G. Lobet

Root System Architecture Reorganization Under Decreasing Soil Phosphorus Lowers Root System Conductance of Zea mays

This study examines how decreasing phosphorus availability affects root system architecture and conductance in Zea mays, showing reduced conductance with lower phosphorus levels.

Root hydraulic properties: an exploration of their variability across scales

This paper reviews empirical studies on root hydraulic properties across scales, identifies factors influencing their variability, and highlights the importance of root system age and measurement conditions.

Development and calibration of the FSPM CPlantBox to represent the interactions between water and carbon fluxes in the soil-plant-atmosphere continuum

The paper develops and calibrates CPlantBox to simulate water and carbon flux interactions in the soil-plant-atmosphere continuum under varying climate conditions.

Phloem anatomy restricts root system architecture development: theoretical clues from in silico experiments.

The paper uses computational models to show that phloem hydraulics significantly affect root growth rates and final length by limiting carbon flow.

Combining deep learning and automated feature extraction to analyze minirhizotron images: development and validation of a new pipeline

This paper develops and validates a pipeline combining deep learning and automated feature extraction to analyze minirhizotron images, showing high accuracy and significantly faster processing than manual methods.

Uncovering natural variation in root system architecture and growth dynamics using a robotics-assisted phenomics platform

This study automates the GLO-Roots platform with robotics and image analysis to examine natural variation in Arabidopsis root system architecture over time, revealing complex traits correlated with climate variables.

Evidence for a multicellular symplasmic water pumping mechanism across vascular plant roots

The paper demonstrates a multicellular symplasmic water pumping mechanism in vascular plant roots by incorporating solute concentration gradients into water flow models, resolving a long-standing enigma about water movement uphill of water potential gradients.

Connecting the dots between root cross-section images and modelling tools to create a high resolution root system hydraulic maps in Zea mays.

The paper uses root cross-section images and modeling tools to generate high-resolution hydraulic conductivity maps for maize root types.

QuoVidi : a open-source web application for the organisation of large scale biological treasure hunts

QuoVidi is an open-source web platform for organizing large-scale biological treasure hunts to enhance student engagement and learning through real-world observation and submission of geotagged images.

CPlantBox, a whole plant modeling framework for the simulation of water and carbon related processes

CPlantBox is a whole plant modeling framework that simulates water and carbon flows, validated against experimental data across multiple case studies.

Call for participation: Collaborative benchmarking of functional-structural root architecture models. The case of root water uptake.

The paper calls for collaborative benchmarking of functional-structural root architecture models to improve their accuracy and reliability in simulating root water uptake.

MARSHAL, a novel tool for virtual phenotyping of maize root system hydraulic architectures

The paper introduces MARSHAL, a tool for generating and analyzing maize root system hydraulic architectures, compatible with observations and useful for virtual breeding.

GRANAR, a new computational tool to better understand the functional importance of root anatomy

GRANAR generates digital root anatomical networks to estimate hydraulic properties and quantify anatomical influences on radial conductivity.

Connecting the dots between computational tools to analyse soil-root water relations

The paper presents a network of computational tools for analyzing soil-root water relations, showing how they can be connected to improve data interpretation and parameterization.

Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large scale genetic studies

The paper combines semi-automated image analysis with machine learning to accelerate genetic studies of plant root systems, reducing analysis time by 73% and identifying quantitative trait loci.

CRootBox: A Structural-Functional Modelling Framework For Root Systems

CRootBox is a root architecture model that simulates root growth and interactions with soil environments, demonstrating its use in various scenarios including field-scale simulations and coupling with soil physics.

Using a structural root system model to evaluate and improve the accuracy of root image analysis pipelines.

The paper evaluates root image analysis pipelines using a synthetic ground-truth dataset and highlights the importance of calibration for accurate results.