| dc.description.abstract | This study is about the impact of rainfall and temperature variability on coffee production in Uganda. The general objective of this study is to evaluate the impact of rainfall and temperature variability on coffee production in Uganda. The study sought to describe the trends of rainfall and temperature variability, to evaluate the impact of rainfall variability on coffee production and to evaluate the impact of temperature variability on coffee production in Uganda. The study area was all Uganda, and the data was obtained online from www.worldclim.com while observed variables such as rainfall, maximum and minimum temperature, relative humidity and evapotranspiration data for the period between 2008 and 2017 for Uganda was obtained from Uganda National Meteorological Authority. The study adopted an AquaCrop agroclimatic risk model to simulate the performance of the coffee crop under varying conditions of rainfall and temperature. The data was analysed using Excel and presented in form of graphs, trends and models. The model was developed from multiple linear regression analysis. A regression analysis was run using SPSS (Statistical Software for Social Scientists version 16.0) along with the help of Microsoft Excel to find out the coefficients of the model. From the data analysed, it was revealed on average that coffee production depends on the amount of rainfall received for a period. More so, it was observed that more out was collected in periods where rainfall was at maximum. Dry weather is needed during the harvest of the final coffee products. More still, the results of the regression, revealed that rainfall and average temperature were found to be significant factors affecting coffee production with p-values of 0.009 and 0.0072 respectively. Therefore, we conclude that rainfall and average temperature have a significant impact on coffee production in Uganda. Basing on the results obtained from the regression analysis, the researcher concluded that there are only two variables that directly influences coffee production, and these are rainfall and average temperature of the productive unit. The researcher recommended that, for future researchers carrying out the same or related study associated with the calibration of the Aqua Crop model in coffee production should perform the regression with all the variables of the model. More so recommended that, they should also perform the field measurement of each of the variables to analyze the behavior of the adjustment coefficient of goodness of fit for the model. | en_US |
