Challenges in imaging and predictive modeling of rhizosphere processes


Autoria(s): Roose, T.; Keyes, S. D.; Daly, K. R.; Carminati, A.; Otten, Wilfred; Vetterlein, D.; Peth, S.
Contribuinte(s)

Abertay University. School of Science, Engineering and Technology

Royal Society

Biotechnology and Biological Sciences Research Council (BBSRC)

Natural Environment Research Council (NERC)

Engineering and Physical Sciences Research Council (EPSRC)

European Research Council (ERC)

Southampton University

Scottish Alliance for Geoscience, Environment and Society (SAGES)

Data(s)

10/11/2016

10/11/2016

08/04/2016

22/03/2016

Resumo

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.

Identificador

Roose, T. et al. 2016. Challenges in imaging and predictive modeling of rhizosphere processes. Plant and Soil. 407(1): pp9-38. doi: 10.1007/s11104-016-2872-7

0032-079X (print)

1573-5036 (online)

http://hdl.handle.net/10373/2525

https://dx.doi.org/10.1007/s11104-016-2872-7

Idioma(s)

en

Publicador

Springer

Relação

Plant and Soil, 407(1)

Direitos

The published version, © 2016 Springer, is available from: http://link.springer.com

Palavras-Chave #Rhizosphere #Mathematical modeling #X-ray CT #Chemical mapping #Correlative imaging #Rhizosphere
Tipo

Journal Article

published

n/a

n/a