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Nanotechnology and artificial intelligence to enable sustainable and precision agriculture

Nature Plants volume 7, pages 864–876 (2021)Cite this article

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Abstract

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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Fig. 1: Applications of nanotechnology in agriculture, focusing specifically on crop production.
Fig. 2: Applications of machine learning to nano-enabled agriculture.
Fig. 3: The complexity of nanomaterial behaviour in the soil–plant environment and the potential impacts in soil–plant systems.
Fig. 4: Approach to integration of AI models needed to assess nanomaterials behaviour, fate and impact in agriculture based on the interplay between nanomaterial and environmental factors including the crop type and soil characteristics.

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Acknowledgements

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).

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  1. School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK

    Peng Zhang, Zhiling Guo, Sami Ullah & Iseult Lynch

  2. Division of Physical Sciences and Applications, Hellenic Military Academy, Vari, Greece

    Georgia Melagraki

  3. Nanoinformatics Department, Novamechanics Ltd, Nicosia, Cyprus

    Antreas Afantitis

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  1. Peng Zhang
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P.Z. and I.L. outlined the manuscript. P.Z., Z.G., S.U. and I.L. wrote the manuscript with contributions and inputs from all authors. P.Z., A.A. and G.M. produced the graphics.

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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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