Supplementary Data for: Embodied mechanical sensing drives support selection in twining plants
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| _version_ | 1866901662039277568 |
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| author | Ohad, Amir Porat, Amir Meroz, Yasmine |
| author_facet | Ohad, Amir Porat, Amir Meroz, Yasmine |
| contents | <p>This repository contains the complete dataset, analysis pipeline, and figure-generation code associated with the scientific article:</p> <p><strong>“Embodied mechanical sensing drives support selection in twining plants”</strong></p> <h3>Summary</h3> <p>This project investigates the mechanics and dynamics of plant stem twining, contact initiation, and force generation through a combination of controlled experiments, motorized perturbations, and numerical simulations. The dataset includes tracking logs (side and top views), two-point contact tracking, material property measurements (Young’s modulus and radius profiles), motor-stage experiments, and simulation outputs.</p> <p>Custom-built experimental setups - including motorized rotation stages and 3D-printed mechanical components - were used to for specific experiments.</p> <p>The analysis framework extracts geometric variables (angles, curvature, support length), computes effective forces and resistances, performs sine fitting of oscillatory trajectories, and evaluates material-property-dependent behavior.</p> <p>The repository is structured to ensure reproducibility:</p> <ul> <li> <p><strong>Raw experimental tracking data</strong></p> </li> <li> <p><strong>Material property measurements</strong></p> </li> <li> <p><strong>Motorized and extreme-condition experiments</strong></p> </li> <li> <p><strong>Simulation data</strong></p> </li> </ul> <h3>Reproducibility and Code Availability</h3> <p>All figures in the manuscript can be regenerated directly from the raw data using the provided Python analysis pipeline. The accompanying GitHub repository contains the full modular codebase required to:</p> <ul> <li> <p>Import raw tracking data</p> </li> <li> <p>Construct plant and event objects</p> </li> <li> <p>Perform geometric and mechanical analysis</p> </li> <li> <p>Fit trajectories and extract parameters</p> </li> <li> <p>Reproduce all manuscript and supplementary figures</p> </li> </ul> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18865114 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Supplementary Data for: Embodied mechanical sensing drives support selection in twining plants Ohad, Amir Porat, Amir Meroz, Yasmine Circumnutations Twining Biomechanics <p>This repository contains the complete dataset, analysis pipeline, and figure-generation code associated with the scientific article:</p> <p><strong>“Embodied mechanical sensing drives support selection in twining plants”</strong></p> <h3>Summary</h3> <p>This project investigates the mechanics and dynamics of plant stem twining, contact initiation, and force generation through a combination of controlled experiments, motorized perturbations, and numerical simulations. The dataset includes tracking logs (side and top views), two-point contact tracking, material property measurements (Young’s modulus and radius profiles), motor-stage experiments, and simulation outputs.</p> <p>Custom-built experimental setups - including motorized rotation stages and 3D-printed mechanical components - were used to for specific experiments.</p> <p>The analysis framework extracts geometric variables (angles, curvature, support length), computes effective forces and resistances, performs sine fitting of oscillatory trajectories, and evaluates material-property-dependent behavior.</p> <p>The repository is structured to ensure reproducibility:</p> <ul> <li> <p><strong>Raw experimental tracking data</strong></p> </li> <li> <p><strong>Material property measurements</strong></p> </li> <li> <p><strong>Motorized and extreme-condition experiments</strong></p> </li> <li> <p><strong>Simulation data</strong></p> </li> </ul> <h3>Reproducibility and Code Availability</h3> <p>All figures in the manuscript can be regenerated directly from the raw data using the provided Python analysis pipeline. The accompanying GitHub repository contains the full modular codebase required to:</p> <ul> <li> <p>Import raw tracking data</p> </li> <li> <p>Construct plant and event objects</p> </li> <li> <p>Perform geometric and mechanical analysis</p> </li> <li> <p>Fit trajectories and extract parameters</p> </li> <li> <p>Reproduce all manuscript and supplementary figures</p> </li> </ul> |
| title | Supplementary Data for: Embodied mechanical sensing drives support selection in twining plants |
| topic | Circumnutations Twining Biomechanics |
| url | https://doi.org/10.5281/zenodo.18865114 |