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Research article2024Peer reviewedOpen access

Using carcass information as a predictor variable of empty body weight, empty body weight gain and retained energy of hair sheep

Brito Neto, Antonio de Sousa; Herbster, Caio Julio Lima; Marcondes, Marcos Inacio; Chagas, Juana Catarina Cariri; Oliveira, Ronaldo Lopes; Bezerra, Leilson Rocha; da Silva, Luciano Pinheiro; Pereira, Elzania Sales

Abstract

The objective was to develop equations to predict carcass weight (CW), use CW to predict empty body weight (EBW); and carcass gain (CG) to predict empty body weight gain (EBWG) and retained energy (RE) in hair sheep. To generate the prediction models, a data set was composed of individual measurements from 569 sheep encompassing intact males (n = 416), castrated males (n = 51), and females (n = 102). Validation analyses were performed by using the Model Evaluation System (MES). The prediction equations for CW, EBW, and EBWG were not influenced by sex class (P > 0.05), and the following equations were generated, respectively: CW (kg) = - 0.234 (+/- 1.1358) + 0.485 (+/- 0.0387) x FBW; EBW (kg) = 1.367 (+/- 0.5472) + 1.681 (+/- 0.0210) x CW and EBWG (kg) = 0.004 (+/- 0.0026) + 1.679 (+/- 0.0758) x CG. There was an effect of sex class on the intercept (P = 0.0013) of the relationship between RE and CG: RE (MJ/day) = 1.448 (+/- 0.0657) x EBW 0.75 x CG (0.797) ((+/- 0.0399)); RE (MJ/day) = 1.522 (+/- 0.0699) x EBW (0.75) x CG (0.797) ((+/- 0.0399)) and RE (MJ/day) = 1.827 (+/- 0.0739) x EBW (0.75 )x CG (0.797) ((+/- 0.0399)) for intact males, castrated males and females, respectively. This study highlights the importance of incorporating carcass information into EBW, EBWG, and RE predictions. Replacing empty body weight gain with carcass gain might be a suitable alternative to estimate the retained energy of hair sheep. In addition, the generated equations will provide support for meat production systems in carcass weight prediction.

Keywords

Carcass gain; energy; meta-analysis; prediction model; sheep

Published in

Journal of Agricultural Science
2024, volume: 162, number: 4

SLU Authors

UKÄ Subject classification

Animal and Dairy Science

Publication identifier

  • DOI: https://doi.org/10.1017/S0021859624000455

Permanent link to this page (URI)

https://res.slu.se/id/publ/140087