Modelling of grain yield in maize
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Date
May 12, 2016
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Abstract
Grain yield is very important in maize production for breeders at the Crops
Research Institute (CRI) of Ghana. However the yields of most varieties that
are high yielding released by breeders does not perform so well after some of
their release.
This study was carried out to nd what causes the reduction in yield of
these maize varieties of CRI over the years.
An autoregressive moving average model (ARMA) was tted using a 20 year
data (1995-2014) from CRI Fumesua. A multiple linear regression model was also
tted to study factors a ecting grain yield in maize. Flowering data recorded on
a trial eld at Fumesua research station in 2014 was used for the regression model.
The study revealed that ARMA (2, 2) was found to be most suitable model for
the di erenced series of maize yield. The multiple regression model showed that
the factors plants height, days to owering and eld weight were statistically
signi cant at 0.05 level. These factors (plants height, the days to ower and eld
weight) are signi cant factors a ecting maize grain yield in Ghana.
Description
A thesis submitted to The Department of Mathematics, Kwame Nkrumah University of Science and Technology in partial fulfillment of the requirement for the degree of M.Phil Applied Mathematics