Estimation of in vivo body composition of Iberian pigs using bioelectric impedance and ultrasonography techniques.
Meat Sci
; 213: 109484, 2024 Jul.
Article
in En
| MEDLINE
| ID: mdl-38492320
ABSTRACT
Iberian pigs are renowned for their high-quality products and distinctive characteristics, including high fat accumulation, low protein deposition rate, and a long productive cycle. The study aimed to assess in vivo body composition of purebred Iberian pigs using bioimpedance analysis (BIA) and ultrasonography. Accurate estimation of body composition in live animals is crucial for adopting decisions at the farm level. The experiment involved three groups of pure male Iberian pigs differing in body weight (BW; 60, 80 and 100 kg) with the same nutritional management. Body measurements, BIA and back fat and loin thickness (measured by ultrasonography) were obtained before slaughter. After slaughter pig carcasses were chemically analysed. A strong correlation between BIA measurements, specifically resistance (Rs) values, and body chemical parameters (total protein, lipids, ash, and water contents; p < 0.001 for all) was found. Reactance values (Xc), however, did not exhibit significant correlations. Regression analyses were conducted to predict carcass composition based on BIA measurements, BW, ultrasonography and linear corporal measurements. The prediction models achieved high R2 values for lipids, protein, total ash, water, and lean tissue (0.957, 0.968, 0.936, 0.961 and 0.976, respectively, p < 0.001 for all), indicating strong predictive power. These findings demonstrate the potential of non-invasive techniques such as BIA for estimating body chemical composition and quality of pig carcasses. However, it is important to acknowledge that the prediction models developed may not be applicable to other pig populations, as they were based on a specific sample of pigs.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Body Composition
/
Ultrasonography
/
Electric Impedance
Limits:
Animals
Language:
En
Journal:
Meat Sci
Journal subject:
CIENCIAS DA NUTRICAO
Year:
2024
Document type:
Article
Country of publication: