Identifying key drivers of coffee quality and yield in Ethiopia’s Gedeo zone through cluster analysis

Through principal component and cluster analysis, the team examined data from topography, climate, soil composition, and farming practices collected over a decade (2013-2022) from 18 rural kebeles in the region. This innovative approach enabled the team to uncover the distinct factors influencing coffee growth and quality, offering actionable insights for improving coffee farming practices tailored to specific local conditions.

Ethiopia, known as the birthplace of coffee, is the fifth-largest coffee producer globally, with the crop accounting for about 24% of the country's foreign exchange earnings. Coffee cultivation plays a crucial role in the socio-economic fabric of Ethiopia, supporting around 15 million people. However, climate change and variability in rainfall and temperature patterns are significantly impacting Arabica coffee production, which thrives in specific climatic and topographic conditions. Understanding these variables is essential to safeguarding Ethiopia's coffee industry against the challenges posed by climate change. Coffee production is not only influenced by biophysical factors such as altitude, soil composition, and climate but also by farmers' management practices. While previous studies have grouped coffee farms by altitude or farming type, this research uses advanced analytical techniques to provide more localized and actionable insights for the Gedeo Zone's coffee producers.

A study (DOI: 10.48130/bpr-0025-0015) published in Beverage Plant Research on 23 September 2025 by Tedla Getahun’s team, Dilla University, highlights the significant role of environmental factors and management practices in shaping coffee yields and quality.

The research team conducted an analysis of 57 variables across 18 kebeles in the Gedeo Zone of southern Ethiopia, using principal component analysis (PCA) and cluster analysis to identify key factors affecting coffee production. The analysis began with tests such as the Kaiser-Meyer-Olkin (KMO) and Bartlett's test to ensure the appropriateness of the data for factor analysis. The PCA identified 12 principal components (PCs) that explained 95.4% of the variation in coffee production, with key variables such as cation exchange capacity (CEC), evapotranspiration, shade trees, total nitrogen, altitude, and organic matter being particularly influential. The analysis revealed that these variables were critical in shaping soil fertility, microclimate conditions, and the management practices employed by farmers, all of which directly affect coffee yield and quality. Following the PCA, the team used hierarchical clustering to categorize the study area into five distinct clusters based on these factors. The clusters, including Konga, Wotiko, Hama, Dumerso, and Tumata Chiracha, exhibited unique combinations of environmental and management characteristics. For example, the Konga cluster had the highest rainfall and optimal soil conditions for producing high-quality coffee, while Tumata Chiracha faced challenges with lower rainfall and higher evapotranspiration, resulting in lower coffee bean quality. These findings underscore the importance of tailoring coffee cultivation strategies to the specific needs and conditions of each cluster, such as adjusting shade tree density, soil management practices, and irrigation techniques. This approach allows for more targeted interventions to enhance both the quality and yield of coffee in the region, helping farmers adapt to climate variability and improve productivity.

The findings of this study provide practical recommendations for farmers, agricultural planners, and policymakers in Ethiopia. By understanding the specific factors influencing coffee production in each cluster, tailored strategies can be implemented to improve yield and quality. For example, in the Konga cluster, increased use of compost and soil amendments such as liming could enhance coffee quality, while in the Wotiko cluster, introducing frost-tolerant coffee varieties and adjusting water management practices would improve productivity. This research underscores the need for cluster-specific strategies to address environmental constraints and optimize resource use.

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References

DOI

10.48130/bpr-0025-0015

Original Source URL

https://doi.org/10.48130/bpr-0025-0015

Funding information

The authors thank Dilla University for funding the study.

About Beverage Plant Research

Beverage Plant Research (e-ISSN 2769-2108) is the official journal of Tea Research Institute, Chinese Academy of Agricultural Sciences and China Tea Science Society. Beverage Plant Research is an open-access, online-only journal published by Maximum Academic Press. Beverage Plant Research publishes original research, methods, reviews, editorials, and perspectives that advance the biology, chemistry, processing, and health functions of tea and other important beverage plants.