RootNav: navigating images of complex root architectures

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.

An ecotype-specific effect of osmopriming and melatonin during salt stress in Arabidopsis thaliana

BACKGROUND

Natural populations of Arabidopsis thaliana exhibit phenotypic variations in specific environments and growth conditions. However, this variation has not been explored after seed osmopriming treatments. The natural variation in biomass production and root system architecture (RSA) was investigated across the Arabidopsis thaliana core collection in response to the pre-sawing seed treatments by osmopriming, with and without melatonin (Mel). The goal was to identify and characterize physiologically contrasting ecotypes.

RESULTS

Variability in RSA parameters in response to PEG-6000 seed osmopriming with and without Mel was observed across Arabidopsis thaliana ecotypes with especially positive impact of Mel addition under both control and 100 mM NaCl stress conditions. Two ecotypes, Can-0 and Kn-0, exhibited contrasted root phenotypes: seed osmopriming with and without Mel reduced the root growth of Can-0 plants while enhancing it in Kn-0 ones under both control and salt stress conditions. To understand the stress responses in these two ecotypes, main stress markers as well as physiological analyses were assessed in shoots and roots. Although the effect of Mel addition was evident in both ecotypes, its protective effect was more pronounced in Kn-0. Antioxidant enzymes were induced by osmopriming with Mel in both ecotypes, but Kn-0 was characterized by a higher responsiveness, especially in the activities of peroxidases in roots. Kn-0 plants experienced lower oxidative stress, and salt-induced ROS accumulation was reduced by osmopriming with Mel. In contrast, Can-0 exhibited lower enzyme activities but the accumulation of proline in its organs was particularly high. In both ecotypes, a greater response of antioxidant enzymes and proline accumulation was observed compared to mechanisms involving the reduction of Na+ content and prevention of K+ efflux.

CONCLUSIONS

In contrast to Can-0, Kn-0 plants grown from seeds osmoprimed with and without Mel displayed a lower root sensitivity to NaCl-induced oxidative stress. The opposite root growth patterns, enhanced by osmopriming treatments might result from different protective mechanisms employed by these two ecotypes which in turn result from adaptive strategies proper to specific habitats from which Can-0 and Kn-0 originate. The isolation of contrasting phenotypes paves the way for the identification of genetic factors affecting osmopriming efficiency.

Beneficial Effects of Phosphite in Arabidopsis thaliana Mediated by Activation of ABA, SA, and JA Biosynthesis and Signaling Pathways

Phosphite (Phi) has gained attention in agriculture due to its biostimulant effect on crops. This molecule has been found to benefit plant performance by providing protection against pathogens, improving yield and fruit quality as well as nutrient and water use efficiency. It is still unclear how Phi enhances plant growth and protects against multiple stresses. It has been hypothesized that Phi acts by directly affecting the pathogens and interacting with the plant cellular components and molecular machinery to elicit defense responses. This study elucidates the mechanisms underlying Phi's beneficial effects on plants, revealing their complex interplay with fundamental signaling pathways. An RNA-seq study of Arabidopsis seedlings under optimal and limiting phosphate conditions helped us unveil Phi's role in promoting plant growth by activating the expression of the genes involved in the biosynthesis and signaling pathways associated with abscisic acid (ABA), salicylic acid (SA), and jasmonic acid (JA). The expression of ABA-related genes, known for their involvement in stress response and development regulation, is triggered by Phi treatment, contributing to enhanced resilience and growth. Simultaneously, the activation of the SA pathway, associated with defense responses, suggests Phi's potential in bolstering plant immunity. Moreover, Phi influences JA biosynthesis and signaling, which are crucial for defense against herbivores and pathogens, thereby strengthening plants' defenses. Our findings reveal a multifaceted mechanism through which Phi benefits Arabidopsis development. Understanding its intricate interplay with key signaling pathways opens avenues for leveraging Phi as a strategic tool to enhance plant resilience, immunity, and growth in agricultural and ecological contexts.

Defying gravity: WEEP promotes negative gravitropism in peach trees by establishing asymmetric auxin gradients

Trees with weeping shoot architectures are valued for their beauty and are a resource for understanding how plants regulate posture control. The peach (Prunus persica) weeping phenotype, which has elliptical downward arching branches, is caused by a homozygous mutation in the WEEP gene. Little is known about the function of WEEP despite its high conservation throughout Plantae. Here, we present the results of anatomical, biochemical, biomechanical, physiological, and molecular experiments that provide insight into WEEP function. Our data suggest that weeping peach trees do not have defects in branch structure. Rather, transcriptomes from the adaxial (upper) and abaxial (lower) sides of standard and weeping branch shoot tips revealed flipped expression patterns for genes associated with early auxin response, tissue patterning, cell elongation, and tension wood development. This suggests that WEEP promotes polar auxin transport toward the lower side during shoot gravitropic response, leading to cell elongation and tension wood development. In addition, weeping peach trees exhibited steeper root systems and faster lateral root gravitropic response. This suggests that WEEP moderates root gravitropism and is essential to establishing the set-point angle of lateral roots from the gravity vector. Additionally, size exclusion chromatography indicated that WEEP proteins self-oligomerize, like other proteins with sterile alpha motif domains. Collectively, our results from weeping peach provide insight into polar auxin transport mechanisms associated with gravitropism and lateral shoot and root orientation.

Genetic control of root morphology in response to nitrogen across rapeseed diversity

Rapeseed (Brassica napus L.) is an oil-containing crop of great economic value but with considerable nitrogen requirement. Breeding root systems that efficiently absorb nitrogen from the soil could be a driver to ensure genetic gains for more sustainable rapeseed production. The aim of this study is to identify genomic regions that regulate root morphology in response to nitrate availability. The natural variability offered by 300 inbred lines was screened at two experimental locations. Seedlings grew hydroponically with low or elevated nitrate levels. Fifteen traits related to biomass production and root morphology were measured. On average across the panel, a low nitrate level increased the root-to-shoot biomass ratio and the lateral root length. A large phenotypic variation was observed, along with important heritability values and genotypic effects, but low genotype-by-nitrogen interactions. Genome-wide association study and bulk segregant analysis were used to identify loci regulating phenotypic traits. The first approach nominated 319 SNPs that were combined into 80 QTLs. Three QTLs identified on the A07 and C07 chromosomes were stable across nitrate levels and/or experimental locations. The second approach involved genotyping two groups of individuals from an experimental F2 population created by crossing two accessions with contrasting lateral root lengths. These individuals were found in the tails of the phenotypic distribution. Co-localized QTLs found in both mapping approaches covered a chromosomal region on the A06 chromosome. The QTL regions contained some genes putatively involved in root organogenesis and represent selection targets for redesigning the root morphology of rapeseed.

Improved Transformer for Time Series Senescence Root Recognition

The root is an important organ for plants to obtain nutrients and water, and its phenotypic characteristics are closely related to its functions. Deep-learning-based high-throughput in situ root senescence feature extraction has not yet been published. In light of this, this paper suggests a technique based on the transformer neural network for retrieving cotton's in situ root senescence properties. High-resolution in situ root pictures with various levels of senescence are the main subject of the investigation. By comparing the semantic segmentation of the root system by general convolutional neural networks and transformer neural networks, SegFormer-UN (large) achieves the optimal evaluation metrics with mIoU, mRecall, mPrecision, and mF1 metric values of 81.52%, 86.87%, 90.98%, and 88.81%, respectively. The segmentation results indicate more accurate predictions at the connections of root systems in the segmented images. In contrast to 2 algorithms for cotton root senescence extraction based on deep learning and image processing, the in situ root senescence recognition algorithm using the SegFormer-UN model has a parameter count of 5.81 million and operates at a fast speed, approximately 4 min per image. It can accurately identify senescence roots in the image. We propose that the SegFormer-UN model can rapidly and nondestructively identify senescence root in in situ root images, providing important methodological support for efficient crop senescence research.

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.

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.

Reproducible growth of Brachypodium in EcoFAB 2.0 reveals that nitrogen form and starvation modulate root exudation

Understanding plant-microbe interactions requires examination of root exudation under nutrient stress using standardized and reproducible experimental systems. We grew Brachypodium distachyon hydroponically in fabricated ecosystem devices (EcoFAB 2.0) under three inorganic nitrogen forms (nitrate, ammonium, and ammonium nitrate), followed by nitrogen starvation. Analyses of exudates with liquid chromatography-tandem mass spectrometry, biomass, medium pH, and nitrogen uptake showed EcoFAB 2.0's low intratreatment data variability. Furthermore, the three inorganic nitrogen forms caused differential exudation, generalized by abundant amino acids-peptides and alkaloids. Comparatively, nitrogen deficiency decreased nitrogen-containing compounds but increased shikimates-phenylpropanoids. Subsequent bioassays with two shikimates-phenylpropanoids (shikimic and p-coumaric acids) on soil bacteria or Brachypodium seedlings revealed their distinct capacity to regulate both bacterial and plant growth. Our results suggest that (i) Brachypodium alters exudation in response to nitrogen status, which can affect rhizobacterial growth, and (ii) EcoFAB 2.0 is a valuable standardized plant research tool.

Semantic segmentation of plant roots from RGB (mini-) rhizotron images-generalisation potential and false positives of established methods and advanced deep-learning models

BACKGROUND

Manual analysis of (mini-)rhizotron (MR) images is tedious. Several methods have been proposed for semantic root segmentation based on homogeneous, single-source MR datasets. Recent advances in deep learning (DL) have enabled automated feature extraction, but comparisons of segmentation accuracy, false positives and transferability are virtually lacking. Here we compare six state-of-the-art methods and propose two improved DL models for semantic root segmentation using a large MR dataset with and without augmented data. We determine the performance of the methods on a homogeneous maize dataset, and a mixed dataset of > 8 species (mixtures), 6 soil types and 4 imaging systems. The generalisation potential of the derived DL models is determined on a distinct, unseen dataset.

RESULTS

The best performance was achieved by the U-Net models; the more complex the encoder the better the accuracy and generalisation of the model. The heterogeneous mixed MR dataset was a particularly challenging for the non-U-Net techniques. Data augmentation enhanced model performance. We demonstrated the improved performance of deep meta-architectures and feature extractors, and a reduction in the number of false positives.

CONCLUSIONS

Although correction factors are still required to match human labelled root lengths, neural network architectures greatly reduce the time required to compute the root length. The more complex architectures illustrate how future improvements in root segmentation within MR images can be achieved, particularly reaching higher segmentation accuracies and model generalisation when analysing real-world datasets with artefacts-limiting the need for model retraining.

The long intergenic noncoding RNA ARES modulates root architecture in Arabidopsis

Long noncoding RNAs (lncRNAs) have emerged as important regulators of gene expression in plants. They have been linked to a wide range of molecular mechanisms, including epigenetics, miRNA activity, RNA processing and translation, and protein localization or stability. In Arabidopsis, characterized lncRNAs have been implicated in several physiological contexts, including plant development and the response to the environment. Here we searched for lncRNA loci located nearby key genes involved in root development and identified the lncRNA ARES (AUXIN REGULATOR ELEMENT DOWNSTREAM SOLITARYROOT) downstream of the lateral root master gene IAA14/SOLITARYROOT (SLR). Although ARES and IAA14 are co-regulated during development, the knockdown and knockout of ARES did not affect IAA14 expression. However, in response to exogenous auxin, ARES knockdown impairs the induction of its other neighboring gene encoding the transcription factor NF-YB3. Furthermore, knockdown/out of ARES results in a root developmental phenotype in control conditions. Accordingly, a transcriptomic analysis revealed that a subset of ARF7-dependent genes is deregulated. Altogether, our results hint at the lncRNA ARES as a novel regulator of the auxin response governing lateral root development, likely by modulating gene expression in trans.

Defying Gravity: WEEP promotes negative gravitropism in Prunus persica (peach) shoots and roots by establishing asymmetric auxin gradients

Trees with weeping shoot architectures are valued for their beauty and serve as tremendous resources for understanding how plants regulate posture control. The Prunus persica (peach) weeping phenotype, which has elliptical downward arching branches, is caused by a homozygous mutation in the WEEP gene. Until now, little was known about the function of WEEP protein despite its high conservation throughout Plantae. Here, we present the results of anatomical, biochemical, biomechanical, physiological, and molecular experiments that provide insight into WEEP function. Our data suggest that weeping peach does not have defects in branch structure. Rather, transcriptomes from the adaxial (upper) and abaxial (lower) sides of standard and weeping branch shoot tips revealed flipped expression patterns for genes associated with early auxin response, tissue patterning, cell elongation, and tension wood development. This suggests that WEEP promotes polar auxin transport toward the lower side during shoot gravitropic response, leading to cell elongation and tension wood development. In addition, weeping peach trees exhibited steeper root systems and faster root gravitropic response, just as barley and wheat with mutations in their WEEP homolog EGT2. This suggests that the role of WEEP in regulating lateral organ angles and orientations during gravitropism may be conserved. Additionally, size-exclusion chromatography indicated that WEEP proteins self-oligomerize, like other SAM-domain proteins. This oligomerization may be required for WEEP to function in formation of protein complexes during auxin transport. Collectively, our results from weeping peach provide new insight into polar auxin transport mechanisms associated with gravitropism and lateral shoot and root orientation.

Contrasting Cd accumulation of Arabidopsis halleri populations: a role for (1→4)-β-galactan in pectin

Cadmium (Cd) accumulation is highly variable among Arabidopsis halleri populations. To identify cell wall (CW) components that contribute to the contrasting Cd accumulation between PL22-H (Cd-hyperaccumulator) and I16-E (Cd-excluder), Cd absorption capacity of CW polysaccharides, CW mono- and poly- saccharides contents and CW glycan profiles were compared between these two populations. PL22-H pectin contained 3-fold higher Cd concentration than I16-E pectin in roots, and (1→4)-β-galactan pectic epitope showed the biggest difference between PL22-H and I16-E. CW-related differentially expressed genes (DEGs) between PL22-H and I16-E were identified and corresponding A. thaliana mutants were phenotyped for Cd tolerance and accumulation. A higher Cd translocation was observed in GALACTAN SYNTHASE1 A. thaliana knockout and overexpressor mutants, which both showed a lengthening of the RG-I sidechains after Cd treatment, contrary to the wild-type. Overall, our results support an indirect role for (1→4)-β-galactan in Cd translocation, possibly by a joint effect of regulating the length of RG-I sidechains, the pectin structure and interactions between polysaccharides in the CW. The characterization of other CW-related DEGs between I16-E and PL22-H selected allowed to identify a possible role in Zn translocation for BIIDXI and LEUNIG-HOMOLOG genes, which are both involved in pectin modification.

A method of cotton root segmentation based on edge devices

The root is an important organ for plants to absorb water and nutrients. In situ root research method is an intuitive method to explore root phenotype and its change dynamics. At present, in situ root research, roots can be accurately extracted from in situ root images, but there are still problems such as low analysis efficiency, high acquisition cost, and difficult deployment of image acquisition devices outdoors. Therefore, this study designed a precise extraction method of in situ roots based on semantic segmentation model and edge device deployment. It initially proposes two data expansion methods, pixel by pixel and equal proportion, expand 100 original images to 1600 and 53193 respectively. It then presents an improved DeeplabV3+ root segmentation model based on CBAM and ASPP in series is designed, and the segmentation accuracy is 93.01%. The root phenotype parameters were verified through the Rhizo Vision Explorers platform, and the root length error was 0.669%, and the root diameter error was 1.003%. It afterwards designs a time-saving Fast prediction strategy. Compared with the Normal prediction strategy, the time consumption is reduced by 22.71% on GPU and 36.85% in raspberry pie. It ultimately deploys the model to Raspberry Pie, realizing the low-cost and portable root image acquisition and segmentation, which is conducive to outdoor deployment. In addition, the cost accounting is only $247. It takes 8 hours to perform image acquisition and segmentation tasks, and the power consumption is as low as 0.051kWh. In conclusion, the method proposed in this study has good performance in model accuracy, economic cost, energy consumption, etc. This paper realizes low-cost and high-precision segmentation of in-situ root based on edge equipment, which provides new insights for high-throughput field research and application of in-situ root.

High-throughput and automatic structural and developmental root phenotyping on Arabidopsis seedlings

BACKGROUND

High-throughput phenotyping is crucial for the genetic and molecular understanding of adaptive root system development. In recent years, imaging automata have been developed to acquire the root system architecture of many genotypes grown in Petri dishes to explore the Genetic x Environment (GxE) interaction. There is now an increasing interest in understanding the dynamics of the adaptive responses, such as the organ apparition or the growth rate. However, due to the increasing complexity of root architectures in development, the accurate description of the topology, geometry, and dynamics of a growing root system remains a challenge.

RESULTS

We designed a high-throughput phenotyping method, combining an imaging device and an automatic analysis pipeline based on registration and topological tracking, capable of accurately describing the topology and geometry of observed root systems in 2D + t. The method was tested on a challenging Arabidopsis seedling dataset, including numerous root occlusions and crossovers. Static phenes are estimated with high accuracy ([Formula: see text] and [Formula: see text] for primary and second-order roots length, respectively). These performances are similar to state-of-the-art results obtained on root systems of equal or lower complexity. In addition, our pipeline estimates dynamic phenes accurately between two successive observations ([Formula: see text] for lateral root growth).

CONCLUSIONS

We designed a novel method of root tracking that accurately and automatically measures both static and dynamic parameters of the root system architecture from a novel high-throughput root phenotyping platform. It has been used to characterise developing patterns of root systems grown under various environmental conditions. It provides a solid basis to explore the GxE interaction controlling the dynamics of root system architecture adaptive responses. In future work, our approach will be adapted to a wider range of imaging configurations and species.

Genetic variation underlying differential ammonium and nitrate responses in Arabidopsis thaliana

Nitrogen is an essential element required for plant growth and productivity. Understanding the mechanisms and natural genetic variation underlying nitrogen use in plants will facilitate the engineering of plant nitrogen use to maximize crop productivity while minimizing environmental costs. To understand the scope of natural variation that may influence nitrogen use, we grew 1,135 Arabidopsis thaliana natural genotypes on two nitrogen sources, nitrate and ammonium, and measured both developmental and defense metabolite traits. By using different environments and focusing on multiple traits, we identified a wide array of different nitrogen responses. These responses are associated with numerous genes, most of which were not previously associated with nitrogen responses. Only a small portion of these genes appear to be shared between environments or traits, while most are predominantly specific to a developmental or defense trait under a specific nitrogen source. Finally, by using a large population, we were able to identify unique nitrogen responses, such as preferring ammonium or nitrate, which appear to be generated by combinations of loci rather than a few large-effect loci. This suggests that it may be possible to obtain novel phenotypes in complex nitrogen responses by manipulating sets of genes with small effects rather than solely focusing on large-effect single gene manipulations.

Integrating advancements in root phenotyping and genome-wide association studies to open the root genetics gateway

Plant adaptation to challenging environmental conditions around the world has made root growth and development an important research area for plant breeders and scientists. Targeted manipulation of root system architecture (RSA) to increase water and nutrient use efficiency can minimize the adverse effects of climate change on crop production. However, phenotyping of RSA is a major bottleneck since the roots are hidden in the soil. Recently the development of 2- and 3D root imaging techniques combined with the genome-wide association studies (GWASs) have opened up new research tools to identify the genetic basis of RSA. These approaches provide a comprehensive understanding of the RSA, by accelerating the identification and characterization of genes involved in root growth and development. This review summarizes the latest developments in phenotyping techniques and GWAS for RSA, which are used to map important genes regulating various aspects of RSA under varying environmental conditions. Furthermore, we discussed about the state-of-the-art image analysis tools integrated with various phenotyping platforms for investigating and quantifying root traits with the highest phenotypic plasticity in both artificial and natural environments which were used for large scale association mapping studies, leading to the identification of RSA phenotypes and their underlying genetics with the greatest potential for RSA improvement. In addition, challenges in root phenotyping and GWAS are also highlighted, along with future research directions employing machine learning and pan-genomics approaches.

Novel method for the quantification of rosette area from images of Arabidopsis seedlings grown on agar plates

Premise

The agar-based culture of Arabidopsis seedlings is widely used for quantifying root traits. Shoot traits are generally overlooked in these studies, probably because the rosettes are often askew. A technique to assess the shoot surface area of seedlings grown inside agar culture dishes would facilitate simultaneous root and shoot phenotyping.

Methods

We developed an image processing workflow in Python that estimates rosette area of Arabidopsis seedlings on agar culture dishes. We validated this method by comparing its output with other metrics of seedling growth. As part of a larger study on genetic variation in plant responses to nitrogen form and concentration, we measured the rosette areas from more than 2000 plate images.

Results

The rosette area measured from plate images was strongly correlated with the rosette area measured from directly overhead and moderately correlated with seedling mass. Rosette area in the large image set was significantly influenced by genotype and nitrogen treatment. The broad-sense heritability of leaf area measured using this method was 0.28.

Discussion

These results indicated that this approach for estimating rosette area produces accurate shoot phenotype data. It can be used with image sets for which other methods of leaf area quantification prove unsuitable.

Phosphite treatment can improve root biomass and nutrition use efficiency in wheat

Phosphite represents a reduced form of phosphate that belongs to a class of crop growth-promoting chemicals termed biostimulants. Previous research has shown that phosphite application can enhance root growth, but its underlying mechanism, especially during environmental stresses, remains elusive. To uncover this, we undertook a series of morphological and physiological analyses under nutrient, water and heat stresses following a foliar application in wheat. Non-invasive 3D imaging of root system architecture directly in soil using X-ray Computed Tomography revealed that phosphite treatment improves root architectural traits and increased root biomass. Biochemical and physiological assays identified that phosphite treatment significantly increases Nitrate Reductase (NR) activity, leaf photosynthesis and stomatal conductance, suggesting improved Nitrogen and Carbon assimilation, respectively. These differences were more pronounced under heat or drought treatment (photosynthesis and photosystem II stability) and nutrient deficiency (root traits and NR). Overall our results suggest that phosphite treatment improves the ability of plants to tolerate abiotic stresses through improved Nitrogen and Carbon assimilation, combined with improved root growth which may improve biomass and yield.

Iterative image segmentation of plant roots for high-throughput phenotyping

Accurate segmentation of root system architecture (RSA) from 2D images is an important step in studying phenotypic traits of root systems. Various approaches to image segmentation exist but many of them are not well suited to the thin and reticulated structures characteristic of root systems. The findings presented here describe an approach to RSA segmentation that takes advantage of the inherent structural properties of the root system, a segmentation network architecture we call ITErRoot. We have also generated a novel 2D root image dataset which utilizes an annotation tool developed for producing high quality ground truth segmentation of root systems. Our approach makes use of an iterative neural network architecture to leverage the thin and highly branched properties of root systems for accurate segmentation. Rigorous analysis of model properties was carried out to obtain a high-quality model for 2D root segmentation. Results show a significant improvement over other recent approaches to root segmentation. Validation results show that the model generalizes to plant species with fine and highly branched RSA’s, and performs particularly well in the presence of non-root objects.

The regeneration factors ERF114 and ERF115 regulate auxin-mediated lateral root development in response to mechanical cues

Plants show an unparalleled regenerative capacity, allowing them to survive severe stress conditions, such as injury, herbivory attack, and harsh weather conditions. This potential not only replenishes tissues and restores damaged organs but can also give rise to whole plant bodies. Despite the intertwined nature of development and regeneration, common upstream cues and signaling mechanisms are largely unknown. Here, we demonstrate that in addition to being activators of regeneration, ETHYLENE RESPONSE FACTOR 114 (ERF114) and ERF115 govern developmental growth in the absence of wounding or injury. Increased ERF114 and ERF115 activity enhances auxin sensitivity, which is correlated with enhanced xylem maturation and lateral root formation, whereas their knockout results in a decrease in lateral roots. Moreover, we provide evidence that mechanical cues contribute to ERF114 and ERF115 expression in correlation with BZR1-mediated brassinosteroid signaling under both regenerative and developmental conditions. Antagonistically, cell wall integrity surveillance via mechanosensory FERONIA signaling suppresses their expression under both conditions. Taken together, our data suggest a molecular framework in which cell wall signals and mechanical strains regulate organ development and regenerative responses via ERF114- and ERF115-mediated auxin signaling.

The Pyla-1 Natural Accession of Arabidopsis thaliana Shows Little Nitrate-Induced Plasticity of Root Development

Optimizing root system architecture is a strategy for coping with soil fertility, such as low nitrogen input. An ample number of Arabidopsis thaliana natural accessions have set the foundation for studies on mechanisms that regulate root morphology. This report compares the Columbia-0 (Col-0) reference and Pyla-1 (Pyl-1) from a coastal zone in France, known for having the tallest sand dune in Europe. Seedlings were grown on vertical agar plates with different nitrate concentrations. The lateral root outgrowth of Col-0 was stimulated under mild depletion and repressed under nitrate enrichment. The Pyl-1 produced a long primary root and any or very few visible lateral roots across the nitrate supplies. This could reflect an adaptation to sandy soil conditions, where the primary root grows downwards to the lower strata to take up water and mobile soil resources without elongating the lateral roots. Microscopic observations revealed similar densities of lateral root primordia in both accessions. The Pyl-1 maintained the ability to initiate lateral root primordia. However, the post-initiation events seemed to be critical in modulating the lateral-root-less phenotype. In Pyl-1, the emergence of primordia through the primary root tissues was slowed, and newly formed lateral roots stayed stunted. In brief, Pyl-1 is a fascinating genotype for studying the nutritional influences on lateral root development.

Recent advances in methods for in situ root phenotyping

Roots assist plants in absorbing water and nutrients from soil. Thus, they are vital to the survival of nearly all land plants, considering that plants cannot move to seek optimal environmental conditions. Crop species with optimal root system are essential for future food security and key to improving agricultural productivity and sustainability. Root systems can be improved and bred to acquire soil resources efficiently and effectively. This can also reduce adverse environmental impacts by decreasing the need for fertilization and fresh water. Therefore, there is a need to improve and breed crop cultivars with favorable root system. However, the lack of high-throughput root phenotyping tools for characterizing root traits in situ is a barrier to breeding for root system improvement. In recent years, many breakthroughs in the measurement and analysis of roots in a root system have been made. Here, we describe the major advances in root image acquisition and analysis technologies and summarize the advantages and disadvantages of each method. Furthermore, we look forward to the future development direction and trend of root phenotyping methods. This review aims to aid researchers in choosing a more appropriate method for improving the root system.

Root system size and root hair length are key phenes for nitrate acquisition and biomass production across natural variation in Arabidopsis

The role of root phenes in nitrogen (N) acquisition and biomass production was evaluated in 10 contrasting natural accessions of Arabidopsis thaliana L. Seedlings were grown on vertical agar plates with two different nitrate supplies. The low N treatment increased the root to shoot biomass ratio and promoted the proliferation of lateral roots and root hairs. The cost of a larger root system did not impact shoot biomass. Greater biomass production could be achieved through increased root length or through specific root hair characteristics. A greater number of root hairs may provide a low-resistance pathway under elevated N conditions, while root hair length may enhance root zone exploration under low N conditions. The variability of N uptake and the expression levels of genes encoding nitrate transporters were measured. A positive correlation was found between root system size and high-affinity nitrate uptake, emphasizing the benefits of an exploratory root organ in N acquisition. The expression levels of NRT1.2/NPF4.6, NRT2.2, and NRT1.5/NPF7.3 negatively correlated with some root morphological traits. Such basic knowledge in Arabidopsis demonstrates the importance of root phenes to improve N acquisition and paves the way to design eudicot ideotypes.

The lncRNA MARS modulates the epigenetic reprogramming of the marneral cluster in response to ABA

Clustered organization of biosynthetic non-homologous genes is emerging as a characteristic feature of plant genomes. The co-regulation of clustered genes seems to largely depend on epigenetic reprogramming and three-dimensional chromatin conformation. In this study, we identified the long non-coding RNA (lncRNA) MARneral Silencing (MARS), localized inside the Arabidopsis marneral cluster, which controls the local epigenetic activation of its surrounding region in response to abscisic acid (ABA). MARS modulates the POLYCOMB REPRESSIVE COMPLEX 1 (PRC1) component LIKE HETEROCHROMATIN PROTEIN 1 (LHP1) binding throughout the cluster in a dose-dependent manner, determining H3K27me3 deposition and chromatin condensation. In response to ABA, MARS decoys LHP1 away from the cluster and promotes the formation of a chromatin loop bringing together the MARNERAL SYNTHASE 1 (MRN1) locus and a distal ABA-responsive enhancer. The enrichment of co-regulated lncRNAs in clustered metabolic genes in Arabidopsis suggests that the acquisition of novel non-coding transcriptional units may constitute an additional regulatory layer driving the evolution of biosynthetic pathways.

Rhizoctonia Resistance Is Negatively Correlated to Early Root Growth Rate in Synthetic Hexaploid Wheat Derivatives

Resistance to the soilborne fungal pathogen Rhizoctonia solani AG-8 is desirable in adapted wheat and barley but remains an elusive trait for prebreeders and breeders. In a previous study, we observed that emergence and root growth was faster in the Rhizoctonia-susceptible 'Scarlet' than in its resistant counterpart, 'Scarlet-Rz1'. The objective of the current study was to quantify early root growth rate and total root length in resistant and susceptible synthetic hexaploid wheat lines, including parental lines and 22 recombinant inbred lines derived crosses between parental lines. In Petri dish assays, the susceptible lines displayed a faster rate of root growth during the first 40 h of root emergence compared with resistant lines. This growth differential was observed in 14-day and 48-h greenhouse assays, in which the total root length of susceptible parental lines was significantly (P < 0.05) greater than that of resistant parental lines. However, the resistant lines sustained less root loss compared with susceptible lines when R. solani AG-8 was present in the soil. Early root growth rate and total root length were not correlated to freezing tolerance in a set of wheat cultivars selected for cold tolerance. The findings indicated that early root growth was negatively correlated to R. solani AG-8 damage in resistant synthetic wheat lines developed for the Pacific Northwest, United States, and suggested that the dynamics of root emergence affect resistance to this soilborne pathogen.

Climate Change Impact on Wheat Performance—Effects on Vigour, Plant Traits and Yield from Early and Late Drought Stress in Diverse Lines

Global climate change is threatening wheat productivity; improved yield under drought conditions is urgent. Here, diverse spring-wheat lines (modern, old and wheat-rye introgressions) were examined in an image-based early-vigour assay and a controlled-conditions (Biotron) trial that evaluated 13 traits until maturity. Early root vigour was significantly higher in the old Swedish lines (root length 8.50 cm) and introgressed lines with 1R (11.78 cm) and 1RS (9.91 cm) than in the modern (4.20 cm) and 2R (4.67 cm) lines. No significant correlation was noted between early root and shoot vigour. A higher yield was obtained under early drought stress in the 3R genotypes than in the other genotype groups, while no clear patterns were noted under late drought. Evaluating the top 10% of genotypes in terms of the stress-tolerance index for yield showed that root biomass, grains and spikes per plant were accountable for tolerance to early drought, while 1000-grain weight and flag-leaf area were accountable for tolerance to late drought. Early root vigour was determined as an important focus trait of wheat breeding for tolerance to climate-change-induced drought. The responsible genes for the trait should be searched for in these diverse lines. Additional drought-tolerance traits determined here need further elaboration to identify the responsible genes.

Improving the efficiency of plant root system phenotyping through digitization and automation

Root system architecture (RSA) determines unevenly distributed water and nutrient availability in soil. Genetic improvement of RSA, therefore, is related to crop production. However, RSA phenotyping has been carried out less frequently than above-ground phenotyping because measuring roots in the soil is difficult and labor intensive. Recent advancements have led to the digitalization of plant measurements; this digital phenotyping has been widely used for measurements of both above-ground and RSA traits. Digital phenotyping for RSA is slower and more difficult than for above-ground traits because the roots are hidden underground. In this review, we summarized recent trends in digital phenotyping for RSA traits. We classified the sample types into three categories: soil block containing roots, section of soil block, and root sample. Examples of the use of digital phenotyping are presented for each category. We also discussed room for improvement in digital phenotyping in each category.

Dissecting the Root Phenotypic and Genotypic Variability of the Iowa Mung Bean Diversity Panel

Mung bean [Vigna radiata (L.) Wilczek] is a drought-tolerant, short-duration crop, and a rich source of protein and other valuable minerals, vitamins, and antioxidants. The main objectives of this research were (1) to study the root traits related with the phenotypic and genetic diversity of 375 mung bean genotypes of the Iowa (IA) diversity panel and (2) to conduct genome-wide association studies of root-related traits using the Automated Root Image Analysis (ARIA) software. We collected over 9,000 digital images at three-time points (days 12, 15, and 18 after germination). A broad sense heritability for days 15 (0.22-0.73) and 18 (0.23-0.87) was higher than that for day 12 (0.24-0.51). We also reported root ideotype classification, i.e., PI425425 (India), PI425045 (Philippines), PI425551 (Korea), PI264686 (Philippines), and PI425085 (Sri Lanka) that emerged as the top five in the topsoil foraging category, while PI425594 (unknown origin), PI425599 (Thailand), PI425610 (Afghanistan), PI425485 (India), and AVMU0201 (Taiwan) were top five in the drought-tolerant and nutrient uptake "steep, cheap, and deep" ideotype. We identified promising genotypes that can help diversify the gene pool of mung bean breeding stocks and will be useful for further field testing. Using association studies, we identified markers showing significant associations with the lateral root angle (LRA) on chromosomes 2, 6, 7, and 11, length distribution (LED) on chromosome 8, and total root length-growth rate (TRL_GR), volume (VOL), and total dry weight (TDW) on chromosomes 3 and 5. We discussed genes that are potential candidates from these regions. We reported beta-galactosidase 3 associated with the LRA, which has previously been implicated in the adventitious root development via transcriptomic studies in mung bean. Results from this work on the phenotypic characterization, root-based ideotype categories, and significant molecular markers associated with important traits will be useful for the marker-assisted selection and mung bean improvement through breeding.

Prospectus of Genomic Selection and Phenomics in Cereal, Legume and Oilseed Breeding Programs

The last decade witnessed an unprecedented increase in the adoption of genomic selection (GS) and phenomics tools in plant breeding programs, especially in major cereal crops. GS has demonstrated the potential for selecting superior genotypes with high precision and accelerating the breeding cycle. Phenomics is a rapidly advancing domain to alleviate phenotyping bottlenecks and explores new large-scale phenotyping and data acquisition methods. In this review, we discuss the lesson learned from GS and phenomics in six self-pollinated crops, primarily focusing on rice, wheat, soybean, common bean, chickpea, and groundnut, and their implementation schemes are discussed after assessing their impact in the breeding programs. Here, the status of the adoption of genomics and phenomics is provided for those crops, with a complete GS overview. GS’s progress until 2020 is discussed in detail, and relevant information and links to the source codes are provided for implementing this technology into plant breeding programs, with most of the examples from wheat breeding programs. Detailed information about various phenotyping tools is provided to strengthen the field of phenomics for a plant breeder in the coming years. Finally, we highlight the benefits of merging genomic selection, phenomics, and machine and deep learning that have resulted in extraordinary results during recent years in wheat, rice, and soybean. Hence, there is a potential for adopting these technologies into crops like the common bean, chickpea, and groundnut. The adoption of phenomics and GS into different breeding programs will accelerate genetic gain that would create an impact on food security, realizing the need to feed an ever-growing population.

Analysis of Plant Root Gravitropism

Gravity is a powerful element in shaping plant development, with gravitropism, the oriented growth response of plant organs to the direction of gravity, leading to each plant's characteristic form both above and below ground. Despite being conceptually simple to follow, monitoring a plant's directional growth responses can become complex as variation arises from both internal developmental cues as well as effects of the environment. In this protocol, we discuss approaches to gravitropism assays, focusing on automated analyses of root responses. For Arabidopsis, we recommend a simple 90° rotation using seedlings that are 5-8 days old. If images are taken at regular intervals and the environmental metadata is recorded during both seedling development and gravitropic assay, these data can be used to reveal quantitative kinetic patterns at distinct stages of the assay. The use of software that analyzes root system parameters and stores this data in the RSML format opens up the possibility for a host of root parameters to be extracted to characterize growth of the primary root and a range of lateral root phenotypes.

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

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

RhizoVision Explorer: open-source software for root image analysis and measurement standardization

Roots are central to the function of natural and agricultural ecosystems by driving plant acquisition of soil resources and influencing the carbon cycle. Root characteristics like length, diameter and volume are critical to measure to understand plant and soil functions. RhizoVision Explorer is an open-source software designed to enable researchers interested in roots by providing an easy-to-use interface, fast image processing and reliable measurements. The default broken roots mode is intended for roots sampled from pots and soil cores, washed and typically scanned on a flatbed scanner, and provides measurements like length, diameter and volume. The optional whole root mode for complete root systems or root crowns provides additional measurements such as angles, root depth and convex hull. Both modes support providing measurements grouped by defined diameter ranges, the inclusion of multiple regions of interest and batch analysis. RhizoVision Explorer was successfully validated against ground truth data using a new copper wire image set. In comparison, the current reference software, the commercial WinRhizo™, drastically underestimated volume when wires of different diameters were in the same image. Additionally, measurements were compared with WinRhizo™ and IJ_Rhizo using a simulated root image set, showing general agreement in software measurements, except for root volume. Finally, scanned root image sets acquired in different labs for the crop, herbaceous and tree species were used to compare results from RhizoVision Explorer with WinRhizo™. The two software showed general agreement, except that WinRhizo™ substantially underestimated root volume relative to RhizoVision Explorer. In the current context of rapidly growing interest in root science, RhizoVision Explorer intends to become a reference software, improve the overall accuracy and replicability of root trait measurements and provide a foundation for collaborative improvement and reliable access to all.

Genomic prediction and QTL mapping of root system architecture and above-ground agronomic traits in rice (Oryza sativa L.) with a multitrait index and Bayesian networks

Root system architecture (RSA) is a crucial factor in resource acquisition and plant productivity. Roots are difficult to phenotype in the field, thus new tools for predicting phenotype from genotype are particularly valuable for plant breeders aiming to improve RSA. This study identifies quantitative trait loci (QTLs) for RSA and agronomic traits in a rice (Oryza sativa) recombinant inbred line (RIL) population derived from parents with contrasting RSA traits (PI312777 × Katy). The lines were phenotyped for agronomic traits in the field, and separately grown as seedlings on agar plates which were imaged to extract RSA trait measurements. QTLs were discovered from conventional linkage analysis and from a machine learning approach using a Bayesian network (BN) consisting of genome-wide SNP data and phenotypic data. The genomic prediction abilities (GPAs) of multi-QTL models and the BN analysis were compared with the several standard genomic prediction (GP) methods. We found GPAs were improved using multitrait (BN) compared to single trait GP in traits with low to moderate heritability. Two groups of individuals were selected based on GPs and a modified rank sum index (GSRI) indicating their divergence across multiple RSA traits. Selections made on GPs did result in differences between the group means for numerous RSA. The ranking accuracy across RSA traits among the individual selected RILs ranged from 0.14 for root volume to 0.59 for lateral root tips. We conclude that the multitrait GP model using BN can in some cases improve the GPA of RSA and agronomic traits, and the GSRI approach is useful to simultaneously select for a desired set of RSA traits in a segregating population.

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

Background

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

Results

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

Conclusions

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

Supplementary Information

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

In situ Phenotyping of Grapevine Root System Architecture by 2D or 3D Imaging: Advantages and Limits of Three Cultivation Methods

The root system plays an essential role in the development and physiology of the plant, as well as in its response to various stresses. However, it is often insufficiently studied, mainly because it is difficult to visualize. For grapevine, a plant of major economic interest, there is a growing need to study the root system, in particular to assess its resistance to biotic and abiotic stresses, understand the decline that may affect it, and identify new ecofriendly production systems. In this context, we have evaluated and compared three distinct growing methods (hydroponics, plane, and cylindric rhizotrons) in order to describe relevant architectural root traits of grapevine cuttings (mode of grapevine propagation), and also two 2D- (hydroponics and rhizotron) and one 3D- (neutron tomography) imaging techniques for visualization and quantification of roots. We observed that hydroponics tubes are a system easy to implement but do not allow the direct quantification of root traits over time, conversely to 2D imaging in rhizotron. We demonstrated that neutron tomography is relevant to quantify the root volume. We have also produced a new automated analysis method of digital photographs, adapted for identifying adventitious roots as a feature of root architecture in rhizotrons. This method integrates image segmentation, skeletonization, detection of adventitious root skeleton, and adventitious root reconstruction. Although this study was targeted to grapevine, most of the results obtained could be extended to other plants propagated by cuttings. Image analysis methods could also be adapted to characterization of the root system from seedlings.

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

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

Mass spectrometry-based quantification and spatial localization of small organic acid exudates in plant roots under phosphorus deficiency and aluminum toxicity

Low-molecular-weight organic acid (OA) extrusion by plant roots is critical for plant nutrition, tolerance to cations toxicity, and plant-microbe interactions. Therefore, methodologies for the rapid and precise quantification of OAs are necessary to be incorporated in the analysis of roots and their exudates. The spatial location of root exudates is also important to understand the molecular mechanisms directing OA production and release into the rhizosphere. Here, we report the development of two complementary methodologies for OA determination, which were employed to evaluate the effect of inorganic ortho-phosphate (Pi) deficiency and aluminum toxicity on OA excretion by Arabidopsis roots. OA exudation by roots is considered a core response to different types of abiotic stress and for the interaction of roots with soil microbes, and for decades has been a target trait to produce plant varieties with increased capacities of Pi uptake and Al tolerance. Using targeted ultra-performance liquid chromatography coupled with high-resolution tandem mass spectrometry (UPLC-HRMS/MS), we achieved the quantification of six OAs in root exudates at sub-micromolar detection limits with an analysis time of less than 5 min per sample. We also employed targeted (MS/MS) matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to detect the spatial location of citric and malic acid with high specificity in roots and exudates. Using these methods, we studied OA exudation in response to Al toxicity and Pi deficiency in Arabidopsis seedlings overexpressing genes involved in OA excretion. Finally, we show the transferability of the MALDI-MSI method by analyzing OA excretion in Marchantia polymorpha gemmalings subjected to Pi deficiency.

Function of the pseudo phosphotransfer proteins has diverged between rice and Arabidopsis

The phytohormone cytokinin plays a significant role in nearly all aspects of plant growth and development. Cytokinin signaling has primarily been studied in the dicot model Arabidopsis, with relatively little work done in monocots, which include rice (Oryza sativa) and other cereals of agronomic importance. The cytokinin signaling pathway is a phosphorelay comprised of the histidine kinase receptors, the authentic histidine phosphotransfer proteins (AHPs) and type-B response regulators (RRs). Two negative regulators of cytokinin signaling have been identified: the type-A RRs, which are cytokinin primary response genes, and the pseudo histidine phosphotransfer proteins (PHPs), which lack the His residue required for phosphorelay. Here, we describe the role of the rice PHP genes. Phylogenic analysis indicates that the PHPs are generally first found in the genomes of gymnosperms and that they arose independently in monocots and dicots. Consistent with this, the three rice PHPs fail to complement an Arabidopsis php mutant (aphp1/ahp6). Disruption of the three rice PHPs results in a molecular phenotype consistent with these elements acting as negative regulators of cytokinin signaling, including the induction of a number of type-A RR and cytokinin oxidase genes. The triple php mutant affects multiple aspects of rice growth and development, including shoot morphology, panicle architecture, and seed fill. In contrast to Arabidopsis, disruption of the rice PHPs does not affect root vascular patterning, suggesting that while many aspects of key signaling networks are conserved between monocots and dicots, the roles of at least some cytokinin signaling elements are distinct.

Root System Phenotying of Soil-Grown Plants via RGB and Hyperspectral Imaging

Phenotyping root systems provide essential information for plant breeding, particularly aiming for better abiotic stress resistance. Rhizobox systems provide a field-near growth environment for in situ imaging of root systems in soil. A protocol for RGB and hyperspectral imaging of rhizobox-grown plants is presented that enables gathering of root structural (morphology, architecture) as well as functional (water content, decomposition) information. The protocol exemplifies the setup of a root phenotyping platform combining low-cost RGB with advanced short-wave infrared hyperspectral imaging. For both types of imaging approach, the essential steps of an image analysis pipeline are provided to retrieve biological information on breeding-relevant traits from the imaging datasets.

QTL mapping of root traits in wheat under different phosphorus levels using hydroponic culture

Background

Phosphorus (P) is an important in ensuring plant morphogenesis and grain quality, therefore an efficient root system is crucial for P-uptake. Identification of useful loci for root morphological and P uptake related traits at seedling stage is important for wheat breeding. The aims of this study were to evaluate phenotypic diversity of Yangmai 16/Zhongmai 895 derived doubled haploid (DH) population for root system architecture (RSA) and biomass related traits (BRT) in different P treatments at seedling stage using hydroponic culture, and to identify QTL using 660 K SNP array based high-density genetic map.

Results

All traits showed significant variations among the DH lines with high heritabilities (0.76 to 0.91) and high correlations (r = 0.59 to 0.98) among all traits. Inclusive composite interval mapping (ICIM) identified 34 QTL with 4.64–20.41% of the phenotypic variances individually, and the log of odds (LOD) values ranging from 2.59 to 10.43. Seven QTL clusters (C1 to C7) were mapped on chromosomes 3DL, 4BS, 4DS, 6BL, 7AS, 7AL and 7BL, cluster C5 on chromosome 7AS (AX-109955164 - AX-109445593) with pleiotropic effect played key role in modulating root length (RL), root tips number (RTN) and root surface area (ROSA) under low P condition, with the favorable allele from Zhongmai 895.

Conclusions

This study carried out an imaging pipeline-based rapid phenotyping of RSA and BRT traits in hydroponic culture. It is an efficient approach for screening of large populations under different nutrient conditions. Four QTL on chromosomes 6BL (2) and 7AL (2) identified in low P treatment showed positive additive effects contributed by Zhongmai 895, indicating that Zhongmai 895 could be used as parent for P-deficient breeding. The most stable QTL QRRS.caas-4DS for ratio of root to shoot dry weight (RRS) harbored the stable genetic region with high phenotypic effect, and QTL clusters on 7A might be used for speedy selection of genotypes for P-uptake. SNPs closely linked to QTLs and clusters could be used to improve nutrient-use efficiency.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07425-4.

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

As plants cannot relocate, they require effective root systems for water and nutrient uptake. Root development plasticity enables plants to adapt to different environmental conditions. Research on improvements in crop root systems is limited in comparison with that in shoots as the former are difficult to image. Breeding more effective root systems is proposed as the "second green revolution". There are several recent publications on root system architecture (RSA), but the methods used to analyze the RSA have not been standardized. Here, we introduce traditional and current root-imaging methods and discuss root structure phenotyping. Some important root structures have not been standardized as roots are easily affected by rhizosphere conditions and exhibit greater plasticity than shoots; moreover, root morphology significantly varies even in the same genotype. For these reasons, it is difficult to define the ideal root systems for breeding. In this review, we introduce several types of software to analyze roots and identify important root parameters by modeling to simplify the root system characterization. These parameters can be extracted from photographs captured in the field. This modeling approach is applicable to various legacy root data stored in old or unpublished formats. Standardization of RSA data could help estimate root ideotypes.

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

As plants cannot relocate, they require effective root systems for water and nutrient uptake. Root development plasticity enables plants to adapt to different environmental conditions. Research on improvements in crop root systems is limited in comparison with that in shoots as the former are difficult to image. Breeding more effective root systems is proposed as the "second green revolution". There are several recent publications on root system architecture (RSA), but the methods used to analyze the RSA have not been standardized. Here, we introduce traditional and current root-imaging methods and discuss root structure phenotyping. Some important root structures have not been standardized as roots are easily affected by rhizosphere conditions and exhibit greater plasticity than shoots; moreover, root morphology significantly varies even in the same genotype. For these reasons, it is difficult to define the ideal root systems for breeding. In this review, we introduce several types of software to analyze roots and identify important root parameters by modeling to simplify the root system characterization. These parameters can be extracted from photographs captured in the field. This modeling approach is applicable to various legacy root data stored in old or unpublished formats. Standardization of RSA data could help estimate root ideotypes.

Genome-Wide Association Study on Seminal and Nodal Roots of Wheat Under Different Growth Environments

The root of wheat consists of seminal and nodal roots. Comparatively speaking, fewer studies have been carried out on the nodal root system because of its disappearance at the early seedling stage under indoor environments. In this study, 196 accessions from the Huanghuai Wheat Region (HWR) were used to identify the characteristics of seminal and nodal root traits under different growth environments, including indoor hydroponic culture (IHC), outdoor hydroponic culture (OHC), and outdoor pot culture (OPC), for three growing seasons. The results indicated that the variation range of root traits in pot environment was larger than that in hydroponic environment, and canonical coefficients were the greatest between OHC and OPC (0.86) than those in other two groups, namely, IHC vs. OPC (0.48) and IHC vs. OHC (0.46). Most root traits were negatively correlated with spikes per area (SPA), grains per spike (GPS), and grain yield (GY), while all the seminal root traits were positively correlated with thousand-kernel weight (TKW). Genome-wide association study (GWAS) was carried out on root traits by using a wheat 660K SNP array. A total of 35 quantitative trait loci (QTLs)/chromosomal segments associated with root traits were identified under OPC and OHC. In detail, 11 and 24 QTLs were significantly associated with seminal root and nodal root traits, respectively. Moreover, 13 QTLs for number of nodal roots per plant (NRP) containing 14 stable SNPs, were distributed on chromosomes 1B, 2B, 3A, 4B, 5D, 6D, 7A, 7B, and Un. Based on LD and bioinformatics analysis, these QTLs may contain 17 genes closely related to NRP. Among them, TraesCS2B02G552500 and TraesCS7A02G428300 were highly expressed in root tissues. Moreover, the frequencies of favorable alleles of these 14 SNPs were confirmed to be less than 70% in the natural population, suggesting that the utilization of these superior genes in wheat root is still improving.

Root response in Pisum sativum under naproxen stress: Morpho-anatomical, cytological, and biochemical traits

Non-steroidal anti-inflammatory drugs as an important group of emerging environmental contaminants in irrigation water and soils can influence biochemical and physiological processes essential for growth and development in plants as non-target organisms. Plants are able to take up, transport, transform, and accumulate drugs in the roots. Root biomass in ten-days old pea plants was lowered by 6% already under 0.1 mg/L naproxen (NPX) due to a lowered number of lateral roots, although 0.5 mg/L NPX stimulated the total root length by 30% as against control. Higher section area (by 40%) in root tip, area of xylem (by 150%) or stele-to-section ratio (by 10%) in zone of maturation, and lower section area in zone of lateral roots (by 18%) prove the changes in primary root anatomy and its earlier differentiation at 10 mg/L NPX. Accumulated NPX (up to 10 μg/g DW at 10 mg/L) and products of its metabolization in roots increased the amounts of hydrogen peroxide (by 33%), and superoxide (by 62%), which was reflected in elevated lipid peroxidation (by 32%), disruption of membrane integrity (by 89%) and lowering both oxidoreductase and dehydrogenase activities (by up to 40%). Elevated antioxidant capacity (SOD, APX, and other molecules) under low treatments decreased at 10 mg/L NPX (both by approx. 30%). Naproxen was proved to cause changes at both cellular and tissue levels in roots, which was also reflected in their anatomy and morphology. Higher environmental loading through drugs thus can influence even the root function.

Rooting ability of rice seedlings increases with higher soluble sugar content from exposure to light

Rooting ability of rice seedling for mechanical transplanting has a large impact on grain yield. This study explored the relationship between endogenous soluble sugar content and rooting ability of rice seedlings. We placed 15-day-old rice seedlings in controlled environment cabinets with stable light and sampled after 0, 3, 6, 9, 12, and 24 hours of light to measure their soluble sugar content, nitrate content, starch content, soluble protein content and rooting ability. The soluble sugar content of the rice seedlings before rooting increased rapidly from 65.1 mg g^-1 to 126.3 mg g^-1 in the first 9 hours of light and then tended to stabilize; however, few significant changes in the other physiological indices were detected. With the light exposure time increasing from 3 hours to 12 hours, the rooting ability measured with fresh weight, dry weight, total length, and number of new roots increased by 91.7%, 120.0%, 60.6% and 30.3%, respectively. Rooting ability was related more closely to soluble sugar content than to nitrate-nitrogen content of rice seedlings before rooting and their correlation coefficients were 0.8582–0.8684 and 0.7045–0.7882, respectively. The stepwise regression analysis revealed that the soluble sugar content before rooting explained 73.6%–75.4% of the variance, and the nitrate-nitrogen content explained an additional 7.3%–14.2% of the variance in rooting ability, indicating that compared with nitrate-nitrogen content, soluble sugar content of rice seedlings before rooting was more dominant in affecting rooting ability. This study provides direct evidence of the relationship between the rooting ability and endogenous soluble sugar content of rice seedlings.

Affordable and robust phenotyping framework to analyse root system architecture of soil-grown plants

The phenotypic analysis of root system growth is important to inform efforts to enhance plant resource acquisition from soils; however, root phenotyping remains challenging because of the opacity of soil, requiring systems that facilitate root system visibility and image acquisition. Previously reported systems require costly or bespoke materials not available in most countries, where breeders need tools to select varieties best adapted to local soils and field conditions. Here, we report an affordable soil-based growth (rhizobox) and imaging system to phenotype root development in glasshouses or shelters. All components of the system are made from locally available commodity components, facilitating the adoption of this affordable technology in low-income countries. The rhizobox is large enough (approximately 6000 cm² of visible soil) to avoid restricting vertical root system growth for most if not all of the life cycle, yet light enough (approximately 21 kg when filled with soil) for routine handling. Support structures and an imaging station, with five cameras covering the whole soil surface, complement the rhizoboxes. Images are acquired via the Phenotiki sensor interface, collected, stitched and analysed. Root system architecture (RSA) parameters are quantified without intervention. The RSAs of a dicot species (Cicer arietinum, chickpea) and a monocot species (Hordeum vulgare, barley), exhibiting contrasting root systems, were analysed. Insights into root system dynamics during vegetative and reproductive stages of the chickpea life cycle were obtained. This affordable system is relevant for efforts in Ethiopia and other low- and middle-income countries to enhance crop yields and climate resilience sustainably.

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

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