Case Study to Investigate the Adoption of Precision Agriculture in Nigeria Using Simple Analysis to Determine Variability on a Maize Plantation AJAERD Case Study to Investigate the Adoption of Precision Agriculture in Nigeria Using Simple Analysis to Determine Variability on a Maize Plantation *Halimatu Sadiyah Abdullahi 1 , Ray E. Sheriff 2 1,2 Faculty of Engineering & Informatics, University of Bradford, Bradford, United Kingdom This study investigated the adoption of precision farming (PF) technology with research into the possible implementation of the technology for increased productivity in a maize plantation in Nigeria. The research understands the nature of the challenges and highlights the possibility of implementing PF technology to Nigerian Agriculture. The methodology uses simple image analysis with fuzzy classification to determine the degree of spatial and temporal variability of the field to develop a treatment plan for an equally fertile and fully productive yield. The results showed that implementing precision agriculture (PA) will yield high productivity with the aid of remote sensing to obtain an aerial view of the farm. Simple PA technologies, such as using the information to determine and test soil nutrient availability to enable land preparation to obtain a uniform field, can help make the managerial decision on the farm efficiently. There is a great chance to optimize production on the field, minimise input resources, cost and maximising profit while preserving the natural environment. By using machine vision technology with fuzzy logic for decision making, not only the shape, size, colour, and texture of objects can be recognised but also numerical attributes of the objects or scene being imaged. Keywords: Precision Agriculture, classification technique, feature extraction, Image analysis, Decision making, variability. INTRODUCTION With the potential of the space agency in Nigeria, aerial surveillance for constantly monitoring an agricultural plantation using satellites and other remote sensing technologies has improved and made possible the adoption of precision agriculture for the optimized production of food (Valente et al., 2011). The National Space Research and Development Agency in Nigeria, for example, has successfully launched five (5) satellites and are planning to launch more to replace others reaching their estimated life-cycle (Nasrda, 2008). These Nigerian satellites have contributed in addressing some the nation’s challenges in areas like the recent flooding(Nema, 2014) in providing: early warning signs and provision of contingency plans; and images of the Sambisa forest, where the kidnapped Chibok girls were believed to be held (Adams, 2014). Also, Nigerian SAT 1 was part of the first satellite to return pictures of the east coast of the United States following the Hurricane Katrina and has provided some images for mapping and development of certain areas (Paul Osas, 2013). Research into the agricultural sector shows that satellite services are very important and yet to be explored in Nigeria (Unoosa, 2016) (Asian Development Bank, 2014) (Meera, Jhamtani, and Rao, 2004) (Vergragt, 2006). With these potential, the use of remote sensing can be explored to monitor agricultural plantation, detect early onset of the effect of pests and diseases, determine the harvest period, prepare soil before planting to ensure maximum production with minimal losses of products, minimize losses on the field by providing exact harvest dates, reduction in addition to input resources and also deliver the right amount of nutrient resources on the field (Mengistu and Salami, 2007). *Corresponding author: Halimatu Sadiyah Abdullahi, Faculty of Engineering & Informatics, University of Bradford, Bradford, United Kingdom. E-mail: h.s.abdullahi1@bradford.ac.uk Journal of Agricultural Economics and Rural Development Vol. 3(3), pp. 279-292, November, 2017. © www.premierpublishers.org. ISSN: XXXX-XXXX Review Article