Simulating Root Growth as a Function of Soil Strength and Yield With a Field-Scale Crop Model Coupled With a 3D Architectural Root Model

Seidel, Sabine J.; Gaiser, Thomas; Srivastava, Amit Kumar; Leitner, Daniel; Schmittmann, Oliver; Athmann, Miriam; Kautz, Timo; Guigue, Julien; Ewert, Frank; Schnepf, Andrea

doi:10.3389/fpls.2022.865188

Cited by 10 publications

(12 citation statements)

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“…Several models for root phenotyping are also being developed, such as 3D and 4D root architecture models, allometric models, R-SWMSbased model, response surface models, etc. [22]. These models predict the changes in root system architecture due to external stresses by coupling with different high-throughput imaging techniques (Figure 1).…”

Section: Root Phenotyping In Field/laboratorymentioning

confidence: 99%

“…R-SWMS-based model, response surface models, etc. [22]. These models predict the changes in root system architecture due to external stresses by coupling with different high-throughput imaging techniques (Figure 1).…”

Section: Root Phenotyping In Field/laboratorymentioning

confidence: 99%

“…Increased crown root angle and length [56] Lateral root development and aerenchyma formation [44] Shallow or deep root [22] Fewer but large size cortical cells [58] Increased root hair length and density [59] Salinity stress Cellular dehydration and ionic imbalance [60] Enhanced lignin and suberin deposition in cell wall [20] Root bending away from saline environment [61] Growth of both primary and lateral root get arrested [62] Decreased root hair length and density [63] Temperature stress…”

Section: Drought Stressmentioning

confidence: 99%

“…Autophagyassociated genes were found to be upregulated only in drought-sensitive species under drought stress [71]. Drought-tolerant varieties have a distinct RSA, including a shallow or deep root, compared to sensitive genotypes, but they do not have a significant difference in physiological mechanism [22]. In drought-tolerant species under drought-stress conditions, hormone signalling genes, such as ERFs, AUX/IAA, and GA2ox, as well as ABA and brassinosteroid biosynthesis play important roles.…”

Section: Drought Stressmentioning

confidence: 99%

“…For the development of lateral roots in rice, OsCYP2/LRL2 plays a critical role, besides degradation of the auxin-responsive proteins [60]. Auxin negatively regulates DRO1, which initiates asymmetric root growth and trigger downward bending of the root in response to gravity [22]. In the root tip and root cap cells, flavonoid gets accumulated, which is released in the rhizosphere from the root [111].…”

Section: Metabolites In Root Developmentmentioning

confidence: 99%

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Root System Architecture and Omics Approaches for Belowground Abiotic Stress Tolerance in Plants

2022

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Plant growth and productivity is negatively affected by several abiotic stresses. To overcome the antagonistic effect of a changing environment, plants have evolved several modifications at the physiological as well as molecular levels. Besides being a vital organ for a plant’s nutrient uptake, roots also plays a significant role in abiotic stress regulation. This review provides insight into changing Root System Architecture (RSA) under varying environmental stimuli using high-throughput omics technologies. Several next-generation and high-throughput omics technologies, such as phenomics, genomics, transcriptomics, proteomics, and metabolomics, will help in the analysis of the response of root architectural traits under climatic vagaries and their impact on crop yield. Various phenotypic technologies have been implied for the identification of diverse root traits in the field as well as laboratory conditions, such as root-box pinboards, rhizotrons, shovelomics, ground-penetrating radar, etc. These phenotypic analyses also help in identifying the genetic regulation of root-related traits in different crops. High-throughput genomic as well as transcriptome analysis has led researchers to unravel the role of the root system in response to these environmental cues, even at the single-cell level. Detailed analysis at the protein and metabolite levels can provide a better understanding of the response of roots under different abiotic stresses. These technologies will help in the improvement of crop productivity and development of resistant varieties.

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Section: Root Phenotyping In Field/laboratorymentioning

confidence: 99%

Section: Root Phenotyping In Field/laboratorymentioning

confidence: 99%

Section: Drought Stressmentioning

confidence: 99%

Section: Drought Stressmentioning

confidence: 99%

Section: Metabolites In Root Developmentmentioning

confidence: 99%

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Root System Architecture and Omics Approaches for Belowground Abiotic Stress Tolerance in Plants

2022

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3–4D soil model as challenge for future soil research: Quantitative soil modeling based on the solid phase

Gerke

Vogel

Weber

et al. 2022

J. Plant Nutr. Soil Sci.

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A 3-4D soil model represents a logical step forward from one-dimensional soil columns (1D), two-dimensional soil maps (2D), and three-dimensional soil volumes (3D) toward dynamic soil models (4D), with time as the fourth dimension. The challenge is to develop modeling tools that account for the states of soil properties, including the spatial structure of solids and pores, as well as their dynamics, including soil mass and solute transfers in landscapes. Our envisioned 3-4D soil model approach aims at improving the capability to predict fundamental soil functions (e.g., plant growth, storage, matter fluxes) that provide ecosystem services in the socioeconomic context.This study provides a structured overview on current soil models, challenges, open questions, and urgent research needs for developing a 3-4D soil model. A 3-4D soil model should provide an inventory of spatially distributed and temporally variable soil properties. As basis for this, we propose a mass balance model for the solid phase, which needs to be supplemented by a model describing its structure. This should eventually provide adequate 3D parameter sets for the numerical modeling of soil functions (e.g., flow and transport). The target resolution is decameters in the horizontal plane and centimeters to decimeters in the vertical direction to represent characteristic soil properties and soil horizons. The actual state of soils and their properties can be estimated from spatial data that represent the soil forming factors, with the use of machine learning tools. Improved modeling of the dynamics of soil bulk density, biological processes, and the pore structure are required to relate the solid mass balance to matter fluxes.A 3-4D soil model can be built from several types of modeling approaches. We distinguish between (1) process models that simulate mass balances, fluxes and soil structure dynamics, (2) statistical pedometric models using machine learning and geostatistics to estimate the soil inventory within landscapes, and (3) pedotransfer functions to link observable attributes to specific model parameters required to simulate soil functions including water and matter fluxes. This should provide the prerequisites to predict the spatial distribution of soil functions and their changes in response to external forcing. This endeavor can draw upon many already established models and techniques, yet combining them into a newly created 3-4D soil model is a truly an ambitious, but promisingThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Root phenotypes for improved nitrogen capture

Lynch,

Galindo-Castañeda,

Schneider

et al. 2023

Plant Soil

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Background Suboptimal nitrogen availability is a primary constraint for crop production in low-input agroecosystems, while nitrogen fertilization is a primary contributor to the energy, economic, and environmental costs of crop production in high-input agroecosystems. In this article we consider avenues to develop crops with improved nitrogen capture and reduced requirement for nitrogen fertilizer. Scope Intraspecific variation for an array of root phenotypes has been associated with improved nitrogen capture in cereal crops, including architectural phenotypes that colocalize root foraging with nitrogen availability in the soil; anatomical phenotypes that reduce the metabolic costs of soil exploration, improve penetration of hard soil, and exploit the rhizosphere; subcellular phenotypes that reduce the nitrogen requirement of plant tissue; molecular phenotypes exhibiting optimized nitrate uptake kinetics; and rhizosphere phenotypes that optimize associations with the rhizosphere microbiome. For each of these topics we provide examples of root phenotypes which merit attention as potential selection targets for crop improvement. Several cross-cutting issues are addressed including the importance of soil hydrology and impedance, phenotypic plasticity, integrated phenotypes, in silico modeling, and breeding strategies using high throughput phenotyping for co-optimization of multiple phenes. Conclusions Substantial phenotypic variation exists in crop germplasm for an array of root phenotypes that improve nitrogen capture. Although this topic merits greater research attention than it currently receives, we have adequate understanding and tools to develop crops with improved nitrogen capture. Root phenotypes are underutilized yet attractive breeding targets for the development of the nitrogen efficient crops urgently needed in global agriculture.

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Simulating Root Growth as a Function of Soil Strength and Yield With a Field-Scale Crop Model Coupled With a 3D Architectural Root Model

Cited by 10 publications

References 54 publications

Root System Architecture and Omics Approaches for Belowground Abiotic Stress Tolerance in Plants

Root System Architecture and Omics Approaches for Belowground Abiotic Stress Tolerance in Plants

3–4D soil model as challenge for future soil research: Quantitative soil modeling based on the solid phase

Root phenotypes for improved nitrogen capture

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