Root Traits and Phenotyping Strategies for Plant Improvement

Unraveling root and rhizosphere traits in temperate maize landraces and modern cultivars: Implications for soil resource acquisition and drought adaptation

A holistic understanding of plant strategies to acquire soil resources is pivotal in achieving sustainable food security. However, we lack knowledge about variety-specific root and rhizosphere traits for resource acquisition, their plasticity and adaptation to drought. We conducted a greenhouse experiment to phenotype root and rhizosphere traits (mean root diameter [Root D], specific root length [SRL], root tissue density, root nitrogen content, specific rhizosheath mass [SRM], arbuscular mycorrhizal fungi [AMF] colonization) of 16 landraces and 22 modern cultivars of temperate maize (Zea mays L.). Our results demonstrate that landraces and modern cultivars diverge in their root and rhizosphere traits. Although landraces follow a 'do-it-yourself' strategy with high SRLs, modern cultivars exhibit an 'outsourcing' strategy with increased mean Root Ds and a tendency towards increased root colonization by AMF. We further identified that SRM indicates an 'outsourcing' strategy. Additionally, landraces were more drought-responsive compared to modern cultivars based on multitrait response indices. We suggest that breeding leads to distinct resource acquisition strategies between temperate maize varieties. Future breeding efforts should increasingly target root and rhizosphere economics, with SRM serving as a valuable proxy for identifying varieties employing an outsourcing resource acquisition strategy.

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.

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.

Investigation of the morphological, physiological, biochemical, and catabolic characteristics and gene expression under drought stress in tolerant and sensitive genotypes of wild barley [Hordeum vulgare subsp. spontaneum (K. Koch) Asch. & Graebn.]

BACKGROUND

Barley (H. vulgare L.) is an important cereal crop cultivated across various climates globally. Barley and its ancestor (H. vulgare subsp. spontaneum) are an economically valuable model for genetic research and improvement. Drought, among various abiotic stresses, is a substantial threat to agriculture due to its unpredictable nature and significant impact on crop yield.

RESULTS

This study was conducted in both greenhouse and laboratory settings. Prior to the study, wild barley accessions were pre-selected based on their sensitivity or tolerance to drought as determined from fieldwork in the 2020-2021 and 2021-2022 cropping seasons. The effects of three levels of drought stress were evaluated (control, 90-95% field capacity [FC]; mild stress, 50-55% FC; and severe stress, 25-30% FC). Several parameters were assessed, including seedling and root growth, enzymatic activity (CAT, SOD, POD), soluble protein levels, chlorophyll content, carotenoids, abaxial and adaxial stomatal density and dimensions, and relative gene expression of Dhn1, SOD, POD, and CAT. Drought stress significantly increased enzyme activities, especially at 25-30% FC, and more in the tolerant genotype. On the other hand, sensitive genotypes showed a notable increase in stomatal density. Under drought stress, there was a general decline in seedling and root growth, protein content, chlorophyll and carotenoids, and stomatal dimensions. Importantly, gene expression analysis revealed that Dhn1, SOD, POD, and CAT were upregulated under drought, with the highest expression levels observed in the drought-tolerant genotype under severe stress conditions (25-30% FC).

CONCLUSIONS

Our investigation highlights the distinct morphological, physiological, biochemical, and gene-expression profiles of drought-resistant and drought-sensitive wild barley genotypes under varying degrees of drought.

Genome-wide dissection and haplotype analysis identified candidate loci for nitrogen use efficiency under drought conditions in winter wheat

Climate change causes extreme conditions like prolonged drought, which results in yield reductions due to its effects on nutrient balances such as nitrogen uptake and utilization by plants. Nitrogen (N) is a crucial nutrient element for plant growth and productivity. Understanding the mechanistic basis of nitrogen use efficiency (NUE) under drought conditions is essential to improve wheat (Triticum aestivum L.) yield. Here, we evaluated the genetic variation of NUE-related traits and photosynthesis response in a diversity panel of 200 wheat genotypes under drought and nitrogen stress conditions to uncover the inherent genetic variation and identify quantitative trait loci (QTLs) underlying these traits. The results revealed significant genetic variations among the genotypes in response to drought stress and nitrogen deprivation. Drought impacted plant performance more than N deprivation due to its effect on water and nutrient uptake. GWAS identified a total of 27 QTLs with a significant main effect on the drought-related traits, while 10 QTLs were strongly associated with the NUE traits. Haplotype analysis revealed two different haplotype blocks within the associated region on chromosomes 1B and 5A. The two haplotypes showed contrasting effects on N uptake and use efficiency traits. The in silico and transcript analyses implicated candidate gene coding for cold shock protein. This gene was the most highly expressed gene under several stress conditions, including drought stress. Upon validation, these QTLs on 1B and 5A could be used as a diagnostic marker for NUE and drought tolerance screening in wheat.

Transplantation of soil from organic field confers disease suppressive ability to conducive soil

Organic agriculture is a sustainable method of farming, and confers disease-suppressing abilities to disease-conducive soils via specialized soil microbiomes. This study aimed at transforming a disease-conducive soil from a conventional field into disease-suppressive soil by inoculating soil from an organic field previously established as "disease-suppressive". The effectiveness of the transformed soil was established with the model plant wheat (Triticum aestivum) grown under natural conditions, with regard to its potential in inhibiting fungal phytopathogens, Rhizoctonia solani and Fusarium oxysporum. The conducive soil inoculated with the disease-suppressive soil performed better than the control conducive soil in terms of reduced disease severity in plants, improved soil nutrient content, increased activity of hydrolytic enzymes, and increased abundance of structural and functional microbial markers. The study demonstrates the efficacy of the soil microbiome under long-term organic agriculture in transforming disease-conducive soil into disease-suppressive soils. Such practises are simple and easy to implement, and could greatly improve the sustainability and crop yield in developing countries.

Comparative Transcriptome Analysis Reveals the Genes and Pathways Related to Wheat Root Hair Length

Tube-like outgrowths from root epidermal cells, known as root hairs, enhance water and nutrient absorption, facilitate microbial interactions, and contribute to plant anchorage by expanding the root surface area. Genetically regulated and strongly influenced by environmental conditions, longer root hairs generally enhance water and nutrient absorption, correlating with increased stress resistance. Wheat, a globally predominant crop pivotal for human nutrition, necessitates the identification of long root hair genotypes and their regulatory genes to enhance nutrient capture and yield potential. This study focused on 261 wheat samples of diverse genotypes during germination, revealing noticeable disparities in the length of the root hair among the genotypes. Notably, two long root hair genotypes (W106 and W136) and two short root hair genotypes (W90 and W100) were identified. Transcriptome sequencing resulted in the development of 12 root cDNA libraries, unveiling 1180 shared differentially expressed genes (DEGs). Further analyses, including GO function annotation, KEGG enrichment, MapMan metabolic pathway analysis, and protein-protein interaction (PPI) network prediction, underscored the upregulation of root hair length regulatory genes in the long root hair genotypes. These included genes are associated with GA and BA hormone signaling pathways, FRS/FRF and bHLH transcription factors, phenylpropanoid, lignin, lignan secondary metabolic pathways, the peroxidase gene for maintaining ROS steady state, and the ankyrin gene with diverse biological functions. This study contributes valuable insights into modulating the length of wheat root hair and identifies candidate genes for the genetic improvement of wheat root traits.

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.

Biotechnology and urban agriculture: A partnership for the future sustainability

The global population is growing rapidly, and with it, the demand for food. In the coming decades, more and more people will be living in urban areas, where land for traditional agriculture is scarce. Urban agriculture can help to meet this growing demand for food in a sustainable way. Urban agriculture is the practice of growing food in urban areas. It can be done on rooftops, balconies, vacant lots, and even in alleyways. Urban agriculture can produce a variety of crops, including fruits, vegetables, and herbs. It can also help to improve air quality, reduce stormwater runoff, and create jobs. Biotechnology can be used to improve the efficiency and sustainability of urban agriculture. Biotechnological tools can be used to develop crops that are resistant to pests and diseases, that are more tolerant of drought and heat, and that have higher yields. Biotechnology can also be used to improve the nutritional value of crops. This review article discusses the need for and importance of urban agriculture, biotechnology, and genome editing in meeting the growing demand for food in urban areas. It also discusses the potential of biotechnology to improve the sustainability of urban agriculture.

Assessing Drought Tolerance in a Large Number of Upland Cotton Plants (Gossypium hirsutum L.) under Different Irrigation Regimes at the Seedling Stage

The cotton plant is important since it provides raw materials for various industry branches. Even though cotton is generally drought-tolerant, it is affected negatively by long-term drought stress. The trial was conducted according to the applied experimental design as a completely randomized design (CRD) with three replications to determine a panel of 93 cotton genotypes' genotypic responses against drought under controlled conditions in 2022. All genotypes were watered with 80 mL-1 of water (100% irrigation, field capacity) until three true leaves appeared, and then water stress was applied at a limited irrigation of 75% (60 mL-1), 50% (40 mL-1), and 25% (20 mL-1) of the field capacity. After the trial terminated at 52 days, the cv. G56, G44, G5, and G86 in RL; G1, G56, G44, G86, G51, and G88 in RFW; advanced line G5, followed by the cv. G56, advanced line G44, G75, and the cv. G90 in RDW; G44, followed by G86, the cv. G56, and elite lines G13 and G5 in NLRs were observed as drought-tolerant genotypes, respectively, while G35, G15, G26, G67, and G56 in SL; G15, G52, G60, G31, and G68 in SFW; G35, G52, G57, G41, and G60 in SDW show the highest drought tolerance means, respectively. In conclusion, the commercial varieties with high means in roots, namely G86, G56, G88, and G90, and the genotypes G67, G20, G60, and G57 showing tolerance in shoots, are suggested to be potential parent plants for developing cotton varieties resistant to drought. Using the cultivars found tolerant in the current study as parents in a drought-tolerant variety development marker-assisted selection (MAS) plant breeding program will increase the chance of success in reaching the target after genetic diversity analyses are performed. On the other hand, it is highly recommended to continue the plant breeding program with the G44, G30, G19, G1, G5, G75, G35, G15, G52, G29, and G76 genotypes, which show high tolerance in both root and shoot systems.

Recent advances in PGPR-mediated resilience toward interactive effects of drought and salt stress in plants

The present crisis at hand revolves around the need to enhance plant resilience to various environmental stresses, including abiotic and biotic stresses, to ensure sustainable agriculture and mitigate the impact of climate change on crop production. One such promising approach is the utilization of plant growth-promoting rhizobacteria (PGPR) to mediate plant resilience to these stresses. Plants are constantly exposed to various stress factors, such as drought, salinity, pathogens, and nutrient deficiencies, which can significantly reduce crop yield and quality. The PGPR are beneficial microbes that reside in the rhizosphere of plants and have been shown to positively influence plant growth and stress tolerance through various mechanisms, including nutrient solubilization, phytohormone production, and induction of systemic resistance. The review comprehensively examines the various mechanisms through which PGPR promotes plant resilience, including nutrient acquisition, hormonal regulation, and defense induction, focusing on recent research findings. The advancements made in the field of PGPR-mediated resilience through multi-omics approaches (viz., genomics, transcriptomics, proteomics, and metabolomics) to unravel the intricate interactions between PGPR and plants have been discussed including their molecular pathways involved in stress tolerance. Besides, the review also emphasizes the importance of continued research and implementation of PGPR-based strategies to address the pressing challenges facing global food security including commercialization of PGPR-based bio-formulations for sustainable agricultural.

Sulla (Hedysarum coronarium L.) Response to Drought Stress during Early Vegetative Stage

Sulla (Hedysarum coronarium L.) is a Mediterranean biannual anthelmintic forage. Due to its high productivity, nutraceutical value, and suitability for harsh environments, interest in this crop is growing. Under the current scenario of climate change and water scarcity, it is important to evaluate crop drought tolerance, especially for newly bred materials. Drought stress and well-watered conditions (50 vs. 80% of the field capacity) were applied in a pot experiment to compare responses of the widespread commercial variety Bellante with those of a recently released variety named 'Centauro', currently registered in the Italian national register of plant varieties but not yet available on the market. Compared to the well-watered treatment, drought-stressed plants showed lower values of fresh biomass (-69%), number of leaves (-68%), and root length (-49%). The Centauro cv. showed a different architecture to Bellante with more shoots (+43% P < 0.05) and a trend for more leaves (+25% P = 0.08). These traits are possibly related to its superior palatability. Centauro also developed a higher root length (+70%, P < 0.05) across irrigation levels. Drought stress affected condensed tannin (CT) content. A significant genotype × environment interaction was found with Centauro displaying more (+50%) and less (-35%) CT than Bellante under drought stress and well-watered conditions, respectively. The higher constitutive root length density of Centauro may be exploited in breeding programs aimed at improving the root sink, given the role of this trait in resource acquisition capacity and root-derived ecosystem services.

Genome-wide association studies: an intuitive solution for SNP identification and gene mapping in trees

Analysis of natural diversity in wild/cultivated plants can be used to understand the genetic basis for plant breeding programs. Recent advancements in DNA sequencing have expanded the possibilities for genetically altering essential features. There have been several recently disclosed statistical genetic methods for discovering the genes impacting target qualities. One of these useful methods is the genome-wide association study (GWAS), which effectively identifies candidate genes for a variety of plant properties by examining the relationship between a molecular marker (such as SNP) and a target trait. Conventional QTL mapping with highly structured populations has major limitations. The limited number of recombination events results in poor resolution for quantitative traits. Only two alleles at any given locus can be studied simultaneously. Conventional mapping approach fails to work in perennial plants and vegetatively propagated crops. These limitations are sidestepped by association mapping or GWAS. The flexibility of GWAS comes from the fact that the individuals being examined need not be linked to one another, allowing for the use of all meiotic and recombination events to increase resolution. Phenotyping, genotyping, population structure analysis, kinship analysis, and marker-trait association analysis are the fundamental phases of GWAS. With the rapid development of sequencing technologies and computational methods, GWAS is becoming a potent tool for identifying the natural variations that underlie complex characteristics in crops. The use of high-throughput sequencing technologies along with genotyping approaches like genotyping-by-sequencing (GBS) and restriction site associated DNA (RAD) sequencing may be highly useful in fast-forward mapping approach like GWAS. Breeders may use GWAS to quickly unravel the genomes through QTL and association mapping by taking advantage of natural variances. The drawbacks of conventional linkage mapping can be successfully overcome with the use of high-resolution mapping and the inclusion of multiple alleles in GWAS.

Spectral reflectance and fluorescence is a rapid, non-destructive tool for drought tolerance monitoring in Withania somnifera (L.) Dunal

Withania somnifera plants were exposed to drought stress for 23 days. Relative water content (RWC), gaseous exchange, fluorescence parameters, and spectral reflectance changes were monitored under drought stress. Assimilation rate and RWC decreased by 81% and 65%, respectively, during drought exposure of 23 days. Photosynthetic reflectance index (PRI) and water index (WI) showed a decreasing pattern under drought stress and correlated with Amax and RWC. Anthocyanin reflectance index and anthocyanin content increased with drought stress. Similarly, rational among R727, R696, R770, and R731 reflects chlorophyll content and Chl a/b ratio and copes with actual chlorophyll content. Fluorescence changes showed the opening and closing of PSII reaction centers, while absorbance change at 830/875 nm showed activity and energy balance of PSI. Non-photochemical quenching increased under drought, which showed depoxydation of xanthine cycle pigment. Energy balance at the acceptor and donor side of PSI adjusted under drought stress by increasing electron carrying limitation at donor side. Energy balance between PSI and PSII is maintained by increasing cyclic electron flux under mild drought stress. Both protective mechanism depoxydation of xanthine cycle pigment and enhancement of cyclic electron flux reduced or diminished under severe drought stress. Decrease in leaf area and stomatal closure may cause a reduction in transpiration that results into loss of RWC and altered physiological processes. Since fluorescence, absorbance change and spectral reflectance are non-invasive measurements that may be used as indicators for assessing drought tolerance in medicinal plants.

Variations in phenological, physiological, plant architectural and yield-related traits, their associations with grain yield and genetic basis

BACKGROUND AND AIMS

Physiological and morphological traits play essential roles in wheat (Triticum aestivum) growth and development. In particular, photosynthesis is a limitation to yield. Increasing photosynthesis in wheat has been identified as an important strategy to increase yield. However, the genotypic variations and the genomic regions governing morphological, architectural and photosynthesis traits remain unexplored.

METHODS

Here, we conducted a large-scale investigation of the phenological, physiological, plant architectural and yield-related traits, involving 32 traits for 166 wheat lines during 2018-2020 in four environments, and performed a genome-wide association study with wheat 90K and 660K single nucleotide polymorphism (SNP) arrays.

KEY RESULTS

These traits exhibited considerable genotypic variations in the wheat diversity panel. Higher yield was associated with higher net photosynthetic rate (r = 0.41, P < 0.01), thousand-grain weight (r = 0.36, P < 0.01) and truncated and lanceolate shape, but shorter plant height (r = -0.63, P < 0.01), flag leaf angle (r = -0.49, P < 0.01) and spike number per square metre (r = -0.22, P < 0.01). Genome-wide association mapping discovered 1236 significant stable loci detected in the four environments among the 32 traits using SNP markers. Trait values have a cumulative effect as the number of the favourable alleles increases, and significant progress has been made in determining phenotypic values and favourable alleles over the years. Eleven elite cultivars and 14 traits associated with grain yield per plot (GY) were identified as potential parental lines and as target traits to develop high-yielding cultivars.

CONCLUSIONS

This study provides new insights into the phenotypic and genetic elucidation of physiological and morphological traits in wheat and their associations with GY, paving the way for discovering their underlying gene control and for developing enhanced ideotypes in wheat breeding.

Genome-Wide Meta-Analysis of QTLs Associated with Root Traits and Implications for Maize Breeding

Root system architecture (RSA), also known as root morphology, is critical in plant acquisition of soil resources, plant growth, and yield formation. Many QTLs associated with RSA or root traits in maize have been identified using several bi-parental populations, particularly in response to various environmental factors. In the present study, a meta-analysis of QTLs associated with root traits was performed in maize using 917 QTLs retrieved from 43 mapping studies published from 1998 to 2020. A total of 631 QTLs were projected onto a consensus map involving 19,714 markers, which led to the prediction of 68 meta-QTLs (MQTLs). Among these 68 MQTLs, 36 MQTLs were validated with the marker-trait associations available from previous genome-wide association studies for root traits. The use of comparative genomics approaches revealed several gene models conserved among the maize, sorghum, and rice genomes. Among the conserved genomic regions, the ortho-MQTL analysis uncovered 20 maize MQTLs syntenic to 27 rice MQTLs for root traits. Functional analysis of some high-confidence MQTL regions revealed 442 gene models, which were then subjected to in silico expression analysis, yielding 235 gene models with significant expression in various tissues. Furthermore, 16 known genes viz., DXS2, PHT, RTP1, TUA4, YUC3, YUC6, RTCS1, NSA1, EIN2, NHX1, CPPS4, BIGE1, RCP1, SKUS13, YUC5, and AW330564 associated with various root traits were present within or near the MQTL regions. These results could aid in QTL cloning and pyramiding in developing new maize varieties with specific root architecture for proper plant growth and development under optimum and abiotic stress conditions.

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.

Genome-wide association study of agronomical and root-related traits in spring barley collection grown under field conditions

The root system is a key component for plant survival and productivity. In particular, under stress conditions, developing plants with a better root architecture can ensure productivity. The objectives of this study were to investigate the phenotypic variation of selected root- and yield-related traits in a diverse panel of spring barley genotypes. By performing a genome-wide association study (GWAS), we identified several associations underlying the variations occurring in root- and yield-related traits in response to natural variations in soil moisture. Here, we report the results of the GWAS based on both individual single-nucleotide polymorphism markers and linkage disequilibrium (LD) blocks of markers for 11 phenotypic traits related to plant morphology, grain quality, and root system in a group of spring barley accessions grown under field conditions. We also evaluated the root structure of these accessions by using a nondestructive method based on electrical capacitance. The results showed the importance of two LD-based blocks on chromosomes 2H and 7H in the expression of root architecture and yield-related traits. Our results revealed the importance of the region on the short arm of chromosome 2H in the expression of root- and yield-related traits. This study emphasized the pleiotropic effect of this region with respect to heading time and other important agronomic traits, including root architecture. Furthermore, this investigation provides new insights into the roles played by root traits in the yield performance of barley plants grown under natural conditions with daily variations in soil moisture content.

Anatomical and physiological responses of Aechmea blanchetiana (Bromeliaceae) induced by silicon and sodium chloride stress during in vitro culture

Salt stress is one of the most severe abiotic stresses affecting plant growth and development. The application of silicon (Si) is an alternative that can increase the tolerance of plants to various types of biotic and abiotic stresses. The objective was to evaluate salt stress's effect in vitro and Si's mitigation potential on Aechmea blanchetiana plants. For this purpose, plants already established in vitro were transferred to a culture medium with 0 or 14 µM of Si (CaSiO₃). After growth for 30 days, a stationary liquid medium containing different concentrations of NaCl (0, 100, 200, or 300 µM) was added to the flasks. Anatomical and physiological analyses were performed after growth for 45 days. The plants cultivated with excess NaCl presented reduced root diameter and effective photochemical quantum yield of photosystem II (PSII) (ΦPSII) and increased non-photochemical dissipation of fluorescence (qN). Plants that grew with the presence of Si also had greater content of photosynthetic pigments and activity of the enzymes of the antioxidant system, as well as higher values of maximum quantum yield of PSII (F_V/F_M), photochemical dissipation coefficient of fluorescence (qP) and fresh weight bioaccumulation of roots and shoots. The anatomical, physiological and biochemical responses, and growth induced by Si mitigated the effect of salt stress on the A. blanchetiana plants cultivated in vitro, which can be partly explained by the tolerance of this species to grow in sandbank (Restinga) areas.

RAV1 mediates cytokinin signaling for regulating primary root growth in Arabidopsis

Root growth dynamics is an outcome of complex hormonal crosstalk. The primary root meristem size, for example, is determined by antagonizing actions of cytokinin and auxin. Here we show that RAV1, a member of the AP2/ERF family of transcription factors, mediates cytokinin signaling in roots to regulate meristem size. The rav1 mutants have prominently longer primary roots, with a meristem that is significantly enlarged and contains higher cell numbers, compared with wild-type. The mutant phenotype could be restored on exogenous cytokinin application or by inhibiting auxin transport. At the transcript level, primary cytokinin-responsive genes like ARR1, ARR12 were significantly downregulated in the mutant root, indicating impaired cytokinin signaling. In concurrence, cytokinin induced regulation of SHY2, an Aux/IAA gene, and auxin efflux carrier PIN1 was hindered in rav1, leading to altered auxin transport and distribution. This effectively altered root meristem size in the mutant. Notably, CRF1, another member of the AP2/ERF family implicated in cytokinin signaling, is transcriptionally repressed by RAV1 to promote cytokinin response in roots. Further associating RAV1 with cytokinin signaling, our results demonstrate that cytokinin upregulates RAV1 expression through ARR1, during post-embryonic root development. Regulation of RAV1 expression is a part of secondary cytokinin response that eventually represses CRF1 to augment cytokinin signaling. To conclude, RAV1 functions in a branch pathway downstream to ARR1 that regulates CRF1 expression to enhance cytokinin action during primary root development in Arabidopsis.

Genome-wide association study in two-row spring barley landraces identifies QTL associated with plantlets root system architecture traits in well-watered and osmotic stress conditions

Water availability is undoubtedly one of the most important environmental factors affecting crop production. Drought causes a gradual deprivation of water in the soil from top to deep layers and can occur at diverse stages of plant development. Roots are the first organs that perceive water deficit in soil and their adaptive development contributes to drought adaptation. Domestication has contributed to a bottleneck in genetic diversity. Wild species or landraces represent a pool of genetic diversity that has not been exploited yet in breeding program. In this study, we used a collection of 230 two-row spring barley landraces to detect phenotypic variation in root system plasticity in response to drought and to identify new quantitative trait loci (QTL) involved in root system architecture under diverse growth conditions. For this purpose, young seedlings grown for 21 days in pouches under control and osmotic-stress conditions were phenotyped and genotyped using the barley 50k iSelect SNP array, and genome-wide association studies (GWAS) were conducted using three different GWAS methods (MLM GAPIT, FarmCPU, and BLINK) to detect genotype/phenotype associations. In total, 276 significant marker-trait associations (MTAs; p-value (FDR)< 0.05) were identified for root (14 and 12 traits under osmotic-stress and control conditions, respectively) and for three shoot traits under both conditions. In total, 52 QTL (multi-trait or identified by at least two different GWAS approaches) were investigated to identify genes representing promising candidates with a role in root development and adaptation to drought stress.

QTL analyses of soybean root system architecture revealed genetic relationships with shoot-related traits

The genetic basis of soybean root system architecture (RSA) and the genetic relationship between shoot and RSA were revealed by integrating data from recombinant inbred population grafting and QTL mapping. Variations in root system architecture (RSA) affect the functions of roots and thus play vital roles in plant adaptations and agricultural productivity. The aim of this study was to unravel the genetic relationship between RSA traits and shoot-related traits in soybean. This study characterized RSA variability at seedling stage in a recombinant inbred population, derived from a cross between cultivated soybean C08 and wild soybean W05, and performed high-resolution quantitative trait locus (QTL) mapping. In total, 34 and 41 QTLs were detected for RSA-related and shoot-related traits, respectively, constituting eight QTL clusters. Significant QTL correspondence was found between shoot biomass and RSA-related traits, consistent with significant correlations between these phenotypes. RSA-related QTLs also overlapped with selection regions in the genome, suggesting the cultivar RSA could be a partial consequence of domestication. Using reciprocal grafting, we confirmed that shoot-derived signals affected root development and the effects were controlled by multiple loci. Meanwhile, RSA-related QTLs were found to co-localize with four soybean flowering-time loci. Consistent with the phenotypes of the parental lines of our RI population, diminishing the function of flowering controlling E1 family through RNA interference (RNAi) led to reduced root growth. This implies that the flowering time-related genes within the RSA-related QTLs are actually contributing to RSA. To conclude, this study identified the QTLs that determine RSA through controlling root growth indirectly via regulating shoot functions, and discovered superior alleles from wild soybean that could be used to improve the root structure in existing soybean cultivars.

Natural selection under conventional and organic cropping systems affect root architecture in spring barley

A beneficial root system is crucial for efficient nutrient uptake and stress tolerance. Therefore, evaluating the root system variation for breeding crop plants towards stress adaptation is critically important. Here, we phenotyped root architectural traits of naturally adapted populations from organic and conventional cropping systems under hydroponic and field trails. Long-term natural selection under these two cropping systems resulted in a microevolution of root morphological and anatomical traits. Barley lines developed under an organic system possessed longer roots with narrow root angle, larger surface area, increased root mass density, and a thinner root diameter with an increased number of metaxylem vessels. In contrast, lines adapted to the conventional system tend to have a shorter and wider root system with a larger root volume with a thicker diameter but fewer metaxylem vessels. Allometry analysis established a relationship between root traits and plant size among barley genotypes, which specifies that root angle could be a good candidate among studied root traits to determine root-borne shoot architecture. Further, multivariate analyses showed a strong tendency towards increased variability of the organically adapted population's root morphological and anatomical traits. The genotyping of ancestor populations validated the observations made in these experiments. Collectively, this results indicate significant differences in root phenotypes between conventional and organic populations, which could be useful in comparative genomics and breeding.

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.

Root system architecture for abiotic stress tolerance in potato: Lessons from plants

The root is an important plant organ, which uptakes nutrients and water from the soil, and provides anchorage for the plant. Abiotic stresses like heat, drought, nutrients, salinity, and cold are the major problems of potato cultivation. Substantial research advances have been achieved in cereals and model plants on root system architecture (RSA), and so root ideotype (e.g., maize) have been developed for efficient nutrient capture to enhance nutrient use efficiency along with genes regulating root architecture in plants. However, limited work is available on potatoes, with a few illustrations on root morphology in drought and nitrogen stress. The role of root architecture in potatoes has been investigated to some extent under heat, drought, and nitrogen stresses. Hence, this mini-review aims to update knowledge and prospects of strengthening RSA research by applying multi-disciplinary physiological, biochemical, and molecular approaches to abiotic stress tolerance to potatoes with lessons learned from model plants, cereals, and other plants.

Root system architecture in rice: impacts of genes, phytohormones and root microbiota

To feed the continuously expanding world's population, new crop varieties have been generated, which significantly contribute to the world's food security. However, the growth of these improved plant varieties relies primarily on synthetic fertilizers, which negatively affect the environment and human health; therefore, continuous improvement is needed for sustainable agriculture. Several plants, including cereal crops, have the adaptive capability to combat adverse environmental changes by altering physiological and molecular mechanisms and modifying their root system to improve nutrient uptake efficiency. These plants operate distinct pathways at various developmental stages to optimally establish their root system. These processes include changes in the expression profile of genes, changes in phytohormone level, and microbiome-induced root system architecture (RSA) modification. Several studies have been performed to understand microbial colonization and their involvement in RSA improvement through changes in phytohormone and transcriptomic levels. This review highlights the impact of genes, phytohormones, and particularly root microbiota in influencing RSA and provides new insights resulting from recent studies on rice root as a model system and summarizes the current knowledge about biochemical and central molecular mechanisms.

Kalanchoë blossfeldiana naturally transformed with Rhizobium rhizogenes exhibits superior root phenotype

Plant transformation with root oncogenic loci (rol) genes and open reading frames (ORFs) from Rhizobium rhizogenes have not yet targeted the underground root phenotype of these transformants. Hence, there is a need to develop plants with more efficient root system architecture (RSA). Here, RSA was assessed in naturally transformed (NT) and single rol/ORF Kalanchoë blossfeldiana 'Molly' lines in an aeroponic growth system combined with gene expression analysis. Three NT lines; 306, 324 and 331; exhibited better-developed RSA with longer roots and increased root biomass. In line 306, longest root was 6.3 ± 0.3 cm while WT had 4.8 ± 0.1 cm. However, root length of all overexpressing lines was ca. 30% shorter than WT. Root fresh weight of NT lines was 4.5-fold higher than WT. The expression of rolB, ∆ORF13a and ORF14 in the leaves of overexpressing lines was many folds higher than in NT lines. Increased expression of ∆ORF13a and ORF14 in leaves and roots may contribute more to a stronger compact phenotype than previously assumed. The moderate compact phenotype of NT lines combined with improved RSA compared to the overexpressing lines and WT strongly indicate that the use of R. rhizogenes has great potential to produce Kalanchoë phenotypes with enhanced RSA.

Efforts towards overcoming drought stress in crops: Revisiting the mechanisms employed by plant growth-promoting bacteria

Globally, agriculture is under a lot of pressure due to rising population and corresponding increases in food demand. However, several variables, including improper mechanization, limited arable land, and the presence of several biotic and abiotic pressures, continually impact agricultural productivity. Drought is a notable destructive abiotic stress and may be the most serious challenge confronting sustainable agriculture, resulting in a significant crop output deficiency. Numerous morphological and physiological changes occur in plants as a result of drought stress. Hence, there is a need to create mitigation techniques since these changes might permanently harm the plant. Current methods used to reduce the effects of drought stress include the use of film farming, super-absorbent hydrogels, nanoparticles, biochar, and drought-resistant plant cultivars. However, most of these activities are money and labor-intensive, which offer limited plant improvement. The use of plant-growth-promoting bacteria (PGPB) has proven to be a preferred method that offers several indirect and direct advantages in drought mitigation. PGPB are critical biological elements which have favorable impacts on plants’ biochemical and physiological features, leading to improved sugar production, relative water content, leaf number, ascorbic acid levels, and photosynthetic pigment quantities. This present review revisited the impacts of PGPB in ameliorating the detrimental effects of drought stress on plants, explored the mechanism of action employed, as well as the major challenges encountered in their application for plant growth and 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.

Arabidopsis weep mutants exhibit narrow root angles

Peach ( Prunus persica ) trees with a mutation in the weep gene exhibit a weeping branch phenotype. In contrast, Arabidopsis ( Arabidopsis thaliana ) weep mutants do not have a shoot architecture phenotype. A recent report revealed that barley ( Hordeum vulgare ) and wheat ( Triticum aestivum ) with mutations in EGT2, a WEEP homolog, have steeper root angles than standard varieties. We investigated the root architecture of three Arabidopsis weep mutant lines. All three lines exhibited steeper root angles and a smaller convex hull area, indicating that the total area explored by the root system is reduced. These results reveal WEEP is important for regulating lateral root angles in a dicot.

Intraspecific Variation for Leaf Physiological and Root Morphological Adaptation to Drought Stress in Alfalfa (Medicago sativa L.)

Drought stress reduces crop biomass yield and the profitability of rainfed agricultural systems. Evaluation of populations or accessions adapted to diverse geographical and agro-climatic environments sheds light on beneficial plant responses to enhance and optimize yield in resource-limited environments. This study used the morphological and physiological characteristics of leaves and roots from two different alfalfa subspecies during progressive drought stress imposed on controlled and field conditions. Two different soils (Experiments 1 and 2) imposed water stress at different stress intensities and crop stages in the controlled environment. Algorithm-based image analysis of leaves and root systems revealed key morphological and physiological traits associated with biomass yield under stress. The Medicago sativa subspecies (ssp.) sativa population, PI478573, had smaller leaves and maintained higher chlorophyll content (CC), leaf water potential, and osmotic potential under water stress. In contrast, M. sativa ssp. varia, PI502521, had larger leaves, a robust root system, and more biomass yield. In the field study, an unmanned aerial vehicle survey revealed PI502521 to have a higher normalized difference vegetation index (vegetation cover and plant health characteristics) throughout the cropping season, whereas PI478573 values were low during the hot summer and yielded low biomass in both irrigated and rainfed treatments. RhizoVision Explorer image analysis of excavated roots revealed a smaller diameter and a narrow root angle as target traits to increase alfalfa biomass yield irrespective of water availability. Root architectural traits such as network area, solidity, volume, surface area, and maximum radius exhibited significant variation at the genotype level only under limited water availability. Different drought-adaptive strategies identified across subspecies populations will benefit the plant under varying levels of water limitation and facilitate the development of alfalfa cultivars suitable across a broad range of growing conditions. The alleles from both subspecies will enable the development of drought-tolerant alfalfa with enhanced productivity under limited water availability.

Foliar-applied cerium oxide nanomaterials improve maize yield under salinity stress: Reactive oxygen species homeostasis and rhizobacteria regulation

Salinity stress seriously threatens agricultural productivity and food security worldwide. This work reports on the mechanisms of alleviating salinity stress by cerium oxide nanomaterials (CeO2 NMs) in maize (Zea may L.). Soil-grown maize plants were irrigated with deionized water or 100 mM NaCl solution as the control or the salinity stress treatment. CeO2 NMs (1, 5, 10, 20, and 50 mg/L) with antioxidative enzyme mimicking activities were foliarly applied on maize leaves for 7 days. The morphological, physiological, biochemical, and transcriptomic responses of maize were evaluated. Specifically, salinity stress significantly reduced 59.0% and 63.8% in maize fresh and dry biomass, respectively. CeO₂ NMs at 10, 20, and 50 mg/L improved the salt tolerance of maize by 69.5%, 69.1%, and 86.8%, respectively. Also, 10 mg/L CeO₂ NMs maintained Na⁺/K⁺ homeostasis, enhanced photosynthetic efficiency by 30.8%, and decreased reactive oxygen species (ROS) level by 58.5% in salt-stressed maize leaves. Transcriptomic analysis revealed that the antioxidative defense system-related genes recovered to the normal control level after CeO₂ NMs application, indicating that CeO₂ NMs eliminated ROS through their intrinsic antioxidative enzyme properties. The down-regulation of genes related to lignin synthesis in the phenylpropanoid biosynthesis pathway accelerated leaf cell elongation. In addition, CeO₂ NMs increased the rhizobacteria richness and diversity through the increment of carbon source in root exudates and improved the abundance of halotolerant plant growth-promoting rhizobacteria (HT-PGPR). Importantly, the yield of salt-stressed maize was enhanced by 293.3% after 10 mg/L CeO₂ NMs foliar application. These results will provide new insights for the application of CeO₂ NMs in management to reduce the salinity-caused crop loss.

Objective Phenotyping of Root System Architecture Using Image Augmentation and Machine Learning in Alfalfa (Medicago sativa L.)

Active breeding programs specifically for root system architecture (RSA) phenotypes remain rare; however, breeding for branch and taproot types in the perennial crop alfalfa is ongoing. Phenotyping in this and other crops for active RSA breeding has mostly used visual scoring of specific traits or subjective classification into different root types. While image-based methods have been developed, translation to applied breeding is limited. This research is aimed at developing and comparing image-based RSA phenotyping methods using machine and deep learning algorithms for objective classification of 617 root images from mature alfalfa plants collected from the field to support the ongoing breeding efforts. Our results show that unsupervised machine learning tends to incorrectly classify roots into a normal distribution with most lines predicted as the intermediate root type. Encouragingly, random forest and TensorFlow-based neural networks can classify the root types into branch-type, taproot-type, and an intermediate taproot-branch type with 86% accuracy. With image augmentation, the prediction accuracy was improved to 97%. Coupling the predicted root type with its prediction probability will give breeders a confidence level for better decisions to advance the best and exclude the worst lines from their breeding program. This machine and deep learning approach enables accurate classification of the RSA phenotypes for genomic breeding of climate-resilient alfalfa.

Root system architecture in cereals: progress, challenges and perspective

Roots are essential multifunctional plant organs involved in water and nutrient uptake, metabolite storage, anchorage, mechanical support, and interaction with the soil environment. Understanding of this 'hidden half' provides potential for manipulation of root system architecture (RSA) traits to optimize resource use efficiency and grain yield in cereal crops. Unfortunately, root traits are highly neglected in breeding due to the challenges of phenotyping, but could have large rewards if the variability in RSA traits can be fully exploited. Until now, a plethora of genes have been characterized in detail for their potential role in improving RSA. The use of forward genetics approaches to find sequence variations in genes underpinning desirable RSA would be highly beneficial. Advances in computer vision applications have allowed image-based approaches for high-throughput phenotyping of RSA traits that can be used by any laboratory worldwide to make progress in understanding root function and dissection of the genetics. At the same time, the frontiers of root measurement include non-invasive methods like X-ray computer tomography and magnetic resonance imaging that facilitate new types of temporal studies. Root physiology and ecology are further supported by spatiotemporal root simulation modeling. The discovery of component traits providing improved resilience and yield advantage in target environments is a key necessity for mainstreaming root-based cereal breeding. The integrated use of pan-genome resources, now available in most cereals, coupled with new in-field phenotyping platforms has the potential for precise selection of superior genotypes with improved RSA.

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

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

Improving Soil Resource Uptake by Plants Through Capitalizing on Synergies Between Root Architecture and Anatomy and Root-Associated Microorganisms

Root architectural and anatomical phenotypes are highly diverse. Specific root phenotypes can be associated with better plant growth under low nutrient and water availability. Therefore, root ideotypes have been proposed as breeding targets for more stress-resilient and resource-efficient crops. For example, root phenotypes that correspond to the Topsoil Foraging ideotype are associated with better plant growth under suboptimal phosphorus availability, and root phenotypes that correspond to the Steep, Cheap and Deep ideotype are linked to better performance under suboptimal availability of nitrogen and water. We propose that natural variation in root phenotypes translates into a diversity of different niches for microbial associations in the rhizosphere, rhizoplane and root cortex, and that microbial traits could have synergistic effects with the beneficial effect of specific root phenotypes. Oxygen and water content, carbon rhizodeposition, nutrient availability, and root surface area are all factors that are modified by root anatomy and architecture and determine the structure and function of the associated microbial communities. Recent research results indicate that root characteristics that may modify microbial communities associated with maize include aerenchyma, rooting angle, root hairs, and lateral root branching density. Therefore, the selection of root phenotypes linked to better plant growth under specific edaphic conditions should be accompanied by investigating and selecting microbial partners better adapted to each set of conditions created by the corresponding root phenotype. Microbial traits such as nitrogen transformation, phosphorus solubilization, and water retention could have synergistic effects when correctly matched with promising plant root ideotypes for improved nutrient and water capture. We propose that elucidation of the interactive effects of root phenotypes and microbial functions on plant nutrient and water uptake offers new opportunities to increase crop yields and agroecosystem sustainability.

Optimisation of root traits to provide enhanced ecosystem services in agricultural systems: A focus on cover crops

Roots are the interface between the plant and the soil and play a central role in multiple ecosystem processes. With intensification of agricultural practices, rhizosphere processes are being disrupted and are causing degradation of the physical, chemical and biotic properties of soil. However, cover crops, a group of plants that provide ecosystem services, can be utilised during fallow periods or used as an intercrop to restore soil health. The effectiveness of ecosystem services provided by cover crops varies widely as very little breeding has occurred in these species. Improvement of ecosystem service performance is rarely considered as a breeding trait due to the complexities and challenges of belowground evaluation. Advancements in root phenotyping and genetic tools are critical in accelerating ecosystem service improvement in cover crops. In this study, we provide an overview of the range of belowground ecosystem services provided by cover crop roots: (1) soil structural remediation, (2) capture of soil resources and (3) maintenance of the rhizosphere and building of organic matter content. Based on the ecosystem services described, we outline current and promising phenotyping technologies and breeding strategies in cover crops that can enhance agricultural sustainability through improvement of root traits.

Genetic Variability of Arabidopsis thaliana Mature Root System Architecture and Genome-Wide Association Study

Root system architecture (RSA) has a direct influence on the efficiency of nutrient uptake and plant growth, but the genetics of RSA are often studied only at the seedling stage. To get an insight into the genetic blueprint of a more mature RSA, we exploited natural variation and performed a detailed in vitro study of 241 Arabidopsis thaliana accessions using large petri dishes. A comprehensive analysis of 17 RSA traits showed high variability among the different accessions, unveiling correlations between traits and conditions of the natural habitat of the plants. A sub-selection of these accessions was grown in water-limiting conditions in a rhizotron set-up, which revealed that especially the spatial distribution showed a high consistency between in vitro and ex vitro conditions, while in particular, a large root area in the lower zone favored drought tolerance. The collected RSA phenotype data were used to perform genome-wide association studies (GWAS), which stands out from the previous studies by its exhaustive measurements of RSA traits on more mature Arabidopsis accessions used for GWAS. As a result, we found not only several genes involved in the lateral root (LR) development or auxin signaling pathways to be associated with RSA traits but also new candidate genes that are potentially involved in the adaptation to the natural habitats.

Apoplastic histochemical features of plant root walls that may facilitate ion uptake and retention

We used brightfield and epifluorescence microscopy, as well as permeability tests, to investigate the apoplastic histochemical features of plant roots associated with ion hyperaccumulation, invasion, and tolerance of oligotrophic conditions. In hyperaccumulator species with a hypodermis (exodermis absent), ions penetrated the root apex, including the root cap. By contrast, in non-hyperaccumulator species possessing an exodermis, ions did not penetrate the root cap. In vivo, the lignified hypodermis blocked the entry of ions into the cortex, while root exodermis absorbed ions and restricted them to the cortex. The roots of the hyperaccumulators Pteris vittata and Cardamine hupingshanensis, as well as the aquatic invasives Alternanthera philoxeroides, Eichhornia crassipes, and Pistia stratiotes, contained lignin and pectins. These compounds may trap and store ions before hypodermis maturation, facilitating ion hyperaccumulation and retention in the apoplastic spaces of the roots. These apoplastic histochemical features were consistent with certain species-specific characters, including ion hyperaccumulation, invasive behaviors in aquatic environments, or tolerance of oligotrophic conditions. We suggest that apoplastic histochemical features of the root may act as invasion mechanisms, allowing these invasive aquatic plants to outcompete indigenous plants for ions.

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.

A stress-related transcription factor belonging to the YL-1 family is differently regulated in durum wheat cultivars differing in drought sensitivity

The Mediterranean area is characterised by unfavorable environmental conditions such as heat stress and drought responsible for yield loss of crops like durum wheat, widely cultivated in this area. The response of plants to stressing environments is mediated by activation of a complex gene network, strictly related to the genetic background. Among the genes induced by drought, those coding for proteins acting as key regulators of signal transduction are of great interest. Characterization of these genes is a crucial point to understand their potential roles in plant stress response, also in view of their possible use in molecular breeding. In this work we have characterised a Triticum durum gene, named TdDRG1, in two commercial cultivars, Primadur and Svevo, differing for drought stress resistance. TdDRG1 codes for a putative transcription factor belonging to the VPS72/YL-1 family, highly conserved in plants and animals. The expression analysis indicates that this gene is expressed at higher level in roots of the resistant cultivar Svevo, than in the susceptible Primadur. The gene structure was determined in both cultivars and the regulatory activity of 5' upstream regions was analyzed by transient expression analysis using tobacco protoplasts. Dissimilar expression level of TdDRG1 in the two cultivars can be explained by the differences observed in gene structure. In particular, differences in 5' upstream regions could account for contrasting ability to cope with drought of the two cultivars. The data obtained in this study provide indications for further insight into the molecular basis of differences in drought stress response.

Plant Gravitropism: From Mechanistic Insights into Plant Function on Earth to Plants Colonizing Other Worlds

Gravitropism, the growth of roots and shoots toward or away from the direction of gravity, has been studied for centuries. Such studies have not only led to a better understanding of the gravitropic process itself, but also paved new paths leading to deeper mechanistic insights into a wide range of research areas. These include hormone biology, cell signal transduction, regulation of gene expression, plant evolution, and plant interactions with a variety of environmental stimuli. In addition to contributions to basic knowledge about how plants function, there is accumulating evidence that gravitropism confers adaptive advantages to crops, particularly under marginal agricultural soils. Therefore, gravitropism is emerging as a breeding target for enhancing agricultural productivity. Moreover, research on gravitropism has spawned several studies on plant growth in microgravity that have enabled researchers to uncouple the effects of gravity from other tropisms. Although rapid progress on understanding gravitropism witnessed during the past decade continues to be driven by traditional molecular, physiological, and cell biological tools, these tools have been enriched by technological innovations in next-generation omics platforms and microgravity analog facilities. In this chapter, we review the field of gravitropism by highlighting recent landmark studies that have provided unique insights into this classic research topic while also discussing potential contributions to agriculture on Earth and beyond.

Pinpointing genomic regions associated with root system architecture in rice through an integrative meta-analysis approach

Applying an integrated meta-analysis approach led to identification of meta-QTLs/ candidate genes associated with rice root system architecture, which can be used in MQTL-assisted breeding/ genetic engineering of root traits. Root system architecture (RSA) is an important factor for facilitating water and nutrient uptake from deep soils and adaptation to drought stress conditions. In the present research, an integrated meta-analysis approach was employed to find candidate genes and genomic regions involved in rice RSA traits. A whole-genome meta-analysis was performed for 425 initial QTLs reported in 34 independent experiments controlling RSA traits under control and drought stress conditions in the previous twenty years. Sixty-four consensus meta-QTLs (MQTLs) were detected, unevenly distributed on twelve rice chromosomes. The confidence interval (CI) of the identified MQTLs was obtained as 0.11-14.23 cM with an average of 3.79 cM, which was 3.88 times narrower than the mean CI of the original QTLs. Interestingly, 52 MQTLs were co-located with SNP peak positions reported in rice genome-wide association studies (GWAS) for root morphological traits. The genes located in these RSA-related MQTLs were detected and explored to find the drought-responsive genes in the rice root based on the RNA-seq and microarray data. Multiple RSA and drought tolerance-associated genes were found in the MQTLs including the genes involved in auxin biosynthesis or signaling (e.g. YUCCA, WOX, AUX/IAA, ARF), root angle (DRO1-related genes), lateral root development (e.g. DSR, WRKY), root diameter (e.g. OsNAC5), plant cell wall (e.g. EXPA), and lignification (e.g. C4H, PAL, PRX and CAD). The genes located within both the SNP peak positions and the QTL-overview peaks for RSA are suggested as novel candidate genes for further functional analysis. The promising candidate genes and MQTLs can be used as basis for genetic engineering and MQTL-assisted breeding of root phenotypes to improve yield potential, stability and performance in a water-stressed environment.

TopoRoot: a method for computing hierarchy and fine-grained traits of maize roots from 3D imaging

BACKGROUND

3D imaging, such as X-ray CT and MRI, has been widely deployed to study plant root structures. Many computational tools exist to extract coarse-grained features from 3D root images, such as total volume, root number and total root length. However, methods that can accurately and efficiently compute fine-grained root traits, such as root number and geometry at each hierarchy level, are still lacking. These traits would allow biologists to gain deeper insights into the root system architecture.

RESULTS

We present TopoRoot, a high-throughput computational method that computes fine-grained architectural traits from 3D images of maize root crowns or root systems. These traits include the number, length, thickness, angle, tortuosity, and number of children for the roots at each level of the hierarchy. TopoRoot combines state-of-the-art algorithms in computer graphics, such as topological simplification and geometric skeletonization, with customized heuristics for robustly obtaining the branching structure and hierarchical information. TopoRoot is validated on both CT scans of excavated field-grown root crowns and simulated images of root systems, and in both cases, it was shown to improve the accuracy of traits over existing methods. TopoRoot runs within a few minutes on a desktop workstation for images at the resolution range of 400^3, with minimal need for human intervention in the form of setting three intensity thresholds per image.

CONCLUSIONS

TopoRoot improves the state-of-the-art methods in obtaining more accurate and comprehensive fine-grained traits of maize roots from 3D imaging. The automation and efficiency make TopoRoot suitable for batch processing on large numbers of root images. Our method is thus useful for phenomic studies aimed at finding the genetic basis behind root system architecture and the subsequent development of more productive crops.

Phenotyping seedlings for selection of root system architecture in alfalfa (Medicago sativa L.)

BACKGROUND

The root system architecture (RSA) of alfalfa (Medicago sativa L.) affects biomass production by influencing water and nutrient uptake, including nitrogen fixation. Further, roots are important for storing carbohydrates that are needed for regrowth in spring and after each harvest. Previous selection for a greater number of branched and fibrous roots significantly increased alfalfa biomass yield. However, phenotyping root systems of mature alfalfa plant is labor-intensive, time-consuming, and subject to environmental variability and human error. High-throughput and detailed phenotyping methods are needed to accelerate the development of alfalfa germplasm with distinct RSAs adapted to specific environmental conditions and for enhancing productivity in elite germplasm. In this study methods were developed for phenotyping 14-day-old alfalfa seedlings to identify measurable root traits that are highly heritable and can differentiate plants with either a branched or a tap rooted phenotype. Plants were grown in a soil-free mixture under controlled conditions, then the root systems were imaged with a flatbed scanner and measured using WinRhizo software.

RESULTS

The branched root plants had a significantly greater number of tertiary roots and significantly longer tertiary roots relative to the tap rooted plants. Additionally, the branch rooted population had significantly more secondary roots > 2.5 cm relative to the tap rooted population. These two parameters distinguishing phenotypes were confirmed using two machine learning algorithms, Random Forest and Gradient Boosting Machines. Plants selected as seedlings for the branch rooted or tap rooted phenotypes were used in crossing blocks that resulted in a genetic gain of 10%, consistent with the previous selection strategy that utilized manual root scoring to phenotype 22-week-old-plants. Heritability analysis of various root architecture parameters from selected seedlings showed tertiary root length and number are highly heritable with values of 0.74 and 0.79, respectively.

CONCLUSIONS

The results show that seedling root phenotyping is a reliable tool that can be used for alfalfa germplasm selection and breeding. Phenotypic selection of RSA in seedlings reduced time for selection by 20 weeks, significantly accelerating the breeding cycle.

Omics-Facilitated Crop Improvement for Climate Resilience and Superior Nutritive Value

Novel crop improvement approaches, including those that facilitate for the exploitation of crop wild relatives and underutilized species harboring the much-needed natural allelic variation are indispensable if we are to develop climate-smart crops with enhanced abiotic and biotic stress tolerance, higher nutritive value, and superior traits of agronomic importance. Top among these approaches are the "omics" technologies, including genomics, transcriptomics, proteomics, metabolomics, phenomics, and their integration, whose deployment has been vital in revealing several key genes, proteins and metabolic pathways underlying numerous traits of agronomic importance, and aiding marker-assisted breeding in major crop species. Here, citing several relevant examples, we appraise our understanding on the recent developments in omics technologies and how they are driving our quest to breed climate resilient crops. Large-scale genome resequencing, pan-genomes and genome-wide association studies are aiding the identification and analysis of species-level genome variations, whilst RNA-sequencing driven transcriptomics has provided unprecedented opportunities for conducting crop abiotic and biotic stress response studies. Meanwhile, single cell transcriptomics is slowly becoming an indispensable tool for decoding cell-specific stress responses, although several technical and experimental design challenges still need to be resolved. Additionally, the refinement of the conventional techniques and advent of modern, high-resolution proteomics technologies necessitated a gradual shift from the general descriptive studies of plant protein abundances to large scale analysis of protein-metabolite interactions. Especially, metabolomics is currently receiving special attention, owing to the role metabolites play as metabolic intermediates and close links to the phenotypic expression. Further, high throughput phenomics applications are driving the targeting of new research domains such as root system architecture analysis, and exploration of plant root-associated microbes for improved crop health and climate resilience. Overall, coupling these multi-omics technologies to modern plant breeding and genetic engineering methods ensures an all-encompassing approach to developing nutritionally-rich and climate-smart crops whose productivity can sustainably and sufficiently meet the current and future food, nutrition and energy demands.

Quantitative Proteome and PTMome Analysis of Arabidopsis thaliana Root Responses to Persistent Osmotic and Salinity Stress

Abiotic stresses such as drought result in large annual economic losses around the world. As sessile organisms, plants cannot escape the environmental stresses they encounter but instead must adapt to survive. Studies investigating plant responses to osmotic and/or salt stress have largely focused on short-term systemic responses, leaving our understanding of intermediate to longer-term adaptation (24 h to d) lacking. In addition to protein abundance and phosphorylation changes, evidence suggests reversible lysine acetylation may also be important for abiotic stress responses. Therefore, to characterize the protein-level effects of osmotic and salt stress, we undertook a label-free proteomic analysis of Arabidopsis thaliana roots exposed to 300 mM mannitol and 150 mM NaCl for 24 h. We assessed protein phosphorylation, lysine acetylation and changes in protein abundance, detecting significant changes in 245, 35 and 107 total proteins, respectively. Comparison with available transcriptome data indicates that transcriptome- and proteome-level changes occur in parallel, while post-translational modifications (PTMs) do not. Further, we find significant changes in PTMs, and protein abundance involve different proteins from the same networks, indicating a multifaceted regulatory approach to prolonged osmotic and salt stress. In particular, we find extensive protein-level changes involving sulfur metabolism under both osmotic and salt conditions as well as changes in protein kinases and transcription factors that may represent new targets for drought stress signaling. Collectively, we find that protein-level changes continue to occur in plant roots 24 h from the onset of osmotic and salt stress and that these changes differ across multiple proteome levels.

DIRT/3D: 3D root phenotyping for field-grown maize (Zea mays)

The development of crops with deeper roots holds substantial promise to mitigate the consequences of climate change. Deeper roots are an essential factor to improve water uptake as a way to enhance crop resilience to drought, to increase nitrogen capture, to reduce fertilizer inputs, and to increase carbon sequestration from the atmosphere to improve soil organic fertility. A major bottleneck to achieving these improvements is high-throughput phenotyping to quantify root phenotypes of field-grown roots. We address this bottleneck with Digital Imaging of Root Traits (DIRT)/3D, an image-based 3D root phenotyping platform, which measures 18 architecture traits from mature field-grown maize (Zea mays) root crowns (RCs) excavated with the Shovelomics technique. DIRT/3D reliably computed all 18 traits, including distance between whorls and the number, angles, and diameters of nodal roots, on a test panel of 12 contrasting maize genotypes. The computed results were validated through comparison with manual measurements. Overall, we observed a coefficient of determination of r2>0.84 and a high broad-sense heritability of Hmean2> 0.6 for all but one trait. The average values of the 18 traits and a developed descriptor to characterize complete root architecture distinguished all genotypes. DIRT/3D is a step toward automated quantification of highly occluded maize RCs. Therefore, DIRT/3D supports breeders and root biologists in improving carbon sequestration and food security in the face of the adverse effects of climate change.

Characterization of Dynamic Regulatory Gene and Protein Networks in Wheat Roots Upon Perceiving Water Deficit Through Comparative Transcriptomics Survey

A well-developed root system benefits host plants by optimizing water absorption and nutrient uptake and thereby increases plant productivity. In this study we have characterized the root transcriptome using RNA-seq and subsequential functional analysis in a set of drought tolerant and susceptible genotypes. The goal of the study was to elucidate and characterize water deficit-responsive genes in wheat landraces that had been through long-term field and biochemical screening for drought tolerance. The results confirm genotype differences in water-deficit tolerance in line with earlier results from field trials. The transcriptomics survey highlighted a total of 14,187 differentially expressed genes (DEGs) that responded to water deficit. The characterization of these genes shows that all chromosomes contribute to water-deficit tolerance, but to different degrees, and the B genome showed higher involvement than the A and D genomes. The DEGs were mainly mapped to flavonoid, phenylpropanoid, and diterpenoid biosynthesis pathways, as well as glutathione metabolism and hormone signaling. Furthermore, extracellular region, apoplast, cell periphery, and external encapsulating structure were the main water deficit-responsive cellular components in roots. A total of 1,377 DEGs were also predicted to function as transcription factors (TFs) from different families regulating downstream cascades. TFs from the AP2/ERF-ERF, MYB-related, B3, WRKY, Tify, and NAC families were the main genotype-specific regulatory factors. To further characterize the dynamic biosynthetic pathways, protein-protein interaction (PPI) networks were constructed using significant KEGG proteins and putative TFs. In PPIs, enzymes from the CYP450, TaABA8OH2, PAL, and GST families play important roles in water-deficit tolerance in connection with MYB13-1, MADS-box, and NAC transcription factors.