scholarly journals Root Trait Variation in Lentil (Lens culinaris Medikus) Germplasm under Drought Stress

Plants ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 2410
Author(s):  
Swati Priya ◽  
Ruchi Bansal ◽  
Gaurav Kumar ◽  
Harsh Kumar Dikshit ◽  
Jyoti Kumari ◽  
...  
Keyword(s):  
Drought Tolerance ◽  
Root System ◽  
System Architecture ◽  
Lens Culinaris ◽  
Seedling Survival ◽  
Root Traits ◽  
Root System Architecture ◽  
Root Diameter ◽  
Fine Tuning ◽  
Tolerance Index

Drought is the most critical environmental factor across the continents affecting food security. Roots are the prime organs for water and nutrient uptake. Fine tuning between water uptake, efficient use and loss determines the genotypic response to water limitations. Targeted breeding for root system architecture needs to be explored to improve water use efficiency in legumes. Hence, the present study was designed to explore root system architecture in lentil germplasm in response to drought. A set of 119 lentil (Lens culinaris Medik.) genotypes was screened in controlled conditions to assess the variability in root traits in relation to drought tolerance at seedling stage. We reported significant variation for different root traits in lentil germplasm. Total root length, surface area, root volume and root diameter were correlated to the survival and growth under drought. Among the studied genotypes, the stress tolerance index varied 0.19–1.0 for survival and 0.09–0.90 for biomass. Based on seedling survival and biomass under control and drought conditions, 11 drought tolerant genotypes were identified, which may be investigated further at a physiological and molecular level for the identification of the genes involved in drought tolerance. Identified lines may also be utilised in a lentil breeding program.

scholarly journals ChronoRoot: High-throughput phenotyping by deep segmentation networks reveals novel temporal parameters of plant root system architecture

2020 ◽  
Author(s):  
Nicolás Gaggion ◽  
Federico Ariel ◽  
Vladimir Daric ◽  
Éric Lambert ◽  
Simon Legendre ◽  
...  
Keyword(s):  
Deep Learning ◽  
Root System ◽  
High Throughput ◽  
System Architecture ◽  
Root Traits ◽  
Root System Architecture ◽  
Machine Intelligence ◽  
Reconstruction Process ◽  
High Throughput Phenotyping ◽  
3D Printed

ABSTRACTDeep learning methods have outperformed previous techniques in most computer vision tasks, including image-based plant phenotyping. However, massive data collection of root traits and the development of associated artificial intelligence approaches have been hampered by the inaccessibility of the rhizosphere. Here we present ChronoRoot, a system which combines 3D printed open-hardware with deep segmentation networks for high temporal resolution phenotyping of plant roots in agarized medium. We developed a novel deep learning based root extraction method which leverages the latest advances in convolutional neural networks for image segmentation, and incorporates temporal consistency into the root system architecture reconstruction process. Automatic extraction of phenotypic parameters from sequences of images allowed a comprehensive characterization of the root system growth dynamics. Furthermore, novel time-associated parameters emerged from the analysis of spectral features derived from temporal signals. Altogether, our work shows that the combination of machine intelligence methods and a 3D-printed device expands the possibilities of root high-throughput phenotyping for genetics and natural variation studies as well as the screening of clock-related mutants, revealing novel root traits.

Does the lack of root hairs alter root system architecture of Zea mays?

2021 ◽  
Author(s):  
Steffen Schlüter ◽  
Eva Lippold ◽  
Maxime Phalempin ◽  
Doris Vetterlein
Keyword(s):  
Zea Mays ◽  
Root System ◽  
Root Hair ◽  
System Architecture ◽  
Volume Fraction ◽  
Root Hairs ◽  
Root System Architecture ◽  
Root Diameter ◽  
Wild Type ◽  
Defective Mutant

<p>Root hairs are one root trait among many which enables plants to adapt to environmental conditions. How different traits are coordinated and whether some are mutually exclusive is currently poorly understood. Comparing a root hair defective mutant with its corresponding wild-type we explored if and how the mutant exhibited root growth adaption strategies and as to how far this depended on the substrate.</p><p>Zea mays root hair defective mutant (rth3) and the corresponding wild-type siblings were grown on two substrates with contrasting texture and hence nutrient mobility. Root system architecture was investigated over time using repeated X-ray computed tomography.</p><p>There was no plastic adaption of root system architecture to the lack of root hairs, which resulted in lower uptake in particular in the substrate with low P mobility. The function of the root hairs for anchoring did not result in different depth profiles of the root length density between genotypes. Both maize genotypes showed a marked response to substrate. This was well reflected in the spatiotemporal development of rhizosphere volume fraction but especially in the strong response of root diameter to substrate, irrespective of genotype.</p><p>The most salient root plasticity trait was root diameter in response to substrate, whereas coping mechanisms for missing root hairs were less evident. Further experiments are required to elucidate whether observed differences can be explained by mechanical properties beyond mechanical impedance, root or microbiome ethylene production or differences in diffusion processes within the root or the rhizosphere.</p>

scholarly journals Trait-Based Root Phenotyping as a Necessary Tool for Crop Selection and Improvement

Agronomy ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1328
Author(s):  
Rebecca K. McGrail ◽  
David A. Van Sanford ◽  
David H. McNear
Keyword(s):  
Root System ◽  
System Architecture ◽  
Production Systems ◽  
Root Traits ◽  
Root System Architecture ◽  
Root Decomposition ◽  
Crop Breeding ◽  
Organic Acid Production ◽  
Nutritional Qualities ◽  
Chemical Traits

Most of the effort of crop breeding has focused on the expression of aboveground traits with the goals of increasing yield and disease resistance, decreasing height in grains, and improvement of nutritional qualities. The role of roots in supporting these goals has been largely ignored. With the increasing need to produce more food, feed, fiber, and fuel on less land and with fewer inputs, the next advance in plant breeding must include greater consideration of roots. Root traits are an untapped source of phenotypic variation that will prove essential for breeders working to increase yields and the provisioning of ecosystem services. Roots are dynamic, and their structure and the composition of metabolites introduced to the rhizosphere change as the plant develops and in response to environmental, biotic, and edaphic factors. The assessment of physical qualities of root system architecture will allow breeding for desired root placement in the soil profile, such as deeper roots in no-till production systems plagued with drought or shallow roots systems for accessing nutrients. Combining the assessment of physical characteristics with chemical traits, including enzymes and organic acid production, will provide a better understanding of biogeochemical mechanisms by which roots acquire resources. Lastly, information on the structural and elemental composition of the roots will help better predict root decomposition, their contribution to soil organic carbon pools, and the subsequent benefits provided to the following crop. Breeding can no longer continue with a narrow focus on aboveground traits, and breeding for belowground traits cannot only focus on root system architecture. Incorporation of root biogeochemical traits into breeding will permit the creation of germplasm with the required traits to meet production needs in a variety of soil types and projected climate scenarios.

scholarly journals Genetic Dissection of the Seminal Root System Architecture in Mediterranean Durum Wheat Landraces by Genome-Wide Association Study

Agronomy ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 364 ◽  
Author(s):  
Martina Roselló ◽  
Conxita Royo ◽  
Miguel Sanchez-Garcia ◽  
Jose Miguel Soriano
Keyword(s):  
Durum Wheat ◽  
Root System ◽  
System Architecture ◽  
Eastern Mediterranean Region ◽  
Root Traits ◽  
Root System Architecture ◽  
Seminal Root ◽  
Large Variability ◽  
Wheat Landraces ◽  
Durum Wheat Landraces

Roots are crucial for adaptation to drought stress. However, phenotyping root systems is a difficult and time-consuming task due to the special feature of the traits in the process of being analyzed. Correlations between root system architecture (RSA) at the early stages of development and in adult plants have been reported. In this study, the seminal RSA was analysed on a collection of 160 durum wheat landraces from 21 Mediterranean countries and 18 modern cultivars. The landraces showed large variability in RSA, and differences in root traits were found between previously identified genetic subpopulations. Landraces from the eastern Mediterranean region, which is the driest and warmest within the Mediterranean Basin, showed the largest seminal root size in terms of root length, surface, and volume and the widest root angle, whereas landraces from eastern Balkan countries showed the lowest values. Correlations were found between RSA and yield-related traits in a very dry environment. The identification of molecular markers linked to the traits of interest detected 233 marker-trait associations for 10 RSA traits and grouped them in 82 genome regions named marker-train association quantitative trait loci (MTA-QTLs). Our results support the use of ancient local germplasm to widen the genetic background for root traits in breeding programs.

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

2020 ◽  
Vol 2020 ◽  
pp. 1-23 ◽  
Author(s):  
Kevin G. Falk ◽  
Talukder Zaki Jubery ◽  
Jamie A. O’Rourke ◽  
Arti Singh ◽  
Soumik Sarkar ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Root System ◽  
System Architecture ◽  
Fourier Transformation ◽  
Root Traits ◽  
Root System Architecture ◽  
Neural Net ◽  
Measurement Variation ◽  
Transformation Methods ◽  
Morphology Parameters

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.

scholarly journals Assessing Root System Architecture of Wheat Seedlings Using A High-Throughput Root Phenotyping System

2019 ◽  
Author(s):  
E. Adeleke ◽  
R. Millas ◽  
W. McNeal ◽  
J Faris ◽  
A. Taheri
Keyword(s):  
Root System ◽  
System Architecture ◽  
Root Traits ◽  
Wheat Seedling ◽  
Root System Architecture ◽  
Rapid Screening ◽  
Wheat Seedlings ◽  
Ploidy Levels ◽  
Seedling Traits ◽  
Root Phenotyping

AbstractBackground and aimsRoot system architecture is a vital part of the plant that has been shown to vary between species and within species based on response to genotypic and/or environmental influences. The root traits of wheat seedlings is critical for the establishment and evidently linked to plant height and seed yield. However, plant breeders have not efficiently developed the role of RSA in wheat selection due to the difficulty of studying root traits.MethodsWe set up a root phenotyping platform to characterize RSA in 34 wheat accessions. The phenotyping pipeline consists of the germination paper-based moisture replacement system, image capture units, and root-image processing software. The 34 accessions from two different wheat ploidy levels (hexaploids and tetraploids), were characterized in ten replicates. A total of 19 root traits were quantified from the root architecture generated.ResultsThis pipeline allowed for rapid screening of 340 wheat seedlings within 10days. Also, at least one line from each ploidy (6x and 4x) showed significant differences (P < 0.05) in measured traits except in mean seminal count. Our result also showed strong correlation (0.8) between total root length, maximum depth and convex hull area.ConclusionsThis phenotyping pipeline has the advantage and capacity to increase screening potential at early stages of plant development leading to characterization of wheat seedling traits that can be further examined using QTL analysis in populations generated from the examined accessions.

scholarly journals Genotypic diversity and plasticity of root system architecture to nitrogen availability in oilseed rape

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0250966
Author(s):  
Christophe Lecarpentier ◽  
Loïc Pagès ◽  
Céline Richard-Molard
Keyword(s):  
Root System ◽  
Oilseed Rape ◽  
System Architecture ◽  
Lateral Root ◽  
Nitrogen Availability ◽  
Root System Architecture ◽  
Root Diameter ◽  
Root Density ◽  
Model Parameters ◽  
New Varieties

In the emerging new agricultural context, a drastic reduction in fertilizer usage is required. A promising way to maintain high crop yields while reducing fertilizer inputs is to breed new varieties with optimized root system architecture (RSA), designed to reach soil resources more efficiently. This relies on identifying key traits that underlie genotypic variability and plasticity of RSA in response to nutrient availability. The aim of our study was to characterize the RSA plasticity in response to nitrogen limitation of a set of contrasted oilseed rape genotypes, by using the ArchiSimple model parameters as screening traits. Eight accessions of Brassica napus were grown in long tubes in the greenhouse, under two contrasting levels of nitrogen availability. After plant excavation, roots were scanned at high resolution. Six RSA traits relative to root diameter, elongation rate and branching were measured, as well as nine growth and biomass allocation traits. The plasticity of each trait to nitrogen availability was estimated. Nitrogen-limited plants were characterized by a strong reduction in total biomass and leaf area. Even if the architecture traits were shown to be less plastic than allocation traits, significant nitrogen and genotype effects were highlighted on each RSA trait, except the root minimal diameter. Thus, the RSA of nitrogen-limited plants was primarily characterised by a reduced lateral root density, a smaller primary root diameter, associated with a stronger root dominance. Among the RSA traits measured, the inter-branch distance showed the highest plasticity with a level of 70%, in the same range as the most plastic allocation traits. This work suggests that lateral root density plays the key role in the adaptation of the root system to nitrogen availability and highlights inter-branch distance as a major target trait for breeding new varieties, better adapted to low input systems.

scholarly journals Exploiting natural variation in crown root traits via genome-wide association studies in maize

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Houmiao Wang ◽  
Xiao Tang ◽  
Xiaoyi Yang ◽  
Yingying Fan ◽  
Yang Xu ◽  
...  
Keyword(s):  
Root System ◽  
Candidate Genes ◽  
System Architecture ◽  
Root Traits ◽  
Root System Architecture ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Crown Root ◽  
Genome Wide ◽  
Maize Varieties

Abstract Background Root system architecture (RSA), which is determined by the crown root angle (CRA), crown root diameter (CRD), and crown root number (CRN), is an important factor affecting the ability of plants to obtain nutrients and water from the soil. However, the genetic mechanisms regulating crown root traits in the field remain unclear. Methods In this study, the CRA, CRD, and CRN of 316 diverse maize inbred lines were analysed in three field trials. Substantial phenotypic variations were observed for the three crown root traits in all environments. A genome-wide association study was conducted using two single-locus methods (GLM and MLM) and three multi-locus methods (FarmCPU, FASTmrMLM, and FASTmrEMMA) with 140,421 SNP. Results A total of 38 QTL including 126 SNPs were detected for CRA, CRD, and CRN. Additionally, 113 candidate genes within 50 kb of the significant SNPs were identified. Combining the gene annotation information and the expression profiles, 3 genes including GRMZM2G141205 (IAA), GRMZM2G138511 (HSP) and GRMZM2G175910 (cytokinin-O-glucosyltransferase) were selected as potentially candidate genes related to crown root development. Moreover, GRMZM2G141205, encoding an AUX/IAA transcriptional regulator, was resequenced in all tested lines. Five variants were identified as significantly associated with CRN in different environments. Four haplotypes were detected based on these significant variants, and Hap1 has more CRN. Conclusions These findings may be useful for clarifying the genetic basis of maize root system architecture. Furthermore, the identified candidate genes and variants may be relevant for breeding new maize varieties with root traits suitable for diverse environmental conditions.

scholarly journals Exploiting natural variation in root system architecture via genome-wide association studies

2020 ◽  
Vol 71 (8) ◽  
pp. 2379-2389 ◽  
Author(s):  
Agnieszka Deja-Muylle ◽  
Boris Parizot ◽  
Hans Motte ◽  
Tom Beeckman
Keyword(s):  
Root System ◽  
System Architecture ◽  
Association Studies ◽  
Root Traits ◽  
Root System Architecture ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Important Research Topic ◽  
Root Growth And Development

Abstract Root growth and development has become an important research topic for breeders and researchers based on a growing need to adapt plants to changing and more demanding environmental conditions worldwide. Over the last few years, genome-wide association studies (GWASs) became an important tool to identify the link between traits in the field and their genetic background. Here we give an overview of the current literature concerning GWASs performed on root system architecture (RSA) in plants. We summarize which root traits and approaches have been used for GWAS, mentioning their respective success rate towards a successful gene discovery. Furthermore, we zoom in on the current technical hurdles in root phenotyping and GWAS, and discuss future possibilities in this field of research.

Exploiting Natural Variation in Crown Root Traits via Genome-Wide Association Studies in Maize

2021 ◽  
Author(s):  
Houmiao Wang ◽  
Xiao Tang ◽  
Xiaoyi Yang ◽  
Yingying Fan ◽  
Yang Xu ◽  
...  
Keyword(s):  
Root System ◽  
Candidate Genes ◽  
System Architecture ◽  
Root Traits ◽  
Root System Architecture ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Crown Root ◽  
Genome Wide ◽  
Maize Varieties

Abstract Background: Root system architecture (RSA), which is determined by the crown root angle (CRA), crown root diameter (CRD), and crown root number (CRN), is an important factor affecting the ability of plants to obtain nutrients and water from the soil. However, the genetic mechanisms regulating crown root traits in the field remain unclear. Methods: In this study, the CRA, CRD, and CRN of 348 diverse maize inbred lines were analysed in three field trials. Substantial phenotypic variations were observed for the three crown root traits in all environments. A genome-wide association study was conducted using three multi-locus methods (FarmCPU, FASTmrMLM, and FASTmrEMMA).Results: A total of 91, 116, and 117 marker–trait associations were identified for CRA, CRD, and CRN, respectively. Additionally, 683 candidate genes within 50 kb of the significant SNPs were identified. A combined analysis of gene annotations and expression profiles revealed 20 promising genes related to auxin synthesis and signal transduction, cytokinin oxidase/dehydrogenase, and transcription factors. These candidate genes may be associated with crown root development. Moreover, GRMZM2G141205, encoding an AUX/IAA transcriptional regulator, was resequenced in all tested lines. Five variants were identified as significantly associated with CRN based on the data for 16SY and 17SY as well as the average values for the three environments. Four haplotypes were detected based on these significant variants, and Hap1 was the optimal haplotype for CRN. Conclusions: These findings may be useful for clarifying the genetic basis of maize root system architecture. Furthermore, the identified candidate genes and variants may be relevant for breeding new maize varieties with root traits suitable for diverse environmental conditions.

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