Literature DB >> 24012600

Dynamic root growth and architecture responses to limiting nutrient availability: linking physiological models and experimentation.

Johannes A Postma1, Ulrich Schurr2, Fabio Fiorani3.   

Abstract

In recent years the study of root phenotypic plasticity in response to sub-optimal environmental factors and the genetic control of these responses have received renewed attention. As a path to increased productivity, in particular for low fertility soils, several applied research projects worldwide target the improvement of crop root traits both in plant breeding and biotechnology contexts. To assist these tasks and address the challenge of optimizing root growth and architecture for enhanced mineral resource use, the development of realistic simulation models is of great importance. We review this research field from a modeling perspective focusing particularly on nutrient acquisition strategies for crop production on low nitrogen and low phosphorous soils. Soil heterogeneity and the dynamics of nutrient availability in the soil pose a challenging environment in which plants have to forage efficiently for nutrients in order to maintain their internal nutrient homeostasis throughout their life cycle. Mathematical models assist in understanding plant growth strategies and associated root phenes that have potential to be tested and introduced in physiological breeding programs. At the same time, we stress that it is necessary to carefully consider model assumptions and development from a whole plant-resource allocation perspective and to introduce or refine modules simulating explicitly root growth and architecture dynamics through ontogeny with reference to key factors that constrain root growth. In this view it is important to understand negative feedbacks such as plant-plant competition. We conclude by briefly touching on available and developing technologies for quantitative root phenotyping from lab to field, from quantification of partial root profiles in the field to 3D reconstruction of whole root systems. Finally, we discuss how these approaches can and should be tightly linked to modeling to explore the root phenome.
© 2013.

Entities:  

Keywords:  Abiotic stress; Biomass allocation; Low fertility soils; Modeling; Non-invasive; Nutrient uptake; Phenotyping; Resource use efficiency; Root architecture; Root growth

Mesh:

Year:  2013        PMID: 24012600     DOI: 10.1016/j.biotechadv.2013.08.019

Source DB:  PubMed          Journal:  Biotechnol Adv        ISSN: 0734-9750            Impact factor:   14.227


  12 in total

1.  The optimal lateral root branching density for maize depends on nitrogen and phosphorus availability.

Authors:  Johannes Auke Postma; Annette Dathe; Jonathan Paul Lynch
Journal:  Plant Physiol       Date:  2014-05-21       Impact factor: 8.340

2.  Image-based high-throughput field phenotyping of crop roots.

Authors:  Alexander Bucksch; James Burridge; Larry M York; Abhiram Das; Eric Nord; Joshua S Weitz; Jonathan P Lynch
Journal:  Plant Physiol       Date:  2014-09-03       Impact factor: 8.340

3.  Root foraging elicits niche complementarity-dependent yield advantage in the ancient 'three sisters' (maize/bean/squash) polyculture.

Authors:  Chaochun Zhang; Johannes A Postma; Larry M York; Jonathan P Lynch
Journal:  Ann Bot       Date:  2014-10-01       Impact factor: 4.357

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

Authors:  Sabine Julia Seidel; Thomas Gaiser; Amit Kumar Srivastava; Daniel Leitner; Oliver Schmittmann; Miriam Athmann; Timo Kautz; Julien Guigue; Frank Ewert; Andrea Schnepf
Journal:  Front Plant Sci       Date:  2022-05-20       Impact factor: 6.627

5.  OpenSimRoot: widening the scope and application of root architectural models.

Authors:  Johannes A Postma; Christian Kuppe; Markus R Owen; Nathan Mellor; Marcus Griffiths; Malcolm J Bennett; Jonathan P Lynch; Michelle Watt
Journal:  New Phytol       Date:  2017-06-27       Impact factor: 10.151

6.  Non-invasive imaging of plant roots in different soils using magnetic resonance imaging (MRI).

Authors:  Daniel Pflugfelder; Ralf Metzner; Dagmar van Dusschoten; Rüdiger Reichel; Siegfried Jahnke; Robert Koller
Journal:  Plant Methods       Date:  2017-11-17       Impact factor: 4.993

7.  Comparative UAV and Field Phenotyping to Assess Yield and Nitrogen Use Efficiency in Hybrid and Conventional Barley.

Authors:  Shawn C Kefauver; Rubén Vicente; Omar Vergara-Díaz; Jose A Fernandez-Gallego; Samir Kerfal; Antonio Lopez; James P E Melichar; María D Serret Molins; José L Araus
Journal:  Front Plant Sci       Date:  2017-10-10       Impact factor: 5.753

8.  Editorial: Roots-The Hidden Provider.

Authors:  Janin Riedelsberger; Michael R Blatt
Journal:  Front Plant Sci       Date:  2017-06-13       Impact factor: 5.753

9.  Phenotyping field-state wheat root system architecture for root foraging traits in response to environment×management interactions.

Authors:  Xinxin Chen; Yinian Li; Ruiyin He; Qishuo Ding
Journal:  Sci Rep       Date:  2018-02-08       Impact factor: 4.379

10.  Sowing Density: A Neglected Factor Fundamentally Affecting Root Distribution and Biomass Allocation of Field Grown Spring Barley (Hordeum Vulgare L.).

Authors:  Vera L Hecht; Vicky M Temperton; Kerstin A Nagel; Uwe Rascher; Johannes A Postma
Journal:  Front Plant Sci       Date:  2016-06-28       Impact factor: 5.753

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