Abstract
In vivo and carcass measurements were evaluated to predict carcass physical and chemical composition and to list the measurements that best fit the prediction of the composition of growing Santa Inês sheep carcasses. Thirty-three animals were used to measure the loin eye area by ultrasound in vivo (LEAu) and in the carcass. We used 39 animals for biometric measurement in vivo and 42 sheep for morphometric measurement in the carcass. For the physical and chemical compositions of carcasses, dissection of the half left carcass was carried out in 42 animals. The data were submitted to Pearson’s correlation analysis and t test. Simple and multiple linear regressions were performed using a stepwise procedure. All correlations between in vivo measurements and the physical and chemical compositions of carcasses (in kg) were significant, except for LEAu. Biometric measurements and hot (HCW) and cold (CCW) carcass weights were considered as predictors of the carcasses’ physical and chemical compositions. Slaughter body weight (SBW) was the variable that most influenced the equations in the assessment of in vivo measurements and HCW and CCW most influenced the equations for measurements on carcasses. Biometric measurements of Santa Inês sheep can be used together with the SBW to estimate the physical and chemical compositions of carcasses, with emphasis on body compactness index, breast width, wither height, and croup height. The morphometric measurements can be used together with carcass weight to estimate the physical and chemical compositions of carcasses, with emphasis on croup width, carcass compactness index, croup perimeter, external and internal carcass lengths, chest width, and leg length and perimeter. The HCW can be used to predict the physical and chemical composition of carcasses without affecting the accuracy of the prediction model.
Highlights
The management of a breeding system associated with factors inherent to the animals and the environment directly affect the production rates [1]
The development of fast and reliable methods to predict the physical and chemical composition of the carcass in ruminants can help the producer to obtain data in vivo to predict carcass composition, with view to making decisions related to animal growth to meet consumer market demands, as well as providing knowledge of the composition of the carcass without the need to dissect it
The descriptive statistics of measurements taken in live animals (Table 1) and after slaughter (Table 2) resulted in means, data amplitude, and variability represented by the mean standard error
Summary
The management of a breeding system associated with factors inherent to the animals and the environment directly affect the production rates [1]. The adoption of indirect methods to predict carcass components offers the possibility to gain a subjective knowledge of carcass composition It allows to follow the growth and development of an animal of interest to the meat industry within the scope of precision management of herds [4]. Such tools can enable the producer to gain control and interference regarding the composition of the final product, seeking to meet the demands of the consumer market [5], and to determine the real nutritional deficiency of growing animals and obtain gains in weight. The development of fast and reliable methods to predict the physical and chemical composition of the carcass in ruminants can help the producer to obtain data in vivo to predict carcass composition, with view to making decisions related to animal growth to meet consumer market demands, as well as providing knowledge of the composition of the carcass without the need to dissect it
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