Challenges in imaging and predictive modeling of rhizosphere process

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dc.contributor.author Roose, T.
dc.contributor.author Keyes, S. D.
dc.contributor.author Daly, K. R.
dc.contributor.author Carminati, A.
dc.contributor.author Otten, Wilfred
dc.contributor.author Vetterlein, D.
dc.contributor.author Peth, S.
dc.date.accessioned 2018-04-24T15:43:01Z
dc.date.available 2018-04-24T15:43:01Z
dc.date.issued 2016-04-08
dc.identifier.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 en_UK
dc.identifier.issn 0032-079X
dc.identifier.uri http://dx.doi.org/10.1007/s11104-016-2872-7
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/13165
dc.description.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. en_UK
dc.language.iso en en_UK
dc.publisher Springer en_UK
dc.rights Attribution 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by/4.0/ *
dc.subject Rhizosphere en_UK
dc.subject Mathematical modeling en_UK
dc.subject X-ray CT en_UK
dc.subject Chemical mapping en_UK
dc.subject Correlative imaging en_UK
dc.title Challenges in imaging and predictive modeling of rhizosphere process en_UK
dc.type Article en_UK


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