ChronoRoot 2.0 is an integrated open-source platform that combines affordable hardware with advanced artificial intelligence to enable sophisticated temporal plant phenotyping.

Depending on your research needs, the system offers two distinct workflows: a Detailed Analysis for individual plant architecture or a High-Throughput Screening for analyzing large populations.

• Multi-organ tracking: Segment and track six distinct plant structures (main root, lateral roots, seed, hypocotyl, leaves, and petiole).
• Deep Learning Integration: Powered by nnU-Net for robust segmentation.
• Novel Metrics: Comprehensive measurements including gravitropic response parameters.
• Quality Control: Interfaces designed for real-time human-in-the-loop validation.

A typical ChronoRoot 2.0 experiment follows this pipeline:

1. Data Acquisition: Capture temporal image sequences (typically every 15 mins) using the ChronoRoot Hardware.
2. Segmentation: Process raw images using the Segmentation App. This utilizes GPU acceleration to automatically identify plant organs.
3. Analysis: Load the segmented data into one of the analysis interfaces:
   • ChronoRoot App: For detailed architectural analysis of individual plants.
   • Screening App: For high-throughput automated analysis of multiple plants.
4. Reporting: Export statistical analysis, visualizations, and group comparisons.

Before installing, ensure your system meets the following criteria:

Note on macOS: Native installation is not supported. Mac users must use the Docker method.

ChronoRoot 2.0 offers automated installers that set up the environment and create Desktop Shortcuts for a point-and-click experience. Choose the method that best fits your setup.

Both native and apptainer installations provide three applications, with shortcuts as follows:

Icon	Application	Description
	ChronoRoot App	Standard detailed architectural analysis.
	ChronoRoot Screening	High-throughput automated screening.
	ChronoRoot Segmentation	nnU-Net image segmentation.

Best for: Personal computers (Linux or Windows WSL) where you want desktop integration.

wget https://raw.githubusercontent.com/chronoroot/ChronoRoot2/master/installer_conda_linux.sh
bash installer_conda_linux.sh

1. Ensure WSL2 is installed and open your Ubuntu terminal.
2. Run the following:

wget https://raw.githubusercontent.com/chronoroot/ChronoRoot2/master/installer_conda_wsl.sh
bash installer_conda_wsl.sh

Best for: HPC Clusters or users preferring single-file containers.

wget https://raw.githubusercontent.com/chronoroot/ChronoRoot2/master/apptainerInstaller/installer_linux.sh
bash installer_linux.sh

wget https://raw.githubusercontent.com/chronoroot/ChronoRoot2/master/apptainerInstaller/installer_windows.sh
bash installer_windows.sh

Best for: macOS users or advanced sandbox environments.

If you are using Docker, you will interact with the software via the terminal.

1. Pull the Image:

docker pull ngaggion/chronoroot:latest

2. Run the Container:

Linux:

xhost +local:docker
MOUNT="YOUR_LOCAL_DATA_PATH"

docker run -it --gpus all \
    -u $(id -u):$(id -g) \
    -v /etc/passwd:/etc/passwd:ro \
    -v /etc/group:/etc/group:ro \
    -v $MOUNT:/DATA/ \
    -e DISPLAY=$DISPLAY \
    -v /tmp/.X11-unix:/tmp/.X11-unix \
    --shm-size=8gb \
    ngaggion/chronoroot:latest

Windows (WSL2):

MOUNT="/mnt/c/path/to/your/data"
# Ensure X Server (like VcXsrv) is running if not using WSLg

docker run -it --gpus all \
    -u $(id -u):$(id -g) \
    -v /etc/passwd:/etc/passwd:ro \
    -v /etc/group:/etc/group:ro \
    -v $MOUNT:/DATA/ \
    -v /tmp/.X11-unix:/tmp/.X11-unix \
    -v /mnt/wslg:/mnt/wslg \
    -e DISPLAY -e WAYLAND_DISPLAY -e XDG_RUNTIME_DIR -e PULSE_SERVER \
    --shm-size=8gb \
    ngaggion/chronoroot:latest

3. Docker CLI Commands: Once inside the container, use these aliases to launch the apps:

• segmentation : Launches Segmentation App
• chronoroot : Launches Standard Interface
• screening : Launches Screening Interface

The pre-trained nnU-Net weights are now hosted on Hugging Face to keep the repository lightweight. The installers above will ask to download them automatically.

If you need to update them later manually, run:

cd segmentationApp
./download_weights.sh

For comprehensive, step-by-step guides, please visit our Official Documentation Website.

We have migrated our tutorials to the web to provide detailed, up-to-date instructions.

• Standard Interface (Detailed Analysis)
  • Tutorial: Arabidopsis Analysis
  • Tutorial: Tomato Analysis
• Screening Interface (High-Throughput)
  • Tutorial: Hypocotyl Etiolation
  • Tutorial: Seed Germination
• AI Segmentation
  • Segmentation Module Usage
  • Guide: Train Your Own Model
• Infrastructure
  • Docker Installation & Usage

We provide a pre-packaged dataset to help you follow along with the tutorials above.

• Docker/Apptainer: Pre-loaded at /Demo/ inside the container.
• Download: Google Drive Link

ChronoRoot2
├── apptainerInstaller         # Scripts for Singularity deployment
├── chronoRootApp              # Standard Root Phenotyping Interface
├── chronoRootScreeningApp     # High-throughput Screening Interface
├── segmentationApp            # AI-based segmentation tools (nnUNet)
├── Docker                     # Dockerfile and instructions
├── Documents                  # Legacy PDF documentation
├── environment.yml            # Conda environment spec
├── environment_no_nnunet.yml  # Conda environment spec without nnU-Net
├── installer_conda_linux.sh   # Linux native installer script
├── installer_conda_wsl.sh     # WSL native installer script
├── logo.ico                   # ChronoRoot icon
├── logo_screening.ico         # ChronoRoot Screening icon
├── logo_seg.ico               # ChronoRoot Segmentation icon
├── LICENSE                    # GNU GPL v3.0
└── README.md                  # This file

For technical details on specific modules, please refer to their internal documentation:

• Standard Interface Docs
• Screening Interface Docs
• Segmentation Module Docs
• Docker Guide

ChronoRoot 2.0 is designed to work with an affordable custom hardware setup that includes:

• Raspberry Pi 3B computer
• Fixed-zoom cameras (RaspiCam v2)
• Infrared LED backlighting
• 3D-printed and laser-cut components

For detailed hardware specifications and assembly instructions, see the ChronoRootModuleHardware repository.

For the controller software for the Raspberry Pi 3B, see the ChronoRoot Module Controller repository.

If you use this platform in your research, please cite:

@article{gaggion2026chronoroot,
  title={ChronoRoot 2.0: An Open AI-Powered Platform for 2D Temporal Plant Phenotyping}, 
  author={Nicolás Gaggion and Noelia A. Boccardo and Rodrigo Bonazzola and María Florencia Legascue and María Florencia Mammarella and Florencia Sol Rodriguez and Federico Emanuel Aballay and Florencia Belén Catulo and Andana Barrios and Luciano J. Santoro and Franco Accavallo and Santiago Nahuel Villarreal and Leonardo I. Pereyra-Bistrain and Moussa Benhamed and Martin Crespi and Martiniano María Ricardi and Ezequiel Petrillo and Thomas Blein and Federico Ariel and Enzo Ferrante},
  journal={arXiv preprint arXiv:2504.14736},
  year={2026}
}

ChronoRoot 2.0 is released under the GNU General Public License v3.0. For support, please open an issue.