Research Article Open Access
Regression Analysis and Spatial Distribution of Drought Indices on Maize Production in the Northern Part of Nigeria
Abstract
Drought is a key abiotic stress affecting maize yield and production in
Sub Saharan Africa contributing between 44% to 58% grain yield decline in
West and Central Africa. For the detection, classification, and control of
drought conditions, drought indices are used. This paper presents the
application of a multiple linear regression model and spatial distribution to
assess the performance of drought indices on maize production in the
Northern part of Nigeria. In this research, observed annual data of drought
indices, RDI and the palmer drought indices which includes SCPDSI, SCPHDI
and SCWLPM, maize yield (measured in tonnes) in Northern states of Nigeria
were obtained from 1993 to 2018. The multiple linear regression was carried
out at different training sets: 70%, 80% and 90%. Results from the multiple
linear regression showed that in the North-Central states, FCT has the lowest
MSE (0.7788234) at 90% training level. In North-Eastern states, Borno state
has the lowest MSE (0.7240276) at 80% training sets. In North-Western
states, Kebbi state has the lowest MSE (0.8029484) at 70% training set.
Results from the spatial distribution revealed that Yobe state has the lowest
maize yield in the Northern states. A Adedayo Adepoju, Grace O Adenuga, Tayo P Ogundunmade
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