Linking wheat root anatomy to hydraulic function under contrasting nitrogen treatments
Masterthesis
Research area
Crop science, Data Science, Image Analysis
Motivation / State of the art / Relevance
Acquiring information about plant roots is key when trying to understand processes involved in the water and nutrient uptake of crops. However, due to the difficulties involved in root sampling, relatively little is known about the variability of root physiological traits between winter wheat cultivars and nitrogen fertilization treatments. To investigate how cultivars choice and nitrogen fertilization can impact the root water uptake capacity of winter wheat, we conducted a two-year field experiment with several winter wheat cultivars grown under contrasting nitrogen fertilization treatments.
Objectives
This project investigates how genotype and nitrogen availability interact to shape root anatomical traits in winter wheat and how these traits influence root hydraulics across scales.
Methodology / Procedure / Workscope / external cooperation
Cross-section images from three experiments, covering contrasting genotypes and nitrogen treatments, will be analyzed to extract key anatomical traits such as xylem number and tissue dimension (e.g., the thickness of root layers involved in water transport). These traits will be used to parameterize the GRANAR–MECHA model to simulate the radial (water movement into the root) and axial (water movement along the root axis) components of root water flow, resulting in segment-scale hydraulic properties. Subsequently, these properties will be used as input for the whole-plant model CPlantBox to assess how tissue-level changes influence water transport through the entire root system. By combining image analysis, mechanistic modeling, and sensitivity analyses, the study will quantify the impact of genotype × nitrogen interactions on root hydraulics from tissue to plant scale. The work is loosely building up on previous work of different cultivars under uniform nitrogen fertilization conditions (https://doi.org/10.1093/plphys/kiaf166; https://doi.org/10.1093/jxb/erag177; https://doi.org/10.1002/csc2.70263).
Expected results
We expect to see differences between the root physiology of the cultivars and in their reaction towards fertilization.
Timeframe
6 Month
Language
English or German
Previous knowledge
Interest in Roots. Basic knowledge of R or Phython for data analysis would be helpful.
Supervisor
Dominik Behrend, Juan C. Baca Cabrera, Thomas Gaiser