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Original Article

Hybrid AI–Quantum Architecture for Sustainable Plant Disease Detection and Pesticide Recommendation

Open Access Peer Reviewed Crossref DOI

Authors

  • Sarasa Jahnavi1
  • Ratnakumari challa2

1 PG Scholar, Department of CSE, RGUKT-RK VALLEY, Vempalli, Andhra Pradesh, India 2 Assistant Professor, Department of CSE, RGUKT-RK VALLEY, Vempalli, Andhra Pradesh, India

Article Information

Published Online
September-December 2026
Pages
579-588
Article Type
Original Article
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References

[1]. Maria Schuld and Francesco Petruccione, Supervised Learning with Quantum Computers, Springer, 2018. DOI:https://doi.org/10.1007/978-3-319-96424-9
[2]. Vojtěch Havlíček et al., “Supervised Learning with Quantum-Enhanced Feature Spaces,” Nature, 2019. DOI:https://doi.org/10.1038/s41586-019-0980-2
[3]. Edward Farhi and Hartmut Neven, “Classification with Quantum Neural Networks,” 2018. DOI:
https://doi.org/10.48550/arXiv.1802.06002
[4]. F. Arute, K. Arya, R. Babbush, D. Bacon, J. C. Bardin, R. Barends, R. Biswas, S. Boixo, F. G. S. L. Brandao, D. A. Buell, et al., “Quantum supremacy using a programmable superconducting processor,” Nature, vol. 574, no. 7779, pp. 505–510, 2019.DOI: https://doi.org/10.1038/s41586-019-1666-5
[5]. Vinod Upputuri, “Transforming agriculture through artificial intelligence: A technical analysis,” International Journal of Research in Computer Applications and Information Technology (IJRCAIT), vol. 8, no. 1, pp. 1750–1766, Jan.–Feb. 2025.DOI: https://doi.org/10.34218/IJRCAIT_08_01_128
[6]. FAO, “Plant Disease Management Guidelines,” 2020.
[7]. S. P. Mohanty, D. P. Hughes, and M. Salathé, “Using Deep Learning for Image-Based Plant Disease Detection,” Frontiers in Plant Science, vol. 7, 2016.DOI: https://doi.org/10.3389/fpls.2016.01419
[8]. S. Sladojevic et al., “Deep Neural Networks Based Recognition of Plant Diseases,” Computational Intelligence and Neuroscience, 2016.DOI: https://doi.org/10.1155/2016/3289801
[9]. K. P. Ferentinos, “Deep Learning Models for Plant Disease Detection,” Computers and Electronics in Agriculture, vol. 145, pp.311–318, 2018.DOI: https://doi.org/10.1016/j.compag.2018.01.009
[10].E. C. Too et al., “Comparative Study of Deep Learning Models,” Computers and Electronics in Agriculture, 2019. DOI:https://doi.org/10.1016/j.compag.2019.105119
[11].S. Zhang et al., “Plant Disease Detection Using CNNs,” 2020. DOI: https://doi.org/10.1109/ACCESS.2020.2975242
[12].Sumit Kumar, Shashank Sheshar Singh, Gourav Bathla, Swati Sharma and Manisha Panjeta, “Fusion of quantum computing with smart agriculture: A systematic review of methods, implementation, applications, and challenges,” Information Fusion, vol. 131, p. 104159, 2026.DOI: https://doi.org/10.1016/j.inffus.2026.104159
[13].Microsoft, “Azure Quantum Development Kit,” 2021.
[14].Marco Benedetti et al., “Parameterized Quantum Circuits as Machine Learning Models,” 2019. DOI:https://doi.org/10.1088/2058-9565/ab4eb5
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