ChronoRoot 2.0: An Open AI-Powered Platform for 2D Temporal Plant Phenotyping
원문 초록
The analysis of plant developmental plasticity, including root system architecture, is fundamental to understanding plant adaptability and development, particularly in the context of climate change and agricultural sustainability. While significant advances have been made in plant phenotyping technologies, comprehensive temporal analysis of root development remains challenging, with most existing solutions providing either limited throughput or restricted structural analysis capabilities. Here, we present ChronoRoot 2.0, an integrated open-source platform that combines affordable hardware with advanced artificial intelligence to enable sophisticated temporal plant phenotyping. The system introduces several major advances, offering an integral perspective of seedling development: (i) simultaneous multi-organ tracking of six distinct plant structures, (ii) quality control through real-time validation, (iii) comprehensive architectural measurements including novel gravitropic response parameters, and (iv) dual specialized user interfaces for both architectural analysis and high-throughput screening. We demonstrate the system's capabilities through three use cases for Arabidopsis thaliana: characterization of circadian growth patterns under different light conditions, detailed analysis of gravitropic responses in transgenic plants, and high-throughput screening of etiolation responses across multiple genotypes. ChronoRoot 2.0 maintains its predecessor's advantages of low cost and modularity while significantly expanding its capabilities, making sophisticated temporal phenotyping more accessible to the broader plant science community. The system's open-source nature, combined with extensive documentation and containerized deployment options, ensures reproducibility and enables community-driven development of new analytical capabilities.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
A Survey on 3D Reconstruction Techniques in Plant Phenotyping: From Classical Methods to Neural Radiance Fields (NeRF), 3D Gaussian Splatting (3DGS), and Beyond
PhenoAssistant: A Conversational Multi-Agent AI System for Automated Plant Phenotyping
GroMo: Plant Growth Modeling with Multiview Images
Spatial Transformer Network YOLO Model for Agricultural Object Detection
3D Multimodal Image Registration for Plant Phenotyping
Data-driven Crop Growth Simulation on Time-varying Generated Images using Multi-conditional Generative Adversarial Networks
토론
이 논문과 연결된 포럼 글이 아직 없습니다.