[1] Smith, A., Johnson, B., & Brown, C. (2020), “IoT-enabled precision nutrient management in agriculture” Journal of
Agricultural Engineering, 25(3), 112-125.
[2] Johnson, D., & Patel, K. (2019), “Machine learning for variable rate application in precision agriculture” Computers and
Electronics in Agriculture, 135, 125-135.
[3] Jones, E., et al. (2021), “Drone-based crop monitoring and pest detection using IoT and ML,” International Journal of
Agricultural Sciences, 45(2), 78-89.
[4] Gupta, S., et al. (2018), “Automated disease detection in crops using machine learning”, Agricultural Automation and
Robotics, 12(1), 45-56.
[5] Kumar, R., & Singh, M. (2020), “IoT-enabled smart irrigation system for sustainable agriculture”, Sustainable
Agriculture Reviews, 18, 125-140.
[6] Lee, H., et al. (2019), “Machine learning approaches for optimizing irrigation in agriculture”, Journal of Water
Resources Management, 35(4), 245-260.
[7] Smith, J., & Brown, K. (2019), “Predictive modeling for crop yield estimation using machine learning” Journal of
Agricultural Informatics, 22(1), 55-68.
[8] Li, L., et al. (2021), “Machine learning for pest risk prediction in agriculture”, Journal of Pest Management, 30(2), 89
102.
[9] Chen, X., et al. (2020), “IoT-enabled soil sensors for optimal crop growth”, Journal of Agricultural Technology, 8(3), 45
58.
[10] Patel, A., & Gupta, B. (2021), “ML algorithms for soil health monitoring and management” International Journal of
Sustainable Agriculture, 15(2), 120-135.
[11] Liang, C., et al. (2019), “IoT-enabled wearable devices for livestock management”, Journal of Livestock Science, 5(1),
78-92.
[12] Wang, X., & Liu, Y. (2022), “Supply chain optimization in agriculture using IoT and ML”, Journal of Agricultural
Economics, 12(1), 30-45.
[13] Kim, S., et al. (2020), “ML algorithms for supply chain visibility and logistics management”, International Journal of
Supply Chain Management, 8(4), 110-125.
[14] Sharma, R., et al. (2021), “Climate-resilient agricultural systems using IoT and ML” Journal of Climate Change
Research, 18(3), 60-75.
[15] Singh, A., & Mishra, S. (2018), “IoT sensors for climate data collection and risk assessment”, Environmental Science
Journal, 25(2), 90-105.
[16] Khan, M., et al. (2020), “Socio-economic impact of IoT and ML adoption in agriculture”, Journal of Agricultural
Economics and Policy, 5(3), 150-165.
[17] Li, J., et al. (2019). Benefits of digital technologies for smallholder farmers. Journal of Rural Development Studies,
18(4), 200-215.
[18] Wang, Y., & Zhang, Z. (2020), “Data privacy and security challenges in IoT-enabled agricultural systems”, International
Journal of Cybersecurity, 7(2), 80-95.
[19] Garg, S., et al. (2019), “Farmer education and training programs for digital technology adoption”, Journal of
Agricultural Education and Extension, 10(1), 40-55.
[20] Wang, Y., & Zhang, Q. (2020), “Data security challenges in IoT-enabled agricultural systems”, International Journal of
Information Security, 15(3), 215-230.
[21] Garg, S., et al. (2019), “Promoting IoT adoption in agriculture: challenges and opportunities”, Journal of Agricultural
Extension, 25(4), 165-180.
[22] Smith, A., Johnson, B., & Brown, C. (2020), “IoT-enabled precision nutrient management in agriculture”, Journal of
Agricultural Engineering, 25(3), 112-125.
[23] Johnson, D., & Patel, K. (2019), “Machine learning for variable rate application in precision agriculture”, Computers
and Electronics in Agriculture, 135, 125-135.
[24] Jones, E., et al. (2021), “Drone-based crop monitoring and pest detection using IoT and ML”, International Journal of
Agricultural Sciences, 45(2), 78-89.
[25] Gupta, S., et al. (2018), “Automated disease detection in crops using machine learning”, Agricultural Automation and
Robotics, 12(1), 45-56.
[26] Kumar, R., & Singh, M. (2020), “IoT-enabled smart irrigation system for sustainable agriculture”, Sustainable
Agriculture Reviews, 18, 125-140.
[27] Lee, H., et al. (2019), “Machine learning approaches for optimizing irrigation in agriculture”, Journal of Water
Resources Management, 35(4), 245-260.
[28] Smith, J., & Brown, K. (2019), “Predictive modeling for crop yield estimation using machine learning” Journal of
Agricultural Informatics, 22(1), 55-68.
[29] Li, L., et al. (2021), “Machine learning for pest risk prediction in agriculture”, Journal of Pest Management, 30(2), 89
102.
[30] Wang, Y., & Zhang, Q. (2020), “Data security challenges in IoT-enabled agricultural systems”, International Journal of
Information Security, 15(3), 215-230.
[31] Garg, S., et al. (2019). “Promoting IoT adoption in agriculture: challenges and opportunities” Journal of Agricultural
Extension, 25(4), 165-180