期刊
LIVESTOCK SCIENCE
卷 113, 期 2-3, 页码 234-242出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.livsci.2007.04.004
关键词
indigenous selection criteria; phenotypic ranking; Ankole cattle; multinomial logistic regression
Ankole cattle are well known for their massive white horns and red coat colour. These characteristics are attributed to centuries of cultural breeding practices. Two experiments with traditional cattle keepers were carried out at a governmental Ankole nucleus farm in south-western Uganda to identify phenotypic characteristics as well as production and fitness traits which are important indigenous selection criteria. Forty one body measurements each were taken from 15 bulls and 35 cows and phenotypic characteristics were described in detail. In the first experiment 12 groups of 6 to 8 cattle keepers were invited to rank several groups of 4-5 animals according to their preference for a breeding bull or cow based on phenotype alone. In the second experiment the ranking was based on phenotype and a hypothetical life history that was randomly assigned to each animal on each day of experiment. The history included milk yield (on own performance for cows and that of the dam for bulls), fertility of the animal and its sire as well as events of East Coast Fever. For analysis, Generalized Multinomial Logit Models were fitted. To compare different models the likelihood-based pseudo R square measure was used. The results indicate that, in the selection of cows, performance and fitness traits are emphasized by the cattle keepers while in the selection of bulls, the phenotypic appearance of the animal plays an important role. Individual fertility followed by milk performance are the main criteria for selecting cows, resistance to East Coast Fever was of highest importance in bulls. In both sexes a dark red coat colour was highly rated. The study indicates that the methodology of preference ranking combining phenotype and a hypothetical life history may provide insight into indigenous selection criteria of stock owners elsewhere. (C) 2007 Elsevier B.V. All rights reserved.
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