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Artificial Intelligence, Climate Change and Sustainable Agriculture: A Method for Improving Food Security in Enugu State, Nigeria
Subject area: Agriculture and Veterinary Sciences · Area of research: Artificial Intelligence
Abstract
Climate change poses a serious threat to agricultural productivity, rural livelihoods and food security in Enugu State, Nigeria. Rising temperatures, irregular rainfall, flooding, soil degradation and erosion increase farmers’ vulnerability and may reduce crop yields. Artificial Intelligence (AI) provides emerging opportunities to address these challenges through data-driven and climate-smart agricultural practices. This paper examines the role of AI, climate-change adaptation and sustainable agriculture in improving food security in Enugu State. The study adopts a qualitative desk-review approach, drawing on relevant scholarly literature, policy documents and institutional reports. It examines AI applications in weather forecasting, crop and soil monitoring, pest and disease detection, precision farming, irrigation management, yield prediction and digital agricultural extension services. The review indicates that integrating AI with sustainable agricultural practices can improve farm productivity, resource-use efficiency, climate resilience and farmers’ decision-making. However, inadequate digital infrastructure, limited technical skills, high technology costs, poor internet connectivity, insufficient agricultural data and weak extension services may constrain adoption, particularly among smallholder farmers. The paper recommends investment in digital infrastructure, farmer training, affordable AI technologies, research, extension services and supportive policies to strengthen sustainable food production and food security in Enugu State.
Keywords
Artificial Intelligence; Climate Change; Sustainable Agriculture; Food Security; Climate-Smart Agriculture; Agricultural Productivity; Smallholder Farmers; Enugu State.
References
[1] Food and Agriculture Organization of the United Nations. (2013). Climate-smart agriculture sourcebook. FAO. FAO
[2] Food and Agriculture Organization of the United Nations. (2022). The state of food and agriculture 2022: Leveraging automation in agriculture for transforming agrifood systems. FAO
[3] Intergovernmental Panel on Climate Change. (2022). Climate change 2022: Impacts, adaptation and vulnerability. Cambridge University Press. IPCC
[4] Kamilaris, A., Kartakoullis, A., & Prenafeta-Boldú, F. X. (2017). A review on the practice of big data analysis in agriculture. Computers and Electronics in Agriculture, 143, 23–37. ScienceDirect
[5] Liakos, K. G., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018). Machine learning in agriculture: A review. Sensors, 18(8), Article 2674. MDPI
[6] Lipper, L., Thornton, P., Campbell, B. M., Baedeker, T., Braimoh, A., Bwalya, M., Caron, P., Cattaneo, A., Garrity, D., Henry, K., Hottle, R., Jackson, L., Jarvis, A., Kossam, F., Mann, W., McCarthy, N., Meybeck, A., Neufeldt, H., Remington, T., ... Torquebiau, E. F. (2014). Climate-smart agriculture for food security. Nature Climate Change, 4, 1068–1072. Nature
[7] Mmbando, G. S. (2025). Harnessing artificial intelligence and remote sensing in climate-smart agriculture: The current strategies needed for enhancing global food security. Cogent Food & Agriculture, 11(1), Article 2454354. Taylor & Francis
[8] Tabe-Ojong, M. P. J., Aihounton, G. B. D., & Lokossou, J. C. (2023). Climate-smart agriculture and food security: Cross-country evidence from West Africa. Global Environmental Change, 81, Article 102697. ScienceDirect
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How to cite this paper
@article{1723721,
author = {Ani Cynthia Helen, Amobi Evelyn Nkechinyere, Asadu Augustina Ngozi, Ugwu Linus Ejiofor},
title = {Artificial Intelligence, Climate Change and Sustainable Agriculture: A Method for Improving Food Security in Enugu State, Nigeria},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {4},
pages = {780-788},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1723721.pdf},
abstract = {Climate change poses a serious threat to agricultural productivity, rural livelihoods and food security in Enugu State, Nigeria. Rising temperatures, irregular rainfall, flooding, soil degradation and erosion increase farmers’ vulnerability and may reduce crop yields. Artificial Intelligence (AI) provides emerging opportunities to address these challenges through data-driven and climate-smart agricultural practices. This paper examines the role of AI, climate-change adaptation and sustainable agriculture in improving food security in Enugu State. The study adopts a qualitative desk-review approach, drawing on relevant scholarly literature, policy documents and institutional reports. It examines AI applications in weather forecasting, crop and soil monitoring, pest and disease detection, precision farming, irrigation management, yield prediction and digital agricultural extension services. The review indicates that integrating AI with sustainable agricultural practices can improve farm productivity, resource-use efficiency, climate resilience and farmers’ decision-making. However, inadequate digital infrastructure, limited technical skills, high technology costs, poor internet connectivity, insufficient agricultural data and weak extension services may constrain adoption, particularly among smallholder farmers. The paper recommends investment in digital infrastructure, farmer training, affordable AI technologies, research, extension services and supportive policies to strengthen sustainable food production and food security in Enugu State.},
keywords = {Artificial Intelligence; Climate Change; Sustainable Agriculture; Food Security; Climate-Smart Agriculture; Agricultural Productivity; Smallholder Farmers; Enugu State.},
month = {October},
}