Climate change, increasing populations, competing demands on land for production of biofuels and declining soil quality are challenging global food security. Finding sustainable solutions requires bold new approaches and integration of knowledge from diverse fields, such as materials science and informatics. The convergence of precision agriculture, in which farmers respond in real time to changes in crop growth with nanotechnology and artificial intelligence, offers exciting opportunities for sustainable food production. Coupling existing models for nutrient cycling and crop productivity with nanoinformatics approaches to optimize targeting, uptake, delivery, nutrient capture and long-term impacts on soil microbial communities will enable design of nanoscale agrochemicals that combine optimal safety and functionality profiles.
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Z.G., I.L. and A.A. acknowledge funding from the EU H2020 project NanoSolveIT (Grant Agreement 814572). I.L. and A.A. acknowledge funding from the EU H2020 projects RiskGone (Grant Agreement 814425) and NanoCommons (Grant Agreement 731032). I.L., P.Z. and Z.G. acknowledge support from the University of Birmingham Institute for Global Innovation Environmental Pollution Solutions theme. S.U. acknowledges funding from the BBSRC Sustainable Agriculture Research and Innovation Club project (BB/R021716/1) and NERC-NSF grant-DiRTS (NE/T012323/1).
The authors declare no competing interests.
Peer review information Nature Plants thanks the anonymous reviewers for their contribution to the peer review of this work.
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Zhang, P., Guo, Z., Ullah, S. et al. Nanotechnology and artificial intelligence to enable sustainable and precision agriculture. Nat. Plants 7, 864–876 (2021). https://doi.org/10.1038/s41477-021-00946-6
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