Modeling the impact of longitudinal factors on wheat yield in selected zones of Oromia region, Ethiopia

Wheat is a vital cereal crop in Ethiopia, contributing 16% to the country's total cereal production, ranking third after teff and maize. Despite its production potential, Ethiopia remains a net importer of wheat. This study was motivated by the need to understand how longitudinal factors impact wheat yield in selected wheat-producing areas of Ethiopia. It specifically models wheat yields in five zones of the Oromia region, assessing changes in yield over a decade and examining the influence of temperature and rainfall. Wheat yield data (2012–2021) were sourced from local agricultural offices, while meteorological data were provided by the National Meteorological Agency of Ethiopia. The study utilized exploratory data analysis and linear mixed models, with model selection based on Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The linear mixed model with a random intercept emerged as the best fit. Diagnostic plots confirmed the model's validity. Findings revealed that temperature and rainfall significantly impacted wheat yield at a 5% significance level. Additionally, the analysis showed a positive trend in wheat yields after 2018 across all zones. These results suggest the need for agricultural agencies action to introduce heat-resistant crops to mitigate the effects of rising temperatures on productivity. Furthermore, farmers should be mindful of factors leading to reduced rainfall, particularly those linked to human activities. • Studied factors affecting wheat yield across Oromia's selected farming zones. • Analyzed the impact of climatic and soil variables on regional wheat productivity. • Found significant regional variability in wheat yield linked to environmental factors. • Developed models predicting wheat yield based on longitudinal data from selected zones. • Results suggest targeted interventions to improve yield in specific Oromia regions.