Topic collection
Methods and systems for observable, quantitative crop and plant traits.
A WeChat Mini Program for plant phenotyping fieldwork: leaf-angle and land-area measurement, site weather, image analysis, AI-assisted charting and data management in one mobile toolkit.
A web application and batch pipeline that removes plant-image backgrounds without task-specific training, using a multimodal image model with a structured prompt, aspect-ratio matching and file-signature format detection.
A desktop platform that processes hyperspectral, LiDAR, RGB and thermal phenotyping data with one interface, interactive parameter tuning, batch processing and structured exports.
A measuring and analysis framework that predicts leaf BRDF parameters from phenotypic traits in four species, combining directional spectroscopy, Cook–Torrance fitting, ensemble learning and canopy ray tracing (Plant Phenomics, 2025).
A local OpenCV method that segments separated plant samples on a uniform background and measures size, shape and colour in calibrated units, with an overlay for every image.
Generating 3D cotton plants from single photographs with 3D generative AI and evaluating them organ by organ against multi-view SfM reconstructions of the same plants.
A UAV workflow for plot-level 3D crop phenotyping: Cross-Circular Oblique flight design, SfM reconstruction, canopy point-cloud processing with CanopyPC, and machine-learning models of crop traits.
An interactive OpenCV tool that turns raw root scans and photographs into clean binary images through polygon ROI selection, illumination correction, thresholding and brush-based correction, ready for root-trait software.
A modular model that reconstructs crop plants from multi-view images, assembles a triangle-facet canopy, simulates its light distribution by ray tracing, and integrates leaf photosynthesis to canopy carbon gain.
