PlantScience.ai: An LLM-powered virtual scientist for plant science

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Authors: Haopeng Yu, Shasha Zhou, Mingyu Huang, Ling Ding, Yuxuan Chen, Y S Wang, Yingyu Ren, Nuo Cheng, Xinya Wang, Jie Liang, Huakun Zhang, Yiliang Ding
+1 more Ke Li
Cited by: 6
References: 5

Abstract

The accelerating growth of plant science knowledge presents a major challenge to extracting accurate, up-to-date knowledge from an increasingly fragmented and domain-specific corpus. General-purpose large language models, while powerful, often misinterpret plant science terminology and lack mechanisms for source traceability. We created PlantScience.ai, a virtual plant biology scientist powered by an automated scientific knowledge graph construction pipeline. PlantScience.ai exhibits expert-level reasoning in plant biology and maintains scholarly rigor inciting the literature. Through continuous learning, it integrates the latest research to ensure that its knowledge base remains current and scientifically robust. Apart from providing the answers to scientific questions, PlantScience.ai can interact with human scientists, follow instructions, and retrieve information with citation awareness, grounding each response in primary sources to ensure accuracy and verifiability. PlantScience.ai marks a pivotal advance toward a collaborative scientific paradigm in which virtual and human plant scientists work synergistically to accelerate discovery while preserving the unique value of human insight. PlantScience.ai is available at https://plantscience.ai.

Fields of Study & Subjects

Genetics Bioinformatics and Biomedical Research Cell Image Analysis Techniques Scientific Computing and Data Management

Publication details

Journal / source
Molecular Plant
Publisher
Elsevier BV
Volume
19
Issue
5
Pages
1117–1123
Publication date
21 March 2026
Language
EN