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The Innovation Informatics > 2026 Vol. 2 > No. 2 > 100036
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AI-Enabled farming systems: Opportunities, limits, and the need for system thinking

  • 1.

    Sino-Danish College, Sino-Danish Centre for Education and Research, University of Chinese Academy of Sciences, Beijing 100049, China

  • 2.

    School of Agriculture and Food Sustainability, The University of Queensland, Brisbane 4072, Australia

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  • Corresponding author: tong.li1@uq.edu.au 
  • Received Date:  January 22, 2026
    Accepted Date:  April 10, 2026
    Published Online:  April 14, 2026
The Innovation Informatics  2(2),  https://doi.org/10.59717/j.xinn-inform.2026.100036  |  Cite this article
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    • REFERENCES
  • [1] Jia Y., Dalal R.C., Li T., et al. (2026). Integrating regenerative and climate-smart agriculture for resilient farming systems. Farming Syst. 2026:100216. DOI:10.1016/j.farsys.2026.100216

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    [2] Li T., Cui L., Wehr B., et al. (2025). Decoding soil constraints in Queensland, Australia: Strategies for precision management to enhance crop productivity. Land Degrad. Dev. 37:302−312. DOI:10.1002/ldr.70111

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    [4] Li T., Xia A., McLaren T.I., et al. (2023). Preliminary results in innovative solutions for soil carbon estimation: Integrating remote sensing, machine learning, and proximal sensing spectroscopy. Remote Sens. 15:5571. DOI:10.3390/rs15235571

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    [5] Wu J., Tian X., Wang Y.-G., et al. (2026). AI ethics in geoscience: Toward trustworthy and responsible innovation. Geogr. Sustain. 7:100414. DOI:10.1016/j.geosus.2026.100414

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  • Cite this article:

    Jia Y., Dalal R. C., Li T., et al. (2026). AI-Enabled farming systems: Opportunities, limits, and the need for system thinking. The Innovation Informatics 2:100036. https://doi.org/10.59717/j.xinn-inform.2026.100036
    Jia Y., Dalal R. C., Li T., et al. (2026). AI-Enabled farming systems: Opportunities, limits, and the need for system thinking. The Innovation Informatics 2:100036. https://doi.org/10.59717/j.xinn-inform.2026.100036

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