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- Title
Studies for meat amount estimation by multiple regression using ultrasound and carcass measurements on Carpatina kids.
- Authors
Lazăr, Cristina; Gras, Mihail Alexandru; Pelmuș, Rodica Ștefania; Rotar, Cătălin Mircea; Burlacu, Radu; Popa, Florin
- Abstract
Meat quality is relatively important for consumers and is accomplished by improving carcass quality in animals designated for meat production. The purpose of this study was to estimate carcass meat quantity by ultrasound and non-linear multiple regression equations. The measurements were conducted on 22 Carpatina kids aged 5.5 months, in two points (P1 - 5 cm from the spine, in line with the 12th rib; P2 - between the 3rd and 4th lumbar vertebra) of the Longisimus dorsi muscle to obtain subcutaneous fat layer thickness (2.02, 1.93 mm), muscle depth (21.05, 20.19 mm), muscle eye area (9.99, 9.71 cm²) and muscle perimeter (130.45; 130. 02 mm). Meat quantity was estimated with coefficients of determination by non-linear multiple regression equations, using four ultrasound parameters, measured in P2 for live weight, semi carcass and carcass weight (0.93), and also in commercial cuts, leg and rack (0.91; 0.90), followed by loin and shoulder (0.86, 0.85). The meat amounts obtained by ultrasound measurements were established in P2 with the best estimation for commercial cuts, loin and shoulder (0.94, 0.94), followed by leg and rack (0.92, 0.90). Very good meat estimation was obtained using four ultrasound parameters in P1 for live weight (0.93), semi carcass (0.92) and carcass weight (0.91) and in commercial cuts, leg and rack (0.91, 0.90), followed by loin and shoulder (0.86; 0.85). The non-linear multiple regression equations developed in this study by ultrasounds showed very high precision coefficients, by estimating meat production and by improving the evaluation of Carpatina goats selected for meat quality.
- Subjects
ULTRASONIC imaging; GOAT meat; ERECTOR spinae muscles; MEAT; NONLINEAR regression; LUMBAR vertebrae
- Publication
Animal Science Papers & Reports, 2021, Vol 39, Issue 2, p151
- ISSN
0860-4037
- Publication type
Article