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    South African Journal of Animal Science

    versão On-line ISSN 2221-4062versão impressa ISSN 0375-1589

    Resumo

    SNYMAN, M.A.  e  OLIVIER, W.J.. Body conformation and weight relationships in Dohne Merino sheep: A comparison of measured and subjective traits. S. Afr. j. anim. sci. [online]. 2025, vol.55, n.6, pp.269-290. ISSN 2221-4062.  https://doi.org/10.17159/sajas.v55i6.02.

    The morphometric and type traits of 269 Dohne Merino ram lambs were measured and/or assessed at four, eight, and 12 months of age. Body conformation scores were also awarded independently by three judges at each age. Estimated phenotypic correlations between conformation traits and body weights were significant for most of the measured morphometric traits and body conformation scores but not for the subjectively evaluated traits. Four principal components that accounted for all of the total variances were extracted for each age. Principal component one was more related to traits describing general body size, whereas principal component two was determined by traits describing the body heights of the sheep. In the stepwise regression of the effects of individual conformation traits on body weight, heart girth and body length explained the most variance in body weight at all three ages. Considerable variation between judges was found in the traits contributing most to the body conformation score. At four months of age, the only trait of importance common to all three judges was heart girth, while at eight months of age, conformation of the head, shoulder width, and body condition score were the most important traits. At 12 months of age, body length was the most important trait for all three judges, when assessing body conformation score. The three judges clearly emphasised different traits when assessing body conformation and awarding classification symbols. This would lead to different sires being eligible for selection at different studs, potentially hindering selection progress in the breed.

    Palavras-chave : correlations; multivariate regression; principal component analysis; repeatability.

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