Participatory selection of breeding bucks in community-based goat breeding programs by combining scientific evidence with farmers’ preferences and local knowledge

This study aimed to participatively select the best bucks for use as breeding animals in five community-based breeding programs (CBBPs) in Burkina Faso, in alignment with farmers’ breeding objectives. Data were collected from 372 goat farmers using questionnaires to assess trait preferences and selection criteria. In total, 5,022 goats, including 786 males, were monitored over a one-year period. Growth performance data were recorded for 156 candidate bucks through monthly live body weight (BW) measurements. A simple selection index was calculated using a linear model and quadratic regression for BW and weight gain (WG) corrected by age and type of kidding. Based on the selection index, animals were classified into three performance groups: high, average and low, and their quantitative characteristics were expressed as mean±standard deviation. The results showed that the mean age of the candidate bucks varied from 11.68 ± 4.85 to 18.83 ± 5.64 months, and average daily gain (ADG) ranged from − 9.26 ± 27.03 g to 32.09 ± 24.82 g. Approximately 61% of the bucks identified by community selection committees as the best belonged to the high performance group defined by the selection index. Conversely, nearly all bucks classified as the poorest, had low selection index values and originated from the low-performance group, with the exception of one animal excluded due to its black coat color. The main attributes considered by farmers during selection were good body conformation, height at withers, and attractive coat color, which were consistent with their stated preferences. Overall, farmers selected breeding bucks primarily based on their production performance, while also considering their specific preferences. The study highlights a strong association between farmers preferences’ and the actual performances of animal when participatory methods are applied within the framework of CBBPs.