Challenges in imaging and predictive modeling of rhizosphere processes

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dc.identifier.uri http://dx.doi.org/10.15488/17031
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/17159
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, W.
dc.contributor.author Vetterlein, D.
dc.contributor.author Peth, S.
dc.date.accessioned 2024-04-15T07:35:27Z
dc.date.available 2024-04-15T07:35:27Z
dc.date.issued 2016
dc.identifier.citation Roose, T.; Keyes, S.D.; Daly, K.R.; Carminati, A.; Otten, W. et al.: Challenges in imaging and predictive modeling of rhizosphere processes. In: Plant and Soil 407 (2016), Nr. 1-2, S. 9-38. DOI: https://doi.org/10.1007/s11104-016-2872-7
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. eng
dc.language.iso eng
dc.publisher Cham : Springer Nature Switzerland AG
dc.relation.ispartofseries Plant and Soil 407 (2016), Nr. 1-2
dc.rights CC BY 4.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by/4.0
dc.subject Chemical mapping eng
dc.subject Correlative imaging eng
dc.subject Mathematical modeling eng
dc.subject Rhizosphere eng
dc.subject X-ray CT eng
dc.subject.ddc 570 | Biowissenschaften, Biologie
dc.subject.ddc 580 | Pflanzen (Botanik)
dc.title Challenges in imaging and predictive modeling of rhizosphere processes eng
dc.type Article
dc.type Text
dc.relation.essn 1573-5036
dc.relation.issn 0032-079X
dc.relation.doi https://doi.org/10.1007/s11104-016-2872-7
dc.bibliographicCitation.issue 1-2
dc.bibliographicCitation.volume 407
dc.bibliographicCitation.firstPage 9
dc.bibliographicCitation.lastPage 38
dc.description.version publishedVersion eng
tib.accessRights frei zug�nglich


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