MODELING LONGITUDINAL FACTORS OF WHEAT YIELD IN SOME SELECTED ZONES OF THE OROMIA REGIONAL STATE, ETHIOPIA

Abstract

Wheat is one of the most important cereal crops in Ethiopia, ranking third in total cereal production (16%) next to teff and maize. Despite its potential for wheat grain production, Ethiopia falls short of being self-sufficient in wheat, and is currently a net importer of the grain. The aim of this study was to model the yield of wheat in five selected zones of the Oromia region. Specifically, this research determined changes in wheat yields over a decade and found out the effect of temperature and rainfall on wheat yield in the study area. Data on wheat crop (2012–2021) were obtained from agriculture and natural resource offices of each zone included in the study. Whereas, metrological data (2012–2021) was obtained from the National Meteorological Agency of Ethiopia. To get insight into the data, exploratory data analysis was performed on the longitudinal change in wheat yields. Linear mixed models were employed for the study. Then a model comparison was done using the AIC and BIC to select the best model to fit the data. A linear mixed model with a random intercept was selected as the best model to fit the data based on different model selection criteria. Diagnostic plots for the fitted linear mixed model revealed a valid model for the analysis. The study revealed that temperature and rainfall significantly affect the yield of wheat in the selected zones at a 5% level of significance. Furthermore, the analysis indicated that there is an increasing trend in wheat yields across all the zones after 2018. Based on these findings, the government must take the initiative to introduce high-temperature resistant crops, as rising temperatures have a negative impact on crop productivity. We further recommend that the farmers should be aware of the situations that lead to a decrease in rainfall, especially due to man made activities.