Challenges in imaging and predictive modeling of rhizosphere processes
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) |
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Data(s) |
10/11/2016
10/11/2016
08/04/2016
22/03/2016
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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) |
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 |