scholarly journals Phenotyping Root Architecture of Soil-Grown Rice: A Robust Protocol Combining Manual Practices with Image-based Analyses

2020 ◽  
Author(s):  
P. De Bauw ◽  
J. A. Ramarolahy ◽  
K. Senthilkumar ◽  
T. Rakotoson ◽  
R. Merckx ◽  
...  

AbstractBackgroundBreeding towards resilient rice varieties is often constrained by the limited data on root system architecture obtained from relevant agricultural environments. Knowledge on the genotypic differences and responses of root architecture to environmental factors is limited due the difficulty of analysing soil-grown rice roots. An improved method using imaging is thus needed, but the existing methods were never proven successful for rice. Here, we aimed to evaluate and improve a higher throughput method of image-based root phenotyping for rice grown under field conditions. Rice root systems from seven experiments were phenotyped based on the “shovelomics” method of root system excavation followed by manual root phenotyping and digital root analysis after root imaging. Analyzed traits were compared between manual and image-based root phenotyping systems using Spearman rank correlations to evaluate whether both methods similarly rank the phenotypes. For each trait, the relative phenotypic variation was calculated. A principal component analysis was then conducted to assess patterns in root architectural variation.ResultsSeveral manually collected and image-based root traits were identified as having a high potential of differentiating among contrasting phenotypes, while other traits are found to be inaccurate and thus unreliable for rice. The image-based traits projected area, root tip thickness, stem diameter, and root system depth successfully replace the manual determination of root characteristics, however attention should be paid to the lower accuracy of the image-based methodology, especially when working with older and larger root systems.ConclusionsThe challenges and opportunities of rice root phenotyping in field conditions are discussed for both methods. We therefore propose an integrated protocol adjusted to the complexity of the rice root structure combining image analysis in a water bath and the manual scoring of three traits (i.e. lateral density, secondary branching degree, and nodal root thickness at the root base). The proposed methodology ensures higher throughput and enhanced accuracy during root phenotyping of soil grown rice in fields or pots compared to manual scoring only, it is cheap to develop and operate, it is valid in remote environments, and it enables fast data extraction.

2010 ◽  
Vol 36 (4) ◽  
pp. 149-159
Author(s):  
Susan Day ◽  
P. Eric Wiseman ◽  
Sarah Dickinson ◽  
J. Roger Harris

Knowledge of the extent and distribution of tree root systems is essential for managing trees in the built environment. Despite recent advances in root detection tools, published research on tree root architecture in urban settings has been limited and only partially synthesized. Root growth patterns of urban trees may differ considerably from similar species in forested or agricultural environments. This paper reviews literature documenting tree root growth in urban settings as well as literature addressing root architecture in nonurban settings that may contribute to present understanding of tree roots in built environments. Although tree species may have the genetic potential for generating deep root systems (>2 m), rooting depth in urban situations is frequently restricted by impenetrable or inhospitable soil layers or by underground infrastructure. Lateral root extent is likewise subject to restriction by dense soils under hardscape or by absence of irrigation in dry areas. By combining results of numerous studies, the authors of this paper estimated the radius of an unrestricted root system initially increases at a rate of approximately 38 to 1, compared to trunk diameter; however, this ratio likely considerably declines as trees mature. Roots are often irregularly distributed around the tree and may be influenced by cardinal direction, terrain, tree lean, or obstacles in the built environment. Buttress roots, tap roots, and other root types are also discussed.


2017 ◽  
Vol 68 (5) ◽  
pp. 965-982 ◽  
Author(s):  
Jiangsan Zhao ◽  
Gernot Bodner ◽  
Boris Rewald ◽  
Daniel Leitner ◽  
Kerstin A. Nagel ◽  
...  

HortScience ◽  
2000 ◽  
Vol 35 (3) ◽  
pp. 475A-475
Author(s):  
Kevin M. Crosby

Improving melon root systems by traditional breeding is one component of the program to develop multiple-stress-resistant melons at the Texas Agricultural Experiment Station, Weslaco. Ten diverse melon lines representing four horticultural groups were intercrossed utilizing a Design II mating scheme. The male parents were: `PI 403994,' `Perlita,' `Doublon,' `Caravelle', and `PI 525106.' The female parents were: `Créme de Menthe,' `Magnum 45,' `BSK,' `PI 124111 × TDI', and `Deltex.' F1 progeny were grown in pasteurized sand in the greenhouse using a randomized complete-block design with four reps. After 4 weeks, root systems from all plants were carefully washed to remove the sand. Each root system was then placed onto a glass, plated, and scanned into the computer software Rhizo Pro 3.8 (Regent Instruments, Quebec). This software calculated root lengths of various diameter classes, root area, and root tip number. All data was input into Agrobase software for calculation of genetic variances based on Design II analysis. Significant differences of contributions by male parents to progeny variation were few. Only length of roots with 1.0- to 1.5-mm-diameter and vine length were significantly different. Differences in contributions by female parents to all traits except root tip number were highly significant. No significant interaction effects were observed for any trait. Narrow-sense heritability estimates were moderate to high for all traits. The range was from 0.56 for root tip number by males to 0.81 for both length of 0.5- to 1.0-mm-diameter roots and vine length for females. Estimates for total root length (0.76) and root surface area (0.77) were high. The lack of male by female interaction suggests very low dominance genetic variation and contributed to high heritability estimates, which represent predominantly additive gene action. Additive genetic variation allows more-efficient progress by selection, making the potential for root system improvement favorable.


2020 ◽  
Author(s):  
◽  
Sulaiman Ahmed Ali

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI-COLUMBIA AT REQUEST OF AUTHOR.] Soybean (Glycine max (L.) is currently grown throughout the world because it has been adapted to many environments and because of the high protein and oil content of the seeds. Water scarcity is responsible for the biggest crop losses worldwide and this is expected to worsen; thus, much attention is directed towards the development of drought tolerant crops. The root system is fundamentally important for plant growth and survival because of its role in water and nutrient uptake. Crops with deep roots can capture more soil resources, particularly water, to support shoot growth and yield formation. However, the investigation of root systems is difficult and remains challenging, especially under field conditions. Nonetheless, a better understanding of root system form and function is critical to develop strategies to breed for more stress-resilient crops for local production environments. Studies of soybean root systems in general, and rooting depth in particular have been limited. Thus, the aims of the research described in this dissertation were to (i) identify genotypic diversity in rooting depth and distribution of roots in the soil profile and relate these traits to above ground characteristics including yield under rainfed field conditions in a wide range of soybean genotypes, (ii) characterize, compare and contrast root systems of selected soybean genotypes grown under field- and greenhouse-conditions, and (iii) explore the influence of scion and rootstock genotype on root growth of contrasting soybean genotypes under well-watered and water deficit stress conditions. In the first series of experiments, a set of five soybean genotypes that represented contrasting root rooting depths and root elongation rates were selected based on greenhouse experiment and grown under rainfed field conditions. The core break method was used to assess root distributions of these genotypes in two years. The main goals of this experiment were to confirm genotypic variation for key root traits, including rooting depth and distribution, and to determine whether rooting depth is related to seed yield and selected shoot traits. This study confirmed significant variation among genotypes regarding their rooting depth and root distribution in the soil profile. Genotypes with greater maximum rooting depth also exhibited greater numbers of roots in the lower soil strata than shallower rooting genotypes, and rooting depth was positively correlated with seed yield. Confirmation of differences in rooting depth among these genotypes and the relationship with seed yield under field conditions establishes the suitability of the selected genotypes for physiological studies, studies of genetic mechanisms underpinning maximum rooting depth in soybean, and to confirm the potential for yield increase as a result of selection for deep rooting. A second study consisted of two greenhouse experiments to evaluate the effect of water availability on the rooting depth plasticity of deep- and shallow-rooted genotypes. Six contrasting genotypes were grown in PVC pipes under well-watered and dry-down conditions. The soil media was a mixture of soil and sand with a ratio of 4:1, respectively. Significant genotype, water treatment, and genotype by water treatment interaction effects were observed for maximum rooting depth. Maximum rooting depth increased in the dry-down compared to the well-watered treatment and induced a reallocation of root length from shallow strata to deeper regions in the profile for all genotypes. The extent of the difference in rooting depth between well-watered and dry-down treatments, measured as plasticity, was significantly different among genotypes. Thus, plasticity in maximum rooting depth appears to be under genetic control in soybean and may be a suitable target for breeding efforts aimed at increasing yields under drought. In a final study, the influence of scion and rootstock genotype on shoot growth and root system characteristics was examined in deep tubes in an automated rainout shelter. Plants were sown into 1.5- m deep tubes filled with a soil-sand mix (4:1) and grown under well-watered and dry-down conditions. Nine days after sowing, self and reciprocal grafts were made using the wedge grafting method. The dry-down treatment resulted in significantly increased rooting depth for all grafted as well as the non-grafted treatments compared to well-watered treatment. As expected, root length densities in the top 30 cm of the soil were greater for well-watered plants than plants in the dry-down treatment whereas the opposite was true for root length density at depth. Overall, whether self-grafted or serving as rootstock only, the deep-rooted genotype had a stimulatory effect on root growth in most soil strata, particularly under dry-down conditions. In general, limited differences observed among the grafting treatments suggest a small influence of the scion or rootstock genotype on the rooting depth and root distribution in the soil profile. However, grafting studies with additional genotypes should be conducted to explore whether this observation is specific to the genotype combination used in this study or whether it applies more generally for soybean. The experiments described in this dissertation lay the foundation for additional physiological and genetic studies. Further research is needed to ascertain the physiological mechanism behind the responses of contrasting genotypes, and to identify molecular markers and/or genes to facilitate incorporation of desirable root traits into a breeding program to increase yields and/or yield stability under drought conditions.


2017 ◽  
Author(s):  
Tianlun Zhao ◽  
Jiahui Hu ◽  
Cheng Li ◽  
Cong Li ◽  
Lei Mei ◽  
...  

AbstractGossypol plays an important role in defense mechanism of Gossypium species and the presence of gossypol also limits the utilization of cottonseeds. However, little is known about the metabolism of gossypol in cotton plant. Here, Detection on the dynamic tendency of gossypol content illustrated that at the germination stage, the main source of gossypol was cotyledon, and at the later stages, gossypol mainly came from root system. Plant grafting between cottons and sunflower proved that gossypol was mainly synthesized in the root systems of cotton plants and both of the glanded and glandless cottons had the ability of gossypol biosynthesis. Besides, the pigment glands expression was uncoupled with gossypol biosynthesis. Root tip and rootless seedling organ culture in vitro further revealed other parts of the seedlings also got the ability to synthesize gossypol except root system. Moreover, root system produced the racemic gossypol and plant synthesized the optically active gossypol. The expression profiling of key genes in the gossypol biosynthetic pathway suggested that downstream key genes had relatively high expression levels in root systems which confirmed that gossypol was mainly synthesized in the root systems. Taken together, our results helped to clarify the complex mechanism of gossypol metabolism.


2021 ◽  
Author(s):  
Justin Miron

Understanding the architecture of tree roots is an important component of urban forestry management practice. Tree roots are structurally and functionally important to the survival of trees, and this can be even more so in urban environments where underground space for roots is limited. Tree root architecture models can provide a complementary approach to traditional on-site field investigation methods. Root architecture models are unique in that they can simulate the spatial arrangements of root system structure explicitly, and allow investigators to create hypothetical simulations to test their assumptions about what may be driving root growth. The use of root architecture models in the literature is extensive and may be applied in diverse streams of investigation, but their application to tree root systems is less common. This research demonstrates a root architecture model, Rootbox, as a case study in the application of plant architecture models to simulate tree root growth in urban conditions. Model parameterization was based on conformity of root simulations to tree root architecture reported in the literature. The model is deployed in four hypothetical urban soil scenarios, which are representative of planting sites commonly observed in urban settings. The analysis demonstrates that plausible tree root system architectures – specifically, commonly observed growth attributes - can be produced by Rootbox, but only after several adaptive changes to both the source code/model design are made. Custom soil models can integrate with the simulation to represent urban conditions by modifying both the growth direction and elongation of portions of the root architecture, and thus offer greater control over the output architecture. Rootbox offers a flexible method of simulating the architecture of tree root systems, but further research should focus on optimizing the model’s parameters and functions to enable greater user control over model output.


2021 ◽  
Author(s):  
Shehan Morandage ◽  
Eric Laloy ◽  
Andrea Schnepf ◽  
Harry Vereecken ◽  
Jan Vanderborght

Abstract Background and aims Characterizing root system architectures of field-grown crops is challenging as root systems are hidden in the soil. We investigate the possibility of estimating root architecture model parameters from soil core data in a Bayesian framework. Methods In a synthetic experiment, we simulated wheat root systems in a virtual field plot with the stochastic CRootBox model. We virtually sampled soil cores from this plot to create synthetic measurement data. We used the Markov chain Monte Carlo (MCMC) DREAM(ZS) sampler to estimate the most sensitive root system architecture parameters. To deal with the CRootBox model stochasticity and limited computational resources, we essentially added a stochastic component to the likelihood function, thereby turning the MCMC sampling into a form of approximate Bayesian computation (ABC). Results A few zero-order root parameters: maximum length, elongation rate, insertion angles, and numbers of zero-order roots, with narrow posterior distributions centered around true parameter values were identifiable from soil core data. Yet other zero-order and higher-order root parameters were not identifiable showing a sizeable posterior uncertainty. Conclusions Bayesian inference of root architecture parameters from root density profiles is an effective method to extract information about sensitive parameters hidden in these profiles. Equally important, this method also identifies which information about root architecture is lost when root architecture is aggregated in root density profiles.


2019 ◽  
Author(s):  
Thibaut Bontpart ◽  
Cristobal Concha ◽  
Valerio Giuffrida ◽  
Ingrid Robertson ◽  
Kassahun Admkie ◽  
...  

AbstractThe analysis of root system growth, root phenotyping, is important to inform efforts to enhance plant resource acquisition from soils. However, root phenotyping remains challenging due to soil opacity and requires systems that optimize root visibility and image acquisition. Previously reported systems require costly and bespoke materials not available in most countries, where breeders need tools to select varieties best adapted to local soils and field conditions. Here, we present an affordable soil-based growth container (rhizobox) and imaging system to phenotype root development in greenhouses or shelters. All components of the system are made from commodity components, locally available worldwide to facilitate the adoption of this affordable technology in low-income countries. The rhizobox is large enough (~6000 cm2 visible soil) to not restrict vertical root system growth for at least seven weeks after sowing, yet light enough (~21 kg) to be routinely moved manually. Support structures and an imaging station, with five cameras covering the whole soil surface, complement the rhizoboxes. Images are acquired via the Phenotiki sensor interface, collected, stitched and analysed. Root system architecture (RSA) parameters are quantified without intervention. RSA of a dicot (chickpea, Cicer arietinum L.) and a monocot (barley, Hordeum vulgare L.) species, which exhibit contrasting root systems, were analysed. The affordable system is relevant for efforts in Ethiopia and elsewhere to enhance yields and climate resilience of chickpea and other crops for improved food security.Significance StatementAn affordable system to characterize root system architecture of soil-grown plants was developed. Using commodity components, this will enable local efforts world-wide to breed for enhanced root systems.


2021 ◽  
Author(s):  
Justin Miron

Understanding the architecture of tree roots is an important component of urban forestry management practice. Tree roots are structurally and functionally important to the survival of trees, and this can be even more so in urban environments where underground space for roots is limited. Tree root architecture models can provide a complementary approach to traditional on-site field investigation methods. Root architecture models are unique in that they can simulate the spatial arrangements of root system structure explicitly, and allow investigators to create hypothetical simulations to test their assumptions about what may be driving root growth. The use of root architecture models in the literature is extensive and may be applied in diverse streams of investigation, but their application to tree root systems is less common. This research demonstrates a root architecture model, Rootbox, as a case study in the application of plant architecture models to simulate tree root growth in urban conditions. Model parameterization was based on conformity of root simulations to tree root architecture reported in the literature. The model is deployed in four hypothetical urban soil scenarios, which are representative of planting sites commonly observed in urban settings. The analysis demonstrates that plausible tree root system architectures – specifically, commonly observed growth attributes - can be produced by Rootbox, but only after several adaptive changes to both the source code/model design are made. Custom soil models can integrate with the simulation to represent urban conditions by modifying both the growth direction and elongation of portions of the root architecture, and thus offer greater control over the output architecture. Rootbox offers a flexible method of simulating the architecture of tree root systems, but further research should focus on optimizing the model’s parameters and functions to enable greater user control over model output.


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