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Halimatu Sadiyah Abdullahi
Ray E. Sheriff
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Halimatu Sadiyah Abdullahi
Ray E. Sheriff
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Journal of Agricultural Economics and Rural Development

Case Study to Investigate the Adoption of Precision Agriculture in Nigeria Using Simple Analysis to Determine Variability on a Maize Plantation

Halimatu Sadiyah Abdullahi, Ray E. Sheriff

Faculty of Engineering & Informatics, University of Bradford, Bradford, United Kingdom

Accepted 25 October 2017

Citation: Abdullahi HS, Sheriff RE (2017). Case Study to Investigate the Adoption of Precision Agriculture in Nigeria Using Simple Analysis to Determine Variability on a Maize Plantation. Journal of Agricultural Economics and Rural Development, 3(3): 279-292.

Copyright: © 2017 Abdullahi and Sheriff. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Abstract

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.