| dc.description.abstract | With liberalization of coffee production, the number of private farmers in Uganda has increased
and so did the competition for coffee production among the coffee farmers (Hons, 2009). Annual
temperatures have risen across the country, potential evapotranspiration increased, and the
distribution of precipitation has become more variable.
In this study both Temperature and rainfall data was used, data analysis methods included the use
of the students t test, regression analysis which was done to reveal the general movement of the
temperature pattern, examining evidence of any changes in the trend of temperature amounts. Such
patterns were investigated by use of both graphical and statistical methods. Graphical methods
were used as a tool for visualization of temporal variation of annual temperature amounts over the
study period – 2001 to 2020. A programming language R was used for both graphical and
statistical analysis.
The results from student t test showed that data: t = 229.16, df = 19, p-value < 2.2e-16 hence the
alternative hypothesis: true mean is not equal to 0,95 percent confidence interval:79.8143 81.2857,
sample estimates: mean of x (max temp) =80.55. and regression analysis results showed, 𝑌 =
4144.2 − 162.7𝑥. for the relationship between temperature and coffee productivity and 𝑌 =
463.113 + 2.574𝑥 for relationship between rainfall and coffee productivity.
On the response of coffee yield to changes in temperature variability, the study found that changes
in temperature and temperature variability have the significant effects on coffee yield. Therefore,
this study has indicated that there was and there is no strong evidence for attributing the increase
in coffee productivity to climate change and variability meaning that the increase could be
attributed to other factors such as application of fertilizers, planting of shade trees among others. | en_US |
