|Título||Prediction of retail beef yield, trim fat and proportion of high-valued cuts in Nellore cattle using ultrasound live measurements
Silva, Saulo da Luz e
Tarouco, Jaime Urdapilleta
Ferraz, Jose Bento Sterman
Gomes, Rodrigo da Costa
Leme, Paulo Roberto
Navajas, Elly Ana
|Abstract||The objective of this study was to develop equations to predict retail product and fat trim (weights and percentages) for Nellore (Bos indicus) cattle. Live ultrasound measurements of the longissimus muscle area, backfat thickness at the 12th rib and rump fat depth and shrunk body weight were obtained from 218 Nellore steers to predict weights and percentages of carcass retail product, pistola retail product and fat trimmings. After slaughter, carcasses were deboned and weighed and percentages of retail cuts were obtained directly. Measurements taken directly in the carcasses explained 97% and 36% of variation in carcass retail product weight and percentage, and 94% and 36% of variation in pistola retail weight and percentage, respectively. Live measurements explained 93% of carcass retail product weight and 39% of carcass retail product percentage. Lower accuracies were observed for pistola retail product weight (R2=0.87) and percentage (R2=0.33). Accuracies for fat trimmings weight and percentage were 79% and 55%, respectively. Ultrasound rump fat thickness showed greater correlations with retail product and fat trimmings (weights and percentages) when compared with ultrasound backfat thickness. The weight and percentage of retail products and of trimmable fat can be estimated in Nellore steers from live animal measurements, with similar accuracy to equations developed based on carcass measurements obtained at slaughter.
|Contido em||Revista brasileira de zootecnia= Brazilian journal of animal science [recurso eletrônico]. Viçosa, MG. Vol. 41, n.9 (set. 2012), p.
[en] Bos indicus
[en] Retail product
|Tipo||Artigo de periódico
|000899864.pdf (272.3Kb)||Texto completo||Adobe PDF||Visualizar/abrir|
Este item está licenciado na Creative Commons License