title: Estimation in vivo of the body and carcass chemical composition of growing lambs by real-time ultrasonography.
abstract: The relationship between ultrasound measurements and empty body and carcass chemical composition was investigated. A 500-V real-time ultrasound with a 7.5-MHz probe combined with image analysis was used to make in vivo measurements to predict the empty body and carcass chemical composition of 31 female lambs of two genotypes, ranging in BW from 18.2 to 48.9 kg. Eleven ultrasound measurements of s.c. fat, muscle, and tissue depth were taken at four different sites (over the 13th thoracic vertebra, between the 3rd and 4th lumbar vertebrae, at the 3rd sternebra of the sternum, and over the 11th rib, 16 cm from the dorsal midline). The single best predictor of empty body fat quantity and energy value was the s.c. fat depth over the 13th thoracic vertebra (r(2) = 0.904 and 0.912; P <0.01, respectively). Body weight was used with ultrasound measurements in multiple regression equations to establish the best independent variables combination for predicting chemical composition. Results showed that BW and two of the three ultrasound measurements (s.c. fat depth over the 13th thoracic vertebra, between the 3rd and 4th lumbar vertebrae, and tissue depth over the 11th rib, 16 cm from the dorsal midline), explained 94.7 to 98.7% (P < 0.01) of the quantity of water and fat and the energy value variation in the empty body and carcass. Body weight per se was the best predictor of the quantity of protein, accounting for 97.5 and 96.8% (P < 0.01) of the variation observed in the empty body and carcass, respectively. The results of this study suggest that BW and some ultrasound measurements combined with image analysis, particularly subcutaneous fat depth over the 13th thoracic vertebra, allow accurate prediction of empty body and carcass chemical composition in lambs.
authors.affiliation: CECAV-Universidade de Trás-os-Montes e Alto Douro, Department of Animal Science, 5000-911 Vila Real, Portugal. ssilva@utad.pt <ssilva@utad.pt>
authors.forename: S R
authors.initials: SR
authors.lastname: Silva
authors.forename: M J
authors.initials: MJ
authors.lastname: Gomes
authors.forename: A
authors.initials: A
authors.lastname: Dias-da-Silva
authors.forename: L F
authors.initials: LF
authors.lastname: Gil
authors.forename: J M T
authors.initials: JM
authors.lastname: Azevedo
mesh_terms: D000273:Adipose Tissue / Q000000981:diagnostic imaging* / Q000502:physiology; D000821:Animal Feed / Q000032:analysis; D000822:Animal Husbandry / Q000379:methods*; D000818:Animals; D001823:Body Composition / Q000502:physiology*; D004032:Diet / Q000662:veterinary*; D004044:Dietary Proteins / Q000032:analysis; D005260:Female; D007091:Image Processing, Computer-Assisted; D011506:Proteins / Q000032:analysis / Q000502:physiology; D012044:Regression Analysis; D012756:Sheep / Q000254:growth & development / Q000502:physiology*; D014463:Ultrasonography; D014867:Water / Q000032:analysis / Q000502:physiology
chemical_list: D004044:Dietary Proteins; D011506:Proteins; D014867:Water