Emerging sensing, imaging, and computational technologies to scale nano-to macroscale rhizosphere dynamics - Review and research perspectives

Amir H Ahkami ¹, Odeta Qafoku ¹, Tiina Roose ²

⁰Environmental Molecular Sciences Laboratory (EMSL), Pacific Northwest National Laboratory (PNNL), Richland, WA, 99454, USA.

Soil Biology & Biochemistry +

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September 6, 2024

View abstract on PubMed

Summary

Understanding the rhizosphere, the soil region around plant roots, is key for carbon storage and climate change mitigation. New sensing, imaging, and modeling technologies are improving our ability to study these complex soil-plant interactions.

Area Of Science

Soil Science
Ecology
Biogeochemistry

Background

The rhizosphere, the soil region influenced by plant roots, is a complex habitat critical for global carbon cycling.
Understanding rhizosphere processes is vital for sustainable ecosystems, carbon storage, and climate change mitigation.
Studying the rhizosphere requires advanced integrated technologies to decode its complexity across scales.

Purpose Of The Study

To review emerging sensing, imaging, and computational modeling approaches for studying the rhizosphere.
To discuss future directions in developing in situ rhizosphere sensing technologies.
To bridge the gap between local-scale rhizosphere interactions and ecosystem-scale impacts.

Main Methods

Review of integrated multimodal imaging for tracking elements and carbon flow (nano- to microscale).
Discussion of synthetic soil/plant habitats for bridging lab-to-field studies.
Description of genetically encoded biosensors and nanotechnology for monitoring nutrient/chemical exchange.
Review of field-deployable sensing technologies (e.g., planar optodes) for rhizosphere gradients.
Integration of model-experiment and image-based modeling approaches.
Utilizing experimental platforms like SMART soils testbeds for ecosystem behavior analysis.

Main Results

Emerging technologies offer advanced capabilities for rhizosphere research.
In situ sensing technologies show promise for correlating local interactions with ecosystem impacts.
Multimodal imaging, synthetic habitats, biosensors, and field-deployable sensors are advancing understanding.
Linking rhizosphere interactions to ecosystem sensing requires advanced predictive models.
Experimental platforms coupled with models can explore ecosystem responses to perturbations.

Conclusions

Novel high-resolution imaging, remote biosensing, and advanced computational models will enable detection and upscaling of rhizosphere processes.
Future studies will improve predictions of rhizosphere functions at ecosystem and global scales.
Integrated technologies are essential for decoding the complexity of the rhizosphere and its global impact.

Keywords:

ModEx Rhizodeposition biosensors carbon flow image-based modeling nutrients gradients

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