Abstract
Crops provide food, clothing and other important products for the global population. To meet the demands of a growing population, substantial improvements are required in crop yield, quality and production sustainability. However, these goals are constrained by various environmental factors and limited genetic resources. Overcoming these limitations requires a paradigm shift in crop improvement by fully leveraging natural genetic diversity alongside biotechnological approaches such as genome editing and the heterologous expression of designed proteins, coupled with multimodal data integration. In this Review, we provide an in-depth analysis of integrated uses of omics technologies, genome editing, protein design and high-throughput phenotyping, in crop improvement, supported by artificial intelligence-enabled tools. We discuss the emerging applications and current challenges of these technologies in crop improvement. Finally, we present a perspective on how elite alleles generated through these technologies can be incorporated into the genomes of existing and de novo domesticated crops, aided by a proposed artificial intelligence model. We suggest that integrating these technologies with agricultural practices will lead to a new revolution in crop improvement, contributing to global food security in a sustainable manner.
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Acknowledgements
We thank G. Lawrence, D. Llewellyn, H. Puchta, F. Lu, P. Lu, J. Luo, R. McIntosh, R. Milne, W. Qian, B. Wang, X. J. Wang, X. W. Wang, F. Zhao and K. T. Zhao for their discussions and critical reading of the manuscript and members of the Li and Gao laboratories for assistance with figures and references. Research in the authors’ laboratories was supported by the following grants: Biological Breeding-National Science and Technology Major Project (2023ZD04070) to G.L.; National Key Research and Development Program (2022YFF1002802 to C.G. and 2022YFA1304402 to G.L.); Key R&D Program of Hubei Province (2023BBB171), National Natural Science Foundation of China (32172373) and Fundamental Research Funds for the Central Universities (2662023PY006, AML2023A05, 2662025ZKPY008 and 2662024ZKPY001) to G.L.; Audacious GC4 (PG117880) for Smart Therapeutics to L.A.; NSFC (32388201); the Ministry of Agriculture and Rural Affairs of China and the New Cornerstone Science Foundation to C.G.; NNSFC (U21A20205), Key Agricultural Core Technology Research Project in Hubei Province (HBNYHXGG2023-9) and FRFCU (2662024ZKPY003) to W.Y.; China National GeneBank (CNGB) to T.W.; Biotechnology and Biological Sciences Research Council (BBS/E/IB/23001 and BBS/E/W/0012843) and Engineering and Physical Sciences Research Council (EP/Y005430/1) to J.H.D.; NNSFC (32293243) to K.X.; the Bill and Melinda Gates Foundation (INV-004428) to E.S.L.; KAUST Baseline and Competitive Research Grants (9 and 10) to R.A.W. This work was also supported by Hubei Hongshan Laboratory.
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G.L., L.A., W.Y., L.Y. and C.G. conceived the study and were responsible for the overall frame of the Review. G.L., L.A., W.Y., L.Y., T.W., J.S., J.W., J.H.D., K.X., A.R.F., E.S.L., R.A.W. and C.G. contributed to the design and writing of the manuscript. G.L., L.A., W.Y., L.Y., J.S., J.W. and C.G. conceptualized and drafted the figures. All authors revised the work, provided critical feedback and approved the final version.
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Supplementary Table 1
High throughput phenotyping method and application in crop improvement.
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Li, G., An, L., Yang, W. et al. Integrated biotechnological and AI innovations for crop improvement. Nature 643, 925–937 (2025). https://doi.org/10.1038/s41586-025-09122-8
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DOI: https://doi.org/10.1038/s41586-025-09122-8
