Chapter One Organic and Mineral Soil Amendments as Enablers of Climate-Smart Agricultural Automation: Implications for Soil Water Management and Food Security *Paul Omaye Joseph1,4, Enya Anari Akpa2,4, King Ndeari Dedan3,4, 1Department of Soil and Environmental Management, Faculty of Agriculture, Prince Abubakar Audu University, Anyigba, Kogi State, Nigeria 2Department of Soil Science, Faculty of Agriculture, University of Calabar, Calabar, Cross River State, Nigeria 3Department of Soil Science, Faculty of Agriculture, Federal University of Kashere, Gombe State, Nigeria 4Department of Soil Science, Faculty of Agriculture, University of Nigeria, Nsukka, Enugu State, Nigeria *Corresponding author (joseph.po@ksu.edu.ng

Conclusion
Climate change is increasing uncertainty in agricultural water management, while soil degradation can reduce the capacity of soils to receive, store, transmit and supply water. Agricultural automation offers opportunities for more precise monitoring and irrigation control, but its effectiveness depends partly on the hydraulic condition of the soil. This chapter has therefore positioned organic and mineral amendments as potential enablers of soil-intelligent agricultural automation rather than as automation technologies themselves.
Poultry manure, rice husk ash and other amendments can modify bulk density, aggregate stability, pore architecture, infiltration, saturated hydraulic conductivity and water retention. However, their effects depend on amendment characteristics, application rate, initial soil condition, parent material and time after incorporation. Effective soil-water management must therefore seek an appropriate balance between water entry, transmission, storage and drainage rather than maximize any single hydraulic property.
The chapter proposes a conceptual pathway linking soil diagnosis and targeted amendment application with hydraulic modification, sensing, predictive modelling and automated water management. Within this framework, sensors monitor soil-water conditions, pedotransfer functions and machine-learning models support the interpretation and prediction of hydraulic behaviour, and automated systems use this information to guide irrigation decisions. Accounting for spatial and temporal soil variability is essential to making these decisions responsive to actual soil–crop conditions.
Despite these opportunities, the complete integration of amendment management, sensing, modelling and automated irrigation remains insufficiently tested, particularly in tropical African soils. Its potential to improve water-use efficiency, yield stability, economic performance and climate resilience therefore requires integrated field validation. Ultimately, amendment-enabled agricultural automation offers a promising framework for climate-smart soil-water management, but its contribution to food security will depend on demonstrated agronomic benefits, environmental sustainability and practical accessibility.
References
Adewole, A. O., Eludoyin, A. O., Chirima, G. J., & Newete, S. W. (2024). Field-scale variability and dynamics of soil moisture in Southwestern Nigeria. Discover Soil, 1, 12. https://doi.org/10.1007/s44378-024-00013-4.
Akpa, E. A., Okon, P. O., Abam, P. O., & Sunday, L. K. (2025). Use of erodibility indices in assessing soil erosion in central and northern Cross River State, Nigeria. Nigerian Journal of Soil Science, 34(2), 7–14. https://doi.org/10.67042/njss.2025.0wv1lbb4.
Akpa, S. I. C., Ugbaje, S. U., Bishop, T. F. A., & Odeh, I. O. A. (2016). Enhancing pedotransfer functions with environmental data for estimating bulk density and effective cation exchange capacity in a data-sparse situation. Soil Use and Management, 32(4), 644–658. https://doi.org/10.1111/sum.12310.
Bantchina, B. B., Gündoğdu, K. S., Arslan, S., Ulusoy, Y., Tekin, Y., Pantazi, X. E., Dolaptsis, K., Paraskevas, C., Tziotzios, G., Qaswar, M., & Mouazen, A. M. (2024). Spatiotemporal Modeling of Soil Water Dynamics for Site-Specific Variable Rate Irrigation in Maize. Soil Systems, 8(1), 19. https://doi.org/10.3390/soilsystems8010019.
Bounajra, A., El Guemmat, K., Mansouri, K., & Akef, F. (2024). Towards efficient irrigation management at field scale using new technologies: A systematic literature review. Agricultural Water Management, 295, 108758. https://doi.org/10.1016/j.agwat.2024.108758.
da Silva, L. C. M., Amorim, R. S. S., Fernandes-Filho, E. I., Bocuti, E. D., & da Silva, D. D. (2023). Pedotransfer functions and machine learning: Advancements and challenges in tropical soils. Geoderma Regional, 35, e00720. https://doi.org/10.1016/j.geodrs.2023.e00720.
Das, B., Pooniya, V., Shivay, Y. S., Zhiipao, R. R., Biswakarma, N., Kumar, D., Saikia, N., Kumar, A., Govindasamy, P., Barman, A., & Critykar, J. (2024). Twenty-one years’ impact of using organic amendments on the productivity of rice-wheat rotation and soil properties. Field Crops Research, 309, 109311. https://doi.org/10.1016/j.fcr.2024.109311.
Datta, S., & Taghvaeian, S. (2023). Soil water sensors for irrigation scheduling in the United States: A systematic review of literature. Agricultural Water Management, 278, 108148. https://doi.org/10.1016/j.agwat.2023.108148.
Food and Agriculture Organization (2022). The State of Food and Agriculture 2022: Leveraging Agricultural Automation for Transforming Agrifood Systems. Rome: Food and Agriculture Organization of the United Nations. https://doi.org/10.4060/cb9479en.
Hamouda, F., Puig-Sirera, A., Bonzi, L., Remorini, D., Massai, R., & Rallo, G. (2024). Design and validation of a soil moisture-based wireless sensors network for the smart irrigation of a pear orchard. Agricultural Water Management, 305, 109138. https://doi.org/10.1016/j.agwat.2024.109138.
Hodges, B. C., Tagert, M. L., Paz, J. O., & Meng, Q. (2023). Assessing in-field soil moisture variability in the active root zone using granular matrix sensors. Agricultural Water Management, 282, 108268. https://doi.org/10.1016/j.agwat.2023.108268.
Intergovernmental Panel on Climate Change (2022). Climate Change 2022: Impacts, Adaptation and Vulnerability. Cambridge University Press. https://doi.org/10.1017/9781009325844.
Ivanova, I. (2025). Soil moisture forecasting from sensors-based soil moisture, weather and irrigation observations: A systematic review. Smart Agricultural Technology, 10, 100692. https://doi.org/10.1016/j.atech.2024.100692.
Joseph, P. O., Ojomah, F. O., & Abioye, J. B. (2025a). Poultry manure-induced influence on soil properties of coarse-textured tropical soil. Journal of Wastes and Biomass Management, 7(1), 1–5. https://doi.org/10.26480/jwbm.01.2025.01.05.
Joseph, P. O., Ojomah, F. O., Ejiga, A. E., & Abioye, J. B. (2025b). Short-term impacts of heavy poultry manure addition on the properties of loamy-sand Alfisols later evaluated using okra. Discovery Agriculture, 11, e4da1617. https://doi.org/10.54905/disssi.v11i23.e4da1617.
Li, X., Wang, H., Qin, S., Lin, L., Wang, X., & Cornelis, W. (2024a). Evaluating ensemble learning in developing pedotransfer functions to predict soil hydraulic properties. Journal of Hydrology, 640, 131658. https://doi.org/10.1016/j.jhydrol.2024.131658.
Li, Y., Feng, X., Huai, Y., Hassan, M. U., Cui, Z., & Ning, P. (2024b). “Enhancing crop productivity and resilience by promoting soil organic carbon and moisture in wheat and maize rotation,” Agriculture, Ecosystems & Environment, 368, 109021. https://doi.org/10.1016/j.agee.2024.109021.
Liu, T., Wu, L., Tang, S., Shaaban, M., Meng, L., Xu, M., & Zhang, W. (2025). Positive effects of amendments on crop yield and organic carbon in sandy soils are regulated by aridity: A global meta-analysis. Geoderma, 462, 117540. https://doi.org/10.1016/j.geoderma.2025.117540.
McCarthy, A. C., Foley, J. P., Raedts, P., & Hills, D. J. (2023). Field evaluation of automated site-specific irrigation for cotton and perennial ryegrass using soil-water sensors and Model Predictive Control. Agricultural Water Management, 277, 108098. https://doi.org/10.1016/j.agwat.2022.108098.
Moosavi, A. A., Nematollahi, M. A., & Omidifard, M. (2024). Comparing machine learning approaches for estimating soil saturated hydraulic conductivity. PLOS ONE, 19(11), e0310622. https://doi.org/10.1371/journal.pone.0310622.
Morales-Salmerón, L., Fernández-Boy, E., León, R., Navarro-Fernández, C. M., & Domínguez, M. T. (2025). Influence of the quality of organic amendments on Mediterranean agricultural soils following a drought episode. Journal of Environmental Management, 380, 125093. https://doi.org/10.1016/j.jenvman.2025.125093.
Nenkam, A. M., Wadoux, A. M. J.-C., Minasny, B., Silatsa, F. B. T., Yemefack, M., Ugbaje, S. U., Akpa, S., Van Zijl, G., Bouasria, A., Bouslihim, Y., Chabala, L. M., Ali, A., & McBratney, A. B. (2024). Applications and challenges of digital soil mapping in Africa. Geoderma, 449, 117007. https://doi.org/10.1016/j.geoderma.2024.117007.
Obalum, S. E., Ugwu, V. U., Etukudo, N. E., Joseph, P. O., Onah, C. J., Eyibio, N. U., & Igwe, C. A. (2024). Residual effects of heavy application of poultry-droppings manure on aggregation, P-fertility and hydraulic properties of well-drained tropical soils. Applied Environmental Biotechnology, 9(2), 58–65. https://doi.org/10.26789/AEB.2024.02.007.
Odo, K. O., Abonyi, D. O., & Eke, J. (2024). Wireless sensor networks: A vital tool for improved agricultural practices in Nigeria. UNIZIK Journal of Engineering and Applied Sciences, 3(5), 1324–1334.
Omokaro, G. O. (2025). Multi-impacts of climate change and mitigation strategies in Nigeria: agricultural production and food security. Science in One Health, 4, 100113. https://doi.org/10.1016/j.soh.2025.100113.
Pham, K., Kim, D., Le, C. V., & Won, J. (2023). Machine learning-based pedotransfer functions to predict soil water characteristics curves. Transportation Geotechnics, 42, 101052. https://doi.org/10.1016/j.trgeo.2023.101052.
Sharma, P., Abrol, V., Nazir, J., Samnotra, R. K., Gupta, S. K., Anand, S., Biswas, J. K., Shukla, S., & Kumar, M. (2025). Optimizing soil properties, water use efficiency, and crop yield through biochar and organic manure integration in organic soil. Journal of Environmental Management, 373, 123673. https://doi.org/10.1016/j.jenvman.2024.123673.
Weber, T. K. D., Weihermüller, L., Nemes, A., et al. (2024). Hydro-pedotransfer functions: A roadmap for future development. Hydrology and Earth System Sciences, 28, 3391–3433. https://doi.org/10.5194/hess-28-3391-2024.
jaerem Akan, P.O.