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* Ihre Aktion  suchen [und] ([PPN] Pica-Produktionsnummer) 769315410
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PPN: 
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Titel: 
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Sprache/n: 
Englisch
Veröffentlichungsangabe: 
2013
Umfang: 
Online-Ressource (PDF-Datei: V, 114 S., 4918 KB)
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Nebent.: Entwicklung einer neuen, nicht invasiven, optischen Methode für die quantitative Darstellung von pH und Sauerstoffdynamiken in Böden
Langzeitarchivierung Langzeitarchivierung gewährleistet
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Potsdam, Universität Potsdam, Diss., 2013
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Dewey Dezimal-Klassifikation: [23sdnb] 610 ; 550
Inhalt: 
In soils and sediments there is a strong coupling between local biogeochemical processes and the distribution of water, electron acceptors, acids and nutrients. Both sides are closely related and affect each other from small scale to larger scales. Soil structures such as aggregates, roots, layers or macropores enhance the patchiness of these distributions. At the same time it is difficult to access the spatial distribution and temporal dynamics of these parameter. Noninvasive imaging techniques with high spatial and temporal resolution overcome these limitations. And new non-invasive techniques are needed to study the dynamic interaction of plant roots with the surrounding soil, but also the complex physical and chemical processes in structured soils. In this study we developed an efficient non-destructive in-situ method to determine biogeochemical parameters relevant to plant roots growing in soil. This is a quantitative fluorescence imaging method suitable for visualizing the spatial and temporal pH changes around roots. We adapted the fluorescence imaging set-up and coupled it with neutron radiography to study simultaneously root growth, oxygen depletion by respiration activity and root water uptake. The combined set up was subsequently applied to a structured soil system to map the patchy structure of oxic and anoxic zones induced by a chemical oxygen consumption reaction for spatially varying water contents. Moreover, results from a similar fluorescence imaging technique for nitrate detection were complemented by a numerical modeling study where we used imaging data, aiming to simulate biodegradation under anaerobic, nitrate reducing conditions.
 
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