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

deep loosening in silico exploration of GxExM plasticity root architecture modeling root phenotypes simulated root length density subsoil melioration

Journal

Frontiers in plant science
ISSN: 1664-462X
Titre abrégé: Front Plant Sci
Pays: Switzerland
ID NLM: 101568200

Informations de publication

Date de publication:
2022
Historique:
received: 18 02 2022
accepted: 11 04 2022
entrez: 7 6 2022
pubmed: 8 6 2022
medline: 8 6 2022
Statut: epublish

Résumé

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.

Identifiants

pubmed: 35668793
doi: 10.3389/fpls.2022.865188
pmc: PMC9164166
doi:

Types de publication

Journal Article

Langues

eng

Pagination

865188

Informations de copyright

Copyright © 2022 Seidel, Gaiser, Srivastava, Leitner, Schmittmann, Athmann, Kautz, Guigue, Ewert and Schnepf.

Déclaration de conflit d'intérêts

DL was employed by Simulationswerkstatt. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Sabine Julia Seidel (SJ)

Crop Science, Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany.

Thomas Gaiser (T)

Crop Science, Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany.

Amit Kumar Srivastava (AK)

Crop Science, Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany.

Daniel Leitner (D)

Simulationswerkstatt, Linz, Austria.

Oliver Schmittmann (O)

Institute of Agricultural Engineering, University of Bonn, Bonn, Germany.

Miriam Athmann (M)

Organic Farming and Cropping Systems, University of Kassel, Witzenhausen, Germany.

Timo Kautz (T)

Albrecht Daniel Thaer-Institut für Agrar- und Gartenbauwissenschaften, Humboldt-Universität zu Berlin, Berlin, Germany.

Julien Guigue (J)

Chair of Soil Science, TUM School of Life Sciences, Weihenstephan, Germany.

Frank Ewert (F)

Crop Science, Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany.
Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany.

Andrea Schnepf (A)

Institute for Bio- and Geosciences, IBG-3, Agrosphere, Forschungszentrum Jülich GmbH, Jülich, Germany.

Classifications MeSH