Evidence map›Paper›PMID 35668793›Full record

ArticleFrontiers in plant science2022

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

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

Abstract read
In one paragraph

Article in Frontiers in plant science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Sabine Julia SeidelCrop Science, Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany.
Thomas GaiserCrop Science, Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany.
Amit Kumar SrivastavaCrop Science, Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany.
Daniel LeitnerSimulationswerkstatt, Linz, Austria.
Oliver SchmittmannInstitute of Agricultural Engineering, University of Bonn, Bonn, Germany.
Miriam AthmannOrganic Farming and Cropping Systems, University of Kassel, Witzenhausen, Germany.
Timo KautzAlbrecht Daniel Thaer-Institut für Agrar- und Gartenbauwissenschaften, Humboldt-Universität zu Berlin, Berlin, Germany.
Julien GuigueChair of Soil Science, TUM School of Life Sciences, Weihenstephan, Germany.
Frank EwertCrop Science, Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany.
Andrea SchnepfInstitute for Bio- and Geosciences, IBG-3, Agrosphere, Forschungszentrum Jülich GmbH, Jülich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate prediction of root growth and related resource uptake is crucial to accurately simulate crop growth especially under unfavorable environmental conditions. We coupled a 1D field-scale crop-soil model running in the SIMPLACE modeling framework with the 3D architectural root model CRootbox on a daily time step and implemented a stress function to simulate root elongation as a function of soil bulk density and matric potential. The model was tested with field data collected during two growing seasons of spring barley and winter wheat on Haplic Luvisol. In that experiment, mechanical strip-wise subsoil loosening (30-60 cm) (DL treatment) was tested, and effects on root and shoot growth at the melioration strip as well as in a control treatment were evaluated. At most soil depths, strip-wise deep loosening significantly enhanced observed root length densities (RLDs) of both crops as compared to the control. However, the enhanced root growth had a beneficial effect on crop productivity only in the very dry season in 2018 for spring barley where the observed grain yield at the strip was 18% higher as compared to the control. To understand the underlying processes that led to these yield effects, we simulated spring barley and winter wheat root and shoot growth using the described field data and the model. For comparison, we simulated the scenarios with the simpler 1D conceptual root model. The coupled model showed the ability to simulate the main effects of strip-wise subsoil loosening on root and shoot growth. It was able to simulate the adaptive plasticity of roots to local soil conditions (more and thinner roots in case of dry and loose soil). Additional scenario runs with varying weather conditions were simulated to evaluate the impact of deep loosening on yield under different conditions. The scenarios revealed that higher spring barley yields in DL than in the control occurred in about 50% of the growing seasons. This effect was more pronounced for spring barley than for winter wheat. Different virtual root phenotypes were tested to assess the potential of the coupled model to simulate the effect of varying root traits under different conditions.

Indexed as

deep looseningin silico exploration of GxExMplasticityroot architecture modelingroot phenotypessimulated root length densitysubsoil melioration

Identifiers

PMID35668793
PMCPMC9164166

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.