ArticleVeterinary medicine and science2024
Prediction of carcass weight using the morphometry of ankle bones in hair goats.
Article in Veterinary medicine and science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Smarter ways to predict rabbit body weight across multiple breeds.Journal of advanced veterinary and animal research · 2025Article
- Investigation of major genes affecting body weight in hair goats using bayesian segregation analysis.Tropical animal health and production · 2025Article
- Prediction of carcass weight using the morphometry of ankle bones in hair goats.Veterinary medicine and science · 2024Article
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2 authors.
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Abstract
bacgroundMorphologic measurements such as body lenght, wither height, heart girth, chest width, body leght, cannon-bone circumference is used to predict carcass weight. For this purpose, estimating carcass weight with measurements of key bones such as ankle bones, which play a significant role in the balance distribution of body weight, seems possible.
objectivesThe aim of this study is to create new regression models for effective carcass weight estimation by using the morphometric data of the talus and calcaneus bones of hair goats.
methodsStudy materials consisted of talus and calcaneus bones obtained from abattoir products of hair goat kids (12-18 months old, 20 female and 20 male) and adult hair goats (36-48 months old, 20 female and 20 male). Morphometric measurements of the talus and calcaneus of each animal were taken by a digital caliper. Using the morphometric measurements, an index and a factor were calculated for each bone. Regression analysis and correlations were examined in IBM SPSS 21 programme.
resultsAs a result, statistical analysis of GLc, GLt, Bd, Calfactor and Talfactor were statistically significant on predicting carcass weight.
conclusionSpecific anatomical structures, such as certain bone measurements, such as talus and calnaneus could serve as indicators of growth performance and also carcass weight performance. In addition new anatomical factors and indices may be produced and new regression methods may be applied with these new parameters to predict carcass weight.
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