Challenges in imaging and predictive modeling of rhizosphere process

Date

2016-04-08

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Springer

Department

Type

Article

ISSN

0032-079X

Format

Free to read from

Citation

Roose T, Keyes S, Daly K, Carminati A, Otten W, Vetterlein D, Peth S, Challenges in imaging and predictive modeling of rhizosphere processes, Plant and Soil, Vol. 407, Issue 1-2, October 2016, pp. 9-38

Abstract

Background

Plant-soil interaction is central to human food production and ecosystem function. Thus, it is essential to not only understand, but also to develop predictive mathematical models which can be used to assess how climate and soil management practices will affect these interactions. Scope

In this paper we review the current developments in structural and chemical imaging of rhizosphere processes within the context of multiscale mathematical image based modeling. We outline areas that need more research and areas which would benefit from more detailed understanding. Conclusions

We conclude that the combination of structural and chemical imaging with modeling is an incredibly powerful tool which is fundamental for understanding how plant roots interact with soil. We emphasize the need for more researchers to be attracted to this area that is so fertile for future discoveries. Finally, model building must go hand in hand with experiments. In particular, there is a real need to integrate rhizosphere structural and chemical imaging with modeling for better understanding of the rhizosphere processes leading to models which explicitly account for pore scale processes.

Description

Software Description

Software Language

Github

Keywords

Rhizosphere, Mathematical modeling, X-ray CT, Chemical mapping, Correlative imaging

DOI

Rights

Attribution 4.0 International

Relationships

Relationships

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Funder/s