Advances in root phenotyping: high-throughput imaging, computational tools and integrative approaches for crop...

Area of Science:

• Plant Science
• Agricultural Science
• Environmental Science

Background:

• Climate change poses significant threats to global agriculture through abiotic stresses and reduced crop yields.
• Understanding root-mediated traits is crucial for enhancing crop resource acquisition and stress resilience.

Purpose of the Study:

• To synthesize recent advances in root-centered plant phenomics and high-throughput phenotyping (HTP).
• To emphasize how HTP enables scalable, high-resolution characterization of root traits for comparative analysis.
• To explore the integration of root phenotyping within a whole-plant and physiological framework.

Main Methods:

• Utilizing multimodal imaging techniques such as X-ray computed tomography (CT) and magnetic resonance imaging (MRI).
• Employing machine learning-integrated rhizotrons for detailed root system architecture reconstruction.
• Integrating organ-specific assessments with physiological phenomics (spectral, thermal data) for whole-plant analysis.

Main Results:

• HTP facilitates detailed reconstruction and temporal dynamics of root systems under various conditions.
• Integrated approaches link specific root traits (e.g., rooting depth) to canopy-level physiological responses under stress.
• Multimodal imaging and physiological phenomics offer insights into water-use dynamics and nutrient acquisition.

Conclusions:

• Significant bottlenecks in data interoperability, scalability, and standardization need addressing.
• Future progress relies on integrating root phenomics with genomics, predictive modeling, and digital twins.
• These integrated approaches are vital for improving resource-use efficiency, yield stability, and climate resilience in cropping systems.