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Multivariate approach for young bull selection from a performance test using multiple traits of economic importance |
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| Authors: | Fernando Brito Lopes Cláudio Ulhôa Magnabosco Mariana Márcia Mamede Marcelo Corrêa da Silva Eliane Sayuri Myiage Fernanda Paulini Raysildo Barbosa Lôbo |
| Institution: | 1. Embrapa Cerrados/Capes, Road GO-462, km 12, Rural Area, Santo Ant?nio de Goiás, PO Box 179, 75375-000, Goiania, Goiás, Brazil 2. Embrapa Cerrados, Planaltina, DF, Brazil 3. Postgraduate Program in Animal Science-PPGCA, Federal University of Goiás, Goiania, GO, Brazil 4. Postgraduate Program in Animal Science-PPGZ, Goiania, GO, Brazil 5. Postgraduate Program in Animal Biology, University of Brasília, Brasília, DF, Brazil 6. Brazilian Society of Breeders and Researchers, Ribeir?o Preto, S?o Paulo, Brazil |
| Abstract: | This study used multivariate statistics to identify clusters of animals with similar expected progeny difference (EPD) and also identify leading traits that discriminate between bulls. Various linear selection indices based on specific selection criteria were proposed. Records were collected from 880 young Nelore bulls submitted to performance testing in central Brazil between 2001 and 2012. Pre-weaning average daily gain and weights at 210 days with direct and maternal effects were used in the analysis, in addition to post-weaning weight, scrotal circumference at 365 and 450 days, carcass finish and rib eye area. EPDs were classified into three groups, and the EPD means of two of these groups stood out and were considered important based on principal component analysis that associated higher values of direct EPD of weights, average daily weight gain and scrotal circumference. The EPDs for weight at 210, 365 and 450 days, pre- and post-weaning daily gain and scrotal circumference at 365 and 450 days were major causes of variation. Each linear selection index proposed (SI1, SI2, SI3, SI4 and SI5) defined a specific approach meaning that a different selection index should be used depending on breeding goals and selection criteria. |
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