Application of Mixed Model in Agricultural Field Experiment on Wheat
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Date
2008-01
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Addis Abeba university
Abstract
This study was designed to explore the efficiency of mixed model over fixed effect model.
Furthermore, it was designed to determine how the REML procedure was used to find the
estimate of variance-covariance matrix of the model. The methods of restricted maximum
likelihood are applied to the data from uniformity and multi-location trials. In this study,
two data sets are used; uniformity trial which was used to determine optimum plot size
and shape, and multi-location trial which is used to identify the effect of location on
different varieties of wheat.
In uniformity trial, two sowing methods: row and broadcast sowing, are considered both
in 1996 and 1997 in which the trial were conducted. These factors are considered as fixed
effect of the model. But, plot sizes ranging between 1 and 24 m2 with different shape are
taken as random factors of the model.
Regarding Multi-location trial, it was conducted in 2001, 2002 and 2003 using 20 wheat
varieties in 14 locations that were expected to have the same agro-ecological effect for
wheat adaptations. All the three years in which the trail was conducted are taken as fixed
effect whereas varieties and locations are considered as random factors of the model.
The result of the study based on restricted maximum likelihood (REML) revealed that
small plot sizes have larger coefficient of variation in both 1996 and 1997 for both row
and broadcast sown methods. This indicates that the coefficient of variation and plot sizes
are inversely proportional. Nevertheless, the coefficients of variation for 1996 sown by
broadcast method have higher values than the other year of the same method. This shows
that the coefficient of variation was influenced not only by soil variability and plot
orientation but also by crop geometry resulting from the sowing method. The test done
for identification and adaptation of different varieties on different location shows that
there is no average effect due to variety and hence all varieties have the same effect on
the response variable. This implies that all varieties are contributing the same average
effects for the yield obtained.
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However, the test statistics for location shows that the coefficients for Bako, Bekoji,
Debre Zeit, Ginchi, Hollota, Kulumsa, and Sinana are significantly different from the
remaining locations. This significance indicates that the average productivity potential of
these locations is higher than that of the remaining locations. In general, the contribution
of each location to yield is not the same unlike that of variety. Hence, the average effect
of location on the response variable is not the same.
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Keywords
Mixed Model in Agricultural