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Wheat Field ERT — Multi-Genotype Root Water Uptake Analysis

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.

Repository Structure

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

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This project uses field-based ERT with ML calibration to quantify root water uptake in wheat. Root architectures were pre-selected in greenhouse experiments, and field results are validated with plant physiology and microclimate data to compare genotype water-use strategies under drought.

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