise agriculture, only the combination of the mentioned modern strategies supported by a proper analysis based on long-term observations seems to be a suitable pathway.

Integration of genome-wide association study, linkage analysis, and population transcriptome analysis to reveal the TaFMO1-5B modulating seminal root growth in bread wheat

Bread wheat, one of the keystone crops for global food security, is challenged by climate change and resource shortage. The root system plays a vital role in water and nutrient absorption, making it essential for meeting the growing global demand. Here, using an association-mapping population composed of 406 accessions, we identified QTrl.Rs-5B modulating seminal root development with a genome-wide association study and validated its genetic effects with two F5 segregation populations. Transcriptome-wide association study prioritized TaFMO1-5B, a gene encoding the flavin-containing monooxygenases, as the causal gene for QTrl.Rs-5B, whose expression levels correlate negatively with the phenotyping variations among our population. The lines silenced for TaFMO1-5B consistently showed significantly larger seminal roots in different genetic backgrounds. Additionally, the agriculture traits measured in multiple environments showed that QTrl.Rs-5B also affects yield component traits and plant architecture-related traits, and its favorable haplotype modulates these traits toward that of modern cultivars, suggesting the application potential of QTrl.Rs-5B for wheat breeding. Consistently, the frequency of the favorable haplotype of QTrl.Rs-5B increased with habitat expansion and breeding improvement of bread wheat. In conclusion, our findings identified and demonstrated the effects of QTrl.Rs-5B on seminal root development and illustrated that it is a valuable genetic locus for wheat root improvement.

Root phenotypes for improved nitrogen capture

Background

Suboptimal nitrogen availability is a primary constraint for crop production in low-input agroecosystems, while nitrogen fertilization is a primary contributor to the energy, economic, and environmental costs of crop production in high-input agroecosystems. In this article we consider avenues to develop crops with improved nitrogen capture and reduced requirement for nitrogen fertilizer.

Scope

Intraspecific variation for an array of root phenotypes has been associated with improved nitrogen capture in cereal crops, including architectural phenotypes that colocalize root foraging with nitrogen availability in the soil; anatomical phenotypes that reduce the metabolic costs of soil exploration, improve penetration of hard soil, and exploit the rhizosphere; subcellular phenotypes that reduce the nitrogen requirement of plant tissue; molecular phenotypes exhibiting optimized nitrate uptake kinetics; and rhizosphere phenotypes that optimize associations with the rhizosphere microbiome. For each of these topics we provide examples of root phenotypes which merit attention as potential selection targets for crop improvement. Several cross-cutting issues are addressed including the importance of soil hydrology and impedance, phenotypic plasticity, integrated phenotypes, in silico modeling, and breeding strategies using high throughput phenotyping for co-optimization of multiple phenes.

Conclusions

Substantial phenotypic variation exists in crop germplasm for an array of root phenotypes that improve nitrogen capture. Although this topic merits greater research attention than it currently receives, we have adequate understanding and tools to develop crops with improved nitrogen capture. Root phenotypes are underutilized yet attractive breeding targets for the development of the nitrogen efficient crops urgently needed in global agriculture.

Multi-year belowground data of minirhizotron facilities in Selhausen

The production of crops secure the human food supply, but climate change is bringing new challenges. Dynamic plant growth and corresponding environmental data are required to uncover phenotypic crop responses to the changing environment. There are many datasets on above-ground organs of crops, but roots and the surrounding soil are rarely the subject of longer term studies. Here, we present what we believe to be the first comprehensive collection of root and soil data, obtained at two minirhizotron facilities located close together that have the same local climate but differ in soil type. Both facilities have 7m-long horizontal tubes at several depths that were used for crosshole ground-penetrating radar and minirhizotron camera systems. Soil sensors provide observations at a high temporal and spatial resolution. The ongoing measurements cover five years of maize and wheat trials, including drought stress treatments and crop mixtures. We make the processed data available for use in investigating the processes within the soil-plant continuum and the root images to develop and compare image analysis methods.

Systems biology of root development in Populus: Review and perspectives

The root system of plants consists of primary, lateral, and adventitious roots (ARs) (aka shoot-born roots). ARs arise from stem- or leaf-derived cells during post-embryonic development. Adventitious root development (ARD) through stem cuttings is the first requirement for successful establishment and growth of planted trees; however, the details of the molecular mechanisms underlying ARD are poorly understood. This knowledge is important to both basic plant biology and because of its necessary role in the successful propagation of superior cultivars of commercial woody bioenergy crops, like poplar. In this review article, the molecular mechanisms that control both endogenous (auxin) and environmentally (nutrients and microbes) regulated ARD and how these systems interact to control the rooting efficiency of poplar trees are described. Then, potential future studies in employing integrated systems biology approaches at cellular resolutions are proposed to more precisely identify the molecular mechanisms that cause AR. Using genetic transformation and genome editing approaches, this information can be used for improving ARD in economically important plants for which clonal propagation is a requirement.

Application of an Improved 2-Dimensional High-Throughput Soybean Root Phenotyping Platform to Identify Novel Genetic Variants Regulating Root Architecture Traits

Nutrient-efficient root system architecture (RSA) is becoming an important breeding objective for generating crop varieties with improved nutrient and water acquisition efficiency. Genetic variants shaping soybean RSA is key in improving nutrient and water acquisition. Here, we report on the use of an improved 2-dimensional high-throughput root phenotyping platform that minimizes background noise by imaging pouch-grown root systems submerged in water. We also developed a background image cleaning Python pipeline that computationally removes images of small pieces of debris and filter paper fibers, which can be erroneously quantified as root tips. This platform was used to phenotype root traits in 286 soybean lines genotyped with 5.4 million single-nucleotide polymorphisms. There was a substantially higher correlation in manually counted number of root tips with computationally quantified root tips (95% correlation), when the background was cleaned of nonroot materials compared to root images without the background corrected (79%). Improvements in our RSA phenotyping pipeline significantly reduced overestimation of the root traits influenced by the number of root tips. Genome-wide association studies conducted on the root phenotypic data and quantitative gene expression analysis of candidate genes resulted in the identification of 3 putative positive regulators of root system depth, total root length and surface area, and root system volume and surface area of thicker roots (DOF1-like zinc finger transcription factor, protein of unknown function, and C2H2 zinc finger protein). We also identified a putative negative regulator (gibberellin 20 oxidase 3) of the total number of lateral roots.

Nitrogen transport and assimilation in tea plant (Camellia sinensis): a review

Nitrogen is one of the most important nutrients for tea plants, as it contributes significantly to tea yield and serves as the component of amino acids, which in turn affects the quality of tea produced. To achieve higher yields, excessive amounts of N fertilizers mainly in the form of urea have been applied in tea plantations where N fertilizer is prone to convert to nitrate and be lost by leaching in the acid soils. This usually results in elevated costs and environmental pollution. A comprehensive understanding of N metabolism in tea plants and the underlying mechanisms is necessary to identify the key regulators, characterize the functional phenotypes, and finally improve nitrogen use efficiency (NUE). Tea plants absorb and utilize ammonium as the preferred N source, thus a large amount of nitrate remains activated in soils. The improvement of nitrate utilization by tea plants is going to be an alternative aspect for NUE with great potentiality. In the process of N assimilation, nitrate is reduced to ammonium and subsequently derived to the GS-GOGAT pathway, involving the participation of nitrate reductase (NR), nitrite reductase (NiR), glutamine synthetase (GS), glutamate synthase (GOGAT), and glutamate dehydrogenase (GDH). Additionally, theanine, a unique amino acid responsible for umami taste, is biosynthesized by the catalysis of theanine synthetase (TS). In this review, we summarize what is known about the regulation and functioning of the enzymes and transporters implicated in N acquisition and metabolism in tea plants and the current methods for assessing NUE in this species. The challenges and prospects to expand our knowledge on N metabolism and related molecular mechanisms in tea plants which could be a model for woody perennial plant used for vegetative harvest are also discussed to provide the theoretical basis for future research to assess NUE traits more precisely among the vast germplasm resources, thus achieving NUE improvement.

Integrated use of polyphosphate and P-solubilizing bacteria enhanced P use efficiency and growth performance of durum wheat

Coupling phosphate-solubilizing bacteria (PSB) with P fertilizers, including polyphosphates (PolyP), was reported as eco-efficient approach to enhance P use efficiency. Although PSB have been recently reported to hydrolyze PolyP, the plant growth promoting mechanisms of PolyP-PSB co-application were not yet uncovered. This study aims to evaluate the effect of a PSB consortium (PSB_Cs) on growth, P use efficiency (PUE), and wheat yield parameters under PolyP (PolyB) application. Co-application of PolyB-PSB_Cs significantly enhanced wheat growth at 75 days after sowing (DAS) compared to 30 DAS. A significant increase in shoot dry biomass (47%), shoot inorganic P content (222%), PUE (91%), and root P absorption efficiency (RPAE, 99%) was noted compared to unfertilized plants. Similarly, the PolyB-PSB_Cs co-application enhanced morphological root traits at 30 DAS, while acid phosphatase activities (root and rhizosphere), RPAE, and PUE were significantly increased at 75 DAS. The improved wheat P acquisition could be attributed to a lower investment in root biomass production, and significant induction of acid phosphatase activity in roots and rhizosphere soil under PolyB-PSB_Cs co-application. Consequently, the PolyB-PSB_Cs co-application significantly improved aboveground performance, which is reflected by increased shoot nutrient contents (P 300%, K 65%), dry weight (54%), and number (50%) of spikes. Altogether, this study provides relevant evidence that co-application of PolyP-PSB_Cs can be an integrated and environmentally preferred P fertilization approach owing to the dual effects of PolyP and PSB_Cs on wheat PUE.

Mining genes regulating root system architecture in maize based on data integration analysis

KEY MESSAGE

A new strategy that integrated multiple public data resources was established to construct root gene co-expression network and mine genes regulating root system architecture in maize. A root gene co-expression network, containing 13,874 genes, was constructed. A total of 53 root hub genes and 16 priority root candidate genes were identified. One priority root candidate was further functionally verified using overexpression transgenic maize lines. Root system architecture (RSA) is crucial for crops productivity and stress tolerance. In maize, few RSA genes are functionally cloned, and effective discovery of RSA genes remains a great of challenge. In this work, we established a strategy to mine maize RSA genes by integrating functionally characterized root genes, root transcriptome, weighted gene co-expression network analysis (WGCNA) and genome-wide association analysis (GWAS) of RSA traits based on public data resources. A total of 589 maize root genes were collected by searching well-characterized root genes in maize or homologous genes of other species. We performed WGCNA to construct a maize root gene co-expression network containing 13874 genes based on public available root transcriptome data, and further discovered the 53 hub genes related to root traits. In addition, by the prediction function of obtained root gene co-expression network, a total of 1082 new root candidate genes were explored. By further overlapping the obtained new root candidate gene with the root-related GWAS of RSA candidate genes, 16 priority root candidate genes were identified. Finally, a priority root candidate gene, Zm00001d023379 (encodes pyruvate kinase 2), was validated to modulate root open angle and shoot-borne roots number using its overexpression transgenic lines. Our results develop an integration analysis method for effectively exploring regulatory genes of RSA in maize and open a new avenue to mine the candidate genes underlying complex traits.

Variation in the Root System Architecture of Peach × (Peach × Almond) Backcrosses

The spatial arrangement and growth pattern of root systems, defined by the root system architecture (RSA), influences plant productivity and adaptation to soil environments, playing an important role in sustainable horticulture. Florida's peach production area covers contrasting soil types, making it necessary to identify rootstocks that exhibit soil-type-specific advantageous root traits. In this sense, the wide genetic diversity of the Prunus genus allows the breeding of rootstock genotypes with contrasting root traits. The evaluation of root traits expressed in young seedlings and plantlets facilitates the early selection of desirable phenotypes in rootstock breeding. Plantlets from three peach × (peach × almond) backcross populations were vegetatively propagated and grown in rhizoboxes. These backcross populations were identified as BC1251, BC1256, and BC1260 and studied in a completely randomized design. Scanned images of the entire root systems of the plantlets were analyzed for total root length distribution by diameter classes, root dry weight by depth horizons, root morphological components, structural root parameters, and root spreading angles. The BC1260 progeny presented a shallower root system and lower root growth. Backcross BC1251 progeny exhibited a more vigorous and deeper root system at narrower root angles, potentially allowing it to explore and exploit water and nutrients in deep sandy entisols from the Florida central ridge.

Omics Approaches in Invasion Biology: Understanding Mechanisms and Impacts on Ecological Health

Invasive species and rapid climate change are affecting the control of new plant diseases and epidemics. To effectively manage these diseases under changing environmental conditions, a better understanding of pathophysiology with holistic approach is needed. Multiomics approaches can help us to understand the relationship between plants and microbes and construct predictive models for how they respond to environmental stresses. The application of omics methods enables the simultaneous analysis of plant hosts, soil, and microbiota, providing insights into their intricate relationships and the mechanisms underlying plant-microbe interactions. This can help in the development of novel strategies for enhancing plant health and improving soil ecosystem functions. The review proposes the use of omics methods to study the relationship between plant hosts, soil, and microbiota, with the aim of developing a new technique to regulate soil health. This approach can provide a comprehensive understanding of the mechanisms underlying plant-microbe interactions and contribute to the development of effective strategies for managing plant diseases and improving soil ecosystem functions. In conclusion, omics technologies offer an innovative and holistic approach to understanding plant-microbe interactions and their response to changing environmental conditions.

Chromosome groups 5, 6 and 7 harbor major quantitative trait loci controlling root traits in bread wheat (Triticum aestivum L.)

Identifying genomic regions for root traits in bread wheat can help breeders develop climate-resilient and high-yielding wheat varieties with desirable root traits. This study used the recombinant inbred line (RIL) population of Synthetic W7984 × Opata M85 to identify quantitative trait loci (QTL) for different root traits such as rooting depth (RD), root dry mass (RM), total root length (RL), root diameter (Rdia) and root surface areas (RSA1 for coarse roots and RSA2 for fine roots) under controlled conditions in a semi-hydroponic system. We detected 14 QTL for eight root traits on nine wheat chromosomes; we discovered three QTL each for RD and RSA1, two QTL each for RM and RSA2, and one QTL each for RL, Rdia, specific root length and nodal root number per plant. The detected QTL were concentrated on chromosome groups 5, 6 and 7. The QTL for shallow RD (Q.rd.uwa.7BL: Xbarc50) and high RM (Q.rm.uwa.6AS: Xgwm334) were validated in two independent F₂ populations of Synthetic W7984 × Chara and Opata M85 × Cascade, respectively. Genotypes containing negative alleles for Q.rd.uwa.7BL had 52% shallower RD than other Synthetic W7984 × Chara population lines. Genotypes with the positive alleles for Q.rm.uwa.6AS had 31.58% higher RM than other Opata M85 × Cascade population lines. Further, we identified 21 putative candidate genes for RD (Q.rd.uwa.7BL) and 13 for RM (Q.rm.uwa.6AS); TraesCS6A01G020400, TraesCS6A01G024400 and TraesCS6A01G021000 identified from Q.rm.uwa.6AS, and TraesCS7B01G404000, TraesCS7B01G254900 and TraesCS7B01G446200 identified from Q.rd.uwa.7BL encoded important proteins for root traits. We found germin-like protein encoding genes in both Q.rd.uwa.7BL and Q.rm.uwa.6AS regions. These genes may play an important role in RM and RD improvement. The identified QTL, especially the validated QTL and putative candidate genes are valuable genetic resources for future root trait improvement in wheat.

Plant root plasticity during drought and recovery: What do we know and where to go?

AIMS

Drought stress is one of the most limiting factors for agriculture and ecosystem productivity. Climate change exacerbates this threat by inducing increasingly intense and frequent drought events. Root plasticity during both drought and post-drought recovery is regarded as fundamental to understanding plant climate resilience and maximizing production. We mapped the different research areas and trends that focus on the role of roots in plant response to drought and rewatering and asked if important topics were overlooked.

METHODS

We performed a comprehensive bibliometric analysis based on journal articles indexed in the Web of Science platform from 1900-2022. We evaluated a) research areas and temporal evolution of keyword frequencies, b) temporal evolution and scientific mapping of the outputs over time, c) trends in the research topics analysis, d) marked journals and citation analysis, and e) competitive countries and dominant institutions to understand the temporal trends of root plasticity during both drought and recovery in the past 120 years.

RESULTS

Plant physiological factors, especially in the aboveground part (such as "photosynthesis", "gas-exchange", "abscisic-acid") in model plants Arabidopsis, crops such as wheat and maize, and trees were found to be the most popular study areas; they were also combined with other abiotic factors such as salinity, nitrogen, and climate change, while dynamic root growth and root system architecture responses received less attention. Co-occurrence network analysis showed that three clusters were classified for the keywords including 1) photosynthesis response; 2) physiological traits tolerance (e.g. abscisic acid); 3) root hydraulic transport. Thematically, themes evolved from classical agricultural and ecological research via molecular physiology to root plasticity during drought and recovery. The most productive (number of publications) and cited countries and institutions were situated on drylands in the USA, China, and Australia. In the past decades, scientists approached the topic mostly from a soil-plant hydraulic perspective and strongly focused on aboveground physiological regulation, whereas the actual belowground processes seemed to have been the elephant in the room. There is a strong need for better investigation into root and rhizosphere traits during drought and recovery using novel root phenotyping methods and mathematical modeling.

Negative effects of soil warming, and adaptive cultivation strategies of maize: A review

Temperature is a key factor in regulating and controlling several ecological processes. As there is a feedback relationship between many biogeochemical processes and climate change, their response to temperature changes is particularly important. Previously, a large volume of literature has extensively explored the impact of rising air temperature on shoot growth and maize yield, from enzymatic responses within the leaf to grain yield. As the global temperature continues to increase and the frequency, duration, and/or intensity of heat wave events increases, the soil temperature of the tilth is likely to rise sharply. As one of the most widely planted food crops in the world, maize may be subjected to additional soil temperature pressure. However, as a nutrient organ in direct contact with soil, the root plays a key role in adapting the whole plant to excessive soil temperature. Little research has been done on the effect of the soil microenvironment induced by higher soil temperature on maize root growth and root to shoot communication regulation. Therefore, this review summarizes (1) the effects of excessive soil temperature on the soil microenvironment, including soil respiration, microbial community composition, carbon mineralization, and enzyme activity; (2) the negative response of absorption of water and nutrients by roots and maize root-shoot growth to excessive soil temperature; and (3) potential cultivation strategies to improve maize yield, including improving tillage methods, adding biochar amendments, applying organic fertilizers, optimizing irrigation, and farmland mulching.

Genetic basis controlling rice plant architecture and its modification for breeding

The shoot and root system architectures are fundamental for crop productivity. During the history of artificial selection of domestication and post-domestication breeding, the architecture of rice has significantly changed from its wild ancestor to fulfil requirements in agriculture. We review the recent studies on developmental biology in rice by focusing on components determining rice plant architecture; shoot meristems, leaves, tillers, stems, inflorescences and roots. We also highlight natural variations that affected these structures and were utilized in cultivars. Importantly, many core regulators identified from developmental mutants have been utilized in breeding as weak alleles moderately affecting these architectures. Given a surge of functional genomics and genome editing, the genetic mechanisms underlying the rice plant architecture discussed here will provide a theoretical basis to push breeding further forward not only in rice but also in other crops and their wild relatives.

Spring Wheat's Ability to Utilize Nitrogen More Effectively Is Influenced by Root Phene Variation

Genetic improvement for nitrogen use efficiency (NUE) can play a very crucial role in sustainable agriculture. Root traits have hardly been explored in major wheat breeding programs, more so in spring germplasm, largely because of the difficulty in their scoring. A total of 175 advanced/improved Indian spring wheat genotypes were screened for root traits and nitrogen uptake and nitrogen utilization at varying nitrogen levels in hydroponic conditions to dissect the complex NUE trait into its component traits and to study the extent of variability that exists for those traits in Indian germplasm. Analysis of genetic variance showed a considerable amount of genetic variability for nitrogen uptake efficiency (NUpE), nitrogen utilization efficiency (NUtE), and most of the root and shoot traits. Improved spring wheat breeding lines were found to have very large variability for maximum root length (MRL) and root dry weights (RDW) with strong genetic advance. In contrast to high nitrogen (HN), a low nitrogen (LN) environment was more effective in differentiating wheat genotypes for NUE and its component traits. Shoot dry weight (SDW), RDW, MRL, and NUpE were found to have a strong association with NUE. Further study revealed the role of root surface area (RSA) and total root length (TRL) in RDW formation as well as in nitrogen uptake and therefore can be targeted for selection to further the genetic gain for grain yield under high input or sustainable agriculture under limited inputs.

Drought stress tolerance mechanisms and their potential common indicators to salinity, insights from the wild watermelon (Citrullus lanatus): A review

Climate change has escalated the effect of drought on crop production as it has negatively altered the environmental condition. Wild watermelon grows abundantly in the Kgalagadi desert even though the environment is characterized by minimal rainfall, high temperatures and intense sunshine during growing season. This area is also characterized by sandy soils with low water holding capacity, thus bringing about drought stress. Drought stress affects crop productivity through its effects on development and physiological functions as dictated by molecular responses. Not only one or two physiological process or genes are responsible for drought tolerance, but a combination of various factors do work together to aid crop tolerance mechanism. Various studies have shown that wild watermelon possess superior qualities that aid its survival in unfavorable conditions. These mechanisms include resilient root growth, timely stomatal closure, chlorophyll fluorescence quenching under water deficit as key physiological responses. At biochemical and molecular level, the crop responds through citrulline accumulation and expression of genes associated with drought tolerance in this species and other plants. Previous salinity stress studies involving other plants have identified citrulline accumulation and expression of some of these genes (chloroplast APX, Type-2 metallothionein), to be associated with tolerance. Emerging evidence indicates that the upstream of functional genes are the transcription factor that regulates drought and salinity stress responses as well as adaptation. In this review we discuss the drought tolerance mechanisms in watermelons and some of its common indicators to salinity at physiological, biochemical and molecular level.

Spatial and Texture Analysis of Root System distribution with Earth mover's Distance (STARSEED)

PURPOSE

Root system architectures are complex and challenging to characterize effectively for agronomic and ecological discovery.

METHODS

We propose a new method, Spatial and Texture Analysis of Root SystEm distribution with Earth mover's Distance (STARSEED), for comparing root system distributions that incorporates spatial information through a novel application of the Earth Mover's Distance (EMD).

RESULTS

We illustrate that the approach captures the response of sesame root systems for different genotypes and soil moisture levels. STARSEED provides quantitative and visual insights into changes that occur in root architectures across experimental treatments.

CONCLUSION

STARSEED can be generalized to other plants and provides insight into root system architecture development and response to varying growth conditions not captured by existing root architecture metrics and models. The code and data for our experiments are publicly available: https://github.com/GatorSense/STARSEED .

Genome-Wide Association Studies of Seven Root Traits in Soybean (Glycine max L.) Landraces

Soybean [Glycine max (L.) Merr.], an important oilseed crop, is a low-cost source of protein and oil. In Southeast Asia and Africa, soybeans are widely cultivated for use as traditional food and feed and industrial purposes. Given the ongoing changes in global climate, developing crops that are resistant to climatic extremes and produce viable yields under predicted climatic conditions will be essential in the coming decades. To develop such crops, it will be necessary to gain a thorough understanding of the genetic basis of agronomic and plant root traits. As plant roots generally lie beneath the soil surface, detailed observations and phenotyping throughout plant development present several challenges, and thus the associated traits have tended to be ignored in genomics studies. In this study, we phenotyped 357 soybean landraces at the early vegetative (V2) growth stages and used a 180 K single-nucleotide polymorphism (SNP) soybean array in a genome-wide association study (GWAS) conducted to determine the phenotypic relationships among root traits, elucidate the genetic bases, and identify significant SNPs associated with root trait-controlling genomic regions/loci. A total of 112 significant SNP loci/regions were detected for seven root traits, and we identified 55 putative candidate genes considered to be the most promising. Our findings in this study indicate that a combined approach based on SNP array and GWAS analyses can be applied to unravel the genetic basis of complex root traits in soybean, and may provide an alternative high-resolution marker strategy to traditional bi-parental mapping. In addition, the identified SNPs, candidate genes, and diverse variations in the root traits of soybean landraces will serve as a valuable basis for further application in genetic studies and the breeding of climate-resilient soybeans characterized by improved root traits.

Burning questions for a warming and changing world: 15 unknowns in plant abiotic stress

We present unresolved questions in plant abiotic stress biology as posed by 15 research groups with expertise spanning eco-physiology to cell and molecular biology. Common themes of these questions include the need to better understand how plants detect water availability, temperature, salinity, and rising carbon dioxide (CO2) levels; how environmental signals interface with endogenous signaling and development (e.g. circadian clock and flowering time); and how this integrated signaling controls downstream responses (e.g. stomatal regulation, proline metabolism, and growth versus defense balance). The plasma membrane comes up frequently as a site of key signaling and transport events (e.g. mechanosensing and lipid-derived signaling, aquaporins). Adaptation to water extremes and rising CO2 affects hydraulic architecture and transpiration, as well as root and shoot growth and morphology, in ways not fully understood. Environmental adaptation involves tradeoffs that limit ecological distribution and crop resilience in the face of changing and increasingly unpredictable environments. Exploration of plant diversity within and among species can help us know which of these tradeoffs represent fundamental limits and which ones can be circumvented by bringing new trait combinations together. Better defining what constitutes beneficial stress resistance in different contexts and making connections between genes and phenotypes, and between laboratory and field observations, are overarching challenges.

Root system architecture of historical spring wheat cultivars is associated with alleles and transcripts of major functional genes

We evaluated root system architecture (RSA) of a set of 58 historical spring wheat cultivars from Pakistan representing 105 years of selection breeding. The evaluations were carried out under control and water-limited conditions using a high-throughput phenotyping system coupled with RhizoVision Explorer software. The cultivars were classified into three groups based on release year as cultivars released pre-1965, released between 1965 and 2000, and cultivars released post-2000. Under water-limited conditions a decline in 20 out of 25 RSA component traits was observed in pre-1965 cultivars group. Whereas cultivars released after the 1965, so-called green revolution period, showed a decline in 17 traits with significant increments in root length, depth, and steep angle frequency which are important root traits for resource-uptake under water-limited conditions. Similarly, cultivars released after 2000 indicated an increase in the number of roots, depth, diameter, surface area, and steep angle frequency. The coefficient of correlation analysis showed a positive correlation between root depth and yield-related traits under water-limited conditions. We also investigated the effects of green-revolution genes (Rht1) and some phenology-related genes such as DRO1, TaMOR, TaLTPs, TaSus-2B on RSA and identified significant associations of these genes with important root traits. There was strong selection pressure on DRO1 gene in cultivated wheat indicating the allele fixed in modern wheat cultivars is different from landraces. The expression of DRO1, and TaMOR were retrieved from an RNAseq experiment, and results were validated using qRT-PCR. The highest expression of DRO1 and TaMOR was found in Chakwal-50, a rainfed cultivar released in 2008, and MaxiPak-65 released in 1965. We conclude that there is a positive historic change in RSA after 1965 that might be attributed to genetic factors associated with favored RSA traits. Furthermore, we suggest root depth and steep angle as promising traits to withstand water-limited environments and may have implications in selection for breeding.

Effects of irrigation on root growth and development of soybean: A 3-year sandy field experiment

Increasing the water use efficiency of crops is an important agricultural goal closely related to the root system -the primary plant organ for water and nutrient acquisition. In an attempt to evaluate the response of root growth and development of soybean to water supply levels, 200 genotypes were grown in a sandy field for 3 years under irrigated and non-irrigated conditions, and 14 root traits together with shoot fresh weight and plant height were investigated. Three-way ANOVA revealed a significant effect of treatments and years on growth of plants, accounting for more than 80% of the total variability. The response of roots to irrigation was consistent over the years as most root traits were improved by irrigation. However, the actual values varied between years because the growth of plants was largely affected by the field microclimatic conditions (i.e., temperature, sunshine duration, and precipitation). Therefore, the best linear unbiased prediction values for each trait were calculated using the original data. Principal component analysis showed that most traits contributed to principal component (PC) 1, whereas average diameter, the ratio of thin and medium thickness root length to total root length contributed to PC2. Subsequently, we focused on selecting genotypes that exhibited significant improvements in root traits under irrigation than under non-irrigated conditions using the increment (I-index) and relative increment (RI-index) indices calculated for all traits. Finally, we screened for genotypes with high stability and root growth over the 3 years using the multi-trait selection index (MTSI).Six genotypes namely, GmJMC130, GmWMC178, GmJMC092, GmJMC068, GmWMC075, and GmJMC081 from the top 10% of genotypes scoring MTSI less than the selection threshold of 7.04 and 4.11 under irrigated and non-irrigated conditions, respectively, were selected. The selected genotypes have great potential for breeding cultivars with improved water usage abilities, meeting the goal of water-saving agriculture.

Responses of root system architecture to water stress at multiple levels: A meta-analysis of trials under controlled conditions

Plants are exposed to increasingly severe drought events and roots play vital roles in maintaining plant survival, growth, and reproduction. A large body of literature has investigated the adaptive responses of root traits in various plants to water stress and these studies have been reviewed in certain groups of plant species at a certain scale. Nevertheless, these responses have not been synthesized at multiple levels. This paper screened over 2000 literatures for studies of typical root traits including root growth angle, root depth, root length, root diameter, root dry weight, root-to-shoot ratio, root hair length and density and integrates their drought responses at genetic and morphological scales. The genes, quantitative trait loci (QTLs) and hormones that are involved in the regulation of drought response of the root traits were summarized. We then statistically analyzed the drought responses of root traits and discussed the underlying mechanisms. Moreover, we highlighted the drought response of 1-D and 2-D root length density (RLD) distribution in the soil profile. This paper will provide a framework for an integrated understanding of root adaptive responses to water deficit at multiple scales and such insights may provide a basis for selection and breeding of drought tolerant crop lines.