Maize Yield Sensitivities for Nigeria

Published: 8 July 2019| Version 1 | DOI: 10.17632/s73x3fmbpr.1
Olanrewaju Lawal


Yield data collated from the Global Yield Gap and Water Productivity Atlas ( were used to compute this sensitivity index. In the case of Nigeria yield data were available for the period between 2002 – 2010. The index was computed using the method described by Shi and Tao (2014). This method involves detrending (multiplicative detrending method) the yield data and this led to the generation of expected yield for each year. The index was then computed as the ration of expected Maize yield divided by the actual linear yield for this period. Detrending has been reported to aid the removal of the potential impact of technology, error in reporting and captures the variations in yield attributable to climate. The computed index can be linked to a GIS file (Shapefiles) availble from the Global Yield Gap and Water Productivity Atlas to create a visual representation of the index. High index value indicate high yield sensitivity.


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University of Port Harcourt


Climate Change, Climate Change Impact, Modelling, Crop Yield, Monitoring in Agriculture, Integrated Modelling