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Predicting the carcass characteristics of Morada Nova lambs using biometric measurements

Authors :
Roberto Germano Costa
Anny Graycy Vasconcelos de Oliveira Lima
Neila Lidiany Ribeiro
Ariosvaldo Nunes de Medeiros
Geovergue Rodrigues de Medeiros
Severino Gonzaga Neto
Ronaldo Lopes Oliveira
Source :
Revista Brasileira de Zootecnia, Vol 49 (2020)
Publication Year :
2020
Publisher :
Revista Brasileira de Zootecnia, 2020.

Abstract

The objective of this work was to use biometric measurements to predict carcass characteristics of lambs of the Morada Nova breed. We used 48 lambs with mean initial body weight (BW) of 15.0±0.04 kg and slaughter body weight (SBW) of 26.37±2.43 kg. The animals were weighed weekly and underwent a period of adaptation of 15 days before slaughter. The biometric measurements were obtained the day before slaughter, comprising body length, withers height, rump height, thigh length, breast width, rump width, thigh perimeter, rump perimeter, thorax perimeter, leg length, and body condition score. Additional measurements included slaughter BW and empty BW (EBW). The data recorded at slaughter comprised the weights of the viscera, carcass, and internal fat and offal. The in vivo measurements of body length were present in most of the equations for predicting the SBW, EBW, hot carcass weight (HCW), and cold carcass weight (CCW). The SBW and EBW presented a variation of approximately 9%. The variables that evaluated the carcass, HCW, and CCW demonstrated less data variation than SBW and EBW, which was probably because these measurements were obtained following evisceration and skinning, thus removing factors of more significant variation in vivo . The prediction models found in the present study varied with an R² of 0.49-0.93, indicating high levels of variation. In sum, biometric measurements can be used to predict the carcass characteristics of Morada Nova lambs with different body conditions.

Details

ISSN :
18069290 and 15163598
Volume :
49
Database :
OpenAIRE
Journal :
Revista Brasileira de Zootecnia
Accession number :
edsair.doi.dedup.....e10d083d3e08274cd9865ec2ec654579
Full Text :
https://doi.org/10.37496/rbz4920190179