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Integrating AI in seed science: Toward an intelligent design paradigm
Ying Zhang1, Jianjun Du2, Guanmin Huang3
1Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; Beijing Key Laboratory of Digital Plant, Beijing 100097, China; Beijing Key Laboratory of Crop Molecular Design and Intelligent Breeding, Beijing 100097, China.
None:
Global agricultural systems face mounting threats to food security from climate change, population growth, and land degradation, with current productivity gains insufficient to meet the demands of a projected global population of 9.7 billion by 2050. Seeds, as both carriers of genetic information and the foundation of agricultural production, directly determine crop yield, resilience, and quality. Advancing seed innovation is therefore essential for achieving sustainable increases in agricultural productivity. This review traces the evolution of seed science from agrarian civilization to the era of intelligent seed design and summarizes recent advances in AI-based methodological innovations and applications. We introduce the emerging paradigm of AI-driven seed design, outline its core scientific questions and key technologies, and propose integrated technological pathways. Furthermore, we analyze current challenges and highlight future directions in this field. By integrating the latest research and technological developments, this review aims to establish an "AI for Science" paradigm for future-oriented seed research that meets the increasing global demand for sustainable and high-quality seed resources.
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