Multi-trait selection index and cluster analyses in Angus cattle

Author:

Fernandes G. M.ORCID,Savegnago R. P.,Freitas L. A.,El Faro L.,Roso V. M.,de Paz C. C. P.

Abstract

AbstractIn breeding programmes, the genetic selection process is based on the prediction of animal breeding values, and its results may vary according to the employed selection method. The current study developed an economic selection index for animals of the Angus breed; performed cluster analyses using the breeding values in order to evaluate the genetic profile of the animals candidates to selection, and compared the obtained results between the economic selection index and the cluster analyses. The evaluated traits included weaning weight, 18-month weight, scrotal circumference, fat thickness and ribeye area. Economic values were obtained using bioeconomic modelling, simulating a complete cycle production system of beef cattle breeds in Brazil, and the selection objective were the weaning rate and slaughter weight. The chosen selection index was composed of all of the traits used as selection criteria for the simulated production system. During the cluster analyses, the population was divided into two to four groups, in which the groupings containing potential animals were assessed. The animals of the grouping which was used for comparison with the selection index were identified, and most of the bulls that were included in the index were among the best in the analysed group. These results suggest that the cluster analyses can be used as a tool for the selection of animals to be used as parents for future generations.

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

Cambridge University Press (CUP)

Subject

Genetics,Agronomy and Crop Science,Animal Science and Zoology

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Optimising desired gain indices to maximise selection response;Frontiers in Plant Science;2024-06-24

2. Bio-economic models for deriving economic values for cattle: a review;Agricultural Science and Technology;2022-06

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