This project integrates Electrical Resistivity Tomography (ERT) with machine learning calibration to quantify root water uptake (RWU) in field-grown wheat under drought conditions. Root system architectures were pre-characterized in controlled greenhouse experiments, and field-scale RWU estimates are validated using plant physiology (fluorescence, stomatal conductance) and microclimate data (VPD, PAR) to compare genotype-specific water-use strategies.
ERT_RWU_Wheat_Project/
├── codes/
│ ├── main_pipeline_all_plots.py
│ ├── validate_ert_tdr.py
│ ├── Rho_log10_plot.py
│ ├── Rho_change_plot.py
│ └── plant_physiology_figures.py
│
├── raw_data/
│ ├── inversion_res_dat/
│ ├── tdr_exports/
│ ├── metadata/
│ └── climate/
│
├── tables/
├── figures/
└── README.md