Modeling the effects of rainfall and temperature on maize production in kisii county using regression analysis.

Abstract

Climate change is one of the biggest environmental threats to food production, water availability, forest biodiversity and livelihood for many countries in the world. Climate change affects maize production which is the staple food for most Africa countries. Little quantitative information is available on the extent and direction of variability in rainfall and temperature which are expected to create an impact on maize production in Kisii County. The study analyzed the effect of rainfall and temperature on maize production in Kisii County, as well as determining the relationship between rainfall, temperature and maize yield, it identified the trend of the explanatory variables and compared different time series models to be used in modelling maize production. Secondary data obtained from KMS was used in the analysis. The data was analyzed using Minitab and Gretl software. Regression model was used to show relationship of rainfall, temperature and maize yield while time series was used to show the trend and predict maize yield. The results of the regression model showed there was a relationship on the three variables and time series indicated a cycle of increase and decrease of the variables under study. Among the three time series models compared (AR, MA, ARIMA) the AR(1) model was found to be the best model and was used for prediction of maize yield.