Artificial Intelligence In Agricultural Extension: Applications and Research Methods
$ 85
Description
The academic textbook authored by Dr. Y. J. Alhassan from the Department of Agricultural Economics and Extension at Federal University Wukari presents a comprehensive examination of how computational intelligence transforms agricultural knowledge delivery, empirical research methodologies, and rural innovation systems. Positioned at the intersection of computer science, agricultural economics, and extension sociology, the text establishes a rigorous theoretical and practical foundation for integrating artificial intelligence into smallholder agricultural production, with a particular focus on the socio-technical realities of Sub-Saharan Africa and Nigeria. Rather than framing artificial intelligence as a replacement for human extension professionals, the volume conceptualizes advanced algorithmic tools as decision-support mechanisms, communication facilitators, and analytical intelligence multipliers that strengthen the triangular linkage connecting agricultural research institutes, public and private extension providers, and rural farming communities. The core thesis of the textbook is organized around an operational system model that traces inputs, analytical processes, tangible outputs, and long-term socio-economic outcomes. On the foundational side, the author traces the historical evolution of agricultural communication from traditional interpersonal and indigenous knowledge channels through state-led Training and Visit systems, early information and communication technology e-extension initiatives, and precision farming, culminating in contemporary machine learning and generative artificial intelligence frameworks. The text differentiates basic symbolic artificial intelligence from machine learning paradigms, deep neural networks, natural language processing architectures, and large-scale multimodal transformer models. By deconstructing these computational foundations, the book provides researchers and postgraduate students with the theoretical vocabulary required to critically evaluate algorithmic applications in rural development.