A Sustainable Breeding and Genetic Optimization Framework for Sheep Adaptation in Dryland Farming Systems of Tharaka Nithi County, Kenya
Keywords:
Sheep breeding, genetic optimization, dryland farmingAbstract
Dryland and semi-arid production systems present persistent constraints to small ruminant productivity due to limited feed resources, climatic variability, disease pressures, and weak genetic improvement infrastructure. In Tharaka Nithi County, Kenya, livestock production remains a critical livelihood strategy; however, performance levels of small ruminants, particularly sheep, are constrained by the absence of structured breeding programs and low adoption of modern genetic improvement tools. This study develops a sustainable breeding and genetic optimization framework aimed at enhancing sheep adaptation, productivity, and resilience in dryland farming systems.
The framework integrates community-based breeding strategies, genomic-informed selection principles, and nucleus breeding structures to optimize genetic gain under low-input conditions. Drawing on established small ruminant genetic improvement models (Kosgey et al., 2006; Rewe et al., 2004; Wurzinger et al., 2011), and comparative evidence from East African livestock systems (Ojango et al., 2004), the study synthesizes adaptive breeding mechanisms suitable for marginal environments. The approach further incorporates participatory livestock management systems that align farmer objectives with genetic selection criteria.
Findings from literature synthesis indicate that structured breeding programs significantly improve productivity, adaptation traits, and long-term sustainability in small ruminants. However, gaps persist in integrating genomic selection tools with community-based systems in arid and semi-arid regions. The proposed framework addresses these gaps by aligning phenotypic selection with environmental adaptability and farmer-driven breeding objectives.
The study concludes that sustainable genetic optimization in sheep requires a hybridized system combining traditional knowledge, structured breeding schemes, and emerging genomic technologies tailored to dryland constraints.
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Copyright (c) 2026 Dr. Ananya Bhattacharya
This work is licensed under a Creative Commons Attribution 4.0 International License.
