植物学报2026，Vol.61Issue(4)：598-610,13.DOI:10.11983/CBB25192
AI4Root:人工智能驱动的植物根系研究进展
AI4Root:a Framework to Advance AI-Driven Plant Root Research
摘要
Abstract
With AI for Science(AI4Science)emerging as a new paradigm for scientific research,artificial intelligence(AI)is driving a transition toward data-driven and intelligent research in plant science.Roots,as the key organs responsible for water and nutrient acquisition,environmental sensing,and above-belowground interactions,are decisive for crop productivity and ecosystem functioning.However,due to their hidden growth in soil,structural complexity,and limited observability,our understanding of root structure and function has long lagged behind that of aboveground parts.Recent advances in AI have provided new tools and pathways for decoding the"underground black box".Using AI as a key driver to integrate mul-ti-source root and environmental data,advanced algorithms,and the broader knowledge base of root science has emerged as a frontier direction in belowground research.In this context,we systematically review the major applications and emerging trends of AI in root studies,encompassing data acquisition,structural modeling,mechanistic inference,and management decision support.AI-based image analysis enables automated recognition and quantification of root architectures,while modeling and data-fusion approaches reveal the multi-scale and multi-process interactions between roots and soil.AI ap-plications in root phenotyping,architectural simulation,and deciphering root exudate-microbiome interactions are also showing great potential,offering unprecedented tools to advance our understanding of root function.However,the applica-tion of AI in root research still faces several challenges,including the difficulty of acquiring high-quality field data,insufficient integration across experimental scales,and limited capacity to model the complexity of root-soil-environment interactions.Looking ahead,the deep integration of multi-source data,cross-disciplinary algorithmic advancements,and the coordinated development of digital agriculture platforms are expected to propel root science into a new era of intelligent research,of-fering innovative pathways for crop improvement and the advancement of smart agriculture.关键词
根系/人工智能/深度学习/智慧农业/AI4RootKey words
roots/artificial intelligence/deep learning/smart agriculture/AI4Root引用本文复制引用
方博,张玉成,郑聪聪,高树琴,段世名,马慧敏,赵洪龙,蒋浩,杨艳敏,龙隆,贺祖光..AI4Root:人工智能驱动的植物根系研究进展[J].植物学报,2026,61(4):598-610,13.基金项目
中国科学院科研项目 （）
