Soybean Root System Research Articles

The WRKY Family Transcription Factor GmWRKY72 Represses Glyceollin Phytoalexin Biosynthesis in Soybean

Phytoalexins are plant defense metabolites that are biosynthesized transiently in response to pathogens. Despite that their biosynthesis is highly restricted in plant tissues, the transcription factors that negatively regulate phytoalexin biosynthesis remain largely unknown. Glyceollins are isoflavonoid-derived phytoalexins that have critical roles in protecting soybean crops from the oomycete pathogen Phytophthora sojae. To identify regulators of glyceollin biosynthesis, we used a transcriptomics approach to search for transcription factors that are co-expressed with glyceollin biosynthesis in soybean and stilbene synthase phytoalexin genes in grapevine. We identified and functionally characterized the WRKY family protein GmWRKY72, which is one of four WRKY72-type transcription factors of soybean. Overexpressing and RNA interference silencing of GmWRKY72 in the soybean hairy root system decreased and increased expression of glyceollin biosynthetic genes and metabolites, respectively, in response to wall glucan elicitor from P. sojae. A translational fusion with green fluorescent protein demonstrated that GFP-GmWRKY72 localizes mainly to the nucleus of soybean cells. The GmWRKY72 protein directly interacts with several glyceollin biosynthetic gene promoters and the glyceollin transcription factor proteins GmNAC42-1 and GmMYB29A1 in yeast hybrid systems. The results show that GmWRKY72 is a negative regulator of glyceollin biosynthesis that may repress biosynthetic gene expression by interacting with transcription factor proteins and the DNA of glyceollin biosynthetic genes.

Additional organic and bacterium fertilizer input regulated soybean root architecture and dry matter distribution for a sustainable yield in the semi-arid Region of China.

In the dryland area of the Loess Plateau in northwest China, long-term excessive fertilization has led to soil compaction and nutrient loss, which in turn limits crop yield and soil productivity. To address this issue, we conducted experiments using environmentally friendly organic fertilizer and bacterium fertilizer. Our goal was to investigate the effects of additional organic and bacterium fertilizer inputs on soil water migration, crop root architecture, and yield formation. We implemented six different fertilizer strategies, namely: Nm (mulching, N 30 kg/ha), NPK1m (mulching, N 60 kg/ha; P 30 kg/ha; K 30 kg/ha), NPK2m (mulching, N 90 kg/ha; P 45 kg/ha; K 30 kg/ha), NPKOm (mulching, N 90 kg/ha; P 45 kg/ha; K 30 kg/ha; organic fertilizer 2 t/ha), NPKBm (mulching, N 60 kg/ha; P 30 kg/ha; K 30 kg/ha; bacterium fertilizer 10 kg/ha), and N (N 30 kg/ha; no mulching). The results revealed that the addition of bacterium fertilizer (NPKBm) had a positive impact on soybean root system development. Compared with the other treatments, it significantly increased the total root length, total root surface area, and total root length density by 25.96% ~ 94.89%, -19.63% ~ 36.28%, and 9.36% ~ 28.84%, respectively. Furthermore, NPKBm enhanced soil water consumption. In 2018, water storage during the flowering and podding periods decreased by 12.63% and 19.65%, respectively, while water consumption increased by 0.97% compared to Nm. In 2019, the flowering and harvest periods decreased by 23.49% and 11.51%, respectively, while water consumption increased by 0.65%. Ultimately, NPKBm achieved high grain yield and significantly increased water use efficiency (WUE), surpassing other treatments by 76.79% ~ 78.97% and 71.22% ~ 73.76%, respectively. Subsequently, NPK1m also exhibited significant increases in yield and WUE, with improvements of 35.58% ~ 39.27% and 35.26% ~ 38.16%, respectively. The use of bacterium fertilizer has a profound impact on soybean root architecture, leading to stable and sustainable grain yield production.

Single-cell transcriptome atlases of soybean root and mature nodule reveal new regulatory programs that control the nodulation process

The soybean root system is complex. In addition to being composed of various cell types, the soybean root system includes the primary root, the lateral roots, and the nodule, an organ in which mutualistic symbiosis with N-fixing rhizobia occurs. A mature soybean root nodule is characterized by a central infection zone where atmospheric nitrogen is fixed and assimilated by the symbiont, resulting from the close cooperation between the plant cell and the bacteria. To date, the transcriptome of individual cells isolated from developing soybean nodules has been established, but the transcriptomic signatures of cells from the mature soybean nodule have not yet been characterized. Using single-nucleus RNA-seq and Molecular Cartography technologies, we precisely characterized the transcriptomic signature of soybean root and mature nodule cell types and revealed the co-existence of different sub-populations of B. diazoefficiens–infected cells in the mature soybean nodule, including those actively involved in nitrogen fixation and those engaged in senescence. Mining of the single-cell-resolution nodule transcriptome atlas and the associated gene co-expression network confirmed the role of known nodulation-related genes and identified new genes that control the nodulation process. For instance, we functionally characterized the role of GmFWL3, a plasma membrane microdomain-associated protein that controls rhizobial infection. Our study reveals the unique cellular complexity of the mature soybean nodule and helps redefine the concept of cell types when considering the infection zone of the soybean nodule.

Transcriptomic investigation unveils the role of energy metabolism under low phosphorus and salt combined stress in soybean (Glycine max).

Soybean (Glycine max) is economically significant, but the mechanisms underlying its adaptation to simultaneous low phosphorus and salt stresses are unclear. We employed the Shennong 94-1-8 soybean germplasm to conduct a comprehensive analysis, integrating both physiochemical and transcriptomic approaches, to unravel the response mechanisms of soybean when subjected to simultaneous low phosphorus and salt stresses. Remarkably, the combined stress exhibited the most pronounced impact on the soybean root system, which led to a substantial reduction in total soluble sugar (TSS) and total soluble protein (TSP) within the plants under this treatment. A total of 20,953 differentially expressed genes were identified through pairwise comparisons. Heatmap analysis of genes related to energy metabolism pathways demonstrated a significant down-regulation in expression under salt and low phosphorus + salt treatments, while low phosphorus treatment did not exhibit similar expression trends. Furthermore, the weighted gene co-expression network analysis (WGCNA) indicated that the blue module had a strong positive correlation with TSS and TSP. Notably, 2,3-bisphosphoglycerate-dependent phosphoglycerate mutase 1, FCS-Like Zinc finger 8, auxin response factor 18 isoform X2, and NADP-dependent malic enzyme emerged as hub genes associated with energy metabolism. In summary, our findings indicate that soybean roots are more adversely affected by salt and combined stress than by low phosphorus alone due to reduced activity in energy metabolism-related pathways and hub genes. These results offer novel insights into the adaptive mechanisms of soybeans when facing the combined stress of low phosphorus and salinity.

Soil compaction development facilitated the decadal improvement of the root system architecture and rhizosheath soil traits of soybean in the North China Plain

Machinery agriculture has increased crop yield but induced soil compaction worldwide in the last decades. The crop yield increase is partly attributed to high-yielding crop breeding, but the effects of emerging soil compaction on the selection of root system traits and its impact on yield increase remain unclear. The objectives of this study were 1) to identify the effects of soil compaction on grain yield and root system architecture and rhizosheath soil traits of soybean (Glycine max (L.) Merr.) at the full-bloom stage, 2) to understand whether and how the development of soil compaction affected the selection of merit root and rhizosheath soil traits through crop breeding and contributed to soybean grain yield increase. Thirty-four most popular soybean cultivars released before and after the wide use of agricultural machinery in the North China Plain were grown in the fields without (NOM) and with (COM) applied soil compaction in 2017 and 2018. The phenotypes of root system, including rhizosheath soil, of soybean, were separated by soil compaction and cultivar release period, confirming the development of soil compaction and its impacts on the co-development of rhizosheaths with the root system of soybean. The correlation with the year of release of the cultivar demonstrated that 21 out of the 24 measured traits were selected by crop breeding. Multivariate analysis of the variance demonstrated that the selection of thinner hypocotyl, more root tips, and denser rhizosheath soil were relevant to the soil compaction development. The selection of shorter plant height, larger root biomass and area, thinner root tip, thicker taproot, and rhizosheath soil mass were likely relevant to the experimental year factor caused by drought or its associated change in nutrient availability. Most of the selected traits increased the resistance or the resilience to soil compaction and nine of them correlated with the grain yield of cultivars released at different periods. These results for the first time suggested that crop breeding increased grain yield partly by increasing the resistance and resilience to soil compaction. Soil compaction could be considered in a future breeding program design to increase crop breeding efficiency by selecting resistant and resilient root traits.

Soybean root image dataset and its deep learning application for nodule segmentation

The root is very important for anchoring the plant and acquiring water and nutrients from the soil for growth. Plant root trait phenotyping using imaging (2D and 3D) techniques is gaining importance in agriculture to enhance the breeding of superior cultivars. However, most root image data have been collected under controlled growth conditions, such as in greenhouses and growth chambers. In this study, we propose collecting soybean root image datasets from open field conditions for root phenotyping. There are numerous methods for segmenting images, but many of them are not suitable for the tiny and nodulated architecture of root. Advancements such as deep learning (DL) methods and semantic segmentation algorithms have been actively applied in many research studies. In the current study, we used convolutional neural network (CNN) based U-Net with six convolution methods and Deeplabv3+ and compared their performance in nodule identification based on the Dice coefficient, GPU memory usage, qualitative image segmentation, training time, and inference time. Also, we employed two image processing, resizing and patching, for efficient training of images with very high resolution. The results indicated accurate segmentation of root nodules; in addition, the results for the segmentation of root nodules using DL high-resolution (HR) images were more precise and efficient than those with low-resolution (LR) images since the Dice coefficient value and rate of nodule size were high in HR images although the former required more training time and higher GPU memory. Furthermore, in comparison to the resizing approach, patch-based approach outperformed in all aspects of performance. Among the DL models that we employed for our study, the grouped convolution-based U-net showed the best results having high Dice coefficient values 0.647 and 0.618 for 600x400 and 300x200 images respectively in resizing approach and dynamic convolution-based U-net showed the best results having Dice coefficient values 0.792 and 0.777 for 600x400 and 300x200 patch images respectively in patch-based approach. Thus, the optimized DL model presented in this study has the potential to be a valuable tool for the automated analysis of soybean root systems, assisting in the measurement of various root quality parameters and contributing to the development of superior cultivars.

Co-application of chitooligosaccharides and arbuscular mycorrhiza fungi reduced greenhouse gas fluxes in saline soil by improving the rhizosphere microecology of soybean

Soil salinization can affect the ecological environment of soil and alter greenhouse gas (GHG) emissions. Chitooligosaccharides and Arbuscular mycorrhizal fungi (AMF) reduced the GHG fluxes of salinized soil, and this reduction was attributed to an alteration in the rhizosphere microecology, including changes in the activities of β-glucosidase, acid phosphatase, N-acetyl-β-D-glucosidase, and Leucine aminopeptidase. Additionally, certain bacteria species such as paracoccus, ensifer, microvirga, and paracyclodium were highly correlated with GHG emissions. Another interesting finding is that foliar spraying of chitooligosaccharides could transport to the soybean root system, and improve soybean tolerance to salt stress. This is achieved by enhancing the activities of antioxidant enzymes, and the changes in amino acid metabolism, lipid metabolism, and membrane transport. Importantly, the Co-application of chitooligosaccharides and Arbuscular mycorrhiza fungi was found to have a greater effect compared to their application alone.

A high-resolution transcriptomic atlas depicting nitrogen fixation and nodule development in soybean.

Although root nodules are essential for biological nitrogen fixation in legumes, the cell types and molecular regulatory mechanisms contributing to nodule development and nitrogen fixation in determinate nodule legumes, such as soybean (Glycine max), remain incompletely understood. Here, we generated a single-nucleus resolution transcriptomic atlas of soybean roots and nodules at 14 days post inoculation (dpi) and annotated 17 major cell types, including six that are specific to nodules. We identified the specific cell types responsible for each step in the ureides synthesis pathway, which enables spatial compartmentalization of biochemical reactions during soybean nitrogen fixation. By utilizing RNA velocity analysis, we reconstructed the differentiation dynamics of soybean nodules, which differs from those of indeterminate nodules in Medicago truncatula. Moreover, we identified several putative regulators of soybean nodulation and two of these genes, GmbHLH93 and GmSCL1, were as-yet uncharacterized in soybean. Overexpression of each gene in soybean hairy root systems validated their respective roles in nodulation. Notably, enrichment for cytokinin-related genes in soybean nodules led to identification of the cytokinin receptor, GmCRE1, as a prominent component of the nodulation pathway. GmCRE1 knockout in soybean resulted in a striking nodule phenotype with decreased nitrogen fixation zone and depletion of leghemoglobins, accompanied by downregulation of nodule-specific gene expression, as well as almost complete abrogation of biological nitrogen fixation. In summary, this study provides a comprehensive perspective of the cellular landscape during soybean nodulation, shedding light on the underlying metabolic and developmental mechanisms of soybean nodule formation.

A novel soybean hairy root system for gene functional validation.

Agrobacterium rhizogenes-mediated transformation has long been explored as a versatile and reliable method for gene function validation in many plant species, including soybean (Glycine max). Likewise, detached-leaf assays have been widely used for rapid and mass screening of soybean genotypes for disease resistance. The present study combines these two methods to establish an efficient and practical system to generate transgenic soybean hairy roots from detached leaves and their subsequent culture under ex vitro conditions. We demonstrated that hairy roots derived from leaves of two (tropical and temperate) soybean cultivars could be successfully infected by economically important species of root-knot nematodes (Meloidogyne incognita and M. javanica). The established detached-leaf method was further explored for functional validation of two candidate genes encoding for cell wall modifying proteins (CWMPs) to promote resistance against M. incognita through distinct biotechnological strategies: the overexpression of a wild Arachis α-expansin transgene (AdEXPA24) and the dsRNA-mediated silencing of an endogenous soybean polygalacturonase gene (GmPG). AdEXPA24 overexpression in hairy roots of RKN-susceptible soybean cultivar significantly reduced nematode infection by approximately 47%, whereas GmPG downregulation caused an average decrease of 37%. This novel system of hairy root induction from detached leaves showed to be an efficient, practical, fast, and low-cost method suitable for high throughput in root analysis of candidate genes in soybean.

Seasonal variation of the rhizosphere soil aggregation in an Oxisol

Soil aggregation is a key process that results in soil structure formation and stabilization and controls several soil functions. The root system and its mycorrhiza symbiosis contribution to aggregate stabilization have been widely studied. However, only a few studies have considered a large variety of cropping systems under different seasons within tropical environments. Our goal was to better understand the response of aggregate stability in the rhizosphere (RS) and bulk soil (BS) to six cropping systems in an Oxisol, in the summer and winter seasons. Readily-dispersible clay and mechanically-dispersible clay were evaluated as aggregate stability indicators. RS and BS were also characterized for soil physical (i.e., water content), chemical (i.e., soil organic carbon, K, P, Ca, Mg, Al, potential acidity), and physicochemical (i.e., pH, ΔpH, and point of zero charge) properties. Dispersible clay was approximately 1.2 times lower (p < 0.05) within the RS than in the BS, which suggests that the crop root systems increased aggregate stability, but their influence on soil aggregation differed among cropping systems. Aggregate stability was approximately 3 times higher (p < 0.05) in the winter compared to the summer season. In general, RS had better chemical and physicochemical soil parameters than BS. Winter season also showed better chemical and physicochemical parameter values. Overall, these results reflect (i) the positive root system influence of the winter crops on soil structure stability, (ii) the negative response of soil structure stability to the addition of high doses of chemical fertilizers to soybean and maize (cash crops) in the summer season, (iii) the minimal influence of soybean and maize root system on formation and stabilization of the aggregates in the summer season, and (iv) the different weather condition in the summer and winter seasons. Thus, better erosion control practices and crops that promote soil aggregation should be adopted in the summer season. Finally, attention should also be given to the root exudates and their relationship with soil, as they can either increase or decrease soil aggregation.

Development of the soybean root system under the influence of weeds, nitrogen mineral fertilizers and herbicides

Aim. The research was to examine the effectiveness of tank mixtures of soil and post-emergence herbicides on the background of mineral and symbiotic nitrogen for implementation of optimal conditions for the functioning and development of the soybean root system. The article presents the results of research on the development of the root system of soybeans under the compatible effect of herbicides and the backgrounds of nitrogen nutrition. Methods. Field research was carried out on the lands of the stationary crop rotation of the Agronomic Research Station of the National University of Life and Environmental Sciences of Ukraine. The cultural plant cultivation technology is generally accepted for the zone. Results. The research results indicate a significant negative impact of crop weed infestation on the formation of the root system of soybeans: the decrease in its raw weight compared to plants in areas free from weeds (with two manual weedings) amounted to 35–44% and the total capacity – by 41–47%. The use of a tank mixture of soil herbicides Zenkor (0.4 l/ha) and Kommand (0.2 l/ha) in the system of protecting soybean crops from weeds resulted in an increase in raw weight and volume of the root system by 1.2–1.5 times with an efficiency close to manual weeding. Pre-sowing seed inoculation had a significant effect on the development of the soybean root system – symbiotic nitrogen increased the raw weight and volume of the root system by 32% and 40% appropriately. The application of the tank mixture Zenkor + Kommand provided the maximum growth upon these biometric indicators within the combined background of mineral and symbiotic nitrogen, where the total volume of the root system increased more than twice. Close correlations were found between both parameters of the soybean root system (r = 0.896). Conclusions. A high correlation dependence (r = 0.785) of soybean productivity on the extent of development of its root system was established. It was noted that while an effective combination of protection and fertilization systems soybeans are able to accumulate in the soil a significant amount of valuable biomass enriched with biological nitrogen, which in field experiments reached 5.6–5.9 t/ha, which was almost three times higher than in the absolute control (2.1 t/ha).

Using machine learning enabled phenotyping to characterize nodulation in three early vegetative stages in soybean.

The symbiotic relationship between soybean [Glycine max L. (Merr.)] roots and bacteria (Bradyrhizobium japonicum) lead to the development of nodules, important legume root structures where atmospheric nitrogen (N2) is fixed into bio-available ammonia (NH3) for plant growth and development. With the recent development of the Soybean Nodule Acquisition Pipeline (SNAP), nodules can more easily be quantified and evaluated for genetic diversity and growth patterns across unique soybean root system architectures. We explored six diverse soybean genotypes across three field year combinations in three early vegetative stages of development and report the unique relationships between soybean nodules in the taproot and non-taproot growth zones of diverse root system architectures of these genotypes. We found unique growth patterns in the nodules of taproots showing genotypic differences in how nodules grew in count, size, and total nodule area per genotype compared to non-taproot nodules. We propose that nodulation should be defined as a function of both nodule count and individual nodule area resulting in a total nodule area per root or growth regions of the root. We also report on the relationships between the nodules and total nitrogen in the seed at maturity, finding a strong correlation between the taproot nodules and final seed nitrogen at maturity. The applications of these findings could lead to an enhanced understanding of the plant-Bradyrhizobium relationship and exploring these relationships could lead to leveraging greater nitrogen use efficiency and nodulation carbon to nitrogen production efficiency across the soybean germplasm.

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.

Parsimonious root systems and better root distribution can improve biomass production and yield of soybean.

Enhancing the acquisition of belowground resources has been identified as an opportunity for improving soybean productivity worldwide. Root system architecture is gaining interest as a selection criterion in breeding programs for enhancing soil resource acquisition and developing climate-resilient varieties. Here we are presenting two novel characteristics of soybean root system architecture that improve aboveground growth and yield. Eleven selected soybean genotypes were tested under rain-fed conditions in 2019 and 2020 at two locations in South Carolina, in which one of the locations was characterized by compacted soils. The elite SC breeding line SC07-1518RR, exotic pedigree line N09-12854, and slow wilting line N09-13890 were superior genotypes in terms of biomass production, seed yield, and/or water use efficiency. Genotypes N09-12854 and N09-13890 demonstrated reduced root development (based on total root count and length), likely to restrict belowground growth and allocate more resources for shoot growth. This characteristic, which can be referred as a parsimonious root phenotype, might be advantageous for soybean improvement in high-input production systems (characterized by adequate fertilizer application and soil fertility) that exist in many parts of the world. Genotype SC07-1518RR exhibited a similar strategy: while it maintained its root system at an intermediate size through reduced levels of total root count and length, it selectively distributed more roots at deeper depths (53–70 cm). The increased root distribution of SC07-1518RR at deeper depths in compacted soil indicates its root penetrability and suitability for clayey soils with high penetration resistance. The beneficial root phenotypes identified in this study (parsimonious root development and selective root distribution in deeper depths) and the genotypes that possessed those phenotypes (SC07-1518RR, N09-12854, and N09-13890) will be useful for breeding programs in developing varieties for optimal, drought, and compacted-soil conditions.

Biochar impacts on the soil environment of soybean root systems

Biochar has been widely studied as a soil amendment, but little is known about the “biochar-freeze-thaw soil-crop root system” interface in seasonally frozen soil areas. In the second year after the application of biochar, we conducted research on the morphological characteristic indicators of the soybean root system and the nutrient migration of the soil in the root zone under different biochar application periods (spring and autumn mixed, autumn, and spring biochar application) and different biochar application rates (3 kg·m−2, 6 kg·m−2, 9 kg·m−2, and 12 kg·m−2). The effects of different biochar treatments on the growth and development of soybean roots were examined. The soil organic carbon, ammonium nitrogen and nitrate nitrogen contents of the soil were measured at different locations in the root zone, and the migration processes of these nutrients in the soil were explored. The conclusions drawn from the experiments are as follows. (i) The biochar application rate and application method together determine the root morphological characteristic indicators of soybean plants. During long freeze-thaw periods, the freeze-thaw cycles change the internal environment of the biochar-freeze-thaw soil complex. (ii) Biochar tends to move towards the root system, which can increase soil organic carbon content, but the effect of biochar on root characteristics is not caused by the change in soil organic carbon content. (iii) Biochar promotes nitrogen cycling in the soil and the migration of soil nitrogen to the root sheath, increasing the number of nitrogen compounds that can be directly absorbed and utilized by crops. (iv) From a comparison of the effects of various biochar treatments on crop roots and farmland soils, we suggest that the 9 kg·m−2 biochar application rate under spring and autumn mixed biochar application is the optimal treatment.

Physiological and transcriptomic response of soybean seedling roots to variable nitrate levels

AbstractNitrate is the main nitrogen source for plant growth and development. Increasing evidence indicates that nitrate plays an important role in root growth and development. However, the effects of different concentrations of nitrate on the physiological and transcriptional response of soybean [Glycine max (L.) Merr.] root development at the seedling stage are not well understood. In this study, we found that both high and low concentrations of nitrate inhibited the growth and development of the soybean root system compared with optimal nitrate supply at the seedling stage. Using transcriptome sequencing technology, we identified 1,654, 1,283, and 2,083 significantly differentially expressed genes in soybean root grown under the low nitrate concentration, optimal nitrate concentration, and high nitrate concentration conditions, respectively. These genes were enriched in the Gene Ontology terms of metabolic process, catalytic activity, and membrane. The genes enriched in the pentose and glucuronate interconversions and glutathione metabolism pathways may play important roles during soybean root response to different concentrations of nitrate. In addition, the expression of 18 nitrate transporter genes changed significantly under different nitrate concentrations. Among them, the expression of two GmNPF6.3 genes was upregulated under the NL condition but downregulated under the NH condition, whereas six GmNPF7.3 genes exhibited opposite expression patterns. Taken together, our physiological data can enable a better understanding of the soybean root response under different nitrate concentrations, and the transcriptome data provide a list of candidate genes for further investigation of the mechanisms of root response under different nitrate concentrations.

English

Nitrate is one of the key sources of nitrogen in natural and agricultural soils. The distribution and concentration of nitrate determine root system architecture in plants. Soybean (Glycine max L) is one of the key leguminous crops, while farmers rarely apply nitrogen in soybean crops except for a starter nitrogen dose at the time of sowing. However, the effects of severe deficiency nitrate on early seedling establishment of soybean before nodulation are not yet studied. Therefore, this study evaluated the effects of high dose of nitrate (54.3 mM) and its deprivationon (0 mM) on the root system architecture of soybean during seedling establishment. Results showed that the root traits including primary root length, fresh biomass, total length, surface area, tips, forks, and its crossings were significantly higher under no nitrate condition than nigh nitrate condition except for root volume, its dry biomass and diameter. Shoot growth attributes such as shoot length, shoot fresh biomass, shoot dry biomass, single leaf area, soil-plant analysis development value, and photosynthesis was significantly decreased while leaf dry mass per area was increased significantly under no nitrate condition. Furthermore, high nitrate supply significantly enhanced the content of nitrate in root tissue, but there was no significant difference between low and optimal nitrate supply. In summary, this study indicated that soybean root system architecture adopts a foraging strategy under nitrogen deprived environment. © 2021 Friends Science Publishers

Soybean inoculation techniques for the region of Tangará da Serra - MT, Brazil

The use of inoculated microorganisms on seeds has increased in Brazil, as they help on the fixation and use of nutrients by plants, promoting increasing yields, mainly due to the reduction in the application of nitrogen fertilizers. The aim of this study was to evaluate the influence of single inoculation and co-inoculation of Azospirillum brasilense and Bradyrhizobium japonicum bacteria on seeds and foliar inoculation on soybean, in the region of Tangará da Serra – MT, Brazil. The experimental design used was a randomized block with 9 treatments and 4 replicates. The treatments were composed by using B. japonicum and A. brasilense bacteria in different combinations and times of application on seeds and sprayed on the leaves. The use of A. brasilense together with B. japonicum significantly improved the agronomic characteristics of the evaluated soybean cultivar. There was an increase in yield with the use of A. brasilense through the co-inoculation technique when compared to the single use of Bradyrhizobium. The use of co-inoculation at V3 soybean stage promoted higher nodulation and yield than the standard inoculation performed in the seeds, ensuring better results of nodulation and yield besides increasing the size of the soybean root system, when there and co-inoculation techniques were implemented.

Topsoil Hardening: Effects on Soybean Root Architecture and Water Extraction Patterns

Topsoil hardening is one of the major causes of poor root growth although its effects on subsoil roots are still not well-known. Our aim was to examine the effects of topsoil hardening on the growth and functioning of shallow and deep roots of soybean plants. Two rain shelter experiments were conducted in two consecutive years. Plants were grown in topsoil monoliths (0–20 cm) with low (LR) or high mechanical resistance (HR), extracted from adjacent no-tillage cropping fields, and placed above 180 cm-high containers filled with a sandy loam soil. The effects of topsoil hardening were largely regulated by the level of water stress. In stressed plants, HR conditions reduced total aboveground biomass (up to 13%), total root biomass, root length density, and root surface area (up to 23, 38, and 37% respectively). Mechanical impedances reduced root biomass and length in both shallow (0–20 cm) and very deep layers (+ 160 cm). No changes were observed in specific root length or specific surface area. Plants growing in HR topsoils showed lower total water extraction but greater specific water uptake rates (29–47% higher in year 1 and 2 respectively). No clear architectural (i.e., root density) or morphological (i.e., specific root length/area) responses of enhanced root foraging capacity were observed in subsoil roots. However, soybean root system responded through functional mechanisms (i.e., specific water uptake) which partially attenuated the negative effects of mechanical impedances.

Soybean Root System Architecture Trait Study through Genotypic, Phenotypic, and Shape-Based Clusters.

We report a root system architecture (RSA) traits examination of a larger scale soybean accession set to study trait genetic diversity. Suffering from the limitation of scale, scope, and susceptibility to measurement variation, RSA traits are tedious to phenotype. Combining 35,448 SNPs with an imaging phenotyping platform, 292 accessions (replications = 14) were studied for RSA traits to decipher the genetic diversity. Based on literature search for root shape and morphology parameters, we used an ideotype-based approach to develop informative root (iRoot) categories using root traits. The RSA traits displayed genetic variability for root shape, length, number, mass, and angle. Soybean accessions clustered into eight genotype- and phenotype-based clusters and displayed similarity. Genotype-based clusters correlated with geographical origins. SNP profiles indicated that much of US origin genotypes lack genetic diversity for RSA traits, while diverse accession could infuse useful genetic variation for these traits. Shape-based clusters were created by integrating convolution neural net and Fourier transformation methods, enabling trait cataloging for breeding and research applications. The combination of genetic and phenotypic analyses in conjunction with machine learning and mathematical models provides opportunities for targeted root trait breeding efforts to maximize the beneficial genetic diversity for future genetic gains.