ArticlePloS one2026
Combining stated and revealed preferences to define smallholder cattle breeding objectives in northwest Ethiopia: Evidence for breeding program design.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Identifying high-priority traits is essential for designing effective breeding programs in smallholder systems. This study employed both stated and revealed preference methods to identify priority traits for cattle breeding objectives among smallholders in northwest Ethiopia. Stated preferences were assessed using a discrete choice experiment (DCE), while revealed preferences were examined through a hedonic pricing approach. The two datasets were analyzed separately and their results compared to provide complementary insights. Data were collected between January and April 2024: 384 farmers participated in the choice survey across three districts (Farta = 91, Simada = 133, and Lay Gayint = 160), and 200 cattle transactions were recorded in three marketplaces-Debre Tabor, Simada, and Nefas Mewucha. Choice data were analyzed with a mixed logit model, and market data with a log-linear ordinary least squares regression. Results showed both convergence and divergence in trait preferences between methods. Farmers' strong preference for large body size in the DCE (p < 0.001) aligned with the significant positive effects of body condition and live body weight on market price (p < 0.001). However, traits not visually observable at sale-such as milk yield, docility, disease tolerance, libido, calving interval, and calf vigor-were highly valued in stated preferences but not captured in market prices due to observability constraints and information asymmetry. Conversely, the hedonic model revealed market structure effects not captured by the DCE, including higher prices paid by traders and premiums for slaughter animals. These findings demonstrate that employing both methods provides a more comprehensive evidence base for defining breeding objectives-capturing both invisible livelihood-critical traits valued by farmers and market dynamics that shape real-world prices. The identified priority traits provide a foundation for subsequent research to estimate genetic parameters and economic weights to design a breeding program.
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